APPENDIX I. ESTIMATION OF MARGINAL HEAT RATES AND 

SITE TO SOURCE CONVERSION FACTORS 

TABLE OF CONTENTS
 

I.1 COMPETING EFFECTS..................................................................................................I-1 

I.2 EXAMPLE CASE ............................................................................................................I-3
 

I.3 ESTIMATION OF MARGINAL HEAT RATES FOR FINAL RULE ANALYSIS ......I-4 

I.3.1 Sectoral Scope of Marginal Heat Rate ................................................................I-4 

I.3.2 Marginal Heat Rates from the NEMS-BT Simulations .......................................I-6 

I.4 SITE-TO-SOURCE ENERGY CONVERSION FACTORS ...........................................I-7 

LIST OF TABLES 

Table I.2.1 Example of Average Heat Rates and Marginal Heat Rates for 

Beverage Vending Machines in 2014 ...................................................................I-3 

Table I.4.1 Marginal Heat Rates, 2012–2042 .........................................................................I-7 

Table I.5.1 Site-to-Source Conversion Factors for Final Rule Analysis .................................I-9 

LIST OF FIGURES 

Figure I.4.1	 Marginal Heat Rates for 20X, 30X, and 40X Cases for the Electric 

Power Sector..........................................................................................................I-6 

I-i 

BVM_FINAL_FR_TSD_AppendixI_08-14-09.doc 

EERE-2006-STD-0125 COMMENT 74
 

 

APPENDIX I. ESTIMATION OF MARGINAL HEAT RATES AND 

SITE-TO-SOURCE CONVERSION FACTORS 

As described in chapter 10 of the technical support document (TSD), site-to-source 

conversion factors are used to convert energy savings at the site (in kilowatt hours [kWh]) to 

obtain primary or source energy savings. These conversion factors are based on two separate 

quantities: (1) the quantity of source energy needed to produce a kWh of electricity at generation 

plants; and (2) the quantity of electricity lost in the transmission and distribution (T&D) of 

electricity to final customers. 

The National Energy Modeling System-Building Technologies (NEMS-BT) is used by 

the U.S. Department of Energy (DOE) to translate end-use electricity savings to source energy 

savings. The amount of source energy saved as a result of a change in generation is termed the 

marginal heat rate (MHR), which is calculated by imposing a load reduction to the end use of the 

equipment being analyzed in NEMS-BT and observing the change in the source energy use. For 

beverage vending machine equipment, the estimated MHR ranges from just over 8,700 British 

thermal units (Btu)/kWh in 2014 to just under 7,000 Btu/kWh in 2030. This variation occurs as 

the utility sector to meet the different magnitude and shape of the load compared with the 

reference case in the April 2009 update to the Annual Energy Outlook (AEO2009-B).

1

 Over the 

entire period from 2014, the MHR averages about 7,400 Btu/kWh. 

Before turning to a detailed discussion of the MHRs derived from the NEMS-BT for 

beverage vending machine equipment, it is useful to consider a number of conceptual issues that 

relate to MHRs (sections I.1 and I.2). Section 0 describes more specifically how the MHRs were 

developed for this overall analysis. Section I.4 discusses how T&D losses were estimated and 

how the MHRs are translated into site-to-source conversion factors. 

I.1 COMPETING EFFECTS 

On first inspection, an MHR near 7,000 Btu/kWh is perplexing, as it is lower than that 

most power plants likely to be in existence by 2030. The key to understanding this result is that 

the conversion rate does not represent a specific marginal generator or combination of generators 

but is actually a reflection of several NEMS-BT simulated effects that stem from an energy 

conservation standard. Thus, the primary reason the MHR associated with a standard for 

beverage vending machine equipment is low is because the overall rate of efficiency 

improvement of the power system (measured as the average heat rate [AHR], Btu/kWh) with the 

standard in place is lower than that of the reference case in the AEO. 

A simple mathematical decomposition of the change in source energy between the 

reference case and the standards case will help clarify this situation. As shown in Eqs. I.1 and I.2, 

the source energy in both the reference and standards cases can be expressed as the product of 

the amount of electricity generated (terawatt-hours [TWh]) times an AHR: 

SE r  TWh r  AHR r Eq. I.1

SEs  TWhs  AHRs Eq. I.2 

 I-1 

BVM_FINAL_FR_TSD_AppendixI_08-14-09.doc 

EERE-2006-STD-0125 COMMENT 74
Where: 

SEr , SEs = source energy in the reference and standards cases, respectively (Btu),
 

TWhr, TWhs = terrawatt-hours in the reference and standards cases, respectively, and 

AHRr, AHRs = average heat rates (Btu/kWh) in the reference and standards cases, respectively. 

A common decomposition of the difference of two products (e.g., variable X times 

variable Y in two situations) is shown in the following expression: 

SE  SEs  SEr  AHR  TWh  TWH  AHR Eq. I.3 

Where: 

AHR = the average of the AHRs for the reference and standards cases (Btu/kWh), 

TWh = the average generation (TWh) for the reference and standards cases, and 

Variables preceded by = 

the difference between standards and references cases (i.e., the difference between 

the cases for the same year). 

Using this formulation, the first term to the right of the second equal sign in Eq. I.3 can 

be thought of as the “displaced generation” effect. The second term can be termed the electric 

utility “system intensity” effect. This is defined in terms of how the AHR changes between the 

reference and standards cases. No implication is suggested as to whether the utility sector 

operates different with regard to economic efficiency between the reference and standards cases. 

In prior appliance and equipment rulemakings, MHR has been employed as convenient 

means of estimating the amount of source energy saved corresponding to a reduction in 

electricity generation brought about by the standard. Based on simulations with the NEMS-BT 

model, the change in source energy is divided by the change in total generation. In terms of Eq. 

I.3, the MHR is calculated by dividing ∆SE by ∆TWh. When both sides of Eq. I.3 are divided by 

the change in generation, we have: 

MHR  SE / TWhr  AHR  TWH  AHR / TWh Eq. I.4 

Expressed in this manner, the MHR is shown to be the AHR (averaged between the two 

cases) plus an adjustment term involving the relative sizes of the changes in the AHR and total 

generation ( AHR / TWh ). Because an efficiency standard will cause total generation to fall, 

the sign of TWh is negative. Qualitatively, if the AHR increases, one can expect to find that the 

MHR is lower than the AHR. Depending on particular circumstances (as illustrated below), the 

differences between the MHRs and AHRs emanating from a particular scenario in NEMS-BT 

can be considerable. 

For cases using NEMS-BT to analyze efficiency standards for various types of 

commercial equipment, the long-term (2020 and later) MHRs are consistently lower than the 

AHRs. This reflects an increase in the AHR between the reference and standards cases. This 

increase in the AHRs can be attributed to two factors. 

 I-2 

BVM_FINAL_FR_TSD_AppendixI_08-14-09.doc 

EERE-2006-STD-0125 COMMENT 74
 

 

 

 

 

In a rulemaking for residential air conditioners and heat pumps (66 Federal Register 7169) 

TSD, Appendix M noted that the first factor is from slower growth in overall electricity 

consumption that retards the investment in new, more efficient generating capacity.2

 The second 

factor involves shifts between different types of generating technologies (e.g., gas-to-coal, coal-tonuclear). These shifts are likely induced by a change in the shape in the overall load shape seen by 

utilities. Any of these shifts that substitute generating capacity with higher heat rates than that of 

the displaced capacity will increase the AHR and, consequently, the lower the MHR. 

I.2 EXAMPLE CASE 

A numerical illustration of the AHR and MHR relationship for one NEMS-BT case is 

shown in Table I.2.1. The numbers are extracted from the NEMS-BT output for a single case for 

a recent (2008) analysis of energy conservation standards for beverage vending machines. 

Table I.2.1 Example of Average Heat Rates and Marginal Heat Rates for Beverage 

Vending Machines in 2014 

Average and Marginal Heat Rates 

Case TWh  Avg Heat Rate Total 

Btu/kWh Btu 

Reference case 4,241.5 10,067.9 42,703,098 

Standards case 4,236.3 10,071.8 42,667,465 

Change -5.2 3.8 -35,633 

MHR = -35,663/-3.8 = 6,917 

Decomposition of Change in Source Energy 

Generation effect Avg of Cases Change Component 

AHR ∆ TWh Change 

10,069.8 -5.2 -51,878 

System intensity Avg TWh ∆ Heat Rate 

4,238.9 3.8 16,245 

AHR Total Change, Btu -35,633 

+ Adjustment = MHR 

10,069.8 -3153.3 6,917 

Table I.2.1 shows generation (in TWh) and AHR (Btu/kWh) for the reference and 

standards cases. To maintain conventional units for generation and heat rates, the source energy 

is expressed in billion Btu (BBtu). 

Comparing the two cases, generation is lower by about 5 TWh in the standards case as 

compared to the reference case in 2030. However, the AHR is higher by nearly 4 Btu/kWh. 

Based on the changes in total source energy (35,633 BBtu) and generation, the MHR is 6,917 

Btu/kWh, which is considerably lower than the AHR. 

The lower portion of the table shows a decomposition of the change in source energy use 

based on the formulation in Eq. I.2. Using this method, the displaced generation effect is 

calculated to be approximately 51,900 BBtu (of savings). The system intensity effect works in 

the opposite direction, with an estimated increase of nearly 16,300 BBtu. The net effect is the 

observed change in source energy of approximately 35,600 BBtu. One possible interpretation of 

the particular result shown is that the system intensity effect essentially reduces the impact of 

displaced generation by about 30 percent (i.e., 16,300/51,900). 

 I-3 

BVM_FINAL_FR_TSD_AppendixI_08-14-09.doc 

EERE-2006-STD-0125 COMMENT 74
 

I.3 ESTIMATION OF MARGINAL HEAT RATES FOR FINAL RULE ANALYSIS 

The estimation of MHRs for use in calculating the source energy savings associated with 

electricity savings shown in TSD chapter 7 are based on a series of simulations with the NEMSBT model. As discussed in TSD Appendix K, these simulations employ multiples of the 

predicted savings in electricity use as a means of overcoming model noise in solving the 

NEMS-BT model. The multiples employed are designated as 20X, 30X, and 40X and are 

described in TSD Appendix K. For purposes of the calculating a single set of MHRs, an average 

of the MHRs derived from these cases was used. A further adjustment involved smoothing the 

resulting projected values by taking a centered 3-year moving average of the heat rates. 

I.3.1 Sectoral Scope of Marginal Heat Rate 

As discussed in section I.2, the most straightforward calculation of the MHR is to divide 

the change in source energy savings by the change in electricity generation. However, some 

consideration as how best to measure these values in terms of the NEMS-BT output may be 

warranted. Three approaches were considered and are described below. 

I.3.1.1 Economy-Wide Measure 

Table 1 in the AEO2009-B displays total energy consumption for eight different major 

fuel types (petroleum, natural gas, coal, nuclear power, hydropower, biomass, other renewable 

energy, and other). The sum of this consumption is total source energy used in the U.S. 

economy, now estimated to be just under 100 quadrillion Btu (1015 Btu or quads). The broadest 

measure of a MHR is to divide the change in economy-wide source energy by the change in total 

electricity generation. 

In essence, the MHR calculated in this manner incorporates more than just the efficiency 

of the electricity generation sector but also any ancillary changes in direct fossil fuel use by other 

sectors of the economy (e.g., residential or commercial customers). As described briefly in TSD 

Appendix K, a typical impact from energy-efficiency standards predicted by the NEMS-BT 

model was to induce a very small increase in retail electricity prices. This small change not only 

magnifies the impact of the initial change in electricity (by further dampening electricity 

consumption) but also leads to small increases in natural gas use by residential and commercial 

customers (as natural gas becomes relatively less expensive than electricity). This increase 

contributes to lower MHRs than would be calculated without this effect. 

I.3.1.2 All Generation 

Electricity in the United States is primarily produced by plants whose primary business is 

to sell electricity, and heat, to the public. These plants are designated by the Energy Information 

Administration (EIA) as the “electric power sector.” Other sources of electricity generation are 

the end-use sectors (residential, commercial, and industrial). As noted by EIA in the notes to 

Table A8 of the (2008) AEO, end-use generation “includes combined heat and power plants and 

electricity-only plant in the commercial and industrial sectors; and small on-site generating 

systems in the residential, commercial, and industrial sectors used primarily for own-use 

generation which may also sell some power to the grid.” In 2012, the effective year of the 

standards for beverage vending machine equipment, end-use generation from the commercial 

 I-4 

BVM_FINAL_FR_TSD_AppendixI_08-14-09.doc 

EERE-2006-STD-0125 COMMENT 74
and industrial sectors is projected in the AEO reference case to account for about 4.1 percent of 

total generation. 

To calculate a MHR associated with all generators requires both the change in total 

generation (in TWh) and the change in total source energy (expressed in Btu) to produce that 

electricity. NEMS-BT reports total generation, broken out between the electric power sector and 

end-use generation, in a single table (as Table A8 in the AEO). Another NEMS-BT table (as 

Table A2 in the AEO) provides fuel inputs, including nuclear and renewables, for the electric 

power sector. Unfortunately, NEMS-BT does not report the fuel consumption used by the enduse sectors for electricity generation. This deficiency suggests that the best approximation to the 

change in source energy (∆SE) for all electricity generation is likely calculated as 

∆ SE (all generators) = ∆ SE (economy-wide) – ∆ non-electricity (residential)

 – ∆ non-electricity (commercial) Eq. I.5 

By subtracting the change in non-electricity (fossil fuel) energy use in the residential 

sector, the induced impact of relative fuel prices is excluded from the MHR calculation. For the 

commercial sector, the change in non-electricity energy use is also expected to primarily result 

from a price response, reflected in space and water heating use, and not in the (very small) 

amount of fuel used to generate on-site electricity. Of total commercial and industrial generation 

of electricity in 2005, only about 5 percent was generated in the commercial sector (Annual 

Energy Review 20073

 Table 8.2d). After making these two adjustments, it is reasonable to expect 

that most of the resulting change in economy-wide source energy is attributable to the change in 

generation by the electric power sector and the industrial sector. To the extent that there is some 

fuel switching for process use in the industrial sector that results from changing relative prices 

due to the standard, the computed MHR will not completely reflect changes due solely to 

electricity generation. Within the current modeling and reporting structure of NEMS, there is no 

way to eliminate that effect completely; thus, the methodology to calculate the change in source 

energy expressed in Eq. I.5 yields only an approximate MHR. 

I.3.1.3 Electric Power Sector 

The third approach is to consider only the MHR that pertains to the electricity produced 

by the electric power sector. NEMS-BT reports both energy inputs and generated electricity by 

major fuel type. This reporting permits calculation of average as well as MHRs for not only for 

the entire sector but also by major type of generating facility. 

The final set of MHRs used in this analysis is based on the third approach. First, while 

the economy-wide measures have some utility in showing some the wider energy system effects 

of an energy-efficiency standard, they are less consistent with the definition of MHRs used in 

prior DOE appliance and equipment rulemakings. Second, because MHRs derived from the 

electric power sector typically show more consistent year-to-year changes while having the same 

general magnitude for all generation, DOE employs the heat rates from the electric power sector 

results. As a better indication of intermediate trends in the heat rates, the MHRs based on the 3-

year moving averages are used. Because of the considerable uncertainty of whether trends in 

MHRs would continue past 2030, the post-2030 heat rates have been fixed at 2030 values. 

 I-5 

BVM_FINAL_FR_TSD_AppendixI_08-14-09.doc 

EERE-2006-STD-0125 COMMENT 74
I.3.2 Marginal Heat Rates from the NEMS-BT Simulations 

As described in TSD Appendix K, the magnitudes of the energy decrements associated 

with the actual savings from the proposed standards are too small for NEMS-BT to produce 

stable results. This instability is caused by the numerical noise in the solution process of the 

model and stems, in part, from a precise balancing not always achieved between the demand and 

supply sides of NEMS. As a result, DOE estimated the various impacts corresponding to 

different trial standard levels (TSLs) using interpolation. The interpolation procedure involved 

implementing reductions to the refrigeration end use at multiples of the proposed standards and 

then linearly interpolating the impacts to correspond to the actual levels of the standards. 

Based upon an preliminary estimate of savings for the entire set of beverage vending 

machine equipment under TSL 7 (the “max tech” case), a single set of multipliers was selected at 

20, 30, and 40 times the predicted savings for that particular TSL. In 2030, the actual electricity 

decrements corresponding to these multiples are 15.2, 22.8, and 30.4 TWh. Relative to total 

projected electricity consumption of the commercial sector in the AEO2009-B, these levels of 

savings correspond to reductions of 0.82, 1.22, and 1.63 percent, respectively. Further details on 

these multipliers are given in section K.2, Choice of Impact Multipliers. 

Figure I.3.1 shows MHRs for the electric power sector for three levels of savings 

associated with three multipliers. The three levels are labeled 20X, 30X, and 40X for consistency 

with the discussion in Appendix K—the actual magnitude of the cooling savings applied to the 

NEMS commercial sector module in 2030 ranges between 15 and 30 TWh. The MHRs in 

Figure I.3.1 are derived from the model-generated responses by the electricity power sector. 

Figure I.3.1 Marginal Heat Rates for 20X, 30X, and 40X Cases for the Electric Power Sector 

As discussed in TSD chapter 14, the behavior of NEMS in any particular case may be 

affected by the capacity planning aspects of the model that can sometimes unduly influence 

overall generation in the years around a “shock” to electricity demand. As Figure I.3.1 shows, 

this is particularly evident in the first year of the forecast period, in which the 20X case shows a 

particularly high MHR and the 30X and 40X cases show a particularly low MHR. While these 

values settle into more similar values thereafter, the 20X case maintains a higher MHR than the 

 I-6 

BVM_FINAL_FR_TSD_AppendixI_08-14-09.doc 

EERE-2006-STD-0125 COMMENT 74
other multipliers throughout the analysis period. For this particular multiplier (20X), the 

(negative) impact on nuclear generation is relatively higher than the other cases, especially in the 

earlier years of the analysis. 

In developing the response functions for the utility impacts described in TSD Appendix 

K, a regression approach was used essentially to average impacts across the simulations. The 

estimated coefficients of the linear regression line were then used to interpolate the utility sector 

impacts to correspond to actual savings levels for the various standards. The regressions were 

estimated for selected years 2015–2030 at 5-year intervals. 

Because the MHRs are required for each year in the future to calculate source energy 

savings, a more straightforward (two-step) approach was chosen. The first step in the approach 

was to average the simulation results across the all three (20X, 30X, and 40X) simulations. 

Because the simulations appear to still produce year-to-year noise in the results, the second step 

was to smooth the resulting series by taking a 3-year centered moving average. For example, the 

smoothed value for 2020 is the average of the heat rates for years 2019, 2020, and 2021. The 

values for years 2013 and 2030 are set equal to the values for years 2014 and 2029, respectively. 

The resulting MHRs are shown in Table I.3.1. 

Table I.3.1 Marginal Heat Rates, 2012–2042 

Year Btu/kWh Year Btu/kWh Year Btu/kWh Year Btu/kWh 

2012 7,970 2017 7,853 2022 8,068 2027 7,165 

2013 8,040 2018 7,950 2023 7,748 2028 6,884 

2014 8,759 2019 8,032 2024 7,623 2029 6,807 

2015 8,230 2020 8,231 2025 7,578 2030 6,934 

2016 8,129 2021 8,204 2026 7,396 2042 6,934 

I.4 SITE-TO-SOURCE ENERGY CONVERSION FACTORS 

The AHRs and MHRs discussed in the previous sections apply only to electricity 

generation. The factors used to convert electricity savings at building site into source energy 

must not only take into account the generation intensity of the utility sector but also T&D losses 

between power plant and final customers. NEMS-BT does not report annual T&D losses in its 

available set of output tables. Thus, one must rely on other information provided by EIA to 

develop an estimate of these losses. 

An explicit treatment of how DOE estimated T&D losses can be clarified by initially 

defining the following variables (in TWh): 

DE =delivered electricity 

GG =gross generation 

NG =net generation 

T&D = T&D losses 

Delivered electricity is the amount electricity delivered to the building site; energy 

efficiency standards will reduce DE. Gross generation is the total amount of electricity produced 

by the electricity sector, including the amount of electricity used in the operation of power plant. 

Net generation is the total generation less the electricity used in power plants. T&D losses 

represent the losses between NG and the electricity delivered to final customers. 

 I-7 

BVM_FINAL_FR_TSD_AppendixI_08-14-09.doc 

EERE-2006-STD-0125 COMMENT 74
 

 

 

The first two pages of section 8 in the Annual Energy Review 2007 present EIA’s 

estimates as to the approximate relationships of these quantities in the U.S. energy sector. 

Beginning with the GG and NG, EIA indicates that the electric energy used in the operation of 

power plants is “estimated as 5 percent of gross generation.” This simple relationship can be 

expressed as 

NG = 0.95 × GG Eq. I.6 

EIA also indicates that “transmission and distribution losses (electricity losses that occur 

between the point of generation and delivery to the customer) are estimated to as 9 percent of 

total generation.” In formal terms, 

T&D = 0.09 × GG Eq. I.7 

Combining Eqs. I.6 and I.7 yields 

T&D = 0.09 × (NG/0.95) = 0.0855 × NG Eq. I.8 

Because T&D is the difference between NG and DE, one can then express DE in terms of 

NG as follows: 

DE = NG – T&D = NG – 0.0855 NG = 0.9145 NG Eq. I.9 

To express the change in NG consistent with a one-unit (e.g., TWh) change in DE, both 

sides of Eq. I.9 are divided by 0.9145: 

NG = (1.0/0.9145) × DE = 1.0935 × DE Eq. I.10 

The values for electricity generation in NEMS-BT (and the AEO) are all in terms of net 

electricity generation. In essence, in NEMS-BT, the plant use of electricity is treated as any other 

losses (e.g., thermal losses in fossil fuel plants) in electricity production. Plant electricity use is 

thus already reflected in the AHRs reported by NEMS-BT. 

All of the discussion in sections I.1 through 0 thus relates to the heat rates defined in 

terms of net electricity. As the AHRs define source energy (SE) in terms of kWh of NG, the 

incorporation of Eq. I.10 provides the following relationship: 

SE = AHR × NG = AHR × 1.0935 × DE Eq. I.11 

For the analysis here, it is assumed that the overall T&D losses, on a percentage basis, 

will be the same before and after the imposition of energy efficiency standards. Thus, to evaluate 

the source energy savings associated with a change in DE use, one obtains: 

∆SE = MHR × 1.0935 × ∆DE Eq. I.12 

Table I.4.1 presents the site-to-source conversion factors expressed in terms of source Btu 

per kWh of (displaced) site electricity. The values are based on Eq. I.12, where the MHRs in 

Table I.3.1 have all been multiplied by a constant factor of 1.0935. 

 I-8 

BVM_FINAL_FR_TSD_AppendixI_08-14-09.doc 

EERE-2006-STD-0125 COMMENT 74
 

Table I.4.1 Site-to-Source Conversion Factors for Final Rule Analysis 

Year Conversion Factor, Conversion Factor, Year Conversion Factor, Conversion Factor, 

source source source source 

Btu/site kWh Btu/site Btu Btu/site kWh Btu/site Btu 

2012 8,715 2.554 2022 8,822 2.586 

2013 8,792 2.577 2023 8,472 2.483 

2014 9,577 2.807 2024 8,335 2.443 

2015 8,999 2.637 2025 8,286 2.429 

2016 8,889 2.605 2026 8,088 2.370 

2017 8,587 2.517 2027 7,835 2.296 

2018 8,693 2.548 2028 7,528 2.206 

2019 8,783 2.574 2029 7,443 2.181 

2020 9,000 2.638 2030 7,582 2.222 

2021 8,971 2.629 2031–2050 7,582 2.222 

In some applications (including some prior DOE energy conservation standards 

rulemakings), the site-to-source conversion factors have been expressed in terms of the ratios 

between source and site energy, both measured in Btu. On a site basis, the conversion of 

electricity from kWh to Btu is made with a factor of 3,412 Btu/kWh. Thus, the values in the last 

pair of columns are derived from the first two columns by dividing all entries by 3,412. 

 I-9 

BVM_FINAL_FR_TSD_AppendixI_08-14-09.doc 

EERE-2006-STD-0125 COMMENT 74
REFERENCES 

1. U.S. Department of Energy–Energy Information Administration. An Updated Annual 

Energy Outlook 2009 Reference Case Reflecting Provisions of the American Recovery 

and Reinvestment Act and Recent Changes in the Economic Outlook. April 2009. 

Washington, D.C. SR/OIAF/2009-03. 

2. U.S. Department of Energy. 2001. Central Air Conditioning Supplemental Notice of 

Proposed Rulemaking (SNOPR) Technical Support Document. Appendix M: Revised 

Utility Impact Analysis and Environmental Assessment. July 25, 2001. Washington, D.C. 

(Last accessed April 10, 2009.) 

<http://www.eere.energy.gov/buildings/appliance_standards/residential/ac_central_1000_ 

r.html> 

3. U.S. Department of Energy–Energy Information Administration. Annual Energy Review 

2007. DOE/EIA-0384(2007). June 2008. (Last accessed April 10, 2009.) 

<http://www.eia.doe.gov/emeu/aer/contents.html> 

 I-10 

BVM_FINAL_FR_TSD_AppendixI_08-14-09.doc 

EERE-2006-STD-0125 COMMENT 74