7-F-i

APPENDIX 7-F. DETERMINATION OF CENTRAL AIR CONDITIONER ENERGY 

USE IN THE LCC ANALYSIS 

TABLE OF CONTENTS

7-F.1 INTRODUCTION ..................................................................................................7-F-1

7-F.2 DETERMINATION OF NON-FURNACE FAN COOLING ENERGY USE......7-F-1

7-F.2.1 Determination Cooling Operating Hours................................................................7-F-1

7-F.2.1.2 Existing Space-Cooling Efficiency (SEERex)...................................... 7-F-5

7-F.2.2 Determination of Power Consumption of non-Furnace Fan Components of the 

Central Air Conditioner ..........................................................................................7-F-6

7-F.2.2.1 Cooling CFM and Cooling Capacity of the Central Air Conditioner 

in 2018 ................................................................................................. 7-F-7

7-F.2.2.2 Central Air Conditioner SEER in 2018 ............................................... 7-F-7

LIST OF TABLES

Table 7-F.2.1 Cooling Degree Day Adjustment Factors.............................................7-F-4

Table 7-F.2.2 Number of Observations for Each Age Group .....................................7-F-5

Table 7-F.2.3 Average Annual Shipped Space-Cooling Efficiency............................7-F-6

Table 7-F.2.4 Distribution of Airflow for Furnaces....................................................7-F-7

Table 7-F.2.5 Distribution of SEER in 2018 by CAC Region and CAC Type ...........7-F-8
7-F-1

APPENDIX 7-F. DETERMINATION OF CENTRAL AIR CONDITIONERS ENERGY 

USE IN THE LCC ANALYSIS

7-F.1 INTRODUCTION

DOE accounted for the fact that more efficient furnace fans will tend to contribute less 

heat and thereby require less cooling operation by the central air conditioner. Since the cooling

load of each sample housing unit is known, it is possible to estimate what the air conditioner 

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

equipment, were used in each housing unit.

7-F.2 DETERMINATION OF NON-FURNACE FAN COOLING ENERGY USE

DOE calculated the non-furnace fan cooling energy using the following formula:

CoolingEnergyUsenon−furnace_fan = COH × Powernon−furnace_fan

Where:

COH = as defined in section 7-F.2.1,

Powernon-furnace_fan = power consumption of all non-furnace fan components of the 

central air conditioner (kW).

7-F.2.1 Determination Cooling Operating Hours

The cooling operating hours are calculated using the following formula:

COH = HCL

CoolingCapacity × Adj_Factormotor

Where:

COH = cooling operating hours, hour/year, 

HCL = house cooling load, MMBtu/year,

CoolingCapacity = cooling capacity of air conditioner, Btu/h (see section 7-

F.2.2.1), and

Adj_Factormotor = adjustment factor to account for impact of motor heat on 

cooling operating hours.
7-F-2

The house cooling load (HCL) assumes that the household has a default furnace fan 

motor power output of 365 watts per 1000 CFM (used in the CAC test procedure). To properly 

account for increased or decreased cooling operating hours due to the higher or lower motor 

power output for different furnace fan efficiencies, DOE used the following equation to 

determine the adjustment factor: 

Adj_Factormotor = 1

(1 + 3.412 ×

365

1000 ∗ CFM − FFPcooling

CoolingCapacity )

Where:

365

1000 ∗ CFM = default central air conditioner blower output used for calculating

SEER, watts,

CFM = nominal cooling load CFM measured at 400 CFM per AC ton, cu. ft. per 

min,

FFPcooling = furnace fan power during the cooling operation, kW, and

CoolingCapacity = cooling capacity of air conditioner, Btu/h.

The house cooling load is derived using the EIA’s RECS 20051 cooling energy use data 

for the sample households as follows:

HCL = CoolingEnergyUseRECS × SEERex

CoolingCapacityex

× Adj_Factor

CoolingEnergyUseRECS = annual electricity consumption for cooling based on 

RECS 2005 (kBtu/yr),

SEERex = SEER of the existing central air conditioner (See Table 7-F.2.3),

Adj_Factor = adjustment factors (discussed below).

DOE made adjustments to the house cooling load to reflect the expectation that newly 

built housing units in 2018 will have a somewhat different house cooling load than the housing 

units in the RECS 2005 sub-sample. Similar to furnace fan energy use calculation above, the 

building shell efficiency index sets the cooling load value at 1.00 for an average home in 2005 

(by type) in each census division. DOE developed adjustment factors to represent the change in 

cooling 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 
7-F-3

households in 2018 is 0.94 for replacements and 1.01 for new construction. To add variability, 

the factor is varied by plus or minus 15 percent. 

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

historical average climate conditions. Table 7-F.2.1 shows the 2002-2011 average heating degree 

days (HDD) as well as the 2005 average CDD for the 29 geographical areas. The adjustment 

factors are calculated using the equation below.

Where:

CDDres_stock_2005 = CDD in 2005 for the specific region where the housing unit is 

located, and

CDD10_yr_avg = 10-year average CDD (2002–2011) based on NOAA data2 for the 

specific region where the housing unit is located. 

_ _ 2005

10 _ _ _ _ lim

res stock

yr avg

average c ate CDD

CDD

Adj Factor =
7-F-4

Table 7-F.2.1 Cooling Degree Day Adjustment Factors

Geographical Areas Average CDD Adjustment Factor

2002-2011 2005

1 CT, ME, NH, RI, VT 485 562 0.86

2 MA 522 576 0.91

3 NY 737 943 0.78

4 NJ 932 1121 0.83

5 PA 765 901 0.85

6 IL 924 1151 0.80

7 IN, OH 879 1027 0.86

8 MI 622 828 0.75

9 WI 552 747 0.74

10 IA, MN, ND, SD 637 792 0.81

11 KS, NE 1327 1491 0.89

12 MO 1325 1534 0.86

13 VA 1206 1250 0.97

14 DE, DC, MD, WV 1004 1034 0.97

15 GA 1832 1804 1.02

16 NC, SC 1654 1644 1.01

17 FL 3558 3436 1.04

18 AL, KY, MS 1813 1832 0.99

19 TN 1517 1576 0.96

20 AR, LA, OK 2266 2392 0.95

21 TX 2841 2908 0.98

22 CO 352 345 1.02

23 ID, MT, UT, WY 575 533 1.08

24 AZ 3171 3130 1.01

25 NV, NM 1753 1740 1.01

26 CA 923 837 1.10

27 OR, WA 235 227 1.04

28 AK NA NA 1.04

29 HI NA NA 1.10

Note: Data for Alaska and Hawaii was not available. The region 27 adjustment factor was used for Alaska, while 

region 26 adjustment factor was used for Hawaii.

DOE is calculating multi-stage cooling the same way as single-stage equipment (i.e., at the 

highest cooling mode only) and therefore used the same number of operating hours, since:

1) Multi-stage heating is not necessarily associated with multi-stage cooling equipment (e.g. 

multi-stage cooling is much less common than multi-stage furnace equipment); and

2) SEER already captures cases when multi-stage heating and cooling equipment are 

matched.

For households in which it is clear that the electricity use for cooling is associated solely 

with the use of central air conditioning equipment, DOE used the annual electricity consumption 

for cooling the household from RECS 2005. DOE adjusted the house cooling load for 

households that used both a central air conditioner and a room air conditioner. RECS 2005 

reports the percentage of cooling energy consumption attributable to room air conditioners. DOE 
7-F-5

derived the house cooling load applicable to the central air conditioner by subtracting the 

estimated amount of cooling provided by the other cooling system.

7-F.2.1.2 Existing Space-Cooling Efficiency (SEERex)

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

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

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

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

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

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

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 the table below

Table 7-F.2.2 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%

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 

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 the table below.

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 data3 and 

is shown in the table below.
7-F-6

Table 7-F.2.3 Average Annual Shipped Space-Cooling Efficiency

Year Central A/C 

SEER

1976 7.15

1977 7.18

1978 7.41

1979 7.45

1980 7.51

1981 7.73

1982 8.30

1983 8.44

1984 8.70

1985 8.84

1986 8.87

1987 8.95

1988 9.11

1989 9.23

1990 9.25

1991 9.44

1992 10.43

1993 10.52

1994 10.58

1995 10.64

1996 10.63

1997 10.62

1998 10.23

1999 10.86

2000 10.95

2001 11.07

2002 11.07

2003 11.22

2004 11.32

2005 11.33

7-F.2.2 Determination of Power Consumption of non-Furnace Fan Components of the 

Central Air Conditioner

DOE determined the power consumption of all non-furnace fan components of the central 

air conditioner as follows.

PowerofnonFanComponents = (

CoolingCapacity

SEER − 3651000 ∗ CFM)

Where:

365

1000 ∗ CFM = default central air conditioner blower output, watts,
7-F-7

CFM = nominal cooling load CFM measured at 400 CFM per AC ton, cfm (see 

Table 7-F.2.4 labeled airflow rating),

SEER = SEER of central air conditioner in 2018, Btu/h/W, and

CoolingCapacity = cooling capacity of air conditioner, Btu/h (see Table 7-F.2.4).

7-F.2.2.1 Cooling CFM and Cooling Capacity of 0the Central Air Conditioner in 

2018

As described in appendix 7-E (section 7-E.6.2), DOE determined the distribution of 

airflow for furnaces based on shipments of central air conditioner equipment by cooling capacity. 

Table 7-F.2.4 shows the distribution of cooling capacity bins that match to cooling airflow based 

on 12,000 Btu/h for every 400 CFM.

Table 7-F.2.4 Distribution of Airflow for Furnaces

Airflow Rating 

cfm

Cooling Capacity

btu/h

2007-2011 AHRI 

Shipments

%

Cumulative Fraction

%

600 18,000 9.5 9.5

800 24,000 19.6 29.1

1000 30,000 16.5 45.6

1200 36,000 22.5 68.0

1400 42,000 8.7 76.8

1600 48,000 12.5 89.2

2000 60,000 10.8 100.0

7-F.2.2.2 Central Air Conditioner SEER in 2018

DOE used the SEER efficiency distributions developed in the 2011 Central Air 

Conditioning, Heat Pump, and Furnace Final Rule,4 as well as central air conditioner standards 

that will take effect before 2018. Table 7-F.2.5shows the distribution of SEER used in the 

analysis. DOE assumed that all central air conditioners with SEER levels above 15 SEER are

associated with ECM furnace fan design option only. 
7-F-8

Table 7-F.2.5 Distribution of SEER in 2018 by CAC Region and CAC Type

North South

Coil Only Blower Coil Coil Only Blower Coil

SEER Frac. SEER Frac. SEER Frac. SEER Frac.

13 24.6% 13 18.5% 14 76.9% 14 57.7%

13.5 48.2% 13.5 36.2% 14.5 7.4% 14.5 5.6%

14 4.1% 14 3.1% 15 5.9% 15 4.4%

14.5 7.4% 14.5 5.6% 15.5 2.1% 15.5 1.5%

15 5.9% 15 4.4% 16 7.2% 16 5.4%

15.5 2.1% 15.5 1.5% 16.5 0.5% 16.5 0.4%

16 7.2% 16 5.4% 17 10.0%

16.5 0.5% 16.5 0.4% 18 7.0%

17 10.0% 19 3.0%

18 7.0% 20 2.0%

19 3.0% 21 2.0%

20 2.0% 22 1.0%

21 2.0%

22 1.0%
7-F-9

REFERENCES

1. U.S. Department of Energy: Energy Information Administration, Residential Energy 

Consumption Survey (RECS), 2005. (Last accessed September, 2011.) Public use data 

files. <http://www.eia.doe.gov/emeu/recs/recspubuse05/pubuse05.html>

2. National Oceanic and Atmospheric Administration, NNDC Climate Data Online, (Last 

accessed February 2009.) <www7.ncdc.noaa.gov/CDO/CDODivisionalSelect.jsp>

3. Air-Conditioning Heating and Refrigeration Institute, Air Conditioning and Refrigeration 

Institute Statistical Profile, 2008, 2008. 

4. U.S. Department of Energy - Energy Efficiency & Renewable Energy, Final Rule 

Technical Support Document: Energy Efficiency Standards for Consumer Products: 

Central Air Conditioners, Heat Pumps, and Furnaces, 2011. Washington, DC.