7-i

CHAPTER 7. ENERGY USE CHARACTERIZATION

TABLE OF CONTENTS

7.1 INTRODUCTION ........................................................................................................... 7-1

7.2 CENTRAL AIR CONDITIONER AND CENTRAL HEAT PUMP .............................. 7-1

7.2.1 Introduction...................................................................................................................... 7-1

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

7.2.1.2 General Approach to the Energy Use Analysis – Commercial...................... 7-4

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

7.2.2 Analyzed RECS Households........................................................................................... 7-5

7.2.3 Baseline Annual Space-Cooling Energy Use – Residential ............................................ 7-6

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

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

7.2.3.3 Stock Space-Cooling Efficiency (SEER)..................................................... 7-10

7.2.3.4 Estimating Baseline Annual Space-Cooling Energy Use ............................ 7-13

7.2.4 Baseline Annual Space-Heating Energy Use for Central Heat Pump Equipment—

Residential...................................................................................................................... 7-14

7.2.4.1 Estimating Stock Annual Space-Heating Energy Use ................................. 7-15

7.2.4.2 Stock Space-Heating Efficiency (HSPF)..................................................... 7-17

7.2.4.3 Estimating Baseline Annual Space-Heating Energy Use ............................ 7-19

7.2.5 Baseline Residential Cooling and Heating Results − Adjusted for RECS Sample 

Weights.......................................................................................................................... 7-20

7.2.6 Baseline Commercial Central Air Conditioner and Central Heat Pump Energy Use.... 7-21

7.2.7 Overview of Commercial Energy Simulation Approach............................................... 7-22

7.2.7.1 Simulation Tool Description........................................................................ 7-23

7.2.7.2 Efficiency Levels Analyzed and Corresponding Simulation Parameters.... 7-23

7.2.7.3 Small Office Building Characteristics......................................................... 7-25

7.2.7.4 Building Operating Characteristics.............................................................. 7-26

7.2.7.5 Building Mechanical Systems and Equipment ............................................ 7-29

7.2.8 Baseline Commercial Energy Distribution .................................................................... 7-30

7.2.9 Commercial Energy for Intermediate Efficiency Levels............................................... 7-31

7.2.10 Market Baseline Space-Cooling and Space-Heating Efficiencies................................. 7-32

7.2.11 Determining Installed Equipment Capacity for RECS Observations............................ 7-32

7.2.12 Regional Energy Consumption by Efficiency Level ..................................................... 7-35

7.2.13 Off Mode Energy Consumption..................................................................................... 7-40

7.3 FURNACES................................................................................................................... 7-43

7.3.1 Introduction.................................................................................................................... 7-43

7.3.2 Household Sample ......................................................................................................... 7-43

7.3.3 Annual Heating Load Calculation ................................................................................. 7-45

7.3.3.1 Overview of Heating Load Estimates.......................................................... 7-47

7.3.4 Annual Energy Consumption......................................................................................... 7-47

7.3.4.1 Fuel Consumption........................................................................................ 7-47

7.3.4.2 Electricity Consumption .............................................................................. 7-48

7.3.5 Assigning Furnace Equipment Characteristics to Sampled Households....................... 7-50

7.3.5.1 Input Capacity of Existing and New Equipment ......................................... 7-51
7-ii

7.3.5.2 Airflow Size of Existing Equipment............................................................ 7-52

7.3.5.3 AFUE of Existing Equipment...................................................................... 7-54

7.3.6 Furnace Energy Consumption Results........................................................................... 7-57

7.3.7 Standby Energy Consumption Results for Furnaces ..................................................... 7-58

LIST OF TABLES

Table 7.2.1 The 30-Year Average CDD (1978–2007) and the 2005 CDD for the Nine 

Census Divisions and the Four Large States........................................................ 7-8

Table 7.2.2 Weather Adjusted Space-Cooling Energy Consumption Statistics at Regional 

Level (CAC-Stock).............................................................................................. 7-9

Table 7.2.3 Weather Adjusted Space-Cooling Energy Consumption Statistics at Regional 

Level (CHP-Stock)............................................................................................... 7-9

Table 7.2.4 Number of Observations for Each Age Group ....................................................... 7-11

Table 7.2.5 Average Annual Shipped Space-Cooling Efficiency.............................................. 7-13

Table 7.2.6 Baseline (13 SEER) Space-Cooling Energy Consumption Statistics at 

Regional Level (Central Air Conditioner)......................................................... 7-14

Table 7.2.7 Baseline (13 SEER) Space-Cooling Energy Consumption Statistics at 

Regional Level (Central Heat Pump)................................................................. 7-14

Table 7.2.8 30-Year Average HDD (1978–2007) and the 2005 HDD for the Nine Census 

Divisions and the Four Large States.................................................................. 7-16

Table 7.2.9 Statistics of Annual Weather-Adjusted Space-Heating Energy Consumption 

for RECS-Stock Central Heat Pump at Regional Level .................................... 7-16

Table 7.2.10 Average Annual Heating Pump HSPF ................................................................. 7-19

Table 7.2.11 Baseline (13 SEER) Space-Heating Energy Consumption Statistics at 

Regional Level (Central Heat Pumps)............................................................... 7-20

Table 7.2.12 Central Air Conditioner and Central Heat Pump Blower and Characteristics 

Used in Modeling Commercial Cooling and Heating Energy Use.................... 7-25

Table 7.2.13 Development of Market Weights for 2-, 3-, and 5-Ton Air Conditioners and 

Heat Pumps........................................................................................................ 7-34

Table 7.2.14 Fraction of Shipments by Product Class to Each Region ..................................... 7-36

Table 7.2.15 Split-System Air Conditioners: Average Annual Energy Use by Efficiency 

Level − Coil-Only Systems................................................................................ 7-37

Table 7.2.16 Split-System Air Conditioners: Average Annual Energy Use by Efficiency 

Level − Blower-Coil Systems............................................................................ 7-37

Table 7.2.17 Split-System Heat Pumps: Average Annual Energy Use by Efficiency Level .... 7-38

Table 7.2.18 Single-Package Air Conditioners: Average Annual Energy Use by 

Efficiency Level................................................................................................. 7-39

Table 7.2.19 Single-Package Heat Pumps: Average Annual Energy Use by Efficiency 

Level .................................................................................................................. 7-39

Table 7.2.20 Small Duct High Velocity Air Conditioners: Average Annual Energy Use 

by Efficiency Level............................................................................................ 7-40

Table 7.2.21 Split-System Blower Coil, Packaged, Space Constrained, and SDHV Air 

Conditioner Off Mode Energy Use.................................................................... 7-41

Table 7.2.22 Split-System Coil-Only Air Conditioner Off Mode Energy Use ......................... 7-42
7-iii

Table 7.2.23 Split-System, Packaged, and Space Constrained Heat Pump Off Mode 

Energy Use......................................................................................................... 7-42

Table 7.2.24 National Average Off Mode Energy Use ............................................................. 7-42

Table 7.3.1 Selection of RECS 2005 Records for Furnaces...................................................... 7-44

Table 7.3.2 Heating Degree Day Adjustment Factors............................................................... 7-46

Table 7.3.3 Range of Annual Heating Load for Each Furnace Product Class by Region ......... 7-47

Table 7.3.4 Values for Delay and Ignition Times...................................................................... 7-49

Table 7.3.5 Fraction of Non-Weatherized Gas Furnace Fan Motors and Controls 

Shipments by Furnace Efficiency and Construction Type in 2016 ................... 7-50

Table 7.3.6 Standby Power Consumption by Efficiency Level and Furnace Type................... 7-50

Table 7.3.7 Distribution of Input Capacity for Non-Weatherized Gas Furnaces ...................... 7-52

Table 7.3.8 Distribution of Airflow for Furnaces...................................................................... 7-53

Table 7.3.9 Common Furnace Input Capacity and Airflow combinations................................ 7-54

Table 7.3.10 Number of Observations for Each Age Group ..................................................... 7-54

Table 7.3.11 Historical Fraction of Regional Gas Furnace Shipments by AFUE Bins............. 7-55

Table 7.3.12 Historical Fraction of Manufactured Home Gas Furnace Shipments by 

AFUE Bins......................................................................................................... 7-56

Table 7.3.13 Historical Fraction of Oil-Fired Furnace Shipments by AFUE Bins.................... 7-56

Table 7.3.14 Annual Energy Consumption for Non-Weatherized Gas Furnaces...................... 7-57

Table 7.3.15 Annual Energy Consumption for Manufactured Home Gas Furnaces................. 7-58

Table 7.3.16 Annual Energy Consumption for Oil-Fired Furnaces........................................... 7-58

Table 7.3.17 Annual Standby Energy Consumption for Furnaces ............................................ 7-59

LIST OF FIGURES

Figure 7.2.1 Flow Diagram for the Determination of Annual Space-Cooling Energy for 

Residential Central Air Conditioners and Central Heat Pumps........................... 7-3

Figure 7.2.2 Flow Diagram for the Determination of Annual Space-Heating Energy for 

Residential Central Heat Pumps.......................................................................... 7-3

Figure 7.2.3 Flow Diagram for the Determination of Annual Space-Cooling and SpaceHeating Energy for Central Air Conditioners and Central Heat Pumps in 

Commercial Use................................................................................................... 7-4

Figure 7.2.4 National Distribution of Weather-Adjusted Space-Cooling Energy for CACRECS Observations ........................................................................................... 7-10

Figure 7.2.5 National Distribution of Weather-Adjusted Space-Cooling Energy for CHPRECS Observations ........................................................................................... 7-10

Figure 7.2.6 The Distribution of Central Air Conditioners in the RECS Sample by Age 

Groups................................................................................................................ 7-11

Figure 7.2.7 The Distribution of Central Heat Pumps in the RECS Sample by Age Groups.... 7-12

Figure 7.2.8 Distribution of RECS Households with Central Air Conditioners by Vintage ..... 7-12

Figure 7.2.9 National Distribution of Weather-Adjusted Space-Heating Energy for RECS 

Observations ...................................................................................................... 7-17

Figure 7.2.10 Distribution of Households with Heating-Performance Heat Pumps by Age 

Groups................................................................................................................ 7-18

Figure 7.2.11 Distribution of RECS Households with Central Heat Pumps by Vintage .......... 7-19
7-iv

Figure 7.2.12 Baseline National Cooling Energy Distribution for Central Air 

Conditioners – Residential................................................................................. 7-20

Figure 7.2.13 Baseline National Cooling Energy Distribution for Central Heat Pumps –

Residential.......................................................................................................... 7-21

Figure 7.2.14 Baseline National Heating Energy Distribution for Central Heat Pumps –

Residential.......................................................................................................... 7-21

Figure 7.2.15 Small Office Building Design View.................................................................... 7-26

Figure 7.2.16 Small Office Building HVAC Zoning................................................................. 7-26

Figure 7.2.17 Small Office Lighting Schedule .......................................................................... 7-27

Figure 7.2.18 Small Office Plug Load Schedule ....................................................................... 7-28

Figure 7.2.19 Small Office Occupancy Schedule...................................................................... 7-28

Figure 7.2.20 Small Office Thermostat Set Point Schedule ...................................................... 7-29

Figure 7.2.21 Baseline National Cooling Energy Distribution for Central Air 

Conditioners − Commercial, Weighted ............................................................. 7-30

Figure 7.2.22 Baseline National Cooling Energy Distribution for CHC − Commercial, 

Weighted............................................................................................................ 7-31

Figure 7.2.23 Baseline National Heating Energy Distribution for Central Heat Pumps −

Commercial, Weighted ...................................................................................... 7-31

Figure 7.2.24 Shipments of Residential Air Conditioners and Heat Pumps by Capacity for 

2009.................................................................................................................... 7-34
7-1

CHAPTER 7. ENERGY USE CHARACTERIZATION

7.1 INTRODUCTION

The life-cycle cost (LCC) and payback period (PBP) analyses described in chapter 8

require determination of the savings in operating cost consumers would realize from more 

energy efficient products. Energy costs are the most significant component of consumer 

operating costs. The U.S. Department of Energy (DOE or the Department) uses annual energy 

use, along with energy prices, to establish energy costs at various energy efficiency levels. This 

chapter describes the determination of annual energy use of central air conditioner (CAC) and 

central heat pump equipment (CHP) as well as residential non-weatherized gas furnaces, 

manufactured home furnaces, and oil-fired furnaces. In contrast to the DOE test procedure, 

which uses typical operating conditions in a laboratory setting, the energy use characterization

seeks to estimate the range of energy consumption of the products in the field.

7.2 CENTRAL AIR CONDITIONER AND CENTRAL HEAT PUMP

7.2.1 Introduction

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

consumption for central air conditioner and central heat pump 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 LCC and PBP analyses (chapter 8 of the technical support 

document [TSD]), which in turn provide the raw energy use data for the national impact analysis 

(chapter 10 of the TSD). Energy use in both the residential sector and the commercial sector is 

considered. In the energy use analysis, 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.

7.2.1.1 General Approach to the Energy Use Analysis – Residential

The general approach adopted in the energy use analysis for central air conditioner 

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)1 to provide estimates of cooling and heating energy for the sample households using 

central air conditioner and central heat pump 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 purchasing and using new equipment at the 

same rates as they would be in 2016 under a base-case standards scenario. 

A sample population of U.S. homes using central air conditioner and central heat pump 

equipment was first identified from the RECS households surveyed. This sample provided a 
7-2

dataset of cooling and heating energy use for 2005 for households with central air conditioners 

and central heat pumps. These data were then adjusted (weather-normalized) to reflect 

corresponding energy-use figures for typical long-term climate conditions. Historical efficiency 

data for shipped central air conditioner and central heat pump 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., seasonal energy efficiency ratio or 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 central 

air conditioner or central heat pump purchase in that year. The 2016 efficiency levels used for 

each household were randomly selected from a distribution of shipped efficiencies developed for 

each product class for the year 2016. This base case is also referred to as the market baseline 

case because the efficiency distribution is representative of the market for central air conditioner 

and central heat pump equipment in that year in the absence of new standards. 

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 

household in the base case by the ratio of the 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, and then further multiplied by a heat pump HSPF improvement degradation 

factor to account for the impact of climate on relative heating efficiency improvement. Figure 

7.2.1 and Figure 7.2.2 provide flow diagrams for the calculation of cooling and heating energy 

for the residential energy use analysis.
7-3

Figure 7.2.1 Flow Diagram for the Determination of Annual Space-Cooling Energy for 

Residential Central Air Conditioners and Central Heat Pumps

Figure 7.2.2 Flow Diagram for the Determination of Annual Space-Heating Energy for 

Residential Central Heat Pumps

RECS 

Stock Household 

Annual Heating 

Energy (Weather 

Normalized)

RECS 

Age of Household 

CHP

Standard Level 

HSPF

Market Baseline 

HSPF Distribution

Baseline SEER

(HSPF 7.7)

AHRI

Shipment Average 

HSPF by Vintage

CHP

Baseline 

Annual Heating 

Energy Use

Market Baseline 

Annual Heating 

Energy Use

Estimated 

HSPF of Stock 

CHP

Standard Level 

Annual Heating 

Energy Use

RECS 

Stock Household 

Annual Cooling 

Energy (Weather 

Normalized)

RECS 

Age of Household 

CAC or CHP

Standard Level 

SEER

Market Baseline 

SEER

Distribution

Baseline SEER

(SEER 13)

AHRI

Shipment Average 

SEER

CAC and CHP

Baseline 

Annual Cooling 

Energy Use

Market Baseline 

Annual Cooling 

Energy Use

Standard Level 

Annual Cooling 

Energy Use

Estimated SEER

of Stock 

CAC or CHP
7-4

7.2.1.2 General Approach to the Energy Use Analysis – Commercial

DOE also developed estimates for the annual energy use for central air conditioner and 

central heat pump equipment sold into the commercial building market. The commercial market 

is estimated to use approximately 7 percent of all central air conditioner and central heat pump 

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 central air conditioner and central heat 

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

between the efficiency levels simulated. Figure 7.2.3 provides a flow diagram for the calculation 

of central air conditioner and central heat pump cooling and heating energy for the commercial 

energy use analysis.

Figure 7.2.3 Flow Diagram for the Determination of Annual Space-Cooling and SpaceHeating Energy for Central Air Conditioners and Central Heat Pumps in Commercial Use

7.2.1.3 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

• Central air conditioner and central heat pump equipment age information for the 

RECS households

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

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
7-5

• Historical average cooling and heating efficiency data for central air conditioner and 

central heat pump equipment from the Air-Conditioning, Heating and Refrigeration 

Institute (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

7.2.2 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 central air 

conditioner unit also being a cooling-performance heat pump. The numbers of households 

actually included in the LCC and PBP analyses were 1,854 for the central air conditioner systems 

and 339 for heat pumps. Of the 1,901 (2,317 − 416) households that could have been considered 

for analysis of central air conditioner energy consumption, 47 were not included in the analysis

for the following reasons:

• The central air conditioner system was reported as not being used (40 households). 

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

second response that the central air conditioner 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 non-furnace heating equipment (i.e., heating stove, 

fireplace, built-in wall furnaces, etc.) as 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 
7-6

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

presence in error (36 households). 

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

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

heating energy use reported from the conditional demand model was representative of a 

heat pump or an electric furnace. Barring more detail on the analysis of these records by 

EIA, these households were removed from consideration in DOE’s analysis (25 

households).

7.2.3 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 central air 

conditioners and central heat pumps 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 coolingperformance heat pumps was estimated for each RECS observation using equation 7.2.1.

base

res stock

res base c res stock c SEER

SEER

UEC UEC _

_ _ = _ _ × Eq. 7.2.1

Where:

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 is discussed.

7.2.3.1 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 
7-7

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 is 

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

conditional demand analysis (CDA)1 model to further break down 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 central air conditioner or central heat pump 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 is first adjusted (weathernormalized) using 30-year average (1978–2007) cooling degree-day (CDD) data (base 65 °F) 

and equation 7.2.2:

_ _ 2005

30 _ _

_ _ _ _ _

res stock

yr avg

res stock c res stock c non adj CDD

CDD

UEC = UEC − × Eq. 7.2.2

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.

7.2.3.2 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. The states included in each of these geographic regions are 

shown in Table 7.2.1. 

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. 
7-8

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 7.2.1.

Table 7.2.1 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 equation 7.2.2. Statistics showing the weather-adjusted annual space-cooling 

energy consumption for the households that have air conditioners are shown in Table 7.2.2. 

Statistics showing the weather-adjusted annual space-cooling energy consumption for the 

households that have heat pumps are shown in Table 7.2.3. The frequency distribution of the 

weather-adjusted annual household energy consumption for space-cooling for central air 

conditioner and central heat pump equipment for the RECS observations is shown in Figure 7.2.4

and Figure 7.2.5.
7-9

Table 7.2.2 Weather Adjusted Space-Cooling Energy Consumption Statistics at Regional 

Level (CAC-Stock)

Division or State Number of 

Observations

Min

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

* kilowatt-hours per year

Table 7.2.3 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
7-10

Figure 7.2.4 National Distribution of Weather-Adjusted Space-Cooling Energy for CACRECS Observations

Figure 7.2.5 National Distribution of Weather-Adjusted Space-Cooling Energy for CHPRECS Observations

7.2.3.3 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 

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

Percentage of Obersavtions

Weather-Adjusted CAC Cooling Energy from RECS 

(kWh/yr)

0%

2%

4%

6%

8%

10%

12%

14%

Percentage of Obersavtions

Weather-Adjusted CHP Cooling Energy from RECS 

(kWh/yr)
7-11

specific vintage year. 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 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 central air conditioner 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 central air conditioner systems in the “less than 2 

years old” age group, it was assumed that 50 percent of heat pumps were 1 year old and the other 

50 percent were 2 years old. A 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 central air conditioners and central heat pumps in the RECS 

households identified for analysis is listed in Table 7.2.4 and shown in Figure 7.2.6 and Figure 

7.2.7, respectively.

Table 7.2.4 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 

Conditioners

243 321 472 502 316 1854

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

Cooling-Performance 

Heat Pump

57 61 104 89 28 339

16.8% 18.0% 30.7% 26.3% 8.3% 100%

Figure 7.2.6 The Distribution of Central Air Conditioners in the RECS Sample by Age 

Groups

Once the age group into which the household equipment falls 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 was assumed to be 

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

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 CAC Systems

Percent Of households
7-12

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

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

sample is shown in Figure 7.2.8.

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 7.2.5.

Figure 7.2.7 The Distribution of Central Heat Pumps in the RECS Sample by Age Groups

Figure 7.2.8 Distribution of RECS Households with Central Air Conditioners by Vintage 

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

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 Equipment

Percent of Households
7-13

Table 7.2.5 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

7.2.3.4 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 equation 7.2.2. 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 7.2.5; 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 7.2.6 for air conditioners and Table 7.2.7 for heat 

pumps. 
7-14

Table 7.2.6 Baseline (13 SEER) Space-Cooling Energy Consumption Statistics at Regional 

Level (Central Air Conditioner)

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 7.2.7 Baseline (13 SEER) Space-Cooling Energy Consumption Statistics at Regional 

Level (Central Heat Pump)

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

7.2.4 Baseline Annual Space-Heating Energy Use for Central Heat Pump Equipment—

Residential

The baseline annual space-heating energy consumption for the central heat pump 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 generic equation:

DF

HSPF

HSPF

UEC UEC

base

res stock

res base h = res stock h × × _

_ _ _ _ Eq. 7.2.3
7-15

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, and

DF= HSPF improvement degradation factor.a

The DF term is a factor used to adjust the HSPF ratio to make it reflect the improvement 

in heating seasonal performance for a particular climate region. See appendix 7-A for a 

discussion of the derivation of the HPSF improvement degradation factor.

7.2.4.1 Estimating Stock Annual Space-Heating Energy Use

The annual space-heating energy consumption for the central heat pump 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 space-heating energy consumption in 2005 was adjusted by using the following equation: 

res stock

yr avg

res stock h res stock h non adj HDD

HDD

UEC UEC

_

30 _ _

_ _ _ _ _ = ⋅ − Eq. 7.2.4

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 the 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 7.2.1. The 30-year average HDD and the 2005 HDD for the 

nine census divisions and the four large states are shown in Table 7.2.8.

 a HSPF improvement degradation factors were assumed to be 1.0 for the calculation of baseline heating energy. 
7-16

Table 7.2.8 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 7.2.4, the weather-adjusted annual space-heating energy consumption 

was estimated for the equipment in each household. Statistics for the weather-adjusted spaceheating energy consumption at both divisional and national level are shown in Table 7.2.9. The 

frequency distribution of the RECS sample households in different heating energy consumption 

bands is shown in Table 7.2.9.

Table 7.2.9 Statistics of Annual Weather-Adjusted Space-Heating Energy Consumption for 

RECS-Stock Central Heat Pump 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
7-17

Figure 7.2.9 National Distribution of Weather-Adjusted Space-Heating Energy for RECS 

Observations

7.2.4.2 Stock Space-Heating Efficiency (HSPF)

The space-heating efficiency of central heat pump 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 1 year old and the other 50 percent were 2 years old. A 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 7.2.10 and the distribution of heat pump vintages is shown in 

Figure 7.2.11.

AHRI does not publish data on the historical average HSPF for central heat pump 

equipment. DOE developed historical HSPF estimates from two data sources. For the years from 

1973 to 1993, DOE used data reported in the TSD for the 2001 CAC Rulemaking.5 For the 

period from 1994 to 2005, DOE examined the 1994 Air-Conditioning & Refrigeration Institute 

(ARI) directory of Certified Products and developed a regression equation that relates the SEER 

of residential split-system heat pumps. DOE used the 1994 ARI Directory of Certified 

Equipment Database6 to generate regressions between SEER and HSPF for central heat pump 

equipment on the market in 1994. For split systems, DOE used a regression based on data for all 

0%

5%

10%

15%

20%

25%

Percentage of Obersavtions

Weather-Adjusted CHP Heating Energy from RECS 

(kWh/yr)
7-18

central heat pump equipment characterized by the AHRI designations HRCU-A-CB and HRCUA-C. For packaged heat pumps, DOE used a regression for all central heat pump equipment with 

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

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

split-system heat pump equipment class and one for the 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 central heat pump equipment was then developed by 

weighting the annual average HSPF values by class using historical shipment data by equipment 

class. Table 7.2.10 shows the resulting historical HSPF values by vintage. 

Figure 7.2.10 Distribution of Households with Heating-Performance Heat Pumps by Age 

Groups

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
7-19

Figure 7.2.11 Distribution of RECS Households with Central Heat Pumps by Vintage 

Table 7.2.10 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

7.2.4.3 Estimating Baseline Annual Space-Heating Energy Use

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

central heat pump equipment was estimated by using equation 7.2.4. 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 central heat pump equipment shown in Table 

7.2.10; and the baseline heating efficiency, 7.7 HSPF.

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

1,9761,9791,9821,9851,9881,9911,9941,9972,0002,003

Vintage Year of the Heat Pump Systems

Percent of Households
7-20

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

households with central heat pump equipment at regional and national level are shown in Table 

7.2.11.

Table 7.2.11 Baseline (13 SEER) Space-Heating Energy Consumption Statistics at Regional 

Level (Central Heat Pumps)

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

7.2.5 Baseline Residential Cooling and Heating Results − Adjusted for RECS Sample 

Weights

Table 7.2.6, Table 7.2.7, and Table 7.2.11 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 7.2.12, Figure 7.2.13, and Figure 7.2.14 show the distribution of 

calculated baseline cooling and heating energy for central air conditioner and central heat pump 

products used in residences, taking into account the RECS household samples weights. 

Figure 7.2.12 Baseline National Cooling Energy Distribution for Central Air Conditioners 

– Residential

0%

5%

10%

15%

20%

25%

Percentage of Households

Baseline CAC Cooling Energy (kWh/yr)
7-21

Figure 7.2.13 Baseline National Cooling Energy Distribution for Central Heat Pumps –

Residential

Figure 7.2.14 Baseline National Heating Energy Distribution for Central Heat Pumps –

Residential

7.2.6 Baseline Commercial Central Air Conditioner and Central Heat Pump Energy Use 

Seven percent of residential-type (i.e., single-phase) central air conditioner and central 

heat pump applications are assumed to be in commercial buildings. While this equipment could 

be used in a wide variety of buildings, DOE believes that the vast majority is used in small 

buildings, in particular small retail and commercial buildings. This is primarily because central 

air conditioner and central heat pump equipment uses single-phase electricity, which limits the 

application to smaller buildings. 

0%

2%

4%

6%

8%

10%

12%

14%

Percentage of Households

Baseline CHP Cooling Energy (kWh/yr)

0%

5%

10%

15%

20%

25%

Percentage of Households

Baseline CHP Heating Energy (kWh/yr)
7-22

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

such use in residential buildings, even for the same equipment. This is predominantly because

commercial buildings are 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 central air conditioner and 

central heat pump equipment using CBECS. In addition, CBECS does not clearly distinguish 

equipment types by electrical phase. Hence, it is difficult to identify buildings that are 

predominantly served by central air conditioner and central heat pump equipment. Given these 

difficulties, DOE determined that CBECS could not be used to estimate the cooling and heating 

energy data for central air conditioner and central heat pump equipment used in commercial 

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

energy usage of central air conditioner and central heat pump equipment in commercial 

buildings.

7.2.7 Overview of Commercial Energy Simulation Approach

In order to develop energy use statistics that reflect the use of central air conditioner and 

central heat pump 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 central air 

conditioner and central heat pump used to satisfy the cooling, supply fan, and, in the case of 

central heat pump, 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 DOE for energy 

benchmarking purposes for this analysis. This commercial reference building model is 1 of 16 

commercial reference building models developed in support of DOE’s Commercial Building 

Initiative program.

11

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

by central air conditioner equipment with a gas furnace backup or were entirely served by central 

heat pump equipment. The simulated building used five individual central air conditioner (or 

central heat pump) units. For each equipment type, DOE simulated the equipment at four 

different efficiency levels, starting from the baseline level. For central air conditioner equipment, 

these levels were 13 SEER, 14 SEER, 16 SEER, and a max-tech level of SEER 24.5 based on 

blower-coil ratings. For central heat pump equipment, these levels were 13 SEER, 14 SEER, 16 

SEER, and a max-tech level of SEER 22 based on blower-coil ratings. Equipment parameters 
7-23

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. locations.12

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

heating from each modeled central air conditioner or central heat pump unit, as well as the 

equipment cooling capacity for each unit from each simulation run, and aggregated these to the 

whole-building level. Using these whole-building cooling and heating data, as well as the 

equipment capacities, DOE normalized the central air conditioner and central heat pump energy 

consumption for each location and efficiency level to that of an average 3-ton central air 

conditioner or central heat pump unit. These normalized energy use statistics were then further 

scaled linearly, as necessary, to reflect the energy use for a 2-, 3-, or 5-ton central air conditioner 

or central heat pump product, depending on the size of unit modeled in 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.

7.2.7.1 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 

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. EnergyPlus 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.

7.2.7.2 Efficiency Levels Analyzed and Corresponding Simulation Parameters

DOE simulated four efficiency levels for central air conditioner equipment and four 

efficiency levels for central heat pump 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 

coefficient of performance (COP)—for central heat pump the heating COP—of the condensing 

unit at rated conditions and the fan power. The central air conditioner and central heat pump 

condensing unit parameters are in turn calculated from 95 °F energy efficiency ratio (EER) and 
7-24

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 central air conditioner 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 values for each SEER level modeled were established based on the 

median EER corresponding to that SEER level in the AHRI Certified Directory as established for 

equipment designated as “not for export only.”b

COP F = −0.0255× HSPF + 0.6239× HSPF 2

47

HSPF levels were established based on the 

engineering analysis HSPF values corresponding to the SEER modeled for split-system heat 

pumps. Because COP47 °F ratings are not provided in the AHRI database, DOE relied on a 

relationship between HSPF and COP47 °F established in the literature.13 This curve fit is shown in 

equation 7.2.5.

Eq. 7.2.5

In addition, DOE modeled the highest efficiency equipment as a multistage condenser 

system with two stages of operation. To properly account for two stages of operation, DOE used 

the EnergyPlus multi-speed unitary heat pump model for both air conditioners and heat pumps, 

disabling the heat pump heating capacity when modeling the unit as an air conditioner and 

relying on a gas furnace for backup heating.

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 inches of water (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 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 central air conditioner/central 

heat pump market as determined in 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 of 138 W/ton at rated conditions 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 cubic feet per minute (cfm) 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 

 

b This refers to the AHRI Certified Directory information as of July 17, 2010, for air conditioning and heat pump 

units.
7-25

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

heating output. Equations 7.2.6 and 7.2.7 provide cooling and heating COP ratings for the 

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

( )

R

EER R COPCUCool F −+ ° = 1/ 3.413 ,95 Eq. 7.2.6





 





−

− = °

° R

COP R COP F

CUHeat F 1

47

,47 Eq. 7.2.7

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 7.2.12 shows the resulting equipment performance statistics for the commercial 

building models.

Table 7.2.12 Central Air Conditioner and Central Heat Pump 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

(Condensing 

Unit Only)

Heating 

COP47°F

(Condensing 

Unit Only)

CAC 13 NA 11.07 NA 0.65 138 0.127 3.86 NA

14 NA 11.8 NA 0.65 138 0.135 4.15 NA

16 NA 12.53 NA 0.80 112 0.117 4.29 NA

24.5 NA 15.0 NA 0.80 112 0.140 5.27 NA

CHP 13 8 11.2 3.29 0.65 138 0.128 3.91 3.71

14 82 11.8 3.36 0.65 138 0.135 4.15 3.75

16 8.7 12.4 3.48 0.80 112 0.116 4.24 3.87

22 10.1 14 3.72 0.80 112 0.130 4.87 4.10

* Calculated for rating conditions.

7.2.7.3 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 5,500 ft2, single-story, 

rectangular, 52 ft by 105 ft, with an aspect ratio of 1.5. The building has a window-area ratio of 

21 percent with a 10-ft floor-to-ceiling height. The small office building is assumed to have slabon-grade construction for the floor and an attic. A picture of the building structure is shown in 

Figure 7.2.15. The building is divided into five HVAC zones, four perimeter zones, and a core 

zone as illustrated in Figure 7.2.16, with a single central air conditioner or central heat pump unit 

assumed for each HVAC zone. The perimeter zone depth in the center of each zone is 16 ft.
7-26

Figure 7.2.15 Small Office Building Design View

Figure 7.2.16 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 American Society of Heating, Refrigerating and AirConditioning Engineers (ASHRAE) Standard 90.1-2004. 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 2003 CBECS 

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.

7.2.7.4 Building Operating Characteristics

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

occupancy occurring from 8 a.m. to 5 p.m. weekdays and limited occupancy from 6 a.m. until 8 

a.m. and from 5 p.m. extending until midnight for janitorial functions. The building is assumed 

to be unoccupied on weekends and holidays. Schedules for lighting and miscellaneous 

equipment were matched to occupancy schedules, with lower usage during unoccupied times. 

HVAC system 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 

7.2.17, Figure 7.2.18, Figure 7.2.19, and Figure 7.2.20 show the EnergyPlus schedules for 

lighting, plug loads, occupancy, and thermostat set point. Detailed schedules are shown in 

appendix 7-B 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 
7-27

assumed that ventilation occurs whenever the fan system is operational. In the case of 

infiltration, a maximum infiltration rate for each hour is calculated 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 are scheduled to be off on weekends and holidays. Building thermostats are 

set to 70 °F heating and 75 °F cooling during the occupied period. Thermostats are set back to 60 

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

mornings, the thermostats are set to 65 °F cooling and 80 °F heating set points to provide a 

1-hour thermostat ramp between the setback and occupied set points to prevent equipment sizing 

and temperature balance problems.

For the occupancy, lighting, plug use, and 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 lighting power density 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 1,000 ft2). Total outdoor air exchange during the 

occupied period (effective ventilation) was based on ASHRAE Standard 62-1999 and set to 0.1 

cfm/ft2 of floor area for each conditioned zone, corresponding to 0.6 air changes per hour. 

Ventilation was introduced directly into the zone and not through a mixed air box associated 

with the cooling system. The peak infiltration for the building was based on hourly wind speed, 

as discussed previously, averaging to 0.2016 cfm/ft2 of total exterior conditioned zone wall area 

at a wind velocity of 10 miles per hour.

Figure 7.2.17 Small Office Lighting Schedule

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
7-28

Figure 7.2.18 Small Office Plug Load Schedule

Figure 7.2.19 Small Office Occupancy Schedule
7-29

Figure 7.2.20 Small Office Thermostat Set Point Schedule

7.2.7.5 Building Mechanical Systems and Equipment

As discussed, the building used either five central air conditioner units or five central heat 

pump 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-B.

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

power efficiency discussed in section 7.2.7.2. However, the total fan static pressure was 1.45 in.

H2O based on the assumption used in the benchmark prototype, compared to 1.105 in. H2O total 

static pressure used to characterize the equipment performance at rating conditions. DOE was not 

able to identify a specific source of information regarding the use of continuous air circulation 

for residential (single-phase) heat pumps in commercial buildings. A California study of 215 

small air conditioners in commercial buildings found intermittent (cycling) ventilation operation 

during the occupied period in 38 percent of cases examined.

14 To emulate this, the commercial 

analysis had 40 percent (two out of five) of the HVAC zones operate in intermittent circulation 

model during the occupied period.

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

for all climates. A sizing run is done before 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.

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
7-30

7.2.8 Baseline Commercial Energy Distribution

To be of use in the central air conditioner analysis, the baseline commercial central air 

conditioner and central heat pump 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 to represent the importance of each

climate in each state. The development and documentation of these weighting factors is found in 

appendix 7-C. Because certain TMY locations represent climates that cover more than one state 

(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 subsequent LCC analysis in addressing central air conditioner and central 

heat pump energy use in commercial buildings. However, 17 locations in Alaska, which make up 

approximately 0.2 percent of the national weight, were removed from the energy analysis due to 

issues with electrical price data. Figure 7.2.21, Figure 7.2.22, and Figure 7.2.23 show 

distributions of commercial central air conditioner cooling and central heat pump cooling and 

heating energy use in the nation that accounts for the relative weights attached to each of the 

remaining 526 TMY-State combinations. 

Figure 7.2.21 Baseline National Cooling Energy Distribution for Central Air Conditioners

− Commercial, Weighted

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Percentage of Simulated 

Commercial Small Offices

Baseline CAC Cooling Energy (kWh/yr)
7-31

Figure 7.2.22 Baseline National Cooling Energy Distribution for CHC − Commercial, 

Weighted

Figure 7.2.23 Baseline National Heating Energy Distribution for Central Heat Pumps −

Commercial, Weighted

7.2.9 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 simulated was by 

interpolation between HSPF levels simulated.

0%

10%

20%

30%

40%

50%

60%

Percentage of Simulated 

Commercial Small Offices

Baseline CHP Cooling Energy (kWh/yr)

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Percentage of Simulated 

Commercial Small Offices

Baseline CHP Heating Energy (kWh/yr)
7-32

7.2.10 Market Baseline Space-Cooling and Space-Heating Efficiencies 

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

baseline space-cooling and space-heating energy use for central air conditioner and central heat 

pump 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 splitsystem central air conditioner and central heat pump 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 used to estimate the baseline energy 

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

from the market baseline distribution. Then equations 7.2.1 and 7.2.3 were used 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. In the case of heat pump heating, HSPF improvement degradation factors were 

used as developed in appendix 7-A to adjust the HSPF improvement to reflect different climate 

regions used in DOE’s analysis. For commercial TMY-State observations, DOE first randomly 

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

corresponding cooling fan and heating energy use for that observation in 2016 by linear 

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

chapter 8 for the market distribution of efficiency levels by product class.

7.2.11 Determining Installed Equipment Capacity for RECS Observations 

The notice of proposed rulemaking analysis was done using cost curves developed for 

three different sizes of split-system air conditioners and three different sizes of split-system heat 

pumps in order to capture variability in the costs to improve the efficiency of the equipment. In 

order to better analyze this within the market as a whole, DOE developed a process to assign a 

particular system size (2-, 3-, or 5-ton) to each RECS observation to support the LCC analysis 

discussed in chapter 8. DOE selected an appropriate capacity to assign to each RECS 

observation, taking into account the size of the residence and the geographic location of the 

residence as it influences the climate and sizing of equipment. The assignment of a cooling 

capacity is done to establish the first cost of equipment provided to the residence. The energy 

consumption is based on the RECS data, as adjusted for the baseline efficiency or other 

efficiency scenario.

The starting point for this process was to allocate all air conditioner and heat pump 

shipments to the capacities analyzed in the engineering analysis. The AHRI website provides a 

breakdown of monthly combined shipments of air conditioners and heat pumps by cooling 
7-33

capacity bins.

15 These data are not shown independently for the product classes, but are assumed 

to be representative for split systems, which are the vast majority of shipments.

For the residential equipment in question, eight cooling capacity bins encompassing 

capacities from 0 to 64.9 kilo British thermal units per hour (kBtu/h) are available. The SEER 

bins and unit shipments for 2009 are shown in the first two columns of Table 7.2.13 under AHRI 

Data. The data show that there are approximately equal values for combined air conditioner and 

heat pump shipments in the 22.0−22.9 kBtu/h and 33.0−38.0 kBtu/h bins, each corresponding to 

nominally sized 2- and 3-ton air conditioners, respectively. There are also significant shipments 

in the intermediate bin between these two. There are relatively fewer, but still significant, 

shipments above and below these bins. Because air conditioning equipment is typically sold in 

nominally one-half cooling ton increments, the estimated average cooling capacity for each bin 

was also estimated and is shown in Table 7.2.13. The distribution of shipments at these nominal 

sizes is shown in Figure 7.2.24. The average cooling capacity shipped was estimated from the 

AHRI data at 34.4 kBtu/h, or very close to a 3-ton unit.

DOE assigned the shipments in each bin to each of the cooling capacities identified in the 

engineering analysis (2-, 3-, or 5-ton). Most bins were wholly assigned to one of the engineering 

capacities. In the case of nominally 30 kBtu/h units (27.0−32.9 kBtu/h bin), shipments were 

equally divided between 2- and 3-ton sizes. In the case of the 48 kBtu/h units (44−53.9 kBtu/h 

bin), shipments were equally divided between 3- and 5-ton sizes. The resulting fraction of the 

market assigned to each of the engineering capacities is shown in Table 7.2.13. Also shown is 

the weighted average cooling capacity based on the overall actual shipments and corresponding 

nominal sizes allocated to each engineering capacity. For example, the engineering 2-ton units 

represent 40.1 percent of all shipments and, on average, those shipments had an actual capacity 

of 23.2 kBtu/h. The 3-ton units represent 44.5 percent of shipments, and the engineering 5-ton 

units are assumed to represent 14.5 percent of shipments. The average capacity of the shipments 

assigned to 2- and 3-ton units is very close to the nominal 2- and 3-ton engineering capacities.

The weighted average of shipments assigned to the 5-ton engineering capacities is approximately 

midway between 4- and 5-ton nominal sizes.

Applying the market percentages assigned to each of the nominal 2-, 3-, and 5-ton 

engineering sizes yields an average market size of 34.9 kBtu/h. This corresponds closely with the 

34.4 kBtu/h average capacity shipped estimated directly from the AHRI data, which suggests

that the percentage weights assigned to the engineering sizes result in a good representation of 

the average total cooling capacity shipped.
7-34

Table 7.2.13 Development of Market Weights for 2-, 3-, and 5-Ton Air Conditioners and 

Heat Pumps

AHRI Data Mapping to Engineering Sizes

SEER Bin 

kBtu/h

Units 

(2009 

Shipped)

Est. 

Avg.

Cooling 

Capacity 

kBtu/h

Assigned to 

Engineering 

Size 

tons

Weighted 

Average 

Cooling 

Capacity 

Assigned 

kBtu/h

Fraction 

of 

Market 

%

Nominal 

Engr. 

Cooling 

Capacity 

kBtu/h

0 - 16.4 155,396 12 2

23.195 0.401 2

16.5 -21.9 380,779 18 2

22.0 - 26.9 1,006,905 24 2

27.0 - 32.9 854,454 30 50% 2-ton

50% 3-ton

36.053 0.445 3

33.0 - 38.9 1,039,122 36 3

39.0 - 43.9 428,931 40 3

44.0 - 53.9 591,554 48 50% 3-ton

50% 5-ton

55.314 0.154 5

54.0 - 64.9 461,598 60 5

Total 4,918,739

Average Cooling Capacity

(kBtu/h) 34.4 34.9

Figure 7.2.24 Shipments of Residential Air Conditioners and Heat Pumps by Capacity for 

2009

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

12 18 24 30 36 40 48 60

2009 Shipments (Units)

Nominal Cooling Capacity (kBtu/h)
7-35

In order to size the RECS households, DOE presumed that the distribution of shipment 

sizes described previously represented the distribution within the RECS sample after taking into 

account the household weights. For each household, DOE extracted all relevant household size 

data, including the cooled square footage of the home. DOE also used ASHRAE design data to 

develop estimates of the average 1 percent design dry bulb temperature in each of the three 

analysis regions. For each region, DOE then developed a scaling factor to be applied to the home 

square footage and equal to:

SFdesign,r = (Tdesign, r – 65) / (95 - 65) Eq. 7.2.8

Where:

SFdesign,r = design scaling factor, and

Tdesign, r = average 1 percent ASHRAE design dry bulb temperature for region (°F).

This scaling factor was then multiplied by the reported cooled area for each household. A 

±20 percent uncertainty factor was then applied to the cooled area to reflect some uncertainty in 

the sizing of the equipment to that observation, which provided some randomization in the size 

assignment to the RECS households. The RECS observations were then sorted by this new 

scaled cooled household area, and the central air conditioner equipment sizes (2-, 3-, and 5-ton) 

were assigned from smallest to largest area and according to each central air conditioner size’s 

share in the overall market. As a check on the results, the estimated cooling full load operating 

hoursc of the equipment (calculated based on the RECS reported cooling energy use, RECS 

estimated SEER, and the selected equipment size) were examined. In a few instances where the 

full load operating hours calculated were very high (e.g., >4,000) and did not appear to represent

reasonable estimates for the regions in question, DOE modified the assignment of equipment size 

by choosing the next larger size central air conditioner available from the engineering analysis.

It is noted that the design scaling factor is used as a proxy to represent lower cooling 

loads for the same household area in cooler climates and supports the allocation of the sizes 

across observations, but that the total relative allocation of sizes is unaffected. This end result 

was a distribution of sizes assigned to the weighted RECS samples that matches the distribution 

of sizes for shipments of residential air conditioners and heat pumps.

7.2.12 Regional Energy Consumption by Efficiency Level 

Under the Energy Policy and Conservation Act, regional efficiency standards for central 

air conditioners 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. As discussed in chapter 2, DOE defined two regions for regional standards: a hot-humid 

region and a hot-dry region. In addition, DOE defined the remainder of the states as “rest-ofcountry.” For each equipment class, DOE developed energy use statistics for the market baseline 

 c Cooling full load operating hours are a measure of how many hours in a year the equipment would run at full 

capacity to provide the total estimated cooling load met by the equipment. 
7-36

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. Of those observations, 

93 percent were residential and 7 percent were commercial instances of the use of central air 

conditioner (or central heat pump) equipment. 

In addition, at the national level, energy use statistics for each equipment class are further 

influenced by relative shipments between each region, not captured in the RECS data. 

Shipments by region for each air conditioner class were provided by AHRI for the years 2008 

and 2009.d

Table 7.2.14

 These were converted to relative fractions of shipments for each product class by 

year. These relative shipment fractions by year are shown in chapter 9. DOE averaged the 

relative shipment fraction for each region across both years to provide product-specific regional 

weighting factors and used these to further adjust the weighting factors developed for each 

observation. For small duct high velocity equipment, AHRI did not provide a weighting factor. 

DOE used the product-specific regional weighting factor developed for split system air 

conditioners also for small duct high velocity equipment. These product-specific regional 

weighting factors are shown in . 

Table 7.2.14 Fraction of Shipments by Product Class to Each Region

Region

Product Class Hot-Dry Hot-Humid Rest of U.S.

Split System CAC 0.374 0.515 0.112

Split System HP 0.194 0.736 0.070

Single Package CAC 0.174 0.578 0.248

Single Package HP 0.033 0.719 0.248

Small Duct High Velocity 

AC

0.374 0.515 0.112

Source: AHRI

In the Monte Carlo simulations for each product class, the relative weighting factors for 

each residential household observation were multiplied by the product-specific regional 

weighting factors for that region that household was in. Similarly, the observation weights 

developed for each commercial observation (TMY-State combination) were multiplied by the 

product specific regional weighting factors for that region. Thus all the individual observation 

weighting factors in a given region were scaled by the same value. This scaling has no impact 

on the relative probability of selection for the observations within a given region, and thus no 

impact on the calculated results from the Monte Carlo simulations within a given region. 

However, when developing national results for each product class these product-specific regional 

weighting factors affect the relative probability of selecting an observation between regions. 

Further details for the Monte Carlo analysis procedure are found in chapter 8. Table 7.2.15 to 

Table 7.2.20 show the resulting baseline, market baseline, and higher efficiency annual energy 

statistics developed for each region for each product class analyzed.

 

d Shipments for hot-humid, hot-dry, and rest-of-country regions provided by AHRI for 2008 and 2009 in shipments 

data provided to DOE (Aug 2010).
7-37

Table 7.2.15 Split-System Air Conditioners: Average Annual Energy Use by Efficiency 

Level − 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 2,470 0 3,411 0 2,226 0 1,334 0

Market 

Baseline

Market 

Baseline

N/A 2,340 0 3,226 0 2,111 0 1,266 0

2 13.5 N/A 2,382 0 3,288 0 2,147 0 1,289 0

3 14.0 N/A 2,301 0 3,174 0 2,074 0 1,247 0

4 14.5 N/A 2,222 0 3,066 0 2,003 0 1,204 0

5 15.0 N/A 2,147 0 2,964 0 1,936 0 1,163 0

6 15.5 N/A 2,078 0 2,868 0 1,873 0 1,124 0

7 16.0 N/A 2,012 0 2,778 0 1,814 0 1,087 0

8 16.5 N/A 1,966 0 2,714 0 1,772 0 1,066 0

9 17 N/A 1,924 0 2,653 0 1,733 0 1,045 0

10 18 N/A 1,892 0 2,606 0 1,707 0 1,032 0

* N/A means not applicable.

Table 7.2.16 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 2,468 0 3,409 0 2,227 0 1,333 0

Market 

Baseline

Market 

Baseline

N/A 2,200 0 3,025 0 1,986 0 1,190 0

2 13.5 N/A 2,381 0 3,286 0 2,148 0 1,288 0

3 14.0 N/A 2,299 0 3,172 0 2,074 0 1,246 0

4 14.5 N/A 2,220 0 3,063 0 2,003 0 1,203 0

5 15.0 N/A 2,146 0 2,962 0 1,937 0 1,162 0

6 15.5 N/A 2,076 0 2,866 0 1,874 0 1,123 0

7 16.0 N/A 2,011 0 2,776 0 1,815 0 1,087 0

8 16.5 N/A 1,952 0 2,695 0 1,762 0 1,057 0

9 17.0 N/A 1,898 0 2,618 0 1,713 0 1,028 0

10 18.0 N/A 1,797 0 2,478 0 1,622 0 976 0

11 19.0 N/A 1,726 0 2,377 0 1,556 0 941 0

12 20.0 N/A 1,662 0 2,286 0 1,497 0 910 0

13 21.0 N/A 1,604 0 2,204 0 1,444 0 882 0

14 22.0 N/A 1,550 0 2,129 0 1,394 0 856 0

1,531 0 2,100 0 1,378 0 848 0

1,504 0 2,061 0 1,356 0 836 0

* N/A means not applicable.
7-38

Table 7.2.17 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 8.00 3,265 1,645 3,664 1,452 4,037 809 1,547 2,738

Market 

Baseline

Market 

Baseline

Market 

Baseline

3,030 1,594 3,401 1,407 3,747 784 1,439 2,656

2 13.5 8.1 3,149 1,629 3,532 1,437 3,891 801 1,494 2,713

3 14 8.2 3,040 1,606 3,410 1,416 3,756 788 1,445 2,680

4 14.5 8.3 2,936 1,588 3,293 1,400 3,627 780 1,395 2,653

5 15 8.5 2,838 1,567 3,184 1,380 3,507 762 1,348 2,648

6 15.5 8.6 2,747 1,554 3,082 1,367 3,394 755 1,303 2,635

7 16 8.7 2,661 1,538 2,985 1,353 3,287 747 1,261 2,613

8 16.5 8.8 2,583 1,526 2,898 1,342 3,192 741 1,226 2,594

9 17 8.9 2,510 1,508 2,815 1,326 3,102 731 1,193 2,569

10 18 9.1 2,378 1,487 2,667 1,307 2,940 719 1,133 2,538

11 19 9.4 2,289 1,466 2,567 1,289 2,811 707 1,099 2,506

12 20 9.6 2,207 1,445 2,477 1,269 2,695 694 1,068 2,476

13 21 9.8 2,134 1,429 2,395 1,255 2,589 685 1,040 2,454

14 22 10.1 2,109 1,421 2,367 1,248 2,557 679 1,029 2,437
7-39

Table 7.2.18 Single-Package Air Conditioners: Average Annual Energy Use by Efficiency 

Level

Efficiency Level Annual Energy 

Consumption 

kWh/yr

National

# SEER HSPF* Cooling Heating

1 13 N/A 2,703 0

Market 

Baseline

Market 

Baseline

N/A 2,648 0

2 13.5 N/A 2,606 0

3 14 N/A 2,517 0

4 14.5 N/A 2,430 0

5 15 N/A 2,349 0

6 15.5 N/A 2,273 0

7 16 N/A 2,202 0

8 16.5 N/A 2,138 0 

Table 7.2.19 Single-Package Heat Pumps: Average Annual Energy Use by Efficiency Level

Efficiency Level Annual Energy 

Consumption

kWh/yr

National

# SEER HSPF Cooling Heating

1 13 8 3,831 1,526

Market 

Baseline

Market 

Baseline

Market 

Baseline

3,682 1,484

2 13.5 7.9 3,694 1,495

3 14 8.1 3,566 1,466

4 14.5 8.3 3,444 1,438

5 15 8.4 3,329 1,425

6 15.5 8.6 3,222 1,398

7 16 8.8 3,121 1,376

8 16.5 9 3,029 1,354
7-40

Table 7.2.20 Small Duct High Velocity 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 N/A 2,469 0 3,409 0 2,227 0 1,334 0

Market 

Baseline

Market 

Baseline

N/A 2,469 0 3,409 0 2,227 0 1,334 0

2 13.5 N/A 2,381 0 3,287 0 2,148 0 1,289 0

3 14 N/A 2,300 0 3,173 0 2,075 0 1,247 0

4 14.5 N/A 2,203 0 3,046 0 1,986 0 1,185 0

* N/A means not applicable.

7.2.13 Off Mode Energy Consumption 

DOE is considering national standards for off mode energy consumption, but does not 

intend to set regional standards for off mode energy consumption. DOE established annual off 

mode energy consumption estimates for each off mode technology option identified in the 

engineering analysis for air conditioners and for heat pumps. DOE estimated annual off mode 

energy consumption for air conditioners based on the shoulder season off mode power 

consumption (P1) and heating season off mode power consumption (P2) defined for each design 

option multiplied by the representative shoulder season rating hours (739 hours) and heating 

season rating hours (5,216 hours) established in the test procedure. DOE estimated annual energy 

consumption for heat pumps based only on the shoulder season off mode power consumption 

multiplied by the representative shoulder season rating hours (739 hours) established in the test 

procedure because heat pumps operate in active mode during the heating season. These seasonal 

hours are consistent with the rating hours used in the SEER and HSPF ratings for air conditioners 

and heat pumps. 

DOE is considering national standards for off mode energy consumption, but does not 

intend to set regional standards for off mode energy consumption. It is recognized that there will 

be some variation in off mode hours depending on location and individual household usage, but 

DOE believes that the defined off mode hours in the test procedure represent a reasonable basis 

for calculation of energy savings from off mode energy conservation standards. DOE does not 

include in the off mode period the time during the cooling season when a unit cycles off because 

energy use during this period is captured in the seasonal SEER rating of the equipment. 

Similarly, DOE does not include in the off mode period the time during the heating season when 

a heat pump cycles off because energy use during this period is captured in the seasonal HSPF 

rating of the equipment. To avoid double counting the benefits of design options which reduce 

energy consumption during the heating or cooling off-cycles as opposed to the defined off mode 

time period, DOE relied on the representative off mode hours from the test procedure to estimate 

national average off mode period for the energy analysis.
7-41

The component that uses the most power during off mode is the crankcase heater, but it is 

not found in all products. Off mode energy use estimates for air conditioners and heat pumps 

were estimated for units with and without crankcase heaters.

DOE was not able to identify a data source establishing the fraction of central air 

conditioner or heat pump products in the U.S. market which would be tested with crankcase 

heaters or would be expected to have crankcase heaters installed in the field. A 2004 study of the 

Australian market estimated that one in six air conditioners in that market utilized crankcase 

heaters.16 However, changes in compressor technology since 2004, in particular market growth 

in the use of scroll compressors, are expected to have resulted in a lower fraction of the air 

conditioner market with crankcase heaters in the U.S. today. DOE assumed that 10 percent of air 

conditioners within each air conditioner product class would utilize crankcase heaters. Crankcase 

heaters are more commonly used in heat pumps, which must be able to cycle on in cold weather. 

Based on discussions with manufacturers, DOE assumed that approximately two-thirds of heat 

pumps would utilize crankcase heaters in each heat pump product class. 

The engineering technology options examined for off mode energy use do not impact 

blower energy consumption in off mode. For this reason, the energy savings from employing 

these options is identical for equipment utilizing either ECM or PSC blower motors. Annual off 

mode energy use for each technology above the baseline are shown in Table 7.2.21 to Table 

7.2.23 for equipment with ECM motors and both with and without a crankcase heater.

While both ECM and PSC motors employing these technologies will have the same 

energy savings, DOE recognized that the wattage savings from the toroidal transformer design 

option was very small and that separate standard levels based on these design options that would 

be set at levels for which equipment with ECM blower motors could meet would not require the 

use of the toroidal transformer design option when PSC blower motors are used. Because of this 

certain efficiency levels options only apply to equipment with ECM motors. See chapter 8 for a 

detailed discussion.

Table 7.2.21 Split-System Blower Coil, Packaged, Space Constrained, and SDHV Air 

Conditioner Off Mode Energy Use

Annual Off Mode Energy 

Consumption with an ECM Motor 

and Crankcase Heater

kWh/yr

Annual Off Mode Energy 

Consumption with an ECM Motor 

and No Crankcase Heater

kWh/yr

Baseline 286 66

Efficiency Level 1 212 61

Efficiency Level 2 180 NA

Efficiency Level 3 175 NA
7-42

Table 7.2.22 Split-System Coil-Only Air Conditioner Off Mode Energy Use

Annual Off Mode Energy 

Consumption with an ECM Motor 

and Crankcase Heater

kWh/yr

Annual Off Mode Energy 

Consumption with an ECM Motor 

and No Crankcase Heater

kWh/yr

Baseline 220 0

Efficiency Level 1 146 NA

Efficiency Level 2 115 NA

Table 7.2.23 Split-System, Packaged, and Space Constrained Heat Pump Off Mode Energy 

Use

Annual Off Mode Energy 

Consumption with an ECM Motor 

and Crankcase Heater

kWh/yr

Annual Off Mode Energy 

Consumption with an ECM Motor 

and No Crankcase Heater

kWh/yr

Baseline 38 10

Efficiency Level 1 24 10

Efficiency Level 2 23 NA

Not all equipment will be at the baseline efficiency level. DOE established a 2016 base 

case distribution of off mode energy use by efficiency level for each product class. This base 

case took into account that an estimated 10 percent of the split system air conditioner market are 

blower coil equipment and 90 percent are coil only equipment. It also took into account that 

approximately 27 percent of the current shipping blower coil split system and packaged air 

conditioner and the split system and packaged heat pump markets use ECM motors. See chapter 

8 for discussion of the base case assumptions. 

DOE determined energy savings for each technology option as compared to the base case 

in the LCC analysis using a special purpose off mode LCC spreadsheet. See chapter 8 for 

discussion of the off mode LCC analysis. For each equipment class, DOE developed energy use 

statistics for the base case and for each off mode efficiency level by using a Monte Carlo random 

selection process to select 10,000 observations using the base case off-mode efficiency 

distributions. The resulting national average energy use estimates from this process are shown in 

Table 7.2.24 by equipment class. 

Table 7.2.24 National Average Off Mode Energy Use 

Efficiency Level Average Annual Off Mode Energy Consumption 

kWh/yr

Split Air 

ConditionersCoil Only

Split Air 

ConditionersBlower Coil 

and SDHV

Split System 

Heat Pumps

Single Package 

Air 

Conditioners

Single Package 

Heat Pumps

Baseline 22 88 28 88 29

2016 Base Case 19 84 24 84 24

Efficiency Level 1 15 80 19 80 20

Efficiency Level 2 11 77 19 77 20

Efficiency Level 3 11 77 NA 77 NA
7-43

7.3 FURNACES

The following sections describe the factors that determine the amount of heat load and 

energy that furnaces use, the characteristics of furnace energy efficiency, and furnace operating 

conditions.

7.3.1 Introduction

A furnace utilizes gas or oil fuel for heating and electric energy to power a blower, a draft 

inducer, an ignitor, and sometimes auxiliary equipment. DOE estimated the energy consumption 

of furnaces in actual housing units, as represented by the sample developed from RECS 2005.17

This sample is further described in section 7.3.2.

DOE calculated the energy use of residential furnaces in each of the three product 

classes: non-weatherized gas furnaces, manufactured home furnaces, and oil-fired furnaces. For 

each household in the sample, DOE used RECS 2005 reported heating energy consumption 

(based on the existing heating system) to calculate the heating load of each household. The 

heating load represents the amount of heating required to keep a housing unit comfortable 

throughout an average year. DOE assigned the energy efficiency of existing systems based on a 

regional historical distribution of energy efficiencies for furnaces and RECS data on the age of 

the existing furnace. The estimation of heating loads also required calculating the electricity 

consumption of the blower (when applicable), because heat from the blower contributes to 

heating the housing unit. In addition, DOE made adjustments based on historical weather data, 

projections of shell efficiency and building square footage, and for homes that had secondary 

heating equipment that used the same fuel as the furnace. To complete the analysis, DOE 

calculated the energy consumption of alternative (more energy-efficient) products, if they 

replaced existing systems in each housing unit. 

7.3.2 Household Sample

DOE’s calculation of the annual energy use of residential furnaces relied on data from the 

RECS 200517. RECS collects energy-related data for occupied primary housing units in the 

United States. The RECS 2005 included data from 4,381 housing units that represent almost 

111.1 million households.

The subset of RECS 2005 records used to study furnaces met all of the following criteria:

• used a furnace as the main or secondary source of heat;

• used a heating fuel that is natural gas, liquefied petroleum gas (LPG), or fuel oil;

• heated only one housing unit; and

• had an energy consumption greater than zero.

DOE divided the furnace subset into three further subsets designed to include households 

that use one of the three furnace product classes (Table 7.3.1). Appendix 7-D presents the 

variables included and their definitions.
7-44

Table 7.3.1 Selection of RECS 2005 Records for Furnaces

Product Class Algorithm Region No. of 

Records

RECS 

2005

DOE 2016

Number 

of Houses 

million

Number of 

Furnaces 

million

Non-Weatherized 

Gas Furnace

Central heating equipment = furnace

Heating fuel = gas

Home type = single or multi-family

Number of Housing Units Heated = 1

National 1726 45.5 45.2

North 990 25.9 26.9

South 736 19.6 18.3

Manufactured 

Home Gas Furnace

Central heating equipment = furnace

Heating fuel = gas

Home type = manufactured home

Number of Housing Units Heated = 1

National 109 2.5 2.5

North 58 1.2 1.2

South 51 1.2 1.3

Oil-Fired Furnace Central heating equipment = furnace

Heating fuel = fuel oil

Home type = manufactured home

Number of Housing Units Heated = 1

National 150 2.9 3.0

DOE made some adjustments to EIA’s weightings for each RECS 2005 household, in 

order to create a furnace population weight for 2016. The RECS 2005 weighting indicates how 

commonly each household configuration occurs in the general population in 2005. The first 

adjustment was to compensate for the fact that the RECS 2005 sample does not distinguish 

between weatherized and non-weatherized gas furnaces. Therefore, to account for nonweatherized gas furnaces, DOE assumed that a fraction of the households in the south with both 

a central air conditioner and gas furnace were using weatherized furnaces. Based on AHRI 

shipment data for weatherized and non-weatherized furnaces (which shows that about 10 percent 

of total furnace shipments are weatherized furnaces), DOE multiplied the RECS 2005 weight for 

households in the south region with both a central air conditioner and gas furnace by 0.80. 

DOE also took into account the growth in population by region from 2005 to 2016 based 

on U.S. census population projections. For all product classes, the number of houses in the north 

was multiplied by a factor of 0.96 and the number of houses in the south by a factor of 1.04. 

Finally, DOE adjusted the weightings to account for households with multiple furnaces. 

According to the 2008 American Comfort Survey, 7 percent of households in the United States 

have multiple gas furnaces.18 For simplicity DOE assumed that these households had two 

furnaces. Therefore, for 7 percent of the households, the weighting was doubled, so it could be 

representative of the furnace weight. DOE believes that the household records, along with their 

adjusted weightings, are representative of housing nationwide in 2016 (see appendix 7-D for 

details).
7-45

7.3.3 Annual Heating Load Calculation 

The annual house-heating load (HHL) is the total amount of heat output from the furnace 

that the house needs during the heating season. This includes heat from the burner and heat from

the blower and the blower motor.

The Department determined HHL for each sampled housing unit, based on the burner 

operating hours (BOH) and the characteristics of the assigned existing furnace, using the 

following calculations:

Adj Factor t t HHL QYR RECS AFUEex BE BOHex N _ 36003.412 , ×





















 



















 − = × + × × + ×

+ −

Eq. 7.3.1

Where:

QYR,RECS = annual fuel consumption for heating based on RECS 2005 (kBtu/yr),

AFUEex = AFUE of the existing furnace (see section 7.3.5.4),

3.412 = constant to convert kW to kBtu/hr,

BEex = power consumption of the blower motor of the existing furnace (kW),

BOHex = as defined below (hr/yr),

N = number of cycles per hour (set equal to 5 for furnaces),

HLH = heating load hours (hr) (see appendix 7-E for the derivation), 

t

+ = off delay (seconds),

t

- = on delay (seconds), and

Adj_Factor = adjustment factor.

Burner operating hours (BOHex), the number of hours the existing furnace burner is on 

during a year, is a key variable in the calculation of HHL. The Department calculated BOH for 

the existing furnace as:

IN ex

YR RECS

ex Q

Q BOH

,

, = Eq. 7.3.2

Where:

BOHex = burner operating hours of existing household (hr/yr),

QYR,RECS = as defined above (kBtu/yr),

QIN,ex = input capacity of the existing furnace (see section 7.3.5.1) (kBtu/hr).

The power consumption of the blower motor depends on the steady-state operating 

conditions (the pressure and airflow) for the furnace. This calculation is explained in appendix 7-

F. 
7-46

The Department made adjustments to reflect the expectation that newly built housing 

units in 2016 will have a somewhat different heating load than the housing units in the RECS 

2005 sub-sample. The adjustment involves multiplying the calculated HHL for each RECS 2005 

housing unit by a building shell efficiency index derived from the NEMS simulation performed 

for EIA’s AEO 2010.

19 The building shell efficiency index sets the heating load value at 1.00 for 

an average home in 2005 (by type) in each census division. The values listed represent the 

change in heating load based on the difference in physical size and shell attributes for homes in 

the future (which takes into account physical size difference and efficiency gains from better 

insulation and windows). This factor differs for new construction and replacement households. 

The value for households in 2016 is 0.87 for replacements and 0.77 for new construction, which 

means that the average new home in 2016 will require less heat energy to maintain indoor 

comfort. To add variability, the factor is varied by plus or minus 15 percent. 

DOE also made adjustments to the HHL calculated using RECS 2005 data to reflect 

historical average climate conditions. Table 7.3.2 shows the 1895 to 2009 average heating degree 

days (HDD) as well as the 2005 average HDD for the nine census divisions. The adjustment 

factors are calculated using the equation below and are almost all positive, which means that 

2005 had warmer temperatures compared to the 115-year average.

_ _ 2005

115 _ _ _ _ lim

res stock

yr avg

average c ate HDD

HDD

Adj Factor = Eq. 7.3.3

Where:

HDDres_stock_2005 = HDD in 2005 for the specific census division or state where the 

housing unit is located, and

HDD115_yr_avg = 115-year average HDD (1895–2009) for the specific census 

division where the housing unit is located.

Table 7.3.2 Heating Degree Day Adjustment Factors

Census Division Average HDD Adjustment Factor

1895-2009 2005

1 New England 6,559 6,567 1.00

2 Middle Atlantic 5,822 5,752 1.01

3 East North Central 6,307 6,102 1.03

4 West North Central 6,582 5,988 1.10

5 South Atlantic 2,756 2,757 1.00

6 East South Central 3,418 3,303 1.03

7 West South Central 2,175 1,928 1.13

8 Mountain 5,105 4,742 1.08

9 Pacific 3,217 3,031 1.06

Nation 4,416 4,246 1.04

For households in which it is clear that the fuel use for heating is associated solely with 

the use of furnace equipment as the primary or secondary heating equipment, DOE used the 
7-47

annual fuel consumption for heating the housing unit from RECS 2005. DOE adjusted the house 

heating load for households that used a both a furnace (either as the primary or secondary heating 

equipment) and other heating equipment using the same fuel. RECS 2005 reports the percentage 

of heating energy consumption attributable to secondary products. DOE derived the house 

heating load applicable to the furnace by subtracting the estimated amount of heat provided by 

the other heating system. In the case when a household was determined to have multiple 

furnaces, the house heating load was divided by the number of furnaces. Details are presented in 

appendix 7-F.

7.3.3.1 Overview of Heating Load Estimates

DOE calculated that the national average annual heating load to be 32.0 for nonweatherized gas furnaces, 27.7 for manufactured home gas furnaces, and 60.7 for oil-fired 

furnaces. The variations between product types primarily reflect differences in the distribution of 

furnaces. These results are smaller than previous studies, primarily due to improvements in 

building shell efficiency and heating equipment efficiency. Table 7.3.3 shows the range in 

heating load among sample households. 

Table 7.3.3 Range of Annual Heating Load for Each Furnace Product Class by Region

Region Min Max Average

Percentiles

5% 25% 50% 75% 95%

Non-Weatherized Gas Furnaces

National 0.3 190.5 32.0 5.7 16.3 28.7 43.0 69.8

North 1.5 190.5 40.5 14.9 26.9 37.1 50.2 76.3

South 0.3 133.2 19.1 3.6 9.0 15.5 25.1 46.5

Manufactured Home Gas Furnaces

National 3.5 104.7 27.7 7.2 17.5 23.7 36.1 57.5

North 3.8 104.7 34.1 13.9 22.0 32.1 42.6 68.4

South 3.5 76.1 21.7 6.1 12.4 20.2 26.4 45.8

Oil-fired Furnaces

National 0.0 220.9 60.7 27.7 41.2 60.3 76.2 99.9

7.3.4 Annual Energy Consumption

Once the heating load of each sample housing unit is known, it is possible to estimate what the 

energy consumption would be if more efficient equipment, rather than the baseline equipment, 

were used in each housing unit.

7.3.4.1 Fuel Consumption 

The Department calculated the fuel consumption (FuelUse) for each furnace using the 

following formulas from the current American Society of Heating, Refrigerating and AirConditioning Engineers (ASHRAE) test procedure SPC 103-2007 section C:
7-48

FuelUse = BOHSS × QIN ,

e,f

for single-stage furnace Eq. 7.3.4

Where:

BOHSS = steady-state burner operating hours (hr), and

QIN = input capacity of existing furnace (kBtu/hr).

The details for calculating energy consumption appear in appendix 7-F.

7.3.4.2 Electricity Consumption 

The Department calculated furnace electricity consumption for the blower, the draft 

inducer, and the ignitor.g The blower moves heated air through the house whenever the furnace 

burner is on (adjusted for delay times between burner and blower operation). It also operates in 

the cooling season (summer) if the house is air conditioned, but the Department only considered 

use during the heating season. DOE also took into account the electricity consumption of such 

auxiliary equipment as condensate pumps and heat tape, which are sometimes installed with 

higher efficiency equipment. The Department calculated the electricity consumption as:

( )

( BOH ) StbyE BOH CPE OH HTE

BOH y BE y PE y PE

ElecUse

SS SS HT

SS p ig ig

− × + × + ×

× × + × + × +

=

8760

,

h

Eq. 7.3.5

for single-stage furnace,

Where:

BOHSS = as defined above,

y = ratio of blower on-time to burner on-time,

BE = power consumption of the blower motor (kW),

yP = ratio of induced-draft blower on-time to burner on-time,

PE = power consumption of the draft-inducer blower-motor (kW),

yIG = ratio of ignitor on-time to burner on-time,

PEIG = power consumption of the ignitor (kW),

StbyE = power consumption during standby (kW),

CPE = power consumption of condensate pump (kW),

OHHT = operating hours of heat tape (hours), and

HTE = power consumption of heat tape (kW).

 e For natural draft equipment this formula is modified to include the pilot light consumption.

f For modulating equipment this formula includes parameters for the operation at full, modulating, and reduced load. g The DOE and ASHRAE test procedures do not count the electricity used by controls when the furnace is not firing.

h For modulating equipment this formula includes parameters for the operation at full, modulating, and reduced load. 

See appendix 7-G.
7-49

The ratio of blower on-time to burner on-time and the ratio of induced draft blower ontime to burner on-time are from the current ASHRAE test procedure SPC 103-200720 using 

delay times (pre-purge, post-purge, on-delay, and off-delay) derived from DOE’s 2007 Furnace 

and Boiler Final Rule.

21 The ratio of ignitor on-time to burner on-time comes from the DOE test 

procedure and the ignition time derived from the 2007 final rule. The delay times are defined as 

follows: pre-purge and post-purge times are the lengths of time the draft inducer operates before 

and after a firing cycle. On-delay is the amount of time the blower waits to begin operating after 

the burner starts firing. Off-delay is the time the blower keeps operating after the burner turns 

off. Ignition time is the length of time the hot surface ignitor is on before gas is sent to the 

burner. The values for the delay and ignition times are shown in Table 7.3.4.

Table 7.3.4 Values for Delay and Ignition Times 

Pre-Purge Post-Purge On-Delay Off-Delay Ignition

15 seconds 5 seconds 30 seconds 120 seconds 37 seconds

A common value for the power consumption of the draft inducer, PE, for basic noncondensing model furnaces is 75 W, and the average value is about 75 W, so DOE selected 75 W 

for all the non-condensing models. The Department found no correlation between the PE and 

input capacity or between PE and airflow capacity. For condensing furnaces, the Department 

used a PE of 90 W, which closely matches the mean for that group. Details on the derivation of 

these values can be found in appendix 7-H.

The standby power consumption (StbyE) values are dependent on the furnace motor 

blower type. DOE considered two motor types: PSC and ECM. Table 7.3.5 shows the fractions 

of installations with different motor types that DOE used based on a 2004 Canadian study of 

furnace fan market in Vancouver for non-weatherized gas furnaces.22 Overall ECM furnace fans 

would represent 29 percent of the market by 2016. For manufactured home gas furnaces, oilfired furnaces, and electric furnaces, DOE assumed that ECM furnace fans would represent 10 

percent of the market in 2016. DOE believes that the furnace fan market in this study is a good 

proxy for the 2016 U.S. non-weatherized gas furnace market, based on the growing market share 

of ECM furnace fan motors. Table 7.3.6 summarizes the power consumption at each standby 

efficiency level. For the furnace energy use calculations only the baseline standby efficiency 

values are used. See appendix 7-G for more details.
7-50

Table 7.3.5 Fraction of Non-Weatherized Gas Furnace Fan Motors and Controls 

Shipments by Furnace Efficiency and Construction Type in 2016

Furnace Technology and Efficiency

AFUE

PSC ECM

Single-Stage Two-Stage Single-Stage Two-Stage

Replacement Market

Non-Condensing (80% AFUE) 50% 40% 0% 10%

Condensing (90%+ AFUE) 40% 10% 0% 50%

New Construction Market

Non-Condensing (80% AFUE) 85% 10% 0% 5%

Condensing (90%+ AFUE) 70% 5% 0% 25%

Table 7.3.6 Standby Power Consumption by Efficiency Level and Furnace Type

Product Class Energy Efficiency 

Level

PSC

Watts

ECM

Watts

Non-Weatherized 

Gas Furnaces

0 (baseline) 8 11

1 8 9.8 

2 8 9 

Manufactured Home 

Gas Furnaces

0 (baseline) 8 11

1 8 9.8 

2 8 9 

Oil-Fired Furnaces

0 (baseline) 9 12

1 9 10.8 

2 9 10 

Electric Furnaces

0 (baseline) 8 11

1 8 9.8 

2 8 9 

Some higher efficiency installations require the use of auxiliary equipment such as 

condensate pumps and heat tape. The electricity consumption of this equipment is calculated by 

DOE and added to the total electricity consumption. If a household required a condensate pump, 

DOE assumed that it consumed 60 watts and operated at the same time as the burner. If a 

household required heat tape to prevent the condensate pipe from freezing, DOE assumed that it 

consumed 3 watts per square foot (on average 45 watts total) and operated only when the average 

monthly outside temperature dropped below 45 °F. Details of how DOE determined whether a 

household required a condensate pump or heat tape can be found in chapter 8.

Details for the calculation of the blower motor energy consumption can be found in 

appendix 7-F.

The details for calculating electricity consumption appear in appendix 7-G.

7.3.5 Assigning Furnace Equipment Characteristics to Sampled Households

To estimate the heating load of each sample housing unit, DOE represented the existing 

furnace by assigning an input capacity, airflow capacity, and AFUE to the furnace in the RECS 

sample housing units. 
7-51

7.3.5.1 Input Capacity of Existing and New Equipment

The Department assigned an input capacity for the existing furnace of each housing unit 

based on an algorithm that correlates the housing unit size and outdoor design temperature with 

the distribution of input capacity of furnaces. DOE assumed that, for the new furnace 

installation, the input capacity would remain the same. For manufactured home and oil-fired 

furnaces, DOE used a single fixed input capacity value of 80 kBtu/h and 105 kBtu/h, 

respectively. The following steps describe the assignment process for non-weatherized gas 

furnaces:

1) The Department ranked all the RECS housing units in ascending order by size (heating 

square foot) multiplied by a scaling factor to account for the outdoor design temperature 

(see equation 7.3.6) and calculated the percentile rank of each housing unit using the 

statistical weight of each of the sample records.

2) The Department constructed percentile tables by input capacity of furnaces based on the 

historical shipment information and number of models in AHRI Directory (see Table 

7.3.7).

3) After selecting a housing unit from the RECS database during each Monte Carlo 

iteration, DOE noted the size of the selected housing unit and determined the percentile 

rank from Step 1.

4) To avoid a one-to-one deterministic relation between the housing unit size and input 

capacity, DOE added a random term to the percentile identified in Step 3 so that the 

correlation was not perfect. The Department used a normal distribution to characterize 

the random term. The random term has a mean of zero and a standard deviation of 8 

percent.

5) Using the percentile from Step 4, DOE looked up the input capacity from the input 

capacity percentile table in Step 2. 

DOE used ASHRAE design data to develop estimates of the average 1 percent design dry 

bulb temperature for each household (see appendix 7-E for more details). Using this data, DOE 

then developed a scaling factor to be applied to the home heating square footage and equal to: 

SFdesign,h = (65- Tdesign, h) / (65 - 42) Eq. 7.3.6

Where: 

SFdesign,h = heating design scaling factor, and

Tdesign, h = average 1 percent ASHRAE design dry bulb temperature (°F) for heating.

It is noted that the design scaling factor is used as a proxy to represent lower heating 

loads for the same household area in cooler climates and supports the allocation of the sizes 

across observations, but that the total relative allocation of sizes is unaffected. The end result was 

a distribution of sizes assigned to the weighted RECS samples that matches the distribution of 

sizes for shipments of residential furnaces by input capacity. Table 7.3.7 shows the distribution 
7-52

of input capacities for the most commonly available input capacity bins based on the June 2010 

AHRI Residential Furnace Directory and AHRI shipment data.

23

Table 7.3.7 Distribution of Input Capacity for Non-Weatherized Gas Furnaces

Input Capacity 

kBtu/h

AHRI 2001 

Shipments

%

2010 AHRI 

Directory 

Fraction of 

Models

%

Shipment 

Weighted 

Fraction of 

Models

%

Cumulative 

Fraction of 

Models

%

45 9.4 10.2 6.8 6.8

50 3.8 2.6 9.4

60 8.6 16.5 8.6 18.0

70 24.8 1.7 5.0 23.0

75 6.6 19.8 42.8

80 13.7 17.2 13.7 56.4

90 23.2 4.6 4.8 61.3

100 17.4 18.4 79.6

110

20.4

5.3 4.9 84.5

120 6.2 5.7 90.2

125 7.7 7.1 97.4

140 2.8 2.6 100.0

7.3.5.2 Airflow Size of Existing Equipment

The Department classified furnaces by nominal maximum airflow in cfm at 0.5 in. w.g. 

of external static pressure. The Department assigned the airflow capacity of existing furnaces for 

housing units that had air conditioners in a manner similar to how it assigned furnace input 

capacity. Larger air conditioners go to larger housing units, according to the distribution of sizes 

of air conditioners sold the year the air conditioner was installed in that housing unit. The 

Department used the air conditioner nominal size of two, three, four, or five tons to set the 

airflow capacity with a ratio of 400 cfm per ton of cooling. The steps were:

1) The Department ranked all the RECS housing units in ascending order by size (cooling 

square foot) multiplied by a scaling factor to account for the outdoor design temperature 

(see equation 7.3.7) and calculated the percentile rank of each housing unit using the 

statistical weight of each of the sample records.

2) Based on historical shipment information of residential central air conditioners by 

capacity, DOE constructed the airflow capacity percentiles table for air conditioners. (See 

Table 7.3.8). The Department restricted the airflow sizes to two, three, four, or five 

tons—the equivalent of 800, 1,200, 1,600, or 2,000 cfm at 0.5 in. w.g. static pressure. 

Since there are no available shipment data on the airflow capacity of furnaces, the 

Department used the airflow capacity of residential central air conditioners as a proxy.

3) After selecting a housing unit from the RECS database during each Monte Carlo 

iteration, DOE noted the size of the selected housing unit and determined the percentile 

rank from Step 1.
7-53

4) To avoid a one-to-one deterministic relation between the housing unit size and input 

capacity, DOE added a random term to the percentile identified in Step 3 so that the 

correlation was not perfect. The Department used a normal distribution to characterize 

the random term. The random term has a mean of zero and a standard deviation of 8 

percent.

5) Using the percentile from Step 4, DOE looked up the airflow from the airflow percentile 

table in Step 2. The Department selected an input capacity and airflow combination with 

the identified airflow capacity, based on commonly available models (see Table 7.3.9). If 

no input capacity and airflow combination with the identified airflow capacity was 

available, the Department selected the input capacity and airflow combination with the 

same input capacity and the closest airflow capacity as a substitute.

DOE used ASHRAE design data to develop estimates of the average 1 percent design dry 

bulb temperature for each household (see appendix 7-E for more details). Using these data, DOE 

then developed a scaling factor to be applied to the home cooling square footage and equal to: 

SFdesign,c = (Tdesign, c – 65) / (95 - 65) Eq. 7.3.7

Where: 

SFdesign,c = cooling design scaling factor, and

Tdesign, c = average 1 percent ASHRAE design dry bulb temperature (°F) for cooling.

It is noted that the design scaling factor is used as a proxy to represent lower cooling

loads for the same household area in warmer climates and supports the allocation of the sizes 

across observations, but that the total relative allocation of sizes is unaffected. This end result 

was a distribution of sizes assigned to the weighted RECS samples that matches the distribution 

of sizes for shipments of residential furnaces. Table 7.3.8 shows the distribution of input 

capacities for the representative product classes listed above, based on AHRI shipment data.

24

Table 7.3.8 Distribution of Airflow for Furnaces

Airflow Rating 

cfm

2010 AHRI 

Shipments

%

Cumulative Fraction

%

800 37.3 37.3

1200 35.0 72.3

1600 16.8 89.0

2000 11.0 100.0

For non-weatherized gas furnaces, DOE selected 25 combinations (“bins”) of input 

capacity and maximum airflow. The marked cells in Table 7.3.9 reflect the input capacity and 

nominal maximum airflow for the most common input and nominal maximum airflow capacities 

of models in the June 2010 AHRI Directory.

25 Most basic models on the market fit into the 25 

bins of input capacity and airflow capacity. Some models do not exactly match the bins, but their 

values are close enough that DOE included them in one of the 25 bins. For example, 40 kBtu/h 
7-54

and 45 kBtu/h models are grouped together into a single 45 kBtu/h bin. Most bins have at least 

two actual models.

Table 7.3.9 Common Furnace Input Capacity and Airflow combinations

Airflow Sizing in cfm 

tons

Input Capacity 

kBtu/h

45 50 60 70 75 80 90 100 115 120 125 140

800 cfm (2 tons) x x x

1,200 cfm (3 tons) x x x x x x x x

1,600 cfm (4 tons) x x x x x x x x

2,000 cfm (5 tons) x x x x x x

7.3.5.3 AFUE of Existing Equipment

The Department assigned the AFUE of existing furnaces based on the equipment age of 

the existing furnace as given by RECS and historical shipments by efficiency. The following 

steps describe this process:

1) After DOE selected a housing unit from the RECS database during each Monte Carlo 

iteration, the Department randomly assigned a percentile value and extracted the furnace 

age information from RECS (see Table 7.3.10). Using the extracted furnace age, DOE 

assigned an installation year from the installation year range for the applicable RECS 

equipment age bin.

2) Based on the historical furnace shipment information sorted by AFUE, DOE constructed 

percentile tables by AFUE shipments of furnaces for 2005 and prior years (see Table 

7.3.11 to Table 7.3.13). AHRI shipments data for non-weatherized gas furnaces indicate 

that housing units in the northern region receive more efficient furnaces. Therefore, DOE 

developed two historical AFUE shipment distributions—one for the northern region and 

one for the southern region—for non-weatherized gas furnaces.

3) DOE determined the AFUE by looking it up from the AFUE percentile table from Step 

(2) corresponding to the age of the existing equipment in the housing unit and whether 

the housing unit was located in the northern or southern regions.

Table 7.3.10 Number of Observations for Each Age Group

RECS Bin 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

Installation Years 2004-2005 2001-2005 1996-2000 1986-1995 1966-1985

Equipment Type

Non-Weatherized 

Gas Furnaces

206 229 367 477 302 1,726

13.2% 13.3% 21.3% 27.0% 17.8% 100.0%

Manufactured Home 

Gas Furnaces

11 14 25 25 27 109

8.5% 12.5% 24.4% 23.5% 23.3% 100.0%

Oil-Fired Furnaces 10 21 29 47 39 150

9.0% 14.1% 14.5% 31.7% 29.7% 100.0%
7-55

Table 7.3.11 Historical Fraction of Regional Gas Furnace Shipments by AFUE Bins

Year North Region South Region

>78 AFUE 78 to <90 >90 AFUE >78 AFUE 78 to <90 >90 AFUE

2005 0.0% 48.8% 51.2% 0.0% 81.6% 18.4%

2004 0.0% 52.2% 47.8% 0.0% 83.6% 16.4%

2003 0.0% 53.7% 46.3% 0.0% 83.6% 16.4%

2002 0.0% 59.0% 41.0% 0.0% 85.2% 14.8%

2001 0.0% 57.7% 42.3% 0.0% 86.0% 14.0%

2000 0.0% 64.6% 35.4% 0.0% 89.6% 10.4%

1999 0.0% 64.9% 35.1% 0.0% 89.5% 10.5%

1998 0.0% 64.6% 35.4% 0.0% 89.8% 10.2%

1997 0.0% 62.9% 37.1% 0.0% 87.8% 12.2%

1996 0.0% 64.8% 35.2% 0.0% 89.8% 10.2%

1995 0.0% 68.3% 31.7% 0.0% 88.9% 11.1%

1994 0.0% 66.6% 33.4% 0.0% 87.6% 12.4%

1993 0.0% 70.2% 27.4% 0.0% 86.8% 10.2%

1992 2.4% 59.3% 34.0% 3.0% 80.2% 10.7%

1991 6.7% 23.9% 29.7% 9.1% 30.9% 9.3%

1990 46.3% 22.3% 25.3% 59.8% 27.4% 7.9%

1989 52.4% 17.4% 24.3% 64.6% 21.2% 7.6%

1988 58.3% 19.6% 25.7% 71.2% 24.2% 8.1%

1987 54.8% 18.3% 23.7% 67.8% 22.2% 7.4%

1986 58.0% 18.7% 10.2% 70.4% 20.1% 3.2%

1985 71.1% 17.3% 16.2% 76.7% 19.6% 5.1%

1984 66.5% 18.2% 17.8% 75.3% 20.9% 5.6%

1983 64.0% 7.8% 22.9% 73.5% 9.4% 7.2%

1982 69.3% 8.2% 19.2% 83.4% 9.6% 6.0%

1981 72.6% 8.6% 15.6% 84.4% 9.7% 4.9%

1980 75.9% 9.0% 11.9% 85.4% 9.8% 3.7%

1979 79.1% 3.9% 5.9% 86.5% 4.1% 1.9%

1978 90.2% 1.4% 0.0% 94.1% 1.4% 0.0%

1977 98.6% 0.9% 0.0% 98.6% 0.9% 0.0%

1976 99.1% 0.5% 0.0% 99.1% 0.5% 0.0%

1975 99.5% 0.0% 0.0% 99.5% 0.0% 0.0%

1966 to 1974 100.0% 0.0% 0.0% 100.0% 0.0% 0.0%
7-56

Table 7.3.12 Historical Fraction of Manufactured Home Gas Furnace Shipments by AFUE 

Bins

Year >78 AFUE 78 to <90 

AFUE

>90 AFUE

2005 15.0% 80.0% 5.0%

2004 15.0% 80.0% 5.0%

2003 15.0% 80.0% 5.0%

2002 15.0% 80.0% 5.0%

2001 15.0% 80.0% 5.0%

2000 15.0% 80.0% 5.0%

1999 15.0% 80.0% 5.0%

1998 15.0% 80.0% 5.0%

1997 7.2% 92.8% 0.0%

1996 7.2% 92.8% 0.0%

1995 7.2% 92.8% 0.0%

1994 7.2% 92.8% 0.0%

1993 7.2% 92.8% 0.0%

1992 7.2% 92.8% 0.0%

1991 65.9% 34.1% 0.0%

1990 70.1% 29.9% 0.0%

1989 75.7% 24.3% 0.0%

1988 72.3% 27.7% 0.0%

1987 74.8% 25.2% 0.0%

1986 77.9% 22.1% 0.0%

1985 78.4% 21.6% 0.0%

1984 77.0% 23.0% 0.0%

1983 89.3% 10.7% 0.0%

1982 89.2% 10.8% 0.0%

1981 89.2% 10.8% 0.0%

1980 89.1% 10.9% 0.0%

1979 94.1% 5.9% 0.0%

1978 98.6% 1.4% 0.0%

1977 99.1% 0.9% 0.0%

1976 99.5% 0.5% 0.0%

1966 to 1975 100.0% 0.0% 0.0%

Table 7.3.13 Historical Fraction of Oil-Fired Furnace Shipments by AFUE Bins

Year >78 AFUE 78 to <90 

AFUE

>90 AFUE

1992-2005 0.0% 100.0% 0.0%

1991 4.0% 96.0% 0.0%

1990 4.0% 96.0% 0.0%

1989 61.0% 39.0% 0.0%

1988 70.0% 30.0% 0.0%

1987 77.5% 22.5% 0.0%

1966-1986 85.0% 15.0% 0.0%
7-57

7.3.6 Furnace Energy Consumption Results

This section presents the average annual energy use and the average energy savings for 

each considered energy efficiency level compared to the baseline energy efficiency for each

furnace product class. For its LCC and PBP analyses, DOE used the full distribution of energy 

use values calculated for the sample households.

Table 7.3.14 lists the average annual energy use for non-weatherized gas furnaces and the 

average energy savings for each considered energy efficiency level compared to the baseline for 

the nation and the northern and southern regions.

Table 7.3.14 Annual Energy Consumption for Non-Weatherized Gas Furnaces

Energy

Efficiency Level

AFUE

Average Energy Consumption Average Energy 

Savings (Gas)

MMBtu/yr

Gas

MMBtu/yr

Electricity

kWh/yr

National

80 (baseline) 37.8 312 -

90 33.7 289 4.1 

92 33.0 283 4.8 

95 32.0 275 5.8 

98 30.7 363 7.1 

North

80 (baseline) 47.4 369 -

90 42.2 342 5.2 

92 41.3 335 6.1 

95 40.1 325 7.3 

98 38.4 438 8.9 

South

80 (baseline) 23.5 228 -

90 20.9 211 2.5 

92 20.5 206 3.0 

95 19.9 200 3.6 

98 19.1 251 4.4 

Table 7.3.15 lists average annual energy use for manufactured home gas furnaces and 

average energy savings for each energy efficiency level evaluated in the LCC analysis, compared 

to the baseline furnace.
7-58

Table 7.3.15 Annual Energy Consumption for Manufactured Home Gas Furnaces

Energy

Efficiency Level

AFUE

Average Energy Consumption Average Energy 

Savings (Gas)

MMBtu/yr

Gas

MMBtu/yr

Electricity

kWh/yr

National

80 (baseline) 43.7 282 -

90 39.0 257 4.7 

92 38.1 252 5.6 

96 36.6 241 7.1 

North

80 (baseline) 53.4 344 -

90 47.6 314 5.8 

92 46.6 307 6.8 

96 44.7 295 8.7 

South

80 (baseline) 34.4 223 -

90 30.7 203 3.7 

92 30.0 199 4.4 

96 28.8 191 5.6 

Table 7.3.16 shows the average annual energy use for oil-fired furnaces and the average 

energy savings for each energy efficiency level, compared to the baseline.

Table 7.3.16 Annual Energy Consumption for Oil-Fired Furnaces 

Energy

Efficiency Level

AFUE

Average Energy Consumption Average Energy 

Savings (Oil)

MMBtu/yr

Oil

MMBtu/y)

Electricity

kWh/yr

National

82 (baseline) 67.3 483 -

83 66.5 477 0.8 

84 65.7 472 1.6 

85 64.9 466 2.3 

97 57.1 410 10.1 

7.3.7 Standby Energy Consumption Results for Furnaces

Table 7.3.17 shows the average annual standby energy use for furnaces and the average 

energy savings for each energy efficiency level, compared to the baseline.
7-59

Table 7.3.17 Annual Standby Energy Consumption for Furnaces

Energy

Efficiency Level

Average Energy 

Consumption

Electricity 

kWh/yr

Average Savings

kWh/yr

Non-Weatherized Gas Furnaces

0 (baseline) 73.6 -

1 70.9 2.7 

2 69.1 4.5 

Manufactured Home Gas Furnaces

0 (baseline) 69.2 -

1 68.2 0.9 

2 67.6 1.6 

Oil-fired Furnaces

0 (baseline) 75.5 -

1 74.6 0.9 

2 73.9 1.5 

Electric Furnaces

0 (baseline) 79.4 -

1 78.5 1.0 

2 77.8 1.6 
7-60

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