CHAPTER 7. ENERGY USE CHARACTERIZATION FOR RESIDENTIAL
 

AIR-CONDITIONING AND HEAT PUMP EQUIPMENT
 

TABLE OF CONTENTS
 

7.1 Introduction ...................................................................................................................... 7-1
 

7.1.1 General Approach to the Energy Use Analysis – Residential ............................. 7-1
 

7.1.2 General Approach to the Energy Use Analysis – Commercial............................ 7-3
 

7.1.3 Overview of Energy Use Analysis Inputs............................................................ 7-4
 

7.2 ANALYZED RECS HOUSEHOLDS ................................................................................ 7-4
 

7.3 BASELINE ANNUAL SPACE-COOLING ENERGY USE – RESIDENTIAL ............... 7-5
 

7.3.1 Methodology for Estimating Stock Annual Space-Cooling Energy Use............. 7-6
 

7.3.2 Stock Annual Space-Cooling Energy Use ........................................................... 7-7
 

7.3.3 Stock Space-Cooling Efficiency (SEER)............................................................. 7-9
 

7.3.4 Estimating Baseline Annual Space-Cooling Energy Use .................................. 7-12
 

7.4	 BASELINE ANNUAL SPACE-HEATING ENERGY USE FOR CHP EQUIPMENTRESIDENTIAL................................................................................................................. 7-13
 

7.4.1 Estimating Stock Annual Space-Heating Energy Use ....................................... 7-14
 

7.4.2 Stock Space-Heating Efficiency (HSPF)........................................................... 7-16
 

7.4.3 Estimating Baseline Annual Space-Heating Energy Use .................................. 7-18
 

7.5	 BASELINE RESIDENTIAL COOLING AND HEATING RESULTS-ADJUSTED 

FOR RECS SAMPLE WEIGHTS.................................................................................... 7-19
 

7.6	 BASELINE COMMERCIAL CAC AND CHP ENERGY USE ...................................... 7-20
 

7.7	 OVERVIEW OF COMMERCIAL ENERGY SIMULATION APPROACH ................. 7-21
 

7.7.1 Simulation Tool Description.............................................................................. 7-21
 

7.7.2 Efficiency Levels Analyzed and Corresponding Simulation Parameters .......... 7-22
 

7.7.3 Small Office Building Characteristics ............................................................... 7-23
 

7.7.4 Building Operating Characteristics.................................................................... 7-24
 

7.7.5 Building Mechanical Systems and Equipment .................................................. 7-27
 

7.8 BASELINE COMMERCIAL ENERGY DISTRIBUTION............................................. 7-27
 

7.9	 COMMERCIAL ENERGY FOR INTERMEDIATE EFFICIENCY LEVELS............... 7-29
 

7.10 MARKET BASELINE SPACE-COOLING AND SPACE-HEATING EFFICIENCIES7-29 

7.11 ESTABLISHMENT OF GEOGRAPHIC REGIONS FOR STANDARDS ANALYSIS
 

AND CORRESPONDING REGIONAL ENERGY CONSUMPTION BY
 

EFFICIENCY LEVEL ...................................................................................................... 7-32
 

7-i 
 

 

LIST OF TABLES
 

Table 7.3.1. The 30-Year Average CDD (1978–2007) and the 2005 CDD for the Nine 

Census Divisions and the Four Large States........................................................ 7-7
 

Table 7.3.2. Weather Adjusted Space-Cooling Energy Consumption Statistics at Regional 

Level (CAC-Stock) .............................................................................................. 7-8
 

Table 7.3.3. Weather Adjusted Space-Cooling Energy Consumption Statistics at Regional 

Level (CHP-Stock)............................................................................................... 7-8
 

Table 7.3.4. Number of Observations for Each Age Group ...................................................... 7-10
 

Table 7.3.5. Average Annual Shipped Space-Cooling Efficiency............................................. 7-12
 

Table 7.3.6. Baseline (13 SEER) Space-Cooling Energy Consumption Statistics at 

Regional Level (CAC) ....................................................................................... 7-13
 

Table 7.3.7. Baseline (13 SEER) Space-Cooling Energy Consumption Statistics at 

Regional Level (CHP)........................................................................................ 7-13
 

Table 7.4.1. 30-Year Average HDD (1978–2007) and the 2005 HDD for the Nine Census 

Divisions and the Four Large States .................................................................. 7-15
 

Table 7.4.2. Statistics of Annual Weather-Adjusted Space-Heating Energy Consumption 

for RECS-Stock CHP at Regional Level ........................................................... 7-15
 

Table 7.4.3. Average Annual Heating Pump HSPF .................................................................. 7-18
 

Table 7.4.4. Baseline (13 SEER) Space-Heating Energy Consumption Statistics at 

Regional Level(CHP)......................................................................................... 7-18
 

Table 7.7.1. CAC and CHP Blower and Characteristics Used in Modeling Commercial 

Cooling and Heating Energy Use ...................................................................... 7-23
 

Table 7.10.1. CAC and CHP Efficiency Distributions Estimated for 2007 .............................. 7-31
 

Table 7.10.2. CAC and CHP Efficiency Distributions Estimated for Market Baseline ............ 7-32
 

Table 7.11.1. Proposed Climate Regions for Regional Standards............................................. 7-33
 

Table 7.11.2. Split-System Air Conditioners: Average Annual Energy Use by Efficiency
 

Level for Coil-Only Systems ............................................................................. 7-34
 

Table 7.11.3. Split-System Air Conditioners: Average Annual Energy Use by Efficiency
 

Level—Blower-Coil Systems ............................................................................ 7-34
 

Table 7.11.4. Split-System Heat Pumps: Average Annual Energy Use by Efficiency
 

Level .................................................................................................................. 7-35
 

Table 7.11.5. Single-Package Air Conditioners: Average Annual Energy Use by
 

Efficiency Level................................................................................................. 7-35
 

Table 7.11.6. Single-Package Heat Pumps: Average Annual Energy Use by Efficiency
 

Level .................................................................................................................. 7-36
 

LIST OF FIGURES 

Figure 7.1.1. Flow Diagram for the Determination of Annual Space-Cooling Energy for 

Residential CAC and CHPs ................................................................................. 7-2
 

Figure 7.1.2. Flow Diagram for the Determination of Annual Space-Heating Energy for 

Residential CHPs ................................................................................................. 7-3
 

Figure 7.1.3. Flow Diagram for the Determination of Annual Space-Cooling and SpaceHeating Energy for CAC and CHPs in Commercial Use .................................... 7-4
 

7-ii 
 

 

Figure 7.3.1. National Distribution of Weather-Adjusted Space-Cooling Energy for 

RECS Observations ............................................................................................. 7-9
 

Figure 7.3.2. National Distribution of Weather-Adjusted Space-Cooling Energy for CHPRECS Observations ............................................................................................. 7-9
 

Figure 7.3.3. The Distribution of CACs in the RECS Sample by Age Groups ......................... 7-10
 

Figure 7.3.4. The Distribution of CHPs in the RECS Sample by Age Groups ......................... 7-11
 

Figure 7.3.5. Distribution of RECS Households with CACs by Vintage.................................. 7-11
 

Figure 7.4.1. National Distribution of Weather-Adjusted Space-Heating Energy for RECS
 

Observations ...................................................................................................... 7-16
 

Figure 7.4.2. Distribution of Households with Heating-Performance Heat Pumps by Age 

Groups................................................................................................................ 7-17
 

Figure 7.4.3. Distribution of RECS Households with Central Heat Pumps by Vintage ........... 7-17
 

Figure 7.5.1. Baseline National Cooling Energy Distribution for CAC – Residential .............. 7-19
 

Figure 7.5.2. Baseline National Cooling Energy Distribution for CHP – Residential .............. 7-19
 

Figure 7.5.3. Baseline National Heating Energy Distribution for CHP – Residential ............... 7-20
 

Figure 7.7.1. Small Office Building Design View..................................................................... 7-24
 

Figure 7.7.2. Small Office Building HVAC Zoning.................................................................. 7-24
 

Figure 7.7.3. Small Office Lighting Schedule ........................................................................... 7-25
 

Figure 7.7.4. Small Office Plug Load Schedule ........................................................................ 7-26
 

Figure 7.7.5. Small Office Occupancy Schedule....................................................................... 7-26
 

Figure 7.7.6. Small Office Thermostat Set Point Schedule ....................................................... 7-27
 

Figure 7.8.1. Baseline National Cooling Energy Distribution for CAC-Commercial, 

Weighted ............................................................................................................ 7-28
 

Figure 7.8.2. Baseline National Cooling Energy Distribution for CHP-Commercial, 

Weighted ............................................................................................................ 7-28
 

Figure 7.8.3. Baseline National Heating Energy Distribution for CHP-Commercial, 

Weighted ............................................................................................................ 7-29
 

7-iii 
 

 

7.1 INTRODUCTION 

The energy use analysis provides estimates of the distribution of annual energy 

consumption for central air conditioner (CAC) and central heat pump (CHP) equipment at the 

base case (i.e., with no new standards) and at efficiency standard levels considered in the 

analysis. This information is used in the subsequent life-cycle cost (LCC) and payback period 

(PBP) analyses (chapter 8 of the technical support document [TSD]), which in turn provides the 

raw energy use data for the national impacts analyses (chapter 11 of the TSD). Both energy use 

in the residential sector customers and to the commercial sector customer are considered. In the 

energy use analysis, the United States (U.S.) Department of Energy (DOE) developed energy 

consumption estimates for four equipment classes analyzed in the engineering analysis (chapter 5 

of the TSD). For one equipment class, split-system air conditioners, two installation methods 

were separately considered: coil-only, where the indoor furnace fan is not replaced for higher 

efficiency equipment, and blower-coil, where the indoor blower is replaced, corresponding to the 

similar breakdown of this equipment class in the engineering analysis. 

7.1.1 General Approach to the Energy Use Analysis – Residential 

The general approach adopted in the energy use analysis for CAC equipment used in 

residences was to utilize energy use and household characteristics data from the DOE Energy 

Information Agency (EIA) 2005 Residential Energy Consumption Survey (RECS) to provide 

estimates of cooling and heating energy for the sample households using CAC and CHP 

equipment. This estimate reflects household stock equipment efficiency levels. The energy use 

estimates are then adjusted to reflect long term average weather conditions and then further 

adjusted to reflect equipment energy consumption for the same households assuming that they 

were using new equipment as would be purchased in 2016 under a base case standards scenario. 

A sample population of U.S. homes using CAC and CHP equipment was first identified 

from the RECS households surveyed. This sample provided a dataset of cooling and heating 

energy use for 2005 for households with CACs and CHPs. This data were then adjusted 

(weather-normalized) to reflect corresponding energy-use figures for typical long-term climate 

conditions. Historical efficiency data for shipped CAC and CHP equipment was used in 

conjunction with equipment age information from RECS to estimate the stock equipment 

efficiency for each household record used in the analysis. The annual energy consumption for 

equipment in the 2016 base case (i.e., no new standards) was then calculated for each equipment 

class by multiplying the weather-adjusted cooling or heating energy use for each RECS 

household by the ratio of the efficiency (e.g., SEER) of the stock unit in that household to that of 

an assumed efficiency for that household in the 2016 base case. This 2016 base case provides an 

efficiency level likely to be purchased for each household assuming a new CAC or CHP 

purchase in that year. The 2016 efficiency levels used for each household were selected at 

random from a distribution of shipped efficiencies developed for each product class. This base 

case is also referred to as the market baseline case, since the efficiency distribution is 

representative of the current market for CAC and CHP equipment. 

Once the base case cooling energy use was established for a selected RECS household 

record, the corresponding annual cooling energy consumption for higher efficiencies under new 

standard scenarios was calculated by multiplying the cooling energy consumption for each 

7-1 
 

 

 

 

 

 

 

household in the base case by the ratio of the seasonal energy efficiency ratio (SEER) in the base 

case to that of the SEER in the standards case. In the case of heating energy use for heat pumps 

the corresponding household annual heat pump heating energy consumption under new standard 

scenarios was calculated by multiplying the heat pump heating energy consumption for each 

household in the base case by the ratio of the heating seasonal performance factor (HSPF) in the 

base case to the HSPF in the standards case. Figure 7.1.1 and Figure 7.1.2 provide a flow 

diagram on calculation of cooling and heating energy for the residential energy use analysis. 

RECS Baseline SEER Market Baseline
 

Stock Household (SEER 13) SEER Standard Level 

Annual Cooling
 

Estimated SEER 

of Stock 

CAC or CHP 

Distribution SEER
 

Energy (Weather
 

Normalized)
 

RECS
 

Age of Household 

CAC or CHP
 Baseline Market Baseline Standard Level 

Annual Cooling Annual Cooling Annual Cooling 

Energy Use Energy Use Energy Use 

AHRI 

Shipment Average 

SEER 

CAC and CHP 

Figure 7.1.1. Flow Diagram for the Determination of Annual Space-Cooling Energy for 

Residential CAC and CHPs 

7-2 
 

 

 

 

RECS 

Stock Household 

Annual Heating 

Energy (Weather 

Normalized) 

RECS 

Age of Household 

CHP 

Baseline SEER 

(HSPF 7.7) 

Baseline 

Annual Heating 

Energy Use 

Market Baseline
 

HSPF Distribution
 

Market Baseline 

Annual Heating 

Energy Use 

Standard Level 

HSPF 

Standard Level 

Annual Heating 

Energy Use 

Estimated 

HSPF of Stock 

CHP 

AHRI 

Shipment Average 

HSPF by Vintage 

CHP 

Figure 7.1.2. Flow Diagram for the Determination of Annual Space-Heating Energy for 

Residential CHPs 

7.1.2 General Approach to the Energy Use Analysis – Commercial 

DOE also developed estimates for the annual energy use for CAC and CHP sold into the 

commercial building market. The commercial market is estimated to use approximately seven 

percent of all CAC and CHP equipment. For the commercial analysis, DOE relied on the use of 

the EnergyPlus building simulation software to estimate the energy consumption of this 

equipment at four specific efficiency levels-from baseline to the max tech level-for 237 climates 

around the United States for a typical commercial application, a small office building. DOE 

extracted equipment sizing, supply fan, condenser and heater energy use from these simulations. 

DOE then used these results to develop estimates of annual energy use for CAC and CHP 

equipment at other efficiency levels defined in the engineering analysis via interpolation between 

the efficiency levels simulated. Figure 7.1.3 provides a flow diagram for the calculation of CAC 

and CHP cooling and heating energy for the commercial energy use analysis. 

7-3 
 

 

Figure 7.1.3. Flow Diagram for the Determination of Annual Space-Cooling and SpaceHeating Energy for CAC and CHPs in Commercial Use 

7.1.3 Overview of Energy Use Analysis Inputs 

The following are the principal inputs to the residential energy use analysis: 

• Household cooling and heating energy from 2005 RECS 

• CAC and CHP equipment age information for the RECS households 

• Historical state average monthly cooling and heating degree day data (1978–2007) 

• Historical average cooling and heating efficiency data for CAC and CHP from AHRI 

• Base case efficiency distributions for 2016 developed for this analysis 

• Engineering efficiency levels to be analyzed 

• The following are the principal inputs to the commercial energy use analysis: 

• Engineering efficiency levels to be analyzed 

• Location specific weather file data for use with building simulation tool 

• Population-based weighting factors for each weather file 

7.2 ANALYZED RECS HOUSEHOLDS 

The 2005 RECS includes data for 4,382 housing units, of which 2,317 were reported to 

have “CAC only” cooling systems. These include 416 housing units reporting their CAC unit 

also being cooling-performance heat pumps. The number of households actually included in the 

LCC and PBP analyses were 1,854 for the CAC systems and 339 for heat pumps. Out of the 

1901 (2317-416) households that could have been potentially considered for analysis of CAC 

energy consumption, 47 were not included in the analysis for the following reasons: 

• the CAC system was reported as not being used (40 households), and 

Small Office 

Building Model 

EnergyPlus Simulation Tool 

CAC or CHP 

Characteristics for 

Four Selected 

Efficiency Levels 

TMY Weather 

Data Bldg. Annual 

Cooling, Heating, 

Fan Energy Use 

Zone Peak 

Equipment Sizes 

Annual Cooling, Heating, Fan Energy Use 

for Selected Efficiency Levels 

 (Normalized to 3-Ton unit) 

Market Baseline 

Annual Cooling , 

Heating, and Fan 

Energy Use 

Market Baseline 

SEER /HSPF 

Distribution 

Standard Level 

SEER/HSPF 

Standard Level 

Annual Cooling , 

Heating, and Fan 

Energy Use 

7-4 
 

 

 

 

 

•	 the household reported a “heat pump” being the main heating equipment, contradicting a 

second response that their CAC system is not a heat pump (7 households). 

For the seven households with conflicting responses, it was considered that the response 

regarding the main heating equipment being a heat pump should override the secondary response 

and these records were included in the set for analyzing energy consumption for heat pumps. 

For the heat pumps, out of the 423 (416+7) candidate households, DOE removed 84 for 

the following reasons: 

•	 The system was reportedly not being used (6 households). 

•	 The survey responses reported a non-furnace heating equipment (i.e., heating stove, 

fireplace, built-in wall furnaces etc. being the main heating equipment), thus implying 

that the heating energy use reported for the household should not be primarily attributed 

to the heat pump (17 households). 

•	 Some households indicated a warm air furnace as the main heating equipment and no 

electrical energy use for space heating implying that the heat pump function is not used at 

all or that the RECS may be reporting the “heat pump” energy consumption or presence 

in error (36 households), and 

•	 Some households report a warm air furnace as well as heat pump, but questions on usage 

of any complementary fuel were skipped. This led to an ambiguity about whether the 

heating energy use reported from the conditional demand model was reported as 

representative of a heat pump or an electric furnace. Barring more detail on the analysis 

of these records by EIA, they were removed from consideration in DOE’s analysis (25 

households). 

7.3 BASELINE ANNUAL SPACE-COOLING ENERGY USE – RESIDENTIAL 

In order to estimate the energy savings for higher standards, DOE first established 

estimates of cooling and heating energy consumption for baseline equipment based on energy 

consumption in the current stock and product efficiency assumptions appropriate to the stock 

equipment and the efficiency of baseline products. The energy consumption of CACs and CHPs 

in the equipment stock is related to the capacity and efficiency of these products, the climate, and 

individual household use patterns. The efficiency of the equipment in the building stock also 

varies depending on the vintage. The energy consumption of residential air-conditioners and heat 

pumps in the current stock and estimates of the efficiency in the current stock are used in 

conjunction with the efficiencies of baseline equipment to provide an estimate of energy 

consumption of baseline equipment. The baseline annual space-cooling energy consumption for 

residential air conditioners and cooling-performance heat pumps was estimated for each RECS 

observation using equation 7.3.1. 

SEERres _ stock UEC = UEC ×	 Eq. 7.3.1 res _ base _ c res _ stock _ c SEERbase 

Where: 

7-5 
 

 

 

UECres_base_c = the baseline annual unit energy consumption for space-cooling, 

UECres_stock_c = the annual unit energy consumption space-cooling associated with the 

stock equipment, 

SEERbase = the space-cooling efficiency associated with the baseline equipment, 

and 

SEERres_stock_c = the space-cooling efficiency associated with the stock equipment. 

Thus, once the annual space-cooling energy consumption associated with the stock 

equipment, UECres_stock_c, and the space-cooling efficiency, SEERres_stock_c, are determined; the 

baseline annual space-cooling energy consumption is estimated. In the next section, the 

methodology for obtaining UECres_stock_c and SEERres_stock are discussed. 

7.3.1 Methodology for Estimating Stock Annual Space-Cooling Energy Use 

The stock annual space cooling energy consumption was estimated based on data from 

the 2005 RECS. This survey contains data on household characteristics, end use energy 

consumption, general location in the United States (limited to location within census division and 

four large states; New York, Florida, Texas and California), and approximate heating and 

cooling degree days for each sample location for the year of the survey. The latter two statistics 

are purposefully kept general or sufficiently masked by EIA to preclude identification of the 

surveyed residences. 

The household energy consumption for the individual surveyed households in RECS are 

obtained by EIA from the energy suppliers via monthly energy bill records. EIA uses a 

conditional demand analysis (CDA)1 model to further breakdown the household energy use into 

end-use energy consumption estimates (e.g., cooling, heating, lighting, and hot water energy) 

which it reports as annual end-use energy in the survey results. The cooling energy use for the 

selected households with CAC or CHP products represents the cooling energy consumption 

associated with the stock equipment for 2005. Because 2005 may not be representative of typical 

weather for that location, the cooling energy consumption associated with the stock equipment in 

the RECS households are first adjusted (weather normalized) using 30-year-average (1978– 

2007) cooling degree day (CDD) data (base 65 °F) and Eq. 7.3.2: 

CDD30 _ yr _ avg UECres _ stock _ c = UECres _ stock _ c _ non−adj ×

CDD Eq. 7.3.2 

res _ stock _ 2005 

Where: 

UECres_stock_c_non-adj = annual space-cooling energy consumption associated with the 

stock equipment, extracted directly from RECS household data, 

UECres_stock_c = annual space-cooling consumption associated with the stock 

equipment, adjusted by using 30-year average CDD data for the 

RECS location, 

CDDres_stock_2005 = CDD in 2005 for the specific Census Division or state where the 

housing unit is located, and 

CDD30_yr_avg = 30-year average CDD (1978–2007) for the specific Census 

Division or state where the housing unit is located. 

7-6 
 

 

 

7.3.2 Stock Annual Space-Cooling Energy Use 

DOE first weather-normalized the cooling energy use data for the selected RECS 

households to better reflect long term average weather conditions for each location. DOE 

obtained CDD data for each state on a monthly basis for 1978–2007 from the National Oceanic 

and Atmospheric Administration (NOAA) National Climatic Data Center (NCDC).2 DOE 

aggregated the monthly data for each year to produce annual CDD data for each state. These 

were then further aggregated geographically to the specific census divisions or four large state 

geographic regions used by RECS. These states included in each of these geographic regions are 

shown in Table 7.3.1. 

In estimating annual CDD for each census division, the annual CDD for the states in each 

division are weighted according to the population in the component states for the specific year. 

Population data from 1978 to 2007 were developed based on 1980, 1990, and 2000 U.S. Census 

Bureau data,3 with estimates for other years obtained by linear interpolation or extrapolation as 

necessary. The resulting 30-year average CDD and the 2005 CDD for the regions are shown in 

Table 7.3.1. 

Table 7.3.1. The 30-Year Average CDD (1978–2007) and the 2005 CDD for the Nine Census 

Divisions and the Four Large States 

Division States 30-Year 

Average CDD 

2005 CDD 

1: New England Connecticut, Maine, Massachusetts, New Hampshire, 

Rhode Island, Vermont 

462 579 

2: Middle Atlantic New Jersey, Pennsylvania 737 991 

3: East North Central Indiana, Illinois, Michigan, Ohio, Wisconsin 758 983 

4: West North Central Iowa, Kansas, Minnesota, Missouri, Nebraska, North 

Dakota, South Dakota 

989 1,171 

5: South Atlantic Delaware, District of Columbia, Georgia, Maryland, 

North Carolina, South Carolina, Virginia, West Virginia 

1,382 1,486 

6: East South Central Alabama, Kentucky, Mississippi, Tennessee 1,620 1,747 

7: West South Central Arkansas, Louisiana, Oklahoma 2,215 2,402 

8: Mountain Arizona, Colorado, Idaho, New Mexico, Montana, Utah, 

Nevada, Wyoming 

1,318 1,498 

9: Pacific Alaska, Hawaii, Oregon, Washington 226 226 

Four Large States New York 654 943 

California 949 837 

Texas 2,711 2,908 

Florida 3,505 3,436 

Based on the 2005 RECS annual space-cooling energy consumption data and the CDD 

data, the weather-adjusted annual space-cooling energy consumption for each household was 

obtained by using Eq. 7.3.2. Statistics showing the weather-adjusted annual space-cooling energy 

consumption for the households that have air-conditioners are shown in Table 7.3.2. Statistics 

showing the weather-adjusted annual space-cooling energy consumption for the households that 

have heat pumps are shown in 

7-7 
Table 7.3.3. The frequency distribution of the weather-adjusted annual household energy 

consumption for space-cooling for CAC and CHP for the RECS observations are shown in 

Figure 7.3.1 and Figure 7.3.2. 

Table 7.3.2. Weather Adjusted Space-Cooling Energy Consumption Statistics at Regional 

Level (CAC-Stock) 

Division or State Number of 

Observations 

Min 

kilowatt 

hours per 

year 

(kWh/yr) 

Max 

kWh/yr 

Average 

kWh/yr 

New England 50 56 4,186 1,229 

Middle Atlantic 127 289 5,420 1,650 

East North Central 346 130 9,459 1,477 

West North Central 224 207 9,882 2,067 

South Atlantic 233 152 8,628 2,952 

East South Central 173 331 11,573 3,653 

West South Central 79 647 12,359 4,070 

Mountain 130 65 26,078 3,167 

Pacific 23 89 3,610 1,273 

New York 34 333 5,361 1,295 

California 160 36 17,335 1,835 

Texas 181 44 29,326 5,780 

Florida 94 1,508 14,688 6,104 

National 1,854 36 29,326 2,851 

Table 7.3.3. Weather Adjusted Space-Cooling Energy Consumption Statistics at Regional 

Level (CHP-Stock) 

Division or State Number of 

Observations 

Min 

kWh/yr 

Max 

kWh/yr 

Average 

kWh/yr 

New England 1 432 432 432 

Middle Atlantic 10 214 2,182 1,460 

East North Central 20 455 6,938 2,315 

West North Central 12 234 5,634 2,413 

South Atlantic 108 445 11,059 3,442 

East South Central 54 1,157 11,586 3,968 

West South Central 6 1,246 9,573 4,545 

Mountain 23 3,220 12,893 7,194 

Pacific 13 78 3,221 1,060 

New York 1 761 761 761 

California 11 312 6,449 2,492 

Texas 15 2,166 11,363 6,423 

Florida 65 1,805 17,380 6,738 

National 339 78 17,380 4,264 

7-8 
 

 

 

 

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

Percentage of Obersavtions 

Weather-Adjusted CAC Cooling Energy from RECS 

(kWh/yr) 

Figure 7.3.1. National Distribution of Weather-Adjusted Space-Cooling Energy for RECS 

Observations 

0%

2%

4%

6%

8%

10%

12%

14%

Percentage of Obersavtions 

Weather-Adjusted CHP Cooling Energy from RECS 

(kWh/yr) 

Figure 7.3.2. National Distribution of Weather-Adjusted Space-Cooling Energy for CHPRECS Observations 

7.3.3 Stock Space-Cooling Efficiency (SEER) 

To estimate annual space-cooling energy consumption data at the baseline and higher 

efficiency levels, DOE relies on the cooling and heating energy calculated for the stock 

households and the historic space-cooling efficiency levels of the stock equipment, SEERres_stock. 

The space-cooling efficiency of stock equipment is related to the vintage of the equipment. In the 

2005 RECS database, the age of the equipment is reported in terms of age groups and not the 

specific vintage year. The five age groups are “less than 2 years old,” “2 to 4 years old,” “5 to 

7-9 
 

 

 

 

9 years old,” “10 to 19 years old,” and “20 years or older.” The data also include one additional 

age category: “as old as the home.” In RECS the years of construction of each residence for older 

homes are also reported in age bands though the specific year of construction is indicated for the 

newer homes. DOE assumed that the age of the CAC system, within a given age group in the 

general population would be approximately uniformly distributed throughout the range of the age 

band. For example, for the CAC systems in the “less than 2 years old” age group, it was 

assumed that 50 percent of heat pumps were one year old and the other 50 percent were 2 years 

old. Similar technique was used in ascertaining the probable vintage year of the home and the 

equipment when the equipment was reported to be the age of the home. The resulting age 

distribution of the CACs and CHPs in the RECS households identified for analysis are shown in 

Table 7.3.4 and graphically in Figure 7.3.3 and Figure 7.3.4, respectively. 

Table 7.3.4. Number of Observations for Each Age Group 

Equipment Type Less than 2 

Years Old 

2 to 4 

Years Old 

5 to 9 

Years Old 

10 to 19 

Years Old 

20 Years 

or Older 

Total 

Central Air 243 321 472 502 316 1854 

Conditioners 13.1% 17.3% 25.5% 27.1% 17.0% 100% 

Cooling-Performance 57 61 104 89 28 339 

Heat Pump 16.8% 18.0% 30.7% 26.3% 8.3% 100% 

0.0% 

5.0% 

10.0% 

15.0% 

20.0% 

25.0% 

30.0% 

Percent Of households 

Less than 2 2 to 4 years 5 to 9 years 10 to 19 20 years or 

years old old old years old older 

Age of CAC Systems 

Figure 7.3.3. The Distribution of CACs in the RECS Sample by Age Groups 

Once the age group in which the household equipment falls into was established, DOE 

estimated the vintage of the equipment for each household in each age group by random 

assignment using the uniform age distribution assumption for each age group and the known 

2005 survey year. For the 20-year and older age group, all equipment were assumed to be 

between 20 and 29 years old with the actual vintage assigned using a uniform distribution. The 

7-10 
 

resulting vintage distribution of the residential air conditioners and heat pumps in the overall 

sample is shown in Figure 7.3.5. 

DOE estimated the stock cooling SEER for each household using equipment vintage and 

average shipped efficiency for each vintage year. The latter was developed from AHRI data4 and 

is shown in Table 7.3.5. 

0.0% 

5.0% 

10.0% 

15.0% 

20.0% 

25.0% 

30.0% 

35.0% 

Less than 

2 years 

old 

2 to 4 

years old 

5 to 9 

years old 

10 to 19 

years old 

20 years 

or older 

Age of Heat Pump Systems 

Percent Of households 

Figure 7.3.4. The Distribution of CHPs in the RECS Sample by Age Groups 

0.0% 

1.0% 

2.0% 

3.0% 

4.0% 

5.0% 

6.0% 

7.0% 

8.0% 

1,9761,9781,9801,9821,9841,9861,9881,9901,9921,9941,9961,9982,0002,0022,004 

Vintage year of CAC Equipm ent 

Percent of Households 

Figure 7.3.5. Distribution of RECS Households with CACs by Vintage 

7-11 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 7.3.5. Average Annual Shipped Space-Cooling Efficiency 

Year Central A/C 

(SEER) 

Heat Pump (SEER) 

1976 7.15 6.87 

1977 7.18 6.89 

1978 7.41 7.24 

1979 7.45 7.34 

1980 7.51 7.51 

1981 7.73 7.70 

1982 8.30 7.79 

1983 8.44 8.23 

1984 8.70 8.45 

1985 8.84 8.56 

1986 8.87 8.70 

1987 8.95 8.93 

1988 9.11 9.13 

1989 9.23 9.26 

1990 9.25 9.41 

1991 9.44 9.73 

1992 10.43 10.56 

1993 10.52 10.82 

1994 10.58 10.89 

1995 10.64 10.93 

1996 10.63 10.95 

1997 10.62 10.93 

1998 10.23 10.52 

1999 10.86 11.24 

2000 10.95 11.23 

2001 11.07 11.31 

2002 11.07 11.32 

2003 11.22 11.48 

2004 11.32 11.58 

2005 11.33 11.69 

7.3.4 Estimating Baseline Annual Space-Cooling Energy Use 

For each class of equipment, the baseline annual space-cooling energy consumption for 

each equipment type (air-conditioner or heat pump) was estimated by using Eq. 7.3.2. The key 

inputs are the weather-adjusted annual space-cooling energy consumption derived from the 2005 

RECS data, the stock space-cooling efficiency estimates for air conditioners and heat pumps 

from Table 7.3.5, and the baseline cooling efficiency, 13 SEER. 

Statistics for the baseline space-cooling energy consumption for RECS households at 

regional and national level are shown in Table 7.3.6 for air conditioners and Table 7.3.7 for heat 

pumps. 

7-12 
 

 

Table 7.3.6. Baseline (13 SEER) Space-Cooling Energy Consumption Statistics at Regional 

Level (CAC) 

Division or State Number of 

Observations 

Min 

kWh/yr 

Max 

kWh/yr 

Average 

kWh/yr 

New England 50 45 3,526 987 

Middle Atlantic 127 246 4,550 1,270 

East North Central 346 104 7,967 1,148 

West North Central 224 145 8,324 1,593 

South Atlantic 233 119 7,513 2,314 

East South Central 173 247 10,078 2,864 

West South Central 79 433 10,115 3,082 

Mountain 130 53 21,344 2,536 

Pacific 23 78 3074 1,029 

New York 34 229 3645 1,016 

California 160 24 15,095 1,440 

Texas 181 30 25,536 4,520 

Florida 94 1,234 12,372 4,860 

National 1,854 24 25,536 2,231 

Table 7.3.7. Baseline (13 SEER) Space-Cooling Energy Consumption Statistics at Regional 

Level (CHP) 

Division or State Number of 

Observations 

Min 

kWh/yr 

Max 

kWh/yr 

Average 

kWh/yr 

New England 1 249 249 249 

Middle Atlantic 10 118 1,823 1,236 

East North Central 20 323 5,566 1,882 

West North Central 12 190 4,911 1,962 

South Atlantic 108 320 9,417 2,779 

East South Central 54 909 9,465 3,203 

West South Central 6 973 6,797 3,568 

Mountain 23 2,424 8,876 5,616 

Pacific 13 68 2,339 842 

New York 1 663 663 663 

California 11 263 5,492 1,960 

Texas 15 1,473 9,191 5,278 

Florida 65 1,311 13,677 5,339 

National 339 68 13,677 3,412 

7.4	 BASELINE ANNUAL SPACE-HEATING ENERGY USE FOR CHP 

EQUIPMENT- RESIDENTIAL 

The baseline annual space-heating energy consumption for the CHP system is estimated 

following procedures similar to that for estimating the baseline annual space-cooling energy 

consumption. The baseline annual space-heating energy consumption for residential heat pumps 

is estimated by using the following equation: 

HSPFres _ stock UEC = UEC ×	 Eq. 7.4.1 res _ base _ h res _ stock _ h HSPFbase 

7-13 
 

 

 

 

 

 

 

Where, 

UECres_base_h = the baseline annual space-heating energy consumption 

UECres_stock_h = the annual space-heating energy consumption associated with the stock 

heat pump 

HSPFres_stock_h = the space-heating efficiency associated with the stock equipment 

HSPFbase = the space-heating efficiency associated with baseline equipment 

7.4.1 Estimating Stock Annual Space-Heating Energy Use 

The annual space-heating energy consumption for the CHP systems in the stock was 

obtained from the 2005 RECS database for the heat pump sample identified. To account for the 

variation in weather conditions for the year 2005 from statistical normals, the annual spaceheating energy consumption in 2005 was adjusted by using the following equation: 

HDD30 _ yr _ avg UECres _ stock _ h = UECres _ stock _ h _ non−adj ⋅ HDD Eq. 7.4.2 

res _ stock 

Where: 

UECres_stock_h = annual space-heating energy consumption associated with the 

stock equipment after weather-adjustment, 

UECres_stock_h_non-adj = annual space-heating energy consumption, obtained directly from 

RECS database, 

HDD30_yr_avg = 30-year (1978-2007) average heating degree day (HDD, base 65 

°F) for the census division or state where the household is located, 

and 

HDDres-stock = HDD in 2005 (base 65 °F) for the census division or state where 

the household is located. 

State-wise monthly HDD data from 1978 to 2007 were obtained from National Oceanic 

and Atmospheric Administration (NOAA) database center.2 DOE aggregated the monthly data 

for each year to produce annual HDD for each state. The state annual HDD data were used to 

derive annual HDD for the regions identified in RECS (census divisions and separately four 

large states). In estimating divisional annual HDD, the annual HDD values for states within the 

regions were weighted by the state population in that year as described in section 7.3.1. The 30­

year average HDD and the 2005 HDD for the nine census divisions and the four large states are 

shown in Table 7.4.1 

7-14 
 

 

 

 

 

 

 

 

 

Table 7.4.1. 30-Year Average HDD (1978–2007) and the 2005 HDD for the Nine Census 

Divisions and the Four Large States 

Division or State 30-Year HDD 

Average 

2005 HDD 

New England 6,571 6,453 

Middle Atlantic 5,602 5,612 

East North Central 6,103 6,323 

West North Central 5,989 6,506 

South Atlantic 3,665 3,720 

East South Central 3,309 3,496 

West South Central 2,415 2,723 

Mountain 4,666 5,142 

Pacific 5,133 5,193 

New York 5,912 5,929 

California 2,450 2,488 

Texas 1,686 1,944 

Florida 647 657 

By using equation (7.3.2), the weather-adjusted annual space-heating energy 

consumption was estimated for the equipment in each household. Statistics for the weatheradjusted space-heating energy consumption at both divisional and national level are shown in 

Table 7.4.2. The frequency distribution of the RECS sample households in different heating 

energy consumption bands is shown in Figure 7.4.1. 

Table 7.4.2. Statistics of Annual Weather-Adjusted Space-Heating Energy Consumption 

for RECS-Stock CHP at Regional Level 

Division or State Number of 

Observations 

Min 

kWh/yr 

Max 

kWh/yr 

Mean 

kWh/yr 

New England 1 2,399 2,399 2,399 

Middle Atlantic 10 581 5,177 2,871 

East North Central 20 1,911 10,037 4,237 

West North Central 12 926 4,778 2,702 

South Atlantic 108 0 6,412 2,692 

East South Central 54 0 5,667 2,468 

West South Central 6 354 4,434 2,386 

Mountain 23 424 1,630 891 

Pacific 13 2,171 5,251 3,621 

New York 1 3,409 3,409 3,409 

California 11 324 3,850 1,391 

Texas 15 998 3,788 1,671 

Florida 65 200 1,470 625 

National 339 0 10,037 2,179 

7-15 
 

0%

5%

10%

15%

20%

25%

Percentage of Obersavtions 

Weather-Adjusted CHP Heating Energy from RECS 

(kWh/yr) 

Figure 7.4.1. National Distribution of Weather-Adjusted Space-Heating Energy for RECS 

Observations 

7.4.2 Stock Space-Heating Efficiency (HSPF) 

The space-heating efficiency of CHP equipment has improved over time in response to 

both technology improvement and minimum efficiency standards. DOE related the space-heating 

efficiency of heat pumps in the stock to the equipment vintage, much as was done for the cooling 

efficiency. In the 2005 RECS database, the age groups of the equipment and not their specific 

vintage is given. The five age groups are “less than 2 years old,” “2 to 4 years old,” “5 to 9 years 

old,” “10 to 19 years old,” and “20 years or older.” The data reported also include one additional 

category: “as old as the home.” The years of construction of the home for older homes are also 

reported in age bands. It was assumed that the age of a heat pump, within a given age group was 

uniformly distributed over the range of the age group. For example, for the heat pumps in the 

“less than 2 years old” age group, it was assumed that 50 percent of heat pumps were one year 

old and the other 50 percent were two years old. Similar technique was used in ascertaining the 

probable vintage year of the home and the equipment when both were reported to have the same 

age. The distribution of households with heating-performance heat pumps by age groups is 

shown in Figure 7.4.2 and the distribution heat pump vintages are shown in Figure 7.4.3. 

AHRI does not publish data on the historical average HSPF for CHP equipment. DOE 

developed historical HSPF estimates from two data sources. For the years from 1973 to 1993, 

DOE used data reported in the Technical Support Document for the 2001 Rulemaking.5

 For the 

period from 1994 to 2005, DOE examined the 1994 ARI directory of Certified Products, and 

developed a regression equation which relates the SEER of residential split system heat pump 

DOE used the 1994 ARI Directory of Certified Equipment Database6

 to generate regressions 

between SEER and HSPF for CHP equipment on the market in 1994. For split systems, DOE 

used a regression based on data for all CHP characterized by the AHRI designations HRCU-ACB and HRCU-A-C. For packaged heat pumps, DOE used a regression for all CHP equipment 

with an HSP-A designation. Only single phase equipment with ratings listed as “Active”, “not 

7-16 
 

intended for export only”, were included. This resulted in two regression equations, one for the 

split system heat pump equipment class and one for single package heat pump equipment class. 

The historical average HSPF for each equipment class was calculated using historical annual 

average SEER values by equipment class from AHRI7

 and the appropriate regression equation. 

The annual average HSPF for all CHP equipment was then developed by weighting the annual 

average HSPF values by class using historical shipment data by equipment class. Table 7.4.3 

shows the resulting historical HSPF values by year. 

0.0% 

5.0% 

10.0% 

15.0% 

20.0% 

25.0% 

30.0% 

35.0% 

Less than 

2 years 

old 

2 to 4 

years old 

5 to 9 

years old 

10 to 19 

years old 

20 years 

or older 

Age of Heat Pump Systems 

Percent Of households 

Figure 7.4.2. Distribution of Households with Heating-Performance Heat Pumps by Age 

Groups 

0.0% 

2.0% 

4.0% 

6.0% 

8.0% 

10.0% 

12.0% 

1,976 

1,979 

1,982 

1,985 

1,988 

1,991 

1,994 

1,997 

2,000 

2,003 

Vintage Year of the Heat Pump Systems 

Percent of Households 

Figure 7.4.3. Distribution of RECS Households with Central Heat Pumps by Vintage 

7-17 
 

Table 7.4.3. Average Annual Heating Pump HSPF 

Year Average HSPF Year Average HSPF 

1973 5.66 1990 6.98 

1974 5.66 1991 7.08 

1975 5.66 1992 7.19 

1976 5.66 1993 7.30 

1977 5.74 1994 7.38 

1978 5.83 1995 7.39 

1979 5.91 1996 7.40 

1980 6.00 1997 7.39 

1981 6.09 1998 7.29 

1982 6.18 1999 7.47 

1983 6.28 2000 7.46 

1984 6.37 2001 7.49 

1985 6.47 2002 7.49 

1986 6.56 2003 7.53 

1987 6.66 2004 7.56 

1988 6.81 2005 7.58 

1989 6.87 

7.4.3 Estimating Baseline Annual Space-Heating Energy Use 

For each class of equipment, the baseline annual space-heating energy consumption for 

CHP was estimated by using equation 7.4.2. The key inputs are the weather-adjusted annual 

space-heating energy consumption derived from the 2005 RECS data, the stock space-heating 

efficiency estimates for CHP shown in Table 7.3.5, and the baseline heating efficiency, 

7.7 HSPF. 

Statistics showing the baseline space-heating energy consumption calculated for RECS 

households with CHP equipment at regional and national level are shown in Table 7.4.4. 

Table 7.4.4. Baseline (13 SEER) Space-Heating Energy Consumption Statistics at Regional 

Level(CHP) 

Division Number of 

Observations 

Min 

kWh/yr 

Max 

kWh/yr 

Average 

kWh/yr 

New England 50 1,869 1,869 1,869 

Middle Atlantic 127 443 5,030 2,778 

East North Central 346 1,869 9,855 4,000 

West North Central 224 789 4,585 2,546 

South Atlantic 233 0 6,105 2,554 

East South Central 173 0 5,068 2,323 

West South Central 79 340 3,956 2,240 

Mountain 130 346 1,329 824 

Pacific 23 2,132 4,542 3,407 

New York 34 3,356 3,356 3,356 

California 160 287 3,745 1,305 

Texas 181 982 3,684 1,580 

Florida 94 170 1,351 586 

National 1,854 0 9,855 2,058 

7-18 
 

7.5	 BASELINE RESIDENTIAL COOLING AND HEATING RESULTS-ADJUSTED 

FOR RECS SAMPLE WEIGHTS 

Table 7.3.6 , Table 7.3.7, and Table 7.4.4 directly reflect the RECS household sample 

data. These tabulated results do not take into account the sample weights assigned by RECS for 

the different households. Figure 7.5.1, Figure 7.5.2, and Figure 7.5.3 show the distribution of 

calculated baseline cooling and heating energy for CAC and CHP products used in residences 

taking into account the RECS household samples weights. 

0%

5%

10%

15%

20%

25%

Percentage of Households 

Baseline CAC Cooling Energy (kWh/yr) 

Figure 7.5.1. Baseline National Cooling Energy Distribution for CAC – Residential 

0%

2%

4%

6%

8%

10%

12%

14%

Percentage of Households 

Baseline CHP Cooling Energy (kWh/yr) 

Figure 7.5.2. Baseline National Cooling Energy Distribution for CHP – Residential 

7-19 
 

 

 

0%

5%

10%

15%

20%

25%

Percentage of Households 

Baseline CHP Heating Energy (kWh/yr) 

Figure 7.5.3. Baseline National Heating Energy Distribution for CHP – Residential 

7.6 BASELINE COMMERCIAL CAC AND CHP ENERGY USE 

Seven percent of residential-type (i.e., single-phase) CAC and CHP applications are 

assumed to be in commercial buildings. While potentially the variety of buildings to which this 

equipment could be utilized is wide, DOE believes that the vast majority of the shipments are 

utilized in small buildings, primarily small retail and commercial buildings. This is primarily 

because CAC and CHP equipment use single-phase electricity which limits the application to 

smaller buildings. 

Cooling and heating energy use in commercial buildings can be distinctly different from 

residential buildings even for the same equipment. This is predominantly due to commercial 

buildings being operated differently, often having defined operating hours when the equipment is 

used to condition the space, thermostatic setback during other hours, induced ventilation into the 

building structure to meet occupant needs, and typically continuous fan operation during 

occupied hours. Space heat gains in commercial buildings can be significantly different than in 

residential buildings due primarily to high internal thermal loads from lighting and electrical 

equipment during the occupied periods. 

In addition multiple cooling and heating units are commonly used. A similar data source 

to the RECS data discussed earlier is the EIA Commercial Building Energy Consumption Survey 

(CBECS)8

 which provides estimates of end-use energy consumption in commercial buildings. 

Because multiple pieces of cooling and heating equipment are the norm in most commercial 

buildings, and the number of units by equipment type is not captured in the survey, it is not 

possible to readily determine the energy use of individual pieces of CAC and CHP equipment 

using CBECS. In addition, CBECS does not clearly distinguish equipment types by electrical 

phase. Hence, identification of buildings that are predominantly served by CAC and CHP 

equipment is difficult. Given these difficulties, it was determined that CBECS could not be used 

to estimate the cooling and heating energy data for CAC and CHP equipment used in 

7-20 
 

 

 

 

commercial buildings. Instead, DOE relied on a building simulation approach to estimate the 

electrical energy usage of CAC and CHP equipment in commercial buildings. 

7.7 OVERVIEW OF COMMERCIAL ENERGY SIMULATION APPROACH 

In order to develop energy use statistics that reflect the use of CAC and CHP equipment 

in commercial buildings, DOE performed an analysis similar to that described in the Framework 

for Central Air Conditioners.9

 DOE used the EnergyPlus10 whole-building energy simulation 

software to estimate the energy consumption of CAC and CHP used to satisfy the cooling, 

supply fan, and in the case of CHP, the electrical heating energy required in a representative 

small office building. Simulations were carried out for 237 locations around the United States. 

The building model used was an existing single story, 5,500 ft2 office building model developed 

by the DOE for energy benchmarking purposes for this analysis. This benchmark building model 

is one of 16 commercial building benchmark models developed in support of the DOE Net Zero 

Energy Commercial Building Initiative.11,12 

Two variations were considered for the simulations: buildings were either entirely served 

by CAC equipment with gas furnace backup or were entirely served by CHP equipment. The 

simulated building utilized five individual CAC (or CHP units). For each equipment type, DOE 

simulated the equipment at four different efficiency levels starting from the baseline level. For 

CAC, these levels were: 13 SEER, 14 SEER, 16 SEER, and a max tech level of SEER 22 based 

on blower-coil ratings. For CHP these levels were: 13 SEER, 14 SEER, 16 SEER, and a max 

tech level of SEER 19.5 based on blower-coil ratings. Equipment parameters used in the 

simulation were adjusted to reflect engineering designs corresponding to each efficiency level. 

Simulations were carried out using Typical Metrological Weather Files (TMY2) for the 237 U.S. 

locations13. 

DOE extracted the annual energy consumption for cooling and fan energy use and 

heating from each modeled CAC or CHP unit as well as the equipment cooling capacity for each 

unit from each simulation run and aggregated these to the whole building level. Using this whole 

building cooling and heating data as well as the equipment capacities, DOE normalized the CAC 

and CHP energy consumption for each location and efficiency level to that of an average 3-ton 

CAC or CHP unit. These normalized energy use statistics were then used to represent the 

commercial energy use for a 3-ton CAC or CHP product for the LCC analysis. 

To estimate the energy consumption for intermediate efficiency levels between those 

simulated, DOE linearly interpolated the energy use estimates for cooling energy, fan energy and 

heating energy based on the results at the four simulated efficiency levels, the SEER or HSPF 

rating as the independent variable, and using the nearest lower and upper SEER or HSPF levels 

simulated. 

7.7.1 Simulation Tool Description 

DOE chose to use EnergyPlus version 3.0 for the energy analysis. EnergyPlus is the most 

recent of several large scale software programs developed for whole-building energy simulation 

analysis and has been validated by comparing its results with thermal and energy use 

measurements on actual buildings and with other software tools and calculations. EnergyPlus 

7-21 
 

 

 

predicts the hourly energy use of a building given hourly weather information and a description 

of the building, the operation of the building, and its heating, ventilation and air-conditioning 

(HVAC) equipment. Energy use statistics for the building can be readily extracted for different 

time steps and at detailed sub-component levels if necessary. EnergyPlus is an integrated 

software tool, where both the building loads and how those loads are served by equipment are 

solved iteratively and has a separate, but robust ground heat transfer model, which is particularly 

useful in the simulation of smaller buildings. DOE is currently using EnergyPlus as the basis for 

most of its building energy simulation research and the tool and its ongoing development are 

actively supported within DOE. 

7.7.2 Efficiency Levels Analyzed and Corresponding Simulation Parameters 

DOE simulated four efficiency levels for CAC equipment and four efficiency levels for 

CHP equipment, corresponding to particular efficiency levels identified in the engineering 

analysis. In order to simulate the equipment within the confines of the simulation software, the 

SEER and HSPF rating from the engineering analysis must be converted to parameters used by 

the simulation software. These parameters are the cooling COP, and for CHP the heating COP, 

of the condensing unit at rated conditions, and the fan power. The CAC and CHP condensing 

unit parameters are in turn calculated from 95 °F EER (EER) and 47 °F COP (COP47 °F) ratings 

for the equipment and the fan power at rated conditions. DOE first estimated these from the 

SEER and HSPF rating. 

The EER rating reflects the cooling performance for CAC equipment at a single-point 

rating condition defined by 95 °F outdoor temperature, 80 °F entering air dry bulb temperature 

and a 67 °F entering air wet bulb temperature. The COP47 °F rating reflects the heating 

performance of the heat pump at a single point rating condition defined by 47 °F outdoor 

temperature, 70 °F entering air dry bulb temperature and a maximum 60 °F entering air wet bulb 

temperature. The EER and COP47 °F ratings for equipment at different SEER levels were 

estimated using best fit curves for residential air conditioning equipment and heat pump 

equipment established by Wassmer and Brandemuehl.14 These curve fits are expressed in 

equation 7.7.1 and 7.7.2. 

EER = −0.0182 × SEER2 +1.1088× SEER Eq. 7.7.1 

COP47 F = −0.0255× HSPF 2 + 0.6239 × HSPF Eq. 7.7.2 

For 13 SEER equipment, the fan power at rating conditions was established assuming a 

blower motor efficiency of 0.65, a fan efficiency of 0.58, and a constant total static pressure of 

1.105 in H2O for the furnace/air handler. The same characteristics for fan power were also 

assumed to apply to the heat pumps at rating condition. The blower motor efficiency was 

assumed to be 0.65 for the 13 and 14 SEER ratings, consistent with that of a permanent split 

capacitor (PSC) blower motor. The blower motor efficiency was assumed to be 0.80 for the 

16 SEER and higher SEER ratings consistent with that of an electronically commutated motor 

(ECM) blower motor in this size range. A transition to ECM blower motors between the 14 and 

16 SEER ratings reflects the use of that technology in the CAC/CHP market from the 

engineering analysis where ECM motors appear to be commonplace at 16 SEER, but not 

common at 14 SEER. These assumptions result in a blower power under rating conditions of 

7-22 
 

 

 

 

 

 

 

 

 

138 W/ton for 13 and 14 SEER equipment, and a lower fan power of 112 W/ton for higher SEER 

equipment at rated conditions. For comparison, using the test procedure default 365 W/1,000 

CFM default for a coil-only rating would provide the same power levels assumed for 13 and 

14 SEER equipment at an airflow rate of 377 CFM/ton. 

The cooling and heating condensing unit COP values that are entered in the EnergyPlus 

software reflect the EER and COP47 °F ratings but are adjusted for the impact of the blower 

power. The blower power is directly incorporated into the total system power for these ratings, 

but because of the effect of fan heat, the incorporating the blower reduces the cooling output and 

raises the heating output. Equations 7.73 and 7.74 provide cooling and heating COP ratings for 

the condensing unit alone after adjusting for the fan power and fan heat. 

(EER / 3.413 + R) COPCUCool ,95°F = Eq. 7.7.3 1− R 

⎛COP 47°F − R ⎞ COPCUHeat,47°F = ⎜ ⎟ Eq. 7.7.4 ⎝ 1− R ⎠

Where: 

R = ratio of supply fan power to total equipment power at the AHRI rating 

condition, 

COPCUCool,95 °F = condensing unit cooling COP, and 

COPCUHeat,47 °F = condensing unit heating COP. 

Table 7.7.1 shows the resulting equipment performance statistics for the commercial 

building models. 

Table 7.7.1. CAC and CHP Blower and Characteristics Used in Modeling Commercial 

Cooling and Heating Energy Use 

Equipment 

Class 

SEER HSPF EER 47 °F 

COP 

Blower 

Motor 

Energy 

Efficiency 

Blower 

Power 

(w/ton)* 

Fan Power to 

Total Power 

(Rated 

Conditions) 

Cool 

COP95°F 

(Condensin 

g Unit Only) 

Heating 

COP47°F 

(Condensing 

Unit Only) 

CAC 13 NA 11.339 NA 0.65 138 0.13 3.966 NA 

14 NA 11.956 NA 0.65 138 0.135 4.208 NA 

16 NA 13.802 NA 0.80 112 0.123 4.511 NA 

22 NA 15.585 NA 0.80 112 0.14 5.471 NA 

CHP 13 7.7 11.339 3.292 0.65 138 0.13 3.966 3.626 

14 8 11.956 3.359 0.65 138 0.135 4.208 3.703 

16 8.6 13.802 3.480 0.80 112 0.123 4.511 3.842 

22 10.3 15.585 3.721 0.80 112 0.14 5.471 4.118 

* Calculated for rating conditions. 

7.7.3 Small Office Building Characteristics 

The small office building prototype model is a theoretical building modeled with 

characteristics typical of buildings of this size and use. The building is a 5,500 ft2

 single-story 

7-23 
building. The building is rectangular shaped, 52 ft by 105 ft with an aspect ratio of 1.5. The 

building has a window-area-fraction of 21 percent with a 10 ft floor-to-ceiling height. The small 

office building is assumed to have slab-on-grade construction for the floor and an attic. A picture 

of the building structure is shown in Figure 7.7.1. The building is divided into five HVAC zones, 

four perimeter zones and a core zone as illustrated in Figure 7.7.2, with a single CAC or CHP 

unit assumed for each HVAC zone. The perimeter zone depth in the center of each zone is 16 ft. 

Figure 7.7.1. Small Office Building Design View 

Figure 7.7.2. Small Office Building HVAC Zoning 

The building model presumes wood frame construction and punch-out type windows. 

Where applicable the building components for this model were assumed to “just meet” the 

minimum prescriptive requirements of the ASHRAE 90.1-2004 standard. Components not 

regulated by Standard 90.1 are assumed to be designed as is considered standard practice for a 

small office building. Standard practice is determined from various sources including a review of 

the Commercial Buildings Energy Consumption Survey (CBECS 2003) and the input of various 

design and construction industry professionals including members of the ASHRAE 90.1 

Standing Standard Project Committee. The following sections provide a review of the baseline 

building and how the baseline building is simulated in EnergyPlus, including characteristics of 

the building envelope, building internal loads (people, lighting, miscellaneous equipment, and 

infiltration), HVAC equipment, and service water heating. 

7.7.4 Building Operating Characteristics 

The building is assumed to follow typical small office occupancy patterns with peak 

occupancy occurring from 8 AM to 5 PM weekdays with limited occupancy beginning at 6 AM 

and extending until midnight for janitorial functions. The building is assumed to be unoccupied 

Saturday, Sunday and holidays. Schedules for lighting and miscellaneous equipment were 

matched to occupancy schedules with lower usage during unoccupied times. HVAC system 

7-24 
 

schedules were matched to the occupancy schedules, and allow for earlier startup times to bring 

the space to the desired temperature at the beginning of normal occupancy. Figure 7.7.3, Figure 

7.7.4, Figure 7.7.5, and Figure 7.7.5 show the EnergyPlus schedules for lighting, plug loads, 

occupancy, and thermostat set point. Detailed schedules are shown in appendix 7-A for these as 

well as for HVAC fans, infiltration, and service hot water. These schedules represent multipliers 

to defined daily “peak” conditions. In the case of ventilation, it is assumed that ventilation occurs 

whenever the fan system is operational. In the case of infiltration, a maximum infiltration rate for 

each hour is calculated hourly using wind speed and multiplied by the value shown in the hourly 

infiltration schedule. That value is 1.0 for hours when the ventilation is off and the building is 

assumed to be unpressurized. The schedule multiplier is assumed to be 0.25 during hours when 

the fan system is on and the building is pressurized. 

The HVAC systems are scheduled to be on from 6 a.m. to 7 p.m. weekdays 

(13 hours/day) and our schedule off weekends and holidays. Building thermostats are set to 

70 °F degree heating, 75 °F degree cooling during the occupied period. Thermostats are setback 

to 60 °F heating, 85 °F cooling during the unoccupied period. Between 6 a.m and 7 a.m weekday 

mornings the thermostats are set to 65 °F and 80 °F cooling heating set points to provide a onehour thermostat ramp between the setback and occupied set points to prevent equipment sizing 

and temperature balance problems. 

For the occupancy, lighting, plug use, ventilation, the schedules shown in Appendix 7-B 

are multipliers to defined peak densities. Lighting density was defined using the ASHRAE 90.1­

2004 maximum LPD requirement of 1.0 w/ft2

. Plug load density (e.g., computers and other 

miscellaneous loads) was 0.63 w/ft2

. Occupancy peak density was defined as 31 persons for the 

building (5.6 persons per thousand square foot). Ventilation was based on ASHRAE Standard 

62-1999 and set to 0.1 cfm/ft2 (cubic feet per minute per square ft) of floor area for each 

conditioned zone. The peak infiltration for the building was based on hourly wind speed as 

discussed previously and averages to 0.2016 cfm/ft2

 of total exterior conditioned zone wall area 

at a wind velocity of 10 miles per hour. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Percent of Peak Power Density

Weekday

Sat/Sun/Hol

Figure 7.7.3. Small Office Lighting Schedule 

7-25 
 

 

Figure 7.7.4. Small Office Plug Load Schedule 

Figure 7.7.5. Small Office Occupancy Schedule 

7-26 
 

 

0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Thermostat Setpoint(°F)

Heat‐Weekday

Heat‐Sat/Sun/Hol

Cool‐Weekday

Cool‐Sat/Sun/Hol

Figure 7.7.6. Small Office Thermostat Set Point Schedule 

7.7.5 Building Mechanical Systems and Equipment 

As discussed, the building used either five CAC units or five CHP units, one for each 

conditioned zone depending on which equipment class was analyzed. Equipment performance 

characteristics were developed using performance curves based on existing equipment. 

Performance curves and model inputs are documented in appendix 7-A. 

Blower energy for the building model used the characteristics for blower motor and fan 

power efficiency discussed in section 7.7.2. However, the total fan static pressure was 1.45 in 

H20 based on the assumption used in the benchmark prototype, compared to 1.105 in H20 total 

static pressure used to characterize the equipment performance at rating conditions. 

Cooling equipment was sized based on ASHRAE 2.5 percent cooling design day sizing 

for all climates. A sizing run is done prior to the hourly simulations in EnergyPlus and is used to 

size all HVAC equipment. The design-day sizes are then used in the annual simulation runs. For 

the heat pumps, equipment sizing is based on cooling design-day and electric resistance heat is 

used to make up any remaining heating load. 

7.8 BASELINE COMMERCIAL ENERGY DISTRIBUTION 

To be of use in the CAC analysis, the baseline commercial CAC and CHP use developed 

for the 237 TMY locations must have relative weighting factors associated with each TMY 

location much as the residential analysis uses the representative RECS weights. DOE used 

population-based weighting factors developed for each TMY climate based on data from the 

2000 U.S. Census data to represent the importance of each climate in each state. The 

development and documentation of these weighting factors is found in Appendix 7-B. Because 

certain TMY locations represent climates that cover more than one state (e.g., for instance where 

the TMY location is on the border between two states), DOE originally developed weighting 

factors for a total of 543 TMY-State combinations. These weighting factors were then used in the 

7-27 
subsequent LCC analysis in addressing CAC and CHP energy use in commercial buildings. 

Seventeen Alaskan locations, which make up approximately 0.2 percent of the national weight, 

were however removed from the energy analysis due to issues with electrical price data. Figure 

7.8.1, Figure 7.8.2, and Figure 7.8.3 shows a distribution of commercial CAC cooling and CHP 

cooling and heating energy use in the nation which accounts for the relative weights attached to 

each of the remaining 526 TMY-State combinations. 

0%

10%

20%

30%

40%

50%

60%

70%

Percentage of Simulated 

Commercial Small Offices 

Baseline CAC Cooling Energy (kWh/yr) 

Figure 7.8.1. Baseline National Cooling Energy Distribution for CAC-Commercial, 

Weighted 

0%

10%

20%

30%

40%

50%

60%

70%

Percentage of Simulated 

Commercial Small Offices 

Baseline CHP Cooling Energy (kWh/yr) 

Figure 7.8.2. Baseline National Cooling Energy Distribution for CHP-Commercial, 

Weighted 

7-28 
 

 

 

0%

10%

20%

30%

40%

50%

60%

Percentage of Simulated 

Commercial Small Offices 

Baseline CHP Cooling Energy (kWh/yr) 

Figure 7.8.3. Baseline National Heating Energy Distribution for CHP-Commercial, 

Weighted 

7.9	 COMMERCIAL ENERGY FOR INTERMEDIATE EFFICIENCY LEVELS 

Calculation of commercial annual cooling, and fan energy for intermediate efficiency 

levels not simulated was by linear interpolation between SEER levels simulated. Calculation of 

commercial heating energy use for heat pumps for intermediate levels not simulation was by 

interpolation between HSPF levels simulated. 

7.10	 MARKET BASELINE SPACE-COOLING AND SPACE-HEATING 

EFFICIENCIES 

The analysis results presented in this chapter up to this point presents the development of 

the baseline space-cooling and space-heating energy use for CAC and CHP equipment. Baseline 

in this discussion refers to the energy consumption if all equipment was brought to the current 

standard levels of SEER 13 and HSPF 7.7 for packaged and split system CAC and CHP product 

classes. Not all equipment is sold at the baseline efficiency levels. Much equipment exceeds the 

baseline level in the current market and is expected to continue to do so in the absence of new 

standards. In order to account for this within the LCC analysis discussed in the next chapter, 

DOE defined a base case efficiency distribution for 2016, also referred to as the market baseline. 

The market baseline efficiency distribution was defined to represent the range of efficiencies 

likely sold into the market in 2016 in the absence of new standards. The market baseline energy 

consumption is calculated as the energy estimated to be consumed by each individual entity (as 

characterized by RECS household observation or commercial building TMY-State combination) 

DOE estimated this energy use in the same manner as was used in estimating the baseline 

energy consumption. For RECS household records, DOE first randomly selected a 2016 

efficiency level from the market baseline distribution and then equations 7.3.1 and 7.4.1 were 

utilized to calculate the cooling and heating consumption for the RECS observations in the 2016 

base case, by replacing the baseline efficiency (cooling or heating) with the selected efficiency 

for each observation in the base case. For commercial TMY-State observations, DOE first 

7-29 
 

randomly selected a 2016 efficiency level from the market baseline distributions and calculated 

the correspond cooling fan, and heating energy use for that observation in 2016 by linear 

interpolation between the efficiency levels simulated in the commercial energy analysis. 

DOE did not have access to sales data describing the actual distribution of efficiencies in 

current sales, nor was such information provided by industry for this rulemaking. As a 

consequence, DOE developed estimates of the distribution of SEER levels for four classes of 

product: split system CAC, single package CAC, split system CHP, and single package CHP. 

The development of these distributions was based on the following key data inputs: 

From AHRI data, the average SEER of equipment sold in each product class in 2006 as 

well as the relative shipments by product class for the market as a whole. 

An industry trade press article which indicated approximate sales segmentation by SEER 

for the CAC/CHP industry in 2007.15 

AHRI Directory of Certified Product Performance16 which allowed review of specific 

efficiencies sold into the market for each product class. 

According to the trade press article, the distribution in 2007 had approximately 9 percent 

of sales at 14 SEER, 3 percent of sales at 15 SEER, 2 percent at 16 SEER, and 2 percent for 

17 SEER. The remainder of the product sales was assumed to fall below 14 SEER. 

According to AHRI data7, product sales in 2007 were as follows: 63.0 percent split CAC, 

5.9 percent single-package CAC, 27.6 percent split CHP, and 3.5 percent single-package CHP. 

Product sales in 2008 through September were as follows: 63.0 percent split CAC, 4.8 percent 

single-package CAC, 28.8 percent split CHP, and 3.4 percent single-package CHP. 

AHRI reported average shipped SEER by product class for 2007: split CAC, 13.72; 

single-package CAC, 12.83; split CHP 13.86, single-package CHP 13.16. DOE did not know if 

the average 12.83 for single-package CAC represented continued sales of pre-SEER 13 

equipment or if it included through the wall or other classes with lower efficiency. As this data 

were provided by AHRI for this rulemaking, it was assumed to be representative of single phase 

equipment only. AHRI reported average shipped SEER for 2008 as: split CAC, 13.77; singlepackage CAC, 13.17; split CHP 13.97, single-package CHP 13.39. 

DOE first created 16 SEER bins corresponding roughly to the SEER efficiency levels 

developed in the engineering analysis with those engineering levels serving as a representative 

efficiency for each bin. These bins are shown in Table 7.10.1. Then through an iterative process 

which took into account available efficiency levels in each product class, DOE developed an 

efficiency distribution for each product class which was consistent with the above data sources in 

that it provided average efficiency by split CAC, split CHP, and single-package CHP product 

class as reported by AHRI in 2007 as well as provided an overall distribution by SEER that 

corresponded with the industry trade press article cited above. Bins that included 14 and 15 

SEER were assumed to be uniformly distributed efficiencies above and below the characteristic 

efficiency in the bin. It was obviously not possible to develop a shipment-weighted efficiency 

below 13 SEER as was seen for single package CAC using this distribution. Instead DOE chose 

7-30 
 

 

 

 

to match the 2008 shipment weighted average value for this product class. The estimated 

distribution for all classes for 2007 is shown in Table 7.10.1. 

Table 7.10.1. CAC and CHP Efficiency Distributions Estimated for 2007 

SEER Bins SEER Distribution by Equipment Class Industry- Wide 

SEER 

Distribution 

(Four Classes) 

% 

Bottom of Bin Top of Bin Characteristic 

Efficiency in Bin Split 

CAC 

Single 

Package 

CAC 

% 

Split 

CHP% 

Single 

Package 

CHP 

% 

13 13.25 13 25.00 76.20 15.00 76.20 27.07 

13.25 13.75 13.5 56.00 18.80 57.00 18.80 52.77 

13.75 14.25 14 6.00 2.00 8.00 2.00 6.18 

14.25 14.75 14.5 2.50 2.00 7.50 2.00 3.83 

14.75 15.25 15 3.00 1.00 5.00 1.00 3.36 

15.25 15.75 15.5 2.00 0.00 2.00 0.00 1.81 

15.75 16.5 16 3.10 0.00 2.00 0.00 2.50 

16.5 17.5 17 1.00 0.00 1.50 0.00 1.04 

17.5 18.5 18 0.60 0.00 1.50 0.00 0.79 

18.5 19.5 19 0.30 0.00 0.50 0.00 0.33 

19.5 20.5 20 0.20 0.13 

20.5 21.5 21 0.20 0.13 

21.5 22.5 22 0.10 0.06 

22.5 23.5 23 

23.5 24.5 24 

24.5 25.5 25 

Wt. Average SEER 13.71 13.16 13.85 13.16 13.70 

13.66 13.78 

DOE was not able to develop a distribution using the same methodology for the 2008 

data that would be consistent with the industry trade press article overall distribution. DOE made 

slight changes to the relative shipment weights by efficiency bin from 2007 distribution, in order 

to match the higher average SEERs in 2008 while maintaining the general flavor of the 

distribution by product class. This overall 2008 distribution is shown in Table 7.10.2. DOE 

assumed that this distribution was representative of the market baseline distribution in 2016 and 

used it as such for the energy and subsequent LCC analysis. 

DOE did not have similar data on space heating efficiencies for CHP equipment. For 

analysis of the market baseline HSPF efficiencies, DOE used the HSPF values that corresponded 

to each CHP SEER level as identified in the engineering analysis. Because these engineering 

levels represented typical market averages based on the AHRI data, they were deemed sufficient 

for characterizing average market HSPF by SEER level and corresponding average CHP heating 

energy use in the market baseline. 

7-31 
 

 

 

 

 

 

 

 

 

 

Table 7.10.2. CAC and CHP Efficiency Distributions Estimated for Market Baseline 

SEER Bins SEER Distribution by Equipment Class IndustryWide SEER 

Distribution 

(Four Classes) 

% 

Bottom of 

Bin 

SEER 

Top of Bin 

SEER 

Characteristic 

Efficiency in Bin 

SEER 

Split 

CAC 

% * 

SinglePackage 

CAC 

% 

Split 

CHP 

% 

SinglePackage 

CHP 

% 

13 13.25 13 24.00 75.00 13.00 50.00 24.18 

13.25 13.75 13.5 55.00 20.00 52.00 32.00 51.66 

13.75 14.25 14 4.00 2.00 10.00 11.00 5.87 

14.25 14.75 14.5 5.25 2.00 9.00 5.00 6.17 

14.75 15.25 15 3.25 1.00 5.50 2.00 3.75 

15.25 15.75 15.5 2.00 0.00 3.50 0.00 2.27 

15.75 16.5 16 3.50 0.00 3.00 0.00 3.07 

16.5 17.5 17 1.50 0.00 2.00 0.00 1.52 

17.5 18.5 18 0.70 0.00 1.50 0.00 0.87 

18.5 19.5 19 0.30 0.00 0.50 0.00 0.33 

19.5 20.5 20 0.20 0.13 

20.5 21.5 21 0.20 0.13 

21.5 22.5 22 0.10 0.06 

22.5 23.5 23 

23.5 24.5 24 

24.5 25.5 25 

Wt. Average SEER 13.77 13.17 13.97 13.39 13.78 

13.72 13.91 *

 A separate, coil-only split air conditioner distribution was created by truncating the split AC distribution shown at 

SEER bin 8 (16.5-17.5 bin) since the max tech level for this type of equipment was 16.5. The distribution was then 

normalized back to 100%. This distribution is shown in chapter 8, Life Cycle Cost and Payback Period Analysis. 

7.11	 ESTABLISHMENT OF GEOGRAPHIC REGIONS FOR STANDARDS 

ANALYSIS AND CORRESPONDING REGIONAL ENERGY CONSUMPTION 

BY EFFICIENCY LEVEL 

Under EPCA, regional efficiency standards for CAC may be defined for up to two 

regions consisting of contiguous groups of states. These regional standards are in addition to a 

base national standard efficiency that represents the minimum efficiency that a manufacturer 

could produce or that could be imported into the United States. In order to consider establishing 

regional standards, DOE needed to identify regions for which such standards might be 

applicable. For cooling equipment performance, the most important regional variations in 

climate are the annual number of operating hours, and the coincident relative humidity during 

those hours. For the CAC standard analysis, DOE is considering establishing two regions, hothumid and hot-dry, for the establishment of regional standards in addition to a national standard. 

In addition, DOE considered using two variants of the SEER rating to establish performance 

standards: the current SEER definition and a modified definition termed “SEER hot-dry” 

(SEERHD). The SEERHD would be calculated using revised temperature bin data and design 

sizing data as established for the defined hot-dry region. 

A national standard and a standard for the proposed hot-humid region may be established 

using SEER, although potentially at different SEER efficiencies based on the cooling load and 

other information characteristic to the nation and to the hot-humid region respectively. The 

7-32 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

SEERHD rating would be developed to be more appropriate for hot and dry climates in certain 

western States where the average outdoor air temperature during cooling may be considerably 

higher than that seen in the remainder of the United States. Whether these regional standards are 

appropriate will be determined by the LCC and other analyses. For the purpose of DOE’s 

preliminary analysis, DOE established the two regions allowed under EPCA as shown in Table 

7.11.1. Region 1 refers to the hot-humid region. Region 2 refers to the hot-dry region. For the 

purpose of characterizing the geographic remainder of the nation, DOE uses a Region 0 

nomenclature. DOE notes that while analysis can be performed for Region 0, DOE does not have 

authority to set a regional standard for this geographic area. Rather, this area would be covered 

under the national standard. 

Table 7.11.1. Proposed Climate Regions for Regional Standards 

Hot-Humid 

(Region 1) 

Hot-Dry 

(Region 2) 

Rest-of-Country 

(Region 0) 

Alabama Arizona Alaska Nebraska 

Arkansas California Colorado New Hampshire 

Florida Nevada Connecticut New Jersey 

Georgia New Mexico Delaware New York 

Hawaii District of Columbia North Dakota 

Louisiana Idaho Ohio 

Mississippi Illinois Oregon 

North Carolina Indiana Pennsylvania 

Oklahoma Iowa Rhode Island 

South Carolina Kansas South Dakota 

Tennessee Kentucky Utah 

Texas Maine Vermont 

Maryland Virginia 

Massachusetts Washington 

Michigan West Virginia 

Minnesota Wisconsin 

Missouri Wyoming 

Montana 

For the purposes of the preliminary analysis for the CAC rulemaking, DOE did not 

develop energy consumption characteristics in conformance with the SEERHD rating as this 

rating was not used in the engineering analysis and no mapping between SEER and SEERHD had 

been developed. However, DOE did develop the energy and subsequent LCC analysis at both the 

national level and individually for the regions defined in Table 7.11.1. A complete discussion on 

the development of both the standard regions and the SEERHD parameter are discussed in 

Appendix 7-C. 

For each equipment class, DOE developed energy use statistics for the market baseline 

and for higher efficiency levels by using a Monte Carlo random selection process to select 

10,000 observations in each region and 10,000 for the nation as a whole. Ninety three percent of 

those observations were residential and 7 percent were commercial instances of the use of CAC 

(or CHP) equipment. Details for the selection process are found in chapter 8, LCC. However 

7-33 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 7.11.6 show the resultant baseline, market baseline, and higher efficiency annual energy 

statistics developed for each region for each equipment class analyzed. 

Table 7.11.2. Split-System Air Conditioners: Average Annual Energy Use by Efficiency 

Level for Coil-Only Systems 

Efficiency Level Annual Energy Consumption 

kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF* Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 N/A 2,407 0 3,564 0 2,176 0 1,378 0 

Market 

Baseline 

Market 

Baseline 

N/A 2,291 0 3,393 0 2,071 0 1,310 0 

2 13.5 N/A 2,322 0 3,437 0 2,100 0 1,331 0 

3 14.0 N/A 2,243 0 3,318 0 2,029 0 1,287 0 

4 14.5 N/A 2,168 0 3,205 0 1,960 0 1,244 0 

5 15.0 N/A 2,097 0 3,100 0 1,897 0 1,204 0 

6 15.5 N/A 2,031 0 3,002 0 1,836 0 1,166 0 

7 16.0 N/A 1,968 0 2,909 0 1,780 0 1,130 0 

8 16.5 N/A 1,912 0 2,825 0 1,730 0 1,099 0 

* N/A means not applicable. 

Table 7.11.3. Split-System Air Conditioners: Average Annual Energy Use by Efficiency 

Level—Blower-Coil Systems 

Efficiency Level Annual Energy Consumption 

kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF* Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 N/A 2,433 0 3,584 0 2,172 0 1,365 0 

Market 

Baseline 

Market 

Baseline 

N/A 2,315 0 3,410 0 2,067 0 1,302 0 

2 13.5 N/A 2,347 0 3,455 0 2,096 0 1,319 0 

3 14.0 N/A 2,267 0 3,336 0 2,025 0 1,275 0 

4 14.5 N/A 2,190 0 3,223 0 1,957 0 1,233 0 

5 15.0 N/A 2,119 0 3,117 0 1,893 0 1,193 0 

6 15.5 N/A 2,052 0 3,018 0 1,833 0 1,155 0 

7 16.0 N/A 1,988 0 2,925 0 1,777 0 1,120 0 

8 16.5 N/A 1,932 0 2,840 0 1,727 0 1,089 0 

9 17.0 N/A 1,878 0 2,760 0 1,679 0 1,060 0 

10 18.0 N/A 1,780 0 2,613 0 1,592 0 1,007 0 

11 19.0 N/A 1,692 0 2,482 0 1,514 0 960 0 

12 20.0 N/A 1,613 0 2,363 0 1,444 0 917 0 

13 21.0 N/A 1,541 0 2,256 0 1,380 0 878 0 

14 22.0 N/A 1,476 0 2,158 0 1,322 0 842 0 

* N/A means not applicable. 

7-34 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 7.11.4. Split-System Heat Pumps: Average Annual Energy Use by Efficiency Level 

Efficiency Level Annual Energy Consumption 

kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 7.70 3,487 1,749 4,275 1,275 4,203 924 1,978 2,968 

Market 

Baseline 

Market 

Baseline 

Market 

Baseline 

3,268 1,687 4,006 1,230 3,937 891 1,857 2,862 

2 13.5 7.85 3,363 1,716 4,122 1,251 4,053 906 1,909 2,912 

3 14.0 8.00 3,248 1,685 3,980 1,228 3,913 890 1,846 2,859 

4 14.5 8.15 3,138 1,654 3,845 1,206 3,780 873 1,784 2,808 

5 15.0 8.30 3,035 1,625 3,719 1,184 3,656 858 1,726 2,758 

6 15.5 8.45 2,939 1,597 3,601 1,163 3,539 843 1,671 2,711 

7 16.0 8.60 2,848 1,570 3,490 1,143 3,430 828 1,620 2,665 

8 17.0 9.10 2,688 1,485 3,293 1,081 3,235 783 1,531 2,522 

9 18.0 9.60 2,545 1,409 3,117 1,026 3,062 743 1,452 2,395 

10 19.0 10.10 2,417 1,341 2,959 976 2,907 706 1,381 2,279 

11 19.5 10.30 2358 1315 2886 957 2835 693 1,348 2,236 

Table 7.11.5. Single-Package Air Conditioners: Average Annual Energy Use by Efficiency 

Level 

Efficiency Level Annual Energy Consumption 

kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF* Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 N/A 2,376 0 3,602 0 2,170 0 1,363 0 

Market 

Baseline 

Market 

Baseline 

N/A 2,348 0 3,559 0 2,144 0 1,348 0 

2 13.5 N/A 2,292 0 3,473 0 2,093 0 1,316 0 

3 14.0 N/A 2,214 0 3,353 0 2,022 0 1,273 0 

4 14.5 N/A 2,139 0 3,239 0 1,954 0 1,230 0 

5 15.0 N/A 2,070 0 3,133 0 1,890 0 1,191 0 

6 15.5 N/A 2,004 0 3,033 0 1,831 0 1,153 0 

7 16.0 N/A 1,942 0 2,940 0 1,774 0 1,118 0 

8 16.6 N/A 1,876 0 2,838 0 1,714 0 1,081 0 

* N/A means not applicable. 

7-35 
 

 

 

 

 

 

 

 

 

 

 

Table 7.11.6. Single-Package Heat Pumps: Average Annual Energy Use by Efficiency Level 

Efficiency Level Annual Energy Consumption

 kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 7.70 3,464 1,720 4,295 1,272 4,211 927 1,964 2,953 

Market 

Baseline 

Market 

Baseline 

Market 

Baseline 

3,372 1,698 4,179 1,256 4,098 915 1,914 2,916 

2 13.5 7.85 3,341 1,688 4,141 1,248 4,060 910 1,896 2,898 

3 14.0 8.00 3,227 1,657 3,999 1,225 3,920 893 1,833 2,845 

4 14.5 8.00 3,117 1,657 3,863 1,225 3,787 893 1,772 2,845 

5 15.0 8.00 3,015 1,657 3,737 1,225 3,663 893 1,714 2,845 

6 15.5 8.50 2,920 1,561 3,618 1,154 3,546 841 1,660 2,682 

7 16.0 9.00 2,829 1,476 3,506 1,091 3,436 795 1,609 2,538 

8 16.4 9.00 2,763 1,476 3,424 1,091 3,356 795 1,572 2,537 

7-36 
 

 

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1. Residential Energy Consumption Survey: Quality Profile, DOE Publication No. DOE/EIA0555(96)/1 

2. NOAA, 2009. NNDC Climate Data Online. 

<www7.ncdc.noaa.gov/CDO/CDODivisionalSelect.jsp> (Assessed February, 2009) 

3. Missouri Census Data Center. U.S. Census Data Archive for 1980, 1990, 2000 U.S. Census 

Data http://mcdc2.missouri.edu/applications/uexplore.shtml#top and (Accessed February 

2009) 

4. AHRI 2008, Air Conditioning and Refrigeration Institute Statistical Profile, 2008. 

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product classes. 

5. DOE, 2001. Central Air Conditioner Rulemaking SNOPR Technical Support Document, 

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V. 2.0. Arlington, Va. 

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of Energy Energy Information Administration. 

<http://www.eia.doe.gov/emeu/cbecs/cbecs2003> (Accessed May, 2009). 

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10. DOE, 2008. EnergyPlus Energy Simulation Software V3.0. U.S. Department of Energy. 

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11. DOE, 2008. DOE to Pursue Zero-Net Energy Commercial Buildings, Available at 

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http://www1.eere.energy.gov/buildings/commercial_initiative/benchmark_models.html 

13. NREL, 1995. Typical Meteorological Years Derived from the 1961-1990 National Solar 

Radiation Database. National Renewable Energy Laboratory. Golden, CO. 

7-37 
 

14. Wassmer M and MJ Brandemuehl. 2006. Effect of Data Availability on Modeling of 

Residential Air Conditioners and Heat Pumps for Energy Calculations. ASHRAE 

Transactions 111(1), pp. 214-225. 

15. ACH&R News, 2007. “Higher SEERs Got Popular”, December 2007. Accessed March 

2009 at http://www.achrnews.com/Articles/Web_Exclusive/BNP_GUID_9-5­

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16. AHRI, 2009. Directory of Certified Product Performance. Available at 

<http://www.ahridirectory.org/ahridirectory/pages/home.aspx>. Accessed March, 2009. 

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