Ask the Scholar
Document scope · 1 page
Scholar
Ask about this object, its catalog metadata, its source description, or the page inventory.
For page-specific OCR and visual context, open one of the page chats.
Scholar Source Context
Document identity
localId
225358557
label
5 Labs Study: Scenarios of U.S. Carbon Reductions, Department of Energy June 10, 1997 Draft [Global Climate Change] [Binder] [2]
core
doc
dtoType
document
citationUrl
pageCount
1
Source metadata
id
225358557
contentType
document
title
5 Labs Study: Scenarios of U.S. Carbon Reductions, Department of Energy June 10, 1997 Draft [Global Climate Change] [Binder] [2]
citationUrl
collections
Records of the Council of Economic Advisers (Clinton Administration)
Vivian Wu's Files
imageCount
1
hasImages
yes
source
import
hasTranscription
no
Source extras
naId
225358557
levelOfDescription
fileUnit
otherTitles
42-t-7422601-20171095F-027-004-2019
recordType
description
ocrSource
nara-archive
Single page context
seq
1
pageIndex
0
type
document
mediaId
be24286f2c8108cd
ocrText
FOIA Number: 2017-1095-F
FOIA
MARKER
This is not a textual record. This is used as an
administrative marker by the William J. Clinton
Presidential Library Staff.
Collection/Record Group:
Clinton Presidential Records
Subgroup/Office of Origin:
Council of Economic Advisers
Series/Staff Member:
Subject Files
Subseries:
OA/ID Number:
21605
FolderID:
Folder Title:
5 Labs Study: Scenarios of U.S. Carbon Reductions, Department of Energy June 10, 1997 Draft
[Global Climate Change] [Binder] [2]
Stack:
Row:
Section:
Shelf:
Position:
S
21
5
1
2
DRAFT
6/11/97
CHAPTER 7
IMPROVED ELECTRICITY SUPPLY TECHNOLOGIES
7.1 INTRODUCTION
The electricity industry has many supply-side options at its disposal to reduce or offset
its CO2 emissions by the year 2010. One of these options was discussed in Chapter 6 -
reconfiguring the generation mix to reflect a $50/ton charge for carbon. We labelled this
option "carbon-ordered dispatching" because it involves the same technologies that
were considered in the EIA reference ("business-as-usual") scenario and the two
efficiency cases. Electricity was redispatched from the existing generation mix, and the
construction and retirement of power plants also changed - but no new technologies
were introduced.
Chapter 7 considers other electricity supply technology options, including:
converting coal-based power plants to natural gas;
cofiring coal with biomass;
efficiency improvements in generation and transmission and distribution (T&D) systems;
extending the life of existing nuclear plants;
increasing generation and capacity at existing hydropower plants; and
constructing new powerplants using advanced coal technologies.
Each of these options is assessed independently. Thus, interactions between the options
are not taken into account, and the possibility of double counting is therefore likely.
]A
Their viability and costs of these supply options in 2010 are based on the assumption
that the electricity grid is transformed by the high efficiency/low carbon scenario, as
described in Chapter 6. Thus, considerable decarbonization has already occurred. The
question addressed is: What additional supply technology options now make sense in a
scenario in which carbon has acquired a value of $50 per metric ton?
We conclude this chapter by discussing the significant contribution that renewable
energy technologies can make by the year 2020.
7.2 CONVERTING COAL-BASED POWERPLANTS TO NATURAL GAS
7.2.1 Objective
The objective of this study was to explore the technical and economic feasibility of
converting (via repowering) coal-fired power plants (>50 MWe) to natural gas
combined cycle (NGCC), as one option to reduce carbon emissions from the U.S. electric
power sector. The effects of gas/coal price differential, SO₂/NOₓ emission credits
(market value), and technical/economic efficiency credits arising from NGCC
repowering were incorporated into the analysis.
7.2.2 Approach
Repowering of existing coal-fired powerplants to NGCC offers an opportunity to
significantly increase the efficiency of power generation and reduce the emissions of both
7.1
DRAFT
6/11/97
criteria air pollutants ( Sulfur Dioxide (SO₂), Nitrogen Oxide (NOx), Total Suspended
Particulates (TSP), and Hazardous Air Pollutants (HAPs) and Carbon (C).¹
The simplest approach to repowering is site repowering, where the existing power plant
site is reused with an entirely new NGCC system. Only the switchyard and cooling
tower are reused. While this approach provides the highest cycle efficiency, it also
requires a greater capital investment.
The more conventional approach is referred to as steam turbine repowering. In this case, a
new gas turbine and heat recovery steam generator (HRSG) are integrated with the
existing steam turbine and auxiliary equipment. Due to age of equipment and the fact
that the steam turbine was designed for linkage with a coal-fired boiler, the efficiency of
a repowered steam turbine plant would be lower than at a site repowered plant. The
steam turbine repowering option has a higher operating cost (due to the lower efficiency)
but a lower capital cost.
The cost-effectiveness ($/tC) of both repowering options was examined in this study.²
In addition, a sensitivity analysis was performed to examine the impact on cost-
effectiveness if additional natural gas pipeline infrastructure (hook-up and
transmission) were not needed to ensure gas deliverability. This sensitivity analysis
(labeled: no transmission cost case) was only conducted on those plants that are
currently connected to the pipeline network (i.e., dual-fuel).
A "static" analysis was performed ( i.e., the cost of repowering was computed for each
candidate power plant but the analysis did not optimize unit/plant production cost,
dispatch, or system load. Moreover, for the steam repowering case, the largest steam
turbine (not each individual steam turbine) at the plant was repowered to generate the
equivalent of 1995 plant output (kilowatt-hours, kWh), since this is both more economic
and consistent with industry practice than repowering each turbine. Lastly, the gas
delivery infrastructure costs (hook-up and transmission) were derived assuming 1) no
excess capacity in the current delivery system, and 2) that if such a fuel switching
strategy were implemented, the natural gas pipeline industry would build capacity (even
if done incrementally) to meet the total estimated gas requirements of repowering all
candidate plants and allocate appropriate delivery costs to each repowered plant.
Appendix G-1 discusses the methodological steps in more detail.
Results
Repowering of coal-fired power plants could reduce between 5 MtC and 269 MtC
depending on the gas/coal price, carbon cost and environmental externality value.
JA
Figure 7.1 portrays the cost-effectiveness of site repowering with NGCC, and the
corresponding cumulative carbon removed, for two alternative gas/coal price
1 Another approach would be to improve the performance of the existing coal-fired power plant
through various management and technical improvements. While less costly than NGCC
repowering, the emissions reduction potential is not as great due to the carbon (together with
sulfur and nitrogen) content of coal versus natural gas.
²The cost-effectiveness calculation included the cost of repowering, hook-up and transmission, a
coal/gas price differential, and a credit for SO2/NOx emission reduction and technical/fuel
efficiency improvement (O&M credit).
7.2
BLANK
DRAFT
6/11/97
differentials ($0.72/MCF and $1.18/MCF).³ When no environmental externalities are
considered, approximately 50 MtC can be removed for $50/tC, 191 MtC for $100/tC,
and 262 MtC for $150/tC with a gas/coal price differential of $0.72/MCF. Table 7.1
summarizes the affected gigawatts (GW), SO₂ and NOx removed, and increase in utility
gas consumption (trillion cubic feet, TCF) for each case examined.
Figures 7.2 and 7.3 depict the effect of environmental externality credits (for SO₂/NOₓ)
on carbon cost-effectiveness. Two alternative market values for used for both SO2 and
NOx:
High ($/ton)
Low ($/ton)
SO₂
100
0
NO,
1400
700
The rationale for these values is explained in Appendix G-1. Both Figures 7.2 and 7.3
(together with Table 7.1) illustrate that the effect of the environmental externality credit
disipates at $100/tC and is almost nonexistent at $150/tC. The reason is twofold: the
number of candidate plants available for repowering is declining, but more importantly
the offsetting effect of the externality credit is substantially reduced at the higher carbon
cost levels (since the investment cost of conversion is greater). In many of the low-cost
repowering cases, the externality credit is approximately equal to the amortized
investment cost of repowering, causing the $/tC to approach zero.
3 The gas/coal price differential of $.72/MCF represents the 1995 value as reported by the
Energy Information Administration (ELA) in its Annual Energy Outlook (AEO96). It represents
a lower bound value, since the differential remains constant over time (and demand), reflecting
no price response by the natural gas industry with increasing utility fuel demand. The
$1.18/MCF reflects the 2010 gas/coal price differential within AEO96. This differential
reflects a real natural gas price increase of $0.40/MCF ($2.04/MCF in 1995 to $2.44/MCF in
2010) and a 1.9 TCF increase in utility gas demand.
7.3
DRAFT
6/11/97
Table 7.1
Summary Statistics: Coal/Gas Repowering Study
Constant 1995 Coal/Gas Price Differential ($0.72/MCF)
NOX
(MMhoones)
(MMitones
(105)
MM/Grines
(Ten)
Externalities
49.6
49
1.1
1
1.7
190.7
207
6.2
3.9
6.9
262.3
311
10.2
5.2
9.7
Externalities
90.2
92.6
2.1
1.9
3.2
233.6
266
8.7
4.8
8.5
266
317
10.4
5.3
9.8
Externalities
143.8
155.4
4.9
3.3
5.1
252.6
293
9.8
5.1
9.3
269
323
10.5
5.4
9.9
Coal/Gas Price Differential in 2010 ($1.18/MCF)
Signature
Subtitume
1545
Chicon
Aferied
Stor
Rentered
Removed
MMRITAS
(MM/DD/YY)
xternalities
4.9
4.8
0.06
0.08
0.2
134.5
140
3.3
2.7
4.7
252.8
294.6
9.8
5.1
9.3
Externalities
36.4
34
0.7
0.9
1.3
185.4
202
6.4
3.9
6.7
259.3
305.5
10.1
5.2
9.6
Externalities
105.4
111
3.3
2.4
3.7
235.8
270
8.8
4.8
8.6
265.7
317
10.4
5.3
9.8
DRAFT
6/11/97
Figure 7.1
Carbon Curve for Coal/Gas Site Repowering
No Environmental Credits
250
200
150
Incremental Cost ($/tC)
100
50
0
50
100
150
200
250
300
0
Cumulative Carbon Removed (MtC)
$1.18 per MMBtu
-
-
$0.72 per MMBtu
Figure 7.2
Carbon Curve for Coal/Gas Site Repowering
Effect of Environmental Credits on Cost of Carbon Removal
Constant 1995 Coal/Gas Price Differential ($0.72/MCF)
250
200
150
Incremental Cost ($/tC)
100
50
0
o
so
100
150
200
250
300
Curnulative Carbon Removed (MtC)
High Externalities
-
Low Externalities
7.5
DRAFT
6/11/97
Figure 7.3
Carbon Curve for Coal/Gas Site Repowering
Effect of Environmental Credits on Cost of Carbon Removal
Coal/Gas Price Differential in 2010 ($1.18/MCF)
250
200
150
Incremental Cost ($/IC)
100
50
0
0
50
100
150
200
250
300
350
Cumulative Carbon Removed (MtC)
High Externality
Low Externality
Since dual-fuel plants are already receiving natural gas (although a lower volumetric
levels than a repowered plant), a sensitivity analysis was conducted wherein no hook-
up or transmission costs were incurred to deliver an increased quantity of gas to these
repowered plant sites. This "no additional transportation cost case" is depicted in
Figures 7.4 and 7.5, which depict alternative gas/coal price differentials and externality
credits for site and steam turbine repowering. Since transportation costs comprise
approximately 30 percent of the total investment cost, the carbon cost curves shift
downward considerably when these costs are removed. In Figure 7.4, approximately 55
GW of coal-fired capacity can be repowered at $50/tC, removing 49 MtC of carbon, 1.4
Mt of SO₂ and 1.0 Mt of NOₓ. The amount of natural gas required by these repowered
plants is 1.7 MCF; 50 percent of 1995 utility consumption.
The cost-effectiveness numbers derived in this study are optimistic and should be used
with caution because they do not (or do not adequately) consider the following factors
that will determine the ultimate cost-effectiveness of the coal-to-gas repowering:
the effect that the potential increase in gas demand from repowering will have on
gas prices
the actual cost of repowering the candidate coal-fired power plants
the capacity utilization of the converted plants
the costs associated with breaking long-term coal contracts
other economic factors (e.g., differential state/federal tax effects)
The analysis and issues that result are discussed below.
7.2.4 DISCUSSION OF THE MAJOR ELEMENTS AND ISSUES
7.6
DRAFT
6/11/97
7.2.4.1 Affected Power Plants
In 1995, there was 335 GW of coal-fired capacity at 408 power plants in the United
States. Figure 7.6 indicates that this capacity was comprised of:
319 dual fuel units (units that can burn both coal and natural gas),
122 multi-fuel units (coal-fired units at sites with natural gas or petroleum units), and
711 coal-fired units (units at coal only plant sites).
These categories were used due to an initial presumption regarding the investment cost
of conversion and deliverability of natural gas ( i.e., those plant sites consuming gas in
1995 would have a natural gas pipeline connection, thereby resulting in a lower hookup
cost.
7.7
DRAFT
6/11/97
Figure 7.4
Carbon Curve for Coal/Gas Site Repowering
Constant 1995 Coal/Gas Price Differential ($0.72/MCF)
Low Environmental Credits
150
140
130
Gas Differentiat: $0.72/MCF
120
SO2 Credit: $0/ton-SO2
NOx Credit $700/ton NOx
110
100
90
Incremental Cost ($/tC)
80
70
60
50
Site Repowering
40
30
20
Steam Turbine
10
0
0
10
20
30
40
50
60
70
Cumulative Carbon Removed (MtC)
Figure 7.5
Carbon Curve for Partial Repowering
Constant 2010 Coal/Gas Price Differential ($1.18/MCF)
High Environmental Credits
150
140
Gas Differential: $1.18/MCF
130
SO2 Credit $100/ton-SO2
Nox Credit: $1,400/ton NOx
120
110
100
90
Incremental Cost ($/tC)
80
70
60
50
Site Repowering
40
30
20
10
Steam Turbine
0
0
10
20
30
40
50
60
70
Cumulative Carbon Removed (MtC)
DRAFT
6/11/97
Figure 7.6 Candidate Coal-Fired Power Plants for NGCC Repowering
Based on unit number
Based on capacity
Dual-Fuel
75,593 MW
Dual-Fuel
23%
319 Units
28%
Multi-Fuel
25,326 MW
Coal Only
8%
711 Units
Coal Only
62%
Multi-Fuel
122 Units
229,777 MW
10%
69%
7.2.4.2 Increase in Natural Gas Demand
Utility gas consumption in 1995 was 3.5 trillion cubic feet (TCF). Figure 7.7 shows the
increases in natural gas demand from this base that would result from either site or
steam turbine repowering for each of three cost effectiveness values ( $50/tC, $100/tC
and $150/tC. The increase in gas demand ranges from 1.7 MCF to 9.7 MCF MCF in the
low gas/coal price differential case without externalities between the $50/tC and
$100/tC cases. This quantity of gas for repowered plants represents a 50 percent and
275 percent increase in 1995 utility gas consumption, respectively.
If all the candidate coal-fired power plants were repowered with NGCC, natural gas
demand in the utility sector would increase by 11.1 TCF/yr (site repowering) or 11.5
TCF/yr (steam turbine repowering) to either 14.52 TCF/yr or 14.95 TCF/yr,
respectively. An increase of over 300 percent from current consumption levels. The
greatest increase would be for repowered coal-only units ( 7.8-8.1 TCF/yr over 1995
levels.
The potential gas price increase resulting from NGCC repowered plants was not
analyzed in this study. Rather, only the current and projected gas/coal price
differentials expected under AEO96 were included in the cost analysis. However, the
EIA has prepared a preliminary estimate; they found that an 11 TCF increase in demand
70
would increase natural gas prices by $3.09/MCF over 20 years (1995-2015), if coal-fired
power plants were converted to natural gas when scheduled for life
extension/refurbishment and there was considerable demand-side energy efficiency
investment.
7.9
DRAFT
6/11/97
Figure 7.7
Increase in Gas Consumption Resulting from Coal to Gas Conversion
30
1- No Environmental Credits
2- Low Environmental Credits
25
3- High Environmental Credits
20
3
1
2
Increase in Gas Consumption, TCF
9.8
3
9.9
9.7
9.3
2
1995 Coal/Gas Price Differential
15
2010 Coal/Gas Price Differential
8.5
1
6.9
10
3
9.6
9.8
9.3
5.1
8.6
6.7
2
5
4.7
3.2
3.7
1
1.7
1.3
0.2
0
50
100
150
Incremental Cost, $/tC
DRAFT
6/11/97
7.2.4.3 Gas Deliverability
The spatial distribution of the 404 candidate plants are depicted in Figure 7.8. Most of
the plants are located in the Mid-Atlantic, South Atlantic, Midwest and Plains regions.
While these are also primary gas consuming regions served by major trunklines, many
industry experts believe there is limited unused/underutilized capacity in the current 1.2
million mile pipeline system (transmission, 264,900 miles; distribution, 935,000 miles;
field, 62,200 miles). Since this capacity is necessary to accommodate peak winter
demand and non-utility growth, it is of little value to powerplants considering
conversion, since these powerplants require firm pipeline commitments.
Due to the potentially significant increase in utility gas demand that would result from
repowering (either site or steam turbine) coal-fired power plants, this study assumed
that new pipeline capacity would be required to ensure deliverability. A detailed
assessment was performed (using a geographical information system, GIS) to compute
the distance of each candidate powerplant to its nearest trunk line. Cost estimates were
derived for the costs of upgrading the lines to meet the increased gas demands. Table 7.2
summarizes the distance of the candidate plants to their closest production zone.
The requirement to add new pipeline capacity could effect the attractiveness of
repowering as a carbon mitigation strategy. Although not likely to occur, if all of the
candidate plants were converted, 52,323 miles of new pipeline (30-inch average) would
be required. For perspective, during 1994 and 1995, between 1,200-1,500 miles of new
pipeline were added to the system.. According to Federal Energy Regulatory
Commission (FERC) filings of pipeline projects, there are a considerable number of new
pipelines and pipeline expansions that have been proposed, some of which are still
pending approval. While mileage is not included with each filing, in the regions of
concern (Central, Midwest, Northeast, and Southeast), more than 8,200 miles of pipe is
projected to be added; this level of expansion is greater than the 1994-95 rate of
addition. However, it is not known how long it will take to complete these proposed
pipelines. So, an accurate assessment of the ability to increase the rate of pipeline
expansion/construction could not be estimated as a part of this study.
Table 7.2 Plant Distance from Production Zone
Dual-Fuel
Multi-Fuel
Coal Only
Total
(Miles
# Units
Percent
#
Units
Percent
# Units
Percent
# Units
Percent
60-440
48
37
5
12
55
22
103
26
440-620
33
25
8
19
64
26
105
25
620-890
30
23
15
35
59
24
104
25
890-
19
15
15
35
67
27
101
24
1480
Total
130
100
43
100
245
100
418
100
7.11
DRAFT
6/11/97
Figure 7.8 Location of Candidate Plants
1
1
7.2.4.4 Emissions Reduction
Due to the difference in the carbon content of natural gas and coal, and the higher
efficiency of NGCC generation, repowering would carbon emissions significantly. If all of
the candidate plants were converted, carbon emissions would be reduced by 50/MtC to
269 MtC at cost effectiveness values of between $50 and $150/tC in the low price
differential ($0.72/MCF), no externality case.
Because of the differences in the sulfur and nitrogen content of coal and gas and the
higher efficiency of the repowered coal units, SO₂ and NOx would be removed as a result
of conversion. Table 7.1 (earlier) summarizes the reduction in SO₂ and NOₓ emissions
for each case and carbon cost. At the $50/tC level, approximately 50 percent of the
SO₂ and NOₓ would be removed; at $100/tC and higher almost all coal-fired SO₂ and
NOₓ emissions would be eliminated. If all of the plants were converted, up to 10.5
million tons of SO₂ and 5.7 million tons of NOx would be removed.
The economic value of the SO₂ and NOₓ emissions reductions that would result from
conversion of the plants also were assessed in this study. Using the methodology
described in the Appendix, SO₂ was valued at between $0 and $100/ton; NOₓ was
valued at between $700 and $1400/ton. These values were used as the basis for the
environmental externality credits used in this report.
7.2.4.5 Cost-Effectiveness
The cost-effectiveness of the repowering options analyzed range from $0/tC to
$500/tC, with the majority of the plants located between $0/tC and $150/tC. As
noted in this report, the cost-effectiveness curves should be used with caution. Gas
7.12
DRAFT
6/11/97
deliverability, gas price increases and proper valuation of SO₂ and NOx credits could
significantly affect the results of the study.
In addition, the effectiveness of repowering as a carbon control strategy will depend
upon whether and to what extent the converted plants are dispatched. If, because
of the costs associated with conversion, the repowered plants are not dispatched or
their utilization minimized, the associated carbon reductions will depend on the fuels
and technologies used at the plants dispatched ahead of the repowered plants.
7.3 CO-FIRING COAL WITH BIOMASS
Summary: Co-firing biomass with coal has the potential to produce 7.5 GW by 2010 and 26
GW by 2020. Though the current substitution rate is negligible, a rapid expansion is possible
based on wood residues (urban wood, pallets, secondary manufacturing products) and
dedicated feedstock supply systems (DFSS) such as willow, poplar and switchgrass. A set of
three cases were analyzed with differing assumptions on the availability and costs of
feedstocks as set out below:
Table 7.3 Summary Table of Parameters and the 2010 Results
Case
Low Biomass
High Biomass
Carbon 50 $/t, with
Costs
Costs
high Biomass Cost
Residue cost Beginning
6 $/ton
15 $/ton
15 $/ton
Residue Cost at End
18 $/ton
25.6 $/ton
41.56 $/ton
DFSS Cost at Beginning
44.7 $/ton
49.8 $/ton
49.8 $/ton
DFSS Cost at End of period
18.2 $/ton
25.2 $/ton
25.2 $/ton
Average Cost in 2010 $/t
18.26 $/ton
25.8 $/t
40.96 $/ton
Average Cost of Energy
0.96 $/10⁶ Btu
1.36 $/10⁶ Btu
1.69 $/10⁶ Btu
Carbon compensation
17.6 $/ton
33.9 $/ton
47.7 $/ton
Carbon replacement in 2010
14.6 Mtonne
14.6 Mtonne
20.1 Mtonne
Fraction of Coal Capacity
2.5%
2.5%
3.5%
The Technology: The current coal fired power generating system represents a direct system for
carbon mitigation by substituting biomass-based renewable carbon for fossil carbon. Extensive
demonstrations and trials have shown that effective substitutions of biomass energy can be
made up to about 15% of the total energy input with little more than burner and feed intake
system modifications to existing stations'. Since large scale power boilers in the current 310 GW
capacity fleet range from 100 MW to 1.3 GW the biomass potential in a single boiler ranges from
15 MW to 150 MW. Preparation of biomass to an appropriate size of minus 1/4 inch and a
moisture content of < 25% involves well known and commercial technologies. After "tuning" the
boilers combustion output- there is little or no loss in total efficiency, implying that the biomass
combustion efficiency to electricity is close to the 33-37% range of the unmodified coal plant, an
efficiency that stand-alone biomass generating capacity has yet to demonstrate. Since biomass
in general has significantly less sulfur than coal, there is a SOx benefit, and early results suggest
that there is also a NOX reduction potential with woody biomass.
4 CONEG 1996. Utility Coal-Biomass Co-fring Plant Opportunities and Conceptual
Assessments. Report available from the Northeast Regional Biomass Program, CONEG Policy
Research Center, Inc. Washington, DC. (Work performed by ANTARES Group, Inc. and Parsons
Power)
7.13
DRAFT
6/11/97
Economics: Investment levels are site-specific and are affected by the available space for
yarding and storing the biomass, installation of size reduction and drying facilities, and the
nature of the boiler burner modifications. Investments are expected to be in the range of 100 -
700 $/kW of biomass capacity. A median value of about 180 $/kW is expected from the early
trials. There is an O&M cost increase of 70 k$/y over coal, as a result of the need for an
additional yard worker to handle the biomass. A 100 MW coal plant at 10% biomass
substitution would then have an investment of 1.8 million dollars. Assuming the GENCO
recovers its investment cost in 3 years, then the annual fuel offset then has to be 670 k$ to cover
capital recovery and the increased O&M. With the average price of coal being about 1.40 $/10⁶
Btu the annual fuel cost of coal is 1081 k$ (10 MW at 85% capacity factor and 32.9% thermal
efficiency 10,337 Btu/kWh). The allowable cost of biomass then is 411 k$ or about 9 $/ton.
Figure 7.9 30 GW Strategic Plan Scenario
Biopower Residue, DFSS
Biomass Consumption, and
Land Impact
Note: Biomess communition estimates by NREL
160
M B
120
80
40
0
0
M
A
4
8
12
1991 1993 1996 1007 1000 2001 2003 2005 2007 2009 2011 20 2018 2017
1990 1998 1998 2000 2002 2008 2008 2010 20 2018 2016 2020
Year
Residue
DFSS
&
MAcres
Mitons
Fuel Costs: The near term potential biomass feedstocks are residues in a radius of about 50
miles around the plant. Based on data from existing biomass power plants in the NE and in
California - there are extensive sources of biomass residues available for about 0.5 $/10⁶ Btu
(<9$/tonne). Transportation costs limit the range over which such biomass feedstocks can be,
acquired, and for the longer term, a dedicated feedstock system much closer to the power plant
is envisaged. By definition, the availability of residues (e.g. urban wood residues, rights of way
clearance, construction and demolition wood, pallets, and sawdust-shavings from secondary
wood processing) is finite and will respond to the prices offered for the residues. In the
sensitivity cases tested - it was presumed that a 50 $/t carbon payment would effectively
increase the available residues by 50% over the base case.
Dedicated feedstocks would escape this constraint. However, such resources are much more
expensive than residues, and though the current development goal is in the range of 1 - 1.5
$/10⁶ Btu, with current technology it is in the 2 $/10⁶ Btu region. It is assumed that with an
7.14
DRAFT
6/11/97
estimated 10.4 million acres will be needed to reach a nominal production of 86 Mtonnes by
2020. Since DFSS is in an early stage of development the model assumes that the initial
planting will only yield about 6 tonnes/acre by 2002 [Which is today's state of the art], and
that by 2010 the yield will be closer to 8 tonnes/acre. Equally today's costs are high with 45
$/tonne being feasible, however, a combination of learning curve improvements along with scale
are presumed to bring the cost down to 18$/tonne by 2020. The sensitivity case also examined
a cost of 25 $/t by 2020 (approximately $1.3 $/GJ). The competing coal prices are assumed to
be 1.40 $/10⁶ Btu (1.33 $/GJ) throughout.
Carbon Substitution Potential: NREL developed a notional 30 GW scenario for biomass
supplies for the current Biomass Power Strategic Plan - this scenario was developed for a mix
of steam, co-firing and IGCC biomass generation. However, the resource plan that was
developed that included residues and DFSS is independent of the end use and involves the
development of almost 12 million acres of land for DFSS by 2020. The resource development is
shown in Figure 7.9, above, and is used as the basis for this carbon assessment. This indicates
that DFSS would come on rapidly after the year 2001 and that residues are assumed to be
capable of only a small increase in quantity - as much is already utilized.
The average cost of residues is expected to increase gradually, while those of DFSS crops are
expected to demonstrate a strong learning curve and large economies of scale as shown in Figure
7.10, below. The data on the quantities and the costs from the previous two figures can be
combined into Figure 7.11, which is the supply curve for biomass for cofiring in the low cost
case. The horizontal line shows the breakeven cost that the biomass has to achieve to be able to
satisfy the generators' requirements that the capital investment be offset by fuel cost savings.
Figure 7.10 Cost of residues and DFSS
US - Supply curve for Cofiring
DFSS cost in year, Aver age cost of Wood Residue
Source 12 Million Acre DFSS
projection
50
$/tonne
42.5
DFSS
$
35
t
27.5
a
20
n
Average Cost
12.6
5
1989
1995
2002
2008
2015
2021
Year
USBIOCST
7.15
DRAFT
6/11/97
Figure 7.11 Biomass supply curve
US Supply curs Cofiring
Milita
Utility Breakwert Cost $
Mic.Btu
Timing: While a coal fired station could be modified for co-firing in less than one year (including
environmental permitting) - the necessary biomass resource assessment, contractual
arrangements and logistics for biomass residues could take the better part of 18 months, based
on actual project experience. While the availability of residues is assumed to be significant and
would ultimately supply 50 Mtonnes or so, it is also recognized that its price and availability
are likely to be variable, with the price increasing with demand level, and for that reason the
biomass feedstock supply is expected to be a blend of dedicated feedstocks supply systems
(DFSS) and residues. The DFSS component is predicated on making a start into land
accumulation (purchase, lease, cooperatives etc.), and at the earliest land preparation and
planting in 1999 - the crops of choice are probably woody species in much of the NE and SE
and would require extensive nursery activity to put in place the needed clonal material for
planting out. With willow - the first harvest cycle would be 4 years after planting and a
rotation of 3 years thereafter, for poplar the cycle is likely to be in the range of 6 to 8 years.
Supply model sensitivities: Three supply models have been put together. The low (optimistic)
and high cost biomass scenarios are based on a 30 GW supply model that uses an incremental
amount of 23 Mtonnes residues over today's estimated 29 Mtonnes (Million tonnes), and the
biomass produced from about 11 Million Acres of DFSS. In the low and the high cases the
assumptions span a range of both residue and DFSS costs, resulting in average 2010 fuel costs
of 0.96 $/MBtu and 1.36 $/MBtu delivered to the GENCO.
Figure 7.12, below, shows the cumulative carbon displacement with time from the proposed
feedstock supply system - the average cost of the carbon substituted is shown by the solid line,
while the cost in the year specified is shown by the dotted line.
7.16
DRAFT
6/11/97
Figure 7.12 Average costs of carbon compensation and cumulative carbon replacement
Implementation Requirements: A significant effort is required to bring on the 10 - 11 Million
Acres proposed for 2020, since today the discussions are for demonstrations in DFSS at the
1000 Acre level. The development of adequate clonal material and management systems for
planting, tending, and harvesting will also be required. An idea of the rate of resource
deployment and the impacts with time is shown in the Table 7.4 below:
Table 7.4 Net Impacts and Costs - low cost biomass scenario
Year
1998
2000
2005
2010
2015
2020
GW-Biomass
0.2
0.75
3.1
7.6
14.6
26.4
Energy TWh
1.4
5.2
21.5
53
103
185
MTonnes Biomass
0.8
3
12
30
58
104
Percent DFSS
0
0
38
67
78
83
Carbon replacement Mtonnes
0.4
1.4
5.9
14.6
28.4
51
Carbon Compensation $/tce
0
0
3.94
12.3
14.4
15.5
Environmental Issues: Since most of the coal fired stations have efficient precipitators and
some have sulfur capture technologies, the net effect of 10% biomass substitution (on an energy
basis) appears to be negligible. The solid wastes (ash) are little changed in either composition
or mass (most biomass has considerably less ash than coal.). However, for some stations that
sell fly ash to Portland cement manufacture, there may be a need to negotiate the acceptance of
mixed biomass and coal ash in such applications with respect to ASTM standards.
The DFSS environmental impact is considered to be dependent on the choice of lands for the
plantation. In the case of replacing annual crop land with perennial DFSS there appears to be a
7.17
DRAFT
6/11/97
net environmental gain. For pasture land it probably is a wash and for replacement of forest
there may be some increased impacts.
The residue utilization has the potential to offset land filling and potential methane emissions
from land filling clean biomass materials. Based on experience in California, the issue will be
one of rationalizing the cost distribution between the "waste generator," the haulage contractor
and the generating station receiving the residue rather than it going to landfill. If such
negotiations were successful and the generating station could guarantee the reception of the
residues at all times (many urban wood residue generators do not have storage facilities) - both
residue costs and their availability could be significantly improved.
7.4 EFFICIENCY IMPROVEMENTS IN GENERATION AND T&D
Increasing operations and maintenance activities to lower heat rates (and thereby improve
efficiencies) can cut carbon emissions significantly and at low-cost. Cutting heat rates for all
fossil-fuel powerplants, both new and existing, by 5 percent, for instance, would cut emissions
by the same 5 percent (Hirst and Baxter, 1997).
Improving the efficiency of transmission and distribution (T&D) systems is another supply-side
option available to utilities. As with generation, T&D improvements can include both captial
investments (for example, new transformers and conductors) and improved operations.
Because T&D losses account for only about seven percent of total generation, the opportunities
to reduce CO2 emissions through such mechanisms are limited. However, they could
nonetheless be cost-effective. Improving T&D efficiency by 10 percent would cut emissions by
less than 1 percent (Hirst and Baxter, 1997).
7.5 NUCLEAR PLANT LIFE EXTENSION
Hydroelectric power currently supplies about 10% of the nation's electricity and constitutes
84% of the nation's renewable energy production. The adverse environmental affects of some
hydropower projects are now relatively well known (e.g., Mattice 1994), but significant progress
is also being made in mitigating these problems (Sale et al. 1991). Regulatory processes such as
the licensing of non-federal hydropower projects and the Endangered Species Act are having
real affects on hydropower projects, leading to a reduction of the environmental impacts from
this important energy source. The end result of these regulatory processes has also been a
consistent reduction in total energy production from hydropower.
In both the EIA reference case and the restructured case described in Chapter 6, nuclear plants
are projected to lose market share in the national mix of electricity generation. The nuclear
power capacity of 99.2 Gigawatts that existed in 1995 is forecast to drop to 88.9 gigawatts in
EIA reference forecast for 2010. This drop is primarily the result of the retirement of 17 plants
whose licenses expire between 1999 and 2010. The combined capacity of these 17 plants is
11.5 gigawatts. The average capacity factor of these plants is expected to remain between 76
and 79 percent throughout the forecast, deviating little from the current capacity factor of 77.
No additional nuclear units are actively under construction in the U.S. Therefore, no new
planned units are assumed to come into service during the 2010 forecast. One nuclear unit,
Watts Bar 1 owned by the Tennessee Valley Authority, received its license in 1996, but several
plants have also recently closed.
7.18
DRAFT
6/11/97
The 1997 AEO defines a "high nuclear case" which assumes that every nuclear plant operating
in 1996 has an additional 10 years of operation, as long as their operating costs do not exceed 4
cents per kilowatt-hour. This 2010 forecast results in the closure of only three nuclear plants
(totalling 1.3 gigawatts of capacity) due to license expirations and the addition of 10.2
gigawatts of new capacity from 14 plant lifetime extensions (ELA, 1996a, Table F5, p. 187;
Nuclear Regulatory Commission, 1996). According to the AEO "high nuclear case," 12 million
metric tons of carbon would be offset by this additional carbon-free source of electricity. Using
the capacity that's on the margin in the restructured case (with carbon emissions averaging 80
grams per kWh), the carbon reduction from this additional nuclear resource drops to 5.6 million
metric tons. A range of 2 to 5 million metric tons would appear to be a more realistic forecast
for the high efficiency/low carbon scenario.
Figure 7.x illustrates the important role that nuclear power life extension could have after 2020.
Only 45 of the nation's 105 nuclear plants have licenses that extend beyond 2020.
EIA (1996b) does not estimate the cost of its high nuclear case, although it acknowledges that
the physical degradation of some units would have to be reversed. OTA (1991) also notes the
potential carbon savings of extending the useful life of all nuclear plants to 45 years, but
assumes that this option involves minimal costs. Understanding the effects of aging in order to
better manage the aging nuclear infrastructure is an important R&D topic. Pressure vessel
embrittlement and the degradation of cables, pumps, and valves can be slowed by advances in
materials science and by developing digital instrumentation and controls technology. Such R&D
can help the U.S. maintain the current licensing basis of its nuclear power plants, thereby
enabling their operation to extend beyond the standard 40-year licensing period.
7.6 INCREASING GENERATION AND CAPACITY AT EXISTING
HYDROPOWER PLANTS
Hydroelectric power currently supplies about 10% (78 GW) of the nation's electricity and
constitutes 84% of the nation's generation from renewables (EIA, 1996a, Table A17).
Hydroelectric power plants produce no greenhouse gas emissions during operation (U.S.
Department of Energy, 1994). In the 1940s, 40% of the country's electricity came from
hydropower plants (Williams and Bateman, 1995). The adverse environmental affects of some
hydropower projects are now relatively well known (e.g., Mattice, 1994), but significant
progress is also being made in mitigating these problems (Sale et al., 1991).
Hydroelectric power uses the energy of falling water to generate electricity. Hydroelectric
generation technologies for utility-scale applications are generally considered to be mature, with
turbine efficiencies typically in the 75%-85% range (Office of Technology Assessment, 1995).
There are three types of hydropower facility:
Most hydropower plants use dams to raise water levels and regulate water availability,
thereby increasing its potential energy. Conventional hydropower (with reservoir storage)
can provide baseload, intermediate, or peaking power, depending on the availability of
water and project design (Office of Technology Assessment, 1995).
Some hydropower plants, called run-of-river systems, do not involve large dams or storage
reservoirs. Instead, smaller diversion structures are used to channel water through a canal
or penstock to a powerhouse, where water is returned to the river. Run-of-river systems
reduce some of the costs and environmental impacts associated with large hydro facilities.
7.19
DRAFT
6/11/97
Pumped storage projects use off-peak electricity (usually from a baseload power plant) to
pump water to an upper reservoir; this water is later released to flow through a generator.
during periods of peak demand. Such plants are net consumers of energy. Although
pumped storage is not a renewable energy technology, it can produce a net reduction in
greenhouse gas emissions when the fuel providing electricity for pumping has a lower carbon
content than the fuel being displaced by the pumped storage generation (U.S. Department of
Energy, 1994).
The main challenge for hydropower in recent years has been the growing concern over its local
environmental impacts. By damming rivers to create storage reservoirs, hydro facilities can
adversely affect terrestrial and aquatic ecosystems. Wildlife habitats can become inundated;
fish migration routes can be cut off, and fish can die in the generating turbines or because the
downstream water quality and habitat is changed; plants that grow along the riverbanks are
disrupted by changes in the natural water level, both above and below the dam; and large or
rapid variations in the amount of water being discharged can disrupt aquatic habitats and
accelerate erosion downstream.
Regulatory processes such as the licensing of non-federal hydropower projects and the
Endangered Species Act are having real affects on hydropower projects, leading to a reduction
of the environmental impacts from this energy source. The end result of these regulatory
processes has been a progressive reduction in total energy production from hydropower.
Between 1995 and 2010, 19 GW of hydropower at non-federal projects will be subject to
relicensing. Recent trends indicate that relicensing results in an average 8% loss in generation
(7,200 Gwh) due to the imposition of new environmental constraints on operation. The most
likely replacement for this lost, emission-free generation comes from a combination of fossil
fuels.
Under the "high efficiency/low carbon" scenario, and assuming a sustained regulatory
reinvention effort between now and the year 2010, incentives will exist that could motivate the
growth of hydroelectric power generation in either of two ways. Neither of these opportunities
involves the construction of hydropower plants at new sites. However, both will required
continued research and development to improve turbine system design and operation to
minimize adverse environmental effects.
Increasing generation at existing hydropower plants - This option consists of
modernizing and upgrading existing turbines and generators to increase their efficiency
and/or electrical output. Given enabling incentives, upgrading hydropower plants can
result energy production gains of 5% to 10%. Hydropower upgrades will have significant
corralary environmental benefits, because new generating technology offers more effective
fish passage, water quality improvements, and opportunities to improve downstream
aquatic habitats.
Adding generating capacity at existing dams - A recent resource assessment identified 21
MW of undeveloped hydropower capacity at existing dams (Rinehart et al., 1997). About
36,000 GWh of new hydropower generation could be added by developing these sites
between 1995 and 2010 (Office of Conservation and Renewable Energy, 1990).
There are additional gains in hydropower that are more uncertain and best evaluated in the
post 2010 period. The national hydropower resource assessment (Rinehart et al., 1997) has
identified 2,400 sites and 10 MW of environmentally acceptable hydropower at undeveloped
sites (projects that would require the construction of new dams or diversions). These resources
may eventually be developed given more adventagous economics, regulatory reinvention, and
technology improvements. Further development of efficient low-head generating technologies
7.20
DRAFT
6/11/97
would also encourage deployment at the many low-head sites that are otherwise unsuitable for
hydropower additions.
Considering just the near-term opportunities (present to 2010), further hydropower
development could reduce carbon emissions in 2010 by between 4.1 and 5.4 million tons.
Additional reductions can be acheived after 2010 with continuing advancements in generating
technologies and environmental mitigation techniques.
7.7 ADVANCED COAL TECHNOLOGIES
To test the possible effects on carbon emissions of other advanced fossil-fired electricity
generation technologies, we replaced the advanced technologies used by EIA with estimates
from DOE's Office of Fossil Energy (Table 5.6). These estimates changed the construction costs
and heat rates for advanced combustion turbines, combined-cycle units, and coal units.
ORCED did not select the advanced coal unit with either the EIA or the Fossil Energy estimates
of this unit's costs and operating characteristics; in both cases, its initial cost was too high to
warrant inclusion in the generation mix. The only significant change to occur was the
replacement of the most advanced combustion turbine as specified by EIA with an older
combined cycle unit. The net effect of this change on carbon emissions was negligible.
Table 7.5 Base Case vs Advanced Technologies (Costs in 1995$)
Original
Alternative
Original
Alternative
Advanced Gas Combined Cycle
Year of construction
2005
2005
2009
2010
Capital Cost, $/kW
410
525
410
500
Heat Rate
6284
5688
5817
5538
Fixed O&M, $/kW-yr
27
16
27
16
Variable O&M, c/kWh
0.05
0.015
0.05
0.015
Advanced Gas Combustion Turbine
Year of construction
2002
2005
2008
2010
Capital Cost, $/kW
339
400
374
364
Heat Rate
10873
8699
7793
8533
Fixed O&M, $/kW-yr
11.9
17.6
16.9
17.6
Variable O&M, c/kWh
0.010
0.012
0.05
0.012
Advanced Coal
Year of construction
2006
2005
Capital Cost, $/kW
1340
1050
Heat Rate
9600
7064
Fixed O&M, $/kW-yr
34
26
Variable O&M, /kWh
0.25
0.2
Source:
This limited analysis suggests that between now and the year 2010, highly efficient (i.e., a
heat rate of about 7000 Btu/kWh) but expensive (i.e., an cost of over $1000/kW) advanced
7.21
DRAFT
6/11/97
coal units cannot compete economically with either the generation mix that remains from the
1990s or with gas-fired combined-cycle units.
7.8 POTENTIAL FOR RENEWABLE OPTIONS IN 2020
7.8.1 Overview
Renewable sources of energy are either continuously resupplied by the sun or they tap
inexhaustible resources, such as geothermal energy. In contrast, fossil fuels - oil, coal and
natural gas - form so slowly in comparison to our rate of energy use that they are regarded as
finite. Today, roughly 12% of the country's electricity generating capacity is based on renewable
power systems, primarily hydropower (EIA, 1996a).
The use of modern renewable energy technologies to generate electricity either does not pollute
or emits far less pollution than burning fossil fuels. Most renewable energy technologies produce
no greenhouse gas emissions, at all during operation, and are responsible for only very small
emissions during manufacture of the components and construction of the generating plant.
Carbon reduction figures quoted in this section are based on emissions during operation only.
With a vigorous and sustained program of research, development and deployment, all of the
renewable energy technologies discussed here are capable of serving carbon-reduction goals at
competitive electricity prices by 2020. Not only could the contribution from renewables be
roughly double that of today, there will be a strong trend toward an even greater reliance on
renewables in the years beyond 2020 (Fig.7.x).⁵ Some renewable energy technologies are already
cost-effective today but are not more widely accepted because of a lack of industry experience,
others could be cost-effective through economies of scale at higher production levels, and still
others need substantial research and development before they will be cost-competitive with
fossil-fuel generating technologies. The intermittency of solar and wind resources means that
these technologies generally must be used in conjunction with energy storage systems, which
themselves require further R&D, although electric utilities have demonstrated that the
intermittency issue can be circumvented with appropriate design and operation of transmission
and distribution systems. Today, solar energy is most suitable for peak power applications
while wind power tends to be used as a fuel saver.
5 Many energy analysts, including some from the major oil companies, have accepted that
humanity as a whole cannot continue to consume energy at the current rate of growth without
eventually turning to renewable energy technologies. In The Evolution of the World's Energy
Systems, Shell International predicts that fossil fuels will continue to sustain global economic
development until 2020-2030, at which time "they reach their maximum potential and no
longer contribute to growth, being limited by the rate of production and commercialisation of
resources economically competitive with renewable energies." Sustained economic growth
beyond this time will be possible only if renewable energy technologies have been developed to
the point where they are ready for large-scale implementation in the 2020-2030 time period.
The alternative, according to Shell, is to curtail the growth of per capita GDP and find ways to
achieve a 2% per year improvement in energy intensity, something that has been seen for only
limited periods in the past (Royal Dutch/Shell Group of Companies, 1996).
7.22
DRAFT
6/11/97
Figure 7.13 Sustained Growth Scenario from Shell International
(Reproduced courtesy of Shell International Petroleum Company)
Exajoules
1500
Surprise
Geothermal/Ocean
Solar
1000
New biomass
Wind
Nuclear
500
Hydroelectric
Gas
Oil & natural gas liquids
Coal
0
Traditional biomass
1860
1880
1900
1920
1940
1960
1980
2000
2020
2040
2060
M68-B220902
The demand for electricity is growing most rapidly in the industrializing nations of the
developing world, and sales of renewable energy technologies to these countries could be an
important component of a U.S. carbon-reduction strategy. Renewables are likely to be adopted
more rapidly in the developing world than in the United States. The lack of infrastructure,
especially extensive electricity grids, in developing nations means that renewable energy
technologies, in particular wind power and photovoltaics, are not competing for marginal
markets with a pre-installed base of conventional power technologies, but rather are competing
on the ground floor for entry into thousands of separate electricity markets. In addition, many
of these countries lack adequate fossil-fuel reserves to meet their projected demand for
electricity. If future carbon credits are tradable between nations, international demand for
renewable power systems could provide markets for the U.S. renewables industry and increase
the supply of carbon credits available for purchase.
Some renewable energy technologies are already cost-effective in certain, specialized
applications. However, with the exception of hydroelectric power, their total contribution to
the U.S. electricity supply (and carbon-reduction goals) is unlikely to be significant until after
2020. More rapid deployment is likely to be hampered by several factors, including the
persistently low price of coal and natural gas. However, the cost of electricity from most of the
renewable energy technologies has fallen dramatically over the past 15 years, and is likely to
continue to decline relative to the cost of fossil-fuel electricity. Ongoing R&D will make
renewables progressively more affordable and competitive in a wider range of applications,
especially after 2010.
7.23
DRAFT
6/11/97
Figure 7.14 Renewable Technology Cost Trends (Source: NREL)
Photovoltaics
Wind
100
40
80
Cost of Electricity
(cents/kWh)
60
40
Cost of Electricity
30
(cents/kWh)
20
20
10
0
0
1980
1985
1990
1995
2000
2005
Solar Thermal
Geothermal
40
10
8
Cost of Electricity
30
(cents/kWh)
20
Cost of Electricity
(cents/kWh)
6
4
10
2
0
0
1980
1985
1990
1995
2000
2005
1980
1985
1990
1995
2000
2005
If renewables are to continue moving down the cost curve into the marketplace, the United
States needs an aggressive, integrated R&D strategy that addresses every part of the
development cycle, from basic research to improvements in manufacturing technology and
commercialization issues. Follow-through is important; if steps are not taken to ensure that a
developed technology is introduced to the marketplace, a firm from another country could
capitalize on U.S. technological advances. - a risk common to all emerging technologies.
Lowering the cost of electricity from each of the renewable energy technologies to the point
where it is competitive will not, however, ensure adequate market penetration to meet carbon-
reduction goals in time. The tendency of markets to "lock in" established technologies could
significantly slow down the adoption of renewables. Buyers tend to choose familiar products
even when they are a little more expensive or in some other way marginally inferior to the
competition. This phenomenon slows down the introduction of new technologies, such as
renewables, because buyers cannot be relied on to purchase the least costly competitive product
(Cowan and Kline, 1996). Demonstration projects go some way toward building industry and
market familiarity and confidence but, if we are to realize the carbon-reduction benefits of
renewables, more concerted action may be necessary to overcome the lock-in of established
(fossil-fuel and hydro) generating technologies.
The potential of each renewable energy technology to reduce atmospheric carbon in 2020 is
estimated in the pages that follow. However, with the exception of large-scale hydro, most
renewables are not technologically very mature. Terrestrial photovoltaics, for example, has only
been in existence for about 25 years, making it difficult to reliably predict the state of the
technology, or its likely role in the marketplace, over the same time period into the future.
7.24
DRAFT
6/11/97
Because of this uncertainty, the potential for carbon reduction is quoted as a range for most of
the renewable technologies.
7.8.2 Hydroelectric Power
The potential for expanding the generation and capacity of hydroelectric power by 2010 is
discussed in Section 7.6. This section discusses the potential to establish hydropower at new
sites by the year 2020.
FERC has identified 74 GW of untapped hydropower potential in this country, about 60% of it
in the western United States and Alaska. Only 2,400 of the nation's 80,000 existing dams are
used to generate electricity (Secretary of Energy Advisory Board, 1995).
Few new hydropower projects are currently slated for development. Environmental concerns
have led to more stringent licensing requirements, increasing the time required and cost of
meeting regulatory requirements. This has not only placed a limit on further hydropower
expansion, it has also discouraged renewal applications, jeopardizing the country's existing
hydropower capacity. Thus, the potential for new hydroelectric power generation in 2020 is
uncertain.6
7.8.3 Wind Power
Utility-scale wind power systems use groups of large wind turbines (wind farms) to harness
wind energy and convert it into electricity. Wind turbines are mounted on tall towers, usually
100 feet or more above the ground where the wind is faster and less turbulent.
Wind turbines produce no greenhouse gas emissions during operation. About three-fourths of
the states in the nation have wind resources that are suitable for utility-scale power generation
(Williams and Bateman, 1995), although competing land-use and environmental factors result in
the exclusion of some of the land (Energy Information Administration, 1996). Even with these
restrictions, however, the U.S. wind resource is large enough to generate one and a half times as
much electricity as is currently consumed in the United States (Williams and Bateman, 1995).
The intermittency of the wind resource means that the use of wind power on this scale would
require careful design and operation of transmission and distribution systems, or the
development of improved energy storage systems.
Wind technology has a wide variety of applications, including off-grid remote power for homes
and communities, but the greatest contribution to U.S. carbon reduction goals is likely to come
from grid-connected utility wind farms. Wind power is already cost-competitive with fossil
fuel power in certain situations. It tends to be used as a fuel-saver today, and increasing
experience will continue to drive cost and performance improvements. By 2020, improved
blade designs could extract even more kinetic energy from the wind, improving the efficiency of
the system, and new materials could help turbine blades to better deal with the large and
variable mechanical stresses they face, lowering costs while maintaining 30-year blade lifetimes.
Computer modeling of components and subsystems will enable the optimization of turbine
designs for site-specific operating conditions, and the use of direct-drive generators and
variable speed turbines will yield higher conversion efficiencies.
6
Throughout section 7.7, calculations for carbon savings are based on 100 kg/MWh, which
assumes that the renewable energy technologies are displacing a combination of the latest
generation of natural-gas-fired combustion turbines and combined-cycle power plants. The
estimate of potential expanded capacity is based on DOE and NREL internal analyses.
7.25
DRAFT
6/11/97
Performance improvements such as these will enable utilities to make use of more moderate
wind resources, increasing the geographic applicability of wind power, in addition to lowering
costs. The cost of wind-generated electricity has already dropped from over 30c/kWh in 1981
to 4c/kWh-5c/kWh today, and is expected to drop another 40% to 50% by 2020 (Office of
Technology Assessment, 1995).
Siting issues may have as large an influence on the rate of adoption of wind power as
technological considerations. There are sometimes competing demands for the land, although
utility-scale wind generation is actually a good complement to agriculture. Good wind sites are
often along the tops of ridges, a highly visible location for a large wind farm, and this can be a
cause for concern when the site is either close to a population center or in an area of particularly
great scenic value. Another environmental consideration affecting site selection is the potential
risk to birds, particularly raptors, flying into the rapidly turning rotor blades. The widespread
adoption of wind technology is partly dependent on finding ways to reduce this problem.
Wind regimes are extremely site-specific, so even though wind resources have been broadly
categorized for the nation as a whole, the siting of individual wind farms requires detailed
information in order to select the best site. Wind speeds can vary dramatically over the course
of seconds (due to turbulence), hours (diurnal variations), days (weather fronts) and months
(seasonal variations). The best locations are those with strong, sustained winds having little
turbulence. Finding such locations requires extensive prospecting and monitoring (Office of
Technology Assessment, 1995). Better tools for resource characterization and prediction will
enhance the value of wind power by enabling utilities to more reliably predict the power output
from wind sites.
Strong international interest in wind power could also speed its rate of adoption in the United
States. Foreign markets currently account for most new wind installations, so this is where U.S.
firms are currently gaining valuable experience with marketing and operations.
In the United States today, wind power accounts for about 2 GW of generating capacity
(Energy Information Administration, 1996a). By 2020, new U.S. wind installations could
amount to 30-60 GW, displacing 9-18 Mt/yr of carbon emissions.⁷
7.8.4 Biomass Power
Biomass refers to living matter, usually plants, used to produce energy. This includes energy
crops grown specifically to be used as fuel, such as fast-growing trees, as well as agricultural
and forestry residues. The biomass content of landfills is considered separately (see 7.8.8).
Generating power from agricultural and forestry residues can contribute to carbon reduction
goals to the extent that the wastes, such as sawmill offcuts, displace fuels with a higher carbon
content per Btu, such as coal. But the greatest carbon savings come when biomass power is
generated from plant feedstocks grown specifically for this purpose. With dedicated energy
crops, biomass power plants generate no net carbon emissions during operation.
There are three primary technologies for converting biomass energy to electricity:
Direct combustion involves burning the biomass in a boiler to convert water to steam, then
running the steam through a turbine, the same process used in coal-fired plants.
Virtually all biomass electric plants today use direct-fired, conventional steam turbines
(Office of Technology Assessment, 1995).
7
This range of potential expanded capacity is based on DOE and NREL internal analyses.
7.26
DRAFT
6/11/97
Gasification involves converting the solid biomass to a gas that is cleaned and then
burned in a combustion turbine - potentially much more efficient, and currently in the
demonstration stage of development.
Cofiring involves burning a mixture of solid biomass and coal in existing power stations,
which requires minimal modifications to the existing station, plus the addition of
biomass fuel-handling equipment.
Cofiring with biomass in existing or new coal power stations offers an attractive near-term
option for reducing carbon emissions with biomass technologies. It can be a relatively low-cost,
low-risk option, particularly for utilities located near existing biomass supplies. Cofiring with
low-sulfur biomass also reduces total sulfur dioxide emissions, which helps utilities meet the
increasingly stringent environmental constraints on conventional power stations. However,
cofiring does not increase generating capacity, so it should not be considered an option for
meeting additional demand for electricity, unless new power stations are cofiring stations.
Biomass gasification systems can take advantage of advanced turbine designs and heat-
recovery steam generators to achieve almost twice the efficiency of currently installed biomass
technologies. This makes it possible to roughly double the amount of electricity or, equivalently,
halve the emissions per kilowatt generated. An attractive near-term application of this
technology will be industrial-scale systems for repowering pulp and paper mills, which usually
cogenerate electricity on site from waste wood. About 70% of the power plants in this industry
will need to be replaced in the next 10 to 15 years (NREL estimates, 1997).
New fuel-handling and energy-conversion technologies promise to bring the cost of biomass-
fueled electricity down below 4c/kWh by 2020 (Secretary of Energy Advisory Board, 1995).
At this price, biomass power will be competitive with the cost of intermediate-load power from
conventional plants. Whole-tree burners, for example, which avoid the cost of chipping the
wood before burning it, could reduce the cost of harvesting and delivering the biomass to the
power plant by about one-third (Office of Technology Assessment, 1995). The most significant
improvements in efficiency and cost are expected to come from the advanced gas turbine
technologies, such as combined-cycle turbines and steam-injected gas turbines, that are currently
under development. High-pressure gasification technologies yield the highest efficiencies but
require more expensive methods for cleaning the hot gases before they enter the turbine (NREL
estimates, 1997).
Our ability to meet carbon reduction goals by expanding biomass power generation is contingent
on developing dedicated biomass fuel crops on a large-enough scale. Some land areas suitable
for biomass development face competition from other uses, such as wildlife habitat or food
crop production, but by 2020, U.S. farmers could be growing sufficient biomass feedstocks or
hybrid (energy/food) crops to meet demand. Energy crop production is likely to exceed current
goals, which include a delivered fuel cost of $34/ton and yields of 8-10 dry tons per acre per
year (Secretary of Energy Advisory Board, 1995), and advances in genetic research could raise
the growth rate of energy crops by 50% (NREL estimates, 1997).
Although the potential for biomass production is quite large, transportation costs are a
potentially limiting factor, since biomass fuels have a low energy density, i.e., a low Btu content
per weight of fuel (Energy Information Administration, 1996a). Because of this, today's
biomass plants typically use materials collected within a 50-mile radius. In the future, most
biomass power stations are likely to be located near farms dedicated to growing energy crops.
Some power stations may run on biomass-derived fuels, such as biocrude oil, which can easily
be transported over long distances from biomass fuel refineries. Biocrude has an energy density
7.27
DRAFT
6/11/97
three to four times that of the original biomass, and has the potential to fire existing gas turbines
with few modifications (Bain and Jones, 1993).
Current grid-connected biomass generating capacity is about 8 GW (Energy Information
Administration, 1996a). By 2020, new grid-connected electricity from biomass could total 20-
40 GW. This increase, which includes all types of biomass capacity additions, would save 11-
22 Mt/yr of carbon emissions, assuming dedicated energy crops are used for three-fourths of
the power generation.8
7.8.5 Geothermal Electricity
Geothermal generating technologies make use of the heat energy stored within the Earth's crust
to produce electricity. There are different types of geothermal resources, each of which requires
a different technology to extract the thermal energy for power generation. Today's geothermal
power plants are driven by hot water and steam from wells drilled into hydrothermal reservoirs
- naturally occurring zones of groundwater trapped in the fissures and pores of underground
rock. In most geothermal power plants, which are typically used to provide baseload power,
steam from hydrothermal reservoirs is used to generate electricity by spinning a turbine
generator directly; in others (binary plants), geothermal hot water is used to vaporize a working
fluid that boils at a low temperature - this vapor is then piped to a turbine to generate
electricity. Tomorrow's geothermal power plants could make use of hot dry rock resources -
areas of exceptionally hot rock (above 150°C) that have little or no water in them. Energy can
be extracted from these zones by injecting water from the surface to be heated underground.
Most geothermal power plants release some carbon dioxide during operation but, overall, these
emissions are less than 4% of those from coal-fired plants (Office of Technology Assessment,
1995).
Potential geothermal energy reserves are so large that they are considered inexhaustible. With
the technologies in use today, however, geothermal power applications in the United States are
geographically limited to western regions that have hydrothermal resources of hot water and
steam (Energy Information Administration, 1996a). These resources represent only about 4% of
the country's total geothermal resources (NREL estimates, 1997). The role of geothermal power
in 2020 could be dramatically expanded with advances in technologies for tapping hot dry
rock, which accounts for most of the nation's geothermal resource. Zones of hot dry rock are
also geographically much more widespread than hydrothermal reservoirs and could provide a
virtually limitless supply of energy.
The major challenge and cost-driver for geothermal power systems is resource exploration and
characterization - finding geothermal energy resources of sufficient temperature and assessing
the amount of energy that can be continuously extracted without depleting them. The cost of
geothermal electricity is highly dependent on resource characteristics such as temperature,
depth, fluid chemistry and ease of drilling. By 2020, improvements in drilling technology,
advanced seismic data gathering and better computer modeling and interpretation of that data
could lower the average cost of locating and assessing geothermal resources by 50% (NREL
estimates, 1997).
Although total geothermal resources are inexhaustible, the fluid in individual hydrothermal
reservoirs can be depleted to the point where the reservoir becomes economically unproductive.
For this reason, sustainable use of specific hydrothermal resources always requires the
8
This range of potential expanded capacity is based on DOE and NREL internal analyses.
7.28
DRAFT
6/11/97
without access to power, this application will have a major impact on PV technology, especially
on manufacturing costs.
The biggest U.S. market for PV, and its greatest potential for domestic carbon reduction,
ultimately lies in grid-connected electricity generation. One of the biggest near-term markets is
likely to be building-integrated photovoltaics. There is a good match between the output of PV
systems and the power requirements of commercial buildings, especially offices. By locating a
PV system on the building, its demand for grid electricity can be reduced. PV modules are now
being developed that can replace standard building materials, such as roofing shingles and
exterior cladding, effectively lowering the cost of PV electricity because the modules serve two
functions. Incorporating PV into building materials is technically complex, requiring joint
development among several normally separate elements of the building industry, but as they
enter mass production during the next ten years, such "architectural" PV modules will
significantly strengthen the economic appeal of installing PV systems. Other promising
applications include utility grid support (when demand at the end of a distribution grid grows
beyond design specifications) and extending the life of thermally overloaded substations. The
modularity of PV systems and the speed with which they can be deployed are advantages in
these applications, since this makes it easy to add incremental power.
Although the cost of PV-generated electricity is still quite high (25¢/kWh to 50c/kWh), costs
have fallen dramatically in the past and are likely to come down by a factor of two to five by
2020,9 reducing the cost of electricity from installed PV systems to less than 10c/kWh (Office
of Technology Assessment, 1995). The cost of photovoltaic modules has dropped from roughly
$30 per watt in the mid-1970s to less than $4 per watt today, and will continue to drop
(Secretary of Energy Advisory Board, 1995). The cost of PV electricity is also affected by the
cost of the "balance of systems" needed to make use of the modules, including wires, mounting
structures, power conditioners, batteries and tracking systems. These components can
represent up to half of the cost of a PV system, so improvements in balance-of-systems costs,
including more-efficient energy storage devices, could have a dramatic effect on the rate at
which PV technology is adopted.
Ongoing research is expected to increase the efficiency of commercial modules by 50% or more
and therefore their average energy per unit area. Module lifetimes, currently 10 to 20 years, are
projected to be 30 years or more by 2020. System installation and maintenance costs are
expected to decline significantly as utilities gain more experience with this technology.
Currently, suppliers have to provide custom-designed systems every time they undertake a new
installation.
Current efforts to improve manufacturing techniques could also have a significant impact on
cost. PV technology is already so advanced that it might be possible to achieve competitive PV
electricity through economies of scale in manufacturing alone. In all mature industrial
technologies, production costs are ultimately limited by the cost of raw material inputs. PV thin
films use highly automated production processes and very little raw material; once their
efficiencies have been raised, they may offer the best potential for low-cost generation of PV
electricity.
Although PV power systems will definitely see major cost decreases over the next few decades,
it is unclear how far and how fast PV will go in penetrating large-scale utility markets in the
U.S. Nonetheless, installed PV capacity in this country could realistically be 10-20 GW by
2020, saving 3-5 Mt/yr of carbon emissions (Secretary of Energy Advisory Board, 1995).
9
Based on DOE and NREL internal analyses.
7.30
DRAFT
6/11/97
reinjection of water into the underground reservoir to maintain pressure. Injection of fluids from.
the Earth's surface can also help to increase output from reservoirs after they have become,
depleted. Uncertain reservoir lifetimes substantially increase investor risk, which means that
geothermal developers face higher finance rates. Research on reservoir characterization could
substantially reduce this risk in the future, speeding the adoption of this technology.
Current geothermal power-generation technologies already enable economic use of many
moderate-temperature (<150°C) geothermal resources, which are likely to be the predominant
source for near-term geothermal development in the United States (U.S. Department of Energy,
1994). Technological advances are likely to continue raising conversion efficiencies and lowering
plant costs. Current R&D in heat exchangers, hot fluid management systems and new thermal
conversion cycles suggest that energy cost reductions of at least 20% are likely in the next few
years (NREL estimates, 1997). Although the engineering feasibility of extracting energy from hot
dry rock has already been demonstrated (Secretary of Energy Advisory Board, 1995), further
R&D is necessary to make the technology commercially viable.
Geothermal generating capacity in the United States is currently about 2 GW. By 2020, new
U.S. geothermal electric capacity could amount to 10-20 GW, saving 7-15 Mt/yr in carbon
emissions.
7.8.6 Photovoltaic Power Systems
Photovoltaic (PV) devices use semiconductor technology to convert light ("photons") into
electricity ("voltage") without any moving parts. Individual PV cells, which produce DC
electricity, are usually connected together to form modules (panels) that have the desired
voltage and output. Photovoltaic systems can provide an independent, stand-alone power
supply or can be connected to the electrical grid. In stand-alone applications, batteries can be
used to store electrical power for periods when the sun isn't shining, and modules can be
connected to inverters to supply AC electricity. Grid-connected systems both feed power into
the grid and use the grid as a source of backup power.
There are three types of PV technology in use today:
Crystalline silicon wafers are the most mature technology, with a high sunlight-to-electricity
conversion ratio but a high materials cost.
Thin films have the potential of inexpensive manufacture, are easier to handle than
silicon wafers, but typically have relatively low conversion efficiencies.
Concentrators use inexpensive lenses to concentrate the sunlight falling on a cell,
producing the highest efficiency of all but requiring the use of tracking equipment to
follow the sun.
PV power systems produce no atmospheric pollution or fuel wastes during operation. They
work well in any climate, can generate electricity in direct or diffuse sunlight, and are suitable
for use in every state in the country.
PV is currently a cost-effective power source for a variety of high-value, off-grid applications
including telecommunications repeaters, water pumping on farms and ranches, remote
residences, highway signs and emergency call boxes. A critical application for PV today, and
one that is rapidly expanding, is power for individual homes and villages in developing nations.
Since PV serves that market very well, and since there are about two billion people in the world
7.29
DRAFT
6/11/97
7.8.7 Solar Thermal Electricity
Solar thermal power systems use the heat energy from solar radiation to generate electricity.
Reflective surfaces concentrate the sun's rays to heat a receiver filled with oil or another heat-
exchange fluid. The heated fluid is then used in some form of heat engine to generate electricity.
Mechanical drives turn the reflective surfaces during the day to keep the solar radiation focused
on the receiver, and natural gas is often used to provide backup power for periods when the sun
isn't shining.
There are three main types of solar concentrators used in solar thermal electric systems:
Parabolic trough systems concentrate solar rays onto a receiver pipe located along the
focal line of a curved, trough-shaped reflector. This technology has a proven track
record, with about 350 MW operating successfully in California since the 1980s.
Power towers (central receivers) use a field of sun-tracking mirrors (heliostats) to reflect
solar radiation onto a receiver that sits on top of a tall tower. Molten salt is typically
used to store heat energy for periods when the sun isn't shining. This technology has
been successfully operated in 10-MW pilot plant configurations, and is expected to be
economic at plant sizes of 30 MW or more.
Parabolic dish systems use a dish-shaped reflector to concentrate solar radiation onto the
receiver of a Stirling heat engine mounted at the focal point of the dish. Dish/engine
technology is still under development, but 25-kW systems are expected to be
commercially available for grid-connected applications by 1999 (Rueckert, 1997).
Solar thermal electric systems produce no greenhouse gas emissions during operation (U.S.
Department of Energy, 1994), although hybrid solar/fossil systems release greenhouse gases in
proportion to the degree of fossil fuel used. Trough and dish/engine systems provide utilities
with a variety of modular, distributed power options and can be constructed and deployed in a
relatively short period of time. Unlike photovoltaic systems, which can generate power in any
climate, solar thermal electric systems require high levels of direct solar radiation (direct
sunlight) for economic operation. Trough systems and power towers also require large land
areas, and face similar siting issues to other large power plants. In the United States, these
technologies are, therefore, particularly well-suited to the desert regions of the Southwest.
Although they are in different stages of development, all three types of solar thermal electric
technologies are advanced enough to make a significant contribution to carbon reduction goals
by 2020. They are likely to become competitive with conventional power technologies when
adequate manufacturing levels are reached, with hybrid (solar. thermal/fossil-fuel) power
systems penetrating utility markets first.
Solar thermal electric technologies need both market deployment and continued R&D to make a
significant contribution to global energy demand. There are a number of near-term opportunities
for development of commercial solar thermal technologies. Most of these openings are either
niches within existing markets or special opportunities related to growing concerns about the
impact of energy development on the local and global environment. Further commercial
deployment of new solar thermal electric systems is contingent on additional R&D to improve
the reliability of the advanced systems currently under development, and to reduce costs
through improved components and manufacturing techniques and lower maintenance
requirements. With further R&D, a highly attractive option for solar thermal technology lies in
hybrid systems that use solar energy for preheat at either stage of a combined-cycle natural gas
power plant.
7.31
DRAFT
6/11/97
There is currently 364 MW of utility-connected solar thermal generating capacity in the United
States. By 2020, new capacity additions could total 8-16 GW, saving the equivalent of 2-5
Mt/yr of carbon emissions.
7.8.8 Landfill Gas Recovery
When food scraps and other organic wastes in landfills decompose, they produce methane, a
potent greenhouse gas that is also the main ingredient of natural gas. According to the
Intergovernmental Panel on Climate Change, each pound of methane is about 21 times more
effective at trapping radiation in the atmosphere than a pound of carbon dioxide. Landfills are
the largest source of anthropogenic methane emissions in the United States, responsible for
almost 40% of these emissions each year (U.S. Environmental Protection Agency, 1997).
New EPA regulations require operators to seal larger, closed landfills with a special cap, collect
the gas, and burn it to prevent atmospheric release of methane. But wells sunk into landfills can
capture the gas before it escapes the surface. It can then be burned in internal combustion
engines to generate electricity, thereby harnessing its energy value. Some landfills clean the gas
so that it can be burned in turbines or heat-generating boilers, and a few clean the gas to
pipeline quality and sell it. One large landfill cleans the gas and uses it to fuel its garbage
trucks.
Today, about 165 landfills recover and utilize methane as a fuel. Various estimates
(Governmental Advisory Associates, 1994; U.S. Environmental Protection Agency, 1997)
indicate that between 300 and 750 of the country's 3,500 landfills could economically recover
methane using currently available technologies. The development of more-efficient, less-
expensive technologies for gas recovery, clean-up and utilization could accelerate the adoption
of landfill gas-to-energy systems. For example, highly efficient fuel cells have been
experimentally operated on landfill gas using new clean-up technology.
By 2020, 0.2-0.5 quads of energy per year could be practicably recovered from the methane in
landfills and converted to electricity, saving the equivalent of 22-54 Mt/yr of carbon emissions
(U.S. Department of Energy, 1994).
7.32
DRAFT
6/11/97
Figure 7.15 Past and Projected Future Costs for Four Renewable Energy Resources
Renewable Technology.CostTrends
Photovoltaics
Wind
100
40
60
Cost of Electricity
(cents/kWh)
60
03
Cost of Efectricity
30
(cents/kWh)
20
10
20
0
0
1960
1985
1990
1995
2000
2005
1980
1985
1990
1995
2000
2005
Biomass
Geothermal
4
10
8
3
Cost of Ethanol
(S/galion)
2
Cost of Electricity
(cents/kWh)
6
4
1
2
0
0
1930
1985
1990
1995
2000
2005
1980
1985
1990
1995
2000
2005
7.8 SUMMARY
Table 7.6 summarizes the potential reductions in carbon emissions that might occur as the result
of the technology options discussed in this chapter. Each option is intended to reflect roughly
the amount that could be achieved under aggressive policies combined with a carbon incentive
of approximately $50/ton. The total carbon reductions by 2010 are estimated to range from 71
to 79 million metric tons.
Table 7.6 Carbon Reduction Potential of Selected Electricity Supply Technology Options:
High Efficiency/Low Carbon Scenario
High
High
Efficiency/Low
Efficiency/Low
Carbon:
Carbon:
Moderate
High
Converting coal-based power plants to natural gas
50
50
Cofiring coal with biomass
15
20
Extending the life of existing nuclear plants
2
4
Hydropower expansions
4
5
Total
71
79
The analysis of renewable energy potential over the next quarter century indicates that with a
vigorous and sustained program of research, development and deployment, renewable energy
technologies could be providing a greater and rapidly growing contribution to electricity
generation by the year 2020. In combination, hydroelectric, wind, biomass, PV, and solar
thermal power options could deliver 78 to 146 GW of electricity in 2020, with a corresponding
reduction of 33 to 48 million metric tons of carbon in that same year.
7.33
DRAFT
6/11/97
7.9 REFERENCES
Electric Power Research Institute (EPRI). 1993. TAGᵀM Technical Assessment Guide Volume 1:
Electricity Supply-1993, Palo Alto, California: TR-102276-V1R7.
Energy Information Administration. 1996a. Annual Energy Outlook 1997 with Projections to
2015, Washington, DC, DOE/EIA-0383(97).
Energy Information Administration. 1996b. Emissions of Greenhouse Gases in the United States
1995, Washington, DC, DOE/EIA-0573(95).
Energy Information Administration. 1995. Inventory of Power Plants in the United States 1994,
Washington, DC, DOE/EIA-0095(94).
Hadley, S. W. 1996. ORFIN: An Electric Utility Financial and Production Simulator, Oak Ridge,
Tennessee: Oak Ridge National Laboratory, ORNL/CON-430.
North American Electric Reliability Council (NERC). 1996. Generating Availability Report,
1991 - 1995, Princeton, NJ, July.
Bains, R. L. and J. Jones. 1993. "Renewable Electricity from Biomass," Solar Today, May/June.
Cowan, R. and D. Kline. 1996. Presented at the International Symposium on Energy and
Environmental Management and Technology, The Implications of Potential "Lock-In" in Markets for
Renewable Energy, December.
Energy Information Administration. 1996. International Energy Outlook. U.S. Department of
Energy.
Electric Power Research Institute and U.S. Department of Energy. 1997. Renewable Energy
Technology Characterizations, draft, February.
Electric Power Research Institute. 1995. Making Biopower Work for Utilities: A Rationale for Near-
Term Investment in Integrated Biomass Power Systems (Report Summary), November.
Office of Technology Assessment, U.S. Congress. 1995. Renewing Our Energy Fulture. OTA-
ETI-614. U.S. Government Printing Office, GPO stock #052-003-01427-1.
RDI (Resource Data International). 1996. Powerdat Database, Boulder, Colorado: Resource
Data International, Inc.
Williams, S. and B. G. Bateman. 1995. Power Plays, Investor Responsibility Research Center.
Yergen report. (Full reference to follow.)
Royal Dutch/Shell Group of Companies. 1996. London, United Kingdom: The Evolution of the
World's Energy Systems.
U.S. Department of Energy. October 1994. Climate Challenge Options Workbook.
U.S. Department of Energy. 1994. Talking Points, Renewable Energy: Biomass and Biofuels,
October.
7.34
DRAFT
6/11/97
U.S. Environmental Protection Agency.
1997.
EnviroSense Web site, at
http://es.inel.gov/partners/xgw01154.html#meth, Landfill Methane Outreach Program.
7.10 REFERENCES (FOR RENEWABLES)
Bain, R. L. and J. Jones. 1993. "Renewable Electricity from Biomass," Solar Today, May/June.
Cowan, R. and D. Kline. 1996. The Implications of Potential "Lock-In" in Markets for Renewable
Energy, presented at the International Symposium on Energy and Environmental Management
and Technology, Newport Beach, CA, December.
Energy Information Administration. 1996a. Annual Energy Outlook 1997 with Projections to
2015, Washington, DC, DOE/EIA-0383(97).
Energy Information Administration. 1996b. Emissions of Greenhouse Gases in the United States
1995, Washington, DC, DOE/EIA-0573(95).
Energy Information Administration. 1996c. International Energy Outlook. U.S. Department of
Energy.
Governmental Advisory Associates, Inc. 1994. Methane Recovery From Landfill Yearbook, 1994-95.
Utility Data Institute.
Mattice, J. S. 1991. Ecological effects of hydropower facilities. Chapt. 8 In J. S. Gulliver and R.
E. A. Arndt (eds.), Hydropower Engineering Handbook, McGraw-Hill, Inc., New York, New
York.
Office of Conservation and Renewable Energy. 1990. Renewable Energy Technology Evolution
Rationales, Internal Working Draft. U.S. Department of Energy, October. Pages 4-5.
Office of Technology Assessment, U.S. Congress. 1995. Renewing Our Energy Future. OTA-
ETI-614. U.S. Government Printing Office, GPO stock #052-003-01427-1.
Rinehart, B. N., G. F. Cada, J. E. Francfort, M. J. Sale, and G. L. Sommers. 1997. DOE
hydropower program, biennial report, 1996-1997. DOE/ID-xxxxx, U.S. Department of Energy,
Idaho Operations Office, Idaho Falls, Idaho (In press).
Royal Dutch/Shell Group of Companies. 1996. London, United Kingdom: The Evolution of the
World's Energy Systems.
Rueckert, Thomas. 1997. Personal communication from Tom Rueckert, DOE Solar Thermal
Program, May.
Sale, M. J., G. F. Cada, L. H. Chang, S. W. Christensen, J. E. Francfort, B. N. Rinehart,
S.F. Railsback, and G. L. Sommers. 1991. Environmental mitigation at hydroelectric projects.
Vol. I. Current practices for instream flow needs, dissolved oxygen, and fish passage.
DOE/ID-10360. U.S. Department of Energy, Idaho Falls, Idaho.
Secretary of Energy Advisory Board. 1995. Task Force on Strategic Energy Research and
Development, Annex 1: Technology Profiles. U.S. Department of Energy, June.
U.S. Department of Energy. 1994. Climate Challenge Options Workbook, October.
7.35
DRAFT
6/11/97
U.S. Environmental Protection Agency.
1997.
EnviroSense Web site, at
http://es.inel.gov/partners/xgw01154.html#meth. Landfill Methane Outreach Program.
Williams, S. and B.G. Bateman. 1995. Power Plays, Investor Responsibility Research Center.
7.36
DRAFT
6/10/97
CHAPTER 8
SUMMARY AND CONCLUSIONS
Two overarching conclusions emerge from the end-use sector analyses. First, a vigorous national
commitment to develop and deploy cost-effective energy-efficient technologies can significantly
restrain the growth in U.S. energy consumption and carbon emissions such that levels in 2010
are close to those in 1997. In combination with low-carbon technologies and utility sector
investments, carbon emisions in the U.S. can be reduced by two-thirds to three-fourths of the
levels necessary for stabilization at 1990 levels in 2010.
Second, a next generation of advanced energy efficiency and renewable energy technologies
promises to enable the continuation of an aggressive pace of energy and carbon reductions over
the next quarter century. Each of the end-use chapters and the analysis of renewable energy
options documents a wide array of advanced technologies that could be cost-effective by the
year 2020, assuming a vigorous and sustained program of energy R&D beyond 2010.
The analyses behind these conclusions are summarized below.
8.1 THE PROSPECT FOR IMPROVED ENERGY EFFICIENCIES BY 2010
8.1.1 Prospects for Improved Efficiencies and Carbon Emission Reductions by the
Year 2010
Table 8.1 and Figure 8.1 compare the nation's primary energy use in quads for the years 1990
and 1997 with the results of the three scenarios for 2010.
Table 8.1 Primary Energy Use in Quads: 1990-2010
2010
High
Business-
Efficiency
as-Usual
Efficiency
/Low
1990
1997
Case
Case
Carbon
Buildings
29.4
33.7
36.0
34.1
32.0
Industry
32.1
32.6
37.4
35.4
33.6
Transportation
22.6
25.5
32.3
29.2
27.8
Total
84.2
91.8
105.7
98.7
93.4
Source: Energy use estimates for 1990 come from Energy Information Administration
(1996a, Table 2.1, p. 39). Energy use estimates for 1997 come from forecasts conducted
for Energy Information Administration (1996b). Note: numbers may not add to the
totals due to rounding.
The major observations from these are as follows.
8.1
DRAFT
6/10/97
In the "business-as-usual" case, energy use increases by 22 quads (26%) between 1990
and 2010; 8 quads of this increase have occurred during the first seven years of this 20-
year period. The fastest growing sector during these initial seven years has been
buildings (4.3 quads) followed by transportation (2.9 quads) and industry (0.5 quads).
In the BAU case, the fastest growing sector during the remaining 13 years is
transportation (6.8 quads) followed by industry (4.8 quads) and then buildings (2.3
quads) in the BAU case. The rapid projected growth in the energy consumed for
transportation is driven by estimates of increased per capita travel and minimal fuel
efficiency gains.
The "efficiency" scenario cuts the overall growth between 1990 and 2010 from 22 to 15
quads. This is a 17% increase over the level of energy consumption in 1990, down from
a 26% increase forecast by the BAU case. Relative to the BAU case, the efficiency
scenario for transportation delivers slightly more energy savings (3.1 quads) than do
efficiency scenarios for the industrial (2.0) or buildings (1.9) sectors. Compared with
1997 levels, the smallest increase in energy growth for the efficiency case is in buildings
(0.4 quads), followed by industry (2.8 quads), and transportation (3.7 quads).
The "high efficiency/low carbon" scenario further decreases the overall growth between
1990 and 2010, reducing it from 22 to 9 quads. This is an 11% increase over the level of
energy consumption in 1990. Relative to the BAU case, the "high efficiency/low
carbon" scenario for buildings, industry, and transportation delivers energy savings
ranging from 3.8 to 4.5 quads. Compared with 1997 levels, buildings is down about 2
quads and industry and transportation are up 1 and 2 quads respectively.
Figure 8.1 Primary Energy Use in Quads: 1990-2010
Revised
Reference
Transportation
Case
Industry
Efficiency
Case
100
Buildings
High Efficiency/
Low Carbon
Case
U. S. Primary Energy Use (in Quads)
50
1990
1997
2010
Year
8.2
DRAFT
6/10/97
Table 8.2 documents the impact of these projected energy savings in 2010 on carbon emissions
in that same year. It also presents the results of a more complete "high efficiency/low carbon"
scenario, which characterizes the impacts of including the high level of efficiency improvements
along with two additional types of low-carbon technologies.
It includes end-use carbon reductions that do not result entirely from reduced energy
consumption, but rather result from either fuel switching or by displacing carbon from
industrial processes. Specifically, the buildings sector includes stationary fuel cells for
cogeneration, and the industrial sector includes advanced turbine systems, biomass
gasification, inert anodes and wettable cathodes in the aluminum industry, and slag cement.
These carbon reductions were not included in the "high efficiency/low carbon" models for
buildings and industry; rather, they are based on additional case studies.
It also includes a number of electricity supply technologies that could reduce carbon
emissions in the year 2010 under the conditions characterized by the "high efficiency/low
carbon" scenario..
Table 8.2 Carbon Emissions (in million metric tons): 1990-2010
2010
High
Efficiency
High
Business-as-
Efficiency
Case
Efficiency/
Usual
Case
(w/o Low-
Low Carbon
Case
Carbon
Caseb
1990
1997
Technologies)
460
511
571
546
532
525 to 530
Buildings
Industry
452
482
534
512
494
461 to 483
Transportation
432
486
616
543
513
513
-
-
-157 to -138
Utilities
-
-
-
Total (rounded)
1340
1480
1720
1600
1540
1340 to 1390
"These carbon forecasts for 2010 represent our best "point estimates." The precision of these estimates is
unknown, since none of the forecasts used in this report are based on parameters with known probability
distributions.
ᵇThis scenario includes the carbon emission reductions resulting from a carbon permit price of $50/tonne:
(1) dispatch of power plants in which natural gas is favored relative to coal, (2) repowering and
partial repowering of coal-based power plants to convert to natural gas, and (3) introduction of selected
low carbon technologies to replace conventional ones, primarily in the industrial sector.
The entries in the last column are negative as they correspond to reductions in carbon emissions
resulting from the increased use of natural gas in power plants as a result of the $50/tonne carbon permit
price in this scenario.
The major observations from the above table are:
8.3
DRAFT
6/10/97
In the BAU case, carbon emissions are forecast to increase by approximately 380 million
metric tons (MtC) (from 1340 to 1720, or 28%) between 1990 and 2010.
The energy efficiency gains incorporated in the "efficiency" case cut overall growth
between 1990 and 2010 by one third (from 380 to 260 million metric tons). This
represents carbon increases of 19% above the emissions in 1990.
The energy efficiency improvements spurred by the "high efficiency" case reduce overall
growth between 1990 and 2010 by an additional 60 MtC (decreasing the increase from
380 to 200 million metric tons or 15% above the emissions in 1990).
The conversion of electrical generation from coal to natural gas and the preferential
dispatch, combined with the use of added low carbon technologies, primarily in the
industrial sector, reduce carbon emissions by an additional 150 to 200 MtC. In this
case, which we estimate to cost less than $50/tonne of carbon (for the additional 150 to
200 MtC), results in approximate carbon stabilization in 2010 at the 1990 level (0 to 30
MtC increase).
Approximately 140 MtC of the increase in carbon emissions between 1990 and 2010 will
have occurred by the end of 1997; thus, it is useful to look at the 13-year forecast
starting with 1997. The carbon reductions incorporated in the efficiency case cut the
overall growth in carbon emissions between 1997 and 2010 from 240 million tons (as
forecast in the BAU case) to 120. The "high efficiency/low carbon" scenario reduces
carbon emissions in 2010 to about 115 MtC (90 to 140 MtC) below the 1997 level.
Table 8.3 provides a comparison of the growth rate in energy and in carbon emissions for the
three cases, from 1990 to 2010. In general, the growth in carbon emissions tracks the increase in
energy demand, with carbon growing slightly more rapidly than energy in the efficiency case.
This is because the efficiency scenario reduces the need for constructing new low-carbon
(combustion turbine and natural gas combined cycle) power plants and therefore results in a
generation mix that has a higher percentage of coal-based electricity than would be true with the
"business-as-usual" case. In all three scenarios, carbon emissions increase more slowly than the
GDP, indicating a net "decarbonization" of the U.S. economy.
Table 8.3 Average Annual Energy and Carbon Growth Rates, 1990 to 2010,
for Three Cases
Revised AEO
Efficiency
High Efficiency/
Reference Case
Case
Low Carbon Case
Energy Demand
1.14%
0.80%
0.52%
Carbon Emissions
1.24%
0.88%
0 to 0.2%
Energy Consumption
-0.74%
-1.08%
-1.35%
Per GDP (E/GDP)
Carbon Emissions Per
-0.64%
-1.00%
-1.7 to -1.9%%
GDP (C/GDP)
*Note that these changes in carbon emissions are for the entire period, including the seven years
that have already occurred. The carbon decrease per unit GDP growth for 1997 to 2010 is 0.7, 1.25,
and 2.3 to 2.5 percent per year for the reference, efficiency, and high efficiency cases, respectively.
8.4
DRAFT
6/10/97
It is useful to compare the scenarios in this study to those of other studies. The 1991 report by
the Office of Technology Assessment (OTA) titled Changing by Degrees (U.S. Congress, 1991)
analyzed the potential for energy efficiency to reduce carbon emissions by the year 2015,
starting with the base year of 1987. Its "moderate" scenario results in a 15% rise in carbon
emissions, from 1300 MtC/year of carbon in 1987 to 1500 MtC/year of carbon in 2015
(compared to a "business-as-usual" forecast of 1900 MtC/year). Its "tough" scenario results in
a 20% to 35% emissions reduction relative to 1987 levels, or emissions levels of 0.85 to 1.0
MtC/year of carbon in 2015. Our "efficiency" and "high efficiency/low carbon" cases of 1.3 to
1.6 billion metric tons of carbon emissions in 2010 is comparable to OTA's "moderate" case
and shows considerably higher emissions than OTA's "tough" case.
Another benchmark is provided by the 1992 National Academy of Sciences (NAS) report on
Policy Implications of Greenhouse Warming (National Academy of Sciences, 1992). This study
identified a set of energy conservation technologies that had either a positive economic return or
that had a cost of less than $2.50 per tonne of carbon. Altogether, NAS concluded that these
technologies offer the potential to reduce carbon emissions by 463 million tons, with more than
half of these reductions arising from cost-effective investments in building energy efficiency.
Our "efficiency" and "high efficiency/low carbon" cases suggest the potential for reducing
carbon emissions by between 120 and 380 million metric tons by the year 2010. This is about
one-fourth to one-third of the potential estimated by the NAS. One of the reasons for this
difference is that the NAS study did not deal with a particular planning horizon. Thus, it did
not take into account the replacement rates for equipment and processes, and other factors that
prevent the instantaneous, full market penetration of cost-effective energy-efficient technologies.
8.1.2 Sector-Specific Findings
The analysis of the buildings sector offers the following conclusions.
The "efficiency" scenario results in 1.9 quads (5.3%) less energy use and 25 Mt (4.4%)
fewer carbon emissions than the "business-as-usual" scenario in 2010. This represents a
savings of $17 billion in fuel costs in 2010 resulting from an annualized incremental cost
of $6 billion in efficiency improvements.
The "high efficiency/low carbon" scenario results in 4.0 quads (11.1%) less energy use
and 39 Mt (6.8%) fewer carbon emissions than the "business-as-usual" scenario in 2010.
These carbon savings increase to 46 Mt (or 8%) when fuel cells are included. This
represents a savings of $31 billion in fuel costs in 2010 resulting from an annualized
incremental cost of $11 billion in efficiency improvements.
In the residential sector, the greatest energy and carbon savings are achieved in the
following end uses: miscellaneous electricity uses, lighting, and water heating. In the
commercial sector, the greatest energy and carbon savings are achieved in the following
end uses: miscellaneous electricity uses, lighting, and space conditioning.
For both residential and commercial buildings, the bulk of the energy saved is electricity
(including related losses): 1.6 of the 1.9 quads in the "efficiency" scenario and 3.4 of the
4.0 quads in the "high efficiency/low carbon" scenario.
The analysis of the industrial sector leads to the following conclusions.
8.5
DRAFT
6/10/97
The "efficiency" scenario results in 2.0 quads (5.4%) less energy use and 22 Mt (4.1%)
fewer carbon emissions than the "business-as-usual" scenario in 2010. This represents a
net present value of fuel savings of $5.2 billion in fuel costs in 2010 resulting from an
incremental annual investment of $2.1 billion in efficiency improvements. Thus, this
scenario generates a net benfit of $3.1 billion in 2010.
The "high efficiency/low carbon" scenario results in 2.5 quads (6.7%) less energy use
and between 57 and 73Mt (or between 5 and 10%) fewer carbon emissions than the
"business-as-usual" scenario in 2010. This represents a net present value of fuel savings
of $9.4 billion in 2010 resulting from an incremental investment of $4.1 billion in
efficiency improvements. Thus, this scenario generates a net benefit of $5.3 billion in
2010. The annual incremental investment required for this scenario is only 3.7% greater
than normal manufacturing investment levels.
The efficiency scenarios indicate that, on a percentage basis, more energy savings can be
achieved in light manufacturing than in the energy-intensive industries.
The energy saved by the "high efficiency/low carbon" scenario is almost equally
distributed between fossil fuels and electricity (including related losses). This represents
a much greater percentage reduction in electricity use, since in 1997 the industrial sector
consumed almost twice as much in fossil fuels as electricity.
The analysis of the transportation sector offers the following conclusions.
The "efficiency" scenario results in 3.1 quads (10%) less energy use and 73 Mt (12%)
fewer carbon emissions than the "business-as-usual" scenario in 2010. For light-duty
highway vehicles (passenger cars and light trucks), this represents a savings of $19
billion in fuel costs to consumers in the year 2010. The total incremental retail price for
these fuel economy improvements to light-duty vehicles is $28 billion.
The "high efficiency/low carbon" scenario results in 4.5 quads (14%) less energy use and
103 Mt (17%) fewer carbon emissions than the "business-as-usual" scenario in 2010.
The incremental costs associated with the breakthrough technologies that are included in
this scenario cannot be quantified, but the fuel savings from light-duty highway vehicles
are estimated to be $-- billion in 2010.
Most of the reduction in energy use and carbon emissions comes from light-duty vehicles.
New light-truck fuel economy improves the most in the efficiency scenarios by 2010,
with passenger car fuel economy improving almost as much.
Both efficiency scenarios forecast the consumption of significant amounts of ethanol
from cellulosic feedstocks (as opposed to corn), as a blending component for motor
gasoline. By 2010, 0.46 quads of cellulosic ethanol are forecast in the "efficiency" case
and 0.65 quads are forecast in the "high efficiency/low carbon" case.
Several key findings also result from the analysis of the electricity sector's response to end-use
efficiencies and carbon charge.
The revised reference case for the U.S. electric-power-supply system in 2010, which was
conducted to assess the impact of a fully competitive industry, resulted in several small
differences relative to the AEO '97 reference case: greater electricity use, lower peak
demand, and a generation mix that includes more natural gas and less coal. Thus,
although consumption is higher, carbon emissions are lower. Comparable reductions in
8.6
DRAFT
6/10/97
the retail price of electricity were forecast by AEO '97 and the simulation of a fully
competitive industry conducted for this study.
The "efficiency scenario" reduces the need for constructing new low-carbon (combustion
turbine and natural gas combined cycle) power plants. The result is a generation mix
that has a higher percentage of coal-based electricity than would be true with the
"business-as-usual" case. As a result, the "efficiency" scenario's 7.0% reduction in
electricity use in 2010 represents only a 4.0% reduction in carbon emissions.
The "high efficiency/low carbon" scenario's 14.5% reduction in electricity use in 2010
represents a 18.4% reduction in carbon emissions, because the introduction of a carbon
charge lowers the carbon intensity of the generation mix.
Finally, the analysis of improved electricity supply technologies concluded the following.
The analysis of advanced coal technologies suggests that between now and the year
2010, highly efficient advanced coal units remain too expensive to compete economically
with either the generation mix that remains from the 1990s or with natural gas combined
cycle units.
8.2 R&D'S POTENTIAL FOR FURTHER BENEFITS BY 2020
By the year 2010, numerous energy efficiency technologies will be introduced into the
marketplace that are not available to consumers today. With an aggressive R&D and market
transformation push, our "high efficiency/low carbon" scenario suggests that these new
technologies, in combination with the greater deployment of existing cost-effective efficiency
products and practices, would result in significant energy and carbon savings in 2010. The
"high efficiency/low carbon" scenario would also produce an R&D pipeline containing the next
generation of energy technologies. It is difficult to estimate the energy and carbon savings that
will accrue from the maturation and commercialization of these technologies by the year 2020.
However, this report does qualitatively characterize the nature of these technologies, and the
results suggest that an aggressive pace of energy and carbon savings over the next quarter
century can be sustained.
In the next quarter century, improved energy efficiency technologies will result from a
combination of incremental advances and fundamental breakthroughs. Incremental
improvements in all sectors can be achieved by the greater reliance on more precise and reliable
sensors and controls integrated into smaller packages that cost less, can withstand harsh
environments, and are able to characterize and optimize currently impenetrable systems
without disturbance. Advanced manufacturing technologies including rapid prototyping and
ultraprecision fabrication also offer broad opportunities for continuous incremental
improvements in energy efficiency and renewable energy. Breakthroughs in bioprocessing,
separations, superconductivity, catalysts, and materials can have wide-ranging impacts on
energy efficiency by the year 2020. Examples of specific technology opportunities are described
below, by sector.
Six R&D areas are forecast to offer great promise to reduce significantly the energy requirements
of our Nation's buildings in 2020.
Construction methods in this time frame will consist primarily of factory-manufactured
modules and components assembled onsite, enabling systems engineering to deliver
8.7
DRAFT
6/10/97
greater energy efficiency, more affordable construction, and increased use of recycled
materials.
Adaptive envelopes will capitalize on changing climatic conditions to reduce energy use
and improve occupant comfort and productivity, and environmental integration strategies
such as reflective roofing materials and turf paving will reduce urban heat island effects.
Multi-functional equipment and appliances offer the opportunity for a quantum leap in
efficiency improvements by combining the functions of several appliances into a single,
highly effective device that puts to use waste heat and employs high efficiency
components to perform dual functions.
Advanced lighting systems in 2020 have the potential to employ highly efficient artificial
light sources in combination with tracking sunlight concentrators, light pipes, and
daylighting to meet the occupants' precise functional needs for lighting with an order-of-
magnitude reduction in energy use.
Controls and communications capabilities will enable greatly reduced energy requirements
by matching current and predicted weather conditions, utility rates, and internal
environmental measurements to meet fluctuating occupant requirements while expending
less energy.
Finally, self-powered buildings will have fuel cells, PV building components, and energy
storage devices to provide building owners with new levels of flexibility in meeting their
energy needs and generating revenues from electricity sales.
Improvements in energy efficiency and carbon reductions in industry beyond 2010 require
further R&D to spawn new and improved technologies. In addition to the broad application of
better process modeling, sensors, and controls mentioned above, some process/industry-
specific examples include the following.
In the pulp and paper industry, there is tremendous opportunity to better exploit energy
sources contained in the biomass that provides the fiber, and to achieve a better balance
between heat and power needs. For example, the black liquor gasification combined
cycle process and biomass gasification combined cycle technologies could produce
significant quantities of low-carbon electricity, and the further development of
polyoxometalate bleaching could reduce the electricity consumed by pulp bleaching, in
addition to reducing effluent loads.
In the chemical industry, biological processes for producing feedstocks, improved
catalysts, and thermochemical processes for producing valuable chemicals from a wide
variety of recycled materials are examples of energy-saving opportunities that hold great
promise.
In petroleum refining, improved catalyst technology for hydroprocessing, catalytic
cracking, and alkylation will be needed to offset the push towards higher energy use that
will otherwise result from changing input feedstocks required by stricter environmental
objectives.
Optimizing electric boost, improving furnace design and operation, and recovering and
reusing waste heat from oxy-fired furnaces represent three of many promising technology
development opportunities for reducing energy intensities in the glass industry.
In the aluminum industry, dramatic reductions in energy and emissions could result from
new and improved smelting technologies and reduction efficiency, including: inert
anodes, carbothermic reduction processes, aluminum chloride processes, and wettable
titanium diboride cathode components.
The iron and steel industry could achieve significant energy savings by incorporating both
ironmaking and steelmaking into a single system with thin strip casting as a final
product, adding a coal-based reductant process that simultaneously produces power,
and using sensors and controls to optimize process efficiencies.
8.8
DRAFT
6/10/97
In the metal casting industry, energy can be saved by making fundamental changes in the
casting process, for example, by using electromagnetic fields to induce eddy currents in
liquid metals to assist with stirring and confinement into thin sheets.
Many of the advanced technologies that have the potential to significantly improve the energy
efficiency of transportation after 2010 need considerable R&D investment before they can
become commercially available in the year 2020.
To achieve fuel economies in the 60-80 mpg range and remain affordable and safe, light-
duty vehicles will need breakthroughs in manufacturing processes for composite
materials, an order of magnitude reduction in fuel cell costs, ultra-low rolling resistance
tires, high efficiency accessories, and highly aerodynamic designs.
Heavy vehicles in 2020 can achieve improved on-road fuel economy through the
development of a high-efficiency, low emission diesel cycle engine with a durable highly
efficient, lean NOₓ catalyst, reduced aerodynamic drag, low rolling resistance tires, and
lightweight material such as magnesium.
Methanol-fueled fuel cell busses will require significant development of the fuel cell itself,
power management strategies, and hydrogen fuel production to enable economical
solutions by the year 2020.
Locomotive engines may be an ideal test bed and early entry for fuel cell powerplant
technologies between 2010 and 2020.
With a vigorous and sustained program of research, development and deployment, renewable
energy technologies could be providing a greater and rapidly growing contribution to electricity
generation by the year 2020.
Hydroelectric power generation may be increased by modernizing and upgrading turbines
at existing sites and by developing efficient low-head generating technologies to enable
deployment at the many low-head sites that are otherwise unsuitable for hydropower
additions.
Wind power systems can become more cost-competitive as the result of improved blade
designs and manufacturing processes, new materials for extended blade lifetimes in their
working environment of large and variable mechanical stresses, and computer modeling
of components and subsystems to optimize turbine designs for site-specific operating
conditions.
Expanding biomass power generation to meet carbon reduction goals is contingent on
developing dedicated biomass fuel crops and improving the technologies for converting
biomass energy to electricity including advanced turbine designs and heat-recovery
steam generators.
Photovoltaic power systems could achieve significant cost savings by improving the
efficiency of the PV modules and lowering the cost of balance of systems components
(including wires, mounting structures, power conditioners, and trácking systems),
especially from the development of more-efficient energy storage devices
The technology opportunities envisioned for the year 2020 will not materialize without stong
public-private partnerships to support the array of R&D and market transformation activities
needed to ensure that cost-effective products and practices are available and deployed.
8.9
DRAFT
6/10/97
8.3 ASSESSMENT OF COSTS AND SOURCES OF CARBON REDUCTIONS
The "business-as-usual" scenario projects an increase of 380 million tonnes/year of carbon
between 1990 and 2010. In our efficiency case, in which the nation actively pursues policies
and programs to promote market acceptance of energy efficiency while expanding commitments
to research and development, energy-efficient technologies reduce this growth in carbon
emissions by 120 MtC/year. A very strongly accelerated drive to promote energy efficiency
could lead to reductions of 180 MtC/year (high efficiency case). Under a carbon cap and
trading system, in which permits for carbon sell for $50/tonne C, very substantial carbon
reductions appear possible. Results for these three cases, showing the sources of the carbon
reductions, are contained in Table 8.4. The indicate that, for the high efficiency/low carbon
case, there is a potential to roughly return to 1990 levels of carbon emissions in 2010 at a cost of
less than $50/tonne carbon.
Table 8.4 Potential Reductions in Carbon Emissions to Achieve 1990 Levels in 2010,
(Reductions are in MtC/Year from Business of Usual Case)
High Efficiency
High
Efficiency
Case (w/o Low
Efficiency/Low
Case
Carbon Technology)
Carbon Case:
Buildings
Energy Efficiency
25
39
39
Fuel Cells
0
2 -7
Industry
Energy Efficiency
22
40
40
Advanced Turbine Systems
0
5 -17
Aluminum Technologies
0
2- 4
Biomass Gasification
0
2 10
Cement
0
2
Transportation
Energy Efficiency & Ethanol
73
103
103
Utility Supply Options
Carbon-Ordered Dispatching
0
77
Converting coal-based power
0
50 a
plants to natural gas
Cofiring coal with biomass
0
5 20
Extending the life of existing
0
2 - 5
nuclear plants
Hydropower expansions
0
4 - 5
Total (rounded)
120
180
330 - 380
"The potential for converting coal-based power plants to natural gas is much greater than 50 MtC/year, as described in chapter 7.
However, the cost-effectiveness of the conversion is highly sensitive to the magnitude of the coal permit charge, the externality
value of NOx, and, and the relative price of natural gas and coal. If natural gas prices are, for example, $10/tonne C higher (lower)
than anticipated in the report, then a $60 ($40)/tonne C permit price would be needed to achieve 50MtC.year reductions.
Because the cost curve of carbon from this source is relatively flat, it may be possible to significant increase the carbon reductions
subject to availability of natural gas.
Note: the results in this table are undergoing review at this time. As a result, there may be some changes in numbers. We do not,
however, anticipate major changes.
8.10
DRAFT
6/10/97
It is important to recognize that there are significant uncertainties in the analysis and many
factors that will determine the degree to which and the costs of achieving the carbon reductions
shown in Table 8.4. We present below a summary of the expected technology costs in 2010, as
well as the cost of implementing a carbon permit system. While these costs are necessarily
uncertain, they are our best estimates and, in our view, as likely to be high as to be low. We
note, however, that we have confined our analysis to technology costs, and have not assessed
policies or programs to achieve market acceptance.
Emissions reductions of 120 to 180 of the 380 MtC needed to achieve stabilization in 2010
result from energy efficiency measures which, based on the data presented in the report, are on
balance cost-effective. Ignoring the implementation costs, this means that the cost of reducing
carbon emissions are negative overall. Unless there are serious difficulties in implementing the
measures, the costs of 120 MtC/year will be close to zero. The next 60 MtC/year - which
includes substantially increased implementation of energy efficiency measures for buildings
(from 35% of potential cost-effective measures to 65%), increases in ethanol as automotive fuel
and the use of more advanced (and costly) energy efficiency technologies for transportation,
and both reductions in hurdle rates as well as market lags for industry - will have a very low
cost. As indicated in the individual sector discussions, the technology for the high efficiency
case is for the most part likely to be cost-effective or near cost-effective in 2010 but there is
somewhat more uncertainty about the ability to achieve market acceptance.
The utility sector provides a substantial part of the next increment of carbon reductions: 125
MtC/year are achieved through increased costs associated with the dispatch of higher-cost
electricity (using natural gas power plants in place of coal plants up to a cost of $50/tonne
carbon) and through repowering existing coal-fired power plants so that they burn natural gas
(again, up to a cost of $50/tonne carbon). Because the new dispatch and the power plant
conversions are up to $50/tonne, a portion of the carbon reductions will be at less than this
cost. The upper limit on these costs is thus $50/tonne times 125 MtC/year = $6 billion per
year.
In addition, one needs to note that these measures increase demand for natural gas. The
demand for natural gas in the AEO '97 business as usual case for 2010 is 30.2 trillion cubic feet
(Tcf). Our base case, which simulates a restructured utility industry, increases use of combined
cycle power plants compared with AEO '97 by 1.3 Tcf per year in 2010. However, the
efficiency case decreases natural gas use by 0.9 Tcf/year compared with AEO '97. This occurs
because efficiency measures reduce demand for natural gas, as expected. Interestingly, the
altered dispatch, when combined with efficiency measures in the high efficiency case, also
reduces demand for natural gas by 0.9 Tcf/year compared with AEO '97. This occurs because
of two countervailing factors that happen to balance in this case: (1) increased energy efficiency
and further substitution of combined cycle gas plants for combustion turbines reduces natural
gas demand while (2) substitution of additional natural gas for coal in the generation mix
increases demand.
The roughly 50 MtC/year from repowering increases natural gas demand by 1.7 Tcf/year. This
means that the high efficiency/low carbon case uses about 0.8 Tcf/year more natural gas than
the AEO '97 (and 0.5 Tcf per year less than a restructured utility industry base case as we have
estimated it). This is less than a 3% increase in natural gas demand. EIA model runs indicate
that such an increase in natural gas demand would be expected to increase natural gas costs
from $0.15 0.20/million cubic feet (Mcf). This price increase has a small economic impact.
Finally, we obtain about 25 to 75 MtC/year from a variety of technologies: advanced turbine
systems for cogeneration in industry, co-firing biomass and coal to produce electricity, fuel cells
for buildings, low carbon technologies for cement making, biomass gasification, and advanced
8.11
DRAFT
6/10/97
aluminum and cement production technologies as well as nuclear plant life extensions and
expansion of hydropower. The text estimates that up to 75 MtC/year of carbon reductions
could be achieved at less than $50/tonne carbon. If these estimates are borne out, then the
upper limit of these costs is $4B/year in 2010 (since many of the technologies are estimated to
produce savings below $50/tonne carbon).
In short, the analysis suggests that the overall additional cost of the measures in the high
efficiency/low carbon scenario are on the order of $10B per year in 2010. To the extent that the
energy efficiency measures cost less than new supply, the net cost of the stabilization case is
reduced. On the other hand, implementation costs of energy efficiency and the other
requirements to achieve rapid and widespread market acceptance of technologies will raise the
cost of the scenarios, as discussed below
The realizability of the cases depends on many factors. In all cases, carbon reductions require
the Nation to embark on an aggressive set of policies and programs, presumably in response to
an international agreement on climate change or other events that result in a national
determination to reduce growth of carbon emissions. In the case studied, we assume that an
international trading regime for carbon has resulted in a domestic permit price of $50/tonne
carbon. Without some scheme that provides an incentive of this nature for switching from coal
to natural gas, and for deploying other low carbon technologies, much of the carbon reductions
in our case would not be possible.
Government policies and programs that encourage and/or require the adoption of energy
efficiency technologies will be needed. Incentives will be needed for industry to increase energy
efficiency investment. Additional private and public investments in energy efficiency and low
carbon technology is necessary, not only to get some new technology into the market before 2010
but especially to have technology for the period after 2010. The transportation sector is
especially dependent on early technological advances to achieve the scenario results in 2010.
There is no assurance that these and other driving forces will cause the scenarios we have
described to take place. Our major conclusion is that the technology is available, at a cost that
appears to be $10 B per year or less, to achieve major reductions in carbon emissions by 2010.
Efficiency alone can get us 30 to 50 % of the way to 1990 levels (from our expected base case
results) at negative or low technology costs. An important new finding is that a detailed
analysis of the utility sector shows two significant ways that an additional 30% of the
reductions at an estimated cost of $50/tonne carbon': carbon-based dispatch and conversion of
existing power plants from coal to natural gas. Finally, we identify additional technologies that
could contribute up to 20% of the carbon reductions, also at a cost of up to $50/tonne. In
addition, a next generation of advanced energy efficiency and renewable energy technologies
promises to enable the continuation of an aggressive pace of energy and carbon reductions over
the next quarter century.
8.4 REFERENCES
Energy Information Administration. 1996. Emissions of Greenhouse Gases in the United States,
1995, DOE/EIA-0573(95) (Washington, DC: U.S. Department of Energy), October.
1 The cost curve for repowering is relatively flat; as such, considerable additional reductions are
possible at a cost new too different from $50/tonne. The results are highly sensitive to the price
differential between coal and natural gas; at a lower (higher) price differential, a higher (lower)
permit price of carbon is needed.
8.12
DRAFT
6/10/97
National Academy of Sciences. 1992. Policy Implications of Greenhouse Warming: Mitigation,
Adaptation, and the Science Base (Washington, DC: National Academy Press).
U.S. Congress, Office of Technology Assessment. 1991. Changing by Degrees: Steps to Reduce
Greenhouse Gases, OTA-0-482 (Washington, DC: U.S. Government Printing Office) February.
U.S. Department of Energy. 1995. Energy Conservation Trends, DOE/PO-0034 (Washington,
DC: U.S. Department of Energy, Office of Policy), April.
8.13
Interlab Study on U.S.
Energy Efficiency and Greenhouse
Gas Emissions
Appendix C-1
Detailed Description of
Forecast Methodology
Residential and Commercial
Sectors
APPENDIX C-1: METHODOLOGY FOR ASSESSING END-USE
EFFICIENCY POTENTIALS FOR BUILDINGS
Analysis focuses on three years: 1990, 1997, and 2010. We derive baseline usage in 1990
from the 1994 Annual Energy Outlook (AEO)¹. We treat 1997 as the base year, and 2010 as
the year in which we are assessing the reservoir of potential savings. We examine a
"snapshot" of the buildings sector in 2010, with our end-use totals benchmarked to the AEO
1997 forecast for that year. All energy use is expressed in primary energy terms². For a
more detailed discussion of the type of analysis described below, see Krause et al. (1995)3.
We discuss each of the input parameters below, and then carry through a particular example,
namely residential refrigerators (all information pertaining to the example is in italics). Tables
C-2.5.a-b and C-2.6.a-b show the input tables containing each of the relevant parameters for
residential and commercial buildings. The end-use categories in these tables are the same as
those in NEMS, for consistency with the AEO.
Base year energy use
The calculations begin with the 1997 total energy use for the end-use or subsector. The
Annual Energy Outlook 1997 is the basis for this base-year breakdown.
For refrigerators, 1997 base year electricity use is 1.21 quads of primary energy (112 TWh).
Stock accounting
In any forecast of the future impacts of technologies, some method for accounting for
changes in the stock of equipment must be adopted. Stock accounting allows calculation of
the effect of normal stock turnover on the efficiency of the stock of equipment existing in any
year. It also accounts for overall growth in the total number of households or floorstock.
We use a simplified stock accounting framework to treat retirements of buildings and
appliances existing in 1997 still existing in 2010. We assume that retirements occur in a
linear fashion so that by the time 4/3 of the average lifetime elapses all of the buildings or
devices retire. Devices added during the 1997 to 2010 period are assumed not to retire or to
be replaced with devices identical to the devices previously added during this period.
For residential building shells, we use a 100 year average lifetime assumption, which results
in about 90% of the stock of buildings existing in 1997 still existing in 2010. AEO 97
¹The 1997 AEO starts its forecast in 1994 and does not present 1990.
2The primary energy conversion factor for electricity is 3.25 in 1990 (from AEO 94), 3.18 in 1997, and
3.07 in 2010 (from AEO 96), which includes losses associated with the generation, transmission, and
distribution of electricity. This factor is multiplied by site electricity use (any units) to get primary energy
in comparable units. As a simplifying assumption, we adopt a factor of 3.17 (10,800 Btu/kWh) as an
average over the analysis period (1997-2010), but when calculating primary energy use in 1990, we use the
actual factor of 3.25. All electricity consumption numbers are expressed in primary energy terms
throughout this analysis. THIS CONVENTION HAS BEEN MODIFIED AS DISCUSSED IN CH. 3,
BUT THIS APPENDIX HAS NOT YET BEEN UPDATED TO REFLECT OUR NEW APPROACH.
3 Krause, Florentin, David Olivier, and Jonathan Koomey. 1995. Negawatt Power: The Cost and Potential
of Low-Carbon Resource Options in Western Europe in Energy Policy in the Greenhouse, Vol. El
Cerrito, CA: International Project for Sustainable Energy Paths.
projects about a 15% growth in households from 1997 to 2010, so total stock in 2010 is
115% expressed as a percentage of 1997 stock. Of this total, 25 percentage points represent
homes built in the 1997 to 2010 period, and 90 percentage points represent homes existing in
1997 still existing in 2010.
For commercial building shells, we use a 50 year average lifetime assumption, which results
in about 81% of the stock of buildings existing in 1997 still existing in 2010. AEO 97
projects about a 12% growth in commercial floor area from 1997 to 2010, so total stock in
2010 is 112% expressed as a percentage of 1997 stock. Of this total, 31 percentage points
represent buildings built in the 1997 to 2010 period, and 81 percentage points represent
buildings existing in 1997 still existing in 2010.
In the frozen efficiency case, all homes and buildings built in the 1997 to 2010 period are
assumed to have equipment with efficiencies equivalent to 1997 new equipment. For homes
and buildings existing in 1997 still existing in 2010, retirements of equipment take place
using the same retirement function as described above for homes (retirements occur in a
linear fashion so that by the time 4/3 of the average lifetime elapses all of the devices retire).
In Tables C-2.5.a-b and C-2.6.a-b we split the stock of existing homes and buildings with
new equipment into two categories: Existing shell and retrofit shell. This distinction is not
used in the Frozen Efficiency and Business-As-Usual cases, but is used in the efficiency
cases.
Average refrigerator lifetimes are 19 years. By 2010, 9.7% of the homes existing in 1997
still existing in 2010 have been replaced with new homes that have new refrigerators, 48.7%
still have 1997 stock refrigerators, and 41.6% have their existing shell but have new
refrigerators. No retrofits of equipment are allowed
Other changes in service demand
Overall growth in service demand is governed by the growth in number of households or
floorstock, but within each sector other trends can affect service demand. These trends, such
as fuel switching, structural shifts, leveling off of service demand, or rapid growth in a new
end-use, can be captured by the use of another factor, which we call here the "other energy
service growth" factor. It can be equal to, more, or less than 1.0. Its value will generally be
determined by an examination of the trends in the end-use markets under analysis.
We use this factor to calibrate our forecast to the AEO 97 end-use consumption numbers in
2010. We calculate our own forecast of end-use consumption based on our stock accounting
framework and the unit energy consumption numbers described below, then take the ratio of
the AEO 97 end-use consumption to our forecast. A ratio less than 1.0 means that our
internally generated forecast overestimates consumption compared to the AEO 97 forecast,
and a ratio greater than 1.0 means our internally generated forecast underestimates
consumption.
In Tables C-2.5.a-b and C-2.6.a-b we distinguish between the service demand growth factor
for existing shells and new shells, but there is no difference between these two columns. We
can change these factors if we feel that growth in service demand will be different in existing
and new buildings, but we have not used this capability in this analysis.
Our internally generated refrigeration forecast overestimates consumption compared to the
AEO 97 forecast, so the service demand growth factor is 0.84. We believe this result occurs
because the AEO reference case forecast contains progress in refrigerator efficiency that our
own residential models do not predict. We are working with EIA to fix this issue with their
forecast.
Frozen efficiency case: Existing stock vs. new energy intensities
The ratio of new device or process intensities (kWh/device or per household) to base year
stock intensities (usually, but not always, less than 1.0) characterizes the efficiency
improvement that we can expect from stock turnover alone in a frozen efficiency case.
For new refrigerators in 1997, Unit Energy Consumption (UEC) is about 647 kWh/year (7.0
MMBtu primary), while stock devices in 1997 are at about 944 kWh/year (10.2
MMBtu/year). The ratio of new to stock is therefore 0.69.
Business-as-Usual case: Existing stock VS. new energy intensities
The ratio of expected average new device or process intensities over the 1997-2010 period
(kWh/device or per household) to base year stock intensities (usually, but not always, less
than 1.0) characterizes the efficiency improvement that we can expect from stock turnover
alone in the Business-as-Usual case.
We expect about a 5% improvement in refrigerator efficiency relative to new equipment in
1997, averaged over the 1997 to 2010 period. For new refrigerators, the expected average
UEC over the 1997 to 2010 period is therefore 647*0.95 = 615 kWh/year (6.7
MMBtu/year), while stock devices in 1997 are at 944 kWh/year (10.2 MMBtu/year). The
ratio of new to stock is therefore 0.65.
Frozen efficiency case energy use
To determine the frozen efficiency energy use in 2010, we use the following formula:
E use in Froz. Eff. Case 2010 = E use in 1997 stock remaining factor + E use in
1997 (stock replacement factor + stock growth factor)
*
new device intensity 1997
stock device intensity 1997
(1)
If the Trends in service demand factor is applicable, it may either be multiplied by the entire
frozen efficiency energy use (in the case where all households are affected by the trends
embodied in this factor) or by either the stock component or the new component terms. We
apply it to both the stock and new components in this analysis.
For refrigerators, this formula yields
E use in Froz. Eff. Case 2010 = 0.84 * (1.21 quads * 0.487 + 1.21 quads * (0.416 + 0.25)
* 647 944 )
= 0.95 quads
Business-as-usual case energy use
To determine the Business-as-usual case energy use in 2010, we use the following formula:
Energy use in B.A.U case 2010 = E use in 1997* stock remaining factor +
E use in 1997* (stock replacement factor + stock growth factor) *
The Cost of Energy Services, in billions of 1995 dollars per year in 2010, is calculated as
follows:
Cost of Energy Services=(E)XP/)+(ESXCCE) (5)
where
EAf = Energy use for end-use A using fuel f in any scenario (Quadrillion Btu of primary
energy per year in 2010).
Pf = price of fuel f (electricity, natural gas, or oil), in 1995$/MMBtu primary,
CCE = Cost of Conserved Energy (1995$/MMBtu primary),
ES = Energy Savings (quads of primary energy per year).
and the other parameters are as described above.
Whenever the CCE is greater than the fuel price, the cost of energy services will increase
compared to the B.A.U. case because of the efficiency measure. Whenever the CCE is less
than the fuel price, the cost of energy services will be less than that in. the B.A.U. case. In
the latter case, carbon reductions can be achieved at negative net cost to society.
Discount rate
We used 7% real as the discount rate. The long term average return on investment for the
utility industry is about 6% real, and the typical rates for auto loans or business loans are
also in this range.
Cost of conserved energy (CCE)
CCE is calculated using the following equation:
d
Capital Cost X
(1-(1+d)-n)
CCE (e/kWh)
(4)
Annual Energy Savings
where d is the discount rate and n is the lifetime of the conservation measure. The
numerator in the right hand side of Equation 1 is the annualized cost of the conservation
investment. Dividing annualized cost by annual energy savings yields the CCE.
Our life-cycle cost analysis for residential refrigerators results in a CCE of $3.13/MMBtu
primary ($0.033/kWh) to achieve the maximum cost effective savings level (in 1995 $).
Fuel and electricity prices
Fuel and electricity price forecasts are taken from the AEO 1997 reference case for 2010.
Conversion to carbon emissions
Emissions factors for fuels do not, of course, change over time or as a function of demand.
These factors are taken from the EIA's recent work on this subject.4
Electricity carbon emissions per kWh for the Business-As-Usual case are based on the
electricity sector analysis, and are multiplied by B.A.U. electricity demand to get total
emissions. The emissions savings are calculated using an estimate of the marginal carbon
savings per kWh derived by running the electricity sector model using a demand level 10%
below that for the Business-As-Usual case in 2010, and calculating the change in emissions
per kWh saved. We multiply this marginal carbon emissions factor by the electricity saved
in the efficiency scenarios, and subtract these saved emissions from the B.A.U. emissions.
In the final version of the report, we will run the electricity sector model using the actual
demand levels from the scenarios to more accurately calculate the emissions associated with
electricity savings.
Assessment of cost effectiveness
The total cost of energy services delivered in 2010 is a function of energy costs and
annualized incremental costs for efficiency improvements in that year.
Superscript(4)-S DOE. 1994. Emissions of Greenhouse Gases in the United States, 1987-1992. Energy Information
Administration, U.S. Department of Energy, Washington, DC. DOE/EIA-0573. October.
E use in Max. Cost Effective Efficiency Case 2010 = 0.84 * 1.21 quads 0.487 + 1.21
quads' 0.028* 647 944 * (1 0.33) + 1.21 quads * 0.388 647 944 * (1 0.33 0) + 1.21 quads *
0.249* 647 944 * - - )
= 0.80 quads primary energy.
The potential savings is therefore 0.95 - 0.80= 0.15 quads relative to the frozen efficiency
case and 0.93-0.80 = 0.13 quads relative to the Business-as-Usual case.
This calculation could just as easily be done relative to the Business-as-usual baseline, but the
absolute result will be the same. The choice of which baseline to use in calculating the
consumption in the high efficiency case is solely a question of computational convenience
and the availability of supply curve data.
Achievable fractions
In the real world, only some fraction of the potential savings can be achieved. We chose
implementation factors of 35%, 50%, and 65% after a review of program experience
(Brown 1993) and a judgemental assessment of how energy service markets would
respond to policies and programs associated with agressive commitments to reduce carbon
emissions. We began with the Brown's conclusion that about half of the techno-economic
potential could be captured given coordinated efforts on minimum efficiency standards,
utility programs, and information programs. Our choice of 35% and 65% brackets this
result. The lower number (efficiency case) matches Brown's most pessimistic sensitivity
case, while the higher number (high efficiency case) corresponds to aggressive
implementation of non-price policies combined with the assumption of a cap and trade
system for carbon and other economic signals that would support these aggressive efforts.
Brown did not address price signals in his report, so the most optimistic scenario he
considers reaches almost 60% of the maximum economic potential. We believe that the
addition of these price signals under an aggressive policy regime would push the achievable
efficiency level to 65%.
We apply these achievable fractions to the savings in the maximum cost effective case
relative to the B.A.U. case to determine the energy use in the cases where 35%, 50%, and
65% of the maximum cost effective efficiency improvement is assumed to be implemented.
In the 35% implementation case for residential, 35% of homes existing in 1997 still
existing in 2010 (i.e., 35% X 90% = 32% of 1997 stock) are assumed to be retrofit. In the
50 and 65% implementation cases, we increase the retrofit percentage to 43%, but do not
increase it further because we assume that only homes where the longest lived equipment
(i.e., a gas furnace) turn over are eligible for shell retrofits. This assumption ensures that
equipment replacement for expensive heating systems occurs at the same time as the
retrofits, and that retrofits do not result in premature retirements of expensive systems
(which are usually uneconomic).
In the 35% implementation case for commercial buildings, 35% of buildings existing in
1997 still existing in 2010 (i:e., 35% X 81% = 28% of 1997 stock) are assumed to be
retrofit. In the 50 and 65% implementation cases, we only increase the retrofit percentage
to 43% for the same reason we limited retrofits in the residential building stock.
expected average new device intensity 1997 to 2010
stock device intensity 1997
(2)
If the Trends in service demand factor is applicable, it may either be multiplied by the entire
Bus. as Usual efficiency energy use (in the case where all households are affected by the
trends embodied in this factor) or by either the stock component or the new component terms
separately. We apply it to both the stock and new components in this analysis.
For refrigerators, this formula yields
E use in B.A.U case 2010 = 0.84 * (1.21 quads * 0.487 + 1.21 quads * (0.416 + 0.25) *
615 944 )
= 0.93 quads
Maximum cost effective efficiency case energy use
To calculate the efficiency case, we add three additional factors to the equation above: a) a
savings factor for equipment relative to 1997 new equipment, b) a savings factor for retrofits
of existing shells (for space conditioning end-uses only) relative to 1997 stock shells, and c)
a savings factor for new shells (for space conditioning end-uses only) relative to 1997 new
shells. We assume that equipment is not retrofit, only replaced with new equipment. The
choice of the savings factors is justified in our detailed discussion of the applicable
technologies and their performance for each end-use. Because our conservation supply curve
analyses explicitly eliminate the effect of double counting for equipment and shell measures,
the savings factors for equipment and shells are additive.
With these modifications, Equation 1 above becomes
E use in Max. Cost Effective Efficiency Case 2010 = Other Energy Service growth factor *
(
E use in 1997 stock remaining factor +
E
use
in
1997*(stock
replacement
factor
[existing
shells])
new device intensity in existing homes 1997
*
stock device intensity 1997
(1- Svgs factor A) +
E
use
in
1997' (stock
replacement
factor
[retrofit
shells]
new device intensity in existing homes 1997
stock device intensity 1997
* (1- Svgs factor A Svgs factor B)
+
E use in 1997* (stock growth factor)
new device intensity in new homes 1997
*
stock device intensity 1997
(1- Svgs factor A - Svgs factor c))
(3)
Refrigerators are not affected by shell retrofits, so savings factors B and C are zero. For new
refrigerators, the minimum life-cycle cost technology yields a savings factor of 33%.
compared to new equipment in 1997.
Appendix C-2: Detailed Results Of
Residential And Commercial Sector Forecasts
Table Of Contents
1. Terminology and Conventions for Buildings Sector Spreadsheets
C-2.1
2. Table C-2.1 Main Results, Buildings Sector Scenarios
C-2.2
3. Table C-2.2 Main Results, Buildings Sector business-as-usual Scenario, by Fuel
C-2.3
4. Table C-2.3 Main Results, residential Sector business-as-usual Scenario, by End-Use
C-2.4
5. Table C-2.4 Main Results, commercial Sector business-as-usual Scenario, by End-Use
C-2.5
6. Table C-2.5a Input Assumptions for U.S. Residential Sector Reference and Efficiency Scenarios
C-2.6-7
7. Table C-2.5b Input Assumptions for U.S. Residential Sector Reference and
High Efficiency/Low Carbon Scenarios
C-2.8-9
e C-2.6a Input Assumptions for U.S. Residential Sector Reference and Efficiency Scenarios
C-2.10-11
9. Table C-2.6b Input Assumptions for U.S. Residential Sector Reference and
High Efficiency/Low Carbon Scenarios
C-2.12-13
14
10. Table C-2.7 Input Assumptions for U.S. Residential Sector Reference and Efficiency Scenarios
C-2.19-1
15
11. Table C-2.8 Energy use untouched by our scenarios, corrected for stock turnover
C-2.16
Interlab Study on U.S.
Energy Efficiency and Greenhouse
Gas Emissions
Appendix C-2
Detailed Results of
Residential and Commercial Sector
Forecasts
Table C-2.6.b: Input assumptions for U.S. commercial sector reference and high efficiency cases
65% implementation of efficiency resources
Other
Other
REFERENCE CASE (NO RETROFITS)
EFFICIENCY CASE
SHELL
Base
Existing
Existing
Retrofit
New
Energy
Energy
Existing
Existing
New
Existing
New
Ex DO retrofit Ex. whetroft New
Existing
Retrofit
New
EQUIPMENT
year
Existing
New
New
New
Service
Service
Existing
New
New
New
New
New
New
New
New
New
New
energy
growth
growth
expid avg
expid ave
shell
shell
Achievable
use
End-use
Stock
Stock
Stock
Stock
factor (1)
factor (1)
Intensity
Intensity
Intensity
Intensity
Intensity
rel. to new
savings
savings
CCP
COB
CCE
Praction
1997
lifetime
factor
factor
factor
factor
Ex. shells
New shells
kBta/sf
kBtu/sf
kBtu/sf
kBtw/sf
kBtu/sf
to 1997
factor
factor
S/MMBIs
$/MMBts
S/MMBts
Fuel
End-use
Quade
years
2010
2010
2010
2010
2010
2010
1997
1997
1997
1997-2010
1997-2010
2010
2010
2010
Electricity
Space heating
0.12
18
0.46
0.00
0.35
0.31
0.96
0.96
1.54
1.36
1.36
1.44
1.32
48%
0%
0%
4.11
4.11
4.11
0.65
Space cooling
0.52
18
0.46
0.00
0.35
0.31
0.96
0.96
5.99
5.38
5.38
5.32
5.21
48%
0%
0%
4.11
4.11
4.11
0.65
Water beating
0.17
9
0.00
0.46
0.35
0.31
1.24
1.24
2.32
1.60
1.60
1.38
1.38
20%
0%
0%
9.41
9.41
9.41
0.65
Ventilation
0.17
18
0.46
0.00
0.35
0.31
1.06
1.06
2.36
2.05
2.05
2.13
2.13
48%
0%
0%
4.11
4.11
4.11
0.65
Cooking
0.03
15
0.35
0.11
0.35
0.31
1.11
1.11
0.43
0.32
0.32
0.31
0.31
0%
0%
0%
N/A
N/A
N/A
0.65
Lighting
1.26
12
0.19
0.27
0.35
0.31
0.94
0.94
17.41
17.32
17.32
17.29
17.29
25%
0%
0%
-10.16
-10.16
-10.16
0.65
Refrigeration
0.14
15
0.35
0.11
0.35
0.31
0.96
0.96
1.99
2.03
2.03
219
2.19
31%
0%
0%
4.62
4.62
4.62
0.65
Office equip.PCs
0.08
5
0.00
0.46
0.35
0.31
1.12
1.12
1.13
1.13
1.13
1.13
1.13
0%
0%
0%
N/A
N/A
N/A
0.65
Office equip.-non-PCs
0.19
8
0.00
0.46
0.35
0.31
1.18
1.18
2.69
2.69
2.69
2.69
2.69
0%
0%
0%
N/A
N/A
N/A
0.65
Other Uses
0.65
7
0.00
0.46
0.35
031
1.49
1.49
9.19
9.19
9.19
9.19
9.19
33%
0%
0%
10.18
10.18
10.18
0.65
Total electric
3.33
1.09
1.09
1.00
1.00
Natural gas
Space heating
1.34
18
0.46
0.00
0.35
0.31
1.02
1.02
1745
15.38
15.38
14.73
13.55
48%
0%
0%
4.11
4.11
4.11
0.65
Space cooling
0.03
18
0.46
0.00
0.35
0.31
0.57
0.57
0.25
0.50
0.50
0.50
0 49
48%
0%
0%
4.11
4.11
4.11
0.65
Water heating
0.48
9
0.00
0.46
0.35
0.31
0.98
0.98
6.43
6.10
6.10
6.39
6.39
10%
0%
0%
9.50
9.50
9.50
0.65
Cooking
0.19
15
0.35
0.11
0.35
031
0.96
0.96
2.63
2.94
2.94
3.14
3.14
0%
0%
0%
N/A
N/A
N/A
0.65
Other Uses
1.29
7
0.00
0.46
0.35
0.31
0.97
0.97
18.25
18.25
1825
18.25
18.25
10%
0%
0%
3.00
3.00
3.00
0.65
Total ghe
3.33
0.98
0.98
1.00
1.00
Distillate all Space beating
0.19
18
0.46
0.00
0.35
0.31
1.04
1.04
2.60
1.67
1.67
1.44
1.33
48%
0%
0%
4.11
4.11
4.11
0.65
Water heating
0.05
9
0.00
0.46
0.35
0.31
1.58
1.58
0.73
0.45
0.45
0.42
0.42
104
0%
0%
9.50
9.50
9.50
0.65
Other Uses
0.13
7
0.00
0.46
0.35
0.31
0.96
0.96
1.84
1.84
1.84
1.84
1.84
10%
0%
0%
3.00
3.00
3.00
0.65
Total all
0.37
1.06
1.06
1.00
1.00
Renewables Biomase
0.00
18
0.46
0.00
0.35
0.31
1.00
1.00
1
1
1
1.00
0.92
0%
0%
0%
N/A
N/A
N/A
0.65
1.00
1.00
Other fuels Coal + berceene
0.31
18
0.46
0.00
0.35
031
1.00
1.00
1
I
I
1.00
0.92
0%
0%
0%
N/A
N/A
N/A
0.65
1.0
1.0
Totals
7.34
1.00
1.00
(1) Energy service growth factors used to normalise to ABO 97 end-sse consumption. Existing shell and new shell growth factors are differentiated la the spreadaheet for potential future use, but this differentiation is not currently used
(2) Energy prices in 2010 are 7.03. 4.78. 5.77 S/MMBte (1997 $) for electricity, natural gas. and distillate oll. respectively. Other fuels are assumed to cost the same as distillate oil.,
(3) All Intensities are taken from NEMS ABO97 data.
(4) 1990 commercial sector carbon emissions - 209 million metric tons.
(5) Electricity consumption and prices measured M site energy at 3412 Btus/kWh.
(6) on efficiency costs and savings are assumed to be the same M for natural gas.
(7) Costs of conserved energy are weighted averages up to the cost effective limit, and are expressed in $/MMBtu of primary energy.
J. Koomey, LBNL 510/486-5974
JGKoomey bi
Table C-2.6.a (continued): Results for U.S. commercial sector reference and efficiency cases
35% implementation of efficiency resources
35%
100%
35%
100%
100% Impleme Non case
33%
100%
35%
100%
Base
Prosen BaseNne Implement. Implement
Prozen
Baseline
Implement.
Implement.
Existing
Retront
New
Implement.
Implement
Base
Prozen
Baseline Implement. Implement
year
efficiency B.A.U. Effic. case Effic. case
efficiency
B.A.U.
Pffic. case
Effic. case
New
New
New
Effic. case
case
year
efficiency
B.A.U.
Effic. case Effic.
case
energy
e bergy
energy
energy
energy
energy
energy
energy
energy
efficiency
efficiency
efficiency
total
total
carbon
carbon
carbon
carbon
carbon
use
100
use
are
UN
costs
costs
costs
costs
costs
costs
costs
costs
costs
emissions
emissions
emissions
emissions
emissions
1997
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
1997
2010
2010
2010
2010
Fuel
End-wae
Quade
Quade
Quade
Quade
Quade
Billion 95$
Billion 95$
Billion 95$
Billion 95$
Billion 95$
Billion 95$
Billion 955
Billion 95$
Billion 95$
MMTC
MMTC
MMTC
MMTC
MMTC
Electricity
Space beating
0.12
0.12
0.12
0.11
0.09
2.50
2.52
2.28
1.83
0.01
0.06
0.06
233
1.97
6
6
6
5
4
Space cooling
0.52
0.53
0.52
0.47
0.38
11.04
10.91
9.86
7.91
0.05
0.24
0.26
10.06
847
26
25
25
23
16
Water heating
0.17
0.16
0.14
0.14
0.13
3.40
2.94
2.86
2.72
0.03
0.02
0.03
2.90
282
I
$
7
7
6
Ventilation
0.17
0.19
0.19
0.17
0.14
3.91
3.99
3.60
2.87
0.02
0.09
0.10
3.67
3.09
9
9
9
9
6
Cooking
0.03
0.03
0.03
0.03
0.03
0.65
0.63
0.63
0.63
0.00
0.00
0.00
0.63
0.63
1
I
1
I
I
Lighting
1.26
1.32
1.32
1.22
1.04
27.74
27.69
25.67
21.90
-1.01
-085
-0.94
24.69
19.10
62
63
63
60
46
Refrigeration
0.14
0.15
0.16
0.15
0.12
3.18
3.36
3.06
2.50
0.04
0.07
0 08
3.12
2.69
7
7
a
7
5
Office equip.PCs
0.08
0.10
0.10
0.10
0.10
2.10
2.10
2.10
2.10
0.00
0 00
0.00
2.10
210
4
5
5
5
5
Office equip.-non-POx
0.19
0.25
0.25
0.25
0.25
5.25
5.25
5.25
5.25
0.00
0.00
0.00
5.25
5.25
9
12
12
12
12
Other Uses
0.65
1.00
1.08
0.96
0.72
22.66
22.66
20.05
15.20
1.70
0.91
1.01
21.32
18.82
32
52
52
48
30
Total electric
333
3.93
3.91
3.59
3.00
82.41
82.03
75.34
62.92
0.86
0.55
0.60
76.05
64.93
163
188
187
178
132
Natural gm
Space beeting
134
1.42
1.36
1.25
1.06
6.42
6.13
5.65
4.76
0.13
0.35
0.61
6.11
6.05
19
21
20
18
15
Space cooling
0.03
0.03
0.03
0.03
0.02
0.14
0.14
0.12
0.09
0.00
0.02
0.02
0.13
all
0
0
0
0
0
Water heating
0.48
0.50
0.52
0.49
0.45
2.24
2.35
2.23
2.02
0.33
0.18
019
2.47
271
7
7
8
7
6
Cooking
0.19
0.22
0.23
0.23
0.23
0.99
1.04
1.04
1.04
0.00
0.00
0.00
1.04
1.04
3
3
3
3
3
Other Uses
1.29
1.40
1.40
1.35
1.26
6.31
6.31
6.09
5.68
0.20
0.11
0.12
6.24
6.10
19
20
20
20
18
Total gm
333
3.57
3.54
3.36
3.01
16.10
15.97
15.13
13.59
0.65
0.85
0 94
15.99
16.03
48
52
51
49
44
Distillate all Space heating
0.19
0.17
0.16
0.15
0.13
0.95
0.87
0.82
0.73
0.01
0.05
0.05
0.86
0.84
4
3
3
3
3
Water heating
0.03
0.05
0.05
0.05
0.05
0.30
0.27
0.27
0.27
0.00
0.00
0 00
0.27
0.28
I
I
I
1
1
Other Uses
0.13
0.14
0.14
0.14
0.13
0.76
0.76
0.73
0.69
0.02
0.01
001
0.75
0.73
3
3
3
3
3
Total all
0.37
0.37
0.35
0.34
0.31
2.00
1.90
1.83
1.68
0.03
0 06
0.06
1.88
1.84
7
7
7
7
6
Repewables Biomase
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0
0
0
0
0
Other
fuels
Coal
+
031
035
0.34
0.34
0.34
1.88
1.84
1.84
1.84
0.00
0.00
0.00
1.84
1.84
6
7
7
7
7
Totals
7.34
8.21
8.14
7.62
6.66
102.40
101.74
94.14
80.03
1.55
146
1.61
95.76
84.64
225
254
252
240
188
1.62
TWh
976
1151
1146
1052
879
J. Koomey, LBNL 510/486-5974
JGKoomey
Table C-2.6.a: Input assumptions for U.S. commercial sector reference and efficiency cases
35% implementation of efficiency resources
Other
Other
REFERENCE CASE (NO RETROFITS)
EFFICIENCY CASE
SHELL
Base
Existing Existing Retront New
Energy
Energy
Existing
Existing
New
Existing
New
Ex DO retront Ex. w/retroft New
Existing
Retrofit
New
EQUIPMENT
year
Existing
New
New
New
Service
Service
Pristing
New
New
New
New
New
New
New
New
New
New
energy
growth
growth
expid avg
exptd DVE
shell
shell
Achievable
⑉
End-ase
Stock
Stock
Stock
Stock
factor (1)
factor (1)
Intensity
Intensity
Intensity
Intensity
Intensity
rel. to new
savings
savings
CCE
CCB
CCE
Praction
1997
Nedmo
factor
factor
factor
factor
Ex. shells
New abells
kBtw/st
kBtu/sf
kBtu/sf
kBiws!
kBiu/sf
In 1997
factor
factor
S/MMBIs
S/MMBIN
$/MMBia
Fuel
End-use
Quade
years
2010
2010
2010
2010
2010
2010
1997
1997
1997
1997-2010
1997-2010
2010
2010
2010
4.11
4.11
4.11
0.35
Electricity
Space heating
0.12
18
0.46
0.06
0.28
0.31
0.96
0.96
1.54
1.36
1.36
144
1.32
48%
0%
0%
Space cooling
052
18
0.46
0.06
0.28
0.31
0.96
0.96
5.99
5.38
5.38
5.32
5.21
48%
0%
0%
4.11
4.11
4.11
0.35
Water heating
0.17
9
0.00
0.52
0.28
0.31
1.24
1.24
2.32
1.60
1.60
1.38
1.38
20%
0%
0%
9.41
9.41
9.41
0.35
2.36
2.05
205
2.13
2.13
48%
0%
0%
4.11
4.11
4.11
0.35
Ventilation
0.17
18
0.46
0.06
0.28
0.31
1.06
1.06
Cooking
0.03
15
0.35
0.17
0.28
0.31
1.11
1.11
0.43
0.32
0.32
0.31
0.31
0%
0%
0%
N/A
N/A
N/A
0.35
0%
0%
-10.16
-10.16
-10.16
0.35
Lighting
1.26
12
0.19
0.34
0.28
0.31
0.94
0.94
17.41
1732
17.32
17.29
17.29
25%
Refrigeration
0.14
15
0.35
0.17
0.28
0.31
0.96
0.96
1.99
2.03
2.03
2.19
219
31%
0%
0%
4.62
4.62
4.62
0.35
Office equip.PCs
0.08
5
0.00
0.52
0.28
0.31
1.12
1.12
1.13
1.13
1.13
1.13
1.13
0%
0%
0%
N/A
N/A
N/A
0.35
Office equip.-nom-POx
0.19
$
0.00
0.52
0.28
0.31
1.18
1.18
2.69
2.69
2.69
2.69
269
0%
0%
0%
N/A
N/A
N/A
0.35
Other Uses
0.65
7
0.00
0.52
0.28
0.31
1.49
1.49
9.19
9.19
9.19
9.19
9.19
33%
0%
0%
10.18
10.18
10.18
0.35
Total electric
333
1.09
1.09
1.00
1.00
4.11
4.11
0.35
Natural gm
Space heating
1.34
18
0.46
0.06
0.28
0.31
1.02
1.02
17.45
15.38
15.38
14.73
13.55
48%
0%
0%
4.11
0.06
0.28
0.31
0.57
0.57
0.25
0.50
0.50
0.50
0.49
42%
0%
0%
4.11
4.11
4.11
0.35
Space cooling
0.03
18
0.46
Water heating
0.48
9
0.00
0.52
0.28
0.31
0.98
0.98
6.43
6.10
6.10
6.39
6.39
10%
0%
0%
9.50
9.50
9.50
0.35
2.94
2.94
3.14
3.14
0%
0%
0%
N/A
N/A
N/A
0.35
Cooking
0.19
15
0.35
0.17
0.28
0.31
0.96
0.96
263
Other Uses
1.29
1
0.00
0.52
0.28
0.31
0.97
0.97
18.25
18.25
18.25
18.25
18.25
10%
0%
0%
3.00
3.00
3.00
0.35
Total gnd
333
0.98
0.98
1.00
1.00
Distillate all
Space heating
0.19
18
0.46
0.06
0.28
0.31
1.04
1.04
2.60
1.67
1.67
1.44
1.33
48%
0%
0%
4.11*
4.11
4.11
035
1.58
0.73
0.45
0.45
0.42
0.42
10%
0%
0%
9.50
9.50
9.50
0.35
Water heating
0.05
9
0.00
0.52
0.28
0.31
1.58
Other Uses
0.13
7
0.00
0.52
0.28
0.31
0.96
0.96
1.84
1.84
1.84
1.84
1.84
10%
0%
0%
3.00
3.00
3.00
0.35
Total all
0.37
1.06
1.06
1.00
1.00
035
Renewables
Biomass
0.00
18
0.46
0.06
0.28
0.31
1.00
1.00
1
1
1
1.00
0.92
0%
0%
0%
N/A
N/A
N/A
1.00
1.00
1.00
1
1
I
1.00
0.92
0%
0%
0%
N/A
N/A
N/A
0.35
Other facls
Coal + Income
031
18
0.46
0.06
0.28
0.31
1.00
1.0
1.0
Totals
7.34
1.00
1.00
(1) Energy service growth factors ased to normalize to ABO 97 end-ase consumption. Existing shell and new shell growth factors are differentiated In the apreadaheet for potential fature use, but this differentiation is DOI currently used.
(2) Energy prices in 2010 are 7.03. 4.78, 5.77 S/MMBts (1997 $) for electricity, natural gas. and distillate all, respectively. Other fuels are assumed to cost the same M distillate oil..
(3) All Intensides are taken from NEMS AB097 data.
(4) 1990 commercial sector carbon emissions - 209 million metric tons.
(5) Electricity consumption and prices measured M site energy at 3412 Bles/kWb.
(6) on efficiency costs and savings are assumed to be the same as for natural gas.
(7) Costs of conserved energy are weighted averages up to the cost effective limit. and are expressed in $/MMBte of primary energy.
J. Koomey, LBNL 510/486-5974
JGKoomey fbl.gov
Table C-2.5.b (continued): Results for the residential sector, reference and high efficiency cases
65% Implementation of efficiency resources
65%
100%
65%
100%
100% Implementation case
65%
100%
65%
100%
Base
Prozen Bascline Implement. Implement.
Prozen
Baseline
Implement.
Implement.
Existing
Retrofit
New
Implement.
Implement
Base
Prozen
Baseline Implement. Implement
year
efficiency
B.A.U.
Bffic. case
Bffic. case
efficiency
B.A.U.
Effic. case
Effic. case
New
New
New
Bffic. case
case
year
efficiency
B.A.U.
Effic. case
Effic. case
carbon
carbon
energy
energy
energy
energy
energy
energy
energy
energy
energy
efficiency
efficiency
efficiency
total
total
carbon
carbon
carbon
use
use
use
use
use
costs
costs
costs
costs
costs
costs
costs
costs
costs
emissions
emissions
emissions
emissions
emissions
1997
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
1997
2010
2010
2010
2010
Fuel
End-use
Quade
Quade
Quade
Quads
Quade
Billion
95$
Billion
95$
Billion 95$
Billion 95$
Billion 95$
Billion 95$
Billion 95$
Billion 95$
Billion 95$
MMTC
MMTC
MMTC
MMTC
MMTC
Electricity
Space heating
0.45
0.50
0.48
0.44
0.42
11.50
10.98
10.10
9.63
0.02
0.32
0.31
10.52
10.27
22
24
23
21
19
Electricity
Space cooling
0.46
051
0.49
0.45
0.43
11.77
11.21
10.26
9.74
0.11
0.19
0.20
10.59
10.25
23
25
23
21
20
0.39
0.38
0.31
0.27
8.92
8.69
7.08
6.20
0.50
0.40
0.26
7.83
7.36
17
19
18
14
12
Electricity
Water beating
035
Electricity
Refrigeration
038
0.32
0.31
0.28
0.27
7.26
7.09
6.46
6.12
0.02
0.25
0.16
6.73
6.54
19
15
15
13
12
Electricity
Cooking
0.12
0.14
0.14
0.13
0.12
3.23
3.20
2.94
2.80
0.00
1.33
0.00
3.80
4.13
6
7
7
6
6
7
Electricity
Clothes Dryers
0.18
0.21
0.21
0.18
0.16
4.80
4.80
4.11
3.74
0.00
1.33
0.00
4.97
5.07
9
10
10
1
Electricity
Preezers
0.12
0.08
0.08
0.07
0.07
1.83
183
1.66
157
0.01
0.09
0.06
1.76
1.72
6
4
4
3
3
16
17
17
9
6
Electricity
Lighting
0.32
0.35
0.35
0.23
0.17
8.01
8.01
5.26
3.78
0.69
0.52
0.33
6.26
5.32
Electricity
Other Uses
135
2.02
2.02
1.60
1.37
46.22
46.22
36.54
31.34
2.88
2.28
1.46
40.85
37.96
66
97
97
71
57
Total electric
3.73
4.52
4.46
3.69
3.27
103.53
102.04
84.41
74.92
4.22
6.70
2.78
93.32
88.62
183
217
213
167
142
Natural gas
Space beating
3.68
3.99
3.88
3.81
3.77
21.04
20.45
20.05
19.84
0.00
0.35
0.24
20.44
20.43
53
58
56
55
54
Natural gas
Space cooling
0.00
0.02
0.02
0.02
0.02
0.11
0.11
0.11
0.11
0.00
0.00
0.00
0.11
0.11
0
0
0
0
0
Natural gas
Water beating
1.27
1.40
139
1.27
1.21
7.37
7.33
6.72
6.39
0.12
0.21
0.14
7.02
6.86
18
20
20
11
18
0.15
0.14
0.16
0.16
0.75
0.74
0.82
0.87
0.00
0.02
0.01
0.85
0.91
2
2
2
2
2
Natural gas
Cooking
0.14
Natural gm
Clothes Dryan
0.05
0.05
0.05
0.09
0.11
0.26
0.26
0.47
0.58
0.00
0.00
0.00
0.47
0.58
I
I
I
I
2
Natural gas
Other Uses
0.09
0.10
0.10
0.09
0.09
0.53
053
0.49
0.48
0.01
0.01
0.01
0.51
0.50
I
1
1
I
I
78
Total gas
5.24
5.70
558
3.44
5.36
30.05
29.41
28.66
28.26
0.13
0.60
0.39
29.40
29.39
76
83
11
79
Distillate oil
Space beating
0.77
0.66
0.65
0.63
0.62
4.92
4.84
4.69
4.60
0.00
0.09
0.06
4.78
4.75
15
13
13
13
12
0.69
2
2
2
2
2
Distillate oil
Water heating
0.10
0.10
0.10
0.09
0.08
0.74
0.75
0.67
0.62
0.01
0.02
0.01
0.66
Distillate oil
Other Uses
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0 00
0.00
0.00
0.00
0.00
0
0
0
0
0
Total oil
0.87
0.76
0.75
0.72
0.70
5.67
5.59
5.35
5.22
0.01
0.10
0.07
5.47
5.41
17
15
15
14
14
LPO
Space besting
0.29
033
032
031
0.30
3.87
3.79
3.66
3.59
0.00
0.04
0.04
3.71
367
5
6
5
s
5
0.08
1.08
107
0.96
0.90
0.01
001
001
0.98
0.93
I
2
2
I
I
LPO
Water beating
0.07
0.09
0.09
0.08
LPG
Cooking
0.03
0.03
0.03
0.03
0.03
0.36
0.36
0.33
0.32
0.00
0.00
0.00
0.34
0.33
I
I
1
0
0
0.01
0.01
0.01
0.01
0.01
0.12
0.12
0.11
0.11
0.00
0.00
0.00
0.11
0.11
0
0
0
0
0
LPO
Other Uses
Total LPO
0.40
0.46
0.45
0.43
0.42
5.43
5.33
5.07
4.93
0.01
0.06
0.05
5.14
5.04
1
1
$
7
7
Renewables Wood
0.58
0.56
0.55
0.55
0.55
5.90
5.80
5.80
5.80
0.00
0.00
0.00
5.80
5.80
0
0
0
0
0
2
2
2
2
Other fuels
Coal + keroses
0.12
0.11
0.11
0.11
0.11
0.83
0.82
0.82
0.82
0.00
0.00
0.00
0.82
0.82
2
Totals
10.94
12.12
11.90
10.93
10.41
151.41
148.99
130.11
119.95
4.37
7.46
3.30
139.95
135.08
285
324
319
269
242
9.84
1093
1326
1307
1081
960
J. Koomey, LBNL 510/486-5974
[email protected]
Table C-2.5.a: Input assumptions for U.S. residential sector reference and efficiency cases
35% Implementation of efficiency resources
Other
Other
REFERENCE CASE (NO RETROPITS)
EFFICIENCY CASB
SHELL
Base
Existing Existing Retrofit New
Energy
Energy
Existing Existing
New
Existing
New
Px no retrofitEs. whetrofit New
Existing
Retront
New
BQUIPMENT
year
Existing
New
New
New
Service
Service
Existing
New
New
New
New
New
New
New
New
New
New
energy
growth
growth
exptd AVE
exptd "I
shell
shell
Achievable
use
Bnd-use
Stock
Stock
Stock
Stock
factor (1)
factor (1)
UEC
UEC
UEC
UEC
UEC
rel. to new
savings
savings
CCB
CCB
CCB
Praction
1997
lifetime
factor
factor
factor
factor
Ex. shells
New shella
MMBN
MMBN
MMBN
kWh
MMBN
in 1997
factor
factor
$/MMBru
$/MMBru
$/MMBer
Fuel
End-use
Quade
years
2010
2010
2010
2010
2010
2010
1997
1997
1997
1997-2010
1997-2010
2010
2010
2010
Electricity
Space heating
0.45
18
0.46
0.13
0.32
0.25
1.04
1.04
32.1
30.5
24.8
28.7
21.7
11%
14%
28%
9.06
10.07
12.15
0.35
Space cooling
0.46
13
0.25
0.34
0.32
0.25
1.16
1.16
55
4.4
4.3
4.2
3.8
15%
1%
7%
9.06
10.07
12.15
0.35
Water beating
0.35
10
0.02
0.56
0.32
0.25
1.22
1.22
16.8
13.3
13.3
13.0
13.0
28%
0%
0%
9.41
9.41
9.41
0.35
Refrigeration
0.38
19
0.49
0.10
0.32
0.25
0.89
0.89
3.2
2.2
2.2
2.1
2.1
33%
0%
0%
9.90
9.90
9.90
0.35
Cooking
0.12
19
0.49
0.10
0.32
0.25
1.02
1.02
2.0
2.0
2.0
2.0
2.0
0%
0%
0%
N/A
N/A
N/A
0.35
Clothes Dryers
0.18
17
0.43
0.16
0.32
0.25
1.05
1.05
3.0
2.8
2.8
2.8
2.8
0%
0%
0%
N/A
N/A
N/A
0.35
Preezers
0.12
19
0.49
0.10
0.32
0.25
0.67
0.67
2.0
1.6
1.6
1.6
1.6
28%
0%
0%
13.19
13.19
13.19
0.35
Lighting
0.32
I
0.00
0.59
0.32
0.25
0.95
0.95
3.2
3.2
3.2
3.2
3.2
53%
0%
0%
8.34
8.34
8.34
0.35
Other Uses
135
10
0.02
0.56
0.32
0.25
1.30
1.30
13.3
13.3
13.3
133
13.3
33%
0%
0%
10.18
10.18
10.18
0.35
Total electric
3.73
1.14
1.14
Natural gm
Space beating
3.68
20
0:51
0.07
0.32
0.25
1.09
1.09
74.6
653
42.4
62.8
38.0
7%
4%
12%
4.99
4.66
4.48
0.35
Space cooling
0.00
12
0.19
0.40
0.32
0.25
1.00
1.00
10
1.0
1.0
1.0
1.0
0%
0%
0%
N/A
N/A
N/A
0.35
Water beating
1.27
14
0.30
0.29
0.32
0.25
1.04
1.04
33.6
29.7
29.7
29.5
29.5
23%
0%
0%
2.15
2.15
2.15
0.35
Cooking
0.15
19
0.49
0.10
0.32
0.25
0.82
0.82
38
3.8
3.8
3.7
3.7
18%
0%
0%
2.38
2.38
2.38
0.35
Clothes Dryers
0.05
17
0.43
0.16
0.32
0.25
0.95
0.95
3.7
3.2
3.2
3.2
3.2
0%
0%
0%
N/A
N/A
N/A
0.35
Other Uses
0.09
10
0.02
0.56
0.32
0.25
0.97
0.97
0.9
0.9
0.9
0.9
0.9
10%
0%
0%
3.00
3.00
3.00
0.35
Total gas
5.24
1.07
1.07
Distillate oil
Space beating
0.77
20
0.51
0.07
0.32
0.25
0.85
0.85
70.5
61.7
43.8
61.1
40.0
7%
4%
12%
4.99
4.66
4.48
0.35
Water beating
0.10
14
0.30
0.29
0.32
0.25
0.95
0.95
33.6
29.7
29.7
29.7
29.7
23%
0%
0%
2.15
2.15
2.15
0.35
Other Uses
0.00
10
0.02
0.56
0.32
0.25
1.00
1.00
1.0
1.0
1.0
1.0
1.0
10%
0%
0%
3.00
3.00
3.00
0.35
Total oil
0.87
0.86
0.86
LPO
Space heating
0.29
20
0.51
0.07
0.32
0.25
1.05
1.05
74.6
65.3
65.3
64.6
59.5
7%
4%
12%
4.99
4.66
4.48
0.35
Water heating
0.07
14
0.30
0.29
0.32
0.25
1.24
1.24
33.6
29.7
29.7
29.2
29.2
23%
0%
0%
2.15
2.15
2.15
0.35
Cooking
0.03
19
0.49
0.10
0.32
0.25
0.88
0.88
3.8
3.8
3.8
3.7
3.7
18%
0%
0%
2.38
2.38
2.38
0.35
Other Uses
0.01
10
0.02
0.56
0.32
0.25
0.87
0.87
0.1
0.1
0.1
0.1
01
10%
0%
0%
3.00
3.00
3.00
0.35
Total LPO
0.40
1.06
1.06
Renewables
Wood
0.58
20
0.51
0.07
0.32
0.25
0.84
0.84
1.0
1.0
1.0
1.0
0.9
0%
0%
0%
N/A
N/A
N/A
0.35
Other fuels
Coal + kerosene
0.12
20
0.51
0.07
0.32
0.25
0.81
0.81
1.0
1.0
1.0
1.0
0.9
0%
0%
0%
N/A
N/A
N/A
0.35
Totals
10.94
1.05
1.05
(1) Energy service growth factors used to normalize to ABO 97 end-use consumption. Existing shell and new shell growth factors are differentiated in the spreadabeet for potential future use, but this differentiation is not currently used.
(2) Energy prices in 2010 are 7.67, 5.59, 7.90, and 1257 S/MMBeu (1997 for electricity, natural gas, distillate oil, and LPG, respectively.
Other fuels are assumed to cost the same as distillate oil, while renewables are assumed to cost noice as much as natural gm.
(3) All UBCs are taken from the LBNL REM and LBNL REEPS residential forecasting models/
(4) 1990 residential sector carbon emissions - 253 million metric tons.
(5) Electricity consumption and prices measured as site energy at 3412 Brus/kWb.
(6) Oil and LPG efficiency costs and savings are assumed to be the same AS for natural gas.
(7) Costs of conserved energy are weighted averages up to the cost effective limit, and are expressed in $/MMBru of primary energy.
average, weighted by grads pe end-use
1. Koomey, LBNL 510/486-5974
[email protected]
Table C-2.4: Main results, commercial sector business-as-usual scenario, by end-use
Energy Costs
Primary Energy Use (Quads)
Carbon Emissions (MMTC)
Billion 1995 $
Fuel
End-use
1990
1997
2010
1990
1997
2010
2010
Electricity
Space heating
0.4
0.4
0.3
6
6
6
3
Space cooling
1.8
1.7
1.5
29
26
25
11
Water heating
0.6
0.5
0.4
9
8
7
3
Ventilation
0.5
0.5
0.6
9
8
9
4
Cooking
0.1
0.1
0.1
2
1
1
1
Lighting
3.7
4.0
3.8
59
62
63
28
Refrigeration
0.4
0.4
0.5
7
7
8
3
PC Off. Equip.
0.1
0.3
0.3
2
4
5
2
non-PC Off. Equip.
0.5
0.6
0.7
8
9
12
5
Other Uses
1.2
2.1
3.1
20
32
52
23
Total electric
9.4
10.6
11.4
150
163
187
82
Natural gas
Space heating
1.3
1.3
1.4
20
19
20
6
Space cooling
0.0
0.0
0.0
0
0
0
0
Water heating
0.5
0.5
0.5
7
7
8'
2
Cooking
0.2
0.2
0.2
2
3
3
1
Other Uses
0.9
1.3
1.4
13
19
20
6
Total gas
2.9
3.3
3.5
42
48
51
16
Distillate oil
Space heating
0.2
0.2
0.2
4
4
3
1
Water heating
0.1
0.1
0.1
1
1
1
0
Other Uses
0.2
0.1
0.1
4
3
3
1
Total oil
0.5
0.4
0.4
10
7
7
2
Renewables Wood
0.0
0.0
0.0
0
0
0
0
Other fuels
Coal + kerosene
0.4
0.3
0.3
7
6
7
2
Totals
13.2
14.6
15.6
209
225
252
102
Table C-2.3: Main results, residential sector business-as-usual scenario, by end-use
Energy Costs
Primary Energy Use (Quads)
Carbon Emissions (MMTC)
Billion 1995 $
Fuel
End-use
1990
1997
2010
1990
1997
2010
2010
Electricity
Space heating
1.0
1.4
1.4
15
22
23
11
Space cooling
1.7
1.5
1.4
27
23
23
11
Water heating
1.1
1.1
1.1
18
17
18
9
Refrigeration
1.7
1.2
0.9
27
19
15
7
Cooking
0.5
0.4
0.4
8
6
7
3
Clothes Dryers
0.6
0.6
0.6
9
9
10
5
Freezers
0.5
0.4
0.2
8
6
4
2
Lighting
1.0
1.0
1.0
15
16
17
8
Other Uses
2.2
4.3
5.9
36
66
97
46
Total electric
10.2
11.9
13.0
162
183
213
102
Natural gas
Space heating
3.1
3.7
3.9
45
53
56
20
Space cooling
0.0
0.0
0.0
0
0
0
0
Water heating
1.1
1.3
1.4
16
18
20
7
Cooking
0.2
0.2
0.1
3
2
2
1
Clothes Dryers
0.1
0.1
0.1
1
1
1
0
Other Uses
0.1
0.1
0.1
1
1
1
1
Total gas
4.5
5.2
5.6
66
76
81
29
Distillate oil
Space heating
0.8
0.8
0.7
15
15
13
5
Water heating
0.1
0.1
0.1
2
2
2
1
Other Uses
0.0
0.0
0.0
0
0
0
0
Total oil
0.8
0.9
0.8
17
17
15
6
LPG
Space heating
0.2
0.3
0.3
4
5
5
4
Water heating
0.1
0.1
0.1
1
1
2
1
Cooking
0.1
0.0
0.0
1
1
1
0
Other Uses
0.0
0.0
0.0
0
0
0
0
Total LPG
0.4
0.4
0.5
6
7
8
5
Renewables
Wood
0.6
0.6
0.6
0
0
0
6
Other fuels
Coal + kerosene
0.1
0.1
0.1
3
2
2
1
Totals
16.7
19.1
20.4
253
285
319
149
Table C-2.2: Main results, buildings sector business-as-usual scenario, by fuel
Energy Costs
Primary Energy Use (Quads)
Carbon Emissions (MMTC)
Billion 1995 $
Fuel
End-use
1990
1997
2010
1990
1997
2010
2010
Residential
Electricity
10.2
11.9
13.0
162
183
213
102
Natural gas
4.5
5.2
5.6
66
76
81
29
Distillate oil
0.8
0.9
0.8
17
17
15
6
Other fuels
1.1
1.1
1.1
9
9
10
12
Total
16.7
19.1
20.4
253
285
319
149
Commercial Electricity
9.4
10.6
11.4
150
163
187
82
Natural gas
2.9
3.3
3.5
42
48
51
16
Distillate oil
0.5
0.4
0.4
10
7
7
2
Other fuels
0.4
0.3
0.3
7
6
7
2
Total
13.2
14.6
15.6
209
225
252
102
Total
Electricity
19.7
22.5
24.3
312
346
401
184
Natural gas
7.4
8.6
9.1
107
124
132
45
Distillate oil
1.3
1.2
1.1
26
25
22
7
Other fuels
1.5
1.4
1.4
16
15
17
14
Total
29.9
33.7
36.0
462
511
571
251
(1) Other fuels includes LPG, renewables, coal, and kerosene.
Table C-2.1: Main results, buildings sector scenarios
Energy
Efficiency
Total Costs of
costs
costs
Energy Services
Primary Energy Use (Quads)
Carbon Emissions (MMTC)
Billion 1995 $
Billion 1995 $
Billion 1995 $
Fuel
End-use
1990
1997
2010
1990
1997
2010
2010
2010
2010
Residential
B.A.U.
16.7
19.1
20.4
253
285
319
149
0
149
Efficiency case
16.7
19.1
19.4
253
285
306
139
5
144
High efficiency case
16.7
19.1
18.2
253
285
269
130
10
140
Commercial
B.A.U.
13.2
14.6
15.6
209
225
252
102
0
102
Efficiency case
13.2
14.6
14.7
209
225
240
94
2
96
High efficiency case
13.2
14.6
13.7
209
225
211
88
3
91
Total
B.A.U.
29.9
33.7
36.0
462
511
571
251
0
251
Efficiency case
29.9
33.7
34.1
462
511
546
233
7
240
High efficiency case
29.9
33.7
32.0
462
511
480
218
13
231
Index
1990 = 1.0
1.00
1.13
1.20
1.00
1.10
1.24
N/A
N/A
N/A
1991 = 1.0
1.00
1.13
1.14
1.00
1.10
1.18
N/A
N/A
N/A
1992 = 1.0
1.00
1.13
1.07
1.00
1.10
1.04
N/A
N/A
N/A
Index
B.A.U. = 1.0
1.00
1.00
1.00
1.00
1.00
1.00
1.00
N/A
1.00
B.A.U. = 1.0
1.00
1.00
0.95
1.00
1.00
0.96
0.93
N/A
0.96
B.A.U. = 1.0
1.00
1.00
0.89
1.00
1.00
0.84
0.87
N/A
0.92
(1) Other fuels includes LPG, renewables, coal, and kerosene.
(2) Efficiency case assumes 35% implementation of efficiency resources, and high efficiency case assumes 65% implementation.
(3) Efficiency costs are annualized in 2010.
TERMINOLOGY AND CONVENTIONS FOR BUILDINGS SECTOR SPREADSHEET
Stock factors
These factors are fractions of the 1997 stock attributable to
different parts of the building stock. They are calculated
using a simple stock acccounting model and the average
equipment lifetimes shown in Tables R.1 and C.1. The
lifetime of building shells is 100 years for residential and 50
years for commercial. The sum of the stock factors for 2010
is 1.15 for residential and 1.12 for commercial, which means
that over the 1997-2010 period, total households and total
floor area grow 15% and 12%, respectively. We separately
account for retrofit and new shells, though in the reference
case there are no retrofits. About 10% of the residential
buildings existing in 1997 are retired by 2010, while about
19% of the commercial buildings existing in 1997 are retired
by 2010.
Energy service growth
These factors are used to normalize our forecasted total
factors
consumption by end-use to the AEO97 results. They correct
for differences in the stock accounting and other aspects of
our methodology. If these numbers are less than 1.0, they
imply that our methodology overforecasts demand compared
to AEO97, while if they are larger than 1.0, our methodology
underforecasts demand compared to AEO97.
UECs and EUIs
The ratios of the UECs or EUIs for the different categories of
houses are used along with our simple stock accounting to
capture the effect of stock turnover on energy use. With the
exception of residential refrigerators and freezers (which come
from LBNL REM), the UECs and EUIs come directly from the
AEO97 model outputs.
Efficiency factors
These are defined relative to current practice in 1997. The
first column in this section (with the heading "EFFICIENCY
CASE") is the savings associated with new equipment,
expressed as the percentage by which this new equipment
exceeds the efficiency of 1997 new equipment. The second
column (ex. with retrofit, new equipment) is the shell savings
factor that is to be added to the equipment efficiency factor
to get total savings for these buildings. The third column (new
shell, new equipment) is the shell savings factor for new
buildings that is to be added to the equipment efficiency
factor to get total savings for new buildings.
CCE ($/MMBtu site)
The cost of conserved energy (CCE) is calculated using a 7%
real discount rate. It represents the average CCE for a
package of measures that all cost less than the price cutoff of
8 cents/kWh or $6/MMBtu. It is the weighted average cost
of adding all technically cost-effective efficiency options up to
that price cutoff.
Efficiency costs (Billion
The costs of improving efficiency are assessed on an
1997$/year)
annualized basis. They are calculated by multiplying the
annual energy savings by the CCE.
Total cost of energy services
Total cost of energy services is the sum of energy costs and
(Billion 1997$/year)
efficiency costs.
Table C-2.5.a (continued): Results for the U.S. residential sector reference and efficiency cases
35% Implementation of efficiency resources
(1)
( )
(2)
(1)
35%
100%
35%
100%
100% Implementation case
35%
100%
35%
100%
Base
Prozen Baseline Implement. Implement
Prozen
Baseline
Implement
Implement.
Existing
Retrofit
New
Implement.
Implement.
Base
Prozen
Baseline
Implement.
Implement
year
efficiency
B.A.U.
Effic. case
Effic. case
efficiency
B.A.U.
Effic. case
Bffic. case
New
New
New
Effic. case
case
year
efficiency
B.A.U.
Effic. case
Effic. case
energy
energy
energy
energy
energy
energy
energy
energy
energy
efficiency
efficiency
efficiency
total
total
carbon
carbon
carbon
carbon
carbon
use
use
use
use
use
costs
costs
costs
costs
costs
costs
costs
costs
costs
emissions
emissions
emissions
emissions
emissions
1997
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
1997
2010
2010
2010
2010
Fuel
End-use
Quads
Quade
Quade
Quade
Quade
Billion
95$
Billion
95$
Billion
951
Billion 95$
Billion 95$
Billion 95$
Billion 95$
Billion 95$
Billion 95$
MMTC
MMTC
MMTC
MMTC
MMTC
Electricity
Space heating
0.45
0.50
0.48
0.46
0.43
11.50
10.98
10.54
9.73
0.04
0.25
0.31
10.75
10.33
22
24
23
22
20
Electricity
Space cooling
0.46
0.51
0.49
0.47
0.43
11.77
11.21
10.70
9.75
0.14
0.16
0.20
10.88
10.25
23
25
23
23
20
Electricity
Water beating
0.35
0.39
0.38
0.34
0.27
8.92
8.69
7.82
6.20
0.58
0.33
0.26
8.23
7.36
17
19
18
17
12
Electricity
Refrigeration
0.38
0.32
031
0.30
0.27
7.26
7.09
6.75
6.12
0.06
0.20
0.16
6.90
6.54
19
15
15
14
12
Electricity
Cooking
0.12
0.14
0.14
0.13
0.12
3.23
3.20
3.06
2.80
0.00
1.33
0.00
3.53
4.13
6
7
7
7
6
Electricity
Clothes Dryers
0.18
0.21
0.21
0.19
0.16
4.80
480
4.43
3.74
0.00
1.33
0.00
4.90
3.07
9
10
10
10
7
Blectricity
Preezers
0.12
0.08
0.08
0.08
0.07
1.83
1.83
1.74
1.57
0.02
0.07
0.06
1.79
1.72
6
4
4
4
3
Electricity
Lighting
0.32
0.35
0.35
0.29
0.17
8.01
8.01
6.53
3.78
0.78
0.42
0.33
7.07
5.32
16
17
17
15
6
Electricity
Other Uses
1.35
2.02
2.02
1.79
1.37
46.22
46.22
41.01
31.34
3.30
1.86
1.46
43.33
37.96
66
97
97
90
57
Total electric
3.73
4.52
4.46
4.05
3.28
103.53
102.04
92.59
75.03
4.93
5.94
2.77
97.37
88.68
183
217
213
202
142
Natural gm
Space heating
3.68
3.99
3.88
3.84
3.78
21.04
20.45
20.25
19.90
0.04
0.27
0.23
20.45
20.44
53
58
56
56
55
Natural gm
Space cooling
0.00
0.02
0.02
0.02
0.02
0.11
0.11
0.11
0.11
0.00
0.00
0.00
0.11
0.11
0
0
0
0
0
Natural gas
Water besting
1.27
1.40
139
133
1.21
737
7.33
7.00
6.39
0.16
0.17
0.14
7.16
6.86
18
20
20
19
18
Natural gas
Cooking
0.15
0.14
0.14
0.15
0.16
0.75
0.74
0.78
0.87
0.01
0.02
0.01
0 80
0.91
2
2
2
2
2
Natural gm
Clothes Dryers
0.05
0.05
0.05
0.07
0.11
0.26
0.26
0.37
0.58
0.00
0.00
0.00
0.37
0.58
1
I
1
1
2
Natural gas
Other Uses
0.09
0.10
0.10
0.10
0.09
0.53
0.53
0.51
0.48
0.01
0.01
0.01
0.52
0.50
I
I
I
I
1
Total gre
5.24
5.70
558
5.51
5.37
30.05
29.41
29.03
28.32
0.22
0.47
0.38
29.40
29.40
76
83
81
80
78
Distillate oil
Space heating
0.77
0.66
0.65
0.64
0.62
4.92
4.84
4.76
4.61
0.01
0.07
0.06
4.81
4.76
15
13
13
13
12
Distillate oil
Water heating
0.10
0.10
0.10
0.09
0.08
0.74
0.75
0.70
0.62
0.01
0.01
0.01
0.71
0.66
2
2
2
2
2
Distillate oil
Other Uses
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0
0
0
0
0
Total oil
0.87
0.76
0.75
0.73
0.70
5.67
5.59
5.46
5.24
0.02
0.08
007
5.53
5.41
17
15
15
15
14
LPO
Space heating
0.29
0.33
0.32
031
0.30
3.87
3.79
3.73
3.60
0.00
0.03
0.04
3.75
3.68
5
6
5
5
5
LPO
Water besting
0.07
0.09
0.09
0.09
0.08
1.08
1.07
1.01
0.90
0.01
0.01
0.01
1.02
0.93
I
2
2
1
1
LPG
Cooking
0.03
0.03
0.03
0.03
0.03
0.36
0.36
0.34
0.32
0.00
0.00
0.00
0.35
0.33
I
I
1
0
0
LPG
Other Uses
0.01
0.01
0.01
0.01
0.01
0.12
0.12
0.11
0.11
0.00
0.00
0.00
0.12
0.11
0
0
0
0
0
Total LPG
0.40
0.46
0.45
0.44
0.42
5.43
5.33
5.19
4.94
0.02
0.05
0.05
5.23
5.05
7
I
$
7
7
Renewables Wood
0.58
0.56
0.55
0.55
0.55
5.90
5.80
5.80
5.80
0.00
0.00
0.00
5.80
5.80
0
0
0
0
0
Other fuels
Coal + kerosen
0.12
0.11
0.11
0.11
0.11
0.83
0.82
0.82
0.82
0.00
0.00
0.00
0.82
0.82
2
2
2
2
2
Totals
10.94
12.12
11.90
11.39
10.43
151.41
148.99
138.89
120.14
5.19
6.54
3.28
144.15
135.15
285
324
319
306
243
1093
1326
1307
1186
961
J. Koomey, LBNL 510/486-5974
Table C-2.5.b: Input assumptions for U.S. residential sector reference and high efficiency cases
65% implementation of efficiency resources
Other
Other
REPERENCE CASE (NO RETROPITS)
EFFICIENCY CASB
SHELL
Base
Existing Existing Retrofit
New
Energy
Energy
Existing
Existing
New
Existing
New
Ex no retrofit Ex. w/retrofit New
Existing
Retrofit
New
EQUIPMENT
Existing
New
New
New
Service
Service
Existing
New
New
New
New
New
New
New
New
New
New
year
Achievable
energy
growth
growth
exptd avg
exptd avg
shell
shell
use
Bnd-use
Stock
Stock
Stock
Stock
factor (1)
factor (1)
UEC
UEC
UEC
UEC
UEC
rel. to new
savings
savings
CCB
CCE
CCH
Praction
1997
lifetime
factor
factor
factor
factor
Ex. shells
New shells
MMBru
MMBru
MMBtu
kWh
MMBru
in 1997
factor
factor
$/MMBru
$/MMBru
$/MMBru
Fuel
End-use
Quade
years
2010
2010
2010
2010
2010
2010
1997
1997
1997
1997-2010
1997-2010
2010
2010
2010
0.46
0.06
0.39
0.25
1.04
1.04
32.1
30.5
24.8
28.7
21.7
11%
14%
28%
9.06
10.07
12.15
0.65
Electricity
Space heating
0.45
18
Space cooling
0.46
13
0.25
0.26
0.39
0.25
1.16
1.16
55
4.4
4.3
4.2
3.8
15%
1%
7%
9.06
10.07
12.15
0.65
0.39
0.25
1.22
1.22
16.8
13.3
13.3
13.0
13.0
28%
0%
0%
9.41
9.41
9.41
0.65
Water heating
0.35
10
0.02
0.49
Refrigeration
0.38
19
0.49
0.03
0.39
0.25
0.89
0.89
3.2
2.2
2.2
2.1
2.1
33%
0%
0%
9.90
9.90
9.90
0.65
0.25
1.02
1.02
2.0
2.0
2.0
2.0
2.0
0%
0%
0%
N/A
N/A
N/A
0.65
Cooking
0.12
19
0.49
0.03
0.39
Clothes Dryers
0.18
17
0.43
0.09
0.39
0.25
1.05
1.05
3.0
2.8
2.8
2.8
2.8
0%
0%
0%
N/A
N/A
N/A
0.65
0.67
0.67
2.0
1.6
1.6
1.6
1.6
28%
0%
0%
13.19
13.19
13.19
0.65
Preezers
0.12
19
0.49
0.03
0.39
0.25
Lighting
0.32
1
0.00
0.51
0.39
0.25
0.95
0.95
3.2
3.2
3.2
3.2
3.2
53%
0%
0%
8.34
8.34
8.34
0.65
1.30
13.3
13.3
13.3
13.3
13.3
33%
0%
0%
10.18
10.18
10.18
0.65
Other Uses
1.35
10
0.02
0.49
0.39
0.25
1.30
Total electric
3.73
1.14
1.14
Natural gm
Space beating
3.68
20
0.51
0.00
0.39
0.25
1.09
1.09
74.6
65.3
42.4
62.8
38.0
7%
4%
12%
4.99
4.66
4.48
0.65
0%
0%
0%
N/A
N/A
N/A
0.65
Space cooling
0.00
12
0.19
0.33
0.39
0.25
1.00
1.00
1.0
1.0
10
1.0
1.0
Water heating
1.27
14
0.30
0.22
0.39
0.25
1.04
1.04
33.6
29.7
29.7
29.5
29.5
23%
0%
0%
2.15
2.15
2.15
0.65
0%
0%
2.38
2.38
2.38
0.65
Cooking
0.15
19
0.49
0.03
0.39
0.25
0.82
0.82
38
3.8
3.8
3.7
3.7
18%
Clothes Dryers
0.05
17
0.43
0.09
0.39
0.25
0.95
0.95
3.7
3.2
3.2
3.2
3.2
0%
0%
0%
N/A
N/A
N/A
0.65
0%
3.00
3.00
3.00
0.65
Other Uses
0.09
10
0.02
0.49
0.39
0.25
0.97
0.97
0.9
0.9
0.9
0.9
0.9
10%
0%
Total gm
5.24
1.07
1.07
Space heating
0.77
20
0.51
0.00
0.39
0.25
0.85
0.85
70.5
61.7
43.8
61.1
40.0
7%
4%
12%
4.99
4.66
4.48
0.65
Distillate oil
Water beating
0.10
14
0.30
0.22
0.39
0.25
0.95
0.95
33.6
29.7
29.7
29.7
29.7
23%
0%
0%
2.15
2.15
2.15
0.65
10
0.02
0.49
0.39
0.25
1.00
1.00
1.0
1.0
1.0
1.0
1.0
10%
0%
0%
3.00
3.00
3.00
0.65
Other Uses
0.00
Total oil
0.87
0.86
0.86
LPO
Space heating
0.29
20
0.51
0.00
0.39
0.25
1.05
1.05
74.6
65.3
65.3
64.6
59.5
7%
4%
12%
4.99
4.66
4.48
0.65
1.24
33.6
29.7
29.7
29.2
29.2
23%
0%
0%
2.15
2.15
2.15
0.65
Water heating
0.07
14
0.30
0.22
0.39
0.25
1.24
Cooking
0.03
19
0.49
0.03
0.39
0.25
0.88
0.88
3.8
3.8
38
3.7
3.7
18%
0%
0%
2.38
2.38
2.38
0.65
0.1
0.1
0.1
0.1
0.1
10%
0%
0%
3.00
3.00
3.00
0.65
Other Uses
0.01
10
0.02
0.49
0.39
0.25
0.87
0.87
Total LPG
0.40
1.06
1.06
Renewables
Wood
0.58
20
0.51
0.00
0.39
0.25
0.84
084
1.0
1.0
1.0
1.0
0.9
0%
0%
0%
N/A
N/A
N/A
0.65
0%
0%
N/A
N/A
N/A
0.65
Other fuels
Coal + kerosene
0.12
20
0.51
0.00
0.39
0.25
0.81
0.81
1.0
1.0
1.0
1.0
0.9
0%
Totals
10.94
1.05
1.05
(1) Energy service growth factors used to normalize to ABO 97 end-use consumption. Existing shell and new shell growth factors are differentiated in the spreadsbeet for potential future use, but this differentiation is not currently used.
(2) Energy prices in 2010 are 7.67, 5.59, 7.90, and 12.57 $/MMBru (1997 $) for electricity, natural gas. distillate oil, and LPG, respectively.
Other fuels are assumed to cost the same as distillate oil, while renewables are assumed to cost twice as much as natural gas.
(3) All UBCs are taken from the LBNL RBM and LBNL REEPS residential forecasting models.
(4) 1990 residential sector carbon emissions - 253 million metric tons.
(5) Blectricity consumption and prices measured as site energy at 3412 Brus/kWh.
(6) Oil and LPO efficiency costs and savings are assumed to be the same as for natural gas.
(7) Costs of conserved energy are weighted averages up to the cost effective limit, and are expressed in $/MMBru of primary energy.
1. Koomey, LBNL 510/486-5974
[email protected]
Fuel cells
Table C-2.7: Fuel cell calculations for high efficiency/low carbon case
970605
Assume 200kW or smaller phosphoric acid fuel cell units (also could use small advanced gas turbines)
Installed electrical capacity by 2010
5 GW
THIS NUMBER NEEDS TO BE VALIDATED AND CHECKED.
Capacity factor (clect load following)
95%
TWh produced
41.6 TWhe
TWh gas used to produce elect.
925 TWh.f (=TWhe/electrical efficiency)
c emissions from cogen gas use
4.6 MMTC
C emissions displaced by cogen elect
8.6 based on marginal C burden of
207 gC/kWh.e
Not all of the usable heat can be utilized in the buildings
% of usable heat that is utilized
75%
Electricity production rate
1.29 kWh.elect/kWh.usablc thermal output (=45%/35%)
Usable heat
32.4 TWh.thermal
Utilized beat
24.3 TWh.thermal
Sise Energy
Service
Sise
Primary
Water heating
use in high
demand
Cogen heat
Energy
Energy
Carbon
2010
efflow C case
Energy use
(loads)
Loads
distributed
displaced
displaced
saved
Quads site
TWhe or TWh.f
Efficiency
TWh.th
%
TWh.th
TWhe or TWh.f
quads
MMTC
Electricity
0.13
39
90%
35
29%
7.2
8.0
0.08
1.6
Natural gas
0.47
138
55%
76
64%
15.5
28.2
0.28
1.4
Oil
0.05
14
55%
8
7%
1.6
2.9
0.03
0.2
Total
0.66
192
119
100%
24.3
39.1
0.39
3.2
SUMMARY OF COGEN SAVINGS
MMTC
primary E
Electric generation
4.0
0.0
Use of cogen. heat
3.2
0.4
Total
7.3
0.4
(1) TWh.e = TWh of site electricity; TWhf = TWh of direct fuel use; TWh.th = TWh of thermal load.
(2) For details on electricity production rate terminology and other standard cogeneration terms, see
Krause, Florentin. Jonathan Koomey, Hans Becht. David Olivier, Giuseppe Onufrio, and Pierre Radanne. 1994.
Energy Policy in the Greenhouse. Volume II, Part 3C. Fossil Generation: The Cost and Potential of Low-Carbon
Resource Options in Western Europe.
El Cerrito, CA: International Project for Sustainable Energy Paths.
(3) Electrical efficiency of fuel cell = 45% for electricity-only operation. Usable heat from fuel cell is 35% of total fuel input,
leaving 20% of heat being unrecoverable. Of the usable heat, only 75% can be utilized in the buildings.
(4) Temperatures of hot water (-160 deg. F) not high enough for absorption chilling, so we allocate heat to
water heating only (Personal communication with Ron Fiskum 4 June 1997, 202/586-9154).
Water heating loads alone are large enough to cover cogen heat (they are not as seasonal as space heating,
so we prefer them for this analysis). We distribute cogen thermal energy across water heating fuels using same ratio of
loads as found in high efficiency/low carbon case.
(5) Primary energy savings on the electric side are zero because primary energy benefits of cogen all allocated to heating side.
Carbon savings accrue on the electric side because marginal carbon burden is much higher than that of gas fired generation.
Table C-2.6.b (continued): Results for U.S. commercial sector reference and high efficiency cases
65% implementation of efficiency resources
65%
100%
65%
100%
100% Implements don case
65%
100%
65%
100%
Base
Prozen
Baseline
Implement.
Implement.
Frozen
Baseline
Implement.
Implement.
Existing
Retrofit
New
Implement.
Implement.
Base
Promen
BaseMoe
Implement.
Implement.
year
efficiency
B.A.U.
Bffic. case
Effic. case
efficiency
B.A.U.
Effic. case
EMc. case
New
New
New
EMc. case
case
year
efficiency
B.A.U.
Effic. case
Effic. case
energy
energy
energy
energy
energy
energy
energy
energy
energy
efficiency
efficiency
efficiency
total
total
carbon
carbon
carbon
carbon
carbon
use
use
are
use
use
costs
costs
costs
costs
costs
costs
costs
costs
costs
emissions
emissions
emissions
emissions
emissions
1997
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
2010
1997
2010
2010
2010
2010
Fwel
End-use
Quade
Quade
Quade
Quade
Quade
Billion 95$
Billion 95$
Billion 95$
Billion 95$
Billion
95$
Billion
95$
Billion 955
Billion 95$
Billion 95$
MMTC
MMTC
MMTC
MMTC
MMTC
Electricity
Space heating
0.12
0.12
0.12
0.10
0.09
2.50
2.52
2.07
1.83
0.00
0.07
0.06
216
1.97
6
6
6
4
4
Space cooling
0.52
0.53
0.52
0.43
0.38
11.04
10.91
8.96
7.91
0.00
0.29
0.26
9.32
847
26
25
25
19
16
Water heating
0.17
0.16
0.14
0.13
0.13
3.40
2.94
2.80
2.72
0.04
0.03
0.03
286
282
I
1
7
6
6
Ventilation
0.17
0.19
0.19
0.16
0.14
3.91
3.99
3.26
2.87
0.00
0.11
0.10
3.40
3.09
8
9
9
7
6
Cooking
0.03
0.03
0.03
0.03
0.03
0.65
0.63
0.63
0.63
0.00
0.00
0.00
0.63
0.63
I
I
I
1
I
Lighting
1.26
1.32
132
1.14
1.04
27.74
27.69
23.93
21.90
-0.82
-1.04
-0.94
2211
19.10
62
63
63
52
46
Refrigeration
0.14
0.15
0.16
0.13
0.12
3.18
3.36
2.80
250
0.03
0.09
0.00
2.92
2.69
7
7
8
6
5
Office equip.PCs
0.08
0.10
0.10
0.10
0.10
2.10
2.10
2.10
2.10
0.00
0.00
0 00
210
2.10
4
5
5
5
5
Office equip.-non-PCs
0.19
0.25
0.25
0.25
0.25
5.25
5.25
5.25
5.25
0.00
0.00
0.00
5.25
5.25
9
12
12
12
12
Other Uses
0.65
1.08
1.08
0.85
0.72
22.66
22.66
17.81
15.20
1.49
1.12
1.01
20.16
18.82
32
52
52
38
30
Total electric
333
3.93
3.91
3.32
3.00
82.41
82.03
69.61
62.92
0.74
0.67
0.60
70.91
64.93
163
188
187
151
132
Natural gm
Space beating
1.34
1.42
1.36
1.16
1.06
6.42
6.13
5.24
4.76
0.00
0.68
0.61
6.08
6.05
19
21
20
17
15
Space cooling
0.03
0.03
0.03
0.02
0.02
0.14
0.14
0.11
0.09
0.00
0.02
0.02
0.13
0.13
0
0
0
0
0
Water heating
0.48
0.50
0.52
0.47
0.45
2.24
2.35
2.13
2.02
0.29
0.22
0.19
258
2.71
7
7
$
7
6
Cooking
0.19
0.22
0.23
0.23
0.23
0.99
1.04
1.04
1.04
0.00
0.00
0.00
1.04
1.04
3
3
3
3
3
Other Uses
1.29
1.40
140
131
1.26
6.31
6.31
5.90
5.68
0.17
0.13
0.12
6.18
6.10
19
20
20
19
18
Total gas
3.33
3.57
3.54
3.20
3.01
16.10
15.97
14.42
13.59
0.46
1.05
0.94
16.01
16.03
48
52
31
46
44
Distillate oil Space heating
0.19
0.17
0.16
0.14
0.13
0.95
0.87
0.78
0.73
0.00
0.06
0.05
0.85
0.84
4
3
3
3
3
Water heading
0.05
0.05
0.05
0.05
0.03
0.30
0.27
0.27
0.27
0.00
0.00
0.00
0.27
0.28
I
I
I
I
1
Other Uses
0.13
0.14
0.14
0.13
0.13
0.76
0.76
0.71
0.69
0.02
0.01
0.01
0.74
0.73
3
3
3
3
3
Total all
0.37
0.37
0.35
0.32
0.31
2.00
1.90
1.76
1.68
0.02
0.07
0.06
1.86
1.84
7
7
7
6
6
Renewables Biomass
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0
0
0
0
0
Other fuels
Coal + keronene
0.31
0.35
0.34
0.34
0.34
1.88
1.84
1.84
1.84
0.00
0.00
0.00
184
1.84
6
7
7
7
7
Totals
7.34
8.21
8.14
7.18
6.66
102.40
101.74
$7.63
80.03
1.22
1.79
1.61
90.63
84.64
225
254
252
211
188
976
1151
1146
972
879
J. Koomey, LBNL 510/486-5974
1GKoomey
Table C-2.8: Energy use untouched by our scenarios, corrected for stock turnover
Primary
Primary
Primary energy
Primary
Primary
Energy use
Energy use
untouched
Energy use
Energy use
B.A.U
untouched
by efficiency corrected
untouched
untouched
case
by efficiency
for stock turnover
by efficiency
corrected
Quads
Quads
Quads
B.A.U. = 1.0
B.A.U. = 1.0
Fuel
End-use
2010
2010
2010
2010
2010
Residential
Electricity
13.0
2.2
1.9
0.17
0.14
Natural gas
5.6
2.5
2.2
0.45
0.40
Distillate oil
0.8
0.4
0.3
0.49
0.43
Other fuels
1.1
0.5
0.5
0.45
0.42
Total
20.4
5.6
4.9
0.27
0.24
Commercial Electricity
11.4
1.9
1.8
0.17
0.15
Natural gas
3.5
0.7
0.6
0.20
0.18
Distillate oil
0.4
0.1
0.1
0.26
0.17
Other fuels
0.3
0.1
0.1
0.42
0.42
Total
15.6
2.8
2.6
0.18
0.17
Total
Electricity
24.3
4.0
3.6
0.17
0.15
Natural gas
9.1
3.2
2.9
0.35
0.31
Distillate oil
1.1
0.5
0.4
0.41
0.34
Other fuels
1.4
0.6
0.6
0.44
0.42
Total
36.0
8.4
7.5
0.23
0.21
(1) Other fuels includes LPG, renewables, coal, and kerosene.
(2) Untouched energy is that energy use associated with equipment that is not replaced during the 1997-2010 analysis
period and hence is not given the opportunity to upgrade its efficiency to the cost effective level. We do not consider
early retirements because they are usually uneconomic.
(3) We correct the Untouched energy by the ratio of new energy intensities to stock energy intensities in 1997
to determine the amount of energy that will still be untouched after normal stock turnover.
Interlab Study on U.S.
Energy Efficiency and Greenhouse
Gas Emissions
Appendix C-3
Assumptions for Energy
Efficiency Calculations
Residential and Commercial
Sectors
Interlab Study on U.S. Energy Efficiency and Greenhouse Gas Emissions
Definition of Terms
Base Year
The base year of the forecast is 1997. Energy use for the base year is based on the output
from the US DOE's Annual Energy Outlook 1997.
Forecast Period
The forecast period for the study is 1997-2010. This generally allows for the penetration of
commercial or near-commercial high efficiency technologies but is too short a period for
any significant penetration of long-term R&D technologies.
Unit Energy
Unit Energy Consumption (UEC) is the amount of energy required to operate an appliance
Consumption (UEC)
or end-use for a specified period. In our study UEC is either specified in kilowatt-bours/year
and Energy Use
(Kwh). particularly for electric appliances or end-uses, or in million British thermal units
Intensity (EUI)
per year (MMBtu) for non-electric appliances and end-uses. The UEC is often derived from
data published by the US Department of Energy on energy consumption of particular
appliances or equipment measured under DOE test procedures. In our study the UEC will
often be a weighted average over various appliance product classes (for equipment) or of
building types (for space conditioning and lighting). Energy Use Intensity (EUI) is a more
aggregate measure of energy use used by the US Energy Information Administration in
their modeling for the AEO 97 forecast. For the commercial sector it is defined as energy
consumption per unit floor area for the sector as a whole.
Maximum cost-
The maximum cost-effective potential is the highest estimated achievable efficiency
effective potential
savings assuming that 100% of cost-effective efficiency resources (or measures) are applied
to the building, and that only technological constraints hamper the implementation of these
resources. For example the maximum cost-effective potential for residential lighting would
estimate the current amount, type, and use rate of current incandescent lamps and calculate
the efficiency savings if all incandescent lamps that can physically be replaced were replaced
with more efficient bulbs (e.g. compact fluorescent, halogen IR A lamps). This calculation
does not take into account some of the often difficult to calculate transaction costs that
hamper the achievement of maximum cost effective levels of penetration, such as lack of
information or imperfect functioning of particular end-use markets.
Achievable cost-
The achievable cost-effective potential implicitly estimates what fraction of the maximum
effective potential
cost-effective potential is achievable for a specific appliance or end-use. For this study we
(efficiency and high-
scale the maximum cost-effective potential assuming 35%, 50%, and 65% implementation
efficiency cases)
of demand-side resources.
Energy Conversion
All electricity end-use energy is converted to site energy assuming a conversion rate of
Factors
3412 Btus/kWh. When primary energy is shown in the report, it is calculated using the
appropriate conversion factors from the electricity utility chapter.
Inflation corrections
We adjust costs from other sources to 1995$ using chain-type price indices from the
and Discount rate
Statistical Abstract of the US Department of Commerce (US DOC, 1996) for 1995 and
before. The discount rate for the analysis is 7% real.
Incremental capital
The incremental capital cost is the additional first cost to the consumer for purchasing a
cost
high-efficiency appliance or package of efficiency measures for a particular end-use.
Life cycle cost
Life cycle cost is the first cost to a consumer of purchasing a particular appliance or set of
efficiency measures plus the cost for operations and maintenance of the appliance (or
efficiency package) over the useful lifetime of the product.
Cost of conserved
The CCE is a ratio of the incremental capital expenditure (amortized over the lifetime of
energy
the appliance) to the annual energy savings expected from the purchase of the unit. The
CCE is used to evaluate the cost-effectiveness of a high-efficiency appliance or efficiency
package. If the CCE is below the average cost of electricity or natural gas, the measure is
considered to be cost-effective.
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Refrigerators
Product/end-use description
The refrigerator is a major household electric appliance designed for the
refrigerated storage of food products. A refrigerator consists of a refrigerated
cabinet at 0°C or above. Many refrigerators are also equipped with freezer
compartments which are designed for the freezing and storing food at
temperatures below -13.3°C. Several varieties of product classes for
refrigerators exist which can affect energy consumption, including volume,
existence of automatic or manual defrost, and those with the
refrigerator/freezer separated by vertical compartments (top mount) versus
side-by-side separations (US DOE, 1995).
Base Year Energy Use
Refrigeration energy use accounts for an estimated 6% (1.2 quads) of
residential primary energy consumption in 1997 (US ELA. 1996).
End-use Lifetime
The end-use lifetime for refrigerators was estimated at 19 years. This is based
on estimates developed by the Federal government in baseline calculations
for energy efficiency standards (US DOE, 1995).
Average Unit Energy Consumption in
Base year UEC for refrigerator stock was estimated at 944 kWh/year (3.2
1997 (UEC)
MMBtu). This is based on output from the LBL-REM model used in (US
DOE, 1995).
1997 New Product UEC
1997 UEC was estimated at 647 kWh/year (2.2 MMBtu). Current UEC was
based on a shipment weighted average of the UEC of current models, based
on calculations from the LBL-REM model used in US DOE (1995).
Maximum Cost-effective Efficiency
The maximum cost-effective efficiency potential as measured in UEC was
Potential
estimated at 437 kWh/year (1.5 MMBtu), or a savings of 33% from the UEC
of current 1997 models. This UEC was based on the 1992 shipment
weighted average UEC for the lowest life-cycle cost models from US DOE
(1995).
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential efficiency case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level
potential high efficiency case
over the analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The average incremental cost for adopting the maximum cost-effective
efficiency model was estimated to be $73 ($1995). This cost is the difference
between the shipment weighted estimated retail price of the high-efficiency
model and the average retail price for models sold in 1997. Both prices are
based on output from the LBL-REM model. Prices were adjusted to 1995
levels based on the personal consumption price index (US DOC. 1996).
Cost of Conserved Energy (CCE)
The CCE is a ratio of the incremental capital expenditure (amortized over the
lifetime of the appliance) to the annual energy savings expected from the
purchase of the unit. The CCE for the high efficiency model was estimated
at $0.03/kWh ($9.9/MMBtu) ($1995).
References:
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Department of Energy, 1995. Technical Support Document: Energy Efficiency Standards for Consumer Products:
Refrigerators, Refrigerator-Freezers, & Freezers. U.S. DOE, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/EIA-0383(97). U.S. Department of Energy, Washington, DC.
B-3.2
Refrigerator UEC and CCE calculations
Source: U.S. Department of Energy. 1995. Technical Support Document: Energy Efficiency Standards for Consumer Products: Refrigerators, Refrigerator-Freezers, & Freezers.
New Moxlel
New Buscline
Baseline Retail
UHC
Lowest LCC
Lowest LCC UEC
Shipments (1992)
Percent of
Product Class
($1992)
(kWh/year)
Retail ($1992)
(kWh/year)
Millions
Shipments
Top Mount Auto Defrost - No thru the door features
$
554.67
7(00.86
$
651.50
436.66
505
65.0%
Top Mount Auto Defrost - thru the door features
$
1,047.28
795.37
$
1,174.66
548.81
0.09
1.2%
Side-by-side Auto Defrost - No thru the door features
$
1,055.08
761.19
$
1,165.75
552.98
0.65
8.3%
Side-by-side Auto Defrost - thru the door features
$
1,161.51
799.9
$
1,278.57
508.33
0.85
10.9%
Bottom Mount Auto Defrost
$
908.95
714.81
$
1,021.93
472.43
0.09
1.1%
Compact Manual Defrost
$
156.20
315
$
158.64
295.29
1.06
13.6%
Total (or weighted average)
$
617.76
665.47
$
705.66
436.60
7.78
Baseline Retail
Baseline UEC
Lowest LCC
Lowest LCC UEC
Shipments (1992)
Percent of
Product Class
($1995)
(MMHtu/year)
Retail ($1995)
(MMBtu/year)
Millions
Shipments
Top Mount Auto Defrost - No thru the door features
$
596.82
2.39
$
701.01
1.49
5.05
65.0%
Top Mount Auto Defrost - thru the door features
$
1,126.87
2.71
$
1,263.93
1.87
0.09
1.2%
Side-by-side Auto Defrost - No thru the door features
$
1,135.27
2.60
$
1,254.35
1.89
0.65
8.3%
Side-by-side Auto Defrost - thru the door features
$
1,249.78
2.73
$
1,375.74
1.73
0.85
10.9%
Bottom Mount Auto Defrost
$
978.03
2.44
$
1,099.60
1.61
0.09
1.1%
Compact Manual Defrost
$
168.07
1.07
$
170.70
1.01
1.06
13.6%
Total (or weighted average)
$
664.71
2.27
$
759.29
1.49
7.78
100.0%
CCE
CCE
kWh
MMBtu
Percent Savings
Retail price ($1992)
Retail price ($1995)
($1995/kWh)
($1995/MMBiu)
Notes
Blu conversion is 3412
n/a
n/a
n/a
n/a
btu/kWh resource
Average Stock in 1997 (LBNL-REM runs for DOE, 1995)
944
3.2
n/a
1997 New Refrigerator (LBNL-REM runs for DOE, 1995)
647
22
n/a
$
637.40
$
685.84
n/a
n/a
Lowest weighted LCC model
Maximum cost-effective energy efficienct refrigerator (DOE, 1995)
437
1.5
n/a
$
705.66
$
759.29
n/a
n/a
from DOE, 1995
Increase in Capital
Increase in Capital
Energy, Cost, and UEC comparison
kWh
MMBtu
Percent Savings
Costs ($1992)
Costs ($1997)
Max. cost effective compared to 1997 new
210
0.7
32.5%
$
68.26
$
73.44
$
0.034
$
9.90
CCH Calculation Assumptions
Capital recovery factor
$0.10
Real discount rate
0.07
Lifetime
19
6/6/97
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Freezers
Product/end-use description
The freezer is a household electric appliance designed for the freezing and
storing food at temperatures below -13.3°C. Several varieties of product
classes for freezers exist which can affect energy consumption, including
volume, existence of automatic or manual defrost, and an upright versus
chest configuration. (US DOE, 1995)
Base Year Energy Use
Energy use by freezers account for an estimated 2% (0.4 quads) of residential
primary energy consumption in 1997. (US EIA, 1996)
End-use Lifetime
The end-use lifetime for freezers was estimated at 19 years. This is based on
estimates developed by the Federal government in baseline calculations for
energy efficiency standards. (US DOE, 1995)
Average Unit Energy Consumption in
Base year average UEC was estimated at 599 kWh/year (2.0 MMBtu). This
1997 (UEC)
is based on output from the LBL-REM model used in (US DOE, 1995)
adjusting for the inclusion of compact freezers.
1997 New Product UEC
1997 new unit UEC was estimated at 455 kWh/year (1.6 MMBtu). Current
UEC was based on a shipment weighted average of the UEC of current
models, based on calculations from the LBL-REM model used in (US DOE,
1995) Compact freezers were also weighted in this calculation.
Maximum Cost-effective Efficiency
The maximum cost-effective efficiency potential as measured in UEC was
Potential
estimated at 328 kWh/year (1.1 MMBtu), or a savings of 28% from the
current 1997 models. This UEC was based on calculating the 1992
shipment weighted average UEC for the lowest life cycle cost models from
(US DOE, 1995).
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential - Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level
potential - High Efficiency Case
over the analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The average incremental cost for adopting the maximum cost-effective
efficiency model was estimated to be $59 ($1995). This cost is the
difference between the shipment weighted estimated retail price of the high-
efficiency model and the average retail price for models sold in 1997. Both
prices are based on output from the LBL-REM model. Prices were adjusted
to 1995 levels based on the personal consumption price index (US DOC,
1996).
Cost of Conserved Energy
The CCE is a ratio of the incremental capital expenditure (amortized over
the lifetime of the appliance) to the annual energy savings expected from
the purchase of the unit. The CCE for the high efficiency model was
estimated at $0.05/kWh ($13.2/MMBtu).
References:
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Department of Energy, 1995. Technical Support Document: Energy Efficiency Standards for Consumer Products:
Refrigerators, Refrigerator-Freezers, & Freezers. U.S. DOE, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/EIA-0383(97). U.S. Department of Energy, Washington, DC.
B-3.3
Freezer UEC and CCE Calculations
Source: U.S. Department of Energy. 1995. Technical Support Document: Energy Efficiency Standards for Consumer Products: Refrigerators, Refrigerator-Freezers, & Freezers.
Baseline Retail
Baseline UEC
Lowest LCC
Lowest LCC UEC
Shipments (1992)
Percent of
Product Class
($1992)
(kWh/year)
Retail ($1992)
(kWh/year)
Millions
Shipments
Upright Auto Defrost
$
451.11
759.24
$
544.43
5318
0.16
10.5%
Upright Manual Defrost
$
379.63
482.94
$
405.29
328
0.47
31.7%
Chest Manual Defrost
$
356.37
471.72
$
395.69
324.43
0.60
40.4%
Compact Freezer Chest (Manual Defrost)
$
220.15
253.43
$
248.35
186.47
0.20
13.7%
Compact Freezer - Upright (Manual Defrost)
$
249.23
410.71
$
269.66
306.22
0.06
3.7%
Total (or weighted average)
$
350.98
473.19
$
389.40
327.69
1.49
100.0%
Baseline Retail
Bascline UEC
Lowest LCC
Lowest LCC UEC
Shipments (1992)
Percent of
Product Class
($1995)
(MMBtu/year)
Retail ($1995)
(MMBtu/year)
Millions
Shipments
Upright Auto Defrost
$
485.39
2.59
$
585.81
1.81
0.16
10.5%
Upright Manual Defrost
$
408.48
1.65
$
436.09
1.12
0.47
31.7%
Chest Manual Defrost
$
383.45
1.61
$
425.76
1.11
0.60
40.4%
Compact Freezer Chest (Manual Defrost)
$
236.88
0.86
$
267.22
0.64
0.20
13.7%
Compact Freezer Upright (Manual Defrost)
$
268.17
1.40
$
290.15
1.04
0.06
3.7%
Total (or weighted average)
$
377.66
1.61
$
419.00
1.12
1.49
100.0%
CCE Calculation
Retail price
CCE
CCE
kWh
MMBtu
Percent Savings
Retail price ($1992)
($1995)
($1995/kWh)
($1995/MMBtu)
Notes
Assumes 15% share of compact
freezers. Btu conversion is 3412
Average Stock in 1997 (LBNL-REM runs for DOE, 1995)
599.42
2.0
n/a
n/a
n/a
n/a
n/a
btu/k Wh resource
Weighted for addition of compact
1997 New Refrigerator (LBNL-REM runs for DOE, 1995)
455.41
1.6
n/a
$
334.18
$
359.58
n/a
n/a
freezers
Maximum cost-effective energy efficient (DOE, 1995)
327.69
1.1
n/a
$
389.40
$
419 00
n/a
n/a
Lowest LCC from DOE, 1995
Increase in Capital
Increase in Capital
Energy, Cost, and UEC comparison
kWh
MMBtu
Percent Savings
Costs ($1992)
Costs ($1997)
Max. cost effective compared to 1997 new
127.71
0.4
28%
$
55.22
$
59.42
$
0.045
$
13.19
CCE Calculation Assumptions
Capital recovery factor
$0.10
Real discount rate
0.07
Lifetime
19
Freezer stock assumptions
Compact Freezer Share in 1997 stock
17%
Non-Compact Freezer Share in 1997 stock
83%
6/6/97
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Electric Water Heating
Product/end-Use description
Water heaters are products that utilize oil, gas, LPG, or electricity to heat
potable water for use outside the heater upon demand. Hot water is used to
provide a variety of services in a household. Most hot water heaters are
storage heaters consisting of a cylindrical insulated storage tank with
electric heating elements or a gas burner. Several appliances or products use
hot water, primarily showerheads and faucets, clothes washers, and
dishwashers. Reductions in water heating energy use can be achieved both
through improvements in the water heating device as well as improvements
in the efficiency of hot-water using appliances, thereby reducing the source
demand for the hot water. (DOE, 1993)
Base Year Energy Use
Electric water heating accounts for an estimated 6% (1.1 quads) of
residential primary energy consumption in 1997. (Source: US EIA. 1996)
End-use Lifetime
The end-use lifetime for electric water heaters was estimated at 10 years.
This is based on estimates developed by the Federal government in baseline
calculations for energy efficiency standards. (US DOE, 1993)
Existing Average Unit Energy
Base year average UEC for electric water heaters in 1997 was estimated at
Consumption (UEC)
4924 kWh (16.8 MMBtu). This estimate is derived from Koomey et al.
(1997).
1997 New UEC
1997 new unit UEC for electric water heaters is 3899 kWh (13.3 MMBtu).
The new unit UEC accounts for the implementation of the Federal 1990
water heater standards and the Federal 1994 standards on showers and
faucets. dishwashers and clotheswashers (Koomey et al., 1994).
B-3.4
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Electric Water Heating (Continued)
Maximum Cost-effective Efficiency
The maximum cost-effective efficiency potential as measured in UEC was
Potential
estimated at 2822 kWh/year (9.6 MMBtu), or a savings of 28% from the
current 1997 models. This UEC was calculated as a stock weighted of four
"efficiency" packages modeled for residences: (1) a high-efficiency electric
water heater (equipped with features to reduce standby losses) combined with
a horizontal axis clothes washer (EWH w/ CW), (2) a high-efficiency
electric water heater without a clothes washer (EWH w/o CW), (3) a heat
pump water heater combined with a horizontal axis clothes washer (HPWH
w/ CW), and (4) a heat pump water heater without a clothes washer (HPWH
w/o CW). In addition, we assume a clothes washer saturation of 81% in
2010, and that of all electrically water-beated households in 2010 (less than
half of all households), 25% of these can be converted to a heat pump water
heater (Koomey et al., 1997). The summary table for this potentials
calculation is shown below.
Summary Table 1: Maximum Cost Effective Efficiency Potential Water
Heaters
EWHH
IES
IES
Savings
IC
(%)
(Kwh)
(MMBtu)
(%)
($1995)
EWH w/ CW
61%
647
2.2
17%
231
EWH w/o CW
14%
286
1.0
7%
49
HPWH. w/CW
20%
2607
8.9
67%
688
HP WH w/o CW 5%
2423
8.3
62%
507
Total/Wtd
Average
100%
1077
3.7
28%
311
Notes: EWHH = households with electric water heating, IES = incremental
energy savings, IC = incremental cost, CW = clothes washers, HP WH =
heat pump water heaters.
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential - Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level
potential - High Efficiency Case
over the analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The average incremental cost for adopting the high-efficiency packages was
estimated to be $311 ($1995). The incremental costs, (listed in summary
table 1 above for each package) represent the difference in cost between the
purchase of a high efficiency package (e.g. high efficiency electric water
heaters, heat pump water heaters, and horizontal axis clothes washers)
compared to new 1997 equipment (Koomey et al., 1997). Prices were
adjusted to 1995 levels based on the personal consumption price index (US
DOC, 1996).
Cost of Conserved Energy
The CCE for the average high efficiency package was the product of the
weighted estimated CCEs for the four maximum cost effective efficiency
potential packages as described above, and was estimated at $0.032/kWh
($9.41/MMBtu). The CCE is a ratio of the incremental capital expenditure
(amortized over the lifetime of the appliance) to the annual energy savings
expected from the purchase of the unit. The CCE for water heating includes
the present value of the water savings from the use of horizontal axis
clothes washers.
B-3.5
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Electric Water Heating (Continued)
References:
Koomey, Jonathan G., Dunham, Camilla, and Lutz, Jim. 1994. The effect of Efficiency Standards on Water Use and Water
Heating Energy Use in the U.S.: A Detailed End-use Treatment. Lawrence Berkeley National Laboratory. LBNL-35475.
Koomey, Jonathan G., Diana A. Vorsatz, Richard E. Brown, and Celina S. Atkinson. 1997. Updated Potential for Electricity
Efficiency Improvements in the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38894. in process.
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Department of Energy, 1993. Technical Support Document: Energy Efficiency Standards for Consumer Products: Room
Air Conditioners, Water Heaters, Direct Heating Equipment, Mobil Home Furnaces, Kitchen Ranges and Ovens, Pool Heaters,
Flourescent Lamp Ballasts. and Television Sets. US DOE, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/E1A-0383(97). U.S. Department of Energy, Washington, DC.
B-3.6
Electric Water Heating. UEC and cost calculations
Source:
U.S. Department of Energy. 1990. Technical Support Document: Energy Conservation Standards for Consumer Products:
Room A/C. Water Heaters. Direct Heating Equip. mobil home furn. kitchen ranges. pool heaters. floures lamp ballasts. and TVs.
Source:
Koomey. Jonathan G., Diana A. Vorsatz. Richard E. Brown and Celina S.Atkinson. 1997. Updated Potential for Electricity
Efficiency Improvements in the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38894. in process
kWh
MMBas
1990 dollars
1995 dollars
Average Stock Water beating UEC from Koomey et al., 1
4924
16.8
Determination of 1997 New Unit efficiency from Koomey et al., 1997
Incremental
Incremental
Fraction of
energy Savings
energy Savings
Incremental
Incremental
CCE
New UEC
Current Electric
Measure
(KWb)
(MMBa)
Cost ($1990)
Cost ($1995)
($1990/kWb)
(KWb)
WH Stock
(a) Electric Water Heater - Baseline
0
0
$
-
$
-
n/a
4786
100%
(b) Improve clothes washers to 1994 standard
199
0.7
$
2.00
$
2.32
-0.009
4587
100%
(c) Improve aerators and showerbeads to 1994 standard
586
2.0
$
53.00
s
61.39
-0.004
4001
100%
(d) Improve dishwashers to 1994 standard
102
0.3
$
21.00
$
24.32
0.016
3899
100%
kWb
MMBa
New Water Heater UEC in 1997 from Koomey et al.,
1997 (measures (a) thru (d))
3899
13.3
Determination of Maximum cost-effective efficiency from Koomey et al- 1997
High Efficiency Electric WITH CLOTHES
WASHERS
Incremental
Incremental
energy Savings
energy Savings
Incremental
Incremental
CCE
New UEC
Measure
(KWb)
(MMBai)
Cost ($1990)
Cost ($1995)
($1990/kWb)
(KWb)
(a) Electric Water Heater - Baseline (1997 new UEC)
0
0
$
-
$
-
n/a
3899
(b) Reduce water beater standby losses
286
1.0
$
42.98
$
49.78
$
0.018
3613
(c) Horizontal axis clothes washer w/ EWH
361
1.2
s
156.49
$
181.25
$
0.032
3252
Total
647
2.21
$
199.47
s
231.03
$
0.026
3252
High Efficiency Electric WITHOUT CLOTHES
WASHERS
Incremental
Incremental
energy Savings
energy Savings
Incremental
Incremental
CCE
New UEC
Measure
(KWb)
(MMBw)
Cost ($1990)
Cost ($1995)
($1990/kWb)
(KWb)
(a) Electric Water Heater - Baseline (1997 new UEC)
0
0
$
-
$
-
n/a
3899
(b) Reduce water beater standby losses
286
1.0
$
42.98
$
49.78
$
0.018
3613
Total
286
0.98
$
42.98
$
49.78
$
0.018
3613
Heat Pump Water Heaters WITH CLOTHES
WASHERS
Incremental
Incremental
energy Savings
energy Savings
Incremental
Incremental
CCE
New UEC
Measure
(KWb)
(MMBtu)
Cost ($1990)
Cost ($1995)
($1990/kWb)
(KWh)
(a) Electric Water Heater Baseline (1997 new UEC)
0
0
$
-
$
-
n/a
3899
(b) Reduce water heater standby losses
286
1.0
$
42.98
$
49.78
S
0.018
3613
(c) Heat pump water beater - post 2000
2137
7.3
$
395.00
$
457.50
$
0.039
1476
(d) Horizontal axis clothes washer w/ HPWH- post 2000
184
0.6
$
156.49
$
181.25
$
0.062
1292
Total (weighted by share of stock in measure (d))
2607
8.9
$
594.47
$
688.53
$
0.038
1292
Heat Pump Water Heaters WITHOUT CLOTHES
WASHERS
Incremental
Incremental
energy Savings
energy Savings
Incremental
Incremental
CCE
New UEC
Measure
(KWh)
(MMBw)
Cost ($1990)
Cost ($1995)
($1990/kWb)
(KWb)
(a) Electric Water Heater - Baseline (1997 new UEC)
0
0
s
-
$
-
n/a
3899
(b) Reduce water beater standby losses
286
1.0
$
42.98
$
49.78
$
-0.018
3613
(c) Heat pump water beater - post 2000
2137
7.3
s
395.00
$
457.50
$
0.039
1476
Total (weighted by share of stock in measure (d))
2423
8.3
$
437.98
$
507.28
$
0.037
1476
6/6/97
Share of
Share of
Saturation Max
Saturation High
electricity only.
electricity only
Shares
Baseline (1997)
econ. case
efficiency case
no constraints
Max econ. case
Non electric water hearting
55.5%
55.5%
55.5%
Baseline electric water healthe
44.5%
0.04
0.0%
0%
0.0%
High Efficiency Eleark WTTH CLOTHES WASHERS
15.7%
27.04
35.3%
60.7%
High Efficiency Electric WITHOUT CLOTHES
WASHERS
3.7%
6.4%
8.3%
14.3%
Heat Pump Water Heaters WITH CLOTHES WASHERS
20.3%
9.0%
45.6%
20.2%
Heat Purp Water Heaters WITHOUT CLOTHES
WASHERS
4.8%
21%
10.8%
4.8%
Total
100%
100%
100%
100.0%
100.0%
Clothes washer saturation (for both cases)
80.9%
High efficiency electric fraction
43.6%
75.0%
Heat pump fraction
56.4%
25.0%
Fraction affected by policies in high efficiency case
100.0%
Max econ. potential case
Incremental
Incremental
% Savings
Internally
energy Savings
energy Savings
relative to New
Incremental Cost
CCE
CCE ($1995/
calculated CCE
Summary Table
(KWh)
(MMBni)
1997 UEC
($1995)
($1995/kWh)
MMBor)
($1995/kWh)
Notes
also include detergent and
water savings which
makes our internally
High Efficiency Electric WITH CLOTHES
calculated CCEs 100 high
WASHERS
647
22
17%
231
0.030
8.76
0.051
in the case where the
High Efficiency Electric WITHOUT CLOTHES
Bm conversion is 3412
WASHERS
286
1.0
7%
50
0.0208
6.11
0.0248
back Wh resource
Heat Pump Water Heaters WITH CLOTHES
WASHERS
2607
8.9
67%
689
0.044
13.01
0.054
Heat Pump Water Heaters WITHOUT CLOTHES
WASHERS
2423
8.3
62%
507
0.042
12.40
0.047
Weighted average NO CONSTRAINTS
1703
5.8
44%
454
0.037
10.87
0.050
Weighted average MAX ECON POTENTIAL
1077
3.7
28%
311
0.032
9.41
0.040
Max Tech Efficiency LEC
2822
9.6
Internal note: WE MUST USE THE SUPPLY CURVES CCE IN THE INTEGRATING SPREADSHEET.
CCE Calculation Assumptions
Capital recovery factor
$0.14
Real discount rate
0.07
Lifetime
10
6/6/97
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Gas/Oil/LPGWater Heating
Product/end-Use description
Water heaters utilize oil, gas, LPG, or electricity to heat potable water for
use outside the heater upon demand. Hot water is used to provide a variety
of services in a household. Most hot water heaters are storage heaters
consisting of a cylindrical insulated storage tank with electric heating
elements or a gas burner. Several appliances or products use hot water,
primarily showerheads and faucets, clothes washers, and dishwashers.
Reductions in water heating energy use can be achieved both through
improvements in the water heating device as well as improvements in the
efficiency of hot-water using appliances, thereby reducing the source
demand for the hot water. For our analysis we have chosen to develop
forecasts based on gas water heaters only since oil and LPG water heaters
have roughly the same per-unit energy use (US DOE, 1993).
Base Year Energy Use
Gas, oil, and LPG water heaters account for an estimated 7.5% (1.4 quads)
of residential primary energy consumption. (Source: US EIA, 1996)
End-use Lifetime
The end-use lifetime for gas water heaters was estimated at 13.9 years. This
is based on estimates developed by the Federal government in baseline
calculations for energy efficiency standards. (US DOE, 1990)
Existing Average Unit Energy
Average UEC for gas water heaters in 1997 is 33.55 MMBtu. This
Consumption (UEC)
estimate is derived from Koomey et al., 1997.
997 New UEC
1997 new UEC for gas/oil/LPG water heaters is 29.7 MMBtu. This
estimate is derived from Koomey et al., 1997. The new UEC accounts for
the implementation of the federal 1990 water heater standards and the federal
1994 standards on showers and faucets, dishwashers and clotheswashers.
Maximum Cost-effective Efficiency
The maximum cost-effective efficiency potential as measured in UEC was
Potential
estimated at 23 MMBtu, or a savings of 23% from the current 1997
models. It was determined that the inclusion of a horizontal axis clothes
washer as an efficiency measure was not cost effective with gas water
heaters, therefore, the maximum efficiency gas water heater package
includes measures that reduce standby losses and an electric ignition and flue
damper only.
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential - Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level
potential - High Efficiency Case
over the analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The incremental cost for adopting the high-efficiency model was estimated
to be $126 ($1995). This cost is the incremental cost between the purchase
of high efficiency equipment compared to new 1997 equipment (Koomey et
al., 1997). Prices were adjusted to 1995 levels based on the personal
consumption price index (US DOC, 1996).
Cost of Conserved Energy
The CCE for the high efficiency model was estimated at $2.15/MMBtu
($1995). The CCE is a ratio of the incremental capital expenditure
(amortized over the lifetime of the appliance) to the annual energy savings
expected from the purchase of the unit
B-3.7
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Gas/Oil Water Heating (continued)
References:
Koomey, Jonathan G., Marla C. Sanchez, Diana Vorsatz, Richard E. Brown, and Celina S. Atkinson. 1997. The Potential for
Natural Gas Efficiency Improvements in the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38893.
in process.
U.S. Department of Commerce. 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Department of Energy, 1993. Technical Support Document: Energy Efficiency Standards for Consumer Products: Room
Air Conditioners, Water Heaters, Direct Heating Equipment, Mobil Home Furnaces, Kitchen Ranges and Ovens, Pool Heaters,
Flourescent Lump Ballasts, and Television Sets. (DOE/EE-0009) U.S. DOE, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/EIA-0383(97). U.S. Department of Energy, Washington, DC.
B-3.8
Gas/Oil Water Heating, UEC and cost calculations
Source:
U.S. Department of Energy. 1993. Technical Support Document: Energy Conservation Standards for Consumer Products:
Room A/C. Water Heaters. Direct Heating Equip. mobil home furn, kitchen ranges, pool heaters, floures lamp ballasts. and TVs.
Source: Koomey. Jonathan G., Marla C. Sanchez, Diana Vorsatz, Richard E. Brown, and Celina S. Atkinson. 1997.
The Potential for Natural Gas Efficiency Improvements in the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38893. in process.
MMBtu
1990 dollars
1997 dollars
Average Stock Water heating UEC from Koomey et al.,
1997
33.55
Determination of 1997 New Unit efficiency from Koomey et al, 1997
Incremental
Fraction of
energy Savings
Incremental Cost
Incremental Cost
CCE
New UEC
Current Gas
Measure
(MMBtu)
($1990)
($1995)
($1990/MMBtu)
(MMBtu)
WH Stock
(a) Gas Water Heater - Baseline
0
S
-
$
-
n/a
36.9
100%
(b) Improve clothes washers 10 1994 standard
1.09
$
2.00
$
2.32
-1.7
35.8
100%
(c) Improve aerators and showerheads to 1994 standard
2.5
S
53.00
$
61.39
-0.9
33.3
100%
(d) Improve dishwashers to 1994 standard
3.6
$
21.00
$
24.32
3.6
29.7
100%
MMBtu
New Water Heater UEC in 1997 from Koomey et al-,
1997 (measures (a) thru (d))
29.7
Determination of Maximum cost-effective efficiency from Koomey et al., 1997
High Efficiency Gas WITH CLOTHES WASHERS
Incremental
energy Savings
Incremental Cost
Incremental Cost
CCE
New UEC
Measure
(MMBtu)
($1990)
($1995)
($1990/MMBtu)
(MMBtu)
(a) Gas Water Healer - Baseline (1997 new UEC)
0
s
-
$
-
n/a
29.7
(b) Reduce water heater standby losses
2.052
$
24.00
$
27.80
$
1.300
27.648
(c) Install electric ignition and flue damper
4.69
$
85.00
s
98.45
S
2.100
22.958
(d) Horizontal axis clothes washer w/ EWH
1.06
$
131.00
$
151.73
$
7.900
21.898
Total
7.802
$
240.00
$
277.98
$
2.678
21.898
Wid avg no horizontal axis $
1.857
High Efficiency Gas WITHOUT CLOTHES
WASHERS
Incremental
energy Savings
Incremental Cost
Incremental Cost
CCE
New UEC
Measure
(MMBtu)
($1990)
($1995)
($1990/MMBtu)
(MMBtu)
(a) Gas Water Heater - Baseline (1997 new UEC)
0
$
-
$
-
n/a
29.7
(b) Reduce water heater standby losses
2.052
$
24.00
$
27.80
$
1.300
27.648
(c) Install electric ignition and flue damper
4.69
$
85.00
S
98.45
$
2.100
22.958
Total
6.74
$
109.00
$
126.25
$
1.857
22.958
Share of gas
Saturation Max
only.- Max tech
Shares
Baseline (1997)
tech econ. case
case
Electric water heating
44.5%
44.5%
Baseline GAS water heating
55.5%
0.0%
0%
High Efficiency GAS W/or W/O CLOTHES WASHERS
55.5%
100.0%
Horizontal axis measure not cost effective.
Total
100%
100%
100.0%
therefore we do not distinguish between homes
have clothes washers and those that don't
Clothes washer saturation (for both cases)
80.9%
High efficiency GAS fraction
100.0%
Non high efficiency GAS
0.0%
Fraction affected by policies in high efficiency case
100.0%
Max econ. potential case
6/6/97
Incremental
% Savings
Internally
energy Savings
relauve to New
Incremental Cost
CCE
calculated CCE
(MMBru)
1997 UEC
(S1995)
(S1995/MMBtu)
(S1995/MMBru)
Notes
Summary Table
High Efficiency Gas WITH CLOTHES WASHERS
6.742
23%
126
2.150
2.150
High Efficiency Gas WITHOUT CLOTHES
6.74
23%
126
2.150
2.150
WASHERS
Max Tech Efficiency UEC
23.0
& savings relative 10 1997 new unit
23%
Internal note: WE MUST USE THE SUPPLY CURVES CCE IN THE INTEGRATING SPREADSHEET.
CCE Calculation Assumptions
Capital recovery factor
$0.11
Real discount rate
0.07
Lifetime
13.9
6/6/97
Background Information Sheet: Interlab Study on
U.S. Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Clothes Dryers (Electric)
Product/end-use description
The clothes dryer is a cabinet-like appliance designed to dry fabrics in a tumble-
type drum with forced-air circulation. The heat source may be either electricity or
natural gas. Electricity is used by the drum and fan motors. Improved clothes
washer efficiency, particularly measures that reduce the moisture content of washed
clothes, reduce clothes drying energy use since less run time is needed for drying
(US DOE, 1990)
Base Year Energy Use
Electric clothes dryers account for an estimated 3% (0.6 quads) of residential
primary energy consumption in 1997. (Source: USELA, 1996)
End-use Lifetime
The end-use lifetime for clothes dryers was estimated to be 17 years. This is based
on data provided by the Association of Home Appliance Manufacturers. (US DOE,
1990)
Existing Average Unit Energy
Base year UEC was estimated at 881 kWh/year (3.0 MMBtu) for electric. This
Consumption (UEC)
average is based on (Koomey et al., 1997)
1997 New UEC
1997 new UEC was estimated at 830 kWh/year (2.8 MMBtu) for electric clothes.
This new unit UEC accounts for the implementation of the federal 1994 standards
on clothes dryers.
Maximum Cost-effective Efficiency
For electric clothes dryers the maximum cost-effective efficiency potential as
Potential
measured in UEC was estimated at 813.5 kWh/year (2.8 MMBtu), or a savings of
2% from the current 1997 models. This maximum cost-effective estimate was a
sales weighted estimate that assumes that from 2005 to 2010 heat pump clothes
dryers capture 15% of the new clothes dryers market. Part of the low savings
potential is a result of reduced moisture content of washed clothes based on
improvements in clothes washers over the forecast period (Koomey et al., 1997).
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential - Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level over the
potential - High Efficiency Case
analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The incremental cost for adopting the high-efficiency model was estimated to be
$72 ($1995). This cost is the incremental cost between the purchase of a heat
pump clothes dryer compared to new 1997 equipment (Koomey et al., 1997a).
Prices were adjusted to 1995 levels based on the personal consumption price index
(US DOC, 1996).
Cost of Conserved Energy
The CCE for the high efficiency model was estimated at $0.04/kWh
($11.1/MMBtu). The CCE is a ratio of the incremental capital expenditure
(amortized over the lifetime of the appliance) to the annual energy savings
expected from the purchase of the unit.
References:
Koomey, Jonathan G., Diana A. Vorsatz, Richard E. Brown, and Celina S. Atkinson. 1997. Updated Potential for Electricity
Efficiency Improvements in the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38894. in process.
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Department of Energy, 1990. Technical Support Document: Energy Conservation Standards for Consumer Products:
Dishwashers, Clothes Washers, and Clothes Dryers. (DOE/CE-0299P). U.S. DOE, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/EIA-0383(97). U.S. Department of Energy, Washington, DC.
B-3.9
Clothes drying (electric) LEC and cost calculations
Source: U.S. Department of Energy. 1990. Technical Support Document: Energy Conservation Standards for Consumer Products: Disbweshers. Clothes Washers. and Clothes Dryers.
Source:
Koomey. Jousthan G_ Diana A Vorame. Richard E Brown. and Celias S.Atkinson 1997. Updated Potential for Electricity
Efficiency Improvements is the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38894. is process
two
MMBa
1990 dollars
1995 dollars
Average Stock Waser heating LEC from Koomey a al., IS
$80.7
3.0
Bar conversion is 10800 book Wh resource
Determination of 1997 Sex Unit efficiency from Koomey of al, 1997
Incremental
Incremental
Fraction of
energy Savings
energy Savings
Incremental
Incremental
CCE
New UEC
Current Electric
Measure
(KWh)
(MMBa)
Con ($1990)
Con ($1995)
($1990/kWh)
(KWh)
WH Stock
(a) Electric Water Heater Baseline
0
0
$
$
S
901
100%
(b) Improve clothes divers to 1994 NAECA standard
73
0.2
$
31.96
$
37.02
0.045
830
100%
kwh
MMBa
New Water Benter LEC in 1997 from Koomey of al.
1997 (measures (a) thre (d))
830
18
Determination of Maximum cost-affective efficiency from Koomey at al. 1997
Bigh Efficiency Electric dothes driers
Incremental
Incremental
Internally
energy Savings
energy Savings
Incremental
Incremental
CCE
CCE
calculated CCE
Measure
(KWh)
(MMBru)
Cost ($1990)
Coa ($1995)
($1990/kh)
($1995/kWh)
New (EC (KWh)
($1995/843)
(a) Electric cloches diver Basefier 1997 new LEC
0
0
$
$
n/a
a/s
830
a/a
the Hea: purp riches drver
286
1.0.
$
330 60
$
382.92
$
0 065
$
0 08
E
014
Towl
286
098
$
330.60
$
382.92
$
0 065
s
0.075
544
Weighted
Securation in
Meximum cost-affective efficiency case: 2010
2010
Share in 1997
Share is 2005
Share in 2010
Notes
(a) Electric clothes drver- Baseline (1997 new L'EC)
94.2%
100%
100%
85%
Assumes that beat pump clothes drvers are produced for 15% of the mar ket
(b) Hear DUTED clothes drver
5.8%
0%
0%
15%
beginning in 2005
Incremental
Incremental
% Savings
Energy Savings
Energy Savings
relative to New
Incremental
CCE
CCE ($1995/
Semmary Table
(KWh)
(MMBru)
1997 LEC
Cost (51995)
($1995/kWh)
MMBai)
1997 new
830
2.8
a/a
a/a
a/s
p/o
2010 high efficiency electric
0
0.0
04
0
0.000
0.00
2010 heat pemp clothes dryers
286
10
34%
382.92
00753
22.06
Weighted average max econ. potential
16.5
0.1
24
22.09
Mar Tech Efficiency LEC
$13.5
28
Cost of Conserved Energy (CCE) calculation
Capital recevery factor
$0.10
Real discount rase
0.07
Lifetime
17
Background information from LBNL REM output and AHAM Fact book. 1996
Rasil price
Retail price
CCE
CCE
From LBNL-REM
kwh
MMBru
Percent Savings
($1990)
($1995)
($1995/kWh)
($1995/MMB))
Notes
Assumes 15% share
of compact freezers
Bau conversion is
3412 bee/k Wh
Average Stock in 1997 :LBNL-REM
902.0
31
p/o
p/a
n/a
p/a
n/s
resource
addtion of compact
1997 New (LBNL-REM. AHAM fact book)
7920
2.7
S
289.0
$
334.78
a/a
S
freezers
Maximum cost-effective energy efficience (new unit UEC.
Lowest LCC from
REM 7% case in 2010)
597.0
2.0
n/a
356.1
$
412.45
a/a
a/a
DOE, 1995
Increase is
Increase in
MMBu
Capital Costs
Capital Costs
Eacrgy Cost. and L'EC comparisos
twh
(primary)
Percept Savings
($1992)
($1997)
Mar. COST effective compared to 1997 new
195.00
0.7
25%
$
67.06
$
7215
$
0.04
$
11.11
REM run assumes that Hor. Axis clothes washers are slowly phased in resulting is reduced moisture costent of clothes and low drying energy requirements
LBNL REM ourput
Clothes dryer saturation (for both cases)
1990
1997
2010
Electric
53%
56%
59%
Gas
16%
17%
18%
None
31%
27%
23%
Total
100%
100%
100%
New Clothes dryer installation is existing & new stock
(millions)
1990
1997
2010
Electric
3469
3.771
4.468
Gas
1.102
1.157
1.385
Towl
4571
4.928
5.853
New Clothes drver installation in existing & new stock
(percent share)
Electric
76%
77%
76%
Gas
24%
23%
24%
6/6/97
Background Information Sheet: Interlab Study on
U.S. Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Clothes Dryers (Gas)
Product/end-use description
The clothes dryer is a cabinet-like appliance designed to dry fabrics in a
tumble-type drum with forced-air circulation. The heat source may be
either electricity or natural gas. Electricity is used by the drum and fan
motors. Improved clothes washer efficiency, particularly measures that
reduce the moisture content of washed clothes, reduce clothes drying
energy use since less run time is needed for drying (US DOE, 1990)
Base Year Energy Use
Gas clothes dryers account for an estimated 0.3% (0.1 quads) of
residential primary energy consumption in 1997. (Source: USEIA,
1996)
End-use Lifetime
The end-use lifetime for clothes dryers was estimated to be 17 years.
This is based on data provided by the Association of Home Appliance
Manufacturers. (US DOE, 1990)
Existing Average Unit Energy
Base year UEC was estimated 3.7 MMBtu for gas clothes dryers. This
Consumption (UEC)
average is based on (Koomey et al., 1997)
1997 New UEC
1997 new UEC was estimated at 3.2 MMBtu for gas clothes dryers.
This new unit UEC accounts for the implementation of the federal 1994
standards on clothes dryers.
Maximum Cost-effective Efficiency
For gas clothes dryers we find no cost-effective approach to reduce
Potential
clothes dryer energy use from the 1997 baseline.
Achievable cost-effective efficiency
Not applicable.
potential - Efficiency Case
Achievable cost-effective efficiency
Not applicable.
potential - High Efficiency Case
Incremental Capital Cost
Not applicable.
Cost of Conserved Energy
Not applicable.
References:
Koomey, Jonathan G., Marla C. Sanchez, Diana Vorsatz, Richard E. Brown, and Celina S. Atkinson. 1997. The Potential for
Natural Gas Efficiency Improvements in the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38893.
in process.
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Department of Energy, 1990. Technical Support Document: Energy Conservation Standards for Consumer Products:
Dishwashers, Clothes Washers, and Clothes Dryers. (DOE/CE-0299P). U.S. DOE, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/ELA-0383(97). U.S. Department of Energy, Washington, DC.
Clothes drying (gas) LEC and cost calculations
Source: U.S. Department of Energy. 1990. Technical Support Document: Energy Conservation Standards for Consumer Products: Dishwasbers. Clothes Washers. and Clothes Dryers.
Source: Koomey. Jonathan G., Maria C. Sancbez. Diana Vorsatz. Richard E. Brown. and Celins S. Atkinson 1997.
The Potential for Natural Gas Efficiency Improvements in the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38893. in process.
MMBai
Average Stock Gas drying UEC from Koomey et al., 1997
3.74
Determination of 1997 New Unit efficiency from Koomey et al., 1997
Incremental
energy Savings
Incremental Cost
Incremental
CCE
New UEC
Fraction of Current
Measure
(MMBtu)
($1990)
Cost ($1995)
($1990/MMBtu)
(MMBtu)
Gas WH Stock
(a) Gas clothes drvers. Baseline
0
$
-
$
-
n/s
3.7
100%
(b) Improve clothes drvers to 1994 standard
0.51
$
27.00
$
31.27
5.5
3.2
100%
MMBai
New Water Heater UEC in 1997 from Koomey et al. 1997
(measures (a) thru (d))
3.2
Determination of Maximum cost-effective efficiency from Koomey et al- 1997
High Efficiency Gas WITH CLOTHES WASHERS
Incremental
energy Savings
Incremental Cost
Incremental
CCE
New UEC
Measure
(MMB(u)
($1990)
Cost ($1995)
($1990/MMBtu)
(MMBa)
(a) Gas clothes drvers - Baseline (1997 new UEC)
0
$
-
$
-
n/a
3.2
(b) Recycle exhaust beat
0.2
$
56.00
$
64.86
$
28.600
2.99
Total
0.2
$
56.00
$
64.86
$
28 600
2.99
There is assumed no cost effective approach to significantly reduce gas clothes dryer energy use beyond the 1997 baseline
Check on calculations with REM output
Retail price
CCE
MMBtu
Percent Savings
($1990)
Real price ($1995)
($1995/MMBtu)
Notes
Average Stock in 1997 (LBNL-REM ruas for DOE. 1995)
3.45
n/a
1997 New (LBNL-REM. AHAM fact book)
2.91
n/a
$
287.27
$
332.73
n/a
Maximum cosseffective energy efficience (new unit UEC.
REM 79 case in 2010)
2.11
n/a
$
356.10
$
412.45
n/a
MMBtu
Capital Costs
Increase in Capital
Energy Cost. and UEC comparison
(primary)
Percent Savings
($1990)
Costs ($1997)
Max. cost effective compared to 1997 new
0.8
27%
$
68.83
$
79.72
$
10.21
CCE calculations
Capital recovery factor
$0.10
Real discount rate
0.07
Lifetime
17
REM output
Clothes dryer saturation (for both cases)
1990
1997
2010
Electric
53%
56%
59%
Gas
16%
17%
18%
None
31%
27%
23%
Total
100%
100%
100%
New Clothes dryer installation in existing & new stock
(millions)
1990
1997
2010
Electric
3.469
3.771
4.468
Gas
1.102
1.157
1.385
Total
4.571
4.928
5.853
New Clothes dryer installation in existing & new stock (percent
share)
Electric
76%
77%
76%
Gas
24%
23%
24%
6/6/97
Background Information Sheet: Interlab Study on
U.S. Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Cooking (Electric)
Product/end-use description
Cooking involves the use of electric, gas, LPG appliances to prepare warm or hot
food. The types of appliances include ranges and ovens, and microwaves. (US
DOE, 1993)
Base Year Energy Use
Electric Cooking accounts for an estimated 2% (0.4 quads) of primary residential
energy consumption in 1997. (Source: US ELA, 1996)
End-use Lifetime
The end-use lifetime for most cooking products is relatively long. For electric
ranges (ovens and cooktops) the end-use lifetime was estimated at 19 years. For
microwaves the lifetime was estimated at 10 years. In our estimates we use a
shipment weighted lifetime estimate of 14 years. This is based on data provided by
the Association of Home Appliance Manufacturers. (LBNL, 1996)
Existing Average Unit Energy
Unit energy consumptions were analyzed in three categories: ovens, cooktops, and
Consumption (UEC)
microwaves. Base year UECs for these three products were estimated to be the
same as 1997 new UECs given available information.
1997 New UEC
1997 new UEC was estimated estimated at 290.9 KWh (1.0 MMBtu) for ovens,
234.4 KWh (0.8 MMBtu) for cooktops, and 143.2 KWh (0.5 MMBtu) for
microwaves. This new unit UECwas based on estimates from (LBNL, 1996)
Maximum Cost-effective Efficiency
For electric cooking equipment we find that there is no cost-effective approach to
Potential
reduce energy use from the 1997 baseline. (LBNL, 1996).
chievable cost-effective efficiency
Not applicable
otential - Efficiency Case
Achievable cost-effective efficiency
Not applicable
potential - High Efficiency Case
Incremental Capital Cost
Not applicable
Cost of Conserved Energy
Not applicable
References:
AHAM. AHAM Fact Book, 1996, Chicago, IL.
LBNL, 1996. Drafi Report on Potential Impact of Alternative Efficiency Levels for Residential Cooking Products.
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/EIA-0383(97). U.S. Department of Energy, Washington, DC.
Background Information Sheet: Interlab Study on
U.S. Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Cooking (Gas)
Product/end-use description
Cooking involves the use of electric or gas appliances to prepare warm or hot
food. The types of appliances include ranges and ovens, and microwaves. (US
DOE, 1993)
Base Year Energy Use
Non-electric cooking accounts for an estimated 1% (0.2 quads) of residential
primary energy consumption in 1997. (Source: USEIA, 1996)
End-use Lifetime
The end-use lifetime for most cooking products is relatively long. For gas
cooktops and gas ranges the lifetime was estimated at 19 years. This is based on
data provided by the Association of Home Appliance Manufacturers. (LBNL,
1996)
Existing Average Unit Energy
1997 existing UEC was estimated at 2.0 MMBtu for gas ovens and 2.1 MMBtu
Consumption (UEC)
for gas cooktops. This is based on data provided by the Association of Home
Appliance Manufacturers. (US DOE. 1993)
1997 New UEC
1997 new UEC was estimated at 2.0 MMBtu for gas ovens and 1.6 MMBtu for
gas cooktops. This is based on data provided by the Association of Home
Appliance Manufacturers. (US DOE. 1993)
Maximum Cost-effective Efficiency
The maximum cost-effective efficiency potential as measured in UEC was
Potential
estimated at 1.4 MMBtu, or a savings of 22% from the current 1997 levels. This
UEC was calculated as a shipments weighted of share of maximum cost-effective
potentials for efficiency improvements to cooktops and ovens (LBNL, 1996).
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential - Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level over the
potential - High Efficiency Case
analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The incremental cost for adopting the high-efficiency model was estimated to be
$7.3 ($1995). This cost is the incremental cost between the high-efficiency
options compared to new 1997 equipment (LBNL, 1996). Prices were adjusted to
1995 levels based on the personal consumption price index (US DOC. 1996).
Cost of Conserved Energy
The CCE for the high efficiency model was estimated at $2.4/MMBtu ($1995).
The CCE is a ratio of the incremental capital expenditure (amortized over the
lifetime of the appliance) to the annual energy savings expected from the purchase
of the unit.
References:
AHAM. AHAM Fact Book, 1996, Chicago, IL.
Koomey, Jonathan G., Marla C. Sanchez, Diana Vorsatz, Richard E. Brown, and Celina S. Atkinson. 1997b. The Potential for
Natural Gas Efficiency Improvements in the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38893.
in process.
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
LBNL, 1996. Draft Report on Potential Impact of Alternative Efficiency Levels for Residential Cooking Products.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/EIA-0383(97). U.S. Department of Energy, Washington, DC.
B-3 12
Gas Cooking UEC and Cost Calculations
Source:
Koomey. Jonathan G., Marla C. Sanchez, Diana Vorsatz, Richard E. Brown. and Celina S. Atkinson. 1997.
The
Potential for Natural Gas Efficiency Improvements in the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38893. in process.
Source:
LBNL. 1996. Draft Report on Potential Impact of Alternative Efficiency Levels for Residential Cooking Products.
Source:
AHAM Fact book. 1996
Oven Gas
Retail price
Retail price
CCE
MMBai
Percent Savings
($1990)
($1995)
($1995/MMBtu)
Notes
Average Stock in 1997 (LBNL-REM runs for DOE,
1993)
2.01
n/a
n/a
n/a
n/a
1997 New (LBNL-REM runs for DOE. 1993)
1.97
n/a
$
573.84
s
617.46
n/a
Maximum.cost-effective energy efficienct oven (DOE,
LCC model from
1995)
1.56
n/a
$
580.59
$
624.71
n/a
LBNL. 1996
Difference between Max tech and 1997 new
0.41
20.8%
$
6.74
$
7.26
1.72
Cooktop Gas
Retail price
Retail price
CCE
MMBtu
Percent Savings
($1990)
($1995)
($1995/MMBtu)
Notes
Average Stock in 1997 (LBNL-REM runs for DOE.
1993)
2.1
n/a
n/a
n/a
n/a
1997 New (LBNL-REM runs for DOE: 1993)
1.6
n/a
$
238.14
$
256.24
n/a
Maximum cost-effective energy efficienct cooktop
LCC model from
(DOE. 1993)
1.3
na
$
245.00
$
263.62
n/a
LBNL. 1996
Difference between Max tech and 1997 new
0.23
14.8%
$
6.86
$
7.38
3.11
Saturation
Saturation Max
Share of gas only
Shares
Baseline (1997)
Baseline
tech econ case
- Max econ. case
Non gas cooking
82.0%
82.0%
82.0%
Baseline gas cooking
18.0%
18.0%
18.0%
Gas Oven
9.4%
52.4%
Gas Cooktop
8.6%
47.6%
Total
100%
100%
18%
100.0%
2010 scenario
Oven saturation
43.0%
Cooktop
39.0%
Max econ. potential case
Incremental
% Savings
Summary Table (efficiency combination weighted
energy Savings
relative to New
Incremental Cost
CCE ($1995/
by saturation in households)
(MMBm)
1997 UEC
($1995)
MMBtu)
Notes
Gas Oven
0.4
20.8%
7
2
Gas Cooktop
0.2
14.8%
7
3
Weighted average MAX ECON POTENTIAL
0.3
18.0%
7.3
2.4
Weighted 1997 New UEC
Gas Oven
1.0
Gas Cooktop
0.7
Weighted average 1997 new
18
Max Tech Efficiency UEC
1.4
Ges Efficien Measures Keome " at. 199761
Incremental
energy Savangs
Incremental Card
Incremental Com
CCE
New UEC
Fraction of
Measure
(MMBN)
($1990)
($1995)
(51990/MBw)
(MMBN)
OursentS weck
Lifetime
Measure
10 Get Ceating 1990 Baseline
14
$
$
D/a
3.40
100%
1900
Add Excess Insurance
2.2
$
48.00
$
55.60
22
1.20
100%
19.00
incremental
energy Savangs
Incremental Cost
Incremental Cost
CCE
New UEC
Fraction of
Measure
Lifets
Meanure
(MMBN)
($1990)
($1995)
($1990/MMB)
(MMBN)
CarrenClock
(1) Car Self Clear gy Over 1990 Baselmer
3.40
$
$
p/s
1.90
100%
19.00
(b) Improve doz MAR & reflecus purfaces
0.27
$
9.00
$
10.42
14
163
100%
19.00
(c) Improver INSULATION at walls & door
021
$
18.00
$
20.85
$.3
142
19.00
(d) Forces copyection pos: 1995 measure'
0.22
$
41.00
$
47.49
17.9
120
19.00
Incremental
energy Savings
Incremental Card
Increasental Cord
COE
New UBC
Practice of
Measure
Mansure
(MMBN)
($1990)
($1995)
($1990/MMBru)
(MMBail
CarrentS tock
Liferge
(a) Standard Car Over 1090 Bascime:
$
$
D/S
300
100%
19.00
an electric glo-pa be
157
$
47.00
$
54.44
29
143
100%
19.00
(c) Improve insulance 03 *alis & door
0.07
$
9.00
$
10.42
124
136
19.00
19.4
1.34
19.00
(d) togrers GODE ased
0 02
$
400
$
4.63
Incremental
energy Savangs
Incrumental Cost
Incremental Card
CCE
New UEC
Fractice of
Measure
Meanure
(MMBni
($1990)
($1993)
(51990/MBail
0448au
CorrentS tock
(a) Standard Gas Over Electrons Ignicies (1990
$
$
n/a
140
100%
19.00
Baseline
ml Improve - or as $ door
0.07
$
9 00
$
10.42
124
133
100%
19 00
$
4.63
19.4
131
1900
(5) programe door seals
002
$
4.00
us DOE 1903 Technical Support Document Energy Effx en Sundards for Consumer Produce: Room AC. Was bearers. Direct bearms equipment mobil bornd furnaces. kirdbed reques and overs pool bearers temp ballest
&
TVs
New Model
New Baselane
Lower LCC
Shipmenes
Incremental
OCE
CCE
New Model
Bancline Read
Bancline Retail
UEC
Lowest LCC
Lower LCC
UEC
(1992)
Percease of
energy use
Incremental Cost
($1995/M
($1995/MM
Gas Cookleps Product Classes
($1990)
($1995)
(MMBou/year)
Received ($1990)
Retail ($1995)
(MMBaureer)
Milbons
Shipments
(MMBru)
($1995)
MBnst
Bru)
$
2987
1.410
1.410
Convenions burpen woul pcs . cord.
$
219 21
253.90
3.37
$
245.00
283.77
1.32
a/s
26.6%
105
burners and power cord:
$
245 00
283771
1.32
$
245.00
28377
1.32
73.4%
Total (or weighted average
$
238.14
275 82
1.87
$
245.00
132
0 00
100.0%
New Model
New Model
New Baselson
Lower LCC
Shipments
bacrumental
CCE
OCE
Percent of
Incremental Cost
($1995/M)
($1995/MM)
Baselms Recal
Bascime Round
UEC
Lower LCC
Lower LCC
UEC
(1992)
corrgy use
Gas Over Product Classes
($1990)
($1995)
(MMBer/year)
Retail ($1990)
Resail ($1995)
(MMBtu/year)
Millions
Shipments
(MMBru)
($1995)
MBa)
Bru)
Sundard over . or were caliver time - Aout power C $
479.00
554.79
2.98
$
503.00
582.59
133
28.1%
1.45
$
27.80
1.850
1.850
153
$
503.00
582.59
15'
48.1%
0.00
1.850
1.850
Sundard evec or woul careiver has 19/ power corc $
503.00
582.59
$
$29.00
960.18
166
$
$29.00
960.18
1.66
23.8%
0.00
$
1.850
1 850
Self-class oven
$
573.84
664.65
1.97
$
580.59
672.46
1.56
0.00
100.0%
0.41
7.81
1.850
1.850
Total (or weighted " wages
LCC at 6% E this document
CCE calculations
Capital recevery factor
$010
Real discount Take
007
decume
19
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
(Miscellaneous Energy)
Product/end-use description
Miscellaneous residential energy use involves end-uses in the home that are not
currently allocated to other end-uses, namely refrigeration, space conditioning,
lighting, cooking, and water heating. While miscellaneous energy (particularly
electricity) can encompass a variety of activities in one's home, for the purposes of
this study we have divided miscellaneous energy into the following categories
shown in table 2 below:
Table 1: Miscellaneous Energy Use
Fuel
Category Main end-uses in category
electricity
electronics
color televisions, Video cassette recorders, cable
boxes, computers
electricity
motors
Furnace fans, ceiling/ventilation fans, pumps
(e.g. pool, well), evaporative cooler
electricity
heating
waterbed heaters, coffee makers. crankcase
heaters. irons, electric blankets. spas/hot tubs,
toasters
natural gas
oil & other
pool heaters, gas fireplaces
petroleum products
Base Year Energy Use
Miscellaneous electricity use was estimated at 23% of residential primary energy
use (4.4 quads) in 1997 (AEO, 1996). Natural gas and oil end-uses account for
another quad of primary energy in 1997. Estimates by main end-use category are
shown in the table below based on (AEO, 1996; LBNL, 1997)
Table 2: 1997 Miscellaneous Energy Use
End-use Category
Share
Quads
Primary
electronics
35.9%
1.6
motors
37.4%
1.6
heating
26.7%
1.2
Total electricity
4.4
natural gas
0.9
oil & other
petroleum products
0.1
Total Miscellaneous
5.4
End-use Lifetime
End-use lifetime was estimated at 12 years. This lifetime was determined as the
energy-use weighted average of the lifetimes of various miscellaneous end-uses.
Average Unit Energy Consumption
Average UECs per household are derived from US DOE (1996).
(UEC)
B-3.13
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
(Miscellaneous Energy) Continued
1997 New UEC
New UECs are assumed to be the same as for existing homes.
Maximum Cost-effective Efficiency
The maximum cost-effective efficiency potential was determined as a weighted
Potential
average of cost-effective energy savings potentials for various end-use categories.
Potentials for each category were estimated from existing studies as well as
judgment by LBNL (see table 3)
Table 3. Estimated Maximum Cost-Effective Efficiency Potential
End-use Category
Potential energy
savings (percent)
electronics
25%
m.tors
53%
heating
33%
Total electric misc.
33%
natural gas
10%
oil & other petroleum products
10%
Sources: US DOE, 1993; Webber. 1997; Meier, 1993; Rieger, 1994; Stevens, 1996;
Meier and Greenberg. 1994: Lamb. 1996
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential - Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level over the
potential - High Efficiency Case
analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The incremental capital cost varied depending on the particular efficiency measures
being examined. Due to the limited availability of data, no attempt was made to
average the total incremental cost for miscellaneous energy. Instead, we directly
estimated the CCE based on cost estimates for the few parts of miscellaneous
electricity that have been explicitly categorized (see below).
Cost of Conserved Energy
We have estimated an average cost of conserved energy of $0.03/KWh ($1990) or
$0.035/KWh ($1995) for miscellaneous electricity, and $6/MMBtu ($1995) for
gas/oil measures. We analyzed the cost of conserved energy for technical efficiency
measures on televisions, video cassette recorders, and waterbed heaters, and found
all three of the CCEs in these cases to be below $0.03/KWh ($1995). The CCE is
a ratio of the incremental capital expenditure (amortized over the lifetime of the
appliance) to the annual energy savings expected from the purchase of the unit.
References:
US DOE, 1993. Technical Support Document: Energy Efficiency Standards for Consumer Products: Room Air Conditioners
Water Heaters, Direct Heating Equipment, Mobile Home Furnaces, Kitchen Ranges and Ovens, Pool Heaters, Fluorescent
Lamp Ballasts & Television Sets
Webber, C. 1997. LBNL Technical Analysis of Reduction of Standby Electricity Use in Televisions and Video Cassette
Recorders
Lamb, Michael. Home Energy Magazine, July/August 1996. "Off is a Three-letter word."
Energy Audtor and Retrofitter, Nov/Dec 1987. "Saving the 'Other' Energy in Homes"
Meier, A. Home Energy Magazine, July/August 1993 "What Stays On When You Go Out"
Meier, A & Greenberg, S. Home Energy Magazine, July/August 1994 "A Journey through the Gray Literature"
B-3.14
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
(Miscellaneous Energy) Continued
Rieger, T. Home Energy Magazine, September/October 1994 "Waterbed Heating: Uncovering the Savings in the Bedroom"
Stevens, D. Home Energy Magazine, March/April 1996 "Mechanical Ventilation for the Home"
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/EIA-0383(97). Department of Energy, Washington, DC.
R-3 15
Misc.-elec
6/6/97
Miscellaneous Energy (Electric)
Potential Energy
Energy Use in 1995
Share of total misc.
Savings by category
Fuel
End-use
TWh
Share of electronics
electricity
Lifetime (years)
(Italics = judgement)
Notes
Electronics
electricity
color television
36.31
49.2%
17.7%
115
25%
1997
electricity
cable boxes
10.34
14.0%
5 0%
10
20%
judgement
Video cassette
electricity
recorders
7.57
10.3%
3.7%
10
40%
Webber, 1997
electricity
computers
2.81
3.8%
1.4%
8
25%
judgement
other electronics
electricity
(excl. microwaves)
16.72
22.7%
8.1%
10
20%
judgement
subtotal
electronics
73.75
100.0%
35.9%
10.7
25%
Motors
Assumes taking
electricity
Furnace fans
28.76
37.4%
14.0%
15
60%
advantage of VSD
electricity
ceiling fans
6.55
8.5%
3.2%
15
50%
Blade redesign
Assuming one can
redesign pool system
(e.g. bigger pipes
electricity
pool pumps
6.53
8.5%
3.2%
12
50%
smaller pumps) esp.
Highly application
electricity
well pumps
4.81
6.3%
2.3%
12
20%
specific, 20% should
pumps analagous;
also assuming high
electricity
aquarlums
4.24
5.5%
2.1%
12
25%
efficiency lighting
Fans are forward
curved, like furnaces-
electricity
evaporative cooler
3.28
4.3%
1.6%
10
50%
lower run time but
Greenberg, 1997.
Mostly shaded pole
electricity
other motors
22.73
29.6%
11.1%
14
60%
(very poor
subtotal
motors
76.9
100.0%
37.4%
13.9
53%
Heating
electricity
waterbed heaters
9.65
17.6%
4.7%
12
40%
1993
electricity
coffee makers
9.4
17.2%
4.6%
8
5%
judgement
electricity
spas/hot tubs
6.6
12.0%
3.2%
18
20%
1994
toasters & toaster
electricity
ovens
5.3
9.7%
2.6%
10
5%
judgement
electricity
crankcase heaters
4.95
9.0%
2.4%
10
10%
judgement
electricity
irons
4.6
8.4%
2.2%
8
10%
judgement
electricity
electric blankets
3.49
6.4%
1.7%
12
10%
judgement
electricity
other heating
10.8
19.7%
5.3%
12
10%
judgement
subtotal
heating
54.79
100.0%
26.7%
11.3
15%
Total Misc. Electricity-all
categories
205.44
100.0%
12.0
33%
Mec.-elec
6/6/97
Implied Share of Recelleneous Prom AEO, 1997
Implied Misc.
Shares from LBNL
Energy based on
Total Misc from AEO. 1997
4.4
Documentation
LONE shares
Electronics
25.9%
1.6
1095 conts/kWh
19955/MBW resource
Motors
31.4%
16
Choose CCE
0.035
16.18
Healing
26.7%
1.2
based on analyses below
3 cente/liWh in 1990
Energy Efficiency Options
Color Televisions
Source: US DOE. 1993. Technical Support Document: Energy Efficiency Standards for Consumer Products: Room An Conditioners
Water Healers, Direct Healing Equipment, Mobile Home Furnaces, Kilchen Ranges and Ovens. Pool Heaters. Fluorescent Lamp Ballasts & Television Sets
Baseline Retail
Basefine UEC
Lowest LCC Reland Lowest LCC Retail Lowest LCC UEC
noremental Cost
% Energy
Baseline Relat ($1990)
($1995)
(XWh)
($1990)
($1895)
(KWh)
Energy Savings
($1990)
Savings
CCE ($1990)
359.55
204.86
37892
138.52
6634
1937
32.4%
$0 04
CCE Calculation Assumptions (Electronics)
CCE Calculation Assumptions (Waterbeds)
Capital recovery lactor
0.13 Capital recovery fact
0.11
Real discount rate
0 07 Real discount rate
007
Lifetime
11.5 Lifetime
15
Source: Webber, C. 1097. LBNL Technical Analysis of Reduction of Standby Electricity Use in Televisions and Video Casselle Recorders
Determination TV Standby Reduction Efficiency
Incremental energy
Incremental energy
Incremental Cost
Incremental Cod
Fraction of Current
% Energy
Measure
Savings (KWh)
Sevings (MMBlu)
($1990)
($1995)
CCE ($1900/kWh)
New UEC (KWh)
Electric WH Stock
Savings
TV Baseline
0
0
$
$
n/a
141
100%
n/a
Set standby to EPA energy
slar
22
0.1
$
5.00
$5.79
$0.03
119
100%
16.6%
Determination VCR Standary Reduction Efficiency
Incremental energy
Incremental energy
Increments Cost
Increment of Cost
Fraction of Current
% Energy
Measure
Sevings (KWh)
Sevings (MMBlu)
($1990)
($1995)
CCE $190AWh)
New VEC (KWh)
Electric WH Stock
Savings
VCR Baseline
9
0
$
$
n/a
57
100%
n/a
Set standby to EPA energy
slar
$
0.1
$
6.00
$5.79
$0.02
25
100%
56.1%
Source: Meior, A. Home Energy Magazine, July/August 1993 "What Stays On When You Go Out
Source: Rieger, T. Home Energy Magazine, September/October 1904 "Waterbed Heating: Uncovering the Savings in the Bedroom*
Source: Slevens, D. Home Energy Magazine, March/April 1996 'Mechanical Ventilation for the Home*
Source: Meter, A & Greenberg, 3. Home Energy Magazine, July/August 1994 "A Journey through the Gray Literature"
Source: Lamb, Michael Home Energy Magazine, July/August 1996 Off is 0 Three-lefter word"
Source: Energy Audior and Retrofter, Nov/Dec 1987. *Saving the "Other" Energy in Homes'
emental energy
Incremental energy
Incremental Cost
Incremental Cost
Fraction of Current
% Energy
% of stock
Electric WH Stock
applicable
Waterbede
Savings (KWh)
Savings (MMBlu)
($1990)
($1995)
CCE ($1990/kWh)
New UEC (KWh)
Savings
Waterbed Basefing
0
0
$
$
n/a
1200
100%
Form bed/carion Instaflation
$47,5
$
90.00
$104.24
$0.02
6525
45.6%
70 percent
& VT. Metime?
Lower thermostel/cover -
blankets
0.0
#DIV/01
1200
100%
Incremental energy
Incremental energy
Incremental Cost
Increment at Cost
Fraction of Current
% Energy
Aquartume
Sevings (KWh)
Savings (MMBlu)
($1990)
($1995)
CCE ($1900/kWh)
New VEC (KWh)
Electric WH Stock
Savings
Aquartum beseling
o
0
$
$
Na
900
100%
0.0
#DIV/01
900
100%
?
Incremental energy
Incremental energy
Increment al Cost
Incremental Cost
Fraction of Current
% Energy
Computers
Sevings (KWh)
Sevings (MMBlu)
($1990)
($1995)
CCE ($1990AWh)
New VEC (KWh)
Electric WH Stock
Savings
100%
Computer basefing
0
0
$
$
IVS
36
?
0.0
#DIV/01
36
100%
Incremental energy
Incremental energy
Increment of Cost
Incremental Cost
Fraction of Current
% Energy
Pool Pumps
Savings (KWh)
Savings (MMB(u)
($1990)
($1995)
CCE ($1990/kWh)
New UEC (KWh)
Electric WH Slock
Savings
Pool pump beseline
0
0
$
$
n/a
1200
100%
?
0.0
#DIV/01
1200
100%
Incremental energy
emental ener
Increment at Cost
Increment al Cost
Fraction of Current
% Energy
Spee
Sevings (KWh)
Sevings (MMB)
($1990)
($1096)
CCE $1900A(Wh)
New LEC (KWh)
Electric WH Block
Sevings
Spe begefing
0
0
1
1
r/a
1200
100%
213%
Improved covers
266.5
09
$0.00
9445
100%
Ventitation Fane
Analysis shows that the majority of the market contains fans with efficiencies of 0.00-0.07 while Panasonic manufactures lane with average
efficiencies of 0 6-0.14. This suggests a conservative max tech cost effective efficiency improvement of 40%
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Lighting
Product/end-use description
Lighting involves the use of electricity to pass electrons through a filament to
produce light and heat (incandescent light) or to pass electrons through an inert gas
which then emits light. Significant savings are possible in residential lighting
systems with the replacement of traditional incandescent lights. About 90% of
lighting energy in residential buildings is from incandescent sources.
Base Year Energy Use
Lighting accounts for an estimated 5% (1.0 quads) of residential primary energy
consumption in 1997. (Source: US EIA, 1996)
End-use Lifetime
The end-use lifetime for lighting was estimated at 1 year. There are many different
lifetimes for lighting products, but incandescent bulbs typically last for about 750
hours. At the average usage level of 2.1 hours/day, these bulbs last about a year.
Existing Average Unit Energy
The AEO 97 forecast assumes a per household lighting UEC of 927 kWh/year
Consumption (UEC)
1997 New UEC
New UEC is the same as the existing UEC.
Maximum Cost-effective Efficiency
The maximum cost-effective efficiency potential was estimated as the savings
Potential
potential from 2010 assuming the implementation of technically cost effective'
lighting measures, including widespread use of halogen IR and compact fluorescent
technologies. The efficiency measures are ranked based on cost of conserved energy
for five separate usage categories (0-1 hours/day, 1-2 hours/day, etc). The savings
costing less than $0.08/kWh are 53% of the 1997 baseline, based on Koomey et
al. (1997).
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential - Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level over the
potential - High Efficiency Case
analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The CCEs are directly calculated in Koomey et al. based on the incremental costs
of halogen IR and compact fluorescent technologies. Prices were adjusted to 1995
levels based on the personal consumption price index (US DOC, 1996).
Cost of Conserved Energy
The weighted average CCE for high efficiency lighting measures costing less than
$0.08/kWh is $0.03/kWh ($8.3/MMBtu). The CCE is a ratio of the incremental
capital expenditure (amortized over the lifetime of the appliance) to the annual
energy savings expected from the purchase of the unit.
References:
Koomey, Jonathan G., Diana A. Vorsatz, Richard E. Brown, and Celina S. Atkinson. 1997. Updated Potential for Electricity
Efficiency Improvements in the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38894. in process.
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/E1A-0383(97). Department of Energy, Washington, DC.
B-3.16
light
6/10/97
CCE
OCE
Energy
Cost in
Cost in 1995
Lighting Efficiency Calculations (Menoure Name)
Massure No. Baduar Code
category
(seats/Wh)
(conts/kWh)
Seved
1990$
$
0 & cost Applicable Stock
1990 $
1995 $
TWh
(1000s)
100W GS Incandescent and Motion Seasor
L100-5.
non space conditioning
0.45
0.52
134
0.58
0.67
0
10467.62
75W GS Incondescent and Motion Sensor
4 L75-5
non space conditioning
0.6
0.69
1.12
0.58
0.67
0
11630.69
GOW GS Incondescent and Motion Semoor
$ 160-1
- space conditioning
1.02
1.18
277
0.78
0.90
0
36055.13
65W Helogen IR
1 L100-5.
non space conditioning
12
139
6.02
0.77
0.29
0
94208.57
asw Helogen IR
L100-4
BOX space senditioning
1.27
1.47
234
0.57
0.66
0
52338.09
65W Helogen IR
L100-3.
- space conditioning
135
156
1.67
0.43
0.50
0
52338.09
sow ES Incandescent
1.100-1.
- space conditioning
153
1.77
0.38
0.03
0.03
0
209352.38
65W Halogen IR
L100-2
- space conditioning
156
121
201
03
035
0
104676.19
STW ES Incardement
160-4
- space conditioning
156
121
1.84
0.16
0.19
0
180275.66
SIW ES Incondecent
1 1601
- space conditioning
157
1.82
4.74
0.23
0.27
0
324496.19
STW ES Incanderment
1160.2
- space conditioning
1.6
1.85
1.58
0.07
0.08
0
340551.32
SIW ES Incondencent and Motion Semeer
6160.5
- space conditioning
1.6
1.85
0.16
0.07
0.04
0
36055.13
4W Halogen IR
1 L75-5.
- space conditioning
1.62
1.88
4.97
0.77
0.89
0
104676.19
SIW ES Incondescent
1 160-3
- space conditioning
1.64
1.90
1.32
0.12
0.14
0
180275.66
49W Halogen IR
1175-4
- space conditioning
1.71
1.98
193
0.57
0.66
0
$8153.44
15W Electronic Separable CR. where CPL fits
21601
- space conditioning
1.79
2.07
13.16
1.21
1.40
0
194697.71
49W Halogen IR
1 L75-3
- space conditioning
121
210
138
0.43
0.50
0
58153.44
sow ES Incandement and Motion Sensor
$ L100-5.
- space senditioning
1.82
211
0.06
0.1
0.12
0
10467.62
52W ES Incandescent
1 L60-1.
- space conditioning
205
237
1.05
0.03
0.03
0
721102.64
6TW ES Incandescent
1 L75-1.
I I I
205
237
0.34
0.03
0.03
0
232613.75
49W Heloges IR
1 L75-2
are - conditioning
211
244
1.66
03
035
0
116306.88
6TW ES Incardescent and Motion Sensor
5 175-5
- space conditioning
2.28
264
0.05
0.1
0.12
0
11630.69
15W Electronic Separable CRL where CFL fire
2160-4
I I 1
2.45
284
5.12
1.16
134
0
108165.4
65W Haloges IR
2 L100-1.
BOX space conditioning
285
3.30
0.96
0.13
0.15
0
209352.38
15W Electronic Inw gral Quad CFL where CFL Fits
21.60-3.
non space conditioning
3.4
3.94
3.65
1.15
133
0
108165.4
30W Elec. Separable CRL when CFL fits
2 1100-5.
non space conditioning
3.6
4.17
3.61
23
266
0
56525.14
41W Halogen IR where OR doesn't fit
3 160-5
non space conditioning
4.18
4.34
261
0.84
0.97
0
129798.47
20W Electronic Separable CFL where CFL fits
2 L75-5
non space conditioning
4.25
4.92
333
225
2.61
0
62805.71
49W Halogen IR
2 L75-1.
non space conditioning
4.26
4.93
0.77
0.14
0.16
0
232613.75
41W Helogen IR where CPL doem't fit
3 L60-4
non space conditioning
4.41
5.11
1.01
0.62
0.72
0
72110.26
30W Electronic Separable CRL where CFL firs
2 L100-4.
nos space conditioning
4.54
5.26
1.4
203
235
0
31402.86
41W Halogen IR where CPL doem't fit
3 L60-3
ace space conditioning
4.68
5.42
0.72
0.47
054
0
72110.26
15W Electronic Inc gral Qued where CFL Fie
3 160-2
non space conditioning
5.27
6.10
3.08
0.75
0.87
0
216330.79
41W Helopen IR
2160-2
non space conditioning
5.31
6.15
2.17
0.32
0.37
0
360551.32
20W Electronic Separable CFL where CFL for
2175-4
son space conditioning
5.42
6.28
1.29
201
2.33
0
34892.06
30W Electronic Separable CRL where CFL fine
2 L100-3.
non space conditioning
551
638
I
1.76
2.04
0
31402.86
20W Electronic Seperable CFL where CFL fits
2 L75-3.
- space conditioning
7.18
832
0.92
1.9
2.20
0
34892.06
15W Elec. Separable CRL and when CRL doesn't fu
4 L60-5
see space conditioning
7.86
9.10
6.16
3.73
432
0
129798.47
30W Electronic Intr goal Quad CPL where CFL fits
2 L100-2
and space conditioning
8.29
9.60
1.2
159
184
0
62805.71
30W Elec. Separable CRL and Pixem where CRL doesn't fit
3 L100-5.
non space conditioning
8.85
10.25
241
5.66
6.56
0
37683.43
41W Halogen IR Incands sceet
2 L60-1.
non space conditioning
8.96
10.38
1.45
0.18
0.21
0
721102.64
15W Elec. Separable CRL and Poster when CRL doesn't fit
4 L60-4
non space conditioning
9.95
11.52
24
331
3.83
0
72110.26
20W Elec. Separable CRL and Pixema when CRL doesn't fit
3 175-5
- space conditioning
10.61
1229
222
5.62
651
0
41870.48
30W Elec. Separable CRL and Pixema when CRL doesn't fit
3 1100-4
non space conditioning
11.24
13.02
0.94
5.03
5.83
0
20935.24
20W Electronic Into gnd Quad CRL where CPL fits
2175-2
nos space conditioning
11.71
13.56
1.11
1.86
2.15
0
69784.13
20W Elec. Separable CRL and Fature where CPL doesn't fit
3 L75-4
BOB space conditioning
1262
14.62
0.86
4.68
5.42
0
23261.38
15W Electronic late gral Quad CPL where CFL file
3 L60-1.
non space conditioning
15.37
17.80
2.06
0.73
0.85
0
432661.58
30W Electronic Inte gnd Quad CFL where CFL fits
3 L100-1.
- space conditioning
19.54
2263
as
1.25
1.45
0
125611.43
20W Electronic Inte gral Quad CFL where CFL fils
3 L75-1.
BOX space conditioning
25.28
29.28
0.74
1.34
1.55
0
139568.25
1995 s/kWh
Savings - to $ ceate/kWh
2.85
8261
24.2
28.0
1995 S/MMB
53%
2010 lighting residential frozen efficiency TWb
8.34
156.6
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Heating, Ventilation, and Air Conditioning (Space Conditioning, Electric)
Product/end-use description
Heating, ventilation, and air-conditioning systems (also known as space
conditioning) in residential buildings are a significant energy use. Systems fueled
by electricity involved the use of either central or dispersed space heating and
cooling. The energy use of space conditioning is most significantly affected by the
climate (or number of days in which heating or cooling is required), the efficiency
of the shell of the home, and the efficiency of the heating and cooling equipment.
Base Year Energy Use
Electric space conditioning accounts for an estimated 15% (2.9 quads) of residential
primary energy consumption in 1997. (Source: US EIA, 1996)
End-use Lifetime
The end-use lifetime for electric space conditioning is different for the building
shell and the space conditioning equipment. Lifetime for the shell was estimated at
100 years. The weighted average lifetime for electric space heating equipment was
estimated at 18 years and the lifetime for electric space cooling equipment was
estimated at 13 years (Koomey et al., 1997a).
Existing Average Unit and New
In our forecast we divide energy consumption between existing and new shells and
Unit Energy Consumption (UEC)
equipment. UECs are calculated for more than 30 different prototypes in North
and South climates, as given in Koomey et al. (1997a).
Maximum Cost-effective Efficiency
The maximum cost-effective efficiency potential was estimated as the savings
Potential
potential assuming the implementation of space conditioning measures costing
less than $0.08/kWh. The savings for equipment efficiency in existing buildings
was estimated at 11% for heating and 15% for cooling (relative to the 1997
baseline efficiencies), while savings new buildings was estimated at 25% for
heating and 18% for cooling. Savings for existing shells are 14% for heating and
1% for cooling, while savings for new shells are 15% for heating and 4% for
cooling. These savings can be directly added to the equipment savings because the
supply curves methodology avoids double counting of energy savings.
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency.
In our high-efficiency case, we assume that the achievable adoption level over the
potential - High Efficiency Case
analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The CCEs are directly calculated in Koomey et al. based on the incremental costs
for space conditioning equipment and thermal shell measures. Prices were adjusted
to 1995 levels based on the personal consumption price index (US DOC, 1996).
Cost of Conserved Energy
The CCE is a ratio of the incremental capital expenditure (amortized over the
lifetime of the appliance) to the annual energy savings expected from the purchase
of the unit. The weighted average CCE for equipment efficiency measures costing
less than $0.08/kWh is $0.031/kWh ($9.1/MMBtu) for existing buildings and
$0.04/kWh ($11.7/MMBtu) for new buildings. The weighted average CCE for
shell efficiency measures costing less than $0.08/kWh is $0.039/kWh
($11.4/MMBtu) for existing buildings and $0.045/kWh ($13.2/MMBtu) for new
buildings. The CCEs do not differ for heating and cooling.
References:
Koomey, Jonathan G., Diana A. Vorsatz, Richard E. Brown, and Celina S. Atkinson. 1997a. Updated Potential for Electricity
Efficiency Improvements in the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38894. in process.
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/EIA-0383(97). Department of Energy, Washington, DC.
B-3.17
Energy
Electric Besting. Ventflation. and Air Conditioning (Measure
Measure
Incremental
CCE
CCE
Total Energy
Cost in
Energy
Saved
Applicable
name)
No.
Enduse Code Cost
SYear
Category
(e/kWh)
(e/kh)
Saved (TWh)
1990 S
Saved Cla
bearing
Stock (1000s)
1990 $
19955
Improve shell in ESF ER/RAC/loose homes. North
1 ESNERL
279
1989 shell
0.24
0.28
1.56
294
0.01
1.55
Reduce infiltration by 25% 19 ESF ER/RACAight homes. North
155.69
1 ESNERT
245
1989 shell
1.67
1.93
0.67
258
0
0.67
533.79
Decrease ACH by 25% ID ESF ER/-Aight homes. North
1 ESNE_T
248
1989 shell
1.69
1.96
0.89
261
0
0.89
712.75
Improve shell in ESF ER/-Roose beenes. North
1 ESNE_L
2656
1989 shell
1.89
219
249
2800
0
2.49
207.89
Improve shell is ESF ER/RACAoose bomes. Somb
1 ESSERL
1714
1989 shell
212
2.46
0.71
1807
0.02
0.69
103.66
Improve shell in ESF ER/-Aose bomes, South
1 ESSE_L
1714
1909 shell
218
252
0.63
1807
0
0.63
93.79
Reduce infiltration in ESF ER/RAChight homes. South
1 ESSERT
422
1989 shell
247
2.86
0.37
445
0.01
0.36
254.21
Low-E argon Elled windows in ESF ER/RACAOOSE homes. North
2 ESNERL
354
1989 shell
251
2.91
0.19
373
0
0.19
155.69
Low-E argon filled windows in ESF Access homes. North
2 ESNE_L
354
1989 shell
252
292
0.25
373
0
0.25
207.89
Reduce infilization LB ESF ER/-Aight homes. South
I ESSE_T
422
1989 shell
255
2.95
0.32
445
0
0.32
230.02
Low.E argos filled windows in ESF ER/RAChight homes. North
2 ESNERT
466
1989 shell
256
297
0.83
491
0.01
0.82
533.79
Los-E argon filled windows is ESF ER/_Might homes. North
2 ESNE_T
466
1989 shell
2.58
2.99
1.1
491
0
1.1
712.75
Double pase windows in ESF AChoose homes. South
2 ESSECL
218
1989 shell
136
3.89
0.33
230
0.05
0.28
606.28
R-25 oriling is ESF ER/CAC/loase homes. South
3 ESSECL
436
1989 shell
359
4.16
0.63
460
0.14
0.49
606.28
Improve shell in ESF ER/CAC Cloose homes, North
3 ESNECL
1281
1989 shell
4.04
4.68
0.22
1350
Q01
0.21
$2.81
Improve floor & ceiling is ESF ER/-Aight homes. North
3 ESNE_T
1959
1989 shell
4.22
4.89
281
2065
0
2.81
712.75
R-23 floor & R-48 ceiling in ESF ER/RACAight homes. North
3 ESNERT
2114
1989 shell
4.26
4.93
225
2228
0.01
224
533.79
Reduce infituation by 25% is ESF ER/CACright homes. North
2 ESNECT
245
1989 shell
4.67
5.41
0.13
258
0
0.13
283.93
Reduce infilization in ESF ER/CACright homes. South
2 ESSECT
211
1989 shell
4.83
5.59
0.55
222
0.09
0.46
1486.83
Low-E argon filled windows in ESF ER/RAChight homes. South
3 ESSERT
715
1989 shell
5.15
5.96
0.3
754
0.02
0.28
254.21
R-33 criling in ESF ER/RAC/loose homes. South
3 ESSERL
115
1989 shell
5.31
6.15
0.02
121
0
0.02
103.66
Reduce infiltration to 0.39 ACH is ESF/HPAight homes. South
2 ESSHPT
422
1949 shell
5.31
6.15
1.4
445
0.23
1.17
2067.37
Low-E argos filled windows ESF ER/RACloose homes. South
4 ESSERL
295
1989 shell
5.45
6.31
0 05
311
0
0.04
103.66
Low-E argos filled windows in ESF ERA-Aight homes. South
2 ESSE_T
715
1989 shell
5.47
6.34
0.26
754
0
0.26
230.02
R-33 oriling in ESF ER-Moose homes. South
2 ESSE_L
115
1989 shell
5.58
6.46
0.02
121
0
0.02
93.79
Low-E arges filled windows in ESF ER/-Goose homes. South
3 ESSE_L
295
1989 shell
5.92
686
0.04
311
0
0.04
9379
Reduce infiltration EL ESF homes. South
4 ESSECL
211
1989 shell
6.03
6.98
0.18
222
0.03
0.15
606.28
Specially relective windows ESF ER/CAC/loose. South
5 ESSECL
288
1989 shell
6.03
6.98
0.25
304
0.36
-0.02
606.28
R-46 criling is ESF ER/-Aight homes. North
4 ESNE_T
180
1989 shell
6.13
7.10
0.18
190
0
0.18
712.75
Superwindows is ESF ER/RACA homes. North (posi- 1995,
6 ESNERL
347
1989 shell
633
7.33
0.07
366
0
0.07
155.69
Superwandows is ESF ER/_Aoose homes. North (post-
6 ESNE_L
347
1989 shell
6.41
7.42
0.1
366
0
0.)
207.89
Superwindows in ESF ER/RACAight homes. North (post.
6 ESNERT
438
1989 shell
6.44
7.46
0.32
483
0.01
032
533.79
Improve shell of ESFAPAOOK home. South
2 ESSHPL
1694
1989 shell
6.47
7.49
0.75
1786
014
0.61
338.3
Superwiadows in ESF ER/-Aight homes. North (post- 1995)
7 ESNE_T
458
1989 shell
6.57
7.61
0.42
483
0
0.42
712.75
Low-E argon filled windows in ESFAPAoose homes. Nonb
2 ESNHPL
938
1989 shell
6.6
7.64
0.03
989
0
0.03
23.05
R-37 ceiling in ESF ER/RAC homes. North
3 ESNERL
87
1989 shell
6.63
7.68
0.02
92
0
0.02
155.69
Low-E argon filled windows in ESF/HPhight homes. North
2 ESNHPT
548
1989 shell
6.63
7.68
0.34
578
0.02
0.32
484.11
R-37 oriling in ESF ER/ Aooer homes. North
3 ESNE_L
87
1989 shell
6.68
7.74
0 02
92
0
0.02
207.89
Low-E argos filled windows in ESF ER/CAC/loose homes. North
4 ESNECL
354
1989 shell
6.77
7.84
0.04
373
0
0.04
$2.81
Low-E argon filled windows is ESF ER/CACAight homes. North
3 ESNECT
466
1989 shell
6.84
7.92
0.16
491
0.01
0.16
283.93
Reduce infiteration (#2) is ESF ER/CACright homes. South
4 ESSECT
211
1989 shell
7.14
$.27
0.37
222
0.06
0.31
1486.83
R-M criling in ESF ER/RACAight homes. South (pre-2000)
4 ESSERT
609
1989 shell
7.4
8.57
0.06
642
0
0.06
90.91
R-38 criling in ESF ER/RAChight homes. South (post-2000)
$ ESSERT
609
1989 shell
7.45
8.63
0.12
642
0
0.11
169.47
Improve floor & criling in ESF ER/CAC/loose homes. North
s ESNECL
895.6
1989 shell
7.49
8.68
0.08
944
0
0.08
$2.81
R-38 criling is ESF ER/-Aight homes. South
3 ESSE_T
609
1989 shell
7.77
9.00
0.15
642
0
0.15
230.02
Spec- selective windows ESF ather/CAC/loose. South
2 ESSGCL
492
1989 shell
7.93
9.18
1.96
519
1.98
0
3751.63
Specially selective windows: ESFAHPAight. South
4 ESSHPT
590
1989 shell
8.15
9.44
1.27
622
1.28
o
2067.37
Spect selective windows: ESF other/CAC/ugh: South
2 ESSGCT
609
1989 shell
8.26
9.57
1.87
642
1.87
o
2990.16
Improve floor insulation in ESF ER/CAC/loose homes. North
6 ESNECL
235
1989 shell
8.33
9.65
0.02
248
0
0.02
82.81
Improve shel: in ESF ER/CACAose homes. South
6 ESSECL
849
1989 shell
8.49
9.83
0.51
895
0.06
0.44
606.28
Spectrally selective windows. ESF ER/CACright. South
5 ESSECT
705
1989 shell
8.51
9.86
1.05
743
0.94
0.11
1486.83
R-11 wall in ESF ER/RACrighs homes. North
4 ESNERT
864
1989 shell
9.3
10.77
0.42
911
0
0.42
533.79
Spectrally selective windows ESF/HPAoose South
3 ESSHPL
571
1989 shell
9.35
10.83
0.18
602
0.18
0
338.3
Improve all insulation in ESF ER-Aight homes. North
5 ESNE_T
874
1989 shell
9.46
10.96
0.56
921
0
0.56
712.75
R-30 criting in ESF/HPAoose homes. North
4 ESNHPL
1065
1989 shell
10.67
12.36
0.02
1123
0
0.02
23.05
R-46 ceiling in ESF ER/RACAight homes. South (pr-2000)
5 ESSERT
161
1989 shell
10.94
12.67
0.01
170
0
0.01
9091
R-46 ceiling is ESF ER/RACAight homes. South (post-2000)
9 ESSERT
161
1989 shell
11.03
12.78
0.02
170
0
0.02
169 47
Improve floor insulation in ESF ER/CACright homes. North
4 ESNECT
1264
1989 shell
11.07
12.82
0.28
1332
0.01
0.27
283.93
R-40 ceiling in ESF ER/CACright homes. North
5 ESNECT
672
1989 shell
11.24
13.02
0.14
706
0.01
0.14
283.93
R-46 criling in ESF ER/-Aight homes. South
4 ESSE_T
161
1989 shell
11.69
1354
0.03
170
0
0.03
230.02
R-33 ceiling in ESF/HP/loose homes. South
4 ESSHPL
145
1989 shell
11.73
13.59
0.04
153
0.01
0.03
338.3
R-45 ceiling in ESF ER/RAC/loose homes. North
4 ESNERL
327
1989 shell
12.3
14.25
0.04
345
0
0.03
155.69
R-45 eviling in ESF ER/ Noose homes. North
4 ESNE_L
327
1989 shell
12.39
14.35
0.05
345
0
0.05
207.89
R-36 criling in ESF ER/RAC/loose bomes. South (pre-2000)
5 ESSERL
72
1989 shell
1248
14.45
0
76
0
0
37.07
R-51 ceiling is ESF ER/RAC/tight homes. North
5 ESNERT
111
1989 shell
1257
14.56
0.04
117
0
0.04
533.79
R-33 criling is ESF ER/CAC/loose homes. South
$ ESSECL
115
1989 shell
1285
14.88
0.05
121
0.01
0.03
606.28
R-51 oriling in ESF ER/-Aight homes. North
6 ESNE_T
112
1989 shell
12.93
14.98
0.05
118
0
0.05
712.75
R-36 criling is ESF ER/-Aose homes. South
4 ESSE_L
72
1989 shell
13.3
15.40
0
76
0
0
93.79
R-44 oriling in ESF/HPAight homes. North
3 ESNHPT
395
1989 shell
14.16
16.40
0.11
416
0.01
0.11
484.11
R-11 wall is ESF ER/RAChight homes. South (pre-2000)
6 ESSERT
775
1989 shell
14.31
16.57
0.04
$17
0
0.04
90.91
R.11 wall is ESF ER/RAChight homes. South (post-2000)
10 ESSERT
775
1989 shell
14.37
16.64
0.04
817
0
0.08
169 47
R-11 wall in ESF ER/-Aight homes. South
5 ESSE_T
775
1989 shell
14.66
16.98
0.1
817
0
0.1
230.02
R-67 criling is ESF ER/RACAose homes. North
5 ESNERL
632
1989 shell
15.41
17.85
0.05
666
0
0.05
155.69
R-67 ceiling is ESF ER/_Noose homes. North
5 ESNE_L
632
1989 shell
15.56
18.02
0.07
666
0
0.07
207.89
Superwiadows in ESF/HPAigts homes. North (post-1995)
4 ESNHPT
539
1989 shell
15.64
18.11
0.14
568
0.02
0.12
484.11
R-48 ceiling in ESF ER/CACAight homes. North
6 ESNECT
179
1989 shell
16
18.53
0.03
189
0
0.03
283.93
Superwindow in ESF/HP/loose homes. North (post-1995)
5 ESNHPL
770
1989 shell
16.43
19.03
0.01
812
0
0.01
23.05
R-38 ceiling in ESF ER/CACAight homes. South
7 ESSECT
609
1989 shell
17.42
20.18
0.44
642
0.1
0.34
1486.83
R-52 ceiling in ESF/HP/ught homes. North
5 ESNHPT
104.5
1989 shell
18.49
21.42
0.02
110
0
0.02
484.11
6/6/97
Dectric Beating. Ventilation. and Air Conditioning (Measure
Measure
Energy
Incremental
CCE
CCE
Total Energy
Cost in
name)
Energy
Saved
No.
Enduse Code Cost
Applicable
SYear
Category
(e/kh)
(c/kWh)
Saved (TWh)
1990 $
Seved Cig
bearing
Stock (1000s)
1990 $
19955
Swich elec fure to HP is ESF ER/CACAose homes. North
1 ESNECL
822
1989 space conditioning
0.68
0.79
0.96
866
0.01
0.95
Sentch elec fure to HP is ESF ER/CAChight homes. North
66.25
1 ESNECT
912
1989 space conditions
0.99
1.15
2.51
961
0.04
2.47
Improve has: pump efficiency is ESF/HP/loose homes. North
227.15
I ESNHPL
241
1989 space conditioning
1.11
1.29
0.08
254
0.01
0.07
Impreve HP in ESF ER/CAC/loose homes. North
30.74
2 ESNECL
90
1989 space conditioning
12
1.39
0.06
95
0
0.06
Improve MP bey ced 9: and in EMF HP homes. North
66.25
1 EANHP
104
1989 space conditionis
1.22
1.41
0.22
110
0.02
0.21
Swinch elec fure to HP in ESF ER/CAC/looer homes. South
218.04
1 ESSECL
822
1989 space conditioning
1.41
1.63
3.42
866
0.37
3.05
485.02
Improve HP beyond 1992 standard in EMH HP homes. North
1 EMNHP
151
1988 space conditionies
1.66
1.92
0.01
167
0
0.01
10.3
Swisch elec fure to HP is ESF ACAight homes. South
1 ESSECT
822
1989 space conditioning
1.71
1.98
6.91
866
0.91
6
1189.47
Improve heat puer m ESF/HPright homes. South
1 ESSHPT
183
1989 space conditioning
1.87
2.17
3.26
193
157
1.69
27565
Improve hear pump is ESF/HP/loose homes. South
1 ESSHPL
292
1989 space conditioning
1.97
2.28
0.8
308
0.31
0.49
451.06
Improve HP ond 1992 standard is EMH HP homes, South
1 EMSHP
183
1988 space conditioning
230
2.73
0.06
202
0.03
0.03
59.59
Improve has: pump efficiency is ESF/HP/ught homes. North
I ESNHPT
241
1989 space conditions
237
2.75
0.79
254
0.07
0.72
645.48
Improve HP beyond 92 and is EMF HP homes. South
1 EASHP
104
1989 space conditioning
271
3.14
0.41
110
0.19
0.22
886
Improve RAC efficiency is ESF Bon-clec/RAC/loose homes. South
1 ESSGRL
18
1989 space conditioning
116
3.66
0.16
19
0.16
0
2429.92
Improve RAC ID EMH ER/RAC homes. South
I EMSER
9.6
1989 space conditioning
3.17
3.67
001
10
0.01
0
136.53
Improve RAC LE EMH Dos-cloc/RAC homes. South
1 EMSGR
96
1989 space conditioning
3.32
3.85
0.02
10
0.02
0
568.52
Improve RAC efficiency in ESF aon-elec/RAC/upht homes. South
1 ESSGRT
18
1989 space conditions
3.86
4.47
0.1
19
0.1
0
1936.72
Improve RAC is ESF ER/RACnight homes. South (pre-2000)
2 ESSERT
18
1989 space conditioning
4.08
473
0.02
19
0.02
0
338 95
Improve HP2) is EMF HP homes. North
2 EANHP
62
1989 space conditioning
4.17
4.83
004
65
0
0.04
218.04
Improve CAC LB ESF Boo-ciec/CAC/100se homes. South
1 ESSGCL
309
1989 space conditioning
475
5.50
4.32
326
4.32
0
5002.17
Variable speed RAC it. ESF non-elec/RACAose. South (post-2000)
3 ESSGRL
122
1989 space conditioning
489
5.66
0.47
129
0.47
0
1619 95
Improve RAC LC EER in ESF homes. South
2 ESSERL
18
1989 space conditioning
5.08
5.88
0.01
19
0.01
0
138.21
Improve RACE: ID EMH ER/RAC homes. South (post-2000)
2 EMSER
55.5
1989 space conditioning
5.7
6.60
0.01
58
0.01
0
91.02
Variable their RAC is ESF non-elec/RACAight South
3 ESSGRT
109
1989 apace conditions
5.71
6.61
0.29
115
0.29
0
1291.15
Improve CAC an ESF son-elec/CAChight homes. South
I ESSGCT
309
1989 space conditioning
573
664
285
326
285
0
3986 88
Swuch tc improved HP is ESF ER/CACAight homes. South
3 ESSECT
90
1989 space conditions
5.96
6.90
0.22
95
0.07
0.15
1189.47
Improve RACE, 10 EMH 200-eiec/RAC homes. South
2 EMSGR
55.5
1989 space conditioning
5.97
6.91
0 05
58
0.05
0
379.01
Improve HP.2) :a EMH HP homes. North
2 EMNHP
90
1988 space conditions
616
7.13
0
99
0
0
10.3
Vanable spond RAC in ESF ER/RAChight homes. South (post.
7 ESSERT
109
1989 space conditioning
647
7.49
0.04
115
0.04
0
225.96
Improve RAC in EMH ER/RAC homes. North
I EMNER
96
1989 space conditioning
689
7.98
0
10
0
0
61.46
Vanable speed RAC 10 ESF ER/RAC Noose. South (post-2000)
6 ESSERL
109
1989 space conditionin
7.13
8.26
0 02
115
0 02
0
92.14
Improve RAC in EMH Doo-elec/RAC homes. Nonh
I EMNGR
9.6
1989 space conditions
7.45
8.63
0
10
0
0
276.82
Improve RAC in EMF ER/RAC homes. South
1 EASER
9.6
1989 space conditionis,
7.77
9 00
0.01
10
0.01
0
402.89
Improve RAC in EMF non-eloc/RAC homes. South
1 EASGR
96
1989 space conditions
ITI
9.00
0 02
10
0 02
0
1017.13
Improve CAC beyond 1992 atd in EMH ER/CAC homes South
I EMSEC
309
1989 space conditioning
7.82
9.06
0.07
326
0.07
0
142.25
Varuble speed CAC compressor is EMF ER/CAC homes South
2 EASEC
105
1989 space conditions
7.91
9.16
0.31
111
031
0
1751.87
Variable speed CAC compressor in EMF Doe-ciec/CAC homes. South
2 EASGC
105
1989 space conditioning
791
9.16
0.24
111
0.24
0
1335.72
Improve CAC beyond 1992 and in EMH Boo-elec/CA homes. South
1 EMSGC
309
1989 space conditioning
19
9.49
0.19
326
0.19
0
386.39
10 OF EER for ESF non-elec/RAChight. South (post-2000)
4 ESSGRT
13.5
1989 space coaditioning
8.22
952
0.02
14
0.02
0
1291.15
Improve heat pump #2: in ESF/HPAight homes. South
3 ESSHPT
109
1989 space conditioning
$36
9.57
044
115
0.15
0.29
2756.5
Swach to improved HP: ESF ER/CAC/loose. South
7 ESSECL
90
1989 space conditioning
8.96
10.38
0.06
95
0.02
0.04
485.02
Improve beat pump efficiency (#2) 10 ESF/HP/loose homes. North
3 ESNHPL
330
1989 space conditioning
9.38
10.86
0.01
348
0
0.01
30.74
Improve CAC beyond 1992 and is EMF ER/CAC homes. South
I EASEC
169
1989 space conditionin)
9.6
11.12
0.22
178
0.22
0
947.28
Improve CAC beyond 1992 and in EMF non-eleck homes. South
1 EASGC
169
1989 space conditionis
9.6
11.12
0.17
178
0.17
0
722.25
improve HP.1, 12 EMF HP homes. North
3 EANHP
228
1989 space conditioning
10.81
12.52
0.06
240
0.01
0.05
218.04
Improve HP:2: IC EMH HP homes. South
2 EMSHP
109
1988 space conditioning
10.88
12.60
0.01
120
0
0.01
59.59
Improved HP . IT ESF ER/CACnigh: homes. South
6 ESSECT
330
1989 space conditioning
11.7
13.55
0.4
348
0.28
0.12
1189.47
EER RAC in ESF ER/RAC/loose. South (post-2000)
7 ESSERL
13.5
1989 space conditionis)
1202
13.92
0
14
0
0
92.14
Improve HP.2, in EMF HP homes. South
2 EASHP
62
1989 space condition(s)
1211
14.03
0.05
65
0.02
0.04
886
Improve RAC(2) in EMH ER/RAC homes. North (post-2000)
2 EMNER
55.5
1989 space conditioning
1242
14.39
0
58
0
0
40.98
Improve in EMH HP homes North
3 EMNHP
330
1988 space conditioning
1276
14.78
0
365
0
0
10.3
CAC (#2) is ESF non-elec/CACficose homes. South
3 ESSGCL
292
1989 space conditioning
13.53
15.67
1.43
308
1.43
0
5002 17
Switch to improved HP ESF ER/C AC/loose. South
9 ESSECL
330
1989 space conditioning
1376
15.94
0.14
348
0.11
0.03
485.02
improve RAC efficiency LB ESF non-clec/RAC/loose homes. North
I ESNGRL
18
1989 space conditioning
1389
16.09
0.06
19
0.06
0
3878.95
Improve RACC 5 EMF ER/RAC homes. South (post2000)
2 EASER
555
1989 space conditioning
14
16.22
001
58
0.01
0
268.59
Improve RAC2) in EMF non-elec/RAC homes. South (post-2000)
2 EASGR
55.5
1989 space conditionis
14
16.22
0.04
58
0.04
0
678.09
Improve HA3, 10 EMH HP homes South
3 EMSHP
399
1988 space conditioning
14.01
16.23
0.02
44)
0.02
0.01
59.59
Switch to improved HP 10 ESF homes. North
, ESNECL
330
1989 space conditioning
14.48
16.77
0.02
348
0.01
0.01
66.25
Improve hear pump (#3) ID ESF/HP/ight homes. South
5 ESSHPT
399
1989 space conditioning
14.53
16.83
0.9)
421
0.65
0.26
27565
Heat pumple3) in ESF/HP/loose homes. South
5 ESSHPL
399
1989 space conditioning
14.57
16.88
0.15
421
0.11
0.04
451.06
improve RAC efficiency is ESF non-clec/RACAigh homes North
1 ESNGRT
18
1989 space conditioning
1488
17.23
0.06
19
0.06
0
4078.34
10.20 EER for ESF non-elec/RAC/loose South (pre-2000)
2 ESSGRL
142
1989 space conditioning
15.36
17.79
0.09
150
0.09
0
$68.94
Improve CAC it ESF aou-elec/CACloose homes. North
1 ESNGCL
264
1989 space conditioning
16.14
18.69
1.05
278
1.05
0
4843.87
Improve HP13, ID EMF HP homes. South
3 EASHP
228
1989 space conditionion
16.75
19.40
0.15
240
0.1
0 05
886
Improve CAC LD ESF homes. North
1 ESNGCT
264
1989 space conditions)
16.84
19.50
1.06
278
1.06
0
5092.85
10.20 EER for ESF mon-clec/RAC/loose. South (post
4 ESSGRL
19.5
1989 space conditioning
17.36
20.11
0.02
21
0.02
0
1619.95
CAC (#2) is ESF non-clec/CACAight homes. South
3 ESSGCT
292
1989 space conditions)
17.86
20.69
0.87
308
0.87
0
3986.88
10.08 EER for ESF Boo-clec/RACAigts. South (pre-2000)
2 ESSGRT
122
1989 space conditionis
18.58
2152
0.05
129
0.05
0
692.57
Existing Shell savings below , crowk Wh
3.89
20.87
20.86
1.04
19.82
Existing Equipment savings below $ cents/kWh
3.09
28.1
28.11
11.95
16.16
616197
Energy
Electric Heating. Ventitation. and Air Conditioning (Measure
Measure
Incremental
CCE
CCE
Total Energy
Cost in
Energy
Saved
Applicable
name)
No.
Enduse Code Cost
Slear
Category
(e/kh)
(e/kh)
Saved (TWh)
1990 S
Saved Cla
beating
Stock (1000s)
1990 $
19953
R-19 wall & reduced infiltration in NSF ER/CAC homes, South
I ASSER
606.1
1989 shell
1.85
2.14
0.46
639
0.01
0.45
165.79
Reduce infiltration & R-19 " al: NSF ER/- homes. South
1 NSSE
606
1989 shell
1.91
2.21
0.4
639
0
0.4
149.74
R-19 all. R-30 floor is NSF ER/RAC homes. North
I NSNER
408.3
1989 shell
239
2.77
02
430
0
Q.2
136.18
R-19 wall. R-30 floor insulation is NSF ER:- homes. North
1 NINE
406
1989 shell
24)
2.79
0.27
430
0
0.27
185.13
Argon-filled windows IS NSF ER/RAC homes. North
2 NSNER
494
1989 shell
249
288
0.23
521
0
0.23
136.18
Infiluation to 0.4 ACH in NSF ER/C AC homes. South
2 NSSEC
227.3
1989 abell
249
2.88
0.71
240
0.12
0.6
917.45
Argos-filled windows It NSF ER/- homes. North
2 NSNE
494
1989 shell
25
2.90
0.31
521
0
031
185.13
Argon-filled low-E windows ID NSF ER/RAC homes. South
2 NSSER
748.2
1989 shell
3.68
4.26
0.29
789
0.02
0.27
165.79
Argon-filled los -E a indows in NSF ER/- homes. South
2 NSSE
748
1989 shell
3.9
452
0.24
788
0
0.24
149.74
Improve shell is NSF HP homes. South
2 NSSHP
529
1989 shell
199
4.62
3.83
558
0.8
3.02
3394.86
Ceiling le R-M 19 NSF ER/RAC homes. North
3 NSNER
148.5
1989 shell
4.23
4.90
0.04
157
0
0.04
136.18
Ceiling to R-34 - NSF ER/- homes. North
3 NSNE
148
1989 shell
4.25
4.92
0.05
156
0
0.05
185.13
Supera 1000s 19 NSF ER/RAC homes North (port-1995)
7 NSNER
455
1989 abell
5.1
5.91
0.1
480
0
01
136.18
Supers indows is NSF ER/. homes. North (post-1995)
6 NSNE
455
1989 shell
5.16
5.98
0.14
480
0
0.14
185.13
Wall to R.19 18 NSF ER/C homes. North
2 NSNEC
185.6
1989 shell
5.24
6.07
0.13
196
0
0.12
423.29
R-19 wall and R.M criling ID NSF HP homes. North
2 NSNHP
360
1989 shell
5.49
6.36
0.7
379
0.03
0.67
1264.73
Spectrally selective windows NSF ERIC AC. South
3 NSSEC
738.1
1989 shell
6.23
7.22
092
778
0.66
026
917.45
Ceiling to R-30 in NSF ER/RAC homes. South
4 NSSER
56.8
1989 shell
6.63
7.68
0.01
60
0
0.01
165.79
Argon-filled indows ID NSF ER/CAC homes. North
3 NSNEC
494
1989 abell
6.7
7.76
0.27
521
0.01
0.26
423.29
R-30 reiling is NSF ER/- homes. South
3 NSSE
57
1989 shell
6.92
8.01
0.01
60
0
0.01
149.74
Ceiling to R-09. wall 10 R-27 10 NSF ER/CAC bemes. North
4 NSNER
1243.5
1989 abell
7.4
8.57
0.19
1311
0
0.19
136.18
R-27 wall & R-49 ceiling ID NSF ER/- homes. North
4 NSNE
1244
1989 shell
7.44
8.62
0.26
1311
0
0.26
185.13
Wall to R-19 in NSF ERC AC homes. South
5 NSSEC
378.8
1989 shell
7.81
9.05
0.38
399
0.06
0.32
91745
Floor to R-30 15 NSF HP homes. Nonh
3 NSNHP
311
1989 shell
7.83
9.07
0.43
328
0.02
041
1264.73
Floor to R 30 ta NSF ER/CAC homes. North
4 NSNEC
2227
1989 shell
7.88
9.13
0.1
235
0.01
0.1
423.29
R-49 criling . NSF HP homes. North
4 NSNHP
100
1989 shell
8.65
10.02
0.12
105
0.01
0.12
1264.73
Ceiling to R-60 10 NSF ER/C AC homes. North
5 NSNER
148.5
1989 shell
9 06
1049
0.02
157
0
0.02
136.18
Criling :2 R.60 = NSF ER: homes. North
5 NSNE
148
1989 shell
9.11
1055
0.03
156
0
0.03
185.13
Speciality selective form :ndows. NSF HP. South
3 NSSHP
710
1989 shell
95
11.00
216
748
205
0.1
3394.86
Speci. serecuse indows NSF other/CAC homes South
2 NSSGC
807
1989 shell
10.1
1170
3.62
851
3.62
0
5324.68
Celling to R-38 it NSF ER/CAC homes, North
5 NSNEC
1485
1989 shell
11.19
12.96
0.05
157
0
0.04
423.29
R-60 ceiling in NSF HP homes North
5 NSNHP
89
1989 shell
11.83
13.70
0.08
94
0.01
0.07
126473
Cerling insulation to R-38 13 NSF ER/CAC homes. South -2000)
5 NSSER
322
1989 she:l
1247
1444
0 02
339
0
0.02
80.14
Ceiling insulation to R-38 is NSF ER/CAC homes. South (post-2000)
6 NSSER
322
1989 shell
1251
14.49
0.02
339
0
0.02
85 64
Supers indows in NSF ER/CAC homes. North
6 NSNEC
455
1989 shell
13.18
15.27
0.12
480
0.01
0.11
423.29
Wall to R-19 is NSF HP homes. South
5 NSSHP
328
1989 shell
13.27
15.37
0.71
346
0.11
0.61
3394.86
Criling to R-38 is NSF ER/- homes. South
4 NSSE
322
1989 shell
13.34
15.45
0.03
339
0
0.03
149.74
Ceiling insulation to R-19 it NSF ER/C homes. South (pre-2000)
6 NSSER
303
1989 shell
13.74
15.91
0.02
319
0
0.01
80.14
Criling insulation 10 R-49 in NSF ER/C homes. South (post-2000)
9 NSSER
303
1989 shell
13.79
15.97
0.02
319
0
0.01
85.64
Ceiling to R-49 it NSF ER/- homes. South
5 NSSE
303
1989 shell
14.71
17.04
0.03
319
0
0.03
149.74
Ceiling to R-30 in NSF ER/C/ homes. South
7 NSSEC
56.8
1989 shell
15.98
1851
0.03
60
0.01
0.02
917 45
Esergy
Electric Beating. Ventilation. and Air Conditioning (Measure
Measure
Incremental
CCE
CCE
Total Energy
Coa in
Energy
Saved
Applicable
name)
No.
Enduse Code
Cost
SYear
Category
(s/kh)
(e/kh)
Seved (TWb)
1990 S
Saved Cla
beating
Stock (1000s)
1990 $
19955
Switch elec furnace to HP is NSF ER/CAC homes. North
1 NSNEC
412
1989 space conditioning
0.64
074
3.3
434
0.1
3.2
423.29
917.45
Switch elec beace to HP in NSF ER/CAC homes. South
1 NSSEC
422
1989 space conditioning
0.79
0.92
5.92
445
0.71
5.21
Emprove HP beyond 1992 sundard in NSF HP homes, North
I NSNHP
241
1989 space conditioning
1.87
2.17
1.97
254
0.17
1.8
1264.73
Improve HP beyond 1992 standard is NSF HP homes. South
1 NSSHP
183
1989 space conditionin,
1.97
2.28
3.81
193
1.93
1.88
3394.86
Improve HP beyond 1992 and is NMF HP homes. North
I NANHP
104
1989 space conditioning
201
233
0.24
110
0.03
0.21
392.31
Improve HP beyond 1992 mandard in NMH HP homes. South
I NMSHP
183
1988 space coaditioning
252
2.92
0.16
202
0.09
0.07
179.56
Improve RAC ID NMH ER/RAC homes. South
I NMSER
9.6
1989 spece conditioning
3.09
3.58
0
10
0
0
14.64
Improve RAC a NMH son-eloc/RAC homes. South
1 NMSGR
9.6
1989 space conditionis
3.09
3.58
0.03
10
0.03
0
661.76
Increase RAC condenser rows is NSF non-elec/RAC. South
I NSSGR
18
1989 space conditioning
179
4.39
0.03
19
0.03
0
487.22
Increase RAC condrase: TOWS in NSF ER/RAC homes. South
3 NSSER
18
1989 space conditioning
4.51
5.22
0.01
19
0.01
0
165.79
Variable speed RAC 10 NSF BOO-elec/RAC. South (pom-2000)
2 NSSGR
108.8
1989 space conditioning
4.81
557
0.07
115
0.07
0
251.69
0.33
110
0.24
0.09
1350.52
Improve HP beyond 1992 and is NMF HP homes. South
1 NASHP
104
1989 space conditions
5.14
5.95
Improve RAC C is NMH ER/RAC homes. South (pon-2000)
2 NMSER
55.5
1949 space conditioning
3.57
6.45
0
58
0
0
7.72
Improve RAC (2) in NMH noo-ele:/RAC homes. South (post-2000)
2 NMSGR
55.5
1989 space conditionis,
5.57
6.45
0.05
58
0.05
0
348.93
1 NSSGC
308.88
1989 space conditioning
5.66
6.56
3.86
326
3.86
0
5324.68
Improve CAC in NSF AC homes. South
Vanable speed RAC in NSF ER/RAC homes. South (posi-2000)
7 NSSER
108.8
1989 space conditionion
6.73
779
0.02
115
0.02
0
8564
4 NSSEC
90
1989 spece conditioning
6.97
$.07
0.14
95
0.04
0.11
917.45
Improve HP in NSF ER/C AC homes. South
Improve RAC in NMH ERRAC homes. North
1 NMNER
9.6
1989 space conduionis,
7.04
8.15
0
10
0
0
5.53
0.01
0.01
0
316.21
Improve RAC in NMH DOB-Clec/RAC homes. North
1 NMNGR
9.6
1989 space conditioning
704
8.15
10
Improve HP (2) . NMF HP homes. North
2 NANHP
62
1989 space conditioning
7.05
8.17
0.04
65
0
0.04
392.31
Improve CAC beyond 1992 and in NMH ER/CAC homes. South
1 NMSEC
309
1989 space conditionis,
764
8.85
0.22
326
0.22
0
414.36
Improve CAC beyond 1992 and is NMH Booclock homes. South
1 NMSGC
309
1989 space conditions)
7.64
8.85
0.48
326
0.48
0
889.49
BacT RAC evaporator area NSF non-elec/RAC. South (post-2000)
3 NSSGR
13.5
1989 space conditionis,
8.58
9.94
0
14
0
0
251.69
Improve RAC is NMF ER/RAC homes. South
I NASER
9.6
1989 space conditions,
9.72
11.26
0
10
0
0
132.75
Improve RAC in NMF Don-eloc/RAC homes. South
1 NASGR
9.6
1989 space conditioning
9.72
1126
0
10
0
0
230.58
0 07
0
493.45
Variable speed CAC compressor 10 NMF ER/CAC. South
2 NASEC
105
1989 space conditions,
9.9
11.47
0.07
111
Vanable speed CAC compressor in NMF DOD-ciec/C homes. South
2 NASGC
105
1989 space conditions)
99
11.47
0.06
111
0.06
0
444.11
4 NSSHP
109
1989 space condiucion
1158
13.41
0.38
115
0.12
026
3394.86
Improve HP LD NSF HP homes. South
Improve HP (2) is NMH HP homes. South
2 NMSHP
109
1988 space conditioning
11.94
1383
0 02
120
0.01
0.01
179.56
Improve CAC beyond 1992 std LD NMF ER/CAC homes. South
I NASEC
169
1989 space conditionin)
1201
13.91
0.06
178
0.06
0
328.3
Improve CAC beyond 1992 std in NMF Doo-cloc/C homes. South
I NASGC
169
1989 space conditionies
1201
1391
0.06
178
0.06
0
295.48
Increase RAC condenser rows in NSF non-elec/RAC homes North
1 NSNGR
15
1989 space conditions,
1205
13.96
0.02
16
0.02
0
11135
0.08
917.45
Improve HP in NSF ER/CAC homes. South
6 NSSEC
330
1989 space conditioning
1267
14.67
0.29
348
0.21
Improve HP to 9.93 HSPF/15.14 SEER ID NSF HP homes. North
6 NSNHP
330
1989 space conditioning
14.1
1633
0.36
348
0.13
0.23
126473
Improve HP (3) is NMH HP homes. South
3 NMSHP
399
1988 space conditioning
15.43
17.87
0.06
441
0.02
0.04
179.56
Improve CAC to SEER ID NSF ace-elec/CAC homes. North
I NSNGC
264
1989 space conditioning
16.84
1950
1.07
278
1.07
0
5163 82
Improve HP (3) in NMF HP homes. North
3 NANHP
228
1989 space conditioning
17.04
19.74
0.06
240
0.01
0.05
392.31
Improve room AC efficiency is NSF ER/CAC homes. North
6 NSNER
18
1989 space conditioning
17.36
20.11
0
19
0
0
136.18
Improve RAC = in NMF ER/RAC bomes. South (poss-2000)
2 NASER
55.5
1989 space conditioning
17.54
20.32
0
58
0
0
79.72
138.46
Improve RAC (2) in NMF Don-clec/RAC homes. South (post-2000)
2 NASGR
55.5
1989 space conditions,
17.54
2032
0.01
58
0.01
0
Improve HP (#2, in NSF HP homes. South
6 NSSHP
399
1989 space conditionion
17.68
2048
0.92
421
0.72
0.21
3394.86
CAC to 14.87 SEER. NSF aca-elec/CAC homes. South
3 NSSGC
292.5
1989 space conditionis,
18.04
20.89
1.15
308
1.15
0
5324.68
32.91
0.04
65
0.02
0.02
1350.52
Improve HP (2) IC NMF HP homes. South
2 NASHP
62
1989 space coaditionis
28.41
Cooling sa' Heating savings
4.50
9.02
9.01
1.64
7.37
New Shell savings below $
3.99
19.78
19.78
7.32
12.46
New Equipment savings below 8 ccous
4.05
29.89
29.87
168
27.19
Total Shell savings below &
3.46
47 88
47.89
19.27
28 62
Total Equipment savings below &
3.70
77.77
Frozen efficiency use in 2010
223.52
80.63
142.89
Existing
90.61
40.2
5041
New
Tow
323.13
129.83
193.3
*savings
9.3%
11%
14.1%
Total Shell savings below R a
14.8%
14.8%
14.8%
Total Equipment savings below 8 ocets/kWh
24.1%
16.9%
28.9%
EXISTING
CCE AW S/MMBTe pri Total
Cooling
Heating
EXISTING
Tow Shell savings below 1 ceet/Wh
3.89
11.41
9.3%
L3%
139%
Total Shell sevings below 8 ceals/kWh
Total Equipment savings below # could/Wh
3.09
9.06
126%
14.8%
11.3%
Total Equipment asvings below $ cente/kWh
Weighted average existing
Weighted average cliening
143
10.07
21.9%
16.1%
252%
NEW
NEW
Total Shell savings below $ cents/kWh
Total Shell sevings below $ ceals/Wh
4.50
13.18
9.9%
4.1%
14.6%
Total Equipment savings below $
3.99
11.69
21.8%
18.2%
24.7%
Total Equipment savings below 8 cents/kWh
Weighted average NW
4.15
12.15
31.8%
22.3%
39.3%
Weighted average new
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Residential Sector
Heating (Space Conditioning, Gas)
Product/end-use description
Heating, ventilation, and air-conditioning systems (also known as space
conditioning) in residential buildings are a significant energy use. Systems fueled
by electricity involved the use of either central or dispersed space heating and
cooling. The energy use of space conditioning is most significantly affected by the
climate (or number of days in which heating or cooling is required), the efficiency
of the shell of the home, and the efficiency of the heating and cooling equipment.
Base Year Energy Use
Gas space conditioning accounts for an estimated 19% (3.7 quads) of residential
primary energy consumption in 1997. (Source: US EIA, 1996)
End-use Lifetime
The end-use lifetime for electric space conditioning is different for the building
shell and the space conditioning equipment. Lifetime for the shell was estimated at
100 years. The weighted average lifetime for gas space heating equipment was
estimated at 20 years (Koomey et al., 1997b).
Existing Average Unit and New
In our forecast we divide energy consumption between existing and new shells and
Unit Energy Consumption (UEC)
equipment. UECs are calculated for more than 30 different prototypes in North and
South climates, as given in Koomey et al. (1997b).
Maximum Cost-effective Efficiency
The maximum cost-effective efficiency potential was estimated as the savings
Potential
potential assuming the implementation of space conditioning measures costing
less than $6/MMBtu. The savings for equipment efficiency in new and existing
buildings was estimated at 7% (relative to the 1997 baseline efficiencies).
Savings for existing shells are 4%, while savings for new shells are 11%. These
savings can be directly added to the equipment savings because the supply curves
methodology avoids double counting of energy savings.
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential - Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level over the
potential - High Efficiency Case
analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The CCEs are directly calculated in Koomey et al. (1997b) based on the
incremental costs for space conditioning equipment and thermal shell measures.
Prices were adjusted to 1995 levels based on the personal consumption price index
(US DOC, 1996).
Cost of Conserved Energy
The CCE is a ratio of the incremental capital expenditure (amortized over the
lifetime of the appliance) to the annual energy savings expected from the purchase
of the unit. The weighted average CCE for equipment efficiency measures costing
less than $6/MMBtu is $5.0/MMBtu for existing buildings and $5.4/MMBtu for
new buildings. The weighted average CCE for shell efficiency measures costing
less than $6/MMBtu is $4.1/MMBtu for existing buildings and $3.9/MMBtu for
new buildings.
References:
Koomey, Jonathan G., Marla C. Sanchez, Diana Vorsatz, Richard E. Brown, and Celina S. Atkinson. 1997b. The Potential for
Natural Gas Efficiency Improvements in the U.S. Residential Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38893.
in process.
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/E1A-0383(97). Department of Energy, Washington, DC.
B-3.18
Incrmental
CCE
Energy
Gas Heating Efficiency (Measure Code)
Enduse Code Cost
Category
(S/MMBtu)
CCE ($/MMBtu)
Saved
(TBtu)
Applicable
Stock
1995 $
Improve Ceiling Insulation to R-19
ESNGFL
321.9 shell
2.81
3.25
18.65
2017.47
Improve ceiling insulation to R-19
ESNGFLC
321.9 shell
2.81
3.25
17.6
1904.73
Improve ceiling insulation to R-19
ESNGFLR
321.9 shell
2.81
3.25
14.1
1525.3
Improve insulation to ceiling R-19 & reduce infiltration by 25%
ESNGBL
580 shell
3.15
3.65
6.56
442.19
Improve insulation to ceiling R-19 & reduce infiltration by 25%
ESNGBLC
580 shell
3.15
3.65
6.19
417.48
Improve insulation to ceiling R-19 & reduce infiltration by 25%
ESNGBLR
580 shell
3.15
3.65
4.96
334.31
Improve insulation to ceiling R-19 and reduce infiltration by 25%
ESSGBL
759.13 shell
4.07
4.71
0.38
25.5
Improve insulation to ceiling R-19 & reduce infiltration 25%
ESSGBLC
759.13 shell
4.07
4.71
0.86
57.13
Improve insulation to ceiling R-19 and reduce infiltration 25%
ESSGBLR
759.13 shell
4.07
4.71
0.42
27.75
Reduce infiltration by 25% & add double pane-wood frame window
ESNGBT
334.76 shell
4.65
5.39
2.7
464.92
Reduce infiltration by 25%, add double pase-wood frame window
ESNGBTC
334.76 shell
4.65
5.39
2.54
438.93
Reduce infiltration by 25% & add double pane-wood frame window
ESNGBTR
334.76 shell
4.65
5.39
2.04
351:5
Improve insulation to wall R-11 &reduce infiltration additional 25%
ESNGBL
1492.81 shell
4.68
5.42
11.37
442.19
Improve insulation to wall R-11 & reduce infiltration additional 25%
ESNGBLC
1492.81 shell
4.68
5.42
10.74
417.48
Improve insulation to wall R-11 & reduce infiltration additional 25%
ESNGBLR
1492.81 shell
4.68
5.42
8.6
334.31
Reduce infilatration by 25%
ESSGFT
222.51 shell
5.01
5.80
2.98
832.27
Reduce infiltration by 25%
ESSGFTC
22251 shell
5.01
5.80
6.68
1864.85
Reduce infiltration by 25%
ESSGFTR
222.51 shell
5.01
5.80
3.24
905.89
Reduce infiltration by 25% & improve wall insulation to R-11
ESNGFL
1492.81 shell
5.02
5.81
48.33
2017.47
Reduce infiltration by 25% & improve wall insulation to R-11
ESNGFLC
1492.81 shell
5.02
5.81
45.63
1904.73
Reduce infiltration by 25% & improve wall insulation to R-11
ESNGFLR
1492.81 shell
5.02
5.81
36.54
1525.3
Reduce Infiltration by 25%
ESSGBT
222.51 shell
5.13
5.94
0.07
20.32
Reduce Infiltration by 25%
ESSGBTC
222.51 shell
5.13
5.94
0.16
45.54
Reduce Infiltration by 25%
ESSGBTR
222.51 shell
5.13
5.94
0.08
22.12
Reduce infilatration by 25% & improve insulation to ceiling R-19
ESSGFL
759.13 shell
5.27
6.10
12.13
1044.21
Reduce infilatration by 25% & improve insulation to ceiling R-19
ESSGFLC
759.13 shell
5.27
6.10
27.18
2339.74
Reduce infilatration by 25% & improve insulation to ceiling R-19
ESSGFLR
759.13 shell
5.27
6.10
13.2
1136.59
Improve window to Double Pane-Wood Frame, reduce infiltration 25%
ESNGFT
334.76 shell
5.29
6.13
10.81
2121.17
Improve window to double pane-wood frame & recrease Infilatration 25%
ESNGFTC
334.76 shell
5.29
6.13
10.21
2002.63
Improve window to double pane-wood frame & reduce infilatration 25%
ESNGFTR
334.76 shell
5.29
6.13
8.17
1603.7
Improve insulation to wall R-11
ESSGBL
735.73 shell
5.52
6.39
0.27
25.5
Improve insulation to wall R-11
ESSGBLC
735.73 shell
5.53
6.41
0.61
57.13
Improve insulation to wall R-11
ESSGBLR
735.73 shell
5.53
6.41
0.3
27.75
Improve insulation to ceiling R-27, add 2-giz,low-E. argon windows
ESNGBL
665.94 shell
5.6
6.49
4.24
442.19
Improve insulation to ceiling R-27 & replace with 2-glz.Jow-E. argon
ESNGBLC
665.94 shell
5.6
6.49
4
417.48
Improve insulation to ceiling R-27 & add 2-glz.Jow-E, argon windows
ESNGBLR
665.94 shell
5.6
6.49
3.2
334.31
Reduce ACH additional 25%.Add Ceiling R-27, 2-giz low-E. argon
ESNGFL
924.04 shell
6.1
7.07
24.61
2017.47
Reduce infl additional 25%.Add Ceiling R-27, 2-giz. low-E, argon
ESNGFLC
924.04 shell
6.1
7.07
23.23
1904.73
Reduce infl additional 25%. add Ceiling R-27. 2-giz. low-E, argon
ESNGFLR
924.04 shell
6.1
7.07
18.6
1525.3
Improve window to 2-81z low-e. argon (from double-wood)
ESNGFT
507.82 shell
6.58
7.62
13.19
2121.17
Improve window to 2-giz low-e. argon (from double-wood)
ESNGFTC
507.82 shell
6.58
7.62
12.45
2002.63
Improve window to 2-giz low-e, argon (from double-wood)
ESNGFTR
507.82 shell
6.58
7.62
9.97
1603.7
Reduce infiltration by an additional 25%
ESSGBT
222.51 shell
7.1
8.22
0.05
20.32
Reduce infiltration additional 25%
ESSGBTC
222.51 shell
7.1
8.22
0.11
45.54
Reduce infiltration by an additional 25%
ESSGBTR
222.51 shell
7.1
8.22
0.06
22.12
Reduce infilatration additional 25% & improve insulation to wall R-11
ESSGFL
958.23 shell
7.55
8.74
10.68
1044.21
Reduce infilatration additional 25% & improve insulation to wall R-11
ESSGFLC
958.23 shell
7.55
8.74
23.92
2339.74
Reduce infilatration additional 25% & improve insulation to wall R-11
ESSGFLR
958.23 shell
7.55
8.74
11.62
1136.59
Reduce infilatration by additional 25%
ESSGFT
222.51 shell
8.09
9.37
1.84
832.27
Reduce infiltration by an additional 25%
ESSGFTC
222.51 shell
8.09
9.37
4.13
1864.85
Reduce infiltration by additional 25%
ESSGFTR
222.51 shell
8.09
9.37
2.01
905.89
Improve insulation to ceiling R-27 & Reduce infiltration additional 25%
ESSGBL
364.39 shell
8.41
9.74
0.09
25.5
Improve insulation to ceiling R-27 & Reduce infiltration additional 25%
ESSGBLC
364.39 shell
8.41
9.74
0.2
57.13
Improve insulation to ceiling R-27
ESSGBLR
364.39 shell
8.41
9.74
0.1
27.75
Improve windows to 2-giz, low-E argon (from double-wood)
ESNGBT
507.82 shell
10.26
11.88
1.85
464.92
Improve window to 2-giz. low-E, argon (from double-wood)
ESNGBTC
507.82 shell
10.26
11.88
1.75
438.93
Improve window to 2-glz, low-E, argon (from double-wood)
ESNGBTR
507.82 shell
10.26
11.88
1.4
351.5
Improve insulation to ceiling R-19
ESNGBT
386.65 shell
10.47
12.13
1.38
464.92
Improve insulation to ceiling R-19
ESNGBTC
386.65 shell
10.47
12.13
1.31
438.93
Improve insulation to ceiling R-19
ESNGBTR
386.65 shell
10.47
12.13
1.05
351.5
Improve windows toSuperwindow & increase to floor R-11
ESNGBL
1316.14 shell
11.53
13.35
4.07
442.19
Improve window to superwindow (from 2-giz,low-E,argon). add floor R-11 ESNGBLC
1316.14 shell
11.53
13.35
3.84
417.48
Improve window to Superwindow (from 2-giz.low-E,argon). add floor R-11 ESNGBLR
1316.14 shell
11.53
13.35
3.07
334.31
Improve window to double pane-wood frame
ESSGFL
171.63 shell
12.66
14.66
1.14
1044.21
Improve window to double pane-wood frame
ESSGFLC
171.63 shell
12.66
14.66
2.56
2339.74
Improve window to double pane-wood frame
ESSGFLR
171.63 abell
12.66
14.66
1.24
1136.59
Improve insulation to floor R-11, floor R-19, ceiling R-30
ESNGFL
1263.27 abell
12.82
14.85
16.02
2017.47
Improve insulation to floor R-11, floor R-19 & ceiling R-30
ESNGFLC
1263.27 shell
12.82
14.85
15.12
1904.73
Improve insulation to floor R-11, floor R-19 & ceiling R-30
ESNGFLR
1263.27 shell
12.82
14.85
1211
1525.3
Improve insulation to floor R-11& wall R-11
ESNGBT
2463.97 abell
12.99
15.05
7.11
464.92
Improve insulation to floor R-11& wall R-11
ESNGBTC
2463.97 shell
12.99
15.05
6.71
438.93
Improve insulation to floor R-11 & wall R-11
ESNGBTR
2463.97 shell
12.99
15.05
537
351.5
Improve insulation to floor R-19 & ceiling R-30
ESNGBL
339.76 shell
13.41
15.53
0.9
442.19
Improve insulation to floor R-19 & ceiling R-30
ESNGBLC
339.76 shell
13.41
15.53
0.85
417.48
Improve insulation to floor R-19 & ceiling R-30
ESNGBLR
339.76 shell
13.41
15.53
0.68
334.31
Improve windows to 2-giz Low-E, argon
ESSGBL
526.88 shell
14.22
16.47
0.08
25.5
Improve windows to 2-giz, Low-E, argon
ESSGBLC
526.88 shell
14.22
16.47
0.17
57.13
Improve windows to 2-giz, Low-E, argon
ESSGBLR
526.88 shell
14.22
16.47
0.08
27.75
Improve insulation to ceiling R-19, wall R-11 & floor R-11
ESNGFT
2850.62 shell
14.31
16.57
34.05
2121.17
Improve insulation to ceiling R-19. wall R-11 & floor R-11
ESNGFTC
2850.62 shell
14.31
16.57
32.15
2002.63
Improve insulation to ceiling R-19. wall R-11 & floor R-11
ESNGFTR
2850.62 ahell
14.31
16.57
25.75
1603.7
Improve windows to double pane-wood frame
ESSGBT
212.55 shell
14.48
16.77
0.02
20.32
6/9/97
Improve windows to double-wood frame
ESSGBTC
212.55 shell
14.48
16.77
0.05
45.54
Improve windows to double-wood frame
ESSGBTR
212.55 shell
14.48
16.77
0.03
22.12
Improve insulation to ceiling R-27 & floor R-19. add superwindow
ESNGBT
945.39 shell
14.72
17.05
2.41
464.92
Improve insulation to ceiling R-27 & floor R-19. add superwindow
ESNGBTC
945.39 shell
14.72
17.05
2.27
438.93
Improve insulation to Ceiling R-27 & floor R-19, add Superwindows
ESNGBTR
945.39 shell
14.72
17.05
1.82
351.5
Improve to ceiling R-27 & improve to 2-81z low-E argon (from double)
ESSGFL
497.14 shell
14.78
17.12
2.83
1044.21
Improve ceiling insulation to R-27, 2-glz & low-E. argon (from double)
ESSGFLC
497.14 shell
14.78
17.12
6.34
2339.74
Improve to ceiling R-27 & improve to 2-giz low-E. argon (from double)
ESSGFLR
497.14 shell
14.78
17.12
3.08
1136.59
Improve window to double pane-wood frame
ESSGFT
212.55 shell
15.68
18.16
0.91
832.27
Improve window to double pane-wood frame
ESSGFTC
212.55 shell
15.68
18.16
2.04
1864.85
Improve window to double pane-wood frame
ESSGFTR
212.55 shell
15.68
18.16
0.99
905.89
Improve window to superwindow (from 2glz. low-E. argon)
ESNGFL
392.63 shell
16.31
18.89
3.91
2017.47
Improve window to superwindow (from 2glz low-E. argon)
ESNGFLC
392.63 shell
16.31
18.89
3.7
1904.73
Improve window to superwindow (from 2g1z low-E, wgon)
ESNGFLR
392.63 shell
16.31
18.89
2.96
1525.3
Improve insulation to ceiling R-27 & floor R-19
ESNGFT
446.64 shell
16.72
19.37
4.57
2121.17
Improve insulation to ceiling R-27 & floor R-19
ESNGFTC
446.64 shell
16.72
19.37
4.31
2002.63
Improve insulation to ceiling R-27 & floor R-19
ESNGFTR
446.64 shell
16.72
19.37
3.45
1603.7
Improve windows to 2-81z low-e. argon (from double-wood)
ESSGBT
439.95 shell
16.74
19.39
0.04
20.32
Improve windows to 2-81z low-e, argon (from double-wood)
ESSGBTC
439.95 shell
16.74
19.39
0.1
45.54
Improve windows to 2-giz low-e, argon (from double-wood)
ESSGBTR
439.95 shell
16.74
19.39
0.05
22.12
Improve window to superwindow (from 2-giz low-e,argon)
ESNGFT
498.75 shell
16.77
19.42
5.08
2121.17
Improve window to superwindow (from 2-giz low-e, argon)
ESNGFTC
498.75 shell
16.77
19.42
4.8
2002.63
Improve window to Superwindow (from 2-giz low-e,argon)
ESNGFTR
498.75 shell
16.77
19.42
3.84
1603.7
Improve window to 2-giz.Jow-E,argon (from double) & add wall R-11
ESSGFT
1260.08 shell
19.98
23.14
4.23
832.27
Improve window to 2-giz.low-E,argon (from Double) & add wall R-11
ESSGFTC
1260.08 shell
19.98
23.14
9.48
1864.85
Switch to 2-giz.low-E.argon (from Double). Add Wall R-11
ESSGFTR
1260.08 shell
19.98
23.14
4.61
905.89
Improve window to Superwindow (from 2-gizJow-E,xgon)
ESSGFL
348.92 shell
99.83
115.63
0.29
1044.21
Improve window to superwindow (from 2-giz,low-E,argon)
ESSGFLC
348.92 shell
99.83
115.63
0.66
2339.74
Improve window to superwindow (from 2-giz.low-E.argon)
ESSGFLR
348.92 shell
99.83
115.63
0.32
1136.59
Improve to Condensing Gas Furnace: Ex. SF/North/no shell
ESNGFL
432.42 space con.
3.74
4.33
26.89
2305.68
Improve to condensing gas furnace: Ex SF/North/CAC/Loosc shell
ESNGFLC
432.42 space con
3.74
4.33
25.39
2176.83
Improve to condensing gas furnace; Ex. SF/North/RAC/Loosc shell
ESNGFLR
432.42 space COD.
3.74
4.33
20.33
1743.2
Improve to condensing gas furnace: Ex. SF/North/no clc/Tight shell
ESNGFT
432.42 space COD.
4.67
5.41
22.64
2424.19
Improve to condensing gas furnace: Ex. SF/North/CAC/Tight shell
ESNGFTC
432.42 space con.
4.67
5.41
21.38
2288.72
Improve to condensing gas furnace; Ex SF/North/RAC/Tight shell
ESNGFTR
432.42 space con.
4.67
5.41
17.12
1832.8
Improve to condensing gas furnace: E1 SF/South/no cig/Loose shell
ESSGFL
432.42 space con.
4.7
5.44
11.08
1193.39
Improve to condensing gas furnace: Ex SF/South/CAC/Loose shell
ESSGFLC
432.42 space con.
4.7
5.44
24.82
2673.99
Improve to condensing gas furnace; Ex. SF/South/RAC/Loose shell
ESSGFLR
432.42 space COD.
4.7
5.44
12.06
1298.96
Improve to condensing gas furnace; Ex. MF/North/no cig
EANGF
432 space COD.
4.98
5.77
9.15
1046.59
Improve to condensing gas furnace: Ex. MF/North/CAC
EANGFC
432 space COD.
4.98
5.77
2.73
311.94
Improve to condensing gas furnace; Ex. MF/North/RAC
EANGFR
432 space con.
4.98
5.77
9.91
1133.81
Improve to condensing gas furnace
ESSGFT
432.42 space con.
6.48
7.51
6.4
951.16
Improve to condensing gas furnace: Ex. SF/South/CAC/Tight shell
ESSGFTC
432.42 space con.
6.48
7.51
14.34
2131.25
Improve to condensing gas furnace; Ex. SF/South/RAC/Tight shell
ESSGFTR
432.42 space con
6.48
751
6.97
1035.31
Improve to condensing gas furnace; Ex. MH/North/no cig
EMNGF
432 space con.
6.81
7.89
2.59
404.01
Improve to condensing gas furnace: Ex. MH/North/CAC
EMNGFC
432 space con.
6.81
7.89
1.56
243.93
Improve to condensing gas furnace: Ex. MH/North/RAC
EMNGFR
432 space con.
6.81
7.89
1.52
237.28
Improve to condensing gas furnace; Ex. MH/South/no cig
EMSGF
432 space con
13.5
15.64
1.39
432.13
Improve to condensing gas furnace; Ex. MH/South/CAC
EMSGPC
432 space con.
13.5
15.64
1.07
331.19
Improve to condensing gas furnace; Ex. MH/South/RAC
EMSGFR
432 space con.
13.5
15.64
1.57
487.3
Improve to condensing gas furnace; Ex. MF/South/no cig
EASGF
432 space con.
15.17
17.57
1.73
601.31
Improve to condensing gas furnace; Ex. MF/South/CAC
EASGRC
432 space con
15.17
17.57
1.89
658.49
Improve to condensing gas furnace; Ex. MF/South/RAC
EASGFR
432 space con.
15.17
17.57
1.2
417.86
Improve to a condensing gas boiler, Ex. MF/North/no clg
EANGB
1245 space con.
15.58
18.05
7.1
1035.99
Improve to a condensing gas boiler. Ex. MF/North/CAC
EANGBC
1245 space con.
15.58
18.05
2.12
308.78
Improve to a condensing gas boiler. Ex. MF/North/RAC
EANGBR
1245 space con
15.58
18.05
7.7
1122.32
Improve to a condensing gas boiler, Ex. MH/North/no clg
EMNGB
1245 space con.
22.02
25.50
0
0
Improve to a condensing gas boiler, Ex. MH/North/CAC
EMNGBC
1245 space COD.
22.02
25.50
0
0
Improve to a condensing gas boiler, Ex. MH/North/RAC
EMNGBR
1245 space con.
22.02
25.50
0
0
Improve to condensing boiler, Ex. SF/South/no cig/Loose shell
ESSGBL
1126.1 space con:
26.88
31.13
0.07
20.4
Improve to condensing boiler, Ex. SF/South/CAC/Loose shell
ESSGBLC
1126.1 space con
26.88
31.13
0.16
45.71
Improve to condensing boiler, Ex. SF/South/RAC/Looec shell
ESSGBLR
1126.1 space con
26.88
31.13
0.08
22.2
Improve to condensing boiler. Ex. SF/North/no clg/Tight shell
ESNGBT
1126.1 space con
28.49
33.00
1.26
371.93
Improve to condensing boiler, Ex. SF/North/CAC/Tight shell
ESNGBTC
1126.1 space con
28.49
33.00
1.19
351.15
Improve to condensing boiler; Ex. SF/North/RAC/Tight shell
ESNGBTR
1126.1 space CODE
28.49
33.00
0.95
281.2
Improve to condensing boiler, Ex. SF/South/no clg/Tight shell
ESSGBT
1126.1 space con
29.62
34.31
0.05
16.26
Improve to condensing boiler; Ex. SF/South/CAC/Tight shell
ESSGBTC
1126.1 space con
29.62
34.31
0.12
36.43
Improve to condensing boiler. Ex. SF/South/RAC/Tight shell
ESSGBTR
1126.1 space COOK
29.62
34.31
0.06
17.7
Improve to condensing boiler, Ex. SF/North/no cig/Loose shell
ESNGBL
1126.1 space CODE
31.94
36.99
1.07
353.75
Improve to condensing boiler: Ex. SF/North/CAC/Looec shell
ESNGBLC
1126.1 space com
31.94
36.99
1.01
333.98
Improve gas boiler to condensing boiler
ESNGBLR
1126.1 space CODE
31.94
36.99
0.81
267.45
Improve to a condensing gas boiler, Ex. MH/South/so cig
EMSGB
1245 space con
43.64
50.55
0
0
Improve to a condensing gas boiler, Ex. MH/South/CAC
EMSGBC
1245 space con
43.64
50.55
0
0
Improve to a condensing gas boiler, Ex. MH/South/RAC
EMSGBR
1245 space CODE
43.64
50.55
0
0
Improve to a condensing gas boiler, Ex. MF/South/no clg
EASGB
1245 space com
47.43
54.94
0.16
69.29
Improve to a condensing gas boiler, Ex. MF/South/CAC
EASGBC
1245 space CODE
47.43
54.94
0.17
75.88
Improve to a condensing gas boiler, Ex. MF/South/RAC
EASGBR
1245 space con
47.43
54.94
0.11
48.15
Existing Shell savings below 6$/MMBru
4.10
107.71
Existing Equipment savings below 6S/MMBtu
4.99
181.71
Increase insulation to celing value 30 & reduce infiltration 25%
NSNGF
300.65 shell
3.03
3.51
4.64
579.56
Improve insulation to ceiling R-30 & reduce infiltration 25%
NSNGFC
300.65 shell
3.03
3.51
39.54
4941.46
Improve insulation to ceiling R-30 8 reduce infiltration 25%
NSNGFR
300.65 shell
3.03
3.51
3.42
427
Improve insulation to ceiling R-30 & reduce Infiltration by 25%
NSNGB
300.65 shell
3.11
3.60
1.05
135.19
Improve insulation to ceiling R-30 & reduce infiltration by 25%
NSNGBC
300.65 shell
3.11
3.60
0.5
63.68
Improve insulation to ceiling R-30 & reduce infiltration by 25%
NSNGBR
300.65 shell
3.11
3.60
0.81
104.48
Reduce infiltration by 36%
NSSGF
274.57 shell
3.76
4.35
0.89
151.61
Reduce infiltration by 25%
NSSGPC
274.57 shell
3.76
4.35
21.43
3641.25
Reduce infilatration by 25%
NSSGFR
274.57 shell
3.76
4.35
0.88
149.95
Reduce infiltration by 25%
NSSGB
274.57 shell
3.86
4.47
1.02
177.51
Reduce infiltration by 25%
NSSGBC
274.57 shell
3.86
4.47
8.39
1463.19
Reduce infiltration by 25%
NSSGBR
274.57 shell
3.86
4.47
1.18
204.88
Improve insulation to wall R-19
NSNGB
284.31 shell
5.03
5.83
0.62
135.19
Improve insulation to wall R-19
NSNGBC
284.31 shell
5.03
5.83
0.29
63.68
Improve insulation to wall R-19
NSNGBR
284.31 shell
5.03
5.83
0.48
104.48
Improve insulation to foundation R5.2ft
NSSGF
376.39 shell
5.7
6.60
0.81
151.61
Improve insulation to foundation R5,2ft
NSSGFC
376.39 shell
5.7
6.60
19.39
3641.25
Improve insulation to foundation R5,2ft
NSSGFR
376.39 shell
5.7
6.60
0.8
149.95
Improve insulation to wall R-19
NSNGF
284.31 shell
5.72
6.63
2.32
579.56
Improve insulation to wall R-19
NSNGFC
284.31 shell
5.72
6.63
19.79
4941.46
Improve insulation to wall R-19
NSNGFR
284.31 shell
5.72
6.63
1.71
427
Improve foundation insulation to R- 5.2
NSSGB
376.39 shell
5.84
6.76
0.92
177.51
Improve foundation to R. 5,2 ft
NSSGBC
376.39 shell
5.84
6.76
7.6
1463.19
Improve foundation insulation to R-5,2 ft
NSSGBR
376.39 shell
5.84
6.76
1.06
204.88
Improve insulation to ceiling R-38 & floor R-30
NSNGB
432.93 shell
6.43
7.45
0.73
135.19
Improve insulation to ceiling R-38 & floor R-30
NSNGBC
432.93 shell
6.43
7.45
0.35
63.68
Improve insulation to ceiling R-38 & floorR-30
NSNGBR
432.93 shell
6.43
7.45
0.57
104.48
Improve insulation to floor R-30 & ceiling R-38
NSNGF
432.93 shell
7.31
8.47
2.77
579.56
Improve insulation to floor R-30 & ceiling R-38
NSNGFC
432.93 shell
7.31
8.47
23.59
4941.46
Improve insulation to floor R-30 & ceiling R-38
NSNGFR
432.93 shell
7.31
8.47
2.04
427
Improve insulation to ceiling R-49
NSNGF
108.23 shell
9.23
10.69
0.55
579.56
Improve insulation to ceiling R-49
NSNGPC
108.23 shell
9.23
10.69
4.67
4941.46
Improve insulation to ceiling R-49
NSNGFR
108.23 shell
9.23
10.69
0.4
427
Improve insulation to ceiling R-49 & add double pane-wood frame window
NSNGB
565.49 shell
9.86
11.42
0.62
135.19
Improve insulation to ceiling R-49. add double pane-wood windows
NSNGBC
565.49 shell
9.86
11.42
0.29
63.68
Improve insulation to ceiling R-49, add double pane-wood frame windows
NSNGBR
565.49 shell
9.86
11.42
0.48
104.48
Improve window to 2-glz. low-E. argon (from double-wood)
NSNGB
618.11 shell
10.55
12.22
0.64
135.19
Improve windows to 2-glz low-E, argon (from double-wood)
NSNGBC
618.11 shell
10.55
12.22
0.3
63.68
Improve windows to 2-8iz, low-E argon (from double-wood)
NSNGBR
618.11 shell
10.55
12.22
0.49
104.48
Improve window to superwindow (from 2-giz, Low-E, argon)
NSNGB
607.08 shell
13.27
15.37
0.5
135.19
Improve windows to superwindow (from 2-giz Low-E, argon)
NSNGBC
607.08 shell
13.27
15.37
0.23
63.68
Improve windows to superwindow (from 2-giz. Low-E argon)
NSNGBR
607.08 shell
13.27
15.37
0.39
104.48
Improve insulation to ceiling R-30 & wall R-19
NSSGB
503.38 shell
14.67
16.99
0.49
177.51
Improve insulation to ceiling R-30 & wall R-19
NSSGBC
503.38 shell
14.67
16.99
4.05
1463.19
Improve insulation to ceiling R-30 & wall R-19
NSSGBR
503.38 shell
14.67
16.99
0.57
204.88
Improve insulation to ceiling R-30 & wall R-19
NSSGF
549.14 abell
15.6
18.07
0.43
151.61
Improve insulation to ceiling R-30 & wall R-19
NSSGFC
549.14 shell
15.6
18.07
10.33
3641.25
Improve insulation to ceiling R-30 & wall R-19
NSSGFR
549.14 shell
15.6
18.07
0.43
149.95
Improve window to 2-giz, low E. argon
NSSGF
903.9 shell
15.86
18.37
0.7
151.61
Improve windows to 2-giz, low E, argon
NSSGPC
903.9 shell
15.86
18.37
16.72
3641.25
Improve windows to 2-giz. low E. argon
NSSGFR
903.9 shell
15.86
18.37
0.69
149.95
Improve windows to 2-giz, low-E, argon
NSSGB
903.9 shell
16.27
18.84
0.79
177.51
Improve windows to 2-giz. low-E, argon
NSSGBC
903.9 shell
16.27
18.84
6.55
1463.19
Improve windows to 2-giz low-E, argon window
NSSGBR
903.9 shell
16.27
18.84
0.92
204.88
Improve to condensing gas furnace; New SF/North/no clg
NSNGF
432.42 space CODE
4.65
5.39
5.44
579.56
Improve to condensing gas furnace; New SF/North/CAC
NSNGPC
432.42 space con
4.65
5.39
46.4
4941.46
Improve to condensing gas furnace: New SF/North/RAC
NSNGFR
432.42 space COB
4.65
5.39
4.01
427
Improve to condensing gas furnace; New MH/North/no dg
NMNGF
432.42 space CODE
7.01
8.12
1.35
217.1
Improve to condensing gas furnace; New MH/North/CAC
NMNGPC
432.42 space CODE
7.01
8.12
2.67
428.81
Improve to condensing gas furnace; New MH/North/RAC
NMNGFR
432.42 space con
7.01
8.12
0.79
127.5
Improve to condensing gas furnace: New MF/North/no clg
NANGF
432.42 space con
8.53
9.88
0.19
37.52
Improve to condensing gas furnace; New MF/North/CAC
NANGFC
432.42 space con
8.53
9.88
6.39
1250.53
Improve to condensing gas furnace: New MF/North/RAC
NANGFR
432.42 space con
8.53
9.88
0.21
40.64
Improve to condensing gas furnace; New MH/South/no dg
NMSGF
432.42 space com
13.52
15.66
0
0
Improve to condensing gas furnace; New MH/South/CAC
NMSGFC
432.42 space CODE
13.52
15.66
0
0
Improve to condensing gas furnace; New MH/South/RAC
NMSGFR
432.42 space con
13.52
15.66
0
0
Improve to condensing gas furnace; New SF/South/no cig
NSSGF
432.42 space CODE
13.88
16.08
0.48
151.61
Improve to condensing gus furnace; New SF/South/CAC
NSSGFC
432.42 space COD.
13.88
16.08
11.44
3641.25
Improve to condensing gas furnace; New SF/South/RAC
NSSGFR
432.42 space CODE
13.88
16.08
0.47
149.95
Improve to condensing boiler, New MH/North/no cig
NMNGB
1250.04 space COOK
22.74
26.34
0
0
Improve to condensing boiler, New MH/North/CAC
NMNGBC
1250.04 space CODE
22.74
26.34
0
0
Improve to condensing boiler. New MH/North/RAC
NMNGBR
1250.04 space COD
22.74
26.34
0
0
Improve to condensing boiler, New MF/North/no dg
NANGB
1250.04 space come
25.59
29.64
1
239.68
Improve to condensing boiler, New MF/North/CAC
NANGBC
1250.04 space COD<
2559
29.64
0
0
Improve to condensing boiler, New MF/North/RAC
NANGBR
1250.04 space com
25.59
29.64
1.09
259.66
Improve to condensing boiler. New MH/South/no clg
NMSGB
1250.04 space con
43.83
50.77
0
0
Improve to condensing boiler. New MH/South/CAC
NMSGBC
1250.04 space cote
43.83
50.77
0
0
Improve to condensing boiler, New MH/South/RAC
NMSGBR
1250.04 space con
43.83
50.77
0
0
Improve to condensing gas furnace: New MF/South/no cig
NASGF
432.42 space CODI
54.36
62.96
0.19
237.82
Improve to condensing gas furnace; New MF/South/CAC
NASGRC
432.42 space COD.
54.36
62.96
0.56
701.62
Improve to condensing gas furnace: New MF/South/RAC
NASGFR
432.42 space con.
54.36
62.96
0.13
165.26
Improve to condensing boiler, New MF/South/no dg
NASGB
1250.04 space con.
163.07
188.87
0
0
Improve to condensing boiler, New MF/South/CAC
NASGBC
1250.04 space COOL
163.07
188.87
0
0
Improve to condensing boiler. New MF/South/RAC
NASGBR
1250.04 space COD.
163.07
188.87
0
0
New Shell savings below 6S/MMBru
3.87
83.75
New Equipment savings below 6S/MMBtu
5.39
55.85
1997 S/MMBru
Total Shell savings below 6S/MMBtu
4.00
191.46
Total Equipment savings below 6S/MMBru
5.08
237.56
4.60
429.02
Frozen efficiency use in 2010
Existing
2631.06
New
754.52
Total
3,386.00
% savings
% Savings
Total Shell savings below 6S/MMBtu
5.7%
Total Equipment savings below 6$/MMBtu
7.0%
127%
EXISTING
EXISTING
CCE $/MMBts
% savings
Total Shell savings below 6$/MMBru
Total Shell savings below 6S/MMBtu
4.10
4.1%
Total Equipment savings below 6S/MMBtu
Total Equipment savings below 6S/MMBtu
4.99
6.9%
NEW
NEW
4.66
11.0%
Total Shell savings below 6$/MMBtu
Total Shell savings below 6S/MMBtu
3.87
11.1%
Total Equipment savings below 6S/MMBtu
Total Equipment savings below 6S/MMBtu
5.39
7.4%
4.48
185%
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Commercial Sector
Heating, Ventilation, and Air Conditioning (Space Conditioning, all fuels)
Product/end-use description
Heating, ventilation, and air-conditioning systems (also known as space
conditioning) in commercial buildings are a significant energy use. Space
conditioning energy use is affected by internal thermal gains from occupants and
equipment, the characteristics of the ventilation system, the climate, the efficiency
of the heating and cooling equipment. and the efficiency of the building shell.
Base Year Energy Use
Space conditioning accounts for an estimated 28% (4.1 quads) of commercial
primary energy consumption in 1997, with 2.6 quads of electricity and the rest
from oil and gas (Source: US EIA, 1996)
End-use Lifetime
The end-use lifetime for space conditioning is different for the building shell and
the space conditioning equipment. Lifetime for the shell was estimated at 50
years. The weighted average lifetime for all space conditioning equipment is
estimated at 18 years (Koomey et al., 1997a).
Existing Average Energy Use Index
In our forecast we divide energy consumption between existing and new shells and
(EUI in kBtu/sf)
equipment. EUIs are taken from US EIA (1996).
1997 New Energy Use Index (EUI
In our forecast we divide energy consumption between existing and new shells and
in kBtu/sf)
equipment. EUIs are taken from US EIA (1996).
Maximum Cost-effective Efficiency
We used data from Sezgen et al. (1995) and plotted the total EUI (primary energy
Potential
terms) for all common combinations of commercial building systems against the
capital costs of the systems. The system types are: Ducted, Unitary, Fan Coil,
Heating Only, and Miscellaneous systems. We then grouped the systems of
common type together, and calculated the weighted average EUI for the typical
new system for each type. We then read the efficiency factors off the graph by
looking at the percentage reduction from the typical system for switching to the
best system of that type, and then weighted by the floor area attributable to each
system type. The cost of achieving a 50% reduction in EUI for the ducted systems
is $0.54/sf (1995$). The cost of achieving a 40% reduction in EUI for the unitary
systems is $0.54/sf (1995$). Fan coils, heating only, and Miscellaneous systems
are assumed to be able to achieve 20% savings for a cost of $0.22/sf. Controls are
assumed to save an additional 10% on all systems for an additional cost of
$0.22/sf. The weighted average energy savings factor based on these assumptions
is 48%, which applies to all heating, ventilation, and air conditioning energy use.
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential - Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level over the
potential - High Efficiency Case
analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The CCEs are directly calculated based on the EUIs from the work documented in
Sezgen et al (1995). Prices were adjusted to 1995 levels based on the personal
consumption price index (US DOC, 1996).
Cost of Conserved Energy
The CCE is a ratio of the incremental capital expenditure (amortized over the
lifetime of the appliance) to the annual energy savings expected from the purchase
of the unit. The weighted average CCE for HVAC end-uses is $1.3/MMBtu.
This cost applies to all heating, ventilation, and air conditioning energy use.
References:
Sezgen, A. Osman, Ellen M. Franconi, Jonathan G. Koomey, Steve E. Greenberg, and Asim Afzal. 1995. Technology data
characterizing space conditioning in commercial buildings: Application to end-use forecasting with COMMEND 4.0. Lawrence
Berkeley Laboratory. LBL-37065. December.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/EIA-0383(97). Department of Energy: Washington, DC.
B-3.19
Commerci
AC
treat all commercial HVAC together. Osman has created EUIs using primary energy (10800 Btu/kwh) and adding up all fuel use.
The reference for this is
Sezgen, A. Osman, Ellen M. Franconi, Jonathan G. Koomey. Steve E. Greenberg. and Asim Afzal. 1995. Technology data characterizing space conditioning in commercial buildings
Application to end-use forecasting with COMMEND 4.0. Lawrence Berkeley Laboratory. LBL-37065. December.
We pulled out the data on the different system types from this report, estimated EUIs by system type (converting electricity to primary energy),
and plotted the data by system type. We then used the graph of capital cost versus EUI for each system type to estimate the percentage savings
that can be purchased for a given cost/sf. Controls are assumed to save 10% for an additional $0.20/sf capital cost.
New bdgs
Weighted
Total
CCE
EUI
Savings
Savings w/
Savings w/
Savings w/
Cost
Cost/sf
Cost w/
1995 $/MMBtu
primary E
controls
controls
controls
1992 $/sf
1995$/sf
controls
% of floor area
kBtu/sf/yr
kBtu/sf/yr
kBtu/sf/yr
1995 $/sf
Ducted systems
26%
148.3
50%
55%
81.57
21.21
0.5
0.54
0.75
0.87
Unitary systems
26%
52.9
40%
46%
24.32
6.32
0.5
0.54
0.75
2.92
Fan coil systems (1)
6%
40.6
20%
28%
11.36
0.64
0.2
0.22
0.43
3.58
Heating only
15%
47.5
20%
28%
13.29
1.98
0.2
0.22
0.43
3.06
Miscellaneous systems
10%
40.6
20%
28%
11.36
1.12
0.2
0.22
0.43
3.58
Unconditioned space
18%
0.0
0%
0%
0.00
0.00
0
0
0
100%
79.7
37.95
1.30
(1) 2% of fan coil floor area uses district beat, and 4% uses standard packaged equipment (total = 6%)
(2) Assume miscellaneous systems have same EUI as fan coil systems.
(3) Controls assumed to save 10% for a cost of $0.20/sf.
Savings
48%
Costs
4.11 1995 $/MMBtu site
discount rate
7%
Lifetime
20 years
CRF
$0.09
controls savings
10%
controls costs
0.22
1995 $/sf
Background Information Sheet: Interlab Study on U.S.
nergy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Commercial Sector
Lighting
Product/end-use description
Lighting involves the use of electricity to pass electrons through a filament to
produce light and heat (incandescent light) or to pass electrons through an inert gas
which then emits light. Significant savings are possible in commercial lighting
systems with the replacement of traditional incandescent lights. Additional savings
can be achieved in fluorescent lighting as well. About 70% of lighting energy in
commercial buildings is from fluorescent sources, 12% from HID sources, and
18% from incandescents.
Base Year Energy Use
Lighting accounts for an estimated 27% (4 quads) of commercial primary energy
consumption in 1997. (Source: US EIA. 1996)
End-use Lifetime
The end-use lifetime for lighting was estimated at 12 years. There are many
different lifetimes for lighting products, fluorescent fixtures and ballasts turn over
on average about once every 12 years.
Existing Average Energy Use Index
EUIs for existing buildings are about 17 kBtu/sf. EUIs are taken from US EIA
(EUI in kBtu/sf)
(1996).
1997 New Energy Use Index (EUI
New EUI is roughly the same as the existing UEC.
in kBtu/sf)
Maximum Cost-effective Efficiency
The maximum cost-effective efficiency potential was estimated as the savings
Potential
potential from 2010 assuming the implementation of technically cost effective
lighting measures, including widespread use of halogen IR and compact fluorescent
technologies. The efficiency measures are ranked based on cost of conserved energy
for different building types, each with its own usage. The savings costing less
than $0.08/kWh are 25% of the 1997 baseline, based on Vorsatz and Koomey
(1997).
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential - Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level over the
potential High Efficiency Case
analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The CCEs are directly calculated in Koomey et al. based on the incremental costs
of halogen IR, fluorescent, and compact fluorescent technologies. Prices were
adjusted to 1995 levels based on the personal consumption price index (US DOC,
1996).
Cost of Conserved Energy
The weighted average CCE for high efficiency lighting measures costing less than
$0.08/kWh is $-0.037/kWh (-$10.2/MMBtu). The CCE is a ratio of the
incremental capital expenditure (amortized over the lifetime of the appliance) to the
annual energy savings expected from the purchase of the unit. The negative CCE
is caused by the labor savings associated with switching to longer lived halogen
IR lamps and compact fluorescents.
References:
Vorsatz, Diana, and Jonathan G. Koomey. 1997. The Potential for Efficiency Improvements in the U.S. Commercial Lighting
Sector. Lawrence Berkeley Laboratory. DRAFT LBNL-38895. in process.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/EIA-0383(97). Department of Energy, Washington, DC.
B-3.20
Lighting
CCE
Energy
Measure
Enduse
(cents/k CCE
Saved
Lighting Efficiency (Measure Name)
Number
Code
Wh)
(cents/kWh)
(TWh)
kWh
1995e/kWh
Halogen IR 55W
1 INC_GRC
-17.21
-19.93
0.15
Halogen IR 55W
1 INC_HLT
-17.21
-19.93
0.49
Halogen IR 55W
1 INC_COL
-17.18
-19.90
039
Halogen IR 55W
1 INC_RET
-17.18
-19.90
2.73
Halogen IR 55W
1 INC_RST
-17.18
-19.90
0.57
Halogen IR 55W
1 INC_LDG
-17.18
-19.90
2.28
Halogen IR 55W
1 INC_LGO
-17.18
-19.90
1.28
Halogen IR 55W
1 INC_MSC
-17.12
-19.83
221
Halogen IR 55W
1 INC_SCH
-17.12
-19.83
0.6
Halogen IR 55W
1 INC_SMO
-17.12
-19.83
0.93
Halogen IR 55W
1 INC_WRH
-17.12
-19.83
0.64
60W HIR flood + occup. sensor
3 INCR_LDG
-3.85
-4.46
0
60W HIR flood + occup. sensor
3 INCR_GRC
-3.85
-4.46
o
20W separable; elec. ballast
2 INC_GRC
-1.96
-227
0.27
20W separable; elec. ballast
2 INC_HLT
-1.96
-2.27
0.86
20W screw-in CFL
2 INC_MSC
-1.88
-2.18
3.87
20W screw-in CFL
2 INC_SCH
-1.88
-2.18
1.05
20W screw-in CFL
2 INC_SMO
-1.88
-2.18
1.64
20W screw-in CFL
2 INC_WRH
-1.88
-218
1.12
20W separable; elec. ballast
2 INC_COL
-1.78
-2.06
0.69
20W separable: elec. ballast
2 DNC_RET
-1.78
-206
4.78
20W separable; elec. ballast
2 INC_RST
-1.78
-2.06
0.99
20W separable; elec. ballast
2 INC_LDG
-1.78
-206
4
20W separable: elec. ballast
2 INC_LGO
-1.78
-2.06
2.24
MH + time switch
1 MH_GRC
-1.17
-1.36
0.01
60W HIR flood + arg mgmt system
4 INCR_LDG
-1.03
-1.19
0.01
60W HIR flood + nrg mgmt system
4 DNCR_GRC
-1.03
-1.19
0.01
MH + time switch
1 MH_RET
-0.78
-0.90
0.07
MH + time switch
1 MH_RST
-0.78
-0.90
0
MH + time switch
1 MH_LGO
-0.78
-0.90
0.02
MH + time switch
1 MH_HLT
-0.78
-0.90
0.01
MH + time switch
1 MH_SCH
-0.52
-0.60
0.01
MH + time switch
1 MH_MSC
-0.52
-0.60
0.01
MH + time switch
1 MH_SMO
-0.52
-0.60
0.02
MH + time switch
1 MH_COL
-0.52
-0.60
0.01
MH + time switch
1 MH_LDG
-0.52
-0.60
0.01
MH + time switch
1 MH_WRH
-0.52
-0.60
0.05
60W HIR flood + occup. sensor
3 INCR_LGO
0.02
0.02
0.06
60W HIR flood + occup. sensor
3 INCR_RET
0.02
0.02
0.01
60W HIR flood + occup. sensor
3 INCR_RST
0.02
0.02
0
ELEC4/4F32T8/RS
1 EM4/4_HLT
0.52
0.60
0.82
ELEC4/4F32T8/RS
1 EM4/4_GRC
0.52
0.60
0.15
ELEC4/4F32T8/RS
1 EM4/4_RST
0.56
0.65
0.22
ELEC4/4F32T8/RS
1 EM4/4_LDG
0.56
0.65
0.59
ELEC4/4F32T8/RS
1 EM4/4_COL
0.58
0.67
0.36
ELEC4/4F32T8/RS
1 EM4/4_RET
0.58
0.67
1.89
ELEC4/4F32T8/RS
1 EM4/4_LGO
0.58
0.67
2.15
ELEC4/4F32T8/RS
1 EM4/4_SCH
0.66
0.76
0.59
ELEC4/4F32T8/RS
1 EM4/4_MSC
0.66
0.76
0.85
ELEC4/4F32T8/RS
1 EM4/4_SMC
0.66
0.76
1.41
ELEC4/4F32T8/RS
1 EM4/4_WRF
0.66
0.76
0.35
HPS
2 MH_GRC
0.86
1.00
0
ELEC4/3F32T8/IS/occupancy sensor
1 EL43_RST
0.94
1.09
0.01
ELEC4/3F3IT8/IS/oocupency sensor
1 EL4/3_LDG
0.94
1.09
0.02
HPS
2 MH_RET
0.98
1.14
0.01
HPS
2 MH_RST
0.98
1.14
0
HPS
2 MH_LGO
0.98
1.14
0
HPS
2 MH_HLT
0.98
1.14
0
ELEC4/4P32T8/RS/occupancy sensor
3 EM4/4_RST
1.05
1.22
0
ELEC4/4F3IT&/RS/occupancy sensor
3 EM4/4_LDG
1.05
1.22
0.01
HPS
2 MH_SCH
1.19
138
0
HPS
2 MH_MSC
1.19
138
0
HPS
2 MH_SMO
1.19
138
0
HPS
2 MH_COL
1.19
138
0
HPS
2 MH_LDG
1.19
1.38
0
HPS
2 MH_WRH
1.19
138
0.01
HPS. no delamping
1 MV_HLT
137
1.59
0
HPS, no delamping
1 MV_GRC
137
1.59
0.01
HPS, no delamping
1 MV_COL
1.46
1.69
0.06
HPS. no delamping
1 MV_LGO
1.46
1.69
0.06
HPS, no delamping
1 MV_RET
1.46
1.69
0.09
HPS, no delamping
1 MV_LDG
1.46
1.69
0.01
HPS, no detemping
1 MV_WRH
1.46
1.69
0.06
6/10/97
Lighting
MH. no delemping
2 MV_HLT
1.74
2.02
0.01
MH. no delamping
2 MV_GRC
1.74
2.02
0.04
HPS, no delamping
MV_SCH
1.76
2.04
0.03
HPS, no delamping
1 MV_MSC
1.76
2.04
0.06
HPS, BO delamping
1 MV_SMO
1.76
2.04
0.01
HPS, no delemping
1 MV_RST
1.76
2.04
0
MH. DO delemping
2 MV_COL
1.82
2.11
0.29
MH. BO delamping
2 MV_LGO
1.82
2.11
031
MH. DO delamping
2 MV_RET
1.82
2.11
0.45
MH. no delamping
2 MV_LDG
1.82
211
0.06
MH. no delemping
2 MV_WRH
1.82
2.11
0.29
ELECS/2P96T12/ES/occupancy sensor
3 EM8/2_GRC
1.93
2.24
0
ELECB/2P96T12/ES/occupancy sensor
3
EM8/2_HLT
1.93
2.14
0
MH. no delamping
2 MV_SCH
2.1
2.43
0.17
MH. no delamping
2 MV_MSC
2.1
2.43
0.29
MH, DO delamping
2 MV_SMO
2.1
2.43
0.03
MH. no delamping
2 MV_RST
21
2.43
0.01
ELBCS/2P96T12/ES/occupancy sensor
3
EM8/2_LDG
2.18
252
0
ELEC8/2P96T12/ES/occupancy sensor
3 EM8/2_RST
2.18
252
0
ELEC8/2P96T12/ES/occupancy sensor
3 EM8/2_LGO
2.18
252
0.08
ELEC8/2P96T12/ES/occupancy sensor
3 EM8/2_RET
2.18
252
0.03
ELECB/2P96T12/ES/occupancy sensor
3 EM8/2_COL
2.18
2.52
0.02
ELEC4/3F32T8/IS/occupency sensor
2
ELA/3_HLT
2.32
2.69
0.02
ELEC4/3F32T8/IS/ocupancy sensor
2 ELA/3_GRC
2.32
2.69
0
ELEC43F32T8/1S/org mgmt system
2 ELA/3_RST
236
2.73
0.02
ELEC4/3F32T8/1S/arg mgmt system
2 EL43_LDG
2.36
2.73
0.06
CCUT42F40T12/ES/RE
1 EM4/2_RST
2.43
2.81
0.14
OCUT42F40T12/ES/RE
1 EM4/2_LDG
2.43
2.81
0.79
ELEC4/3F3ZT &/IS/org mgmt system
3 EL43_HLT
2.49
2.88
0.02
ELEC4/3F3ZT8/1S/org mgmt system
3
EL4/3_GRC
2.49
2.88
0.09
CCUT4/2F40T12/ES/RE
1 EM4/2_COL
2.51
2.91
0.43
CCUT42F40T12/ES/RE
1
EM4/2_RET
251
2.91
0.96
CCUT42F40T12/ES/RE
I EM4/2_LGO
251
2.91
0.86
ELEC4/4F3ZT8/IS/org mgmt system
5 EM4/4_RST
2.54
2.94
0.01
ELEC4/4F32T8/1S/org mgmt system
5 EM4/4_LDG
2.54
2.94
0.02
60 W Halogen DR flood reflector
1 INCR_LDG
2.61
3.02
0.44
60 W Halogen IR flood reflector
1 INCR_GRC
2.61
3.02
0.11
60 W Halogen IR flood reflector
1 INCR_LGO
2.65
3.07
0.75
60 W Halogen IR flood reflector
1 INCR_RET
2.65
3.07
1.66
60 W Halogen IR flood reflector
1 INCR_RST
2.65
3.07
0.17
60 W Halogen IR flood reflector
1 INCR_SMO
2.69
3.12
0.49
60 W Halogen IR flood reflector
1 INCR_WRH
2.69
3.12
0.37
60 W Halogen IR flood reflector
1 INCR_HLT
2.69
3.12
0.18
CCUT42F40T12/ES/RE
1 EM4/2_SCH
2.74
3.17
0.68
CCUT42F40T12/ES/RE
1 EM4/2_MSC
2.74
3.17
0.58
CCUT42F40T12/ES/RE
1
EM4/2_SMC
2.74
3.17
0.46
CCUT42F40T12/ES/RE
1
EM4/2_WRI
2.74
3.17
0.15
60 W Halogen IR flood reflector
1 INCR_MSC
2.8
3.24
02
60 W Halogen IR flood reflector
1 INCR_SCH
2.8
3.24
0.1
60 W Halogen IR flood reflector
1 INCR_COL
2.8
3.24
0.07
OCUT42F40T12/ES/RE + occupancy sensor
2 EM4/2_RST
3.01
3.49
0
CCUT42F40T12/ES/RE + occupancy sensor
2 EM4/2_LDG
3.01
3.49
0.02
ELEC4/4F3TT8/RS/occupaDcy sensor
3 EM4/4_HLT
3.08
3.57
0.01
ELEC4/4P3IT8/RS/occupancy sensor
3 EM4/4_GRC
3.08
3.57
0
ELEC4/4F3IT8/RS/occupancy sensor
3 EM4/4_COL
3.44
3.98
0.08
ELEC4/4P32T8/RS/occupancy sensor
3
EM4/4_RET
3.44
3.98
0.03
ELEC4/4F32T8/RS/occupancy sensor
3
EM4/4_LGO
3.44
3.98
0.46
ELEC4/4P32T8/IS/org mgmt system
6 EM4/4_HLT
4.03
4.67
0.01
ELEC4/4P32T8/IS/arg mgmt system
6 EM4/4_GRC
4.03
4.67
0.02
ELEC8/2P96T12/ES/rg mgmt system
4 EM8/2_HLT
435
5.04
0
ELBCB/2P96T12/ES/nrg mgmt system
4 EM8/2_GRC
4.35
5.04
0.07
ELEC4/3F32T8/IS/occupancy sensor
2 ELA/3_COL
4.37
5.06
0.13
ELEC4/3P32T&/IS/occupancy sensor
2
ELA/3_RET
4.37
5.06
0.04
ELEC4/3P32T8/IS/oocupancy sensor
2 EL4/3_LGO
437
5.06
0.45
60W HIR flood + mg mgmt system
4 INCR_LGO
4.56
5.28
0.04
60W HIR flood + arg mgmt system
4 INCR_RET
4.56
5.28
0.12
60W HIR flood + mg mgmt system
4 INCR_RST
4.56
5.28
0
ELECB/2P96T12/ES/occupency sensor
3
EM8/2_SCH
4.6
533
0.02
ELBCS/2P96T12/ES/occupancy sensor
3
EM8/2_MSC
4.6
533
0.02
ELBCI/2P96T12/ES/occupancy sensor
3 EM8/2_SMC 4.6
5.33
0.07
ELEC8/2P96T12/ES/ocupancy sensor
3 EM8/2_WRI
4.6
5.33
0.12
60W HIR flood + occup. sensor
3
INCR_SMO
4.84
5.61
0.04
60W HIR flood + occup. sensor
3
INCR_WRH
4.84
5.61
0.03
60W HIR flood + occup. sensor
3 INCR_HLT
4.84
5.61
0
ELEC8/2P96T12/ES/nrg mgmt system
4
EM8/2_RST
4.98
5.77
0
FLEC8/2P96T12/ES/nrg mgmt system
4 EM8/2_LGO
4.98
5.77
0.06
ELEC8/2P96T12/ES/nrg mgm system
4
EM8/2_RET
4.98
5.77
0.44
Lighting
ELEC82P96T12/ESAurg mgmt system
4 EM8/2_LDG
4.98
5.77
0.01
ELBC8/2P96T12/ES/urg mgmt system
4 EM8/2_COL
4.98
5.77
0.01
60W HIR flood + time switch
2 INCR_LGO
5.22
6.05
0.01
60W HIR flood + time switch
2 INCR_RET
5.22
6.05
0.04
60W HIR flood + time switch
2 INCR_RST
5.22
6.05
0
ELBC4/4F32T8/SAtne switch
3 EM4/4_SCH
5.24
6.07
0.02
ELEC4/4F32T8/SAime switch
3 EM4/4_MSC
524
6.07
0.01
ELBC4/4P32T8/ISAtne switch
3 EM4/4_SMC
524
6.07
0.05
ELEC4/4P3IT8/SAtme switch
3 EM4/4_WRI
5.24
6.07
0.02
60W HIR flood + time swich
2 INCR_SMO
5.27
6.10
0.01
60W HIR flood + time switch
2
DNCR_WRH
5.27
6.10
0.01
60W HIR flood + time switch
2 INCR_HLT
527
6.10
0
ELBC8/2P96T12/ES/tine switch
2 EM8/2_SCH
535
6.20
0.01
switch
2
EM8/2_MSC
535
6.20
0
ELECB2P96T12/ES/tine switch
2 EM8/2_SMC
535
6.20
0.01
ELECB/2P96T12/ES/ttne switch
2 EM8/2_WRJ
5.35
6.20
0.03
ELEC4/4P3IT SVIS/Atme switch
4 EM4/4_COL
5.47
634
0.01
ELEC4/4P32T8/ISAtme switch
4
EM4/4_RET
5.47
634
0.11
switch
4 EM4/4_LGO
5.47
634
0.06
ELEC4/4F32T8/15/org mgmt system
6
EM4/4_COL
5.51
638
0.06
ELEC4/4P32T &/IS/org mgmt system
6
EM4/4_RET
551
638
035
ELEC4/4F32T MS/hrg mgmt system
6 EM4/4_LGO
5.51
638
033
ELECB/2P96T 12/ES
1 EM8/2_HLT
5.53
6.41
0.05
ELEC82P96T12/ES
1 EM8/2_GRC
5.53
6.41
0.2
ELEC4/4F32T8/LS/occupency sensor
4
EM4/4_SCH
558
6.46
0.07
ELEC4/4F3IT8/IS/occupency sensor
4
EM4/4_MSC
5.58
6.46
0.04
ELEC4/4F3IT8/IS/occupency sensor
4
EM4/4_SMC
558
6.46
0.25
ELEC4/4F3IT8/IS/occupancy sensor
4
EM4/4_WRJ
5.58
6.46
0.07
ELEC8/2P96T12/ES
1
EM8/2_LDG
5.96
6.90
0.08
ELEC8/2P96T12/ES
1 EM8/2_RST
5.96
6.90
0.05
ELEC8/2P96T12/ES
1 EM8/2_LGO
5.96
6.90
0.19
ELEC8/2P96T12/ES
1 EM8/2_COL
5.96
6.90
0.04
EC8/2P96T12/ES
1 EM8/2_RET
5.96
6.90
1.16
EC8/2P96T12/ES/ttme switch
2 EM8/2_RST
6.35
7.35
0
LEC8/2P96T12/ES/ie switch
2 EM8/2_LGO
6.35
7.35
0.01
ELEC8/2P96T12/ESAtme switch
2
EM8/2_RET
6.35
7.35
0.11
ELEC8/2P96T12/ESAtne switch
2
EM8/2_LDG
6.35
735
0
ELEC&/2P96T12/ES/Aime switch
2 EM8/2_COL
6.35
735
0
ELEC8/2P96T12/ES
1
EM8/2_SCH
6.52
755
0.09
ELEC8/2P96T12/ES
1
EM8/2_MSC
6.52
7.55
0.23
ELEC8/2P96T12/ES
1 EM8/2_SMC
6.52
7.55
0.19
ELEC8/2P96T12/ES
1
EM8/2_WRI
6.52
7.55
0.29
ELEC4/4F32T8/IS
2
EM4/4_SCH
6.74
7.81
0.15
ELEC4/4F32T8/IS
2
EM4/4_MSC
6.74
7.81
0.21
ELEC4/4F32T8/IS
2 EM4/4_SMC
6.74
7.81
0.35
ELEC4/4P32T8/IS
2
EM4/4_WRF
6.74
7.81
0.09
ELEC4/3P32T8/IStime switch
1 ELA/3_SCH
7.01
8.12
0.02
ELEC4/3F32T8/1SAtme switch
1 EL4/3_MSC
7.01
8.12
0
ELEC4/3F32T8/ISAime switch
1 ELA/3_SMO
7.01
8.12
0.04
ELEC4/3F32T8MISAime switch
1 EL4/3_WRH
7.01
8.12
0.03
ELEC4/4F32T8/IS
2 EM4/4_COL
7.02
8.13
0.08
ELEC4/4F32T815
2
EM4/4_RET
7.02
8.13
0.46
ELEC4/4F32T81S
2 EM4/4_LGO
7.02
8.13
0.45
ELEC8/2P96T12/ES/org mgmt system
4
EM8/2_SCH
7.1
8.22
0.02
ELEC8/2P96T12/ES/nrg mgmt system
4 EM8/2_MSC
7.1
8.22
0.02
ELEC8/2F96T12/ES/arg mgmt system
4 EM8/2_SMC
7.1
8.22
0.04
ELBC8/2P96T12/ES/nrg mgmt system
4
EM8/2_WRF
7.1
8.22
0.11
ELEC4/4F32T8/IS
2 EM4/4_RST
7.14
8.27
0.05
ELEC4/4F32T81S
2 EM4/4_LDG
7.14
8.27
0.14
ELBC4/4F32T8/IS/org mgmt system
5 EM4/4_SCH
7.17
8.30
0.07
ELEC4/4P32T8/S/arg memt system
5 EM4/4_MSC
7.17
8.30
0.03
ELEC4/4F32T1/S/brg mgmt system
5 EM4/4_SMC
7.17
8.30
0.22
ELEC4/4F32T8/IS/org memt system
5 EM4/4_WRJ
7.17
8.30
0.06
ELBC4/4P32T8/IS
2 EM4/4_HLT
731
8.47
0.2
ELBC4/4P32T8/IS
2 EM4/4_GRC
731
8.47
0.04
ELEC4/3P32T8/IS/occup. sensor
2 EL4/3_SCH
7.31
8.47
0.07
ELEC4/3F32T8/IS/occup. sensor
2 EL4/3_MSC
731
8.47
0.03
ELEC4/3F32T8/IS/occup. sensor
2 ELA/3_SMO
731
8.47
0.21
sensor
2 EL4/3_WRH
731
8.47
0.12
EC4/3P32T SVISttne switch
1 ELA/3_COL
735
851
0.02
switch
1 EL4/3_RET
7.35
8.51
0.19
ELEC4/3P32T8/ISAtme switch
1 EL43_LGO
735
851
0.07
ELEC4/3F32TMS/hrg mgmt system
3 EL4/3_COL
7.39
8.56
0.1
ELEC4/3F32TM/IS/org mgmt system
3 ELA/3_RET
7.39
8.56
0.57
mgmt system
3 EL4/3_LGO
7.39
8.56
035
CCUT42F40T12/ES/RE + occupancy sensor
3 EM4/2_COL
7.44
8.62
0.13
CCUT4/2F40T12/ES/RE + occupancy sensor
3 EM4/2_RET
7.44
8.62
0.02
Lighting
CCUT42F40T12/ES/RE + occupancy sensor
EM4/2_LGO
7.44
8.62
0.26
ELEC4/4F3IT8/S/occupancy sensor
5 EM4/4_COL
7.59
8.79
0.01
sensor
5 EM4/4_RET
7.59
8.79
0
ELEC4/4F3IT8/IS/occupancy sensor
5 EM4/4_LGO
7.59
8.79
0.05
ELEC4/4F32T8/IS/occupsncy sensor
5 EM4/4_HLT
7.64
8.85
0
ELEC4/4F32T8/IS/occupescy sensor
5 EM4/4_GRC
7.64
8.85
0
ELEC4/4F3IT8/IS/occupancy sensor
4
EM4/4_RST
7.85
9.09
0
ELBC4/4F32T8/IS/occupancy sensor
4
EM4/4_LDG
7.85
9.09
0
CCUT4/2F40T12/ES/RE + mg mgmt system
3
EM4/2_RST
8.6
9.96
0.01
CCUT4/2F40T12/ES/RE + mg mgm( system
3 EM4/2_LDG
$.6
9.96
0.05
ELEC4/3F32T8/IS/org memt system
ELA/3_SCH
952
11.03
0.07
ELBC4/3F32T8/IS/org mgmt system
3 ELA/3_MSC
9.52
11.03
0.03
ELEC4/3P32T8/IS/brg mgmt system
3 ELA/3_SMO
9.52
11.03
0.14
ELBC4/3F32T8/IS/org mgmt system
EL43_WRH
9.52
11.03
0.1
CCUT4/2F40T12/ES/RE + occupancy sensor
EM4/2_SCH 11.41
13.22
0.12
CCUT4/2F40T12/ES/RE + occupancy sensor
EM4/2_MSC 11.41
13.22
0.04
CCUT42F40T12/ES/RE + occupancy sensor
3 EM4/2_SMC 11.41
13.22
0.12
CCUT42F40T12/ES/RE + occupancy sensor
3 EM4/2_WRJ 11.41
13.22
0.04
60W HIR flood + arg mgmt system
4 INCR_SMO
11.84
13.71
0.02
60W HIR flood + mg mgmt system
4 INCR_WRH
11.84
13.71
0.03
60W HIR flood + are mgmt system
4
INCR_HLT
11.84
13.71
0
CCUT4/2F40T12/ES/RE + time switch
2 EM4/2_SCH
12.96
15.01
0.04
CCUT4/2F40T12/ES/RE + time switch
2 EM4/2_MSC 12.96
15.01
0.01
CCUT4/2F40T12/ES/RE + time switch
2 EM4/2_SMC 12.96
15.01
0.03
CCUT4/2F40T12/ES/RE + time switch
2 EM4/2_WRJ 12.96
15.01
0.01
60W HIR flood + occup. sensor
3 INCR_MSC
12.99
15.05
0
60W HIR flood + occup. sensor
3 INCR_SCH
12.99
15.05
0
60W HIR flood + occup. sensor
3 INCR_COL
12.99
15.05
0
CCUT42F40T12/ES/RE + mg mgmt system
EM4/2_COL
13.7
15.87
0.1
CCUT42F40T12/ES/RE + are mgmt system
4
EM4/2_RET
13.7
15.87
0.26
CCUT4/2F40T12/ES/RE + arg mgmt system
4
EM42_LGO
13.7
15.87
0.2
ELEC4/2FT32T8MS+nrg mgmt system
6
EM4/2_RST
13.77
15.95
0
ELEC4/2FT32T8/IS+nrg mgmt system
6 EM42_LDG 13.77
15.95
0.01
CCUT4/2F40T12/ES/RE + time switch
2
EM42_COL
14.3
16.56
0.02
CCUT42F40T12/ES/RE + time switch
2
EM4/2_RET
14.3
16.56
0.09
CCUT4/2F40T12/ES/RE + time switch
2 EM4/2_LGO
14.3
16.56
0.04
ELBC4/2FT32T8MS+me switch
6
EM4/2_COL
14.36
16.63
0.01
ELEC4/2FT32T8MS+lme switch
6 EM4/2_RET
14.36
16.63
0.02
ELEC4/2FT32T8/ISHine switch
6 EM4/2_LGO
14.36
16.63
0.01
ELEC4/2FT32T8MS+org mgmt system
I
EM4/2_COL
14.6
16.91
0.02
ELEC4/2FT32T8/S+nrg mgmt system
EM4/2_RET
14.6
16.91
0.05
ELEC4/2FT32T8/S+brg mgmt system
EM4/2_LGO
14.6
16.91
0.04
60W HIR flood + time switch
2
INCR_MSC
14.85
17.20
0
60W HIR flood + time switch
2
INCR_SCH
14.85
17.20
0
60W HIR flood + time switch
2
INCR_COL
14.85
17.20
0
60W HIR flood + nrg mgmt system
4
INCR_MSC
15.57
18.03
0
60W HIR flood + are mgmt system
4
INCR_SCH
15.57
18.03
0
60W HIR flood + nrg mgmt system
4
INCR_COL
15.57
18.03
0
CCUT4/2F40T12/ES/RE + occupancy sensor
3
EM4/2_HLT
16.27
18.84
0.01
CCUT4/2F40T12/ES/RE + occupancy sensor
3 EM4/2_GRC 16.27
18.84
0
CCUT4/2F40T12/ES/RE + mg mgmt system
4 EM4/2_SCH 16.31
18.89
0.12
CCUT4/2F40T12/ES/RE + mg mgmt system
4 EM4/2_MSC 16.31
18.89
0.03
CCUT4/2F40T12/ES/RE + arg mgmt system
4 EM4/2_SMC 16.31
18.89
0,08
CCUT4/2F40T12/ES/RE + are mgmt system
4 EM4/2_WRI 16.31
18.89
0.04
separable CFL + occupancy sensor
4 INC_COL
16.75
19.40
0.02
separable CFL + occupancy sensor
4 INC_RET
16.75
19.40
0.01
separable CFL + occupancy sensor
4 INC_RST
16.75
19.40
0
separable CFL + occupancy sensor
4 INC_LDG
16.75
19.40
0.01
separable CFL + occupancy sensor
4 INC_LGO
16.75
19.40
0.07
ELBC4/2FT32T8/IS+me switch
6 EM4/2_SCH 16.79
19.45
0.01
switch
6 EM4/2_MSC 16.79
19.45
0
ELEC4/2FT32T&/1S+ine switch
6 EM4/2_SMC 16.79
19.45
0.01
switch
6 EM4/2_WR} 16.79
19.45
0
separable CFL + occupancy sensor
4 INC_GRC
16.9
19.57
0
separable CFL + occupancy sensor
4 INC_HLT
16.9
19.57
0
ELEC4/2FT32T&/S+erg mgmt system
$ EM4/2_SCH 17.02
19.71
0.02
ELBC4/2FT32TMS+nrg mgmt system
$ EM4/2_MSC 17.02
19.71
0.01
ELBC4/2FT32TMS+arg mgmt system
8 EM4/2_SMC 17.02
19.71
0.02
ELBC4/2FT32T&/S+arg mgmt system
EM4/2_WRJ 17.02
19.71
0.01
CCUT42F40T12/ES/RE
1 EM4/2_HLT 17.62
20.41
0:63
CCUT4/2F40T12/ES/RE
1 EM4/2_GRC 17.62
20.41
0.11
ELBC4/2F32T8/IS
EMA/2_RST 22.81
26.42
0.04
ELBC4/2F32T8/IS
4 EM4/2_LDG 22.81
26.42
0.21
ELBC4/2F32T8/IS
5 EM4/2_COL 23.06
26.71
0.07
ELEC4/2F32T815
5 EM4/2_RET
23.06
26.71
0.18
ELECM2F3IT8/IS
5 EM4/2_LGO 23.06
26.71
0.15
ELBC4/2F32T8/IS
EM4/2_SCH 23.76
27.52
0.14
6/10/97
Lighting
ELBC4/2F32T8/15
5 EM4/2_MSC 23.76
27.52
0.15
ELEC42F32T815
5 EM4/2_SMC 23.76
27.52
0.09
ELBC4/2F32T8/IS
5 EM4/2_WRF 23.76
27.52
0.02
ELEC4/2FT32T8MS+occup. sensor
5 EM4/2_RST 24.97
28.92
0
ELEC4/2FT32TBMS+ocup. sensor
5 EM4/2_LDG 24.97
28.92
0
sensor
7 EM4/2_COL 24.98
28.93
0.01
ELEC4/2FT32T8/S+up. sensor
7 EM4/2_RET 24.98
28.93
0
sensor
7 EM4/2_LOO 24.98
28.93
0.02
separable CFL + mg mgmt system
5 INC_GRC
25.81
29.89
0.01
separable CPL + arg mgmt system
5 INC_HLT
25.81
29.89
0
ELEC42FT32T8MS+occup. sensor
7 EM4/2_SCH 26.29
30.45
0.01
ELBC4/2FT32T8MS+occup. sensor
7 EM4/2_MSC 26.29
30.45
0
sensor
7 EM4/2_SMC 26.29
30.45
0.01
ELEC42FT32TBMS+ocoxp. sensor
7
EM4/2_WRJ
26.29
30.45
0.01
CCUT42F40T12/ES/RE + arg mgmt system
4 EM4/2_HLT 26.8
31.04
0.01
CCUT4/2F40T12/ES/RE + mg mgmt system
4 EM4/2_GRC
26.8
31.04
0.03
separable CFL + mg mgmt system
5 INC_COL
28.65
33.18
0.02
separable CFL + mg mgmt system
5 INC_RET
28.65
33.18
0.13
separable CFL + mg mgmt system
5 INC_RST
28.65
33.18
0.01
separable CFL + mg mgmt system
5 INC_LDG
28.65
33.18
0.02
separable CFL + mg mgmt system
5 INC_LGO
28.65
33.18
0.05
20W screw-in CFL + time switch
3 INC_MSC
31.7
36.72
0
20W screw-in CFL + time switch
3 INC_SCH
31.7
36.72
0.01
20W screw-in CFL + time switch
3 INC_SMO
31.7
36.72
0.01
20W screw-in CFL + time switch
3 INC_WRH
31.7
36.72
0.01
20W screw-in CFL + occup sensor
4 INC_MSC
34.06
39.45
0.03
20W screw-in CFL + occup sensor
4 INC_SCH
34.06
39.45
0.02
20W screw-in CFL + occup sensor
4 INC_SMO
34.06
39.45
0.04
20W screw-in CFL + occup sensor
4 INC_WRH
34.06
39.45
0.03
20W screw-in CFL + arg mgmt system
5 INC_MSC
42.24
48.92
0.02
20W screw-in CFL + arg mgmt system
5 INC_SCH
42.24
48.92
0.02
20W screw-in CFL + arg mgmt system
5 INC_SMO
4224
48.92
0.03
20W screw-in CFL + mg mgmt system
5 INC_WRH
42.24
48.92
0.03
separable CFL + time switch
3 INC_COL
42.38
49.09
0
separable CFL + time switch
3 INC_RET
4238
49.09
0.03
separable CFL + time switch
3 INC_RST
42.38
49.09
0
separable CFL + time switch
3 INC_LDG
42.38
49.09
0.01
separable CFL + time switch
3 INC_LGO
42.38
49.09
0.01
ELEC8/2P96T12/ESAime switch
2 EM8/2_GRC 45.62
52.84
0
ELEC8/2P96T12/ESAime switch
2 EM8/2_HLT 45.62
52.84
0
ELECU4F3IT8/ISAtme switch
4
EM4/4_HLT
49.85
57.74
0
ELEC44F3IT8/IS/time switch
4 EM4/4_GRC 49.85
57.74
0
ELEC43F32T8/ISAime switch
1 EL4/3_HLT 64.41
74.60
0
ELEC43F32T8/IS/Mime switch
1 EL4/3_GRC 64.41
74.60
0
60W HIR flood + time switch
2 INCR_LDG 74.85
86.69
0
60W HIR flood + time switch
2 INCR_GRC 74.85
86.69
0
ELEC4/2F32T8/IS
2 EM4/2_HLT
84.1
97.41
0.18
ELEC4/2F32T8/IS
2 EM4/2_GRC 84.1
97.41
0.02
separable CFL + time switch
3 INC_GRC 228.06
264.15
0
separable CFL + time switch
3 INC_HLT
228.06
264.15
0
Savings costing less than 8 cents/kWh
-3.47
61.59
Business M usual electricity use
243.21
CCE S/MMBru
-10.16
% savings rel. to 1997
253%
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Commercial Sector
Refrigeration
Product/end-use description
Commercial refrigeration involves cooling large volumes to a variety of different
temperatures.
Base Year Energy Use
Refrigeration accounts for an estimated 3% (0.5quads) of commercial primary
energy consumption in 1997. (Source: US EIA, 1996)
End-use Lifetime
The end-use lifetime for refrigeration was estimated at 15 years.
Existing Average Energy Use Index
EUIs for existing buildings are 2.0 kBtu/sf. EUIs are taken from US ELA (1996).
(EUI in kBtu/sf)
1997 New Energy Use Index (EUI
EUIs for new buildings are 2.0 kBtu/sf. EUIs are taken from US ELA (1996).
in kBtu/sf)
Maximum Cost-effective Efficiency
The maximum cost-effective efficiency potential was estimated as the savings
Potential
potential from 2010 assuming the implementation of all measures with a simple
payback time of 5 years or less. The cost effective savings are 31% of the 1997
baseline. based on Westphalen et al. (1996).
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential - Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level over the
potential - High Efficiency Case
analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
The incremental costs for efficient refrigeration equipment vary widely. All were
taken from Westphalen et al. (1996). Prices were adjusted to 1995 levels based on
the personal consumption price index (US DOC, 1996).
Cost of Conserved Energy
The weighted average CCE for high efficiency lighting measures with less than a
five year payback is $0.016/kWh ($4.66/MMBtu). The CCE is a ratio of the
incremental capital expenditure (amortized over the lifetime of the appliance) to the
annual energy savings expected from the purchase of the unit.
References:
Sezgen, A. Osman. and Jonathan G. Koomey. 1995. Technology data characterizing refrigeration in commercial buildings:
Application to end-use forecasting with COMMEND 4.0. Lawrence Berkeley Laboratory. LBL-37397. December.
Westphalen, Detlef, Robert A. Zogg, Anthony F. Varone, and Matthew A. Foran. 1996. Energy Savings Potential for
Commercial Refrigeration Equipment. Prepared by Arthur D. Little, Inc. for the Building Equipment Division, Office of
Building Technologies, US Department of Energy. ADL Reference No. 46230. June.
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/EIA-0383(97). Department of Energy, Washington, DC.
B-3.21
Refrigeration
Commercial Refrigeration Efficiency Calculations
Westphalen, Detlef, Robert A. Zogs, Anthony F. Varone, and Matthew A. Foran. 1996. Energy Savings Potential for Commercial Refrigeration Equipment. Prepared by Arthur D. Little, Inc.
for the Building Equipment Division, Office of Building Technologies, US Department of Energy. ADL Reference No. 46230. June.
ASSUME 1995 $ (COULDNT FIND IT IN THE REPORT)
Equipment
Total 1996
Total 1996
Usage
% savings
cost
Savings 1996
Savings
CCE
CCE
CCE
inventory
Primary E
Electricity
per unit
<5 year SPT
premium
Electricity
per unit
1995$/kWh
1995$/kWh
S/MMBtu
(1000s)
TBtu
TWh
kWh/unit
per unit
TWh
site
Ice makers
1200
102
9.4
7822
18%
146
1.7
1408
0.010
0.010
2.87
Supermarkets
30
326
30.0
999969
20%
36650
6.1
201744
0.017
0.017
5.03
Centralized systems (exc. supermarkets): Walk-ins
880
180
16.6
18823
30%
1000
5.0
5647
0.017
0.017
4.90
Centralized systems (exc. supermarkets): Small grocery
20
26
2.4
119628
30%
1000
0.7
35888
0.003
0.003
0.77
Vending machines
4100
134
12.3
3008
42%
290
5.2
1263
0.022
0.022
6.35
Self contained: Reach-in refrigerators
1300
54
5.0
3822
45%
313
2.2
1720
0.017
0.017
5.03
Self contained: Reach-In freezers
800
65
6.0
7477
44%
382
2.6
3290
0.011
0.011
3.21
Self contained: Beverage merchandisers
800
52
4.8
5981
55%
376
2.6
3290
0.011
0.011
3.16
Self contained: Other
1150
54
5.0
4321
45%
313
2.2
1944
0.015
0.015
4.45
Total
993.0
91.4
31%
28.3
0.016
0.016
4.62
ADL primary E conversion factor
10,867 Btu/kWh
THIS CONVERSION FACTOR IS ONLY USED TO CONVERT ADL TBUS TO KWH.
3.185
Discount rate
7%
Lifetime
20.00 years
CRF
$0.09
(1) These systems consist of supermarket-style display cases with single remotely located condensing units (compressor configuration is not parallel as in supermarkets).
(2) Other consists of roll-ins, under-counter, over-counter, non-beverage merchandisers.
(3) % svgs and cost premium per unit for centralized systems taken from "combination of technologies" option
for walk in refrigerators and freezers (small grocery cent. system svgs and costs assumed to be the same as for Walk-ins)
Supermarkets
(4) Other savings and costs assumed to be the same as reach-in refrigerators.
% machine room E
5%
% display case E
95%
6/10/97, 11:07 AM
Background Information Sheet: Interlab Study on U.S.
Energy Efficiency and Greenhouse Gas Emissions
Assumptions for Energy Efficiency Calculations: Commercial Sector
Miscellaneous electricity, natural gas, and oil
Product/end-use description
Miscellaneous energy use in the commercial sector covers a wide variety of end-
uses including office equipment, telecommunications equipment, pumps, cooking,
and other uses (US EIA, 1996).
Base Year Energy Use
Miscellaneious energy accounts for an estimated 24% (3.5 quads) of commercial
primary energy consumption in 1997. (Source: US EIA, 1996)
End-use Lifetime
The end-use lifetime for miscellaneous varies depending on the particular end-use.
Existing Average Energy Use Index
EUIs for existing buildings are 10.5 kBtu/sf. EUIs are taken from US EIA (1996).
(EUI in kBtu/sf)
1997 New Energy Use Index (EUI
No EUI's for miscellaneous energy for new buildings are available.
in kBtu/sf)
Maximum Cost-effective Efficiency
Little information was available to construct a detailed cost-effective potential
Potential
analysis for this end-use. We therefore assumed that niscellaneous electricity,
natural gas, and oil end uses are assumed to have the same efficiency potentials and
costs as in the residential sector.
Achievable cost-effective efficiency
In our efficiency case, we assume that the achievable adoption level over the
potential - Efficiency Case
analysis period is 35% of maximum cost-effective potential levels.
Achievable cost-effective efficiency
In our high-efficiency case, we assume that the achievable adoption level over the
potential - High Efficiency Case
analysis period is 65% of maximum cost-effective potential levels.
Incremental Capital Cost
Inadequate information was available to construct incremental costs for efficiency
improvements in the commercial misc. energy.
Cost of Conserved Energy
We have estimated an average cost of conserved energy of $0.03/KWh ($1990) or
$0.035/KWh ($1995) for miscellaneous electricity, and $6.00/MMBtu ($1997) for
gas/oil measures. These are CCE values which are consistent with those derived
from the analysis of miscellaneous energy uses in the residential sector. The CCE
is a ratio of the incremental capital expenditure (amortized over the lifetime of the
appliance) to the annual energy savings expected from the purchase of the unit.
References:
U.S. Department of Commerce, 1996. Statistical Abstract of the US. Economics and Statistics Administration, Bureau of the
Census, Washington, DC.
U.S. Energy Information Administration, Office of Integrated Analysis and Forecasting, 1996. Annual Energy Outlook 1997.
Report Number DOE/E1A-0383(97). Department of Energy, Washington, DC.
B-3.22
Interlab Study on U.S.
Energy Efficiency and Greenhouse
Gas Emissions
Appendix C-4
Memoranda re:
Calculations for Energy Saving Potential for
Miscellaneous Energy Use,
Impact from Electricity to Gas Fuel
Switching, and Savings from High Albedo
Roofs
Residential and Commercial
Sectors
ENERGY ANALYSIS PROGRAM
ENVIRONMENTAL ENERGY TECHNOLOGIES DIVISION
LAWRENCE BERKELEY NATIONAL LABORATORY
BLDG: 90 ROOM 4000
MEMORANDUM
March 27, 1997
TO:
Mark Levine
FROM:
Jon Koomey and Nathan Martin
RE:
Energy Efficiency Savings Potential for Miscellaneous Energy Use in Buildings
This memo summarizes our calculations of the potential for energy savings for miscellaneous energy end-
use in buildings. (Miscellaneous end-uses include electricity required to operate electronics, motors in
pumps and ventilation systems, and gas or oil required for assorted miscellaneous heating end-uses.)
Based on our current calculations we have estimated that the maximum cost effective potential for
miscellaneous energy savings in both residential and commercial buildings in 2010 is 33% for
miscellaneous electricity and 10% for miscellaneous gas and oil end-uses. For our scenario calculations
we used an average cost of conserved energy of $3/MMBtu for miscellaneous energy.
Description of calculation
We first developed an estimate of miscellaneous energy savings in the residential sector and then
applied similar savings estimates to miscellaneous energy savings potential in the commercial sector.
Our savings calculations for the residential sector involved 1) characterizing residential energy use, 2)
collecting and analyzing existing literature on energy savings in specific miscellaneous energy end-uses,
and 3) extrapolating these potentials to all end-uses based on best judgment.
The characterization of miscellaneous energy use in the residential sector was based on Sanchez (1997)
where we estimated 1997 miscellaneous electricity use by main category (electronics, motors, heating)
and applied these shares to 1997 energy use given in (US DOE, 1996). We then determined energy
savings for the main miscellaneous electricity end-uses based on judgment and existing literature as
shown in the detailed spreadsheet accompanying this memo. (Documented information on potential
energy savings was available for televisions, video cassette recorders, and waterbed heaters, where we
found all three of the CCEs in these cases to be below $0.03/KWh ($1995)). Savings estimates for non-
electricity miscellaneous end-uses were based on judgment. Table 1 below shows the summary results of
our calculations.
Table 1: 1997 Miscellaneous Energy Use and Estimated Energy Efficiency Potentials
End-use Category
Primary
Share of Primary
Estimated
Energy Use
Energy Use
Energy
(Quads)
(Percent)
Efficiency
Potential
(Percent)
electronics
1.6
29%
25%
motors
1.6
29%
53%
heating
1.2
22%
33%
Total electricity
4.4
80%
33%
natural gas
0.9
17%
10%
oil & other petroleum products
0.1
2%
10%
Total Miscellaneous
5.4
100%
29%
While we feel that these estimates are both credible and conservative, the paucity of existing research
literature on miscellaneous energy savings suggests that significantly more effort would be required to
develop more detailed and robust estimates of energy savings for specific end uses, and that this is a
subject clearly worthy of continued investigation.
ENERGY ANALYSIS PROGRAM
ENVIRONMENTAL ENERGY TECHNOLOGIES DIVISION
LAWRENCE BERKELEY NATIONAL LABORATORY
BLDG: 90 ROOM 4000
MEMORANDUM
March 27, 1997
TO:
Mark Levine
FROM:
Jon Koomey
RE:
Calculation of Impact from Electricity to Gas Fuel Switching in Residential Buildings
I am writing this memo to report to you our findings concerning our calculations of impact from switching
from electricity-based to gas-based water heating, cooking, and drying in residential homes that
currently have gas space conditioning and electric appliances for these end-uses. Based on our current
calculations we have estimated that in the business as usual scenario fuel switching energy savings is
0.11 quads. The additional capital cost for these measures was estimated to be $27 billion in 2010 or $2.7
billion on an annualized basis.
Description of calculation
The calculation of energy savings and cost potential involved several steps: 1) characterization of the
U.S. residential building stock to estimate what percentage of homes that currently have gas space
conditioning would replace their electric water-heating, cooking, and drying appliances within on or
before 2010, 2) estimation of the unit incremental cost and energy savings for switching from electric
water heating, cooking, and drying to gas systems for these end-uses, 3) calculation of the electricity
savings, increased gas use, and increased cost to the appropriate segments of the residential building
stock in our spreadsheet calculation model, 4) calculation of total increase in capital expenditures
nationally for undertaking this fuel switching measure.
Background analysis undertaken for estimated that by 2010 between 5 and 36% of residential buildings
would be candidates for replacing their electric water heating, cooking, and drying appliances with gas
appliances in 2010. These percentages reflect those buildings that have gas space-conditioning systems
and are expected to need to purchase a replacement appliance during the forecast period and were
derived from background analysis for (Koomey et al, 1997) combined with end-use stock accounting
calculations undertaken for this study. For each end-use, the displacement of electricity by the gas end-
use results in unit energy savings between 29% and 59% (table 1). The incremental costs for the fuel
switching includes any increase in the cost of the gas appliance in addition to the additional labor and
materials charges for installing the gas system and are further detailed in the attached spreadsheet.
To estimate the electricity savings we calculated the business as usual electricity demand for electric
water-heating, cooking, and drying appliances but excluded the fraction of housing stock that would be
switching to gas appliances. After accounting for the increase in gas we were then able to calculate the
net energy savings from this option for each end use (table 1). The additional national cost for the fuel
switching was the product of the incremental capital cost per unit of electricity savings for each end use
and the total electricity savings. Similar calculations of energy savings and cost were undertaken for
the 100% implementation of maximum cost-effective efficiency technology scenario, thereby enabling
the use of a business as usual and efficiency scenario that includes fuel switching.
Table 1: Summary of Fuel Switching Calculations
End-use
Fraction of
Unit energy
Unit Energy
Incremental
U.S. Energy
U.S. incremental
Category
2010 housing
savings from
Savings from
unit cost
Savings in 2010
cost BAU Case
stock
Fuel Switch
Fuel Switch
($1995)
BAU Case
($Billion 1995)
(Percent)
(MMBtu)
(Percent)
(Quads)
Water heating
5%
12.4
29%
$1,266
0.02
$1.7
Cooking
22%
1.9
33%
$1,391
0.01
$13.0
Clothes Drying
36%
4.7
59%
$690
0.08
$12.3
ENERGY ANALYSIS PROGRAM
ENVIRONMENTAL ENERGY TECHNOLOGIES DIVISION
LAWRENCE BERKELEY NATIONAL LABORATORY
BLDG: 90 ROOM 4000
MEMORANDUM
April 1, 1997
TO:
Mark Levine
FROM:
Jon Koomey and Sarah Bretz
RE:
Calculation of Savings from high albedo roofs in buildings
This memo summarizes our calculations of impacts from high albedo roofs.
Description of calculation
We relied on calculations conducted by Steve Konopacki and conversations that Sarah Bretz had with
Hashem Akbari and Konopacki (Bretz 1997). We summarized the Heat Island Group's latest DOE-2
analyses and boiled them down to two parameters in residential and commercial buildings: 1) the
percentage change in total electrical cooling use associated with high albedo roofing, averaged across
northern and southern regions, and 2) the number of kBtu that gas heating use goes up per kBtu of site
electricity saved in cooling. We initially calculated the percentage savings figures separately for
north and south regions, but we found that the percentage savings were not very different across the
regions. Therefore, we chose the round numbers of 7% savings for residential, and 5% savings for
commercial, which were close to the results for both regions. We did calculate a weighted average for
the increase in gas use per kBtu of savings across the regions, using the distribution of cooling energy use
from Koomey et al (1997) for residential and from US DOE (1994) for commercial.
To estimate the electricity savings from high albedo roofs in 2010, we calculated the business-as-usual
electricity demand associated with cooling appliances that are expected to be replaced during the
analysis period, and applied the percentages shown in Table 1 to that demand. For simplicity, we
assumed that roofs are replaced at the same rate as cooling equipment in each sector (this assumption
implies average roof lifetimes of 13 years for residential and 18 years for commercial). The electricity
savings were then multiplied by the kBtu of gas demand increase associated with each kBtu of
electricity demand reduced, and this gas use was then added to the gas heating category. The capital
cost is assumed to be zero, because the incremental costs for these materials is negligible.
Table 1: Summary of high albedo roofing calculations
End-use
Cooling
kBtu gas use
Incremental
Category
energy use
increase per kBtu
unit costs
savings
cooling elect.
($1995)
(Percent)
saved (site)
Residential
7%
1.1
$0
North
7%
3.7
$0
South
7%
0.5
$0
Commercial
5%
0.8
$0
North
5%
1.5
$0
South
5%
0.3
$0
References
Koomey, Jonathan G., Diana Vorsatz, Richard E. Brown, Celina S. Atkinson, and Marla C. Sanchez.
1997. Updated Potential for Electricity Efficiency Improvements in the U.S. Residential Sector.
Lawrence Berkeley Laboratory. DRAFT LBNL-38894. in process.
US DOE, U.S. Department of Energy. 1994. Energy End-Use Intensities in Commercial Buildings. Energy
Information Administration. DOE/EIA-0555(94)/2. September.
DRAFT
6/10/97
APPENDIX D
DRAFT
6/10/97
APPENDIX D-1: Details of the NEMS and LIEF Models
This appendix describes the procedure used to create the LIEF and NEMS model scenarios
presented in the industrial chapter. The LIEF model runs on a PC platform and is available,
with the input files for each scenario, upon request. The NEMS industrial model run use a
standalone version of the workstation model used by EIA. The version used for this study is
the same as that used for the AEO97, compiled for a SUN workstation instead of a IBM RISC
workstation. The full output (and input) files from the NEMS runs are also available on
request.
Three basic steps were used to perform the scenario analysis with LIEF; calibration to AEO and
modification of the input files to represent the efficiency and high efficiency/low carbon case.
In addition the NEMS industrial model was run in a standalone mode and compared to the
LIEF model scenarios.
Calibration of the LIEF model to the AEO97 industrial forecast.
The LIEF model was run using all of the macroeconomic growth rates and energy prices from the
1997 AEO. Growth rates for the value of shipments were taken from supplemental Table 23.
Industrial Sector Macroeconomic Indicators. Industrial delivered energy prices were taken from
table A3. Since LIEF requires an aggregate weighted fossil fuel price, the AEO fuel
consumption in Industry (Table A2) for each fossil fuel was use to construct the weighted
average fossil fuel price. Based on these inputs the LIEF model was run. A technology
penetration rate of 3% was found to provide the same overall decline in energy intensity in LIEF
as for the AEO forecast.
Efficiency case
In the efficiency case the capital recovery rate in the LIEF model, which is set at a default of
33%, was changed to 15% for each industry sector. Since the LIEF model runs in five year time
steps the change was made effective in the time step 2000-2005. The growth rates of energy
intensity between this run and the calibrated LIEF BAU were calculated for the period 1995-
2010 for each industry and for each energy type, fossil and electric.
High Efficiency / Low Carbon case
In the High Efficiency / Low Carbon case the penetration rate in the LIEF model, which was set
at 3% for purposes of calibration to AEO was changed to 6% for each industry sector. Since
the LIEF model runs in five year time steps the change was made effective in the time step 1995-
2000. This timing differs slightly from the efficiency case. Since the falling prices imply that the
idealized energy intensity does not differ greatly from the average energy intensity, increasing
penetration rates in the earlier time step has very little effect. Most of the effect comes in the
period 2000-2005, when the CRF is lower. The growth rates of energy intensity between this run
and the calibrated LIEF BAU were calculated for the period 1995-2010 for each industry and
for each energy type, fossil and electric.
Presentation of results
The average annual growth rates based on the three 5-year time steps, 1995-2010, were
assumed to apply for the 13-year period 1998-2010. The cumulative effect of the lower energy
intensity, for each industry and energy form, was computed by compounding the computed
D-1.1
DRAFT
6/10/97
annual growth rates. The cumulative energy savings in 2010, in percentage terms, was used to
calculate energy and carbon savings from the AEO industrial baseline energy consumption
(table A6) and carbon emissions (table A19).
NEMS model runs
Several standalone NEMS industrial model were performed to compare to the LIEF model
scenarios. The two that were presented reflect a doubling of the NEMS industrial model
retirement rate and a doubling of the slope of the TPC, representing an acceleration of the
technology improvement in the process industries. Both of these changes were achieved by
means of the NEMS model input file (available on request). Since these runs only effect the
NEMS process industry sectors it was necessary to compare those sector specific results to the
corresponding LIEF sectors. The reduction in total energy use in the sectors for which both
models had similar levels of (dis)aggregation was computed and compared on a percentage
basis.
D-1.2
DRAFT
6/10/97
APPENDIX D-2
EXAMPLES OF ENERGY SAVING TECHNOLOGIES FOR THE FUTURE
D-2.1 TECHNOLOGY EXAMPLES FOR PULP AND PAPER
The Forest Products Industry, as the association is now known, consists of wood products
manufacturing and paper manufacturing, and in 1994 consumed more than 3 Quads of energy
(14.6% of all manufacturing energy consumption). Paper manufacturing was also one of the
most energy intensive industries in the United States in 1994, using more than 18,500 Btu per
dollar value of shipments. The manufacturing of paper requires that a fiber source, normally
wood, be chipped, digested, bleached, and then formed as a slurry to make paper or board.
Once formed as paper, the product must be dried. Large amounts of steam and power are used
to debark and chip the wood, digest the wood, bleach the pulp and dry the paper products.
Much of this energy source (over 51%) comes from the reprocessing of lignins from the wood,
bark and unusable portions of the tree. In lumber and wood products, the fraction of biomass
energy sources is even higher - nearly 70%.
D-2.1.1 Technology Examples Available before 2010
In paper manufacturing especially, any technology that will economize on the use of steam,
reduce the need for heat, better utilize the biomass fuel sources available, or help to balance
both steam and power needs will improve the performance of the industry. The technologies
that hold promise to reduce energy and carbon emissions in the near term continue to economize
on the use of heat. Longer term options alter the balance between steam and power. The most
promising near term options are:
Impulse Drying
In the papermaking process, a dilute slurry of <1% pulp fibers and 99% water are laid down on
a moving wire. Removing the 99% water is a very energy intensive process which includes
draining, pressing, and finally evaporative drying. Impulse drying reduces the huge energy
requirements of evaporative drying by removing more water in the pressing section and reducing
the amount of water which must be evaporated from about 1.5 lb. per lb. of paper to about b lb.
per lb. of paper.
The technology uses pressure and heat to superheat water in the sheet and increase the normal
hydraulic forces for expelling water from the sheet. The energy saved in the evaporating section
more than offsets the extra heat required to superheat the sheet. The total energy savings for
full implementation of this technology could be approx. 0.25 quad/yr. The net energy savings
have been estimated to be about 12 trillion Btu annually from a market penetration of only 60
drying units by 2020.
Multiport Cylinder Drying
The evaporative drying in a paper mill is accomplished by winding the continuous sheet of
paper serpentine over a series of rollers. The rollers are pressurized with steam inside which
condenses on the inside of the roller. The accumulating condensate must then be removed from
the drum or it builds up and interferes with the heat transfer from the steam to the roller to the
paper. Current technology implements a "shoe" in the bottom of the hollow roller to pick up
the condensate from the roller and convey it out of the drum. As the shoes wear they become
D-2.1
DRAFT
6/10/97
less effective at removing condensate and a thicker film of condensate is left in the drum. The
multiport cylinder drying concept utilizes a different method to remove the condensate from the
drien. This has been shown to reduce the condensate film thickness inside the drier to 25-30%
of conventional technology which improves heat transfer and increases drying.
On-Machine Sensors for Paper Properties
While many people think of paper in terms of three grades, brown, white, and tissue,
papermaking involves literally hundreds of grades. Each grade is designed and manufactured
to optimize its performance in the customers application. To achieve its various performance
characteristics the paper grades differ in thickness, strength, moisture content, stiffness,
porosity, smoothness, and many other parameters. The individual parameter are controlled
through multiple process controls which are intended to be constant but, in fact, are not.
Current technology for some properties relies on spot samples individually tested in a paper
testing laboratory to determine whether the operation was on grade at the time the sample was
tested. Significant off-grade material can be produced between samples.
The development of new sensors to provide real-time feedback on whether the process and
product are within specification can save the energy of reprocessing off-grade material and
allow the use of greater amounts of recycled fiber. Recycled fiber is weaker than virgin fiber. In
paper grades where strength is important the amount of recycled fiber which can be used is
limited by the need to keep a safety margin between the process target and customer
specifications. The safety margin allows for normal process variability while producing an
acceptable product. With an on-line sensor for strength properties the process variability can
be reduced and greater proportions of recycled fiber utilized. In particular, the stiffness
properties of the paper sheet can be measured using an ultrasonic sensor in real time this
information can be used to reduce refiner energy in the process. A 10% reduction in refiner
energy at a single mill saves 70+ billion Btu/yr. Reducing the normal off-grade production rate
by 50% (from a typical 5% to 2.5%) can save an additional 118 billion Btu/yr.
D-2.1.2 Technology Examples beyond 2010 Requiring Further R&D
The Vision process for the Forest Products Industry of the Future was developed by the
industry in collaboration with the Department of Energy's Office of Industrial Technologies, and
is called "Agenda 2020 -- A Technology Vision and Research Agenda for America's Forest,
Wood, and Paper Industry". Two of the major concerns of this document are Environmental
Performance and Energy Performance. Some of the ways these objectives might be met are with
the following technologies.
Black Liquor Gasification
The pulp and paper industry is a highly energy intensive industry but also one which generates
a high fraction of its own energy. Traditionally, about 40% of the energy used in a mill is
generated from burning the lignin solids. Lignin is that portion of the wood which holds the
fibers together and makes them stiff. The pulping process separates the lignin from the pulp
fiber. The lignin is a dilute solution which is evaporated and burned in a boiler designed to
recover the pulping chemicals and heat from the combustion to make steam. The steam is used
to supply the mill's needs plus some is used to generate electricity for the mill. The energy
efficiency of the electricity generation is about 25%.
D-2.2
DRAFT
6/10/97
In the black liquor gasification combined cycle (BLGCC) process a little less steam is generated
to supply the mill but significantly more electricity is produced, 2-3 times more. Trends in
process changes to make mills more environmentally friendly change the balance of energy forms
that a mill uses. Mills are using less steam energy and more electrical energy; the BLGCC
process fits right into the future process needs.
The technology is coming on the scene at an opportune time because most of the existing
recovery boilers in the industry are reaching the end of their useful safe operating life. If the new
technology is implemented as these old boilers are retired, between approx. 2005 and 2020, it
would represent approximately 8 gigawatts of installed power generation.
Biomass Gasification
The pulp and paper industry is already utilizing nearly all of the available wood residues. The
residues from lumber manufacture and residues from pulping (e.g., bark, shives, etc.) are used in
hog-fuel boilers to generate extra stream and electricity for the mill. This offsets fuel fired (e.g.,
natural gas or oil) boilers and purchased electricity. If these boilers were also converted to
gasification type technology, biomass gasification combined cycle (BGCC), then they would
complete the industry steam needs and generate an extra 2 gigawatts of electricity.
A larger impact from this technology may be realized if additional forest residues which are not
now utilized were brought to a BGCC facility; then as much as 30 gigawatts of electricity could
be generated. A life cycle value of this would have to include significant transportation costs
to collect these residues; this is not yet established.
Polyoxometalate Bleaching
Traditionally, the last remnants of lignin from the pulp have been removed with a chlorine
bleaching process. However, the environmental impacts of chlorine has led to significant effort
to find alternative methods to produce a desirable soft white fiber. Among these have been
ozone bleaching and peroxide bleaching. Unfortunately, nothing has come to market which is as
effective and selective as chlorine or chlorine dioxide. Polyoxometalates may be just such a new
process. They are highly selective and can be regenerated within the process. In addition to
desirable performance characteristics, the polyoxometalate system is consistent with the goals
of increasing recycling of process water and reducing the effluent load from pulp mills.
Compared to chlorine based systems the new process promises to reduce electrical energy
consumption of pulp bleaching by 50%.
Sulfur-Free Pulping
The general public perception of the pulp and paper industry derives from the "rotten egg" or
"stinky cabbage" odors which come from sulfur by-products formed during pulping. The actual
emissions of these sulfur containing compounds may be quite small and environmentally benign.
Nevertheless, these odors are unpleasant and bothersome to a mill's neighbors. Although
tremendous strides have been made to reduce these emissions, the particular compounds are so
odiferous that alternatives are being sought which can achieve the same performance.
Anthraquinone is one compound known to produce a high quality pulp and improve the yield
of pulp from wood, thus conserving the use of wood. However, anthraquinone is currently too
expensive to be used to replace sulfur. The basic building blocks of anthraquinone are within
the wood itself. If a suitable manufacturing process can be developed, anthraquinone can be
D-2.3
DRAFT
6/10/97
manufactured reasonably and in sufficient supply to impact the entire industry. Alternative
sulfur substitutes are also being sought.
D-2.2 TECHNOLOGY EXAMPLES FOR CHEMICALS
The chemical industry is almost too complex to characterize as a single industry. Some
products - chlorine and other industrial gases - are made electrolytically or using electricity to
compress and liquify gases. Other processes, such as petrochemical processing, require high
temperatures and pressures to effect the chemical combination or separation that is required.
Within chemical manufacturing there are over 30 industries and more than 10,000 products.
Reaction and separation are at the heart of most chemical engineering processes, and they
typically require heat, high pressure, or both. Because of these requirements, the industry in
1994 used 5.3 Quads of energy (second only to Petroleum Refining) and required nearly 16,000
Btu per dollar of product shipped.
D-2.2.1 Technology Examples Available before 2010
As with paper, the most promising technologies for the near term are those that economize on
the use of heat or cooling or bring the two in better balance. Examples are:
Pinch Analytical Techniques
The "pinch" technique was originally a method for optimizing heat recovery in thermal
processes and was first applied in the 1970s. It has more recently been applied as a general
optimization tool.
Energy savings occur because of the heat recovery process (waste heat from one process is used
to provide needed heat to another). In the classic case of heat exchanger networks, the pinch
point helps to define the best match between available and needed heat, allowing the heat
exchange system to be optimally sized for greatest cost effectiveness. A larger system would
save more energy but would have an excessively long payback period; a smaller system might
pay back sooner but would save less than the optimal amount of energy.
Pinch optimization was originally applied to any new or existing system where there was
available waste heat at a higher temperature than required. Today's applications are much
broader, extending to water, emissions, and site integration, with benefits including capital and
energy cost reductions, emissions reduction and improvements in yield and operability. A slight
drawback to broad application of this analytical method is its complexity for use by energy
managers who prefer to use "rules of thumb"; however, the energy savings sometimes prove a
stronger motivation.
In early applications, energy savings averaging 30%, with capital cost savings in new plant
designs and one year paybacks in retrofits are common. Refinements to the technique have
resulted in typical savings of 50% in new plants and retrofit paybacks of six months. By the
mid-1980s the use of pinch analysis was widespread in the chemical industry, and its use has
broadened further since then. (WEC, 1995)
Advanced Distillation Control Techniques
Distillation in refining and chemical industries consumes 3% of total U.S. energy use, which
amounts to approximately 2.4 Quads of energy annually. In addition, distillation columns
D-2.4
DRAFT
6/10/97
usually determine the quality of final products and many times determine the maximum
production rates.
Distillation columns are often over-refluxed to ensure that the product purity specifications are
met. That is, more energy than necessary is used to meet the product specifications. As a
result, industry commonly uses 30% to 50% more energy than is necessary to produce its
products. It has been estimated that an overall average 15% reduction of distillation energy
consumption can be attained if better column controls are applied.
Industry does not have a consistent basis on which to compare the various options for
distillation control. Since distillation controls are not fully understood, they may be applied
where not needed or not applied where needed. Current research is involved in performing
detailed simulations of a range of distillation columns with varying degrees of control difficulty
to assess the control performance of various control options. It is expected that the refinement
of distillation control techniques resulting from this research will yield energy savings of 288
trillion Btu by the year 2010. (DOE, 1997)
D-2.2.2 Technology Examples beyond 2010 Requiring Further R&D
Biological/Chemical Caprolactam Process
Nylon-6 is currently produced from caprolactam. The chemical synthesis of caprolactam from
cumene is a complex, multi-step process that is energy intensive and generates considerable
waste. Nylon-6 could also be produced from caprolactone. However, the current market price
for caprolactone makes this route uneconomical.
A laboratory-demonstrated biological process has been developed that would provide a one-
step, cost-effective production process for caprolactam manufacture that requires 50% less
energy than the current process, costs half as much (considering both capital and energy costs),
and produces almost no waste byproducts. Research on this process has established the
technical feasibility of the biomanufacturing process for converting inexpensive cyclohexane into
caprolactone. Under this project, the feasibility of the laboratory-demonstrated
biomanufacturing process was established, and the process is now available to be optimized for
possible scale-up to pilot plant scale. It is estimated that by the year 202, this technology can
provide annual energy savings of 12 trillion Btu. (DOE, 1997)
Flexible Chemical Processing of Polymeric Materials
Waste textiles and recycled waste materials from automobiles, appliances, and furniture
contain polymers (such as nylon-6, nylon-66, PET, and polyurethanes) that can be converted
into valuable chemical feedstocks. However, processes that can only convert a single type of
recycled material can face high costs for material collection and for transportation of the
resulting feedstocks. Becuase these costs are the major contributors to process costs, processes
are needed that can convert a variety of recycled materials.
Research in this area is working toward developing a thermochemical process that can convert a
wide variety of recycled materials into valuable chemicals. A two-stage process is envisioned:
the first will use selective catalytic pyrolysis to recover chemicals such as caprolactam,
hexamethylendiamine, and dimethyl-terephathalate; the second will convert the unreacted
organic material into sythesis gas, which can be converted to a variety of chemicals of use to the
chemical industry.
D-2.5
DRAFT
6/10/97
Because the process can address a wide variety of recycled materials, large regional recycling
plants can be developed, lowering material collection and transportation costs and thereby
increasing the viability of recycling many materials. It is estimated that by the year 2020, the
use of this technology will save 265 trillion Btu annually. (DOE, 1997)
D-2.3 TECHNOLOGY EXAMPLES FOR PETROLEUM REFINING
[Prepared by M. Petrick, Argonne National Laboratory]
The amount of process energy used in refining petroleum crude oil to supply the US marketplace
depends upon many factors and not surprisingly therefore has varied over time. Key factors
impacting energy use and its utilization efficiency are (1) the quality of crude slate processed;
(2) the cost and availability of fuel and energy; (3) product slate produced to meet market
demand; (4) refinery configuration (complexity and size); (5) capital availability; and (6)
environmental dictates (product specifications). Over the past three decades these factors have
forced the refining industry to change dramatically; these changes in turn have impacted energy
utilization. Over the time period of 1969 to 1974 energy used/bbl processed declined at a rate
of 0.8%/yr (Haynes, 1976). In 1975, energy use was about 3.2 Quads. The oil supply
disruptions and high price of oil in the 70s motivated the industry to continue efforts to
minimize energy usage. By 1983, energy utilization had dropped to 2.6 Quads (DOE, 1990).
Since 1985 the refineries have become more complex and plant size has increased. Gasoline is
tending to become a commodity whose specifications are being set by environmental regulations.
The quality of the crude slate processed has declined. The deteriorating crude quality and the
market pressures to produce more "white products" per barrel processed motivated refiners to
add more advanced processing capability, thus increasing refining complexity and energy
utilization per unit of output. By 1990 energy usage had again risen to a level of about 3.0
Quads. Since 1990, energy usage has remained relatively constant; projected 1997 utilization is
2.941 Quads (EIA, 1996)
Potential For Future Reductions In Energy Utilization
The potential for reducing energy utilization in the future will continue to be impacted in large
measure by the various factors cited above. The 1997 ELA outlook, taking into account market
and crude supply factors, projects that the energy usage in the industry can be expected to
increase by 0.3%/yr. To reverse this trend (and thus to achieve reductions in the critical
greenhouse gas, CO₂), the energy efficiency of key (highest energy consuming) refining processes
and energy supply systems must be improved. Such efficiency improvements can be achieved
via various steps, e.g.s., (1) introduction of more efficient equipment; (2) reducing process
activation energies (through improved catalysts); (3) improving equipment integration to recover
more heat; (4) adopting improved process control, etc. Before such steps are taken, however,
they must be shown to be economically viable and be demonstrated to have acceptable risk (in
accordance with the industry's standards). A number of studies have identified the key
processes that must be addressed and processes and technology innovations/modifications
that have the potential to substantially reduce energy consumption (Haynes, 1976; DOE, 1990)
The most energy intensive processes in a refinery considering both specific energy use for the
process stream and percentage of total energy use in the refining process were identified as;
distillation; catalytic hydrocracking, reforming and hydrotreating; alkylation; and hydrogen
production. While the aforementioned studies cite numerous technology options that could
D-2.6
DRAFT
6/10/97
improve the processes energy efficiency utilization, the issues of the economic viability and risk
involved in retrofitting these modifications/components into the spectrum of plant
configurations that exist in the industry today were not addressed. It is clear that the
cost/benefit ratios for incorporating the candidate technologies/processes are highly site
specific and are very sensitive to future market and governmental dictates.
An important parallel issue is that while refiners can make improvements/modifications to
improve energy utilization, they may also be forced to modify refinery processes/configurations
to be able to refine crudes of lower quality and comply with environmental dictates. While such
changes may not be driven by energy issues, they will very likely impact energy usage as well as
emissions. They could result in a decrease in energy efficiency or an increase in CO2 emissions, a
major greenhouse gas. A clear example of this is given by Ladeur and Bijwaard (1993), wherein
a major $2.2 billion revamp of a 400,000 bbl/day refinery that is being made to meet current
and future product volume and quality demands is described. The refinery crude supply is
expected to shift to a higher proportion of Middle East crude, increasing the sulfur intake (to
the refinery) by about 45%. The changes in refinery output as a result of the extensive
modifications are (1) the white product make will increase by 10% and (2) fuel oil production
will decrease by 40%. With regard to environmental emissions, SO₂ and NOx emissions are
expected to be reduced by 35 and 45%, respectively, due primarily to reduced residual oil firing;
also, particulate matter emissions will be halved. However, CO2 emissions from the refining site
are expected to rise substantially - by about 22% - because of the use of greater amounts of
hydrogen in the refining process. The global emission level of CO2 resulting from the refining and
the combustion of the products produced is, however, expected to remain essentially constant,
because of the higher hydrogen content of the refinery's products.
The above example serves to underscore the complexity/uncertainties in generating projections
relative to levels of energy efficiency improvements and the magnitude of emission reductions
that can be achieved. Nevertheless, it seems clear that there are a number of steps and/or
technology options that, if implemented, could reduce energy usage and help reduce emissions.
Specific opportunities are cited in the following sections. The implementation of refining proc-
ess/configurations modifications to reduce energy areas will require that the industry provide
strong environmental stewardship and that an appropriate investment climate exist.
Examples Of Technologies And Changes In Operations That Would Likely Improve Energy
Efficiency Utilization
The current ambiance in the refining industry is such that energy utilization improvement
programs have a lower priority relative to requisite environmental and general process
optimization activities. Nevertheless, based on the argument that "it is just good business and
good citizenship" to be energy efficient, the following sections contain examples of
process/technology/operating improvements that could potentially generate substantial
improvements in energy utilization efficiency. They are broken down into three categories,
namely: (1) near-term, straightforward improvement opportunities; (2) process/equipment
modifications; and (3) long-range opportunities requiring further R&D.
D-2.7
DRAFT
6/10/97
D-2.3.1 Technology Examples Available before 2010
Near-Term Improvement Opportunities
There are a number of equipment, maintenance, and operational improvements that can be
considered relatively straight forward and that can be made to improve overall system energy
utilization efficiency. Such improvements generally can be expected to have longer pay-backs
than current industry standards. They are likely to be difficult to justify under current economic
conditions of low fuel costs, limited availability of capital (from cash flow) and management
preoccupation with meeting environmental regulatory mandates, etc. Nevertheless, under an
"appropriate investment climate" their implementation could produce substantial energy
savings.
Monitoring Overall Energy Performance
Every refinery could promote energy efficiency stewardship by rigorously pursuing a program to
monitor equipment/process/overal refinery energy performance to identify (as early as
possible) when a system or piece of equipment begins to become inefficient so that corrective
actions can be initiated. Measured usage of energy for key equipment/systems can be
compared with allocated energy values based on efficient, established (allocated) performance
criteria and/or targets. Estimates of energy savings that can be realized through such action
range from 1-4% (Robertson, 1997; ANL, 1997)
Utility Svstem Improvements
The principal utility systems in a refinery are the cooling, steam, power, and fuel-gas systems.
They are integrated with virtually every process subsystem. Relatively speaking, these systems
in general have not and do not receive the same level of attention as the critical refining process
subsystems since they basically support these systems, and their impact on the overall refinery
operating profit margin is relatively small. The potential for energy savings, however, is
substantial (Robertson, 1997).
The lowest water temperature available from the cooling water system can impact the energy
utilization/separation characteristics (operation) of the distillation towers substantially.
Operating the distillation towers at the lowest possible temperature reduces the amount of
energy required to perform a separation. Reducing tower overhead temperatures by reducing
pressure (through more cooling) also reduces tower bottom temperatures. This in turn opens up
the temperature difference between the reboiled fluid and the energy source for the distillation
tower.
Cooling Water. Perhaps the most overlooked opportunity for saving energy lies within the
cooling water system. Reduction in light ends from towers (e.g., deethanizer, depropanizer and
debutanizers) reduce the reboiler duty for a constant separation. Similarly, lower temperature
operation of absorbers reduces the amount of light hydrocarbons lost to fuel gas. Cooling the
feed to the suction of a compressor may knock out additional liquid and is more efficient, so
lowering the suction and intercooler temperatures will improve efficiency even if no additional
liquid is formed.
The cooling water temperature is especially critical in the summer. Refineries generally
maximize gasoline make in the summer. This leads to additional light hydrocarbons made from
coking, cracking, and reforming processes. Ethane and ethylene can "lift" additional
D-2.8
DRAFT
6/10/97
hydrocarbons from the light ends systems associated with these processes. Proper cooling of
the absorber-deethanizers can reduce the light hydrocarbon losses that often wind up in the
flare, thus improving product recovery. The larger flares observed at refineries in the summer
demonstrates this phenomenon.
Lower cooling water temperatures can be achieved by revamping cooling towers using modern
fill material to get a closer approach to the wet bulb temperature. Additional/enhanced cooling
capability can be achieved by judicious use of the new generation of more efficient waste heat-
driven absorption chiller systems to either further cool waste streams or to cool process streams
directly. Such systems also provide an opportunity to utilize low-grade heat that is in excess in
many parts of the refinery. A Climate Wise Program demonstration of the use of a waste-heat
ammonia absorption refrigeration system (WHAARP) is currently under way at the Total
Refinery in Denver (ANL, 1997) The chiller is being used to cool the net gas/treat gas stream in
the reformer unit, the FCC main column overhead wet gas stream, and the unsat gas plant
sponge absorber light cycle oil streams. The enhanced cooling not only provides direct energy
savings but also indirect savings from enhanced product recovery and debottlenecking and
improved operating characteristics of the FCC wet gas compressors.
Steam Systems. Steam is used for a number of purposes throughout the refinery and accounts
for about 20% of energy use. It is used as stripping agent, in vacuum jets, as a heating medium,
and in powering turbines and pumps. Steam is used at several different pressures and
temperatures. Several opportunities exist to increase steam (energy) utilization efficiency. For
example, as an alternative to using letdown valves, back-pressure turbines can be used to
reduce pressures to the desired intermediate levels and in so doing produce electrical power
supporting purchased power. The steam used in condensing turbines that drives pumps,
blowers, etc. can be replaced by the new generation of more efficient electrical motors thus
generating a net reduction in energy usage. Similar benefits can be derived by replacing the
steam ejector system on the vacuum still with a mechanical system driven by efficient motors.
The opportunity also exists to use low-grade steam to preheat boiler feedwater in many
refineries. More vigorous maintenance of steam traps, valves, and rapid repair of other steam
leaks can also generate significant steam savings.
Increased attention to stripping steam usage can also provide dividends. Stripping steam is
often sent through a restriction orifice at a constant rate initially set to be proportional to some
maximum feed rate. Controlled reduction of stripping steam can have several benefits besides
the obvious direct energy consumption. For atmospheric pipestills, reducing the stripping steam
to the minimum required to achieve the flash point or IBP specifications can help unload the
vapor rate at the top of the fractionator. This in turn can make the fractionation more efficient
in the top of the tower and reduce the reflux or pumparound requirements to meet separation
specifications. Furthermore, less steam means less sour water from the tower overhead and
consequently less energy requirement in the sour water stripper.
The opportunities for reduction of steam usage cited can be best accomplished in conjunction
with introduction and integration of a state-of-the-art cogeneration plant into the refinery and
optimizing both steam and electricity use as discussed in a subsequent section.
Fuel Gas System. The refinery fuel gas system supplies about 1/2-2/3 of the energy consumed in
the refining process. The fuel gas is derived from the various conversion processes in the
refinery. The heat content of the gases' combustion products can, under certain conditions,
actually exceed the total energy requirements of the refinery; then the refinery is faced with the
situation of having excess energy. Traditionally, the excess fuel gas problem has been dealt with
D-2.9
DRAFT
6/10/97
by tolerating inefficient combustion, generating excess steam, and flaring (burning) the gas into
the atmosphere. The excess gas (energy) problem, if it exists in a refinery, is generally
exacerbated in the summer when the light ends separation systems are overtaxed, thus
generating additional losses of propane and other higher heating value products into the fuel gas
system. A number of opportunities can be pursued to "recover" a greater fraction of the fuel
gas (excess energy). Examples of potential solutions include (1) generating additional electrical
energy via an on-site cogeneration plant to reduce electrical purchases from utilities; (2) sale of
the gas to a utility (if one exists near by); (3) isolating and utilizing high hydrogen containing
streams as feed to the hydrogen plant, thus supplanting the usual methane (purchased gas)
feed; and (4) utilizing waste heat driven absorption refrigeration systems to recover the heavier
hydrocarbon products from the fuel streams, as described previously.
Equipment Maintenance
Aggressive maintenance programs to keep equipment operating in optimal condition can reduce
energy consumption substantially. A major opportunity exists with regard to controlling heat
exchanger fouling.
Heat Exchanger Fouling Minimization. Heat exchangers, including furnaces, are the workhorses
in refineries. A typical modern day refinery is equipped with hundreds of heat exchangers in
variable sizes. The overall energy efficiency of refineries is heavily dependent on the
feed/effluent heat exchangers that recover thermal energy from high temperature processes.
Foulant buildup impedes heat transfer, and the lost energy must be compensated by burning
additional gas or liquid fuels in furnaces. Thus, fouling of equipment significantly reduces the
efficiency of process operations and increases capital and operating costs. The resulting
economic and energy costs for the US refineries are well known: 0.2 Quads of energy (about
6.5% of the total energy consumed in refining) and more than $2 billion are lost each year due to
fouling (Leach and Holuska, 1981). The total worldwide energy and cost penalties are in the
range of 8 to 10 times that of the US refineries. The fouling problem (energy inefficiency) will
become more critical as more heavy oil and residuum is processed in the future.
It is estimated that the energy penalty due to fouling can be reduced by a factor of two with an
accelerated deployment of mitigation technologies. The key to achieving significant fouling
mitigation in the near term (3-7 years) is extending laboratory experimental data to field
operating conditions and incorporating various mitigation technologies in retrofitting the existing
heat exchange equipment and/or pursuing more rigorous maintenance procedures, e.g.,
increased frequency of heat exchanger cleaning, operating heat exchanger equipment below
threshold fouling conditions, and use of optimally designed physical devices such as enhanced
tubes and tube inserts in conjunction with chemical additives. In the long-term, research on
developing mitigation measures which can be employed before the process lines go into
operation can generate even larger dividends. The long-term solution of the refinery fouling
problem will require the development of prediction models and comprehensive data bases. An
added benefit from an aggressive effort to control fouling is that this will facilitate additional
heat integration of process equipment, thereby further increasing the energy efficiency.
A major factor impacting the pursuit of an aggressive program to minimize fouling is the eco-
nomic justification. The energy savings must be balanced against other costs, e.g., down time
for cleaning (which is generally very expensive), installation of fouling prevention devices, etc. It
is clear that these costs could easily exceed energy saving values.
D-2.10
DRAFT
6/10/97
Mid-Term Improvement Opportunities
Major opportunities to reduce energy usage in the mid-term also exist through retrofitting
and/or replacement of existing equipment nearing the end of its useful life and during major
refinery revamps that are periodically undertaken to meet market/environmental dictates.
Examples of process/equipment modification opportunities are as follows.
Fired (Process) Heaters
As indicated previously, over 60% of the energy used in refineries is obtained from burning
gaseous fuels in refinery heaters. Several approaches that seek to alter furnace designs and
control and greater heat recovery can be used to improve process heater efficiency. One of
these, "heat release profiling", seeks to match heat release with load and the flame shape with
process tube configuration. Radiant burners, which can be constructed to conform to the shape
of the load and thus can concentrate heat where it is needed can also be used. (Radiant burners
are generally more expensive than conventional burners, however.) Another approach is to
improve heat transfer through improved luminosity. Efficiency gains in the 5 to 10% range are
possible. A variety of luminosity enhancing techniques have been tried with varying degrees of
success. Also, the use of oscillating (pulsed) combustion, in which the fuel flow is oscillated
while the air flow remains constant, a technique now being evaluated, is realizing efficiency
gains of 5 to 10% in process heater applications. Also possible are re-radiation plates which
have been reported to produce similar gains. The use of recouperators to recover energy, e.g., air
preheat, is possible, especially for higher temperature processes; cost and an increase in NOx
emissions constrain the use of this approach.
Boilers
As indicated previously about 20% of all energy used by petroleum refiners is used for gen-
eration of steam. One route for improving boiler efficiency is through improved sensors and
controls. For example, balancing the burners in a multi-burner boiler and reducing excess air can
cut fuel use by 10 to 25%. In single burner boilers, excess air control can lead to similar gains.
The technology to automate excess air firing is available.
Recouperative systems such as air preheaters and feedwater preheaters can capture waste heat.
For many industrial-scale boilers, air preheaters are however not cost effective and they also
can impact NOx emissions. Installation of additional boiler tubes at the back end of the boiler
can also improve heat recovery but with the current price of energy and current investment
climates it will likely be difficult to justify this additional capital cost.
Distillation
Approximately one-fourth of the energy used in refining is in the distillation process (DOE
1990). Accordingly, a number of studies have been undertaken to identify opportunities to
reduce energy usage in the distillation system. As an example, an exergy analysis was
conducted to identify where, within the overall distillation system, the highest potential exists
to reduce energy consumption (Rivero, 1989). Not surprisingly, the equipment/subsystems with
the highest improvement potential identified were the fired heater, condensate reflux system,
the crude preheating train, and the effluent cooling train. The opportunities identified
underscore the importance of enhancing combustion efficiency and improving waste heat
recovery. The result is consistent with the most frequently recommended modifications to the
distillation processes, summarized in (Levine et al, 1995; Mix et al, 1978) namely, (1) improving
D-2.11
DRAFT
6/10/97
the fired heater combustion efficiency through modification of the burners, applying advanced
control technology, and use of a recuperative air preheater; (2) incorporating staged crude
preheat; and (3) replacement of stream ejector vacuum pumps with efficient electrically-driven
mechanical vacuum pumps (as discussed earlier). Other recommended actions to improve
distillation energy efficiency include (1) Selective introduction of vapor recompression into the
overhead reflux condenser subsystem, e.g., in the depropanizer column (Flores, 1984) ; (2)
improving heat recovery and integration between the crude and vacuum distillation units
(estimates of reduction of distillation energy usage range from 10-20%) (Levine et al, 1995); and
(3) substitution of reboilers heated by the main column bottom for the stripping steam in the
stripping columns (Rivero et al, 1989)
A more limited opportunity exists to improve the efficiency of the distillation tower (process)
itself, for example, by optimizing the number of trays, using more efficient packings, etc. The
greatest potential for improving distillation efficiency would require major revamps of towers to
essentially alter the distillation process by increasing the number of heat-integrated (internal)
and condensing steps, thus. reducing the loads on the fired heater and main condenser.
Although the improvements in distillation efficiency that can be achieved in this manner is
limited, it should be noted that small increases in efficiency can have major impact on the
consumption of energy because of the amount of high-quality energy used. Major opportunities
thus exist to reduce the energy consumption in the refinery distillation processes; a 10%
reduction in energy usage would reduce overall refinery energy consumption by about 2%.
Fluid Catalvtic Cracker (FCC)
As indicated previously, substantive reductions in total industry energy usage can be achieved
through modification of key processes to increase efficiency and/or increase product yields per
barrel processed to meet market demand. This approach not only reduces energy usage and
emissions but also improves competitiveness. The FCC presents an especially attractive
opportunity because it is now and is likely to continue to be a key process for meeting future
demand for "white products". As an example, the FCC currently produces approximately 40%
of the gasoline pool. The product slate yields from the FCC can be adjusted through
modification of operating parameters in the riser reactor, e.g., residence time, and/or equipment
such as feed nozzles, injection locations, etc., and by utilizing improved catalysts as discussed
in a following section. Recent studies suggest that it may be possible to increase desired
product yields from 2-6% per barrel of crude processed with appropriate modifications of
equipment and operating conditions and in so doing producing an essentially similar reduction
in energy usage and emissions. The expected shift to lower quality (lower API gravity and
higher sulfur) crudes expected to occur in the future will impact the savings achievable because
of their impact on FCC as well as overall refining operations. Expected increases in coke
generation provides opportunities to generate more heat and/or H2 as discussed in a following
section. Higher coke lay down on the FCC catalyst will turn the FCC into an exporter of energy
that will require installation of additional heat recovery equipment such as catalyst coolers, CO
boilers, etc.; that can be used for generation of additional steam, air preheat, etc. or for
production of electric power. Judicious integration of the excess heat into the refinery utility
system would thus reduce consumption of other fuels such as gas and electricity purchased
from utilities. The FCC thus stands in sharp contrast to the catalytic hydrocracker which is a
major consumer of energy.
D-2.12
DRAFT
6/10/97
Process Heat Integration
Process heat recovery and integration is one of the most effective means for reducing energy
usage in the refinery. The objective is to identify, capture and utilize the waste heat that is
generated when process streams are cooled and/or that result from the combustion of the
variety of fuels used in the refinery (e.g., from fired heaters). At times the industry has in fact
pursued process heat recovery and integration vigorously when economically justified (e.g.,
under high-cost energy conditions such as occurred in the 1970s). An example of such a success
is given in (Robertson, 1990), wherein it was reported that EXXON had improved energy
refinery energy efficiency by about 25% between 1969-1981; a significant fraction of the
improvement was due to enhanced heat integration. There are undoubtedly substantial
additional opportunities to achieve enhanced integration assuming a lower ROI can be justified
and the issue of capital availability can be resolved. The application of pinch technology
analysis to streams within a process and hence between processes can be used to develop a
composite heat availability/recovery balance sheet that can be used to identify which
equipment can be most advantageously modified, added, or relocated to debottleneck the heat
recovery system and thus to achieve the highest energy recovery and the "biggest bang for the
buck." (Robertson, 1997, 1990) One of the most promising opportunities where heat integration
can substantially reduce energy use is between the crude and vacuum distillation towers.
Several studies (Sunden, ?; Clayton, ?) have indicated potential energy saving in excess of 10%
with payback less than 2 years.
Requisite heat exchanger modifications can be achieved by adding heat transfer area or instal-
lation of devices that will improve heat transfer such as turbulence promotors, auto fouling
devices, extended surface tubing, plate heat exchangers, etc. The introduction of these and
other evolving new heat exchanger improvement technologies will require that the risk issue be
adequately addressed in order not to degrade refinery reliability.
Coke/Residue Gasification for Cogeneration/H, Production
The gasification technology that exists today provides refiners with a unique opportunity, albeit
a costly one, to simultaneously improve energy utilization, reduce emissions, and add value to
the bottom of the barrel by converting the coke and waste residues to a synthesis gas that can
be used for producing electricity, process steam and H2. The integration of a coke/residue
gasifier with a cogeneration plant and H2 production system would provide refiners with an
enhanced capability to process the lower quality petroleum feeds (expected in the future), to
meet changing market product demand and environmentally mandated specifications. The
technology would also allow the refiner to become an exporter of energy and provide an
inherent capability to dispose of various problem liquid/solid carbonaceous residues. The
gasifier converts the various residues into a clean syngas composed of H2 and CO which can
then be split into several streams that can be fed to a cogeneration plant to produce electricity
and steam at desired pressure levels and to a H2 plant. If desired, the syngas can also be fed
into the fuel gas system and used as the fuel for fired heaters. The conventional cleanup
process used in the gasification system recovers the sulfur from the fuel gas in the elemental
state and thus reduces SO₂ emissions dramatically. The cleanup system can also be sized to
clean up segments of the primary fuel gas stream as well. Any excess electrical power generated
in the cogeneration plant can be fed into the utility grid stream. Incorporation of a cogeneration
plant also provides the capability to optimize the steam utility system. The syngas generated
from the low-value residual waste thus supplants natural gas normally needed to augment the
D-2.13
DRAFT
6/10/97
refinery's fuel gas supply and that used for the production of H2. The technology is already
being introduced into various refineries.( Ladeur and Bijwaard, 1993; Quintana et al, ?)
D-2.3.2 Technology Examples beyond 2010 Requiring Further R&D
Long-Range Opportunities Requiring Further R&D
For the longer term there are a number of research directions in regard to novel refinery process
development/improvement that have the potential to produce breakthroughs in regard to refin-
ery efficiency and hence reductions of emissions of NOx, SOx and CO2. As indicated, the
quality of the crude supply is expected to continue to deteriorate in the future in regard to
sulfur metals and API gravity level (increased resid content). To process such crudes more
energy in general will likely be needed since process complexity will increase. To counteract the
pressure on increasing refinery complexity and energy utilization, new approaches to refining
need to be developed. A number of R&D directions have been identified that hold considerable
promise. Examples of several promising directions that can have major impacts on enhancing
refinery efficiency and reducing gaseous emissions are briefly described below.
Development of Improved Catalysts
The purpose of a catalyst is not to lower the energy needs of a reaction (which are governed by
thermodynamics) but to lower the energy of activation for a process and thereby increase the
kinetics and/or product selectivity. If it accomplishes either or both of these tasks, the energy
demands on a given process should decrease either due to lower heat demand (lower energy of
activation) or from greater throughput. Three major process areas which impact the energy utili-
zation efficiency in a refinery and thus that could benefit from improvements in catalyst
technology are: (1) hydroprocessing; (2) catalytic cracking; and (3) alkylation.
In hydroprocessing, much energy is utilized in heating up heavy oils and resids to temperatures
where the catalyst activity is high enough. Additional energy is expended in the compression of
hydrogen to pressures up to 2000 psi. Improved catalysts (capable of functioning at lower
temperatures and pressures) could reduce the energy used by decreasing the reaction tem-
perature of this process. Currently the hydrotreating reactions take place at temperatures of
660-750°F. Work on various catalysts and catalysts combined with various solvents has shown
that significant hydrotreating activity can be attained at 570°F. In addition, the hydrogen
selectivity of some of these catalysts is equal or superior to that of commercial catalysts.
Improved hydrogen selectivity would reduce hydrogen consumption per barrel of oil converted
and hence less hydrogen will need to be generated and compressed.
Energy usage could be improved for catalytic cracking in terms of product selectivity. Cracking
catalysts are extremely efficient at converting "good" gas oils to gasoline and distillate.
However, when significant fractions of resid and the metals that come along with these resids
are used as FCC feeds the selectivity (in terms of gasoline yield) drops dramatically. This
gasoline loss comes at the expense of increased coke and dry gas make. This requires catalyst
coolers in order to keep the temperature of the catalyst bed down (which comes from increased
coke burn) and higher compressor capacity to handle the increased dry gas yield. If catalysts
were designed to more properly handle higher amounts of heavy oils without the detrimental
effects outlined above then more resid could be handled in the highly efficient FCC with and
subsequent decreased utilization of the less efficient hydrotreaters.
D-2.14
DRAFT
6/10/97
The largest energy demand in the alkylation units are in the refrigeration units used to keep the
HF temperature down. Here the need is for a catalyst which will operate at temperature above
ambient. Many solid alkylation catalysts which are in pre-commercial testing and evaluation
function at temperatures around 300°F. This is a relatively low temperature for the refiner and
many of the streams requiring alkylation are at or near this temperature when they exit their
respective processing units. Such heat is normally considered waste heat and thus could easily
be utilized for the alkylation process. Therefore, even though the reaction temperature would go
up, the energy demand would go down.
Refining Process Modifications
In order to more effectively process the lower quality (higher metal, nitrogen and sulfur) crudes
while maintaining or enhancing product yields and energy utilization efficiency modifications of
current refining practice will likely be necessary. As indicated in the previous section, metals,
sulfur, and nitrogen, adversely affect catalyst performance (product yields) and energy
utilization in key processes, such as fluid catalytic cracking and hydrocracking and
hydrotreating processes. An incentive exists therefore to remove or reduce the levels of metals,
sulfur, and nitrogen as early as possible in refining process. An incentive also exists to reduce
the amounts of energy used in the crude and vacuum distillation, towers, the major consumers
of energy in the refinery process. An example of a potentially attractive process modification
that has been suggested is to input the crude directly into a thermal cracking unit bypassing the
atmospheric and vacuum towers. (Bartholis et al, 1986) The objective is to initially crack the
heaviest (aspheltenes) molecules in the 1000+ fraction of crude into lower boiling point
products while simultaneously removing the major portion of the metals, sulfur, and nitrogen
from the crude in the coke that would also be generated from this fraction. An equally
important parallel objective is not to alter the molecular structure of the material boiling at
<1000°F. The products emerging from the Thermal Cracking Unit are then processed through
the catalytic cracking, hydrocracking and hydrotreating units to generate the product yields
desired. Hydrogen requirements are expected to be less in these processing steps as is the
catalyst volume needed. Also enhanced product yield and selectively can be anticipated.
These improvements are expected to be derived from the removal of 30-50 % sulfur, 50-80%
nitrogen and greater than 90% of metals with the coke that is sent to the regenerator and burned
to provide the heat for the cracking process. Major energy savings and reduced gaseous
emissions would evolve from such a process. The technology can also be used as a field
upgrader (Dawson et al, 1995), thus facilitating utilization of heavy US crudes, e.g., California
Midwest Sunset crudes.
D-2.3.3 References
ANL, 1997, Ongoing Study of Energy Efficiency Improvements at a Low Complexity Refinery,
Internal Technical Memoranda/ANL
B. Bartholis et al., 1986, Petroleum Refinery of the Future, Japan Petroleum Institute, Tokyo, Oct.
27,.
W. Clayton, ?, Cost Reduction in an Oil Refinery Identified by a Process Integration Study at Gulf Oil
Refining, Ltd., Harwell, UK:ETSU.
N. Dawson et al., 1995, Heavy Crude Oil Processing Via Fluidized Bed Cracking and Hydro-
generation -Final Report, CRADA No. C/ANL-9301001, September 1995
Energy Information Administration, 1996, Annual Energy Outlook 1997,, Dec..
D-2.15
DRAFT
6/10/97
Flores, et al., 1984, "Recompression Saves Energy", Hydrocarbon Processing, July.
Haynes, 1976, Energy Use in Petroleum Refineries, ORNL/TM-5433, September.
Ladeur and H. Bijwaard. 1993, "Shell Plans $2.2 Billion Renovation of Dutch Refinery", Oil &
Gas Journal, April.
Leach and J. L. Holuska, 1981, Fouling of Refinery Heat Transfer Equipment, Hemisphere
Publishing Co., Washington DC, pp. 619-643.
Levine et al., 1995, Efficient Use of Energy Utilizing High Technology-Assessment of Energy Use in
Industry and Buildings, World Energy Council Report, September, London, Kogan Page Ltd.
Mix et al., 1978, "Energy Conservation in Distillation", CEP, April.
Quintana et al., ? The Gasification Solution--Heavy End Optimization
Rivero, et al., 1989, "Energy Analysis of a Crude Oil Atmospheric Distillation Unit",
Proceedings of the International Symposium on Thermodynamic Analysis and Improvement of Energy
Systems TAIES '89, International Academy Publishers, Beijing, PP. 506-510.
L. Robertson, 1990, Energy and the Environment in the 21st Century, MIT Press, Cambridge, MA.
Robertson, 1997. Potential Energy Improvements-Emphasis on Refining, Personal Communica-
tion to ANL, March 1997
Sunden, ?, "Analysis of the Heat Recovery in Two Crude Distillation Units", Heat Recovery
Systems and CHP 5(8): p. 483-488.
US Department of Energy, Office of Industrial Technologies, 1990, Industry Profiles - Final
Report: Energy Profiles for us Industry, Washington, DC; US Government Printing Office.
D-2.4 TECHNOLOGY EXAMPLES FOR GLASS
(Prepared by Zhuoxiong Mao and Hann Huang, Energy Systems Division, ANL)
The glass industry is comprised of several major product segments each with their own
processes for producing final products. The segments include container, flat glass, wool and
textile fiber, specialty, lighting, and hand glass. The major common energy intensive stage of the
glass industry is the glass furnace. There are nearly 500 furnaces in over 200 plants in the glass
industry (ignoring the smaller hand glass segment). While there are other stages of product
finishing which also require significant amounts of energy, the examples below focus on the glass
furnace as the primary area of concern for energy efficiency. Other process and product specific
areas of energy efficiency are also possible.
D-2.4.1 Technology Examples Available before 2010
Considerable energy savings may be achieved by the year of 2010 by partially adopting current
commercially available technologies, such as the oxy-fuel process, advanced burner and
batch/cullet preheating technology.
D-2.16
DRAFT
6/10/97
Oxy-Fuel Process
Since 1991, the fiber, container and specialty glass industries have accepted the oxy-fuel
process as an alternative to regenerative and recuperative air-fuel furnaces. According to one
source, more than 50 major (20 ton/day) furnaces have been converted to oxy-fuel combustion
technology (Geiger 1996). The advantages of oxy-fuel over air-fuel combustion system are
reduced NO, and SO, emissions, lowered particulate carryover, improvements in glass quality,
and higher throughput and energy efficiency.
Anticipated or recently enacted air emission regulations will be a significant driving force for
oxy-fuel conversion in the near future, especially for NO, and particulates. In particular, oxy-
fuel provides a viable option for resolving the NO, "new source" issues of increasing production
in Ozone non-attainment areas, requiring Best Available Control Technology or Best Available
Retrofit Control Technology. Particulate stack emissions are reduced by inherently lower gas
velocities over the melt and reduced flue gas volumes.
Oxy-fuel glass melting has a number of significant operational improvements over conventional
furnaces. Varying the individual burner inputs longitudinally and flame length laterally, to
establish desirable thermal profiles of the melter, will use energy only where needed, and avoid
excessive temperature in other areas. Configurations for placing oxy-fuel burners in a melter can
allow more precise thermal input and more closely control the melting process. Where
previously glass quality has been affected by marginal melting conditions, oxy-fuel conversions
have been reported to also improve quality.
In the oxy-fuel process, oxygen or oxygen-enriched air is used in combustion in the melting
furnace. Energy input with oxy-fuel firing is reduced because the energy required for heating the
79% of inert nitrogen in the air-fuel process is avoided. This results in further efficiency
improvement by reducing the volume of combustion products, which remove BTU's from the
system. The atmosphere of oxy-fuel furnaces is different from conventional furnaces. Water
and CO2 concentrations in the oxy-fuel furnace are much higher than in the conventional furnace.
This results in higher heat transfer efficiency from the combustion gas to the melting batch
because the radiative emissivities of water and CO2 are much higher than nitrogen. It is
reported that fuel savings from oxy-fuel conversions are typically 10-15% for well designed
soda-lime regenerative furnaces, and at least 30-40% for direct fired or regenerative boro-silicate
or lead glasses (Ross 1996).
The reasons for converting to oxy-fuel are different for each segment of the glass industry. The
cost of purchasing oxygen for furnace conversion must be justified by specific benefits and other
desired attributes. Meeting the NO, requirement is the most significant reason for converting to
oxy-fuel. Other important reasons, in descending order, are capital cost reduction, energy
savings and production increase. In the container segment, NO, reduction is the dominant
reason for conversion to oxy-fuel. The oxy-fuel process has become the preferred process in the
fiberglass industry, with capital reduction being the leading reason. The flat glass segment is the
only segment that hasn't adopted the oxy-fuel process.
Currently, approximately 15% of the large commercial furnaces in the U.S. have been converted
to the oxy-fuel process (Ross 1996). By the year 2010, an additional 35% of the large
commercial furnaces may be converted to the oxy-fuel process.
D-2.17
DRAFT
6/10/97
Advanced Burner Technology
Adoption of newly developed burners in the oxy-fuel process further improves the energy
efficiency of the process. Replacement of conventional burners with the new burners is less
complicated and requires less cost and downtime. It is anticipated that the new burners will be
100% used in the oxy-fuel process by 2010. Descriptions of three different types of burners
follow.
Air Products and Chemicals Inc. (Allentown, PA) has developed clean-fire High Radiation (HR)
oxy-fuel burners (Chemical Engineering 1995), and has demonstrated this technology in a glass
manufacture's furnace. These burners produce flames that have higher radiation and better bath
coverage than conventional oxy-fuel burners. Increased flame radiation is accomplished through
a proprietary soot generation process. The system's design provides twice the radiation and
creates potential cost savings by reducing fuel and oxygen requirements, each by up to 10%.
The key to the burner's performance is a proprietary oxygen-proportioning system, which uses a
diverter valve that can introduce oxygen in stages. This enables glass producers to cut NO,
emissions by an additional 30-40%, relative to traditional oxy-fuel burners.
A full-scale, field demonstration was undertaken at Owens-Brockway (Los Angeles) with
Praxair's oxy-fuel burner system technology in a container-glass furnace (Geiger 1996). The
technology uses a J-L burner configuration developed by Praxair. A major portion of the oxygen
for combustion in this system is diverted to an oxygen lance, typically located between the
burner and the glass surface. The oxygen introduced through the lance is diluted to low
concentration by mixing it with furnace atmosphere before reacting with fuel. This results in
staged combustion of the fuel and a flame with much lower peak temperatures than the flame of
conventional oxy-fuel burners, so that reduced NO, emissions and improved glass quality can
be achieved.
BOC Gases (Maumee, OH) presented results on application of the Flat Jet oxy-fuel burner to
three different furnaces and glass types (Geiger 1996). The Flat Jet oxy-fuel burner is designed to
produce a low momentum, highly laminar flame that has a well-defined envelop over a wide
operating range. Use of this burner in a conversion of a lighting products furnace to oxy-gas
firing has resulted in 35% increase in daily pull rate, 30% decrease in fuel use, and improvement
of product quality.
Glass Batch/Cullet Preheater Technology
With Gas Research Institute support, a dual batch/cullet preheater technology has recently been
developed. The batch/cullet preheater uses the oxy-gas furnace's waste heat to preheat cullet
and batch before feeding it to the furnace. The cullet is fed from the top and encounters waste
heat-the hot combustion gases rising from below. Preheating cullet and batch reduces the
amount of energy and oxygen required in the overall melting process. Because there is no
consolidation of batch (briquetting) required as a first step in the so-called "raining bed"
preheater, heat transfer is more efficient, leading to smaller units that are less expensive.
Corning, Inc. has been granted a license to the technology (GRID 1996).
D-2.4.2 Technology Examples beyond 2010 Requiring Further R&D
In January, 1996, the glass industry issued "A Clear Vision For A Bright Future" to meet the
challenges by the year 2020. The document presented the goals of the industry and the research
D-2.18
DRAFT
6/10/97
priorities that will ensure its continuing competitiveness. To build a strong foundation for the
future of American glass, the industry has identified the following areas for technology
improvements:
Production efficiency, including improved manufacturing processes and new
techniques that maximize glass strength and quality;
Energy efficiency and conservation;
Recycling;
Environmental protection, including control of nitrogen oxides, sulfur oxides and
particulate; solid waste reductions; and waste water reuse;
Innovative uses of glass.
The industry has set a goal to reduce process energy consumption from the present level by
50%. This indicates that energy savings of 63 trillion Btu per year will be achieved according to
the current level of 170 trillion Btu per year. In the following, R&D needs relevant to the
improvement of energy efficiency will be discussed according to the vision document.
Optimizing Electric Boost to Reduce Total Energy Consumption
High energy efficiency, through conversion of electric energy into useful heat, and low
volatilization are the primary advantages of electric melting. Current operating practice has
shown that effective use of electricity near the back end of the furnace, where the batch is
added, can reduce fossil fuel needs. Research needs for optimizing electric boost include, but
are not limited to, investigating new electrode and electric arc melting processes, modeling of the
current technology to fine-tune operation conditions, such as energy inputs and locations of the
electrodes, and improving the electrode control system (Glass Industry Working Group date?).
Improving Furnace Design and Operation to Maximize Combustion Efficiency
In recent years, furnace energy efficiency has significantly increased through adoption of new
refractory, oxy-fuel process, new burners and other technologies. However, the basic design of
conventional fuel-fired furnaces has remained unchanged for many years. There is a need to
improve the furnace design to integrate the newly developed technologies and optimize furnace
performance.
Computer modeling can provide a cost-effective tool for testing new design ideas, such as
furnace configuration, burner arrangement, firing strategy, etc. The model should include the
dynamics of combustion, heat transfer between the gas phase and the melting phase, mixing
and reaction in the batch and glass melt. In order to develop a reliable model, thorough
understanding of chemical and physical processes in the melting phase is essential. Physical
properties and kinetic data need to be acquired and validated. Finally, the model should be
evaluated against data measured in a typical glass furnace.
There is a need to develop commercially viable rapid glass melters that speed up the melting
process, reducing the size of the batch and the time required to produce glass. These melters
should have higher energy efficiency and flexibility, and lower pollution emissions, so that they
can be built in close proximity to consumers to reduce transportation costs.
Heat losses from the furnace wall and openings consists of more than one third of the energy
required in the melting process. New port designs and better insulation materials are needed to
increase the furnace heat efficiency.
D-2.19
DRAFT
6/10/97
Recovering and Reusing Waste Heat from Oxy-Fired Furnaces
Recovery and reuse of waste heat from the oxy-fuel process will further increase energy
efficiency of the process. Preheating the batch and cullet, described above, is one method to
recover heat from the flue gas. Other options, such as regenerative oxygen heat recovery
(Browning and Nabors 1996) and a "synthetic air" concept (Argent 1997), have been proposed,
and need to be tested and evaluated.
Producing Oxygen More Efficiently for Oxy-Fuel Firing
A Thermal Swing Adsorption (TSA) oxygen production process has been demonstrated in the
laboratory with enrichments of up to 89% (Mathur date?). The process is based on synthetic
chemicals that can reversibly bind oxygen at low temperatures and release it at elevated
temperatures. The operation is in a temperature range of 70 to 220°F, so low grade waste heat
can be used to drive the process, and the external energy required for produce oxygen can be
reduced.
Discussion of Energy Savings in the Glass Industry
The estimation of energy savings by using the oxy-fuel process does not include energy
consumption in the production of oxygen. It is estimated that about 2 MMBtu is required to
produce one ton of pure oxygen. If an energy input for melting one ton of glass of 6 MMBtu and
a heat content of 1000 Btu/ft for natural gas are assumed, approximately 0.5 ton of oxygen is
required to melt one ton of glass. Therefore, about 1 MMBtu per ton of glass is consumed in the
production of oxygen. Considering this factor, the total energy savings by using the oxy-fuel
process is not as significant as calculated above, unless waste heat in the process can be
recovered for the use in the production of oxygen, such as the TSA process.
In a regenerative glass furnace, a rough heat balance indicates that about 37% of the energy
input goes to the melted glass, 23% to the stack and 40% through the wall. Most of current
research is focused on reducing heat loss through the stack. However, potential for energy
savings would be even greater by recovering heat from the melted glass and from reducing heat
loss through the wall. From increasing energy efficiency point of view, research in these two
area should be enhanced.
In the forming process, cullet is generated and circulated back to the melter. Technologies to
reduce cullet generation in the forming process can increase production efficiency and reduce the
cullet amount, so that the energy consumption per ton of glass will be decreased.
D-2.4.3 References
[no call out] "Industry Identified Combustion Research Needs for the Glass Industry", Idaho
National Engineering and Environmental Laboratory, End Use Energy Efficiency Processes
Department, Lockheed Martin Idaho Technology Company.
Argent, R.D. 1997. "Synthetic Air" for Oxy-Fuel Glass Melting Furnaces with Filtration and
Regeneration," Presented at the Annual Meeting of the Society of Glass Technology, January 17,
1997, Clearwater, FL.
D-2.20
DRAFT
6/10/97
Browning, R. and J. Nabors. 1996. "Regenerative Oxygen Heat Recovery for Improved Oxy-Fuel
Glass Melter Efficiency," Presented at the 57th Conference on Glass Problems, October 8th and
9th, 1996, Columbus, OH.
Chemical Engineering. 1995. "A Novel Burner Design Cuts Fuel and O₂ Consumption by 10%,"
August.
Geiger, G., ed. 1996. "Glass Problems Conference Focuses on Oxy-Fuel," The American Ceramic
Society Bulletin, Vol. 75, No. 3, March.
Glass Industry Working Group. Adapted from discussion in the Energy Efficiency and
Conservation Subcommittee..
GRID. 1996. "License Granted to Corning, Inc.," Summer.
Mathur, V.K. date? Thermal Swing Absorption Process for Oxygen Separation from Air,
DOE/CE40927-3, Prepared for U.S. Department of Energy, Office of Industrial Technologies.
Ross, C.P. 1996. "Oxy-Fuel Conversion Challenges For Glass Manufactures," Presented at
American Flame Research Committee Meeting, May 6-7, 1996, Orlando, FL.
D-2.5 TECHNOLOGY EXAMPLES FOR ALUMINUM
Aluminum smelting is highly capital intensive, with capacity cost estimates ranging from $3,000
per metric ton for expansion of existing facilities to $5,000 per metric ton for new facilities
(BOM 1993). Low energy costs in countries such as Brazil, Canada, and Australia have made
the international aluminum industry extremely competitive, and near term construction of
smelting capacity is not expected in the United States. Investment in state-of-the-art
technology has also been limited by capital constraints.
D-2.5.1 Technology Examples Available before 2010
A variety of technologies exist, however, that have the potential to incrementally reduce energy
intensity in the aluminum industry in the timeframe to 2010.
Improving Hall-Heroult Cell Efficiency
The primary starting material for the production of aluminum is bauxite, containing high
concentrations (45 - 60%) of aluminum hydroxide. Bauxite is mined and, through the Bayer
process, converted into alumina (aluminum oxide) which is ground to a powder and then
reduced to aluminum by the Hall-Heroult process.
In the Hall-Heroult process the alumina is dissolved in steel boxes, or cells, in a mixture of
molten cryolite. Direct electrical current is passed through the mixture, reducing the alumina to
aluminum and oxygen. The oxygen combines with carbon at the system anode forming carbon
dioxide. The aluminum, which is heavier than cryolite, sinks to the bottom of the cell and then
can be tapped off.
Modern aluminum smelting cells consist of a steel shell lined with refractory insulation. These
are then lined with either a rammed mix of pitch and anthracite coal or coke baked in place by
D-2.21
DRAFT
6/10/97
the passage of electric current, or prebaked cathode blocks cemented together. The carbon lining
acts as a cathode in the system. Cell relining, which normally occurs every 2 to 4 years, is an
appreciable part of production expense, including not only the cost of labor, collectors, lining,
and insulation materials, but also loss of electrolyte materials absorbed by the spent lining.
Anodes, either prebaked or Soderberg, are suspended from a superstructure above the cell and
connected to a movable bus so that their vertical position can be adjusted. The cell is brought
into operation by first lowering the anode until it contacts the carbon cathode lining of the cell.
Current is then passed through the cell to increase the temperature. Cryolite is added and the
anode raised until the cell fills to the appropriate height. During operation of the cell a crust
forms on the surface of the molten bath. Alumina is added on top of the crust, where it
preheats and water is removed. The crust is then broken and the alumina stirred into the bath.
The current U.S. composite baseline energy intensity for aluminun smelting is estimated at 15.2
kWh/kg of aluminum, with the potential near-term reduction using retrofit technology estimated
at 13 kWh/kg (Energetics 1997). Performance in the range of 13 to 15 kWh/kg has been
achieved in domestic smelters through a variety of techniques including enhanced potline
controls, better anode rod connections, improved cathode block materials, and increases in
anode size resulting in lower current density (Newsted et al. 1992, Jeltsch and Franklin 1992)
Additional research to design dimensionally stable cells and to optimize materials use for
internal control of cells, and to use signal analysis to analyze cell voltages in potlines are seen as
areas which can improve smelting performance in the next 10 years (Energetics 1997). The
primary barriers to adoption of high efficiency technologies may be economic, however.
Materials Recycling
Remelting aluminum scrap requires only a small fraction of the energy required to smelt
aluminum from alumina. Recovery of old scrap (discarded aluminum products) has increased
from less than 200 metric tons per year in 1970 to more than 1,600 metric tons in 1992
(Aluminum Association 1993). In 1993, aluminum recovered from old scrap was equivalent to
about 25% of apparent consumption in the U.S. (DOI 1994).
While some of the barriers to higher recycling rates are institutional (e.g., perceived value of
recycling beverage containers), technological barriers also exist. These include problems with
scrap sorting, separation, cleaning, and pre-treatment, which inhibit the increased use of
different types of scrap and also contribute to problems with metal quality. Byproduct
recycling (e.g., salt cake and spent potlining) is also inhibited by a lack of knowledge of
byproduct characteristics (Energetics 1997).
Research needs identified by the DOE include the development of alternative pre-treatment
technologies for scrap, the development of lower-cost aluminum purification technologies, and
statistical analysis to characterize the composition of waste streams from smelters. A critical
review of the U.S. recycling industry infrastructure could also identify ways to enhance
aluminum recycling rates (Energetics 1997). Given the magnitude of energy savings associated
with recycled aluminum versus virgin aluminum, enhanced recycling may offer the greatest
energy savings and greenhouse gas emissions reduction opportunities in the short term.
D-2.22
DRAFT
6/10/97
Improve Furnace Efficiency
Improving energy efficiency of melting and holding furnaces offers significant potential for
energy savings in the secondary aluminum industry. Several commercially available technologies
exist for reducing energy use in furnaces including heat recuperators and regenerators, and the
use of oxygen assisted combustion. Heat recuperators operate by passing the combustion
products through heat exchanger tubes allowing the preheating of inlet combustion air and
recovery of heat that would otherwise be exhausted to the atmosphere. Heat regenerators
accomplish heat recovery through a paired burner/exhaust system in which the burners
alternate in the firing mode in cycles lasting about 20 seconds. As the combustion products are
exhausted through the non-firing burner, a heat storage material absorbs energy. In the firing
cycle this stored energy is released to the cool intake air, with the result that again less heat is
rejected to the atmosphere.
Oxygen assisted combustion uses oxygen in a dual-firing burner to increase furnace melt rates,
reduce energy use, and reduce emissions. Oxygen assisted combustion has been used for more
than 30 years in the aluminum industry (Heffron et al. 1993), but often results in problems such
as large dross formation, excessive refractory consumption, and less than expected energy
savings. Low flame luminosity with oxygen assisted burners can also reduce radiative heat
transfer. Advanced burner designs incorporate more precise gas, air, and oxygen control to
produce a high temperature, high luminosity flame. Energy savings from oxygen assisted
combustion can be substantial.
D-2.5.2 Technology Examples beyond 2010 Requiring Further R&D
Many advanced technologies have been researched that could provide dramatic reductions in
energy use in the aluminum manufacturing process. Because of the inherently high energy
requirements of the Hall-Herault process, the most dramatic energy savings and emissions
reductions are likely to result from new or improved smelting technologies. These include the
development and commercialization of inert anodes, carbothermic reduction processes,
aluminum chloride processes, and wettable titanium diboride cathode components.
Inert Anodes
Inert anodes offer a variety of advantages over traditional carbon anodes, including increased
cell productivity, reduction in cell shorting due to undulations in the molten metal, and higher
metal purity. The most promising materials presently being evaluated are ceramic/metal
composites consisting primarily of nickel oxide and nickel ferrite with a copper/nickel metal
phase (Windisch and Strachan 1991). Energy savings from inert electrodes are estimated at
11% over current production methods (Energetics 1990). In addition, inert anodes have the
potential to substantially reduce CO2 emissions during smelting.
Carbothermic Reduction Process
Direct reduction processes for aluminum production have long been the subject of research by
the aluminum industry. Several carbothermic production methods have been patented, for
instance, and one was even brought into production by the Pechiney Company in France, but
none are currently operating. One problem with carbothermic reduction of alumina in electric
furnaces is low yields as the result of formation of solid aluminum carbide and aluminum
suboxide, and aluminum vapors that react with carbon monoxide as they leave the furnace.
Vaporization and carbide formation can be reduced by adding a metal to the furnace, thus
D-2.23
DRAFT
6/10/97
forming an alloy. Aluminum can then be extracted through a separate purification process.
Direct reduction has the potential to reduce energy consumption as much as 25% below that of
conventional Hall-Herault cells (Energetics 1990).
Aluminum Chloride Process
In aluminum chloride processes, alumina, carbon, and chlorine are reacted to produce aluminum
chloride and carbon dioxide. The aluminum chloride is then electrolyzed in bipolar electrode
cells to produce aluminum and chlorine. Though the process has the potential to reduce energy
consumption as much as 25% below existing Hall-Heroult cells (Energetics 1990), the need for a
reactor to convert chlorine to aluminum chloride offsets the cost advantages.
Titanium Diboride Cathodes
Wettable titanium diboride cathodes have the potential to significantly reduce energy use in
aluminum production. Because of its good electrical conductivity, titanium diboride cathodes
can significantly reduce voltage drop at the cathodic aluminum interface. Potential energy
savings are estimated as high as 30% over conventional cells (DOE 1990). Though most of the
major aluminum producers have conducted research on titanium diboride cathodes, the high
cost of production and early failure of the components have kept them from commercialization.
D-2.6 TECHNOLOGY EXAMPLES FOR IRON AND STEEL
(Prepared by Ken Natesan, Energy Technology Division and Leslie Nieves, Decision and
Information Sciences Division, Argonne National Laboratory.)
Iron and steel industry comprises of the ore based integrated steel plants and the scrap based
"mini mill". Steel production via integrated plants has been decreasing, while that of the
Electric Arc Furnace (EAF) based mini mills has been increasing. At present, the production
capacity of the mini mills is comparable to some of the smaller integrated plants. Mini-mills are
more energy efficient, since they use 100% scrap, but the range of products that can be
produced in mini-mill is somewhat limited by scrap quality issues.
As technologies introduced for mini-mills are adopted in the integrated mills and mini-mill begin
to backward integrate into the manufacturing of iron (rather than relying exclusively on scrap)
these distinctions begin to blur. Most of the issues the iron and steel industry face are generic in
nature, such as process development, process efficiency, raw material availability and
flexibility, process control, environmental compliance, sensors and monitors, and intelligent
processing. The following sections identify some currently available technologies, if
implemented, can have a significant impact on the industry.
Technology and R&D discussions in this section are grouped by their relationship to the topics
of ironmaking, steelmaking, and thermomechanical processing. However, many of the issues
faced by the iron and steel industry are generic in nature, such as process development, process
efficiency, raw material availability and flexibility, process control, and environmental
compliance.
D-2.24
DRAFT
6/10/97
D-2.6.1 Technology Examples Available before 2010
Ironmaking
The current practice for primary production of iron is by blast furnace processes which involve
reaction of iron ore with a reductant (traditionally coke) and a flux (limestone) at elevated
temperatures in a shaft furnace. The process normally takes about 6-8 h to produce liquid
metal from a given charge. The industry currently is in a state of flux regarding ironmaking
process alternatives to the blast furnace. Direct reduction and direct smelting are the two
approaches that are being examined in a variety of processes under development in the U.S.
and abroad. The drivers for the alternate processes are the elimination/minimization of coke
and coke oven batteries (which are environmentally unacceptable without significant
investments for compliance) and increased reaction rates thereby improving the iron production
rate.
Gas-based direct reduction processes
These processes include MIDREX, HYL, SPIREX, Iron Carbide, and CIRCORED, which all
involve direct reduction of iron ore pellets/fines with natural gas/hydrogen as a reductant to
produce a solid or, sometimes, liquid iron-rich product.
Coal-based direct reduction processes
These include the Rotary Kiln, Grate Car, Fastmet, Comet, Circofer processes, involving intimate
mixing of iron ore fines and coal at elevated temperatures to accomplish the reduction process.
The processes differ in details with regard to feedstock, type of reactor, operational features,
and level of development.
Typical examples of direct reduction processes are:
Qualitytech Steel Corporation, Corpus Christi, Texas, has begun construction of an iron
carbide facility, expected to be operational by July 1998. The facility will annually
convert 1.2 million tons of high-grade iron ore fines, by deoxidizing the ore and adding
a carbon bond, to create iron carbide for use by electric furnace steel makers. Only one
other facility worldwide manufactures iron carbide on a large scale.
Kobe Steel and Midrex Direct Reduction Corp. have developed a production approach
for molten iron that reduces the process from hours to minutes (Metals Industry 1996).
Midrex (a subsidiary of Kobe Steel located in Charlotte, NC) hopes within five years to
commercialize the process. With this approach, pellets made of iron ore fines and
pulverized coal are heated to 1300-1500°C using natural gas as a reductant. A
reduction time of 6-10 minutes is claimed, compared to the 6-8 h with a traditional
blast furnace. Because the product is in molten form, there are savings in downstream
steelmaking operations and the material can be cooled to iron shot or ingots without
reoxidation.
A rotary hearth process called COMET is being developed by the Belgian steel research
organization and a demonstration plant is under construction at Sidmar's plant near
Gent (Steel Times 1997). The process produces high-grade sponge iron from ore fines
and coal, without pelletizing the charge materials.
D-2.25
DRAFT
6/10/97
Direct smelting processes
Direct smelting takes iron ore and coal and directly converts them to hot metal without the use
of coke. Several processes (COREX, HISMELT, AUSMELT, ROMELT, Cyclone Converter
furnace, etc.) are under development in the U.S. and abroad (Nilles 1996). All of these
processes have goals of high productivity, simplicity of engineering, ability to use a wide range
of coals, ability to scale-up to a level equivalent to a blast furnace, and environmental
compliance with minimum cost. All produce hot metal with compositions comparable to that
from a blast furnace.
Typical examples of direct smelting processes are:
The COREX process is commercially available and the C-2000 module at Posco's
Pohang Works in Korea has successfully demonstrated hot metal production at a rate
of 2000 t/day with acceptable steel composition (Steel times 1997). Several COREX
C-2000 modules are under construction in Korea, India, and South Africa.
Cyclone converter furnace technology is being examined in a 20 t/h pilot plant in
Holland. Independent evaluation of a cyclone converter furnace is also being made by
Centro Sviluppo Materiali (CSM) in Italy with a pilot unit of 3-5 t/h (Steel Times
1997).
Top Gas Power Recovery Turbines, Compression/Expansion
Due to its energy content, blast furnace top gas is used as fuel in various facility stoves,
furnaces, and boilers after cleaning. In large, newer blast furnaces which operate at higher
pressures, installation of an energy-recovery turbine in the gas cleaning system can contribute to
the facility's electricity needs. A gas expansion turbine using the excess pressure can recover
both pressure energy and some sensible heat energy from the gas. Energy savings are estimated
at 0.6 GJ/tonne crude steel (De Beer, et al. 1994).
Coal or Natural Gas Injection
Pulverized or granulated coal, residual oil, or natural gas can be injected directly into the blast
furnace to partially substitute for coke inputs, thus reducing CO2 production and toxic
emissions of coke production. The injection of oil or natural gas has operational benefits, and
has been practiced for many years. Interest in very high levels of injection is more recent,
encouraged by the diminishing availability of domestic coke. Coke remains essential to blast
furnace operation, since coke layers are essential for supporting alternating layers of ore and
maintaining bed permeability.
Operation based on all coke requires about 1000 lb of coke per ton of hot metal (THM). Coal
injection rates range from about 200 to 400 lb per THM, with each ton of coal displacing
approximately one ton of coke. There is a tendency for this coke replacement ratio (mass of
coke displaced per unit mass of coal injected) to drop at higher levels of injection. Typical
values are 0.8 to 1.0. The reduction in net energy consumption and CO2 emissions are realized
as a result of the fact that about 1.39 tons of coal are required to produce a ton of coke. Thus,
even at a coke replacement ratio of 0.8 tons of coke displaced per ton of coal injected, the
injection of that ton of coal avoids the use of 0.8 X 1.39 = 1.11 tons of coal for coke production
for a net reduction in coal use of 0.11 ton. This substitution increases the oxygen requirement of
D-2.26
DRAFT
6/10/97
the iron reduction process. The net savings, given the increased oxygen production needed, is
estimated at 3.76 GJ/tonne of coal injected (De Beer et al. 1994).
Injection of hydrocarbons into the lower section of the furnace also has the advantage of
improving furnace stability and hot metal quality. Pulverized coal injection allows substitution
of lower grade, lower cost coal for metallurgical coal, which is used for coke making.
All active U.S. furnaces inject one or a combination of supplemental fuels. Natural gas is
injected at rates up to 250 lb. per ton of iron (125 lb./ton average) at 25 furnaces (Hogan and
Koelble 1996a). Current coal injection designs, of which there are three basic types,
theoretically can inject at a rate of up to 400 lb/ton of hot metal (Carmichael 1992). In the US
as of 1993, 15 furnaces incorporated coal injection systems. These include some of the largest
furnaces totaling over one third of 1993 North American hot metal production (Gardner et al.
1996). Injection rates currently range up to 375 lb./ton of iron. Four more furnaces are
scheduled to start coal injection in 1997.
Steelmaking
Steelmaking operations are generally conducted in two stages, melting of the iron/scrap in a
basic oxygen furnace (BOF) or in an electric arc furnace (EAF) and subsequent refining
operations. Some of the major concerns are the variability in feedstock composition (especially,
scrap quality and trace elements in scrap which may impart deleterious properties to the final
product), availability of sufficient scrap material, and costs involved in front-end separation
and/or preparation of the scrap material as a feedstock for EAFs. Directly reduced iron, hot
briquette iron, and iron carbide constitute less than 5% of the feedstock in EAF operations but
are expected to increase substantially in the next 15 years.
Scrap Preheating
Energy consumption in electric arc furnace operations can be reduced by preheating scrap to
approximately 400°C with EAF offgases. Heated metal charges comprising 20-30% of inputs
can result in power consumption rates of <300 kWh/tonne liquid steel (Scheidig 1995). The
potential energy savings is roughly 90 kWh/ton of liquid steel. This is based on a 76 ton
furnace, with an annual capacity of 900,000 tons. For a DC Fuchs shaft furnace compared to a
conventional DC furnace, energy savings of 13.5% are estimated and reduced electrode
consumption of 29%. Baghouse dust reduction is estimated at 30% (Haissig 1994).
In addition to energy savings, scrap preheating with furnace offgases has other advantages. In
the dual shaft furnace design, iron particles in the offgas tend to adhere to the scrap, resulting in
iron recovery in the melt and leaving the offgas zinc-enriched (Burgmann and Pelts 1995). If
zinc levels are enriched to above 25%, the dust may be an acceptable input to zinc refining,
rather than requiring disposal as a RCRA-listed hazardous waste (Center for Metals Production
1987). Preheating also reduces furnace tap-to-tap time (normally about an hour) by 12 to 15
minutes (Scheidig 1995), resulting in increased raw steel production capacity, measured in terms
of sustainable annual production.
A British study of scrap preheating involving modification of an existing furnace found an
energy saving of about 25 kWh/liquid tonne. The plant-specific investment required had an
actual payback period of over four years (Dept. of Energy 1987).
D-2.27
DRAFT
6/10/97
Use of DC, Rather Than AC EAFs
DC EAFs are similar to more widely used AC EAFs except that they are powered by DC
current and have one large electrode in the furnace roof, rather than three, and a smaller one in
the furnace floor. DC arc furnaces require slightly less energy for heating than AC designs due
to better heat transfer and less radiant heat loss (Center for Metals Production 1987). In
operation, the top electrode is covered by foamy slag to increase the power input and reduce
electrode consumption. The technology is used in Europe and Japan; in the US, use is mainly
by one company, Nucor. Existing AC units can be modified for DC operation, but new
installations that incorporate scrap preheating systems and other energy saving features
provide substantial advantages over modification.
DC arc furnaces have several advantages over AC furnaces: 1) more even distribution of
temperatures due to the central location of the electrode, 2) lower rate of refractory furnace
lining wear due to less arcing to the side walls, 3) increased bath stirring, 4) less electrical
network disturbance (Center for Metals Production 1987), and 5) a lower rate of electrode
consumption. Reduced electrode consumption is important from an electrode cost perspective,
as well as reduced downtime.
Thermomechanical Processing
Regardless of whether steel is made by BOF, EAF, or any of the specialty processes discussed
earlier, the ingot or the continuous cast steel product generally has to be thermomechanically
treated to achieve the desired microstructures and mechanical properties for usage. The plate,
sheet, bar, and pipe products undergo different rolling, annealing, forging, and pickling
treatments dictated by the steel composition and properties desired.
Process Controls
At present, thermomechanical treatments are predominantly based on empirically developed
technical information and the practice is largely dictated by tradition and accomplished by a
trial and error approach. The time and temperature sequence for an annealing line is set, based
on trial and error, to achieve a given hardness. The systems have almost no intelligent
processing (with feedback) to obtain microstructural control in the sheets. As a result, the steels
are normally over annealed (with regard to time at temperature). This is especially inefficient in
processes where the continuous annealing lines operate at 50-200 m/min. Significant advances
in thin strip casting have been made in Japan and the process, if implemented, can result in
reduction in intermediate rolling steps and lower energy consumption, a decrease in industrial
scrap generation, and lower unit cost of the product.
Hot Connection
Depending on plant layout, moving forms from the continuous casting operation to the rolling
operation with minimal cooling may provide energy savings. Reheat furnaces are generally
employed to bring the cast forms back to rolling temperature. Adjusting plant layout to move
the cast semi to the rolling operation at a temperature of 600° to 800°C can result in an energy
savings of 0.4 to 0.6 GJ/tonne semi based on the IISI reference plant defined in 1982 (Etienne
and Irving 1985). A Dutch study based on a transport or connection temperature of 700°C
estimated an 18% reduction in energy for reheating, for a savings of 0.3 GJ/tonne of crude steel
(De Beer et al. 1994).
D-2.28
DRAFT
6/10/97
D-2.6.2 Technology Examples beyond 2010 Requiring Further R&D
Ironmaking
Activity will be largely dictated by the viability of different ironmaking processes that are under
development. R&D effort should focus on developing a process scheme that incorporates both
ironmaking and steelmaking into one system with thin strip casting as a final product. The
effort should incorporate a coal-based reductant process which can be coupled with
steelmaking operations and simultaneously produce power in a combined cycle that includes
both gas and steam turbines
Steelmaking
Steelmaking processes currently utilize computer technology primarily to implement
prespecified procedures in a timely manner. There is very little feedback in these systems to
either enhance process efficiency or improve the product quality. Key process parameters
should be identified so that interactive logic and high-speed computer systems can be used to
control/modify/maintain these process parameters to obtain a quality product. Such an
intelligent-processing approach is essential for the production of so called "cleaner steel" with
low residual elements.
Thermomechanical Processing
The development of sensors for all aspects of process control and for enabling process changes
with a feedback system is essential for improving process efficiency and optimizing different
stages of the melting, casting, thermomechanical processing, and final heat treatment.
Applications of novel ideas and approaches need to be explored and transfer of technologies
available from defense and chemical processing industries may be a fruitful approach.
D-2.6.3 References
1993. "A Revolution in the Making?" World Coal, November, pp. 26-32.
Burgmann, W. and B.B. Pelts. 1995. "Scrap preheating shaft furnaces - development and
results," Steel Times International, 19(1):16-17, Jan.
Carmichael, I.F. 1992. "An Introduction to Blast Furnace Coal Injection," Iron & Steelmaker,
19(3):67-73.
Center for Metals Production. 1987. Technoeconomic Assessment of Electric Steelmaking Through
the Year 2000, EPRI EM-5445, Electric Power Research Institute, Palo Alto, CA.
De Beer, J.G., M.T. van Wees, E. Worrell, and K. Blok. 1994. The Potential of Energy Efficiency
Improvement in the Netherlands up to 2000 and 2015, Utrecht University, Utrecht, Netherlands.
Department of Energy. 1987. A Guide to Investment Appraisal of Energy Efficiency Projects in the
Steel Industry, Energy Efficiency Office, U.K.
Etienne, A. and W.R. Irving. 1985. "The Status of Continuous Casting," in Institute of Metals,
1985, Continuous Casting '85, conference proceedings May 22-24, 1985, London, UK.
D-2.29
DRAFT
6/10/97
Gardner, D.T., D.M. Hamblin, R.K. Clark, G.D. Pine, and D.M. Smith. 1996. An Assessment of
Blast Furnace Coal Injection in North America, Gas Research Institute, Chicago, IL.
Haissig, M. 1994. "The d-c shaft furnace," Iron and Steel Engineer, May, pp. 25-27.
Hogan, W.T., and F.T. Koelble. 1996. "Fewer blast furnaces, but higher productivity," New
Steel, November.
Metals Industry News. 1996. Vol. 13, No. 4, p. 3.
Nilles, P.E. 1996. "Alternative Technologies in Iron and Steelmaking," Metallurgical and
Materials Transactions B, Vol. 27B, p. 541.
Scheidig, K. 1995. "Hot metal from oxygen cupola furnaces as an alternative charge material
for electric arc furnaces," Stahl und Eisen, 15 May, 115(5): 59-64.
Steel Times International. 1997. Vol. 21, No. 1, p. 24.
D-2.7 TECHNOLOGY EXAMPLES FOR METAL CASTING
(Prepared by Jim Chang, Energy Systems Division, Argonne National Laboratory.)
Metal casting is not a single industry segment according to the SIC system, but covers a diverse
group of products and metals. Products range from cast pipes, motor vehicle components, and
tools. Iron, steel, aluminum, copper and zinc are all metals used by the industry. The industry
is labor intensive, with many small plants; four out of five have fewer than 100 workers. Over
half of the energy use is in melting metal. Technologies which improve the melting stage or
reduce waste/recasting have important energy implications.
D-2.7.1 Technology Examples Available before 2010
The technologies described below can lower energy use and are not currently in widespread use
in the metal casting industry.
Computer-Aided Casting Design
Rapid advances in computer modeling of the casting process and in computer-aided drafting of
castings have led to an increased use of computers in working foundries, and hence, an
increased need for integration in casting design systems. Increased integration in the casting
design functions is needed to realize the full potential of the computer for improving both
casting designs and production lead time.
Two kinds of information are produced by the casting analysis and simulation function: (a)
results predicting the outcome of casting the current design; and (b) the processing parameters
for the casting process, if the casting design appears sound. The predictive results allow the
foundry engineer to evaluate the filling of the mold cavity, the potential for defects such as
D-2.30
DRAFT
6/10/97
porosity in the casting to occur, the sequence of solidification, and the time for complete
solidification.
Benefits have already been realized based on the proportion of parts being cast with the
software (Hickie 1996, Cooley 1996). An average of 25% improvement was found in the
casting yield among the PC and workstation users. Overall, the mean improvement was at least
25%, regardless of either performance criteria or computer platform (Lensen 1996, Lensen et al.
1996).
Optimized Coreless Induction Melting
Most foundries can dramatically reduce a major portion of their energy costs without spending
a single capital equipment dollar, simply through proper optimization of their induction melting
equipment. It has been estimated that foundries are only operating their induction furnaces at
50-80% of their optimal efficiency (Horwath et al. 1996), wasting valuable energy dollars daily.
For instance, a foundry melting 1000 tons/month could easily reduce its monthly melting costs
by $5/ton simply by altering its melting practice.
Four major variables were considered the most important in determining power required for
melting: (1) charge makeup, (2) furnace cover, (3) power application, and (4) furnace condition.
These variables were found to be significant in determining the power consumption during
coreless induction melting. In some cases, optimal material use resulted in higher energy use
(22% more) and use of a furnace cover reduced energy consumption by 12%. Furnace condition
(i.e., hot, medium, or cold) interacts with the charge to significantly affect energy consumption.
Maintaining the furnace in hot condition resulted in 15.4% less energy consumption for melting
the charge (Horwath et al. 1996). A better recognition of the impact of these variables will
trigger operational changes to better control the melt power consumption.
D-2.7.2 Technology Examples beyond 2010 Requiring Further R&D
The R&D issues/opportunities described below are critical to the development of the metal
casting industry and must be addressed to achieve further energy savings after 2010.
Electromagnetic Casting
An electromagnetic field in a casting is brought about by an inductor that produces a time-
varying magnetic field. The field induces eddy currents in the liquid metal that, together with
the field, give rise to an EM force (Lorentz force) that stir and contain the liquid metal in the
casting. Two examples are discussed below:
EM Stirring: In continuous casting, the solidification process can be improved by EM stirring.
EM stirring can produce better metallurgical results, improve internal quality of the casting, and
even reduce meniscus instability and surface defects (Beitelman and Mulcahy 1994, Chang et al.
1995). Therefore, a study of EM stirring is needed to design and fabricate EM stirrers, optimize
the existing casting processes and improve the quality of products.
The benefit from EM stirring will be reduced wastage per cast. Thus, less metal will need to be
melted and poured per cast part. As a minimum, we expect that the present average yield of
55% for the industry will increase to 65%, a saving of 130,000 tons per year, with an associated
energy savings of 25 trillion BTUs per year (American Foundrymen's Society 1995).
D-2.31
DRAFT
6/10/97
EM Confinement: In the presently dominant sheet-forming process, thick steel slabs are cast
and then hot-rolled. The hot-rolling stage is very capital- and energy-intensive and adds greatly
to the cost of the final product. Twin-roll casting with EM confinement has the potential to cast
thin sheets by eliminating the hot-rolling stage and it gives the sheet product an enormous
economic advantage over products made by competing methods (Saucedo and Blazek 1994,
Blazek et al. 1994). Because there is no contact with liquid metal, EM confinement bypasses
fundamental problems of solid dams and provides benefits that include energy conservation,
cost savings, and enhancement of the competitiveness of US industry in the world market
(Argonne National Laboratory 1995, Chang et al. 1996).
Clean Metal Casting
It is necessary to develop a technology for clean metal processing that is capable of consistently
providing a metal cleanliness level fit for metal casting. The technology to economically produce
sound castings and lower energy use will be important for the survival of many
steel/iron/aluminum foundries (American Foundrymen's Society 1995, Cast Metal Coalition
1997). The technology is expected to improve casting product quality by (1) removing or
minimizing oxide defects and allowing the production of higher integrity castings, (2) reducing
the incidence of macroinclusions in castings, and (3) reducing reoxidation of the metal during
pouring. The required technology is summarized below (DOE 1996a, b):
Use of inert and reactive gases for reducing hydrogen and inclusions (oxides,
carbides), and minimizing hydrogen absorption.
Use of alloying elements and cover media to reduce melt oxidation.
Reduced pressure techniques.
Development of specific apparatus and procedures for measuring air entrainment
during pouring.
Phase separation technology including knowledge of sedimentation, filtration, and
fluxing techniques.
Metal Penetration in Iron and Steel Castings
Penetration defects cost American iron and steel foundries about $65 million per year.
Penetration in castings is caused by mechanical pressure of metal forcing itself into the sand
mold and most penetration defects are caused by pool casting design and poor molds. In the
past years, it has been found that the probability of penetration occurring in cast iron increases
with 1) higher pouring temperatures, 2) higher silicon and carbon levels, 3) higher casting
heights, and 4) faster pouring speeds (Lane et al. 1996).
Further research is underway on steel castings and, while common principles apply to the two
metal groups, there are some important differences, especially regarding the conditions under
which chemical penetration can occur. However, prevention of penetration in both iron and
steel is a combination of mold practice and casting design. If both are done correctly, nearly all
cast penetration problems can be eliminated. Research in this area should be planned to
establish methodology to determine interfacial gas composition, develop computer models of
liquid metal oxidation, and determine effects of iron/steel composition at the mold/metal
interface (DOE 1995).
D-2.32
DRAFT
6/10/97
D-2.7.3 References
American Foundrymen's Society. 1995. Foundry Industry Research Plan.
Argonne National Laboratory. 1995. Tech Transfer Highlights, Vol. 6, No. 1, pp. 11.
Beitelman, L. and J. A. Mulcahy. 1994. "Flow Control in the Meniscus of Continuous Casting
Mold with an Auxiliary A.C. Magnetic Fields," International Symposium on Electromagnetic
Processing of Materials, EPM'94, Iron and Steel Institute of Japan, pp. 235-241.
Blazek, K. E., H. G. Gerber, and I. G. Saucedo. 1994. "Application of Alternating Magnetic
Fields for Edge Containment in Strip Casting," International Symposium on Electromagnetic
Processing of Materials, EPM'94, Iron and Steel Institute of Japan, pp. 197-202.
Cast Metal Coalition. 1997. Technology Roadmap for the Metalcasting Industry.
Chang, F. C., J. R. Hull and L. Beitelman. 1995. "Simulation of Fluid Flow Induced by
Opposing AC Magnetic Fields in a Continuous Casting Mold," Process Technology Conference
Proceedings, Vol. 13, Iron and Steel Society, PP. 79-88,.
Chang, F. C., J. R. Hull, Y. H. Wang, and K. E. Blazek. 1996. "Computer Modeling of
Electromagnetic Fields and Fluid Flows for Edge Containment in Continuous Casting," ASME
PVP Fluid-Structure Interaction, Vol. 337, pp. 203-213.
Cooley, E. M. 1996. "Computer Models Give Accurate Iron Melting Method Economics,"
Modern Casting, September, pp. 34-36.
Hickie, J. 1996. "Can You Justify the Simulation Investment? Ask Sivyer Steel," Modern Casting,
September, pp. 32-33.
Horwath, J. A., T. Klemp III, and J. M. Svoboda. 1996. "Variables Identified for Optimal
Coreless Induction Melting", Modern Casting, May, pp. 33-35.
Lane, A. M., D. M. Stefanescu, T.S. Piwonka, and R. Pattabhi. 1996. "Understanding Metal
Penetration in Green Sand: Cast Iron," Modern Casting, October, pp. 54-55.
Lensen, D. H. 1996. "Survey Provides Profile Casting Design Software Use", Modern Casting,
September, pp. 29-31.
Lensen, D. H., C. Beckermann, and G. W. Fischer. 1995. "Implementation Issues for Computer-
Aided Casting Design", Summary Report to American Metalcasting Consortium.
Saucedo, I. G. and K. E. Blazek. 1994. "Development of an Electromagnetic Edge Dam for
Twin-Roll Casting," METEC-94, PP. 457-462.
U.S. Department of Energy. 1995. Metal Casting - Annual Report Fiscal Year 1995, Washington,
D.C.
U.S. Department of Energy, Office of Industrial Technologies. 1996a. Clean Metal Casting -
Aluminum, Washington, D.C.
D-2.33
DRAFT
6/10/97
U.S. Department of Energy, Office of Industrial Technologies. 1996b. Clean Cast Steel
Technology, Washington, D.C.
D-2.8 TECHNOLOGY EXAMPLES FOR CROSSCUTTING TECHNOLOGIES
(Prepared by John Molburg, Information and Decision Sciences Division, Argonne National
Laboratory.)
There are a variety of crosscutting technologies, i.e., those that are not process or product
specific, in operation in industry. Some include the lighting and HVAC examples that are in
common with commercial applications and are not discussed here (see chapter 2). Others
include sensors and computer control systems which have a common underlying technology, but
have a variety of configurations and benefits depending on the industry. Motor systems, on the
other hand, encompass a wide range of industrial applications are discussed here as an
example of non-process specific efficiency applications.. The second major type of efficiency
application is cogeneration, sometimes also referred to as combined heat and power (CHP).
Cogeneration is the joint production of useful steam and electricity, either for on-site use or
sales back the to electric grid. This section also discusses cogeneration as an energy efficiency
option.
D-2.8.1 Technology Examples Available before 2010
Electric Motor Applications
Energy use by Electric Motor Systems Systems employing electric motors convert only a portion
of the energy consumed into useful mechanical work. This fraction of useful work is the system
efficiency. To understand the energy conservation opportunities presented by these
applications, it is essential to trace the energy conversion processes throughout the system,
which includes power supply and controls, electric motor, power transmission, and the load
(the driven equipment).
D-2.34
DRAFT
6/10/97
Table D-2.8.1 shows a schematic of an electric motor application and lists some of the factors
associated with each component that affect system efficiency.
D-2.35
DRAFT
6/10/97.
Table D-2.8.1 Efficiency Losses in Electric Motor Applications
Component
Energy Efficiency Issues
Power Supply
Voltage unbalance (uneven voltage between phases) can increase motor
+
losses and damage motors.
Deviations from design voltage can reduce motor efficiency and motor
torque even if balance is maintained between phases.
Voltage
Harmonics (deviations from simple sinusoidal voltage form) can reduce
motor efficiency and adversely affect mechanical operation.
Adjustable speed drives can introduce harmonics.
Motor
Controller
Power losses in motor feed cables can lead to low voltage at the motor.
and Power Feed
Low voltage can reduce efficiency.
High starting currents (five to seven times normal operating currents)
may push the limits of feeders, resulting in low voltage.
A high power factor can increase losses in distribution lines and
transformers and can lead to undervoltage and the associated problems
of low motor torque and efficiency.
Electric Motor
Motor energy losses include electrical resistance losses, magnetic field
losses, mechanical (frictional) losses, and stray losses due largely to
minor design compromises and manufacturing irregularities. These are
addressed by high efficiency motors.
Motor efficiency is often reduced by rewinding.
Energy efficient motors are typically 1% to 5% more efficient than
standard motors for large motors. For fractional HP motors the
difference may be 40%.
Transmission
Drive train efficiency, including belts, gears, etc., can be as high as 95%,
but may be below 50%.
Helical gears are more efficient than worm gears in most applications.
Helical gear efficiency drops at part load applications.
About 1/3 of drives use belts and pulleys. These are typically 90% to
99% efficient if properly selected and installed.
Load
Oversized motors are very frequently selected. Motor efficiency
declines rapidly at loads below 40% of rated load. About 20% of
motors over 5 HP are in this category.
Fans and pumps account for most motor power consumption. Optimal
selection of fans and pumps and associated control systems can reduce
motor drive requirements substantially. Use of variable speed controls
rather than throttling is a particularly important strategy.
An overview of the distribution of motors and energy consumption by motor size is essential
for targeting an efficiency program. Based on an assumed 3% growth rate in motor population
since 1977, ACEEE (Nadel, Shepard et al. 1992) estimates the current population of motors
over 1/6 HP at about 1 million units. Motors of less than 1 HP constitute 90% of the
population and consume about 15% of the energy. Conversely, motors exceeding 1 HP, though
only 10% of the motor population, consume 85% of the electrical energy consumed for motor
drive. Figure D-2.8.1 provides a summary of the population and energy use estimates by motor
size classification. In fact, motors larger than 50 HP consume about 60% of motor drive power
consumption. This has led ACEEE to conclude that most of the potential for energy
1
One of the few comprehensive surveys of U.S. motor populations was completed by A.D. Little in 1977.
D-2.36
DRAFT
6/10/97
conservation lies in the large motors. Given the size of the embeded motor population, this
seems fortunate for planning an energy conservation strategy. However, as noted below, the
replacement of standard motors with high efficiency motors results in a far higher percentage
efficiency improvement for fractional HP motors than for large motors. Therefore, at least for
the motor replacement strategy, the fractional HP motors are still an important target for
conservation programs.
Figure D-2.8.1 Comparison of Motor Population and Energy Use by Horsepower (Nadel,
Shepard et al. 1992 Fig. 6-1)
900
1000
600
500
75
100
400
15
10
5
300
3
200
1
0.2
100
0.1
0
1 5
1/6
1
125
-
5.1
2Q
50
-
125
Horsepow
Energy Efficient Motors
As noted above, energy efficient motors (EEMs) present only one of several important options
to reduce energy consumption by motor systems. In fact, the direct substitution of EEMs for
equivalent size standard motors for the existing population characterized in Figure D-2.8.1
would result in about a 7% reduction in power consumption. This estimate is based on the
assumption that the current motor population efficiency is at a level representative of new
standard motors in the respective size classes. While the actual efficiency of older motors is
probably below the efficiency of current standard units, high efficiency motors have been
available for two decades and are included in the current motor population². The resulting
errors tend to cancel. For this hypothetical comprehensive replacement program, the total
savings is 109 Twh/yr out of the total motor power consumption of 1570 Twh/yr for the
current motor population.
High efficiency or energy efficient motors are more efficient than standard motors because they
reduce one or more of the four types of losses associated with motor operation: electrical losses
(rotor and stator losses), magnetic losses (core losses), mechanical losses (friction and
windage), and stray losses. Electrical losses are due to the familiar conversion of electrical
power to heat due to current flow through conductors of non-zero resistance. These are known
2 Several sources cited by ACEEE (Nadel, Shepard et al. 1992) suggest that about 3% of current motors are EEMs
on a horsepower-weighted basis.
D-2.37
DRAFT
6/10/97
as I²R losses because they are proportional to the resistance, R, and to the square of the current,
I. These electrical losses are controlled by reducing conductor resistance through increased
conductor wire size.
Magnetic or core losses result from the build-up and break-down of magnetic fields in the
laminated iron cores in response to currents. Hysteresis and eddy current losses result. While
these are small compared to the electrical losses, considerable effort has been invested in new
magnetic materials to reduce similar core losses in transformers. These new materials, along
with larger cores and thinner laminations can reduce magnetic losses. Magnetic losses are
roughly equivalent to rotor and to stator electrical losses at very low load, but are far less than
electrical losses at full load.
Frictional losses result from bearing friction and from windage, the consumption of motor power
for intentional and inadvertent air movement due to motor rotation. These are nearly
independent of load, depending primarily on rotational speed. Changes in motor frame and fan
design can reduce windage losses.
An important advantage of energy efficient motors is that they maintain (or increase) their
efficiency advantage at part load. This is particularly important in view of the prevalence of
motor oversizing, as discussed below.
Table D-2.8.2 provides some indication of the relative efficiencies of standard and high
efficiency motors. Since the term "high efficiency" is vague, the industry has made some effort
to specify requirements for motors carrying that designation. Because of manufacturing and
materials variations, motor efficiency can vary considerably and must be described by a
statistical distribution applicable to a given motor. Motor efficiency is nearly normally
distributed about a mean or nominal efficiency value. The standards specify that the minimum
efficiency at full load and rated voltage must be close to the nominal efficiency for that motor.
Standards in place in 1991 required that the losses associated with the minimum efficiency be
within 20% of the losses associated with the nominal efficiency. Thus, for a given design to
claim 95% efficiency (5% loss), any particular motor of that design must not have losses greater
than 1.2x5% or 6% (94% efficiency). A more restrictive class, with maximum losses 10% greater
than nominal losses, has also been established.
Table D-2.8.2, Hypothetical Savings from Comprehensive Motor Replacements
Horsepower
Standard
High
Efficiency Energy Savings (TWh/yr)
Efficiency
1/6 1
0.55
0.75
60
1.1 5
0.76
0.84
15
5.1 20
0.87
0.91
4
21 50
0.89
0.93
7
50 125
0.92
0.95
11
> 125
0.94
0.96
12
Source: Efficiency values from manufacturer's data as reported in (Nadel, Shepard et al. 1992
Table 2-3).
In addition to the statistical allowance for variation, a minimum criteria for high efficiency
motors has also been adopted by the National Electrical Manufacturer's Association (NEMA).
The minimum requirement is shown in Figure D-2.8.2 for one common motor type.
D-2.38
DRAFT
6/10/97
Figure D-2.8.2, Minimum Efficiency Criteria for High Efficiency Motors
95
90
Efficiency
85
80
75
0
50
100
150
200
Horsepower
Source: NEMA MG 1-1987, TEFC, 4-pole, 1800 RPM as cited in Resource Dynamics Corp.
(1992).
Efficiency Opportunities in Power Supply, Controller, and Feed
Alternating current or AC motors consume about 90% of the power provided for motor drive.
In addition, the market for AC motors is growing at the expense of DC motors. DC motors
offered the advantage of economical speed control and high starting torque. As recently as
1987, about 50% of motors over 1 HP sold were DC motors, though this corresponds to only
2.5% of the market because of the large number of fractional HP motors sold (Resource
Dynamics Corporation 1992). ACEEE notes that the development of economical speed control
for AC motors has reduced the DC motor market to less than 5% (Nadel, Shepard et al.
1992)p.32. While this appears to be inconsistent with the 1987 sales, the ACEEE data may
include small DC motors for portable power applications. In any case, AC motors are
dominant both in power consumption and in population. Therefore, we have addressed power
supply concerns as they pertain to AC motors.
AC motors are of two basic types: single phase and polyphase (generally three phase). While
fractional HP motors essentially all single phase, sales of integral HP motors are fairly equally
split between single and polyphase units. A three phase motor simply has three sets of
windings, each connected to a separate AC line. The three windings are offset to improve
uniformity of the magnetic forces exerted on the rotor. Two power characteristics are important
for optimum motor performance. The voltage must be uniform in all three phases and the
voltage wave form must be smoothly sinusoidal.
Unfortunately, the voltage can vary substantially between the three phases of a polyphase
motor. This can result from a plant electrical layout that imposes more load on one phase than
on the others, which leads to a greater voltage drop in one phase before it reaches the motor. A
modest phase voltage unbalance can severely impact motor performance. ACEEE notes that a
2% unbalance in phase voltage can result in a 25% increase in losses (Nadel, Shepard et al.
1992, P. 66). This would reduce the efficiency of a 90% efficient motor to 87.5%. Unbalanced
D-2.39
DRAFT
6/10/97
phase voltage also results in reduced motor torque, requiring derating to protect the motor from
over heating. Since unbalanced phase voltage generally reflects deficiencies in plant electrical
layout, the cure lies in modifications to plant wiring, including conductor sizing, redistribution
of plant loads, and proper overcurrent protection.
AC motors are ideally suited to operation with smooth sinusoidal input voltage. However,
certain loads cause distortions in the voltage waveform that can affect motor operation. These
distortions can result in reduced or pulsating torque, motor vibration, increased losses,
overheating, and damage to electronic controls. Among the loads that can cause these
distortions or harmonics are adjustable speed drives (ASD). If adjustable speed drives are
used on a substantial fraction of total plant load and particularly on large motors, great care
should be taken to properly install the ASD. Energy efficient motors are less susceptible to
operating problems associated with harmonics, providing additional incentive for EEM
installation.
AC and DC motors are also adversely affected by low voltage. That is, even if the voltage is
balance across phases, it may be below the motor design specification because of electrical
power losses in the plant distribution wiring or motor feed wires. While voltage deviations of
10% are generally acceptable, larger deviations can result in reduced efficiency and reduced
service life. The solution is to provide adequate wire size for the distribution and feed cables
that service motors. Electrical code standards for wire gauge are based on safety concerns,
primarily limiting I'R heating losses to prevent risk of fire. However, larger wire sizes may be
recommended by overall economics, since increased wire size reduces electrical losses. If these
reduced losses also improve motor efficiency and operation, the economics of increased wire
size are further improved. However, increasing wire size in existing plants may be difficult or
uneconomic because of constraints imposed by existing conduits.
Power Transmission Efficiency Issues
Mechanical transmission systems are generally required to transfer the motor torque to the
driven load. In most cases the motor speed must be matched to the desired load speed by the
intervention of a drive train of gears, pulleys, or both. About one third of motor applications
employ belt drive systems, which are highly efficient if properly selected and installed. V-belts
are about 90% efficient, with losses resulting from friction on pulleys, slippage, and belt flexing.
Some improvement in efficiency is possible through the use of notched v-belts, which are more
flexible than standard v-belts. Further improvement is possible with thin synchronous belts
that have cogs or teeth that engage mating teeth in the pulley. Belt drive efficiency up to 99% is
possible with such systems.
Gear-based transmission systems are of two basic types, worm gears and helical gears. Worm
gears provide inexpensive means of large speed reductions for power applications below about
15 HP. However, worm gears result in high friction losses, particularly for large reduction
ratios. Worm gear efficiency is typically 70% to 80%. Helical gear systems are more efficient
and are more economical for higher power applications. Helical gear efficiency is 90% to 96%.
For high reductions, efficiencies of both gear types are greatly reduced. A worm gear operating
at a reduction of 60:1 will have an efficiency of 50% to 65%. In contrast, a helical gear train at
that reduction ratio remains over 90% efficient.
The efficiency of helical reducers drops slightly at part-load down to about 20% of rated load.
Below that the efficiency drops precipitously, emphasizing the importance of matching
equipment to load, as discussed for motors below.
D-2.40
DRAFT
6/10/97
One of the most important loads, pumps, are most often directly coupled to the motor via
flexible or rigid couplings between the motor and pump shafts. These generally result in little
efficiency loss, though failure to properly align the shafts can result in reduced efficiency and
accelerated bearing wear, which leads to higher frictional losses.
Motor and Load Issues
When the load presented to an electric motor is below the rated load of the motor, the motor
will draw less current and perform less work. For instance, the motor operating an air
compressor will draw more current as the pressure builds in the storage tank. Since both power
output and power input are reduced in part load operation, these changes do not reflect a
precipitous decline in efficiency (the ratio of output to input). However, some change in
efficiency does normally accompany part load operation. Peak efficiency is normally achieved
at about 75% of full load. As the load increases to full rated load, a slight decline in efficiency
(1% to 2%) occurs. At loads exceeding rated load some additional decline is experienced. The
more troubling effect is the rapid decline in efficiency at part load, particularly below 40% of
rated load. A 10% decline in efficiency (from 85% to 75%) is representative of operation at
25% of rated load. It has been estimated that one third of motors are operated below 50% of
rated load (Nadel, Shepard et al. 1992, P. 162).
Proper sizing of motors is not an easy task. As in the example of the compressor, loads may
vary over a broad range during normal operation. In addition, transient loads must be taken
into account, and the aging of equipment changes load. For instance, the buildup or scale in
piping systems increases pumping load. Finally, it may be prudent to design a system for
growth. In addition there is a tendency to oversize motors by the application of formal or
informal safety factors. A very common practice is to oversize motors in ventilation systems.
Motors in owner or consultant designed ventilation systems frequently operate below 35% of
rated load (Nadel, Shepard et al. 1992, p. 163).
Fans and pumps are the most common motor loads, constituting over 40% of industrial motor
loads (Resource Dynamics Corporation 1992). As noted above, it is common to oversize
motors for these applications. However, it is also common to design fan and pump
applications that consume more energy than is actually required to accomplish the fluid
movement task at hand. Power consumption by a fan or pump is proportional to the product
of flow rate and pressure drop. The pressure drop is the pressure loss caused by friction as the
fluid flows through its conduit. However, the pressure drop is proportional to the square of the
flow rate. Therefore, the power consumed is proportional to the cube of the flow rate. For
instance, a flow rate reduction from 1 unit to 0.8 units (20% reduction) results in a power
requirement of about one half, (0.8)³, of that at full load. Thus, substantial savings may be
possible if flow rates can be reduced in a given process, say in building ventilation. The recent
switch to smoke free offices has reduced the need for fresh air, suggesting a change in ventilation
standards may be appropriate in some older buildings.
Related issues arise in consideration of fan and pump design. The efficiency of fans and pumps
are the ratio of the theoretical power required to maintain a given flow rate against a given
pressure drop to the actual power required by a particular fan or pump. The efficiency of this
equipment is highest within a narrow operating range of pressure and flow. Outside of this
range, the efficiency can drop substantially. Therefore, it is important to match a fan or pump
to a particular set of operating requirements. It is common practice to adjust pump
performance by reducing the impeller diameter. this too is accompanied by reduced efficiency.
D-2.41
DRAFT
6/10/97
As an alternative, pump speed can be varied to adjust flow rate. This can allow operation at
higher efficiency while matching load. The use of speed control on fans can be equally
important, permitting operation near optimum efficiency over a range of flow conditions.
Current practice relies on throttling (restricting flow by valves or dampers) to achieve flow
control. This is obviously accompanied by substantial friction losses and, less obviously, by
operation of fans and pumps at sub-optimal efficiency.
The development of economical adjustable speed drives for AC motor systems may provide the
largest potential efficiency opportunity. On average, adjustable speed drives result in 15% to
40% reduction in energy consumption, and only about 10% of appropriate opportunities for
adjustable speed drives have been exploited (Resource Dynamics Corporation 1992).
Cogeneration
An important strategy for reducing greenhouse gas emissions is to implement improvements in
the efficiency of energy conversion processes. Fossil fuel is used at many industrial sites to raise
steam for process heating and other process requirements. Depending on the relative electricity
demand (steam to electricity ratio, kWh/Btu) and the price of electricity, such industrial sites
may be candidates for the cost effective application of cogeneration. However, NO, emission
regulations may be a major impediment to the expanded adoption of industrial cogeneration.
In a cogeneration system, the thermal energy generated by the combustion of fossil fuels is first
used to generate electricity before it is used to provide process steam. The advantage of such
an approach is that little additional fuel is required for the electricity generation over that
required for simple steam production. Thus, the efficiency for use of the thermal energy
available from the fuel is higher than with separate electricity generation and steam production,
and the net green house gas emissions can be reduced by the application of cogeneration. There
are two common alternatives for the power generation side of cogeneration: a Rankine cycle
(steam turbine) with turbine exhaust steam directed to meet process requirements and a
Brayton cycle (gas turbine) with steam raised in a heat recovery steam generator (HRSG) using
the hot turbine exhaust gas.
The economics of a cogeneration system depend on the steam requirements of the plant and can
vary tremendously, depending on the industry. Local steam load, need for backup power
charges, and on site electrical equipment may be required. Based on a typical boiler
configuration, the gas turbine with HRSG appears to be the most cost effective application. In
1994, manufacturing cogeneration accounted for 158 billion kWh. A relative penetration
cogeneration index shows that paper and chemicals have much higher than average
cogeneration. The penetration index developed shows substantial variation in penetration by
industry and by state. (Boyd, Molburg and Thimmapuram, 1996)
A new generation of advanced turbine systems (ATS) is likely to be commercially available
before 2010. Estimates of a 22% lower CO2 emission relative to the best available gas-fired-
combined cycle central station electric generating system have been made for 15MW industrial
ATS projected to be commercially available by the year 2000 (Major and Davidson 1997).
D-2.8.2 References
Elliot, R. N. 1995. "Energy Efficiency in Electric Motor Systems," American Council for an
Energy-Efficient Economy, Washington, DC.
D-2.42
DRAFT
6/10/97
Nadel, S., M. Shepard, et al. 1992. Energy Efficient Motor Systems: A Handbook on Technology,
Program, and Policy Opportunities, American Council for an Energy-Efficient Economy,
Washington DC.
Resource Dynamics Corporation. 1992. Electric Motors: Markets, Trends, and Applications,
Electric Power Research Institute, Palo Alto, CA.
D-2.43
DRAFT
6/10/97
APPENDIX E
APPENDIX E-1 SUPPLEMENTAL TABLES
Table E-1.1 Standard. Technology Matrix for Cars
Vehicle Technology
Fractional
Incremental
Incremental
Incremental
Incremental
First Year
Fractional
Fuel
Cost
Cost
Weight (lbs)
Weight
Introduced
Horsepower
Efficiency
($1990)
($/unit wgt)
(lbs/unit wgt)
Change
Change
FRONT WHEEL DRIVE
0.06
160
0
0
-0.08
1980
0
UNIT BODY
0.04
80
0
0
-0.05
1980
0
MATERIAL SUBSTITUTION II
0.033
0
0.6
0
-0.05
1987
0
MATERIAL SUBSTITUTION III
0.066
0
0.8
0
-0.1
1997
0
MATERIAL SUBSTITUTION IV
0.099
0
I
0
-0.15
2007
0
MATERIAL SUBSTITUTION V
0.132
0
1.5
0
-0.2
2017
0
DRAG REDUCTION II
0.023
32
0
0
0
1985
0
DRAG REDUCTION III
0.046
64
0
0
0.05
1991
0
DRAG REDUCTION IV
0.069
112
0
0
0.01
2004
0
DRAG REDUCTION V
0.092
176
0
0
0.02
2014
0
TCLU
0.03
40
0
0
0
1980
0
4-SPEED AUTOMATIC
0.045
225
0
30
0
1980
0.05
5-SPEED AUTOMATIC
0.065
325
0
40
0
1995
0.07
CVT
0.1
250
0
20
0
1995
0.07
6-SPEED MANUAL
0.02
100
0
30
0
1991
0.05
ELECTRONIC TRANSMISSION
0.005
20
0
5
0
1988
0
ELECTRONIC TRANSMISSION II
0.015
40
0
5
0
1998
0
ROLLER CAM
0.02
16
0
0
0
1987
0
OHC 4
0.03
100
0
0
0
1980
0.2
OHC 6
0.03
140
0
0
0
1980
0.2
OHC 8
0.03
170
0
0
0
1980
0.2
4C/4V
0.08
240
0
30
0
1988
0.45
6C/4V
0.08
320
0
45
0
1991
0.45
8C/4V
0.08
400
0
60
0
1991
0.45
CYLINDER REDUCTION
0.003
-100
0
-150
0
1988
-0.1
4C/5V
0.1
300
0
45
0
1998
0.55
TURBO
0.05
500
0
80
0
1980
0.45
ENGINE FRICTION REDUCTION
0.02
20
0
0
0
1987
0
ENGINE FRICTION REDUCTION I
0.035
50
0
0
0
1996
0
ENGINE FRICTION REDUCTION III
0.05
90
0
0
0
2006
0
ENGINE FRICTION REDUCTION IV
0.065
140
0
0
0
2016
0
VVTI
0.08
140
0
40
0
1998
0.1
VVTII
0.1
180
0
40
0
2008
0.15
LEAN BURN
0.1
150
0
0
0
2012
0
TWO STROKE
0.15
150
0
-150
0
2004
0
TBI
0.02
40
0
0
0
1982
0.05
MPI
0.035
80
0
0
0
1987
0.1
AIR PUMP
0.01
0
0
-10
0
1982
0
DFS
0.015
15
0
0
0
1987
0.1
OIL 5W-30
0.005
2
0
0
0
1987
0
OIL SYNTHETIC
0.015
5
0
0
0
1997
0
TIRES I
0.01
16
0
0
0
1992
0
TIRES II
0.02
32
0
0
0
2002
0
TIRES III
0.03
48
0
0
0
2012
0
TIRES IV
0.04
64
0
0
0
2018
0
ACCT
0.005
15
0
0
0
1992
0
ACC II
0.01
30
0
0
0
1997
0
EPS
0.015
40
0
0
0
2002
0
4WD IMPROVEMENTS
0.03
100
0
0
-0.05
2002
0
AIR BAGS
-0.01
300
0
35
0
1987
0
EMISSIONS TIER I
-0.01
150
0
10
0
1994
0
EMISSIONS TIER II
-0.01
300
0
20
0
2003
0
ABS
-0.005
300
0
10
0
1987
0
SIDE IMPACT
-0.005
100
0
20
0
1996
0
ROOF CRUSH
-0.003
100
0
3
0
2001
0
INCREASED SIZE/WT
-0.033
0
0
0
0.05
1991
0
E-1.1
Table E-1.2 Standard Technology Matrix for Trucks
Vehicle Technology
Fractional
Incremental
Incremental
Incremental
Incremental
First Year
Fractional
Fuel
Cest
Cost
Weight (lbs)
Weight
Introduced
Horsepower
Efficiency
($1990)
($/unit wgt)
(lbs/unit wgt)
Change
Change
FRONT WHEEL DRIVE
0.02
160
0
0
-0.08
1985
0
UNIT BODY
0.06
80
0
0
-0.05
1995
0
MATERIAL SUBSTITUTION II
0.033
0
0.6
0
-0.05
1996
0
MATERIAL SUBSTITUTION III
0.066
0
0.8
0
-0.1
2006
0
MATERIAL SUBSTITUTION IV
0.099
0
I
0
-0.15
2016
0
MATERIAL SUBSTITUTION V
0.132
0
1.5
0
-0.2
2026
0
DRAG REDUCTION II
0.023
32
0
0
0
1990
0
DRAG REDUCTION III
0.046
64
0
0
0.05
1997
0
DRAG REDUCTION IV
0.069
112
0
0
0.01
2007
0
DRAG REDUCTION V
0.092
176
0
0
0.02
2017
0
TCLU
0.03
40
0
0
0
1980
0
4-SPEED AUTOMATIC
0.045
225
0
30
0
1980
0.05
5-SPEED AUTOMATIC
0.065
325
0
40
0
1997
0.07
CVT
0.1
250
0
20
0
2005
0.07
6-SPEED MANUAL
0.02
100
0
30
0
1997
0.05
ELECTRONIC TRANSMISSION
0.005
20
0
5
0
1991
0
ELECTRONIC TRANSMISSION II
0.015
40
0
5
0
2006
0
ROLLER CAM
0.02
16
0
0
0
1986
0
OHC 4
0.03
100
0
0
0
1980
0.15
OHC 6
0.03
140
0
0
0
1985
0.15
OHC 8
0.03
170
0
0
0
1995
0.015
4C/4V
0.06
240
0
30
0
1990
0.3
6C/4V
0.06
320
0
43
0
1990
0.3
8C/4V
0.06
400
0
60
0
2002
0.3
CYLINDER REDUCTION
0.03
-100
0
-150
0
1990
-0.1
4C/5V
0.08
300
0
45
0
1997
0.55
TURBO
0.05
500
0
80
0
1980
0.45
ENGINE FRICTION REDUCTION I
0.02
20
0
0
0
1991
0
ENGINE FRICTION REDUCTION 1
0.035
50
0
0
0
2002
0
ENGINE FRICTION REDUCTION III
0.05
90
0
0
0
2012
0
ENGINE FRICTION REDUCTION IV
0.065
140
0
0
0
2022
0
VVT I
0.08
140
0
40
0
2006
0.1
VVT II
0.1
180
0
40
0
2016
0.15
LEAN BURN
0.1
150
0
0
0
2018
0
TWO STROKE
0.15
150
0
-150
0
2008
0
TBI
0.02
40
0
0
0
1985
0.05
MPI
0.035
80
0
0
0
1985
0.1
AIR PUMP
0.01
0
0
-10
0
1985
0
DFS
0.015
15
0
0
0
1985
0.1
OIL SW-30
0.005
2
0
0
0
1987
0
OIL SYNTHETIC
0.015
5
0
0
0
1997
0
TIRES I
0.01
16
0
0
0
1992
0
TIRES II
0.02
32
0
0
0
2002
0
TIRES Ш
0.03
48
0
0
0
2012
0
TIRES IV
0.04
64
0
0
0
2018
0
ACC I
0.005
15
0
0
0
1997
0
ACC II
0.01
30
0
0
0
2007
0
EPS
0.015
40
0
0
0
2002
0
4WD IMPROVEMENTS
0.03
100
0
0
-0.05
2002
0
AIR BAGS
-0.01
300
0
35
0
1992
0
EMISSIONS TIERT
-0.01
150
0
10
0
1996
0
EMISSIONS TIER II
-0.01
300
0
20
0
2004
0
ABS
-0.005
300
0
10
0
1990
0
SIDE IMPACT
-0.005
100
0
20
0
1996
0
ROOF CRUSH
-0.003
100
0
5
0
2001
0
INCREASED SIZE/WT
0.033
0
0
0
0.05
1991
0
DRAFT
6/10/97
APPENDIX E-2
ENERGY USE AND REDUCTION IN LIGHT-DUTY VEHICLES
Understanding how an automobile uses energy is an important first step in evaluating the wide
array of technologies available to improve fuel economy. Briefly, vehicles use energy primarily to
produce power at the wheels to overcome three tractive forces that would otherwise prevent the
vehicle from moving:
aerodynamic drag, the force of air fiction on the body surfaces of the vehicle;
rolling resistance, the resistive forces between the tires and the road; and
inertia and gravity forces, the first the resistance of any mass to acceleration, the second the
downward restraining force of gravity on the vehicle's mass when it is climbing a grade.
In addition, the vehicle must produce energy to power accessories such as heating fan, air
conditioner, lights, radio, and power steering. And, unless the engine is turned off, during idle and
braking the engine energy is largely wasted because it is not being used to provide motive force.
To obtain motive power, the automobile must transform the chemical energy in its fuel into power
at the wheels. First, the engine translates the fuel's chemical energy into shaft power. Some of
this power is then bled off to power accessories and the remainder is transformed by the
transmission and other drivetrain components into power that can drive the wheels.
The transformation from chemical energy to motive force is a relatively inefficient process. Energy
is lost because moving parts in the engine create friction; because air and fuel must be pumped
through the engine, causing aerodynamic and fluid drag losses; because much of the heat generated
by combustion cannot be used for work and is wasted; and because slippage in the transmission
causes losses. As discussed later, a conventional vehicle drivetrain generally will be able to
transform about 14 (city) to 23 (highway) percent of the fuel energy into usable power at the
wheels.
To reduce fuel consumption, vehicle designers can work to reduce all of the forces acting on the
vehicle (the tractive forces) and the accessory power, as well as the losses in turning fuel into
motive power. Each of these are treated in turn, below.
1. Reducing Tractive Forces: Aerodynamic Drag
Aerodynamic drag is the resistive force of the air as the vehicle tries to push its way through it.
The power required to overcome the aerodynamic drag force increases with the cube of vehicle
speed,¹ and the energy/mile required varies with the square of speed. Thus, aerodynamic drag
principally affects highway fuel economy. Aside from speed, aerodynamic drag depends
primarily on the vehicle's frontal area, its shape, and the smoothness of its body surfaces. To
minimize drag, vehicle designers thus seek to minimize frontal area by shaving off unused
space, redesigning seating arrangements, and finding ways to make the vehicle's side structure
thinner; smooth vehicle surfaces by flush-mounting windows, achieving better fit of body
panels, even changing the texture of vehicle paint or adding panels to the vehicle's underside;
reduce or eliminate obstructions to air flow by removing radio antennae or putting cowlings on
outside mirrors; redirect airflow with front air dams and other devices; and change the vehicle's
basic shape both to smooth airflow (e.g., by increasing the slope of the windshield) and
eliminate problems associated with issues such as boundary layer separation and flow regimes,
subjects for aerodynamic specialists. There are also more arcane measures that can be taken,
but these are unlikely for the time period of this study.
E-2.1
DRAFT
6/10/97
The effect of the vehicle's shape and smoothness on drag is characterized by the vehicle drag
coefficient Cₚ, a nondimensional measure of how the vehicle compares aerodynamically to a
flat surface of the same frontal area directly facing the airflow. In today's automobiles, a 10
percent C₀ reduction typically will result in a 2 to 2.5 percent improvement in fuel economy, if
vehicle performance is held constant.² The same ratio holds for a reduction in frontal area,
although the potential for such reductions is limited by interior space requirements. Note that
the ratio of reduced Cₚ to increased fuel economy will depend on the relative values of the three
tractive forces and accessory loss. As vehicles evolve and the balance of forces change,
reducing Cₚ may yield a higher or lower fuel economy benefit. Also, the ratio is dependent on
the driving cycle; in this case, the cycle referred to is the Federal Test Procedure. At a lower
speed cycle, for example, reducing Cₚ would have less effect because aerodynamic forces are
less important.
2. Reducing Tractive Forces: Rolling Resistance
Rolling resistance is the resistive force between the tires and the road, and depends on the
design and materials of the tire (and road) and on the weight borne by the tire; depending on
how it's measured, rolling resistance may also include friction losses in wheel bearings and
seals. The primary source of tire rolling resistance is internal fiction in the rubber compounds
as the tire deflects on contact with the road.
Rolling resistance may be reduced by:
(1) redesigning tires and tire materials to minimize the energy lost as the tire flexes,
(2) lowering vehicle weight (see below), and
(3) redesigning wheel bearings and seals.
A major concern in tire redesign is to avoid compromising tire durability and handling capabilities.
The rolling resistance coefficient (RRC), like the aerodynamic drag coefficient, is a measure of the
resistance to a vehicle's movement-in this case, of the tires. A reduction in rolling resistance of 6
percent will typically yield a fuel economy improvement of about 1 percent. As with the Cᵥ, this is
an approximate value that will change as vehicle design changes.
3. Reducing Tractive Forces: Inertial Force (Weight Reduction)
Inertial force is the resistance of vehicle mass to acceleration or grade-climbing, and is largest in
city driving, with its frequent speed changes, and hill-climbing. Inertial force is reduced by making
the vehicle lighter, e.g., by reducing waste, using lighter, stronger materials, and possibly by
redesigning the vehicle interior or structure. An added benefit of reducing vehicle weight is the
resulting reduction in rolling resistance, which varies linearly with weight. Starting from current
vehicles, a 10 percent weight reduction will yield as much as a 6 percent increase in fuel economy,
at constant performance.3
4. Reducing Accessory Power
Accessory losses may be reduced by improving the design of air conditioners, water and oil
pumps, power steering, and other power equipment, or by reducing the work these accessories
must do (for example, heating and cooling loads can be reduced by providing insulation and
coating window surfaces with coatings that reflect unwanted solar radiation).
E-2.2
DRAFT
6/10/97
5. Turning Fuel Energy into Motive Power-Improving Engine Efficiency
The process of turning fuel's chemical energy into shaft power is inefficient. To begin with, spark
ignition (SI) engines, the dominant passenger car and light truck powerplant in the United States,
have a theoretical maximum efficiency of about 45 percent (for a compression ratio of 10:1, and the
stoichiometric air-fuel ratio needed to allow current emission control systems to operate properly.⁴
And for several reasons, SI engines cannot achieve this theoretical efficiency level.
First, even the 45 percent maximum efficiency assumes an ideal cycle where combustion is
instantaneous and occurs precisely at the point where it can do the most work; the finite time of the
combustion process allows some fuel to be burned at less than the highest possible pressure and
some heat to be lost through the cylinder walls before it can do work. Second, mechanical friction
associated with the motion of the piston, crankshaft, and valves consumes a significant fraction of
total power. Friction is a stronger function of engine speed than of torque; therefore, efficiency is
degraded considerably at light load and high rpm conditions. Third, aerodynamic frictional and
pressure losses associated with air flow through the air cleaner, intake manifold and valves,
exhaust manifold, silencer, and catalyst are significant, especially at high air flow rates through the
engine. Fourth, SI engines reduce their power output by throttling the air flow, which causes
additional aerodynamic losses called "pumping losses" that are very high at light loads.
Because of these losses, production spark ignition engines are significantly less efficient than their
theoretical maximum even when they are operating at their most efficient operating point. Further,
in real world driving they often operate under conditions that push their efficiencies even lower.
For example, their maximum efficiency point generally occurs at relatively high loads, whereas
most driving is under light load conditions, when pumping losses are highest (e.g., during city
driving and steady state cruise on the highway). The high power that these engines are capable of
is used only during strong accelerations, at very high speeds or when climbing steep grades. And
during stop-and-go driving conditions typical of city driving, a substantial amount of time is spent
at idle, where efficiency is zero. Typical modern spark ignition engines have an efficiency of about
18 to 20 percent on the city part of the Environmental Protection Agency driving cycle, and about
26 to 28 percent on the highway part of the cycle.
The complex nature of engine efficiency losses implies that engine designers have a wide variety of
pathways to explore in the search for higher efficiency. These range from measures that would
improve thermodynamic efficiency (measures that will improve spark timing, allow increased
compression ratios, and promote faster combustion - for example, advanced electronic controls
and better cylinder design) to measures that attack mechanical friction (lighter valve-trains,
advanced coatings on pistons, improved lubricants) and aerodynamic losses (increased number of
valves per cylinder, deactivating cylinders at light loads, variable timing for valve opening).
6. Turning Fuel Energy into Motive Power-Improving Automatic Transmissions
Automatic transmissions match the speed and power required at the wheels to the speed and power
output of the engine, choosing gear ratios that keep the engine operating in speed ranges that allow
the engine to maintain high efficiency. Energy is lost within the transmission itself, through
hydraulic losses in the torque converter, and in the engine because the transmission may not have
the capability to keep the engine at its maximum efficient point -- either because it has a finite
number of gears, or because it lacks the sensing technology or sensitive controls that would allow
the perfect choice of shift points. Also, the vehicle designer may deliberately move shift points
from the true (efficiency) optimum to gain an improvement in other attributes, for example, less
frequent downshifts or smoother engine operation.
E-2.3
DRAFT
6/10/97
Transmission improvements can come from reducing torque converter losses with better design
and materials, increasing the number of gears (or ultimately moving to continuously variable
transmissions), and improving the electronics that control transmission shift points and sense when
shifts should occur.
7. Another Potential Source of Energy Savings-Sacrificing Vehicle Capabilities
Fuel consumption may also be reduced by sacrificing consumer amenities--reducing the size of the
passenger compartment (and, consequently, the size and weight of the vehicle), using a less
powerful engine that cannot provide the same acceleration (and that may cause greater noise and
vibration), designing transmission shifts that achieve higher efficiency at the cost of more
harshness, reducing the number of accessories such as air conditioning or power locks and
windows, and so forth. Most modern attempts to reduce fuel consumption do not contemplate
sacrificing these amenities, but some types of vehicle redesigns may achieve higher efficiency only
at the cost of such a sacrifice.
Maintenance of consumer amenities is not the goal of vehicle designers, however-their
goal generally is improvement. All technologies with the potential to enhance fuel economy
can be used for other consumer amenities such as acceleration performance, and tradeoffs
between fuel economy and other, competing amenities are a constant feature of vehicle
design -- with fuel economy often the loser in today's marketplace. Examples include:
Structural redesign using supercomputers can be used to increase structural stiffness at
constant weight rather than to reduce weight at constant stiffness. Anecdotal evidence
suggests that increasing structural stiffness is virtually a universal goal for car designers,
and all new models have increased stiffness;
Technologies that increase engine power density and efficiency can be used to increase
power at constant displacement, with a lesser or zero fuel economy improvement, rather
than downsize the engine to achieve the same power with improved fuel economy.
Generally, replacement of 2-valve engines with 4-valve engines has involved higher
power, no change in displacement, and little fuel economy increase.
As noted earlier, the balance of energy losses will vary from vehicle to vehicle according to each
vehicle's design, and will shift as technology advances. Nevertheless, an examination of the
energy losses in a typical 1995 mid-size car will provide an indicator of target areas for saving fuel.
The vehicle in question gets 27.7 mpg on the EPA test cycle (22.7 mpg city; 38.0 mpg, highway):
Engine efficiency: the fraction of fuel energy that emerges as shaft horsepower-is about
22 percent on the city part of the test and 27 percent on the highway, 24 percent composite.
In other words, three quarters of fuel energy is lost in the engine, a tempting target for
improvement. Raising engine efficiency from 24 to 25 percent would reduce fuel
consumption by 4 percent.
Of the energy that is converted by the engine to actual shaft horsepower:
braking and idling loss: 16 percent (city), 2 percent (highway), 11 percent (composite)
is lost because it cannot be used when the vehicle is braking or idling. Systems that turn
the engine off during braking and idle (engine off or electric drivetrains), or store the
energy produced (hybrid systems can do this), can recover much of this 11 percent;
E-2.4
DRAFT
6/10/97
transmission loss: 10 percent (city), 7 percent (highway), 9 percent (composite) is lost
by transmission inefficiencies. This is the target for improved transmissions or, for
electric vehicles, avoiding the need for a transmission;
accessory loss: 11 percent (city), 7 percent (highway), 9 to 10 percent (composite) is
used to power the accessories. Aside from conventional strategies to improve accessory
efficiency or to reduce heating and cooling loads, electric vehicles have a different mix
of accessories--some differences help (no oil pump), and some hurt (may need a heat
pump to generate cabin heat);
energy for motive power: 63 percent (city), 84 percent (highway), 71 percent
(composite) is actually used to overcome the tractive forces on the vehicle.
The three tractive forces play different roles at different speeds:
rolling resistance accounts for 28 percent of total tractive forces in the city, and 35
percent on the highway, 31 percent composite. Both improvement to tires and weight
reduction work to reduce this large fiction of tractive forces;
aerodynamic drag accounts for 18 percent (city) and 50 percent (highway), 30 percent
composite; and
inertia (weight) force accounts for 54 percent (city) and 14 percent (highway), 40
percent composite. Weight reduction directly attacks this force, or some of the energy
used to overcome it can be recovered by regenerative braking.
1. More precisely, the relative speed of the vehicle and the air. If the vehicle is heading into the wind, the relative
speed is the sum of vehicle speed and windspeed; with a tailwind, the relative speed is the difference of the two
speeds.
2 One way to hold performance constant is to change the ratio of the highest transmission gear; at high speeds, a
reduced Cₚ means that the engine need not deliver as much power to the wheels to maintain speed or accelerate,and
the gears can be adjusted accordingly.
3 Including a less powerful engine, since a lighter vehicle is easier to accelerate and take up steep grades.
4 Stoichiometric defines a balance of air to fuel that allows just enough oxygen to complete burn the fuel and no
more. Avoiding an excess of fuel is important to minimizing engine-out emissions of hydrocarbons; avoiding an
excess of air provides the oxygen-free exhaust that allows current NOx catalysts to operate.
E-2.5
DRAFT
6/10/97
APPENDIX F
DRAFT
6/10/97
The chart shows the generating price of power at the busbar for the peak and offpeak seasons.
These prices are higher during the fraction of each season when higher-cost plants are required
to operated to meet demand.
F-1.3
BLAW K
RommAppF-2Tables.xds:AEOInput
Case ID
2010 AEO
CAPITALIZAT IOU-Existing
IPP-Existing
IPP-New
IPP-Renew
Peak Season LDC
Peak Demand
14685.1517
Fuel Type
$/MMBTU kg C/MBTU
1
2
3
4
Season Peak Shoulder
2
Shoulder 1
Min (100%)
Ratio of Off-peak to peak
87.8%
Gas
2.59
14.47
Term (Years)
30
30
20
20 % of Season
0
6
95
100
Peak fraction of year
25%
Coal
1.34
25.72 Tax life
20
20
12
6 Template ratic
100%
90%
49%
39%
Load Factor, %
62.8%
Oil
3.00
21.49 Inc. Tax Rate
36%
36%
36%
36% Ratio to Peak
100%
90%
49%
39%
Peak Season Load Factor
69.7%
Nuclear
0.70
0 Prop. Tax rate
5%
5%
5%
5% Demand MW
14,685
13,257
7,223
5,755
Off-Peak Season Load Factor
68.9%
Hydro
0.00
0 Debt %
48%
30%
30%
30% Off-Peak Season LDC
Carbon Tax, $/netric ton C
0.00
Other
0.00
0 Interest Rate
6.0%
10.0%
10.0%
10.0% % of Season
0
2
96
100
Capacity Payment,$/kW
0 Year of Study
2010
Preferr Equity
14%
0%
0%
0% Template ratic
100%
83%
55%
46%
Uplift Charge, e/kWh
0 Year of $
1995
Return Rate
10.0%
10.0%
10.0%
10.0% Ratio to Peak
100%
83%
55%
46%
Unserved Energy, c/kWh
0 Start-up Cost, $/MW
40 Common Equi
38%
70%
70%
70% Demand MW
12,892
10,735
7,108
5,994
Non-generat. Price, c/kWh
3.18 Min Capacity w/ probab
0 Return Rate
11.0%
14.0%
14.0%
14.0%
Price Elasticity(not used If 0)
0.05 Min Outage Rate w/ probab
0.0% Vary FCR by
TRUE
TRUE
TRUE
TRUE
Default Unserved E calc (always slew
Max # Plants with prob.
10 Include in Avo
FALSE
FALSE
FALSE
FALSE
Fractional change to start year
0.30
Capacity
Forced
Planned
Variable
Fixed
- Plant Construction -
Captilization
Unavoidable
Variable
Adjust Factor
Outage
Outage
Heat Rate
Fuel Price
O&M Cost
Bid Price or
O&M Cost
Nominal
Construction
Structure
Fixed Cost
Cost
Name
Capacity
(0 to1)
Rate
Rate
(BTUkWh)
Fuel Type
Adjustment
e/kwh
OP, c/kwh
$/kW-yr
Cost/kW
Year
to Use const $/kW-yr
#kwh
Nuclear1
1,000
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
800
1973
1
26
0.73
Nuclear2
800
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
2,750
1988
1
180
0.73
Coal1
950
1
7.0%
14.2%
9,600
Coal
0.833
0.21
OP
11.7
490
1983
1
26
1.28
Coal2
850
1
6.5%
8.8%
9,700
Coal
1.000
0.22
OP
11.7
370
1978
1
15
1.51
Coat3
850
1
6.5%
8.8%
9,800
Coal
1.000
0.22
OP
11.7
300
1973
1
10
1.53
Coal4
600
1
6.6%
10.3%
9,900
Coal
1,000
0.23
OP
12.4
680
1981
1
31
1.55
Coal5
600
1
6.6%
10.3%
10,000
Coal
1.000
0.24
OP
12.4
380
1960
1
0
1.58
Coal6+7
850
1
8.5%
12.3%
10,200
Coal
1.000
0.32
OP
15.2
500
1980
1
21
1.68
Coals
450
1
8.5%
12.3%
10,600
Coal
1.167
0.32
OP
15.2
300
1970
1
8
1.97
Coal9+10
450
1
6.4%
10.9%
11,200
Coal
1.167
0.35
OP
16.3
300
1970
1
8
2.09
Coal-Adv.
400
1
4.1%
12.3%
9,600
Coal
1.000
0.25
OP
33.6
1,816
2006
3
277
1.53
Oil1
500
1
11.6%
5.2%
10,100
Oll
0.840
0.50
OP
6.0
127
1973
1
4
3.05
GasST1
600
1
9.7%
6.8%
10,000
Gas
0.951
0.13
OP
9.4
170
1976
1
6
2.59
GasST2
500
1
9.7%
6.8%
10,100
Gas
1.084
0.13
OP
9.4
150
1970
1
4
2.96
GasST3
450
1
9.7%
6.8%
10,200
Gas
1.111
0.13
OP
9.4
220
1967
1
0
3.06
GasCC1
300
1
6.8%
13.0%
9,665
Gas
0.951
0.10
OP
10.0
470
1992
2
45
2.48
GasCC2-New
420
1
5.5%
7.5%
7,760
Gas
1.000
0.05
OP
28.9
452
1999
3
49
2.06
GasCC3-new
420
1
5.5%
7.5%
7,618
Gas
1.000
0.05
OP
28.9
477
2001
3
55
2.02
GasCC4-Adv
420
1
5.5%
7.5%
6,284
Gas
1.000
0.05
OP
26.6
538
2005
3
76
1.68
GasCCS-Adv
600
1
5.5%
7.5%
5,817
Gas
1.000
0.05
OP
26.6
615
2009
3
109
1.55
GasCT1+2
450
1
10.0%
5.4%
12,800
Gas
0.969
0.22
OP
6.0
140
1986
1
9
3.42
GasCT3-new
650
1
3.6%
4.0%
11,460
Gas
1.000
0.01
OP
11.9
364
1998
3
36
2.98
GasCT4-new
650
1
3.6%
4.0%
10,873
Gas
1.000
0.01
OP
11.9
406
2002
3
50
2.82
GasCT5-Adv.
650
1
3.8%
3.9%
7,793
Gas
1.000
0.05
OP
16.9
542
2008
3
89
2.07
Renewable
250
1
25.0%
15.0%
10,280
Other
1.000
1.27
OP
65.5
2,361
2008
4
351
1.27
Limited Energ Capacity, MW
Peak CF
Non-peak CF
Hydro
1,600
1
55.0%
40.0%
Hydro
0.10
10
400
1957
1
0
0.10
Total Capacity
16,260
SWH,6/9/97,6:34 PM
Page 1
RommAppF-2Tables.xds:AEOOutput
2010 AEO
Peak
Offpeak # of Unprofitable plants
% of Total
Cap fact
Avoidable
Variable
Annual
season
season
Against avoid O&M
8
Capacity Generation
%
c/kWh
c/kWh
Reserve Margin
10.7%
10.7%
11.2%
Against all costs
16 w/ unserve
Hydro
9.8%
7.6%
43.8%
0.36
0.10
LOLP, % of period
0.13
0.34
0.07
Average Price, C/KWh
2.50
2.50
Nuclear
11.1%
15.5%
79.6%
202
0.73
LOLP. day/10 Year
4.90
12.40
2.41
Avg. Variable Cost
1.43
1.43
Coal
36.9%
50.8%
78.0%
1.78
1.57
Load factor
62.8%
69.7%
68.9% Avg. Vari+Avoid O&M
1.90
1.90
Oil
3.1%
0.1%
1.0%
11.59
4.44
Peak Demand, MW
14,685
14,685
12,892
Total Cost
2.61
2.81
Gas-ST
9.5%
1.8%
10.7%
3.74
2.74
Energy. GWh
80,793
22,423
58,370
Max loss, $/avail kW
(9.71)
Gas-CC
13.3%
17.2%
73.6%
2.21
1.82
Generation, GWh
80,790
22,419
58,371
Start-up Cost, S/MW
40
Gas-CT
14.8%
5.4%
20.7%
2.93
2.26
Unserved Energy. G'
5
3
2
# plants Probabilistic
10
Other
1.5%
1.6%
60.0%
2.51
1.27
Round arr not in UE
(2)
1
(2)
Plant
Output
Capac
Time on
Revenue
Var.
+Start
Avoidable
Unavoidable
Total Net
Avoidable Net Rev
Avoidable
Carbon release
Name
Capacity
MWyr
Factor
Margin, %
MS
Cost MS xd Cst MS
Fxd Cst MS
Rev MS
MS
$/kW
cost,
c/kWh
Million Tons
Nuclear1
1,000
796.00
79.6%
0.00
168
51
90
26
0
26.91
33.80
2.02
0.00
Nuclear2
800
636.80
79.6%
0.00
134
41
72
144
(122)
21.53
33.80
2.02
0.00
Coal1
950
748.60
78.8%
0.00
158
84
11
25
39
63.07
84.25
1.45
1.62
Coal2
850
719.95
84.7%
0.00
152
96
10
13
34
46.38
64.42
1.67
1.57
Coal3
850
719.95
84.7%
0.00
152
96
10
8
37
45.53
63.25
1.69
1.59
Coal4
600
498.60
83.1%
0.00
105
68
7
18
12
29.98
60.12
1.72
1.11
Coal5
600
495.96
82.7%
0.40
105
68
7
0
29
28.96
58.08
1.75
1.12
Coal6+7
850
648.28
76.3%
3.70
138
96
13
18
12
30.02
44.59
1.91
1.49
Coal8
450
330.48
73.4%
286
71
57
7
3
4
7.39
20.73
2.21
0.79
Coal9+10
450
186.72
41.5%
12.44
46
34
7
3
1
4.29
11.53
2.54
0.47
Coal-Adv.
400
334.40
83.6%
0.00
71
45
13
111
(98)
12.31
36.82
1.99
0.72
Oil
500
4.79
1.0%
0.88
3
2
3
2
(4)
(2.07)
(4.97)
11.59
0.01
GasST1
600
137.54
22.9%
16.52
38
31
6
4
(3)
0.80
1.59
3.06
0.17
GasST2
500
25.92
5.2%
3.81
10
8
5
2
(5)
(2.68)
(6.42)
5.43
0.03
GasST3
450
2.06
0.5%
0.39
2
1
4
O
(3)
(3.49)
(9.29)
28.31
0.00
GasCC1
300
96.17
32.1%
8.17
25
21
3
14
(13)
0.98
4.05
2.83
0.12
GasCC2-New
420
290.81
69.2%
8.93
64
52
12
20
(20)
(0.06)
(0.17)
2.53
0.29
GasCC3-new
420
321.04
76.4%
7.46
70
57
12
23
(22)
0.93
2.53
2.45
0.31
GasCC4-Adv
420
361.45
86.1%
0.90
77
53
11
32
(20)
12.28
33.61
2.03
0.29
GasCC5-Adv
600
521.31
86.9%
0.27
110
71
16
65
(42)
23.04
44.13
1.90
0.38
GasCT1+2
450
0.88
0.2%
0.21
1
0
3
4
(6)
(2.06)
(5.41)
40.68
0.00
GasCT3-new
650
17.37
2.7%
2.76
8
6
8
24
(29)
(5.83)
(9.71)
8.86
0.03
GasCT4-new
650
81.59
12.6%
11.27
25
20
8
33
(35)
(2.53)
(4.22)
3.91
0.11
GasCT5-Adv.
650
395.92
60.9%
18.88
91
72
11
58
(49)
8.44
14.06
2.38
0.39
Renewable
250
150.00
60.0%
0.00
32
17
16
88
(89)
(1.35)
(8.97)
2.51
0.00
Hydro
1,600
700.00
43.8%
166
6
16
0
144
143.86
89.91
0.36
0.00
Totals
16,260
9,223
57%
2,021
1,152
382
739
(252)
487
12.62
Avoidable
Total
Unserved Energy
0.54
2
2
w/o UE
1,534
2,273
Avg. Carbon kg/MWhr
156
Totals w/ Unserved
9,223
2,022
1,154
w/ UE
1,536
2,274
Time wtd marginal cost
240
Time wid Unserv E Price
18.94
Unserv E. Cost/kWh
38.42
Sort by Net Revenue/kW
Price Increase to pay avoided losses
0.02
Avoidable
Reserve
Name
Net Rev/kW
Capacity
Margin
Marginal Power Costs and Prices
Hydro
89.91
1,600
11%
10.00
Coal1
84.25
950
17%
Coal2
64.42
850
23%
9.00
Coal3
63.25
850
29%
Peak Season Cost
Coal4
60.12
600
33%
8.00
Peak Season Price
Coal5
58.08
600
37%
Off-Season Cost
Coal6+7
44.59
850
43%
GasCC5-Adv
44.13
600
47%
7.00
Off-Season Price
Cosi-Adv.
36.82
400
50%
Nuclear1
33.80
1,000
57%
6.00
Nuclear2
33.80
800
62%
GasCC4-Adv
33.61
420
65%
Coals
450
#/kWH
5.00
20.73
68%
GasCT5-Adv.
14.06
650
72%
Coal9+10
11.53
450
75%
4.00
GasCC1
4.05
300
77%
GasCC3-new
2.53
420
80%
3.00
GasST1
1.59
600
84%
GasCC2-New
(0.17)
420
87%
2.00
GasCT4-new
(4.22)
650
92%
Oil1
(4.97)
500
95%
1.00
GasCT1+2
(5.41)
450
96%
GasST2
(6.42)
500
102%
Renewable
(8.97)
250
103%
0.00
asST3
(9.29)
450
106%
0
10
20
30
40
50
60
70
80
90
100
Percent of Period
lasCT3-new
(9.71)
650
111%
SWH,6/9/97,6:45 PM
Page 1
RommAppF-2Tables.xds:Restrucinpurt
Case ID
Restructure case
CAPITALIZAT IOU-Existing
IPP-Existing
IPP-New
IPP-Renew
Peak Season LDC
Peak Demand
14188.3366
Fuel Type
$/MMBTU kg C/MBTU
1
2
3
4
Season Peak
Shoulder 2
Shoulder 1
Min (100%)
Ratio of Off-peak to peak
88.7%
Gas
2.59
14.47
Term (Years)
30
30
20
20 % of Season
0
5
95
100
Peak fraction of year
25%
Coal
1.34
25.72
Tax life
20
20
12
5 Template ratic
100%
94%
53%
42%
Load Factor, %
65.8%
Oil
3.00
21.49
Inc. Tax Rate
36%
36%
36%
36% Ratio to Peak
100%
94%
53%
42%
Peak Season Load Factor
73.1%
Nuclear
0.70
0 Prop. Tax rate
5%
5%
5%
5% Demand MW
14,188
13,276
7,491
5,918
Off-Peak Season Load Factor
71.4%
Hydro
0.00
0 Debt %
48%
30%
30%
30% Off-Peak Season LDC
Carbon Tax, $/netric ton C
0.00
Other
0.00
0 Interest Rate
8.0%
10.0%
10.0%
10.0% % of Season
0
2
96
100
Capacity Payment,$/kW
0 Year of Study
2010
Preferr Equity
14%
0%
0%
0% Template ratic
100%
85%
58%
50%
Uplift Charge, c/kWh
0 Year of $
1995
Return Rate
10.0%
10.0%
10.0%
10.0% Ratio to Peak
100%
85%
58%
50%
Unserved Energy, c/kWh
0 Start-up Cost, $/MW
40 Common Equi
38%
70%
70%
70%
Demand MW
12,589
10,755
7,285
6,285
Non-generat. Price, c/kWh
3.18 Min Capacity w/ probab
0 Return Rate
11.0%
14.0%
14.0%
14.0%
Price Elasticity(not used If 0)
0.05 Min Outage Rate w/ probab
0.0% Vary FCR by
TRUE
TRUE
FALSE
FALSE
Default Unserved E calc (always allow
Max # Plants with prob.
10 Include in Avo
FALSE
FALSE
TRUE
TRUE
Fractional change to start year
0.30
Capacity
Forced
Planned
Varlable
Fixed
- Plant Construction -
Capillization
Unavoidable
Variable
Adjust Factor
Outage
Outage
Heat Rate
Fuel Price
O&M Cost
Bld Price or
O&M Cost
Nominal
Construction
Structure
Fixed Cost
Cost
Name
Capacity
(0 to1)
Rate
Rate
(BTU/kWh)
Fuel Type
Adjustment
c/kwh
OP, c/kwh
$/kW-yr
Cost/kW
Year
to Use const $/kW-yr
c/kwh
Nuclear1
1,000
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
800
1973
1
26
0.73
Nuclear2
800
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
2,750
1988
1
180
0.73
Coal1
900
1
7.0%
14.2%
9,600
Coal
0.833
0.21
OP
11.7
490
1983
1
26
1.28
Coal2
850
1
6.5%
8.8%
9,700
Coal
1.000
0.22
OP
11.7
370
1978
1
15
1.51
Coal3
850
1
6.5%
8.8%
9,800
Coal
1.000
0.22
OP
11.7
300
1973
1
10
1.53
Coal4
600
1
6.6%
10.3%
9,900
Coal
1.000
0.23
OP
12.4
680
1981
1
31
1.55
Coal5
600
1
6.6%
10.3%
10,000
Coal
1.000
0.24
OP
12.4
380
1960
1
0
1.58
Coal6+7
850
1
8.5%
12.3%
10,200
Coal
1.000
0.32
OP
15.2
500
1980
1
21
1.68
Coals
450
1
8.5%
12.3%
10,600
Coal
1.167
0.32
OP
15.2
300
1970
1
8
1.97
Coal9+10
450
1
6.4%
10.9%
11,200
Coal
1.167
0.35
OP
16.3
300
1970
1
8
2.09
Coal-Adv.
50
1
4.1%
12.3%
9,600
Coal
1.000
0.25
OP
33.6
1,816
2006
3
222
1.53
OII1
500
1
11.6%
5.2%
10,100
Oil
0.840
0.50
OP
6.0
127
1973
1
4
3.05
GasST1
600
1
9.7%
6.8%
10,000
Gas
0.951
0.13
OP
9.4
170
1976
1
6
2.59
GasST2
500
1
9.7%
6.8%
10,100
Gas
1.084
0.13
OP
9.4
150
1970
1
4
2.96
GasST3
450
1
9.7%
6.8%
10,200
Gas
1.111
0.13
OP
9.4
220
1967
1
0
3.06
GasCC1
300
1
6.8%
13.0%
9,665
Gas
0.951
0.10
OP
10.0
470
1992
2
45
2.48
GasCC2-New
200
1
5.5%
7.5%
7,760
Gas
1.000
0.05
OP
28.9
452
1999
3
55
2.06
GasCC3-new
200
1
5.5%
7.5%
7,618
Gas
1.000
0.05
OP
28.9
477
2001
3
58
2.02
GasCC4-Adv
800
1
5.5%
7.5%
6,284
Gas
1.000
0.05
OP
26.6
538
2005
3
66
1.68
GasCC5-Adv
950
1
5.5%
7.5%
5,817
Gas
1.000
0.05
OP
26.6
615
2009
3
75
1.55
GasCT1+2
450
1
10.0%
5.4%
12,800
Gas
0.969
0.22
OP
6.0
140
1966
1
9
3.42
GasCT3-new
350
1
3.6%
4.0%
11,460
Gas
1.000
0.01
OP
11.9
364
1998
3
44
2.98
GasCT4-new
350
1
3.6%
4.0%
10,873
Gas
1.000
0.01
OP
11.9
406
2002
3
50
2.82
GasCT5-Adv.
450
1
3.8%
3.9%
7,793
Gas
1.000
0.05
OP
16.9
542
2008
3
66
2.07
Renewable
50
1
25.0%
15.0%
10,280
Other
1.000
1.27
OP
65.5
2,361
2008
4
260
1.27
Limited Energy
Peak CF
Non-peak CF
Hydro
1,600
1
55.0%
40.0%
1028000.0%
Hydro
0.10
10
400
1957
1
0
0.10
Total Capacity
15,150
BWH,6/9/97,6:36 PM
Page 1
RommAppF-2Tablesxds:RestrucOutpu/
Restructure case
Peak
Offpeak # of Unprofitable plants
% of Total
Cap fact
Avoidable
Variable
Annual
season
season
Against avoid O&M
9
Capacity Generation
%
c/kWh
e/kWh
Reserve Margin
6.8%
6.8%
6.1%
Against all costs
12 w/ unserve
Hydro
10.6%
7.5%
43.8%
0.36
0.10
LOLP. % of period
0.92
2.12
0.52 Average Price, c/kWh
2.84
2.86
Nuclear
11.9%
15.4%
79.6%
2.02
0.73
LOLP, day/10 Year
33.67
77.55
19.04 Avg. Variable Cost
1.45
1.47
Coal
37.0%
47.4%
78.9%
1.80
1.58
Load factor
65.7%
73.1%
71.4% Avg. Vari+Avoid O&M
217
2.19
Oil
3.3%
0.3%
4.8%
4.91
3.49
Peak Demand, MW
14,188
14,188
12,589
Total Cost
2.51
2.53
Gas-ST
10.2%
3.3%
19.6%
3.27
2.73
Energy, GWh
61,727
22,703
59,024
Max loss, $/avail kW
(417.34)
Gas-CC
16.2%
21.0%
80.0%
2.95
1.74
Generation, GWh
81,692
22,682
59,010 Start-up Cost, $/MW
40
Gas-CT
10.6%
4.9%
28.6%
4.34
2.32
Unserved Energy. G
34
21
13 # plants Probabilistic
10
Other
0.3%
0.3%
60.0%
7.47
1.27
Round err not in UE
1
o
0
Plant
Output
Capac
Time on
Revenue Var. +Start Avoidable Unavoidable
Total Net
Avoidable Net Rev
Avoidable
Carbon release
Name
Capacity
MWyr
Factor
Margin, %
MS
Cost MS xd Cst MS
Fxd Cst MS
Rev MS
MS
$/kW
cost,
c/kWh
Million Tons
Nuclear1
1,000
796.00
79.6%
0.00
188
51
90
26
21
47.00
59.04
2.02
0.00
Nuclear2
800
636.80
79.6%
0.00
150
41
72
144
(106)
37.60
59.04
2.02
0.00
Coal1
900
709.20
78.8%
0.00
168
79
11
23
54
77.73
109.60
1.45
1.53
Coal2
850
719.95
84.7%
0.00
170
96
10
13
52
64.39
89.44
1.67
1.57
Coal3
850
719.95
84.7%
0.00
170
96
10
8
55
63.55
88.27
1.69
1.59
Coal4
600
498.60
83.1%
0.00
118
68
7
18
24
42.50
85.23
1.72
1.11
Coal5
600
497.33
82.9%
0.31
118
69
7
0
41
41.48
83.18
1.75
1.12
Coal6+7
850
650.83
76.6%
3.76
156
96
13
18
29
46.99
69.80
1.91
1.50
Coale
450
331.95
73.8%
2.76
80
57
7
3
13
16.33
45.83
2.21
0.79
Coal9+10
450
248.27
55.2%
12.40
66
46
7
3
10
13.36
35.90
243
0.63
Coal-Adv.
50
41.80
83.6%
0.00
10
6
13
(8)
(8.49)
(203.14)
5.02
0.09
Oil1
500
24.14
4.8%
3.60
14
7
3
2
2
3.65
8.78
4.91
0.05
GasST1
600
218.00
36.3%
18.17
64
49
6
4
5
9.32
18.60
288
0.28
GasST2
500
74.36
14.9%
9.00
28
19
5
2
2
3.65
8.75
3.68
0.10
GasST3
450
11.21
2.5%
2.29
9
4
4
0
1
1.27
3.39
8.20
0.01
GasCC1
300
135.63
45.2%
8.25
38
29
3
14
(8)
5.54
23.02
2.73
0.17
GasCC2-New
200
149.36
74.7%
4.20
37
27
17
(7)
(6.78)
(38.94)
3.34
0.15
GasCC3-new
200
156.58
78.3%
4.00
38
28
17
(7)
(6.90)
(39.66)
3.29
0.15
GasCC4-Adv
800
691.10
86.4%
0.77
163
101
74
-
(12)
(11.85)
(17.02)
2.90
0.55
GasCC5-Adv
950
826.46
87.0%
0.06
195
113
97
(14)
(14.19)
(17.17)
2.89
0.61
GasCT1+2
450
5.10
1.1%
0.87
7
2
3
4
(2)
232
6.10
10.77
0.01
asCT3-new
350
34.22
9.8%
5.76
15
9
20
(14)
(13.54)
(41.87)
9.59
0.05
asCT4-new
350
92.17
26.3%
12.00
30
23
22
(14)
(14.26)
(44.10)
5.49
0.13
GasCT5-Adv.
450
326.60
72.6%
10.89
83
59
37
-
(14)
(13.80)
(33.22)
3.37
0.32
Renewable
50
30.00
60.0%
0.00
7
3
16
(13)
(12.52)
(417.34)
7.47
0.00
Hydro
1,600
700.00
43.8%
195
6
16
0
173
172.60
107.88
0.36
0.00
Totals
15,150
9,326
62%
2,317
1,184
586
284
263
547
12.50
Avoidable
Total
Unserved Energy
3.87
17
17
w/o UE
1.770
2,054
Avg. Carbon kg/MWhr
153
Totals w/ Unserved
9,329
2,335
1,202
w/ UE
1,788
2,071
Time wid marginal cost
261
Time wtd Unserv E Price
19.86
Unserv E. Cost/kWh
50.65
Sort by Net Revenue/kW
Price increase to pay avoided losses
0.13
Avoidable
Reserve
Name
Net Rev/kW
Capacity
Margin
Marginal Power Costs and Prices
Coal1
109.60
900
6%
10.00
Hydro
107.88
1,600
18%
Coal2
89.44
850
24%
9.00
Coal3
88.27
850
30%
Peak Season Cost
Coal4
85.23
600
34%
Peak Season Price
8.00
Coal5
83.18
600
38%
Off-Season Cost
Coal6+7
69.80
850
44%
Off-Season Price
Nuclear2
59.04
800
50%
7.00
Nuclear1
59.04
1,000
57%
Coal8
45.83
450
60%
6.00
Coal9+10
35.90
450
63%
GasCC1
23.02
300
65%
GasST1
600
69%
e/kWH
6.00
18.60
Oil1
8.78
500
73%
GasST2
8.75
500
76%
4.00
GasCT1+2
6.10
450
80%
GasST3
3.39
450
83%
3.00
GasCC4-Adv
(17.02)
800
88%
GasCC5-Adv
(17.17)
950
95%
2.00
GasCT5-Adv.
(33.22)
450
98%
GasCC2-New
(38.94)
200
100%
1.00
GasCC3-new
(39.66)
200
101%
GasCT3-new
(41.87)
350
104%
GasCT4-new
(44.10)
350
106%
0.00
50
106%
0
10
20
pal-Adv.
(203.14)
30
40
50
60
70
60
90
100
Percent of Period
Inewable
(417.34)
50
107%
SWH,6/9/97,6:36 PM
Page 1
RommAppF-2Tables.xis:Efflnput
Case ID
Efficiency Case
CAPITALIZAT IOU-Existing
IPP-Existing
IPP-New
IPP-Renew
Peak Season LDC
Peak Demand
13019.9318
Fuel Type
$/MMBTU kg C/MBTU
1
2
3
4
Season Peak Shoulder 2
Shoulder 1
Min (100%)
Ratio of Off-peak to pelak
88.4%
Gas
2.59
14.47
Term (Years)
30
30
20
20 % of Season
0
5
95
100
12
5 Template ratic
100%
93%
53%
42%
Peak fraction of year
25%
Coal
1.34
25.72 Tax life
20
20
Load Factor, %
65.5%
OIl
3.00
21.49
Inc. Tax Rate
36%
36%
36%
36% Ratio to Peak
100%
93%
53%
42%
Peak Season Load Factor
72.9%
Nuclear
0.70
0 Prop. Tax rate
5%
5%
5%
5% Demand MW
13,020
12,133
6,870
5,409
Off-Peak Season Load Factor
71.4%
Hydro
0.00
0 Debt %
48%
30%
30%
30% Off-Peak Season LDC
Carbon Tax, $/netric ton C
0.00
Other
0.00
0 Interest Rate
8.0%
10.0%
10.0%
10.0% % of Season
0
2
96
100
Capacity Payment,$/kW
0 Year of Study
2010
Preferr Equity
14%
0%
0%
0% Template ratic
100%
85%
58%
50%
Uplift Charge, e/kWh
0 Year of $
1995
Return Rate
10.0%
10.0%
10.0%
10.0% Ratio to Peak
100%
85%
58%
50%
Unserved Energy, c/kWh
0 Start-up Cost, $/MW
40 Common Equi
38%
70%
70%
70%
Demand MW
11,507
9,823
6,669
5,731
Non-generat. Price, c/kWh
3.18 Min Capacity w/ probab
0 Return Rate
11.0%
14.0%
14.0%
14.0%
Price Elasticity(not used if 0)
0.05 Min Outage Rate w/ probab
0.0% Vary FCR by
TRUE
TRUE
FALSE
FALSE
Default Unserved E calc (always sllow
Max # Plants with prob.
10 Include in Avo
FALSE
FALSE
TRUE
TRUE
Fractional change to start year
0.30
Unavoidable
Variable
Capacity
Forced
Planned
Variable
Fixed
- Plant Construction -
Captilization
Adjust Factor
Outage
Outage
Heal Rate
Fuel Price
O&M Cost
Bld Price or
O&M Cost
Nominal
Construction
Structure
Fixed Cost
Cost
Name
Capacity
101)
Rate
Rate
(BTU/kWh)
Fuel Type
Adjustment
c/kwh
OP, e/kwh
$/kW-yr
Cost/kW
Year
to Use const $/kW-yr
c/kwh
1973
1
26
0.73
Nuclear1
1,000
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
800
Nuclear2
800
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
2,750
1988
1
180
0.73
9,600
Coal
0.833
0.21
OP
11.7
490
1983
1
26
1.28
Coal1
900
1
7.0%
14.2%
Coal2
850
1
6.5%
8.8%
9,700
Coal
1.000
0.22
OP
11.7
370
1978
1
15
1.51
Coal3
850
1
6.5%
8.8%
9,800
Coal
1.000
0.22
OP
11.7
300
1973
1
10
1.53
31
1.55
Coal4
600
1
6.6%
10.3%
9,900
Coal
1.000
0.23
OP
12.4
680
1981
1
Coal5
600
1
6.6%
10.3%
10,000
Coal
1.000
0.24
OP
12.4
380
1960
1
0
1.58
1.000
0.32
OP
15.2
500
1980
1
21
1.68
Coal6+7
850
1
8.5%
12.3%
10,200
Coal
Coals
450
1
8.5%
12.3%
10,600
Coal
1.167
0.32
OP
15.2
300
1970
1
8
1.97
Coal9+10
450
1
6.4%
10.9%
11,200
Coal
1,167
0.35
OP
16.3
300
1970
1
8
2.09
Coal-Adv.
50
1
4.1%
12.3%
9,600
Coal
1.000
0.25
OP
33.6
1,816
2006
3
222
1.53
1
11.6%
5.2%
10,100
Oil
0.840
0.50
OP
6.0
127
1973
1
4
3.05
Oil1
500
OP
9.4
170
1976
1
6
2.59
GasST1
600
1
9.7%
6.8%
10,000
Gas
0.951
0.13
GasST2
500
1
9.7%
6.8%
10,100
Gas
1.084
0.13
OP
9.4
150
1970
1
4
2.96
1
9.7%
6.8%
10,200
Gas
1.111
0.13
OP
9.4
220
1967
1
0
3.06
GasST3
450
GasCC1
300
1
6.8%
13.0%
9,665
Gas
0.951
0.10
OP
10.0
470
1992
2
45
2.48
200
1
5.5%
7.5%
7,760
Gas
1.000
0.05
OP
28.9
452
1999
3
55
2.06
GasCC2-New
477
2001
3
58
2.02
GasCC3-new
200
1
5.5%
7.5%
7,618
Gas
1.000
0.05
OP
28.9
GasCC4-Adv
800
1
5.5%
7.5%
6,284
Gas
1.000
0.05
OP
26.6
538
2005
3
66
1.68
7.5%
5,817
Gas
1.000
0.05
OP
26.6
615
2009
3
75
1.55
GasCC5-Adv
300
1
5.5%
GasCT1+2
450
1
10.0%
5.4%
12,800
Gas
0.969
0.22
OP
6.0
140
1986
1
9
3.42
GasCT3-new
350
1
3.6%
4.0%
11,460
Gas
1.000
0.01
OP
11.9
364
1998
3
44
2.98
3
50
2.82
GasCT4-new
350
1
3.6%
4.0%
10,873
Gas
1.000
0.01
OP
11.9
406
2002
GasCT5-Adv.
0
1
3.8%
3.9%
7,793
Gas
1.000
0.05
OP
16.9
542
2008
3
66
2.07
Renewable
50
1
25.0%
15.0%
10,280
Other
1.000
1.27
OP
65.5
2,361
2008
4
260
1.27
Limited Energy
Peak CF
Non-peak CF
Hydro
1,600
1
55.0%
40.0%
1028000.0%
Hydro
0.10
10
400
1957
1
0
0.10
Total Capacity
14,050
Page 1
SWH,6/9/97,6:37 PM
RommAppF-2Tables.ds:EffOutput
Efficiency Case
Peak
Offpeak # of Unprofitable plants
% of Total
Cap fact
Avoidable
Variable
Annual
season
season
Against avoid O&M
8
Capacity Generation
%
ckWh
c/kWh
Reserve Margin
7.9%
7.9%
7.3%
Against all costs
11 w/ unserve
Hydro
11.4%
8.2%
43.8%
0.36
0.10
LOLP. % of penod
0.73
1.64
0.43
Average Price, c/kWh
2.85
2.87
Nuclear
12.8%
16.8%
79.6%
2.02
0.73
LOLP. day/10 Year
26.77
59.92
15.72
Avg. Variable Cost
1.43
1.45
Coal
39.9%
52.1%
79.4%
1.80
1.58
Load factor
65.5%
72.9%
71.4% Avg. Vari+Avoid O&M
2.08
2.09
OF
3.6%
0.3%
4.8%
4.92
3.49
Peak Demand, MW
13,020
13,020
11,507
Total Cost
2.46
2.47
Gas-ST
11.0%
4.0%
22.1%
3.20
2.72
Energy. GWh
74,733
20,777
53,956
Max loss, S/avall kW
(415.33)
Gas-CC
12.8%
16.5%
78.1%
2.97
1.82
Generation, GWh
74,709
20,761
53,948
Start-up Cost, $/MW
40
Gas-CT
8.2%
1.7%
12.8%
6.33
2.92
Unserved Energy, G
24
15
9 # plants Probabllistic
10
Other
0.4%
0.4%
60.0%
7.47
1.27
Round err not in UE
(1)
0
(1)
Plant
Output
Capac
Time on
Revenue
Var.
+Start
Avoidable
Unavoidable
Total Net
Avoidable Net Rev
Avoidable
Carbon release
Name
Capacity
MWYT
Factor
Margin, %
MS
Cost
MS
xd
Cst
M$
Fxd Cst MS
Rev MS
MS
$/kW
cost,
c/kWh
Million Tons
Nuclear
1,000
796.00
79.6%
0.00
190
51
90
26
22
48.80
61.31
2.02
0.00
Nuclear2
800
636.80
79.6%
0.00
152
41
72
144
(105)
39.04
61.31
2.02
0.00
Coal1
900
709.20
78.8%
0.00
169
79
11
23
56
79.29
111.80
1.45
1.53
Coal2
850
719.95
84.7%
0.00
172
96
10
13
53
66.12
91.84
1.67
1.57
Coal3
850
719.95
84.7%
0.00
172
96
10
8
57
65.28
90.67
1.69
1.59
Coal4
600
498.60
83.1%
0.00
119
68
7
18
25
43.67
87.58
1.72
1.11
Coal5
600
497.67
82.9%
0.32
119
69
7
0
43
42.65
85.53
1.75
1.12
Coal6+7
850
649.88
76.5%
4.25
157
96
13
18
30
48.51
72.05
1.91
1.49
Coal8
450
329.66
73.3%
3.58
81
57
7
3
14
17.18
48.20
2.21
0.79
Coal9+10
450
279.28
62.1%
11.64
73
51
7
3
11
14.24
38.28
2.39
0.70
Coal-Adv.
50
41.80
83.6%
0.00
10
6
13
(8)
(8.40)
(200.85)
5.02
0.09
OR1
500
24.03
4.8%
4.24
13
7
3
2
0
2.54
6.11
4.92
0.05
GasST1
600
250.40
41.7%
20.53
71
57
6
4
5
8.74
17.45
2.84
0.32
GasST2
500
81.68
16.3%
11.55
28
21
5
2
1
254
6.09
3.62
0.10
GasST3
450
10.09
2.2%
2.26
8
3
4
0
0
0.22
0.58
8.74
0.01
GasCC1
300
155.17
51.7%
9.26
42
34
3
14
(8)
5.40
22.44
270
0.19
GasCC2-New
200
145.06
72.5%
4.99
37
26
17
(6)
(6.31)
(36.27)
3.38
0.14
GasCC3-new
200
153.58
76.8%
4.84
38
27
17
(6)
(6.45)
(37.05)
3.32
0.15
GasCC4-Adv
800
691.42
86.4%
0.71
165
101
74
-
(10)
(10.14)
(14.57)
2.90
0.55
GasCC5-Adv
300
261.00
87.0%
0.00
62
36
30
,
(4)
(3.64)
(14.72)
2.89
0.19
ssCT1+2
450
4.41
1.0%
0.84
6
2
3
4
(3)
1.31
3.45
11.80
0.01
asCT3-new
350
36.25
10.4%
6.35
15
9
20
(14)
(14.26)
(44.11)
9.19
0.05
asCT4-new
350
106.55
30.4%
13.91
33
26
22
-
(15)
(14.97)
(46.28)
5.13
0.15
GasCT5-Adv.
0
-
0.0%
0.00
.
-
-
-
0.00
0.00
Renewable
50
30.00
60.0%
0.00
7
3
16
-
(12)
(12.46)
(415.33)
7.47
0.00
Hydro
1,600
700.00
43.8%
194
6
16
0
172
171.63
107.27
0.36
0.00
Totals
14,050
8,528
61%
2,132
1,069
483
284
296
580
11.92
Avoidable
Total
Unserved Energy
2.79
13
13
w/o UE
1,552
1,836
Avg. Carbon kg/MWhr
159
Totals w/ Unserved
8,531
2,145
1,082
w/ UE
1,565
1,849
Time wtd marginal cost
2.65
Time wtd Unserv E Price
19.99
Unserv E Cost/kWh
53.89
Sort by Net Revenue/kW
Price increase to pay avoided losses
0.10
Avoidable
Reserve
Name
vet Rev/kW
Capacity
Margin
Marginal Power Costs and Prices
Coal1
111.80
900
7%
10.00
Hydro
107.27
1,600
19%
Coal2
91.84
850
26%
9.00
Coal3
90.67
850
32%
Peak Season Cost
Coal4
87.58
600
37%
Peak Season Price
8.00
Coal5
85.53
600
41%
Off-Season Cost
Coal6+7
72.05
850
48%
Off-Season Price
Nuclear2
61.31
800
54%
7.00
Nucleart
61.31
1,000
62%
Coal8
48.20
450
65%
6.00
Coal9+10
38.28
450
69%
GasCC1
22.44
300
71%
5.00
GasST1
17.45
600
76%
Oill
6.11
500
79%
4.00
GasST2
6.09
500
83%
GasCT1+2
3.45
450
87%
GasST3
0.58
450
90%
3.00
GasCT5-Adv.
-
-
90%
GasCC4-Adv
(14.57)
800
96%
2.00
GasCCS-Adv
(14.72)
300
99%
GasCC2-New
(36.27)
200
100%
1.00
GasCC3-new
(37.05)
200
102%
GasCT3-new
(44.11)
350
104%
SasCT4-new
(46.28)
350
107%
0.00
0
10
20
30
40
50
60
70
80
90
100
bal-Adv.
(200.85)
50
108%
Percent of Period
Renewable
(415.33)
50
108%
SWH,6/9/97,6:38 PM
Page 1
RommAppF-2Tables.xds:HiEfflnput
Case ID
Hi Effic./Low Carbon
CAPITALIZAT IOU-Existing
IPP-Existing
IPP-New
IPP-Renew
Peak Season LDC
Peak Demand
11911.4734
Fuel Type
$/MMBTU kg C/MBTU
1
2
3
4
Season Peak Shoulder 2
Shoulder 1
Ratio of Off-peak to peak
88.1%
Gas
Min (100%)
2.59
14.47
Term (Years)
30
30
20
20 % of Season
0
6
95
100
Peak fraction of year
25%
Coal
1.34
25.72
Tax life
20
20
12
5 Template ratic
100%
93%
Load Factor, %
52%
41%
65.5%
Oil
3.00
21.49
Inc. Tax Rate
36%
36%
36%
36% Ratio to Peak
100%
93%
Peak Season Load Factor
52%
41%
72.6%
Nuclear
0.70
0 Prop. Tax rate
5%
5%
5%
5% Demand MW
11,911
11,108
Off-Peak Season Load Factor
6,223
71.7%
4,927
Hydro
0.00
0 Debt %
48%
30%
30%
30% Off-Peak Season LDC
Carbon Tax. $/netric ton C
50.00
Other
0.00
0 Interest Rate
8.0%
10.0%
10.0%
10.0% % of Season
0
2
96
100
Capacity Payment,$/kW
0 Year of Study
2010
Preferr Equity
14%
0%
0%
0% Template ratic
100%
86%
58%
51%
Uplift Charge, ckWh
0 Year of $
1995
Return Rale
10.0%
10.0%
10.0%
10.0% Ratio to Peak
100%
86%
58%
51%
Unserved Energy. c/kWh
0 Start-up Cost, $/MW
40 Common Equi
38%
70%
70%
70%
Demand MW
10,488
9,000
Non-generat. Price, c/kWh
6,105
5,305
3.18 Min Capacity w/ probab
0 Relum Rate
11.0%
14.0%
14.0%
14.0%
Price Elasticity(not used if 0)
0.05 Min Outage Rate w/ probab
0.0% Vary FCR by
TRUE
TRUE
FALSE
FALSE
Default Unserved E calc (always slew
Max # Plants with prob.
10 Include in Avo
FALSE
FALSE
TRUE
TRUE
Fractional change to start year
0.30
Capacity
Forced
Planned
Variable
Fixed
- Plant Construction
Capillization
Unavoidable
Varlable
Adjust Factor
Outage
Outage
Heat Rate
Fuel Price
O&M Cost
Bid Price or
O&M Cost
Nominal
Construction
Structure
Fixed Cost
Name
Cost
Capacity
(0 101)
Rate
Rate
(BTU/kWh)
Fuel Type
Adjustment
c/kwh
OP, c/kwh
$/kW-yr
Cost/kW
Year
Nuclear1
to Use const $kW-yr
c/kwh
1,000
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
800
1973
1
26
0.73
Nuclear2
800
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
2,750
1988
1
180
0.73
Coal1
900
1
7.0%
14.2%
9,600
Coal
0.833
0.21
OP
11.7
490
1983
1
26
2.51
Coal2
850
1
6.5%
8.8%
9,700
Coal
1.000
0.22
OP
11.7
370
1978
1
15
2.76
Coal3
850
1
6.5%
8.8%
9,800
Coal
1.000
0.22
OP
11.7
300
1973
1
10
2.79
Coal4
600
1
6.6%
10.3%
9,900
Coal
1.000
0.23
OP
12.4
680
1981
1
31
2.82
Coal5
600
1
6.6%
10.3%
10,000
Coal
1.000
0.24
OP
12.4
380
1960
1
0
2.86
Coal6+7
850
1
8.5%
12.3%
10,200
Coal
1.000
0.32
OP
15.2
500
1980
1
21
2.99
Coals
0
1
8.5%
12.3%
10,600
Coal
1.167
0.32
OP
15.2
300
1970
1
8
3.33
Coal9+10
0
1
6.4%
10.9%
11,200
Coal
1.167
0.35
OP
16.3
300
1970
1
8
3.53
Coal-Adv.
50
1
4.1%
12.3%
9,600
Coal
1.000
0.25
OP
33.6
1,816
2006
3
222
2.76
OII1
500
1
11.6%
5.2%
10,100
Oil
0.840
0.50
OP
6.0
127
1973
1
4
4.13
GasST1
600
1
9.7%
6.8%
10,000
Gas
0.951
0.13
OP
9.4
170
1976
1
6
3.31
GasST2
500
1
9.7%
6.8%
10,100
Gas
1.084
0.13
OP
9.4
150
1970
1
4
3.69
GasST3
450
1
9.7%
6.8%
10,200
Gas
1.111
0.13
OP
9.4
220
1967
1
0
3.80
GasCC1
300
1
6.8%
13.0%
9,665
Gas
0.951
0.10
OP
10.0
470
1992
2
45
3.18
GasCC2-New
200
1
5.5%
7.5%
7,760
Gas
1.000
0.05
OP
28.9
452
1999
3
55
2.62
GasCC3-new
200
1
5.5%
7.5%
7,618
Gas
1.000
0.05
OP
28.9
477
2001
3
58
2.57
GasCC4-Adv
450
1
5.5%
7.5%
6,284
Gas
1.000
0.05
OP
26.6
538
2005
3
66
2.13
GasCC5-Adv
950
1
5.5%
7.5%
5,817
Gas
1.000
0.05
OP
26.6
615
2009
3
75
1.98
GasCT1+2
450
1
10.0%
5.4%
12,800
Gas
0.969
0.22
OP
6.0
140
1986
1
9
4.35
GasCT3-new
350
1
3.6%
4.0%
11,460
Gas
1.000
0.01
OP
11.9
364
1998
3
44
3.80
GasCT4-new
350
1
3.6%
4.0%
10,873
Gas
1.000
0.01
OP
11.9
406
2002
3
50
3.61
GasCT5-Adv.
0
1
3.8%
3.9%
7,793
Gas
1.000
0.05
OP
16.9
542
2008
3
66
2.63
Renewable
50
1
25.0%
15.0%
10,280
Other
1.000
1.27
OP
65.5
2,361
2008
4
260
1.27
Limited Energy
Peak CF
Non-peak CF
Hydro
1,600
1
55.0%
40.0%
1028000.0%
Hydro
0.10
10
400
1957
1
0
0.10
Total Capacity
13,450
8WH,6/9/97,6:39 PM
Page 1
RommAppF-2Tables.xds:HiEffOutpurt
Hi Effic./Low Carbon
Peak
Offpeak # of Unprofitable plants
% of Total
Cap fact
Avoidable
Variable
Annual
season
season
Against avoid O&M
10
Capacity Generation
%
c/kWh
c/kWh
Reserve Margin
12.9%
12.9%
13.2%
Against all costs
15 w/ unservé
Hydro
11.9%
9.0%
43.8%
0.36
0.10
LOLP, % of period
0.17
0.40
0.10
Average Price, c/kWh
3.45
3.45
Nuclear
13.4%
18.4%
79.6%
2.02
0.73
LOLP, day/10 Year
6.34
14.58
3.59
Avg. Variable Cost
2.07
2.07
Coal
34.9%
46.2%
76.8%
3.00
2.77
Load factor
65.5%
72.6%
71.7% Avg. Vari+Avoid O&M
2.80
2.81
Oil
3.7%
0.1%
0.9%
13.45
5.58
Peak Demand, MW
11,911
11,911
10,488
Total Cost
3.21
3.21
Gas-ST
11.5%
3.3%
16.5%
4.12
3.47
Energy, GWh
68,373
18,949
49,424
Max loss, $/avall kW
(359.93)
Gas-CC
15.6%
21.8%
80.9%
3.41
2.23
Generation, GWh
68,350
18,945
49,405
Start-up Cost, $/MW
40
Gas-CT
6.6%
0.9%
6.4%
10.59
3.78
Unserved Energy, G'
6
4
2 # plants Probabilistic
9
Other
0.4%
0.4%
60.0%
7.47
1.27
Round em not in UE
18
0
17
Plant
Output
Capac
Time on
Revenue Var. +Start Avoidable Unavoidable
Total Net
Avoidable Net Rev
Avoidable Carbon release
Name
Capacity
MWyr
Factor
Margin, %
MS
Cost MS xd Cst MS
Fxd Cst MS
Rev MS
MS
$/kW
cost,
c/kWh
Million Tons
Nucleart
1,000
796.00
79.6%
0.00
234
51
90
26
67
93.00
116.84
2.02
0.00
Nuclear2
800
636.80
79.6%
0.00
187
41
72
144
(70)
74.40
116.84
2.02
0.00
Coal1
900
709.20
78.8%
0.00
209
156
11
23
19
41.94
59.14
2.68
1.53
Coal2
850
719.20
64.6%
0.32
211
174
10
13
15
27.47
38.15
2.92
1.57
Coat3
850
713.96
84.0%
1.30
210
174
10
8
17
25.82
35.87
2.95
1.58
Coal4
600
479.35
79.9%
3.75
142
119
7
18
(3)
15.80
31.68
3.00
1.07
Coal5
600
454.18
75.7%
8.52
136
114
7
0
14
14.31
28.70
3.05
1.02
Coal6+7
850
490.19
57.7%
25.20
151
129
13
18
(8)
9.83
14.60
3.29
1.13
Coal8
0
-
0.0%
0.00
.
-
-
-
-
-
.
0.00
0.00
Coal9+10
0
-
0.0%
0.00
-
-
-
-
-
-
-
0.00
0.00
Coal-Adv.
50
41.64
83.3%
0.04
12
10
13
-
(11)
(10.59)
(253.46)
6.26
0.09
Oil1
500
4.35
0.9%
0.96
4
2
3
2
(4)
(1.59)
(3.83)
13.45
0.01
GasST1
600
188.70
31.5%
24.18
64
55
6
4
(0)
3.40
6.79
3.65
0.24
GasST2
500
47.81
9.6%
8.38
20
16
5
2
(3)
(0.71)
(1.69)
4.86
0.06
GasST3
450
19.32
4.3%
4.00
9
7
4
0
(2)
(2.05)
(5.44)
6.81
0.02
GasCC1
300
132.15
44.1%
11.09
43
37
3
14
(11)
2.79
11.60
3.44
0.16
GasCC2-New
200
174.00
87.0%
0.00
51
40
17
-
(6)
(5.59)
(32.15)
3.72
0.17
GasCC3-new
200
174.00
87.0%
0.00
51
39
17
-
(5)
(5.50)
(31.58)
3.72
0.17
GasCC4-Adv
450
391.50
87.0%
0.00
115
73
42
-
0
0.46
1.18
3.34
0.31
GasCC5-Adv
950
826.50
87.0%
0.00
243
143
97
-
3
3.33
4.03
3.31
0.61
GasCT1+2
450
1.37
0.3%
0.40
2
1
3
4
(5)
(1.58)
(4.14)
28.97
0.00
sCT3-new
350
7.62
2.2%
1.78
5
3
20
-
(18)
(18.27)
(56.49)
34.28
0.01
sCT4-new
350
64.64
18.5%
9.93
24
20
22
-
(18)
(17.89)
(55.32)
7.41
0.09
asCT5-Adv.
0
-
0.0%
0.00
-
-
-
1
-
,
-
0.00
0.00
Renewable
50
30.00
60.0%
0.00
9
3
16
-
(11)
(10.80)
(359.93)
7.47
0.00
Hydro
1,600
700.00
43.8%
224
6
16
0
201
201.45
125.90
0.36
0.00
Totals
13,450
7,802
58%
2,355
1,413
502
277
163
439
9.85
Avoidable
Total
Unserved Energy
0.65
3
3
w/o UE
1,915
2,192
Avg. Carbon kg/MWhr
144
Totals w/ Unserved
7,803
2,358
1,416
w/ UE
1,919
2,195
Time wid marginal cost
3.34
Time wid Unserv E Price
23.44
Unserv E. Cost/kWh
57.52
Sort by Net Revenue/kW
Price increase to pay avoided losses
0.11
Avoidable
Reserve
Name
Net Rev/kW
Capacity
Margin
Marginal Power Costs and Prices
Hydro
125.90
1,600
13%
10.00
Nuclear2
116.84
800
20%
Nuclear1
116.84
1,000
29%
9.00
Coal1
59.14
900
36%
Peak Season Cost
Coal2
38.15
850
43%
Peak Season Price
6.00
Coal3
35.87
850
50%
Off-Season Cost
Coal4
31.68
600
55%
Off-Season Price
Coal5
26.70
600
60%
7.00
Coal6+7
14.60
850
68%
GasCC1
11.60
300
70%
6.00
GasST1
6.79
600
75%
GasCC5-Adv
4.03
950
83%
GasCC4-Adv
1.18
C/KWH
5.00
450
87%
Coals
-
.
87%
Coal9+10
-
-
87%
4.00
GasCT5-Adv.
-
-
87%
GasST2
(1.69)
500
91%
3.00
Oil1
(3.83)
500
95%
GasCT1+2
(4.14)
450
99%
2.00
GasST3
(5.44)
450
103%
GasCC3-new
(31.58)
200
105%
1.00
GasCC2-New
(32.15)
200
106%
GasCT4-new
(55.32)
350
109%
GasCT3-new
(56.49)
350
112%
0.00
50
112%
0
10
20
30
40
50
60
70
(253.46)
80
90
100
al-Adv.
Percent of Period
newable
(359.93)
50
113%
SWH,6/9/97,6:39 PM
Page 1
RommAppF-2Tables.xis:AlTechinput
Case ID
Alt. Technology
CAPITALIZAT IOU-Existing
IPP-Existing
IPP-New
IPP-Renew
Peak Season LDC
Peak Demand
14134.3982
Fuel Type
$/MMBTU kg C/MBTU
1
2
3
4
Season Peak Shoulder 2
Shoulder 1
Min (100%)
Ratio of Off-peak to peak
88.7%
Gas
2.59
14.47
Term (Years)
30
30
20
20 % of Season
0
5
95
100
Peak fraction of year
25%
Coal
1.34
25.72
Tax life
20
20
12
5 Template ratic
100%
94%
53%
42%
Load Factor, %
65.7%
Oil
3.00
21.49
Inc. Tax Rate
36%
36%
36%
36% Ratio to Peak
100%
94%
53%
42%
Peak Season Load Factor
73.0%
Nuclear
0.70
0 Prop. Tax rate
5%
5%
5%
5% Demand MW
14,134
13,226
7,452
5,887
Off-Peak Season Load Factor
71.3%
Hydro
0.00
0 Debt %
48%
30%
30%
30% Off-Peak Season LDC
Carbon Tax, $/netric ton C
0.00
Other
0.00
0 Interest Rate
8.0%
10.0%
10.0%
10.0% % of Season
0
2
96
100
Capacity Payment,$/kW
0 Year of Study
2010
Preferr Equity
14%
0%
0%
0% Template ratic
100%
85%
58%
50%
Uplift Charge, </kWh
0 Year of $
1995
Return Rate
10.0%
10.0%
10.0%
10.0% Ratio to Peak
100%
85%
58%
50%
Unserved Energy, c/kWh
0 Start-up Cost, $/MW
40 Common Equi
38%
70%
70%
70%
Demand MW
12,538
10,707
7,242
6,225
Non-generat. Price, c/kWh
3.18 Min Capacity w/ probab
0 Return Rate
11.0%
14.0%
14.0%
14.0%
Price Elasticity(not used If 0)
0.05 Min Outage Rate w/ probab
0.0% Vary FCR by)
TRUE
TRUE
FALSE
FALSE
Default Unserved E calc (always sllow
Max # Plants with prob.
10 Include in Avo
FALSE
FALSE
TRUE
TRUE
Fractional change to start year
0.30
Capacity
Forced
Planned
Variable
Fixed
- Plant Construction -
Capilization
Unavoidable
Variable
Adjust Factor
Outage
Outage
Heat Rate
Fuel Price
O&M Cost
Bid Price or
O&M Cost
Nominal
Construction
Structure
Fixed Cost
Cost
Name
Capacity
(0 to1)
Rate
Rate
(BTU/kWh)
Fuel Type
Adjustment
c/kwh
OP, c/kwh
$/kW-yr
Cost/kW
Year
to Use const $/kW-yr
c/kwh
Nuclear1
1,000
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
800
1973
1
26
0.73
Nuclear2
800
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
2,750
1988
1
180
0.73
Coal1
900
1
7.0%
14.2%
9,600
Coal
0.833
0.21
OP
11.7
490
1983
1
26
1.28
Coal2
850
1
6.5%
8.8%
9,700
Coal
1.000
0.22
OP
11.7
370
1978
1
15
1.51
Coal3
850
1
6.5%
8.8%
9,800
Coal
1.000
0.22
OP
11.7
300
1973
1
10
1.53
Coal4
600
1
6.6%
10.3%
9,900
Coal
1.000
0.23
OP
12.4
680
1981
1
31
1.55
Coal5
600
1
6.6%
10.3%
10,000
Coal
1.000
0.24
OP
12.4
380
1960
1
0
1.58
Coal6+7
850
1
8.5%
12.3%
10,200
Coal
1.000
0.32
OP
15.2
500
1980
1
21
1.68
Coals
450
1
8.5%
12.3%
10,600
Coal
1.167
0.32
OP
15.2
300
1970
1
8
1.97
Coal9+10
450
1
6.4%
10.9%
11,200
Coal
1.167
0.35
OP
16.3
300
1970
1
8
2.09
Coal-Braltch
50
1
4.1%
12.3%
6,805
Coal
1.000
0.20
OP
26.0
1,377
2005
3
168
1.11
Oil1
500
1
11.6%
5.2%
10,100
Oil
0.840
0.50
OP
6.0
127
1973
1
4
3.05
GasST1
600
1
9.7%
6.8%
10,000
Gas
0.951
0.13
OP
9.4
170
1976
1
6
2.59
GasST2
500
1
9.7%
6.8%
10,100
Gas
1.084
0.13
OP
9.4
150
1970
1
4
2.96
GasST3
450
1
9.7%
6.8%
10,200
Gas
1.111
0.13
OP
9.4
220
1967
1
0
3.06
GasCC1
300
1
6.8%
13.0%
9,665
Gas
0.951
0.10
OP
10.0
470
1992
2
45
2.48
GasCC2-Now
550
1
5.5%
7.5%
7,760
Gas
1.000
0.05
OP
28.9
452
1999
3
55
2.06
GasCC3-new
200
1
5.5%
7.5%
7,618
Gas
1.000
0.05
OP
28.9
477
2001
3
58
2.02
GasCC4-Brai
800
1
5.5%
7.5%
5,688
Gas
1.000
0.015
OP
16.0
689
2005
3
84
1.49
GasCC5-Brai
900
1
5.5%
7.5%
5,538
Gas
1,000
0.015
OP
16.0
774
2010
3
95
1.45
GasCT1+2
450
1
10.0%
5.4%
12,800
Gas
0.969
0.22
OP
6.0
140
1986
1
9
3.42
GasCT3-new
350
1
3.6%
4.0%
11,460
Gas
1.000
0.01
OP
11.9
364
1998
3
44
2.98
GasCT4-Bral
350
1
3.8%
4.0%
8,699
Gas
1.000
0.012
OP
17.6
525
2005
3
64
2.26
GasCT5-Bral
0
1
3.8%
3.9%
8,533
Gas
1.000
0.012
OP
17.6
564
2010
3
69
2.22
Renewable
50
1
25.0%
15.0%
10,280
Other
1.000
1.27
OP
65.5
2,361
2008
4
260
1.27
Limited Energy
Peak CF
Non-peak CF
Hydro
1,600
1
55.0%
40.0%
Hydro
0.10
10
400
1957
1
0
0.10
Total Capacity
15,000
SWH,6/9/97,6:40 PM
Page 1
RommAppF-2Tables.xds:AltTechOuput
Alt. Technology
Peak
Offpeak # of Unprofitable plants
% of Total
Cap
fact
Avoidable
Variable
Annual
season
season
Against avoid O&M
8
Capacity Generation
%
c/kWh
c/kWh
Reserve Margin
6.1%
6.1%
5.3%
Against all costs
10 w/ unserve
Hydro
10.7%
7.5%
43.8%
0.36
0.10
LOLP. % of period
1.14
2.55
0.66 Average Price, c/kWh
2.89
2.91
Nuclear
12.0%
15.4%
79.6%
2.02
0.73
LOLP. day/10 Year
41.49
93.21
24.25
Avg. Variable Cost
1.42
1.45
Coal
37.3%
47.7%
79.0%
1.79
1.58
Load factor
65.6%
73.0%
71.3%
Avg. Vari+Avoid O&M
2.15
2.18
OIl
3.3%
0.3%
5.7%
4.59
3.39
Peak Demand, MW
14,134
14,134
12,538
Total Cost
2.50
252
Gas-ST
10.3%
3.0%
17.9%
3.36
2.76
Energy. GWh
81,326
22,607
58,720
Max loss, $/avall kW
(414.51)
Gas-CC
18.3%
23.1%
78.0%
2.98
1.67
Generation, GWh
81,282
22,580
58,702
Start-up Cost, $/MW
40
Gas-CT
7.7%
2.6%
20.7%
4.90
2.45
Unserved Energy, G'
44
27
18 # plants Probabilistic
10
Other
0.3%
0.3%
60.0%
7.47
1.27
Round err not in UE
(0)
(0)
(0)
Plant
Output
Capac
Time on
Revenue Var. +Start Avoidable Unavoidable
Total Net
Avoidable Net Rev
Avoidable
Carbon release
Name
Capacity
MWyr
Factor
Margin, %
MS
Cost
MS
xd
Cst
MS
Fxd Cst M$
Rev MS
M$
$/kW
cost,
c/kWh
Million Tons
Nucleart
1,000
796.00
79.6%
0.00
190
51
90
26
23
49.10
61.69
2.02
0.00
Nuclear2
800
636.80
79.6%
0.00
152
41
72
144
(105)
39.28
61.69
2.02
0.00
Coal1
900
709.20
78.8%
0.00
170
79
11
23
56
79.64
112.30
1.45
1.53
Coat2
850
719.95
84.7%
0.00
172
96
10
13
54
66.23
91.99
1.67
1.57
Coal3
850
719.70
84.7%
0.16
172
96
10
6
57
65.38
90.82
1.69
1.59
Coal4
600
496.76
82.8%
0.32
119
68
7
18
25
43.79
87.82
1.72
1.11
Coal5
600
494.59
82.4%
0.66
118
68
7
0
43
42.77
85.79
1.75
1.11
Coal6+7
850
650.83
76.6%
3.73
158
96
13
18
31
48.83
72.54
1.91
1.50
Coals
450
331.98
73.8%
2.83
81
57
7
3
14
17.31
48.57
221
0.79
Coal9+10
450
261.37
58.1%
11.74
70
48
7
3
11
14.36
38.58
2.41
0.66
Coal-Braitch
50
41.80
83.6%
0.00
10
4
10
(4)
(3.78)
(90.46)
3.76
0.06
Oil1
500
28.64
5.7%
4.50
17
9
3
2
4
5.92
14.24
4.59
0.05
GasST1
600
179.04
29.8%
18.47
58
41
6
4
8
11.39
22.74
2.95
0.23
GasST2
500
85.25
17.1%
10.80
33
22
5
2
4
5.87
14.05
359
0.11
GasST3
450
13.87
3.1%
2.59
12
5
4
0
3
3.27
8.70
7.25
0.02
GasCC1
300
117.82
39.3%
8.45
35
26
3
14
(7)
6.40
26.60
2.77
0.14
GasCC2-New
550
392.25
71.3%
11.87
100
71
46
(17)
(17.39)
(36.33)
3.40
0.39
GasCC3-new
200
156.44
78.2%
4.06
39
28
17
(6)
(6.45)
(37.06)
3.29
0.15
GasCC4-Braitch
800
696.00
87.0%
0.00
166
91
80
-
(5)
(4.79)
(6.88)
2.80
0.50
GasCC5-Braitch
900
783.00
87.0%
0.00
187
99
99
-
(12)
(12.16)
(15.53)
2.90
0.55
SasCT1+2
450
6.21
1.4%
1.18
9
3
3
4
0
4.18
10.96
9.57
0.01
sCT3-new
350
40.82
11.7%
6.28
19
11
20
-
(12)
(11.74)
(36.29)
8.49
0.06
scT4-Braitch
350
190.48
54.4%
11.23
53
38
29
-
(13)
(13.07)
(40.41)
3.98
0.21
GasCT5-Braitch
0
-
0.0%
0.00
.
-
,
-
0.00
0.00
Renewable
50
30.00
60.0%
0.00
7
3
16
-
(12)
(12.44)
(414.51)
7.47
0.00
Hydro
1,600
700.00
43.8%
201
6
16
0
178
178.46
111.54
0.36
0.00
Totals
15,000
9,279
62%
2,346
1,154
591
264
317
600
12.35
Avoidable
Total
Unserved Energy
5.06
24
24
w/o UE
1,745
2,029
Avg. Carbon kg/MWhr
152
Totals w/ Unserved
9,284
2,370
1,178
w/ UE
1,770
2,053
Time wtd marginal cost
261
Time wid Unserv E Price
21.69
Unserv E Cost/kWh
54.37
Sort by Net Revenue/kW
Price increase to pay avoided losses
0.10
Avoidable
Reserve
Name
Net Rev/kW
Capacity
Margin
Marginal Power Costs and Prices
Coal1
112.30
900
6%
10.00
Hydro
111.54
1,600
16%
Coal2
91.99
850
24%
9.00
Coal3
90.82
850
30%
Peak Season Cost
Coal4
87.82
600
34%
Pask Season Price
8.00
Coal5
85.79
600
38%
Off-Seeson Cost
Coal6+7
72.54
850
44%
Off-Season Price
Nucleart
61.69
1,000
51%
7.00
Nuclear2
61.69
800
57%
Coal6
48.57
450
60%
6.00
Coal9+10
38.58
450
63%
GasCC1
26.60
300
65%
600
#/kWH
5.00
GasST1
22.74
70%
O#1
14.24
500
73%
GasST2
14.05
500
77%
4.00
GasCT1+2
10.98
450
80%
GasST3
8.70
450
83%
3.00
GaeCT5-Braitch
.
-
83%
GasCC4-Braltch
(6.88)
800
89%
2.00
GasCC5-Braitch
(15.53)
900
95%
GasCT3-new
(36.29)
350
98%
1.00
GasCC2-New
(36.33)
550
102%
GasCC3-new
(37.06)
200
103%
SasCT4-Braitch
(40.41)
350
105%
0.00
al-Braitch
(90.46)
50
106%
0
10
20
30
40
50
60
70
60
90
100
Percent of Period
newable
(414.51)
50
106%
SWH,6/9/97.6:41 PM
Page 1
DRAFT
6/10/97
APPENDIX F-2
INPUTS AND OUTPUTS OF THE 2010 ELECTRICITY SECTOR SCENARIOS
F-2.1
Case ID
2610 ARO
CAPITALIZAT IDU-Exteing
PP-Ealing
PP.New
P.Renew
Peak Beeson LDC
Total MYY,
Pook Demand
1486,1517
Fuel Type
SAMMITU be CARITU
2
a
4
Beason Pash Shoulder a
Shoulder
Min (100%)
0.223
Police OR pock to pouk
87.0%
Area under template surves
One
1.00
14.47 Term (Years)
20
so
Energy
.
Land Factor Adjust Factor Templete Annual LF
29 Season
0
$
"
100
Pack
470
Pack baction of year
N%
02 78 78
221
Cod
17.43
1.24
MYS
Tex
" 7th
the
0
"
to
# n
12
8 Templete -
100%
N%
4%
30%
OR Pack
1 63
Load Factor, %
"N
--
OR
100
4837
2.00
21 00 ins Tax Park
30%
64.9%
É
0.17948-17
20%
20%
30% Role Pook
100%
$
-
&
MWSeases
Pask Season Load actor
80.7%
Muslear
8.78
0 Pres. Tem rete
60.9%
5%
0%
"
1% Demand MW
14,648
13,257
7223
5,754
10.239
OF Peek Seeson and Factor
00.9%
Hydro
are
0 Debt %
40%
sex
$
- OR Peck - LDC
Carbon Tax Shorts - c
0.00
Other
0.00
0 Interest Rate
1.0%
10.0%
NOT
10.0% % of learn
0
2
98
100
Capacity Payment SAW
0 Yes of Study
3018
Proten Each
14%
E
5
0% Terrefale -
100%
17%
N%
any
Lipits Charge, Minh
0 Year
1998
Return Rate
10.9%
10.0%
18.0%
19.0% Rate Pook
100%
are
M%
or
Unserved Energy. with
0 Start-up Cost, SAIW
40 Common Em
30%
E
70%
70% Demand MW
12,002
10.736
7,100
1.094
1844
Non-genest Price, Minh
210 Min Capacity of probab
0 Return Rate
11.0%
14.0%
14 0%
14.0%
Price Eleaticitying used 04
are Min Cutage Rate - probab
a.o% Very FOR by
TRUE
TRUE
TRUE
TRUE
Delault Unserved E cok (always - with prob
10 Include h Avt
FALSE
FALSE
FALSE
FALSE
Proctional change to - year
020
DATA TO DISPATCH
Capacity
Forced
Planned
Veriable
Fined
Off-pesk period
Plant Construction
Capilization
Univelsable
Variable
Forced
Planned
Adjust Factor
Cutage
Outage
Heat Rete
Pust Price
Avaidable
can Cast
IN Price -
O&M Cost
Univoidable
0 75
Nominal Construction
Flood Cost
Cast
be Price
Capacity
Cutage
Name
RWD
Rete
Rate
STUDEN
Pvel Type
Cutage Pook Bettern Carbon Over Variable Cost Food Dest
Road Cost
Advatment
sich
OP shah
OF Season
saw-w
Copyte
Yes
Use senel MW-p
grinch
Number
Name
show
Relp
Huclear
Rate Capacity
1,000
,
8.2%
12.2%
sawn
MW-W
16,400
Nuclear
1,000
0.00
OP
Capacity
90 0
800
1973
I
26
073
I Nuclear |
073
n
12%
1,000
0
Muclear 2
800
8.7%
078
123%
90 00
8
10,000
Nuclear
1.000
$ 00
OP
26
223
00.0
2,750
1988
180
073
2
073
"
12%
800
Coul1
use
0
7.0%
0.78
14.2%
80 00
0,000
Cod
0.033
8.21
OP
100
058
11.7
400
1883
26
128
3 Cost
129
7
14%
150
247
Comil
sse
1.20
ask
11.70
as
0,700
Cod
1.008
0.22
OP
28
787
11.7
378
1078
IS
181
4 Coall
131
7%
(
850
Coal)
use
240
181
0.0%
S.FR
1170
2,000
Cod
OP
IS
1,000
0.22
743
11.7
200
1973
10
193
a Costs
183
PM
#
850
Costs
are
0.0%
252
153
10.3%
8,800
11.70
Cod
1,000
0.23
OP
to
12.4
743
600
1941
31
183
0 Costs
168
7%
10%
800
Costs
soe
256
1.58
0.0%
10.3%
10,000
Cod
1.000
0.24
OP
12.40
$1
12.4
$12
200
1900
0
150
, Coold
150
*
10%
600
ComM+7
-
237
0.5%
1.50
12.3%
10,300
Cod
12.40
1,000
a.22
OP
0
15.2
812
see
1000
21
1.00
0 Coals.7
168
-
12%
Could
454
850
0.5%
202
1.00
12.7%
1.107
15 30
10,000
Cod
6.22
OP
21
004
182
300
1970
a
197
, Coals
197
n
12%
-
Coal6-18
see
273
197
are
10.0%
11,300
Cod
1.197
0.38
OP
16 20
.
16.3
see
300
1978
a
$ 00
10 Come.10
200
:
11%
i
Cost- Mr.
400
4.1%
200
200
12.3%
0,000
Cod
1 000
0.25
OP
16.30
8
23.8
300
1,810
2008
9
ETT
133
11 Cost-Adv
133
C
12%
see
400
OR1
247
11.0%
1.93
8.2%
10,100
os
83 63
****
277
a.so
OP
232
se
127
1979
.
3.05
12 Oil
3 08
12%
t
see
One ST1
217
see
are
$ 00
are
0.00
4
10,000
-
0.051
Q 13
OP
461
0.4
170
1970
#
111
13 GesST:
199
10%
L
600
GaeST2
are
145
87%
250
8.5%
18,100
940
Gas
1,004
0.13
OP
8
S40
0.4
130
1970
4
111
14 One STE
114
10%
7%
see
-
140
8.7%
2.00
0.40
a.ex
God
4
10,300
1.111
a 13
OP
-
9.4
220
1987
.
300
IS
108
10%
#
400
QueCC1
148
300
s os
6.8%
04
13.0%
0,000
Chas
0.001
.
0.10
OP
406
10.0
478
1962
45
1.40
18 OseCCI
140
7%
13%
300
QaeCC2-Nee
-
140
8.5%
2.40
7.8%
98.00
-
7,700
-
1,000
0.00
OP
244
20.0
402
1900
-
100
17 CasCC2 Has
200
(
t
i
112
GaeCC3-nes
420
as
2.00
7.0%
--
-
7,019
One
1,000
0.00
OP
STO
20.0
477
2001
M
202
10 0asCC3-new
2 02
É
É
&
110
DasCCA-Ade
are
a.e%
202
7.8%
0,204
20.00
-
-
1,000
370
0.00
OP
20 $
830
2006
70
144
10 OseCCA-Adv
1.00
:
t
&
01
1 00
are
8.8%
7.0%
8,017
Ches
20.00
&
STO
1,000
0.00
OF
20.6
615
2000
ICS
155
20 Ome CCS-Adv
188
(
É
600
04
QaeCT1e3
1 56
400
10.0%
8.4%
20.00
12,000
Gas
100
B37
6,000
a.22
OP
"
148
1946
0
3.42
21 QeeCT1.2
$ 42
10%
8%
-
108
141
QaeCTS-now
ase
0 00
.
10%
414
4.0%
11,000
Gas
1,000
0.01
OP
11.8
204
1090
36
196
22 GmsCT 3-mail
1 00
C
t
me
100
QaeCT4-new
ass
2.00
3.0%
11.02
4.0%
=
Gos
014
10,073
1,000
0.01
OP
11.0
808
2002
9
so
183
23 OneCT 4-now
183
-
⑆
ase
187
100
QaeCT6-Adv
ase
1.8%
2.0%
11.02
so
7,793
Date
014
1,000
0.00
OP
10.9
542
2000
as
207
24 OneCTS Adv.
107
(
#
-
113
207
10 02
Renewable
-
250
***
ass
16.0%
10,200
Other
1,000
1.27
OP
06.8
2,341
2000
4
351
127
= Renewable
127
25%
18%
210
.
1.87
Pack OF
68.40
Limited Enery Capacity, MW
361
183
Non-pook CF
29 Hydre
$10
M3
$
1,000
.
0.10
10 00
9
1,000
Hydro
1,000
1
06.0%
40.0%
Hydro
are
10
400
1947
$
0
010
10.200
and Capacity
14,200
14.329
year
1990
1991
1992
1993
1994
1998
1994
1997
1998
1999
2000
2001
some
2003
2004
2008
2004
2007
1000
2000
2018
2011
2018
2013
OOP dellarer
1.127
2014
2018
1.171
1.203
1.225
1.303
1.206
1328
1.367
1.390
1.420
LMS
1.500
1.548
1.504
L046
1.000
1.794
1.014
1075
1.920
2.006
2077
2148
1987-100
0.040
2.224
2.308
2.300
PM
Page
RommAppF-2Tables.xds:AEOOutput
2010 AEO
Peak
Offpeak # of Unprofitable plants
% of Total
Cap fact
Avoidable
Variable
Annual
season
season
Against avoid O&M
8
Capacity Generation
%
e/kWh
e/kWh
Reserve Margin
10.7%
10.7%
11.2%
Against all costs
16 w/ unserve
Hydro
9.5%
7.6%
43.8%
0.36
0.10
LOLP. % of period
0.13
0.34
0.07
Average Price, e/kWh
2.50
2.50
Nuclear
11.1%
15.5%
79.6%
2.02
0.73
LOLP. day/10 Year
4.90
12.40
2.41
Avg. Variable Cost
1.43
1.43
Coal
36.9%
50.8%
78.0%
1.78
1.57
Load factor
62.8%
69.7%
68.9%
Avg. Vari+Avoid O&M
1.90
1.90
Oil
3.1%
0.1%
1.0%
11.59
4.44
Peak Demand, MW
14,685
14,685
12,892
Total Cost
2.81
2.81
Gas-ST
9.5%
1.8%
10.7%
3.74
2.74
Energy. GWh
80,793
22,423
58,370
Max loss, $/avail kW
(9.71)
Gas-CC
13.3%
17.2%
73.6%
2.21
1.82
Generation, GWh
80,790
22,419
58,371
Start-up Cost, $/MW
40
Gas-CT
14.8%
5.4%
20.7%
2.93
2.26
Unserved Energy. G
5
3
2
# plants Probabilistic
10
Other
1.5%
1.6%
60.0%
2.51
1.27
Round BIT not in UE
(2)
1
(2)
Plant
Output
Capac
Time on
Revenue Var. +Start Avoidable Unavoidable
Total Net
Avoidable Net Rev
Avoidable Carbon release
Name
Capacity
MWyr
Factor
Margin, %
MS
Cost
MS
xd
Cst
MS
Fxd Cst MS
Rev MS
MS
$/kW
cost,
e/kwh
Million Tons
Nucleart
1,000
796.00
79.6%
0.00
166
51
90
26
0
26.91
33.60
2.02
0.00
Nuclear2
800
636.80
79.6%
0.00
134
41
72
144
(122)
21.53
33.80
2.02
0.00
Coal1
950
748.60
78.8%
0.00
158
84
11
25
39
63.07
84.25
1.45
1.62
Coal2
850
719.95
84.7%
0.00
152
96
10
13
34
46.38
64.42
1.67
1.57
Coat3
850
719.95
84.7%
0.00
152
96
10
8
37
45.53
63.25
1.69
1.59
Coal4
600
498.60
83.1%
0.00
105
68
7
18
12
29.98
60.12
1.72
1.11
Coals
600
495.96
82.7%
0.40
105
68
7
o
29
28.96
58.08
1.75
1.12
Coal6+7
850
648.28
76.3%
3.70
138
96
13
18
12
30.02
44.59
1.91
1.49
Coal8
450
330.48
73.4%
2.86
71
57
7
3
4
7.39
20.73
2.21
0.79
Coal9+10
450
186.72
41.5%
12.44
46
34
7
3
1
4.29
11.53
2.54
0.47
Coal-Adv.
400
334.40
83.6%
0.00
71
45
13
111
(98)
12.31
36.82
1.99
0.72
Oill
500
4.79
1.0%
0.88
3
2
3
2
(4)
(2.07)
(4.97)
11.59
0.01
GasST1
600
137.54
22.9%
16.52
38
31
6
4
(3)
0.80
1.59
3.06
0.17
GasST2
500
25.92
5.2%
3.81
10
8
5
2
(5)
(2.68)
(6.42)
5.43
0.03
GasST3
450
2.06
0.5%
0.39
2
1
4
0
(3)
(3.49)
(9.29)
28.31
0.00
GasCC1
300
96.17
32.1%
8.17
25
21
3
14
(13)
0.98
4.05
2.83
0.12
GasCC2-New
420
290.81
69.2%
8.93
64
52
12
20
(20)
(0.06)
(0.17)
2.53
0.29
GasCC3-new
420
321.04
76.4%
7.46
70
57
12
23
(22)
0.93
2.53
2.45
0.31
GasCC4-Adv
420
361.45
86.1%
0.90
77
53
11
32
(20)
12.28
33.61
2.03
0.29
GasCC5-Adv
600
$21.31
86.9%
0.27
110
71
16
65
(42)
23.04
44.13
1.90
0.38
GasCT1+2
450
0.88
0.2%
0.21
1
0
3
4
(6)
(2.06)
(5.41)
40.68
0.00
GasCT3-new
650
17.37
2.7%
2.76
8
6
8
24
(29)
(5.83)
(9.71)
8.86
0.03
GasCT4-new
650
81.59
12.6%
11.27
25
20
8
33
(35)
(2.53)
(4.22)
3.91
0.11
GasCT5-Adv.
650
395.92
60.9%
18.88
91
72
11
58
(49)
8.44
14.06
2.38
0.39
Renewable
250
150.00
60.0%
0.00
32
17
16
88
(89)
(1.35)
(8.97)
2.51
0.00
Hydro
1,600
700.00
43.8%
166
6
16
0
144
143.86
89.91
0.36
0.00
Totals
16,260
9,223
57%
2,021
1,152
382
739
(252)
487
12.62
Avoidable
Total
Unserved Energy
0.54
2
2
w/o UE
1,534
2,273
Avg. Carbon kg/MWhr
156
Totals w/ Unserved
9,223
2,022
1,154
w/ UE
1,536
2,274
Time wid marginal cost
2.40
Time wid Unserv E Price
18.94
Unserv E. Cost/kWh
38.42
Sort by Net Revenue/kW
Price Increase to pay avoided losses
0.02
Avoidable
Reserve
Name
Net Rev/kW
Capacity
Margin
Marginal Power Costs and Prices
Hydro
89.91
1,600
11%
10.00
Coal1
84.25
950
17%
Coal2
64.42
850
23%
9.00
Coal3
63.25
850
29%
Peak Season Cost
Coal4
60.12
600
33%
Peak Season Price
8.00
Coal5
58.08
600
37%
Off-Season Cost
Coal6+7
44.59
850
43%
Off-Season Price
GasCC5-Adv
44.13
600
47%
7.00
Coal-Adv.
36.82
400
50%
Nucleart
33.80
1,000
57%
6.00
Nuclear2
33.80
800
62%
GasCC4-Adv
33.61
420
65%
Coal8
68%
#/kWH
5.00
20.73
450
GasCT5-Adv.
14.06
650
72%
4.00
Coal9+10
11.53
450
75%
GasCC1
4.05
300
77%
GasCC3-new
2.53
420
80%
3.00
GasST1
1.59
600
84%
GasCC2-New
(0.17)
420
87%
2.00
GasCT4-new
(4.22)
650
92%
Oilt
(4.97)
500
95%
1.00
GasCT1+2
(5.41)
450
98%
GasST2
(6.42)
500
102%
0.00
Renewable
(8.97)
250
103%
0
10
20
30
40
50
60
70
80
90
100
GasST3
(9.29)
450
106%
Percent of Period
GasCT3-new
(9.71)
650
111%
SWH,6/9/97,6:05 PM
Page 1
RommAppF-2Tables.
cinput
Case ID
Restructure case
CAPITALIZAT IOU-Existing
IPP-Existing
IPP-New
IPP-Renew
Peak Season LDC
Peak Demand
14188.3366
Fuel Type
$/MMBTU kg C/MBTU
1
2
3
4
Season Peak
Shoulder
2
Shoulder 1
Min (100%)
Ratio of Off-peak to peak
88.7%
Gas
2.59
14.47
Term (Years)
30
30
20
20 % of Season
0
5
95
100
Peak fraction of year
25%
Coal
1.34
25.72
Tax life
20
20
12
5 Template ratic
100%
94%
53%
42%
Load Factor, %
65.8%
Oil
3.00
21.49
Inc. Tax Rate
36%
36%
36%
36% Ratio to Peak
100%
94%
53%
42%
Peak Season Load Factor
73.1%
Nuclear
0.70
0 Prop. Tax rate
5%
5%
5%
5% Demand MW
14,188
13,276
7,491
5,918
Off-Peak Season Load Factor
71.4%
Hydro
0.00
0 Debt %
48%
30%
30%
30% Off-Peak Season LDC
Carbon Tax, $/netric ton C
0.00
Other
0.00
0 Interest Rate
8.0%
10.0%
10.0%
10.0% % of Season
0
2
96
100
Capacity Payment,$/kW
0 Year of Study
2010
Preferr Equity
14%
0%
0%
0% Template ratic
100%
85%
58%
50%
Uplift Charge, c/kWh
0 Year of $
1995
Return Rate
10.0%
10.0%
10.0%
10.0% Ratio to Peak
100%
85%
58%
50%
Unserved Energy. e/kWh
0 Start-up Cost, $/MW
40 Common Equi
38%
70%
70%
70%
Demand MW
12,589
10,755
7,285
6,285
Non-generat. Price, c/kWh
3.18 Min Capacity w/ probab
0 Return Rate
11.0%
14.0%
14.0%
14.0%
Price Elasticity(not used If 0)
0.05 Min Outage Rate w/ probab
0.0% Vary FCR by
TRUE
TRUE
FALSE
FALSE
Default Unserved E calc (always allow
Max # Plants with prob.
10 Include in Avo
FALSE
FALSE
TRUE
TRUE
Fractional change to start year
0.30
Capacity
Forced
Planned
Variable
Fixed
- Plant Construction -
Captilization
Unavoidable
Variable
Adjust Factor
Outage
Outage
Heat Rate
Fuel Price
O&M Cost
Bid Price or
O&M Cost
Nominal
Construction
Structure
Fixed Cost
Cost
Name
Capacity
to1)
Rate
Rate
(BTU/kWh)
Fuel Type
Adjustment
e/kwh
OP, /kwh
$/kW-yr
Cost/kW
Year
to Use const $/kW-yr
e/kwh
Nuclear1
1,000
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
800
1973
1
26
0.73
Nuclear2
800
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
2,750
1988
1
180
0.73
Coalt
900
1
7.0%
14.2%
9,600
Coal
0.833
0.21
OP
11.7
490
1983
1
26
1.28
Coal2
850
1
6.5%
8.8%
9,700
Coal
1.000
0.22
OP
11.7
370
1978
1
15
1.51
Coal3
850
1
6.5%
8.8%
9,800
Coal
1.000
0.22
OP
11.7
300
1973
1
10
1.53
Coal4
600
1
6.5%
10.3%
9,900
Coal
1.000
0.23
OP
12.4
680
1981
1
31
1.55
Coal5
600
1
6.6%
10.3%
10,000
Coal
1.000
0.24
OP
12.4
380
1960
1
0
1.58
Coal6+7
850
1
8.5%
12.3%
10,200
Coal
1.000
0.32
OP
15.2
500
1980
1
21
1.68
Coals
450
1
8.5%
12.3%
10,600
Coal
1.167
0.32
OP
15.2
300
1970
1
B
1.97
Coal9+10
450
1
6.4%
10.9%
11,200
Coal
1.167
0.35
OP
16.3
300
1970
1
8
2.09
Coal-Adv.
50
1
4.1%
12.3%
9,600
Coal
1.000
0.25
OP
33.6
1,816
2006
3
222
1.53
Oil1
500
1
11.6%
5.2%
10,100
OII
0.840
0.50
OP
6.0
127
1973
1
4
3.05
GasST1
600
1
9.7%
6.8%
10,000
Gas
0.951
0.13
OP
9.4
170
1976
1
6
2.59
GasST2
500
1
9.7%
6.8%
10,100
Gas
1.084
0.13
OP
9.4
150
1970
1
4
2.96
GasST3
450
1
9.7%
6.8%
10,200
Gas
1.111
0.13
OP
9.4
220
1967
1
0
3.06
GasCC1
300
1
6.8%
13.0%
9,665
Gas
0.951
0.10
OP
10.0
470
1992
2
45
2.48
GasCC2-New
200
1
5.5%
7.5%
7,760
Gas
1.000
0.05
OP
28.9
452
1999
3
55
2.06
GasCC3-new
200
1
5.5%
7.5%
7,618
Gas
1.000
0.05
OP
28.9
477
2001
3
58
2.02
GasCC4-Adv
800
1
5.5%
7.5%
6,284
Gas
1.000
0.05
OP
26.6
538
2005
3
66
1.68
GasCC5-Adv
950
1
5.5%
7.5%
5,817
Gas
1.000
0.05
OP
26.6
615
2009
3
75
1.55
GasCT1+2
450
1
10.0%
5.4%
12,800
Gas
0.969
0.22
OP
6.0
140
1986
1
9
3.42
GasCT3-new
350
1
3.6%
4.0%
11,460
Gas
1.000
0.01
OP
11.9
364
1998
3
44
2.98
GasCT4-new
350
1
3.6%
4.0%
10,873
Gas
1.000
0.01
OP
11.9
406
2002
3
50
2.82
GasCT5-Adv.
450
1
3.8%
3.9%
7,793
Gas
1.000
0.05
OP
16.9
542
2008
3
66
2.07
Renewable
50
1
25.0%
15.0%
10,280
Other
1.000
1.27
OP
65.5
2,361
2008
4
260
1.27
Limited Energy
Peak CF
Non-peak CF
Hydro
1,600
1
55.0%
40.0%
1028000.0%
Hydro
0.10
10
400
1957
1
0
0.10
Total Capacity
15,150
SWH,6/9/97,6:06 PM
Page 1
RommAppF-2Tables.xis:RestrucOutput
:
Restructure case
Peak
Offpeak # of Unprofitable plants
% of Total
Cap fact Avoidable
Variable
Annual
season
season
Against avoid O&M
9
Capacity Generation
%
c/kWh
c/kWh
Reserve Margin
6.8%
6.8%
6.1%
Against all costs
12 w/ unserve
Hydro
10.6%
7.5%
43.8%
0.36
0.10
LOLP. % of period
0.92
2.12
0.52
Average Price, c/kWh
2.84
2.86
Nuclear
11.9%
15.4%
79.6%
2.02
0.73
1.58
LOLP. day/10 Year
33.67
77.55
19.04 Avg. Variable Cost
1.45
1.47
Coal
37.0%
47.4%
78.9%
1.80
Load factor
65.7%
73.1%
71.4% Avg. Varl+Avoid O&M
2.17
2.19
Oil
3.3%
0.3%
4.8%
4.91
3.49
Peak Demand, MW
14,168
14,188
12,589
Total Cost
2.51
2.53
Gas-ST
10.2%
3.3%
19.6%
3.27
2.73
(417.34)
Gas-CC
16.2%
21.0%
80.0%
2.95
1.74
Energy. GWh
81,727
22,703
59,024
Max loss, $/avall kW
Generation, GWh
81,692
22,682
59,010
Start-up Cost, $/MW
40
Gas-CT
10.6%
4.9%
28.6%
4.34
232
Unserved Energy, G'
34
21
13 # plants Probabilistic
10
Other
0.3%
0.3%
60.0%
7.47
1.27
Round GIT not in UE
1
0
0
Plant
Output
Capac
Time on
Revenue Var. +Start Avoidable Unavoidable
Total Net
Avoidable Net Rev
Avoidable Carbon release
c/kWh
Million
Tons
Name
Capacity
MWyr
Factor
Margin, %
MS
Cost MS xd Cst MS
Fxd Cst MS
Rev MS
MS
$/kW
ost,
Nuclear1
1,000
796.00
79.6%
0.00
188
51
90
26
21
47.00
59.04
202
0.00
Nuclear2
800
636.80
79.6%
0.00
150
41
72
144
(106)
37.60
59.04
2.02
0.00
109.60
1.45
1.53
Coal1
900
709.20
78.8%
0.00
168
79
11
23
54
77.73
Coal2
850
719.95
84.7%
0.00
170
96
10
13
52
64.39
89.44
1.67
1.57
Coal3
850
719.95
84.7%
0.00
170
96
10
8
55
63.55
88.27
1.69
1.59
42.50
85.23
1.72
1.11
Coal4
600
496.60
83.1%
0.00
118
68
7
18
24
Coal5
600
497.33
82.9%
0.31
118
69
7
0
41
41.48
83.18
1.75
1.12
Coal6+7
850
650.83
76.6%
3.76
156
96
13
18
29
46.99
69.80
1.91
1.50
13
16.33
45.83
2.21
0.79
Coal8
450
331.95
73.8%
2.76
80
57
7
3
Coal9+10
450
248.27
55.2%
12.40
66
46
7
3
10
13.36
35.90
2.43
0.63
Coal-Adv.
50
41.80
83.6%
0.00
10
6
13
(8)
(8.49)
(203.14)
5.02
0.09
3
2
2
3.65
8.78
4.91
0.05
Oil1
500
24.14
4.8%
3.60
14
7
GasST1
600
218.00
36.3%
18.17
64
49
6
4
5
9.32
18.60
2.88
0.28
GasST2
500
74.36
14.9%
9.00
28
19
5
2
2
3.65
8.75
3.68
0.10
4
4
0
1
1.27
3.39
8.20
0.01
GasST3
450
11.21
2.5%
2.29
9
GasCC1
300
135.63
45.2%
8.25
38
29
3
14
(8)
5.54
23.02
2.73
0.17
GasCC2-New
200
149.36
74.7%
4.20
37
27
17
-
(7)
(6.78)
(38.94)
3.34
0.15
4.00
38
28
17
(7)
(6.90)
(39.66)
3.29
0.15
GasCC3-new
200
156.58
78.3%
-
GasCC4-Adv
800
691.10
86.4%
0.77
163
101
74
-
(12)
(11.85)
(17.02)
2.90
0.55
GasCC5-Adv
950
826.46
87.0%
0.06
195
113
97
-
(14)
(14.19)
(17.17)
2.89
0.61
GasCT1+2
450
5.10
1.1%
0.87
7
2
3
4
(2)
2.32
6.10
10.77
0.01
GasCT3-new
350
34.22
9.8%
5.76
15
9
20
.
(14)
(13.54)
(41.87)
9.59
0.05
GasCT4-new
350
92.17
26.3%
12.00
30
23
22
-
(14)
(14.26)
(44.10)
5.49
0.13
450
326.60
72.6%
10.89
83
59
37
-
(14)
(13.80)
(33.22)
3.37
0.32
GasCT5-Adv.
Renewable
50
30.00
60.0%
0.00
7
3
16
-
(13)
(12.52)
(417.34)
7.47
0.00
Hydro
1,600
700.00
43.8%
195
6
16
0
173
172.60
107.88
0.36
0.00
Totals
15,150
9,326
62%
2,317
1,184
586
284
263
547
12.50
Avoidable
Total
Unserved Energy
3.87
17
17
w/o UE
1,770
2,054
Avg. Carbon kg/MWhr
153
Totals w/ Unserved
9,329
2,335
1,202
w/ UE
1,788
2,071
Time wtd marginal cost
261
Time wtd Unserv E Price
19.86
Unserv E. Cost/kWh
50.65
Price Increase to pay avoided losses
0.13
Sort by Net Revenue/kW
Avoidable
Reserve
Name
Net Rev/kW
Capacity
Margin
Marginal Power Costs and Prices
Coal1
109.60
900
6%
10.00
Hydro
107.88
1,600
18%
Coal2
89.44
850
24%
9.00
Peak Season Cost
Coal3
88.27
850
30%
Peak Season Price
Coal4
85.23
600
34%
8.00
Coal5
83.18
600
38%
Off-Season Cost
Coal6+7
69.80
850
44%
Off-Season Price
Nuclear2
59.04
800
50%
7.00
Nuclear1
59.04
1,000
57%
Coals
45.83
450
60%
6.00
Coal9+10
35.90
450
63%
GasCC1
23.02
300
65%
5.00
GasST1
18.60
600
69%
e/kWH
Oil1
8.78
500
73%
4.00
GasST2
8.75
500
76%
GasCT1+2
6.10
450
80%
GasST3
3.39
450
83%
3.00
GasCC4-Adv
(17.02)
800
88%
GasCC5-Adv
(17.17)
950
95%
2.00
GasCT5-Adv.
(33.22)
450
96%
GasCC2-New
(38.94)
200
100%
1.00
GasQC3-new
(39.66)
200
101%
GasCT3-new
(41.87)
350
104%
0.00
GasCT4-new
(44.10)
350
106%
0
10
20
30
40
50
60
70
80
&
100
Coal-Adv.
(203.14)
50
106%
Percent of Period
Renewable
(417.34)
50
107%
SWH,6/9/97,6:12 PM
Page 1
RommAppF-2Tables
ut
Case ID
Efficiency Case
CAPITALIZAT IOU-Existing
IPP-Existing
IPP-New
IPP-Renew
Peak Season LDC
Peak Demand
13019.9318
Fuel Type
$/MMBTU kg C/MBTU
1
2
3
4
Season Peak Shoulder 2
Shoulder 1
Min (100%)
Ratio of Off-peak to peak
88.4%
Gas
2.59
14.47 Term (Years)
30
30
20
20 % of Season
0
5
95
100
12
5 Template ratic
100%
93%
53%
42%
Peak fraction of year
25%
Coal
1.34
25.72
Tax life
20
20
Load Factor, %
65.5%
ON
3.00
21.49 Inc. Tax Rate
36%
36%
36%
36% Ratio to Peak
100%
93%
53%
42%
Peak Season Load Factor
72.9%
Nuclear
0.70
0 Prop. Tax rate
5%
5%
5%
5% Demand MW
13,020
12,133
6,870
5,409
Off-Peak Season Load Factor
71.4%
Hydro
0.00
0 Debt %
48%
30%
30%
30% Off-Peak Season LDC
Carbon Tax, $/netric ton C
0.00
Other
0.00
0 Interest Rate
8.0%
10.0%
10.0%
10.0% % of Season
0
2
96
100
Capacity Payment,$/kW
0 Year of Study
2010
Preferr Equity
14%
0%
0%
0% Template ratic
100%
85%
58%
50%
Uplift Charge, c/kWh
0 Year of $
1995
Return Rate
10.0%
10.0%
10.0%
10.0% Ratio to Peak
100%
85%
58%
50%
0 Start-up Cost, $/MW
40 Common Equi
38%
70%
70%
70%
Demand MW
11,507
9,823
6,669
5,731
Unserved Energy, e/kWh
Non-generat. Price, c/kWh
3.18 Min Capacity w/ probab
0 Return Rate
11.0%
14.0%
14.0%
14.0%
Price Elasticity(not used if 0)
0.05 Min Outage Rate w/ probab
0.0% Vary FCR by
TRUE
TRUE
FALSE
FALSE
Default Unserved E calc (always sllow
Max I Plants with prob.
10 Include in Avo
FALSE
FALSE
TRUE
TRUE
Fractional change to start year
0.30
Unavoidable
Variable
Capacity
Forced
Planned
Variable
Fixed
- Plant Construction -
Capilization
Adjust Factor
Outage
Outage
Heat Rate
Fuel Price
O&M Cost
Bid Price or
O&M Cost
Nominal
Construction
Structure
Fixed Cost
Cost
Name
Capacity
(0 to1)
Rate
Rate
(BTU/kWh)
Fuel Type
Adjustment
c/kwh
OP, e/kwh
$/kW-yr
Cost/kW
Year
to Use const $AW-yr
e/kwh
1973
1
26
0.73
Nuclear1
1,000
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
800
Nuclear2
800
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
2,750
1988
1
180
0.73
9,600
Coal
0.833
0.21
OP
11.7
490
1983
1
26
1.28
Coal1
900
1
7.0%
14.2%
Coal2
850
1
6.5%
8.8%
9,700
Coal
1.000
0.22
OP
11.7
370
1978
1
15
1.51
Coal3
850
1
6.5%
8.8%
9,800
Coal
1.000
0.22
OP
11.7
300
1973
1
10
1.53
31
1.55
Coal4
600
1
6.6%
10.3%
9,900
Coal
1.000
0.23
OP
12.4
680
1981
1
Coal5
600
1
6.6%
10.3%
10,000
Coal
1.000
0.24
OP
12.4
380
1960
1
0
1.58
1.000
0.32
OP
15.2
500
1980
1
21
1.68
Coal6+7
850
1
8.5%
12.3%
10,200
Coal
Coal8
450
1
8.5%
12.3%
10,600
Coal
1.167
0.32
OP
15.2
300
1970
1
8
1.97
Coal9+10
450
1
6.4%
10.9%
11,200
Coal
1.167
0.35
OP
16.3
300
1970
1
8
2.09
Coal-Adv.
50
1
4.1%
12.3%
9,600
Coal
1.000
0.25
OP
33.6
1,816
2006
3
222
1.53
Oil1
500
1
11.6%
5.2%
10,100
Oil
0.840
0.50
OP
6.0
127
1973
1
4
3.05
OP
9.4
170
1976
1
6
2.59
GasST1
600
1
9.7%
6.8%
10,000
Gas
0.951
0.13
GesST2
500
1
9.7%
6.8%
10,100
Gas
1.084
0.13
OP
9.4
150
1970
1
4
2.96
1
9.7%
6.8%
10,200
Gas
1.111
0.13
OP
9.4
220
1967
1
0
3.06
GasST3
450
GasCC1
300
1
6.8%
13.0%
9,665
Gas
0.951
0.10
OP
10.0
470
1992
2
45
2.48
GasCC2-New
200
1
5.5%
7.5%
7,760
Gas
1.000
0.05
OP
28.9
452
1999
3
55
2.06
477
2001
3
58
2.02
GasCC3-new
200
1
5.5%
7.5%
7,618
Gas
1.000
0.05
OP
28.9
GasCC4-Adv
800
1
6.5%
7.5%
6,284
Gas
1.000
0.05
OP
26.6
538
2005
3
66
1.68
7.5%
5,817
Gas
1.000
0.05
OP
26.6
615
2009
3
75
1.55
GasCC5-Adv
300
1
5.5%
GasCT1+2
450
1
10.0%
5.4%
12,800
Gas
0.969
0.22
OP
6.0
140
1986
1
9
3.42
GasCT3-new
350
1
3.6%
4.0%
11,460
Gas
1.000
0.01
OP
11.9
364
1998
3
44
2.98
3
50
2.82
GasCT4-new
350
1
3.6%
4.0%
10,873
Gas
1.000
0.01
OP
11.9
406
2002
GasCT5-Adv.
0
1
3.8%
3.9%
7,793
Gas
1.000
0.05
OP
16.9
542
2008
3
66
2.07
Other
1.000
1.27
OP
65.5
2,361
2008
4
260
1.27
Renewable
50
1
25.0%
15.0%
10,280
Limited Energy
Peak CF
Non-peak CF
Hydro
1,600
1
55.0%
40.0%
1028000.0%
Hydro
0.10
10
400
1957
1
0
0.10
Total Capacity
14,050
Page 1
SWH,6/9/97,6:13 PM
RommAppF-2Tables.xds:EffOutput
Efficiency Case
Peak
Offpeak # of Unprofitable plants
% of Total
Cap fact
Avoidable
Variable
Annual
season
season
Against avoid O&M
8
Capacity Generation
%
c/kWh
</kWh
Reserve Margin
7.9%
7.9%
7.3%
Against all costs
11 w/ unserve
Hydro
11.4%
8.2%
43.8%
0.36
0.10
LOLP, % of period
0.73
1.64
0.43
Average Price, c/kWh
2.85
2.67
Nuclear
12.8%
16.8%
79.6%
2.02
0.73
LOLP, day/10 Year
26.77
59.92
15.72
Avg. Variable Cost
1.43
1.45
Coal
39.9%
52.1%
79.4%
1.80
1.58
Load factor
65.5%
72.9%
71.4% Avg. Vari+Avoid O&M
2.08
2.09
O#
3.6%
0.3%
4.8%
4.92
3.49
Peak Demand, MW
13,020
13,020
11,507
Total Cost
2.46
2.47
Gas-ST
11.0%
4.0%
22.1%
3.20
2.72
Energy, GWh
74,733
20,777
53,956
Max loss, $/avall kW
(415.33)
Gas-CC
12.8%
16.5%
78.1%
2.97
1.82
Generation, GWh
74,709
20,761
53,948
Start-up Cost, $/MW
40
Gas-CT
8.2%
1.7%
12.8%
6.33
2.92
Unserved Energy, G'
24
15
9 # plants Probabilistic
10
Other
0.4%
0.4%
60.0%
7.47
1.27
Round err not in UE
(1)
o
(1)
Plant
Output
Capac
Time on
Revenue Var. +Start Avoidable Unavoidable
Total Net
Avoidable Net Rev
Avoidable Carbon release
Name
Capacity
MWyr
Factor
Margin, %
MS
Cost MS xd Cst M$
Fxd Cst MS
Rev MS
MS
$/kW
cost, c/kWh Million Tons
Nucleart
1,000
796.00
79,6%
0.00
190
51
90
26
22
46.80
61.31
2.02
0.00
Nuclear2
800
636.80
79.6%
0.00
152
41
72
144
(105)
39.04
61.31
2.02
0.00
Coal1
900
709.20
76.8%
0.00
169
79
11
23
56
79.29
111.80
1.45
1.53
Coal2
850
719.95
64.7%
0.00
172
96
10
13
53
66.12
91.84
1.67
1.57
Coal3
850
719.95
84.7%
0.00
172
96
10
8
57
65.28
90.67
1.69
1.59
Coal4
600
498.60
83.1%
0.00
119
68
7
18
25
43.67
87.58
1.72
1.11
Coal5
600
497.67
82.9%
0.32
119
69
7
o
43
42.65
85.53
1.75
1.12
Coal6+7
850
649.88
76.5%
4.25
157
96
13
18
30
48.51
72.05
1.91
1.49
Coal8
450
329.66
73.3%
3.58
81
57
7
3
14
17.18
48.20
2.21
0.79
Coal9+10
450
279.28
62.1%
11.64
73
51
7
3
11
14.24
36.28
2.39
0.70
Coal-Adv.
50
41.80
83.6%
0.00
10
6
13
(8)
(8.40)
(200.85)
5.02
0.09
Oil1
500
24.03
4.8%
4.24
13
7
3
2
0
254
6.11
4.92
0.05
GasST1
600
250.40
41.7%
20.53
71
57
6
4
5
8.74
17.45
2.84
0.32
GasST2
500
81.68
16.3%
11.55
28
21
5
2
1
2.54
6.09
3.62
0.10
GasST3
450
10.09
22%
2.26
8
3
4
o
0
0.22
0.58
8.74
0.01
GasCC1
300
155.17
51.7%
9.26
42
34
3
14
(8)
5.40
22.44
270
0.19
GasCC2-New
200
145.06
72.5%
4.99
37
26
17
-
(6)
(6.31)
(36.27)
3.38
0.14
GasCC3-new
200
153.58
76.8%
4.84
38
27
17
-
(6)
(6.45)
(37.05)
332
0.15
GasCC4-Adv
800
691.42
86.4%
0.71
165
101
74
-
(10)
(10.14)
(14.57)
2.90
0.55
GasCC5-Adv
300
261.00
87.0%
0.00
62
36
30
-
(4)
(3.84)
(14.72)
289
0.19
GasCT1+2
450
4.41
1.0%
0.84
6
2
3
4
(3)
1.31
3.45
11.80
0.01
GasCT3-new
350
36.25
10.4%
6.35
15
9
20
-
(14)
(14.26)
(44.11)
9.19
0.05
GasCT4-new
350
106.55
30.4%
13.91
33
26
22
-
(15)
(14.97)
(46.28)
5.13
0.15
GasCT5-Adv.
0
-
0.0%
0.00
-
-
-
-
-
-
.
0.00
0.00
Renewable
50
30.00
60.0%
0.00
7
3
16
-
(12)
(12.46)
(415.33)
7.47
0.00
Hydro
1,600
700.00
43.8%
194
6
16
o
172
171.63
107.27
0.36
0.00
Totals
14,050
8,528
61%
2,132
1,069
483
284
296
580
11.92
Avoidable
Total
Unserved Energy
2.79
13
13
w/o UE
1,552
1,836
Avg. Carbon kg/MWhr
159
Totals w/ Unserved
8,531
2,145
1,082
w/ UE
1,565
1,849
Time wtd marginal cost
265
Time wtd Unserv E Price
19.99
Unserv E. Cost/kWh
53.89
Sort by Net Revenue/kW
Price increase to pay avoided losses
0.10
Avoidable
Reserve
Name
Net Rev/kW
Capacity
Margin
Marginal Power Costs and Prices
Coal1
111.80
900
7%
10.00
Hydro
107.27
1,600
19%
Coal2
91.84
850
26%
9.00
Coal3
90.67
850
32%
Peak Season Cost
Coal4
87.58
600
37%
Peak Season Price
8.00
Coal5
85.53
600
41%
Off-Season Cost
Coal6+7
72.05
850
48%
Off-Season Price
Nudear2
61.31
800
54%
7.00
Nudear1
61.31
1,000
62%
Coal8
48.20
450
65%
6.00
Coal9+10
38.28
450
69%
GasCC1
22.44
300
71%
5.00
GasST1
17.45
600
76%
c/kWH
Oil1
6.11
500
79%
GasST2
6.09
500
83%
4.00
GasCT1+2
3.45
450
87%
GasST3
0.58
450
90%
3.00
GasCT5-Adv.
-
-
90%
GasCC4-Adv
(14.57)
800
96%
2.00
GasCC5-Adv
(14.72)
300
99%
GasCC2-New
(36.27)
200
100%
1.00
GasCC3-new
(37.05)
200
102%
GasCT3-new
(44.11)
350
104%
GasCT4-new
(46.28)
350
107%
0.00
Coal-Adv.
(200.85)
50
108%
0
10
20
30
40
50
60
70
80
90
100
Percent of Period
Renewable
(415.33)
50
108%
SWH,6/9/97,6:16 PM
Page 1
RommAppF-2Tables.
but
Case ID
HI Effic./Low Carbon
CAPITALIZAT IOU-Existing
IPP-Existing
IPP-New
IPP-Renew
Peak Season LDC
Peak Demand
11911.4734
Fuel Type
$/MMBTU kg C/MBTU
1
2
3
4
Season Peak Shoulder
2
Shoulder 1
Min (100%)
Ratio of Off-peak 10 peak
88.1%
Gas
2.59
14.47
Term (Years)
30
30
20
20 % of Season
0
5
95
100
100%
93%
52%
41%
Peak fraction of year
25%
Coal
1.34
25.72
Tax life
20
20
12
5 Template ratk
Load Factor, %
65.5%
OH
3.00
21.49
Inc. Tax Rate
36%
36%
36%
36% Ratio to Peak
100%
93%
52%
41%
Peak Season Load Factor
72.6%
Nuclear
0.70
0 Prop. Tax rate
5%
5%
5%
5% Demand MW
11,911
11,106
6,223
4,927
Off-Peak Season Load Factor
71.7%
Hydro
0.00
0 Debt %
48%
30%
30%
30% Off-Peak Season LDC
Carbon Tax, $/netric ton C
50.00
Other
0.00
0 Interest Rate
8.0%
10.0%
10.0%
10.0% % of Season
0
2
96
100
Capacity Payment,$/kW
0 Year of Study
2010
Preferr Equity
14%
0%
0%
0% Template ratic
100%
86%
58%
51%
10.0%
10.0%
10.0% Ratio to Peak
100%
86%
58%
51%
Uplift Charge, c/kWh
0 Year of $
1995
Return Rate
10.0%
Unserved Energy, e/kWh
0 Start-up Cost, $/MW
40 Common Equi
38%
70%
70%
70%
Demand MW
10,488
9,000
6,105
5,305
Non-generat. Price, c/kWh
3.18 Min Capacity w/ probab
0 Return Rate
11.0%
14.0%
14.0%
14.0%
Price Elasticity(not used if 0)
0.05 Min Outage Rate w/ probab
0.0% Vary FCR by
TRUE
TRUE
FALSE
FALSE
Max # Plants with prob.
10 Include in Avo
FALSE
FALSE
TRUE
TRUE
Fractional change to start year
0.30
Default Unserved E calc (always sllow
Capacity
Forced
Planned
Variable
Fixed
- Plant Construction
Capilization
Unavoidable
Variable
Adjust Factor
Outage
Outage
Heat Rate
Fuel Price
O&M Cost
Bid Price or
O&M Cost
Nominal
Construction
Structure
Fixed Cost
Cost
Name
Capacity
(0 to1)
Rate
Rate
(BTU/kWh)
Fuel Type
Adjustment
c/kwh
OP, e/kwh
$/kW-yr
Cost/kW
Year
to Use const $/kW-yr
e/kwh
0.73
Nuclear1
1,000
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
800
1973
1
26
Nuclear2
800
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
2,750
1988
1
180
0.73
0.21
OP
11.7
490
1983
1
26
2.51
Coalt
900
1
7.0%
14.2%
9,600
Coal
0.833
Coat2
850
1
8.5%
8.8%
9,700
Coal
1.000
0.22
OP
11.7
370
1978
1
15
2.76
850
1
6.5%
8.8%
9,800
Coal
1.000
0.22
OP
11.7
300
1973
1
10
2.79
Coal3
600
1
6.6%
10.3%
9,900
Coal
1.000
0.23
OP
12.4
680
1981
1
31
2.82
Coal4
600
1
6.6%
10.3%
10,000
Coal
1.000
0.24
OP
12.4
380
1960
1
0
2.86
Coal5
15.2
500
1980
1
21
2.99
Coal6+7
850
1
8.5%
12.3%
10,200
Coal
1.000
0.32
OP
Coals
0
1
8.5%
12.3%
10,600
Coal
1,167
0.32
OP
15.2
300
1970
1
8
3.33
6.4%
10.9%
11,200
Coal
1.167
0.35
OP
16.3
300
1970
1
8
3.53
Coal9+10
0
1
Coal-Adv.
50
1
4.1%
12.3%
9,600
Coal
1.000
0.25
OP
33.6
1,816
2006
3
222
2.76
500
1
11.6%
5.2%
10,100
OII
0.840
0.50
OP
6.0
127
1973
1
4
4.13
Oill
1976
1
6
3.31
GasST1
600
1
9.7%
6.8%
10,000
Gas
0.951
0.13
OP
9.4
170
GasST2
500
1
9.7%
6.8%
10,100
Gas
1.084
0.13
OP
9.4
150
1970
1
4
3.69
10,200
Gas
1.111
0.13
OP
9.4
220
1967
1
0
3.80
GasST3
450
1
9.7%
6.8%
GasCC1
300
1
6.8%
13.0%
9,665
Gas
0.951
0.10
OP
10.0
470
1992
2
45
3.18
200
1
5.5%
7.5%
7,760
Gas
1.000
0.05
OP
28.9
452
1999
3
55
2.62
GasCC2-New
58
2.57
GasCC3-new
200
1
5.5%
7.5%
7,618
Gas
1.000
0.05
OP
28.9
477
2001
3
GasCC4-Adv
450
1
5.5%
7.5%
6,284
Gas
1.000
0.05
OP
26.6
538
2005
3
66
2.13
1.000
0.05
OP
26.6
615
2009
3
75
1.98
GasCC5-Adv
950
1
5.5%
7.5%
5,817
Gas
GasCT1+2
450
1
10.0%
5.4%
12,800
Gas
0.969
0.22
OP
6.0
140
1986
1
9
4.35
GasCT3-new
350
1
3.6%
4.0%
11,460
Gas
1.000
0.01
OP
11.9
364
1998
3
44
3.80
GasCT4-new
350
1
3.6%
4.0%
10,873
Gas
1.000
0.01
OP
11.9
406
2002
3
50
3.61
1
3.8%
3.9%
7,793
Gas
1.000
0.05
OP
16.9
542
2008
3
66
2.63
GasCT5-Adv.
0
OP
65.5
2,361
2008
4
260
1.27
Renewable
50
1
25.0%
15.0%
10,280
Other
1.000
1.27
Limited Energy
Peak CF
Non-peak CF
Hydro
1,800
1
55.0%
40.0%
1028000.0%
Hydro
0.10
10
400
1957
1
0
0.10
Total Capacity
13,450
Page 1
SWH,6/9/97,6:15 PM
RommAppF-2Tables.xds.HEIfOutp/
Hi Effic./Low Carbon
Peak
Offpeak # of Unprofitable plants
% of Total
Cap fact Avoidable
Variable
Annual
season
season
Against avoid O&M
10
Capacity Generation
%
c/kWh
</kWh
Reserve Margin
12.9%
12.9%
13.2%
Against all costs
15 w/ unserve
Hydro
11.9%
9.0%
43.8%
0.36
0.10
LOLP, % of period
0.17
0.40
0.10 Average Price, c/kWh
3.45
3.45
Nuclear
13.4%
18.4%
79.6%
2.02
0.73
LOLP. day/10 Year
6.34
14.58
3.59 Avg. Variable Cost
2.07
2.07
Coal
34.9%
46.2%
76.8%
3.00
2.77
Load factor
65.5%
72.6%
71.7% Avg. Vari+Avoid O&M
2.80
2.81
Oil
3.7%
0.1%
0.9%
13.45
5.58
Peak Demand, MW
11,911
11,911
10,488
Total Cost
3.21
3.21
Gas-ST
11.5%
3.3%
16.5%
4.12
3.47
Energy. GWh
68,373
18,949
49,424
Max loss, $/avail kW
(359.93)
Gas-CC
15.6%
21.8%
80.9%
3.41
2.23
Generation, GWh
68,350
18,945
49,405
Start-up Cost, $/MW
40
Gas-CT
8.6%
0.9%
6.4%
10.59
3.78
Unserved Energy. G
6
4
2
# plants Probabilistic
9
Other
0.4%
0.4%
60.0%
7.47
1.27
Round em not in UE
18
0
17
Plant
Output
Capac
Time on
Revenue Var. +Start Avoidable Unavoidable
Total Net
Avoidable Net Rev
Avoidable Carbon release
Name
Capacity
MWyr
Factor
Margin, %
MS
Cost MS xd Cst MS
Fxd Cst MS
Rev MS
MS
$/kW
lost,
c/kWh
Million
Tons
Nuclear1
1,000
796.00
79.6%
0.00
234
51
90
26
67
93.00
116.84
2.02
0.00
Nuclear2
800
636.80
79.6%
0.00
187
41
72
144
(70)
74.40
116.84
202
0.00
Coal1
900
709.20
78.8%
0.00
209
156
11
23
19
41.94
59.14
2.68
1.53
Coal2
850
719.20
84.6%
0.32
211
174
10
13
15
27.47
38.15
2.92
1.57
Coat3
850
713.96
84.0%
1.30
210
174
10
8
17
25.82
35.87
2.95
1.58
Coal4
600
479.35
79.9%
3.75
142
119
7
18
(3)
15.80
31.68
3.00
1.07
Coal5
600
454.18
75.7%
8.52
136
114
7
0
14
14.31
28.70
3.05
1.02
Coal6+7
850
490.19
57.7%
25.20
151
129
13
18
(8)
9.83
14.60
3.29
1.13
Coal8
0
-
0.0%
0.00
.
-
-
-
-
-
-
0.00
0.00
Coal9+10
0
-
0.0%
0.00
-
-
-
-
-
-
.
0.00
0.00
Coal-Adv.
50
41.64
83.3%
0.04
12
10
13
-
(11)
(10.59)
(253.46)
6.26
0.09
Oil1
500
4.35
0.9%
0.96
4
2
3
2
(4)
(1.59)
(3.83)
13.45
0.01
GasST1
600
188.70
31.5%
24.18
64
55
6
4
(0)
3.40
6.79
3.65
0.24
GasST2
500
47.81
9.6%
8.38
20
16
5
2
(3)
(0.71)
(1.69)
4.86
0.06
GasST3
450
19.32
4.3%
4.00
9
7
4
0
(2)
(2.05)
(5.44)
6.81
0.02
GasCC1
300
132.15
44.1%
11.09
43
37
3
14
(11)
2.79
11.60
3.44
0.16
GasCC2-New
200
174.00
87.0%
0.00
51
40
17
-
(6)
(5.59)
(32.15)
3.72
0.17
GasCC3-new
200
174.00
87.0%
0.00
51
39
17
-
(5)
(5.50)
(31.58)
3.72
0.17
GasCC4-Adv
450
391.50
87.0%
0.00
115
73
42
-
0
0.46
1.18
3.34
0.31
GasCC5-Adv
950
826.50
87.0%
0.00
243
143
97
-
3
3.33
4.03
3.31
0.61
GasCT1+2
450
1.37
0.3%
0.40
2
1
3
4
(5)
(1.58)
(4.14)
28.97
0.00
GasCT3-new
350
7.62
2.2%
1.78
5
3
20
-
(18)
(18.27)
(56.49)
34.28
0.01
GasCT4-new
350
64.64
18.5%
9.93
24
20
22
-
(18)
(17.89)
(55.32)
7.41
0.09
GasCT5-Adv.
0
-
0.0%
0.00
-
.
-
-
-
0.00
0.00
Renewable
50
30.00
60.0%
0.00
9
3
16
-
(11)
(10.80)
(359.93)
7.47
0.00
Hydro
1,600
700.00
43.8%
224
6
16
0
201
201.45
125.90
0.36
0.00
Totals
13,450
7,802
58%
2,355
1,413
502
277
163
439
9.85
Avoidable
Total
Unserved Energy
0.65
3
3
w/o UE
1,915
2,192
Avg. Carbon kg/MWhr
144
Totals w/ Unserved
7,803
2,358
1,416
w/ UE
1,919
2,195
Time wid marginal cost
3.34
Time wid Unserv E Price
23.44
Unserv E Cost/kWh
57.52
Sort by Net Revenue/kW
Price increase to pay avoided losses
0.11
Avoidable
Reserve
Name
Net Rev/kW
Capacity
Margin
Marginal Power Costs and Prices
Hydro
125.90
1,600
13%
10.00
Nuclear2
116.84
800
20%
Nuclear1
116.84
1,000
29%
9.00
Coal1
59.14
900
36%
Peak Season Cost
Coal2
38.15
850
43%
Peak Season Price
8.00
Coal3
35.87
850
50%
Off-Season Cost
Coal4
31.68
600
55%
Off-Season Price
Coal5
28.70
600
60%
7.00
Coal6+7
14.60
650
68%
GasCC1
11.60
300
70%
6.00
GasST1
6.79
600
75%
GasCC5-Adv
4.03
950
83%
5.00
GasCC4-Adv
1.18
450
87%
e/kWH
Coal8
-
.
87%
Coal9+10
87%
4.00
-
-
GasCT5-Adv.
-
-
87%
GasST2
(1.69)
500
91%
3.00
Oil1
(3.83)
500
95%
GasCT1+2
(4.14)
450
99%
2.00
GasST3
(5.44)
450
103%
GasCC3-new
(31.58)
200
105%
1.00
GasCC2-New
(32.15)
200
106%
GasCT4-new
(55.32)
350
109%
GasCT3-new
(56.49)
350
112%
0.00
Coal-Adv.
(253.46)
50
112%
0
10
20
30
40
50
60
70
80
90
100
Percent of Period
Renewable
(359.93)
50
113%
SWH,6/9/97,6:19 PM
Page 1
RommAppF-2Tables.x
Input
Case ID
Alt. Technology
CAPITALIZAT IOU-Existing
IPP-Existing
IPP-New
IPP-Renew
Peak Season LDC
Peak Demand
14134.3982
Fuel Type
$/MMBTU kg C/MBTU
1
2
3
4
Season Peak
Shoulder
2
Shoulder 1
Min (100%)
Ratio of Off-peak to peak
88.7%
Gas
2.59
14.47
Term (Years)
30
30
20
20 % of Season
0
5
95
100
Peak fraction of year
25%
Coal
1.34
25.72
Tax life
20
20
12
5 Template ratk
100%
94%
53%
42%
Load Factor, %
65.7%
Oil
3.00
21.49
Inc. Tax Rate
36%
36%
36%
36% Ratio to Peak
100%
94%
53%
42%
Peak Season Load Factor
73.0%
Nuclear
0.70
0 Prop. Tax rate
5%
5%
5%
5% Demand MW
14,134
13,226
7,452
5,887
Off-Peak Season Load Factor
71.3%
Hydro
0.00
0 Debt%
48%
30%
30%
30% Off-Peak Season LDC
Carbon Tax, $/netric ton C
0.00
Other
0.00
0 Interest Rate
8.0%
10.0%
10.0%
10.0% % of Season
0
2
96
100
Capacity Payment,$/kW
0 Year of Study
2010
Preferr Equity
14%
0%
0%
0% Template ratic
100%
85%
58%
50%
Uplift Charge, c/kWh
0 Year of $
1995
Return Rate
10.0%
10.0%
10.0%
10.0% Ratio to Peak
100%
85%
58%
50%
Unserved Energy, c/kWh
0 Start-up Cost, $/MW
40 Common Equi
38%
70%
70%
70%
Demand MW
12,538
10,707
7,242
6,225
Non-generat. Price, c/kWh
3.18 Min Capacity w/ probab
0 Return Rate
11.0%
14.0%
14.0%
14.0%
Price Elasticity(not used If 0)
0.05 Min Outage Rate w/ probab
0.0% Vary FCR by
TRUE
TRUE
FALSE
FALSE
Default Unserved E calc (always allow
Max # Plants with prob.
10 Include in Avo
FALSE
FALSE
TRUE
TRUE
Fractional change to start year
0.30
Capacity
Forced
Planned
Variable
Fixed
- Plant Construction
Captilization
Unavoidable
Variable
Adjust Factor
Outage
Outage
Heat Rate
Fuel Price
O&M Cost
Bid Price or
O&M Cost
Nominal
Construction
Structure
Fixed Cost
Cost
Name
Capacity
(0 to1)
Rate
Rate
(BTU/kWh)
Fuel Type
Adjustment
c/kwh
OP, */kwh
$/kW-yr
Cost/kW
Year
to Use const $AW-yr
e/kwh
Nucleart
1,000
1
8.2%
12.2%
10,460
Nuclear
1,000
0.00
OP
90.0
800
1973
1
26
0.73
Nuclear2
800
1
8.2%
12.2%
10,460
Nuclear
1.000
0.00
OP
90.0
2,750
1988
1
180
0.73
Coal1
900
1
7.0%
14.2%
9,600
Coal
0.833
0.21
OP
11.7
490
1983
1
26
1.28
Coal2
880
1
6.5%
8.8%
9,700
Coal
1.000
0.22
OP
11.7
370
1978
1
15
1.51
Coal3
850
1
6.5%
0.8%
9,800
Coal
1.000
0.22
OP
11.7
300
1973
1
10
1.53
Cosi4
600
1
6.6%
10.3%
9,900
Coal
1.000
0.23
OP
12.4
680
1981
1
31
1.55
Coal5
600
1
6.6%
10.3%
10,000
Coal
1.000
0.24
OP
12.4
380
1960
1
0
1.58
Coal6+7
850
1
8.5%
12.3%
10,200
Coal
1.000
0.32
OP
15.2
500
1980
1
21
1.68
Coals
450
1
8.5%
12.3%
10,600
Coal
1.167
0.32
OP
15.2
300
1970
1
8
1.97
Coal9+10
450
1
6.4%
10.9%
11,200
Coal
1.167
0.35
OP
16.3
300
1970
1
8
2.09
Coal-Braltch
50
1
4.1%
12.3%
6,805
Coal
1.000
0.20
OP
26.0
1,377
2005
3
168
1.11
OII1
500
1
11.6%
5.2%
10,100
OII
0.840
0.50
OP
6.0
127
1973
1
4
3.05
GasST1
600
1
9.7%
6.8%
10,000
Gas
0.951
0.13
OP
9.4
170
1976
1
6
2.59
GasST2
500
1
9.7%
6.8%
10,100
Gas
1.084
0.13
OP
9.4
150
1970
1
4
2.96
GasST3
450
1
9.7%
6.8%
10,200
Gas
1.111
0.13
OP
9.4
220
1967
1
0
3.06
GasCC1
300
1
6.8%
13.0%
9,665
Gas
0.951
0.10
OP
10.0
470
1992
2
45
2.48
GasCC2-New
550
1
5.5%
7.5%
7,780
Gas
1.000
0.05
OP
28.9
452
1999
3
55
2.06
GasCC3-new
200
1
5.5%
7.5%
7,618
Gas
1.000
0.05
OP
28.9
477
2001
3
58
2.02
GasCC4-Bral
800
1
5.5%
7.5%
5,888
Gas
1.000
0.015
OP
16.0
689
2005
3
84
1.49
GasCC5-Bral
900
1
5.5%
7.5%
5,538
Gas
1.000
0.015
OP
16.0
774
2010
3
95
1.45
GasCT1+2
450
1
10.0%
5.4%
12,800
Gas
0.969
0.22
OP
6.0
140
1986
1
9
3.42
GasCT3-new
350
1
3.6%
4.0%
11,460
Gas
1.000
0.01
OP
11.9
364
1998
3
44
2.98
GasCT4-Bral
350
1
3.6%
4.0%
8,699
Gas
1.000
0.012
OP
17.6
525
2005
3
64
2.26
GasCT5-Bral
0
1
3.8%
3.9%
8,533
Gas
1.000
0.012
OP
17.6
564
2010
3
69
2.22
Renewable
50
1
25.0%
15.0%
10,280
Other
1.000
1.27
OP
65.5
2,361
2008
4
260
1.27
Limited Energy
Peak CF
Non-peak CF
Hydro
1,600
1
55.0%
40.0%
Hydro
0.10
10
400
1957
1
0
0.10
Total Capacity
15,000
SWH,6/9/97,6:20 PM
"Page 1
RommAppF-2Tables.xds:AitTechOutpurt
Alt. Technology
Peak
Offpeak # of Unprofitable plants
% of Total
Cap fact
Avoidable
Variable
Annual
season
season
Against avoid O&M
8
Capacity Generation
%
c/kWh
e/kWh
Reserve Margin
6.1%
6.1%
5.3%
Against all costs
10 w/ unserve
Hydro
10.7%
7.5%
43.8%
0.36
0.10
LOLP. % of period
1.14
2.55
0.66 Average Price, e/kWh
2.89
2.91
Nuclear
12.0%
15.4%
79.6%
2.02
0.73
LOLP. day/10 Year
41.49
93.21
24.25 Avg. Variable Cost
1.42
1.45
Coal
37.3%
47.7%
79.0%
1.79
1.58
Load factor
65.6%
73.0%
71.3% Avg. Vari+Avoid O&M
2.15
2.18
Oil
3.3%
0.3%
5.7%
4.59
339
Peak Demand, MW
14,134
14,134
12,538
Total Cost
2.50
2.52
Gas-ST
10.3%
3.0%
17.9%
3.36
2.76
Energy, GWh
81,326
22,607
58,720
Max loss, $/avall kW
(414.51)
Gas-CC
18.3%
23.1%
78.0%
2.98
1.67
Generation, GWh
81,282
22,580
58,702
Start-up Cost, S/MW
40
Gas-CT
7.7%
26%
20.7%
4.90
245
Unserved Energy. G
44
27
18
# plants Probabilistic
10
Other
0.3%
0.3%
60.0%
7.47
1.27
Round em not in UE
(0)
(0)
(0)
Plant
Output
Capac
Time on
Revenue Var. +Start Avoidable Unavoidable
Total Net
Avoidable Net Rev
Avoidable Carbon release
Name
Capacity
MWyr
Factor
Margin, %
MS
Cost MS xd Cst MS
Fxd Cst MS
Rev M$
MS
$/kW
cost,
c/kWh
Million
Tons
Nuclear1
1,000
796.00
79.6%
0.00
190
51
90
26
23
49.10
61.69
2.02
0.00
Nuclear2
800
636.80
79.6%
0.00
152
41
72
144
(105)
39.28
61.69
2.02
0.00
Coalt
900
709.20
78.8%
0.00
170
79
11
23
56
79.64
112.30
1.45
1.53
Coal2
850
719.95
84.7%
0.00
172
96
10
13
54
66.23
91.99
1.67
1.57
Coal3
850
719.70
84.7%
0.16
172
96
10
8
57
65.38
90.82
1.69
1.59
Coal4
600
496.76
82.8%
0.32
119
68
7
18
25
43.79
87.82
1.72
1.11
Coal5
600
494.59
82.4%
0.66
118
68
7
o
43
42.77
85.79
1.75
1.11
Coal6+7
850
650.83
76.6%
3.73
158
96
13
18
31
48.83
72.54
1.91
1.50
Coal8
450
331.98
73.8%
2.83
81
57
7
3
14
17.31
48.57
2.21
0.79
Coal9+10
450
261.37
58.1%
11.74
70
48
7
3
11
14.36
38.58
241
0.66
Coal-Braitch
50
41.80
83.6%
0.00
10
4
10
(4)
(3.78)
(90.46)
3.76
0.06
Oilf
500
26.64
5.7%
4.50
17
9
3
2
4
5.92
14.24
4.59
0.05
GasST1
600
179.04
29.8%
18.47
58
41
6
4
8
11.39
22.74
2.95
0.23
GasST2
500
85.25
17.1%
10.80
33
22
5
2
4
5.87
14.05
3.59
0.11
GasST3
450
13.87
3.1%
2.59
12
5
4
0
3
3.27
8.70
7.25
0.02
GasCC1
300
117.82
39.3%
8.45
35
26
3
14
(7)
6.40
26.60
2.77
0.14
GasCC2-New
550
392.25
71.3%
11.87
100
71
46
-
(17)
(17.39)
(36.33)
3.40
0.39
GasCC3-new
200
156.44
78.2%
4.06
39
28
17
-
(6)
(6.45)
(37.06)
3.29
0.15
GasOC4-Braitch
800
696.00
87.0%
0.00
166
91
80
-
(5)
(4.79)
(6.88)
2.80
0.50
GasCC5-Braitch
900
783.00
87.0%
0.00
187
99
99
-
(12)
(12.16)
(15.53)
2.90
0.55
GasCT1+2
450
6.21
1.4%
1.18
9
3
3
4
0
4.18
10.98
9.57
0.01
GasCT3-new
350
40.82
11.7%
6.28
19
11
20
-
(12)
(11.74)
(36.29)
8.49
0.06
GasCT4-Brartch
350
190.48
54.4%
11.23
53
38
29
-
(13)
(13.07)
(40.41)
3.98
0.21
GasCT5-Braltch
0
-
0.0%
0.00
-
.
.
-
0.00
0.00
Renewable
50
30.00
60.0%
0.00
7
3
16
-
(12)
(12.44)
(414.51)
7.47
0.00
Hydro
1,600
700.00
43.8%
201
6
16
0
178
178.46
111.54
0.36
0.00
Totals
15,000
9,279
62%
2,346
1,154
591
284
317
600
12.35
Avoidable
Total
Unserved Energy
5.06
24
24
w/o UE
1,745
2,029
Avg. Carbon kg/MWhr
152
Totals w/ Unserved
9,284
2,370
1,178
w/ UE
1,770
2,053
Time wid marginal cost
2.61
Time wid Unserv E Price
21.69
Unserv E. Cost/kWh
54.37
Sort by Net Revenue/kW
Price increase to pay avoided losses
0.10
Avoidable
Reserve
Name
Net Rev/kW
Capacity
Margin
Marginal Power Costs and Prices
Coal1
112.30
900
6%
10.00
Hydro
111.54
1,600
18%
Coal2
91.99
850
24%
9.00
Coat3
90.82
850
30%
Peak Season Cost
Coal4
87.82
600
34%
Peak Season Price
8.00
Coal5
85.79
600
38%
Off-Season Cost
Coal6+7
72.54
850
44%
Off-Season Price
Nuclear1
61.69
1,000
51%
7.00
Nuclear2
61.69
800
57%
Coals
48.57
450
60%
6.00
Coal9+10
38.58
450
63%
GasCC1
26.60
300
65%
5.00
GasST1
22.74
600
70%
C/KWH
Oilt
14.24
500
73%
GasST2
14.05
500
77%
4.00
GasCT1+2
10.98
450
80%
GasST3
8.70
450
83%
3.00
GasCT5-Braitch
-
-
83%
GasCC4-Braitch
(6.88)
800
89%
2.00
GasCC5-Braitch
(15.53)
900
95%
GasCT3-new
(36.29)
350
98%
1.00
GasCC2-New
(36.33)
550
102%
GasCC3-new
(37.06)
200
103%
GasCT4-Braitch
(40.41)
350
105%
0.00
Coal-Braltch
(90.46)
50
106%
0
10
20
30
40
50
60
70
80
06
100
Percent of Period
Renewable
(414.51)
50
106%
SWH,6/9/97,6:21 PM
Page 1
DRAFT
6/10/97
APPENDIX G
Appendix G-1
Methodology
Figure G-1.1 defines the methodological steps performed in conducting the coal/gas
repowering analysis. Each step is described in more detail in this Appendix. Some elements
of the methodology are described in even greater detail in Appendices G-2 and G-3.
Figure G-1.1 Methodological Steps
Estimate Carbon (other AP)
Emissions Reductions
Dual-Fuel
Estimate NG Demand
Power Plants
(w/fixed MW, kWh)
Assess NG Deliverability,
Infrastructure Costs
Estimate CE ($/ton carbon),
Derive MC curve
Multi-Fuel
Power Plants
Sum Conversion and
Assess Technical/Economic
Infrastructure Costs,
Cost of Conversion
Derive MC curve
Coal-Fired
Power Plants
Powerplant Population Analyzed
The candidate powerplants for repowering with natural gas combined cycle were the
population of coal-fired plants greater than 50 megawatts (MW). Three categories of coal-
fired powerplants were assessed:
dual-fuel powerplants (319 units, 130 plants, 86 GW);
multi-fuel powerplants (122 units, 29 plants, 15 GW);
coal-fired powerplants (711 units, 245 plants, 230 GW).
Dual-fuel plants are those designed to burn either coal or natural gas. They were assessed
separately since it was presumed that they have adequate natural gas hook-up and
transmission supply infrastructure to operate at current design capacity, and may be able to
expand generation capacity without additional infrastructure costs. Multi-fuel plants burn
coal, natural gas and/or petroleum at the same site, but generally in single fuel boilers; only a
small proportion of multi-fuel plant sites have dual-fuel boilers. In those sites were gas is
consumed it was presumed (as with dual-fuel) that they have adequate natural gas hook-up
and transmission supply infrastructure to operate at current design capacity; however, here it
was presumed that additional transmission infrastructure would be required to expand natural
gas usage at the plant. Coal-fired plants have boilers that can only burn coal, and do not have
natural gas supply infrastructure, except in those instances where it is used as start-up fuel.
Technical/Economic Cost of Conversion
For each plant type (dual-fuel, multi-fuel and coal) the investment cost of converting them to
natural gas combined cycle (NGCC) was derived by correlating the nameplate capacity of
each plant site with the closest NGCC system commercially available. The capital cost of
repowering the plant ( both steam turbine repowering and site repowering ( was estimated
together with the cost associated with hook-up and transmission infrastructure to deliver
natural gas to the plant site. These investment costs were then adjusted for 1) the
fixed/variable operations and maintenance (O&M) savings (credit) that would result from
using natural gas (relative to coal), 2) the credit for reducing sulfur dioxide (SO2) and
nitrogen oxide (NOx) emissions with the fuel switch, and 3) the coal/gas price differential and
increase in real natural gas prices due to increased gas demand from the power sector after
repowering.
Current industry estimates for NGCC with a state-of-the-art General Electric (GE) H-frame
turbine were used. Credit of $30/kW and $1/MWh was included to represent annual savings
(coal-to-gas) in fixed O&M and variable O&M costs, respectively. A "partial" repowering
case was examined, wherein it was presumed that up to approximately 2 trillion cubic feet
(TCF) of new utility gas demand, no additional gas transmission infrastructure would be
required.¹ Thus, hook-up and transmission costs were excluded from the repowering
investment cost.
Natural Gas Demand
Based on the existing nameplate rating of the plant, an appropriate NGCC system was selected
with the objective of achieving the equivalent of 1995 plant-level generation. A
corresponding heat rate (ranging from 7770 Btu/kW for 60 MW, to 6320 Btu/kW for >400
MW) was assigned and gas demand for the repowered unit/plant derived. The increase in gas
demand was derived by subtracting 1995 gas consumption from the estimated value after
repowering. In addition to estimating the quantity of gas demand, the analysis also included
the physical and economic efficiency improvements that would result from NGCC-
repowering.
Natural Gas Deliverability and Infrastructure Costs
To ensure natural gas deliverability to the repowered plants ( since the gas requirements are
annual, baseload ( it was presumed that new transmission capacity was necessary (except in
the partial repowering sensitivity analysis). While some unused/underutilized capacity does
exist in the system, it is either regionally or seasonally constrained.
To determine the required transmission capabilities and infrastructure cost of delivering gas
to the repowered NGCC plants a geographic information system (GIS) was used. The GIS
permitted examination of each pipeline link between the repowered plant and the closest gas
supply region to 1) identify the least-cost route, and 2) tabulate the cost of expanding
existing transmission capacity to meet the cumulative gas requirement of all repowered
candidate plants.
Since the ranking of cost-effective NGCC-repowered power plant was not known in advance
of the GIS analysis, the cost of expanding the transmission infrastructure was based on the
requirement to deliver 11 TCF of gas, or the equivalent of repowering all the candidate plants.
The cost to each plant was then based on its respective pipeline routing and volume of gas
I While "partial repowering" actually refers to repowering a portion of the steam turbine (ST) to meet a
load requirement more cost-effectively, in this static analysis1) it was determined that (based on the data)
such an option was not cost-effective, and 2) is was not possible to ensure that the balance of plant. after
partial ST-repowering, would be capable of meeting 1995 generation (kWh) at the plant.
required. Based on the methodology employed, the hook-up/transmission costs allocated to
each plant are a conservative estimate of the ultimate infrastructure delivery cost.
Total Cost of Conversion
The sum of conversion and hook-up/transmission cost represents total investment cost. This
value was then adjusted for the O&M credit discussed above. In addition, several alternative
coal/gas price differentials were included to reflect 1) the fuel price difference between coal
and gas, and 2) an approximation of the gas price increase from higher utility demand for
natural gas.
Based on a special Energy Information Administration (EIA), National Energy Modelling
System (NEMS) simulation,² the 1995 gas/coal price differential was $0.72/MMBtu (1994
dollars); in 2010 this differential increases to $1.18/MMBtu, which reflects both an increase in
natural gas prices and a decrease in coal prices. The increase in natural gas prices is partially
attributable to increased utility demand from NGCC (merchant) plants constructed to meet
new load growth and displace nuclear power plants not relicensed.
The total cost of repowering (conversion, hook-up/transmission, gas/coal price differential,
O&M credit and SO2/NOx credit) for each plant was then divided by the reduction in carbon
emissions arising from the repowering.
Value of Environmental Externalities
There is considerable debate in the literature regarding the value of environmental
externalities. In this study, the market value for SO2 and NOx were included, not their
estimated damage effects. For SO2 values of zero (0) and $100/ton were used, where zero
represents a market saturated with allowances; at the high end, $100/ton represents the current
spot market price.
For NOx, the low end represents estimates of a saturated NOx market; $2,000/ton represents a
nationwide average for NOx, with values approaching $10,000/ton in nonattainment areas.
The ultimate value will be a function of the forthcoming recommendations from the Ozone
Transport Assessment Group (OTAG), and subsequent regulatory action by EPA.
2 DOE/ELA, An Analysis of Carbon Mitigation Cases, Service Report SR/OIAF/96-01 (June 3, 1996).