7

- F

- i APPENDIX 7

- F. DETERMINATION OF CE N TRAL AIR CONDITIONER ENERGY

USE IN THE LCC ANALY SIS

TABLE OF CO NTENTS

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 (SEER

ex )

................................ ...... 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 Condit ioner

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

- 87

- F

- 1 APPENDIX 7

- F. DETERMINATION OF CENTRAL AIR CONDITIO NERS ENERGY

USE IN THE LCC ANALY SIS

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 ener gy using the following formula:

CoolingEnergyUs e non

− furnace

_ fan = COH × Power
non

− furnace

_ fan

Where:

C OH = as defined in section 7

- F.2.1

,

Power

non

- 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 calcula ted using the following formula:

COH = HCL
CoolingCapacity × Adj

_ Factor motor

W here:

COH = cooling operating hours, hour/year,

HCL = house cooling load, MMBtu/year,

CoolingCap acity = cooling capacity of air conditioner, Btu/h (see section 7

- F.2.2.1 ), and

Adj

_ Factor motor = 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 defa ult 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

_ Factor motor = 1

( 1 + 3

. 412 × 365

1000 ∗ CFM

− FFPcooling
CoolingCapacity )

W here:

365

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

SEER, watts,

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

FF P cooli ng = furnace fan power during the cooling operation, kW, and

CoolingCap acity = cooling capacity of air conditioner, Btu/h.

The house cooling load is derived using the EIA’s RECS 2005 1 cooling energy use data for the sample households as follows:

HCL = CoolingEnergyUseRECS × SEER
ex CoolingCapacity
ex × Adj

_ Factor

CoolingEnergyUseRECS = annual electricity consumption for cooling based on RECS 2005 (kBtu /yr),

SEER

ex = 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, t he 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 develo ped 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 for7

- 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 adjustm ents to the HC L calculated using RECS 2005 data to reflect historical average climate conditions. Table 7

- F.2.1 shows the 2002

- 2011 average heating degree days (HD D) as well as the 2005 average C DD for the 29 geographical areas . The adjustment factors are calculated using the equation below

.

Where:

CDD res_stock _2005 = CDD in 2005 for the specific region where the housing unit is located, and

CDD 10

_ yr_avg = 10

- ye ar average CDD (2002

– 2011) based on NOAA data 2 for the specific region where the housing unit is located

. 2005

_ _ _

_ 10

lim

_ _ stock res avg yr

ate c average CDD CDD Factor Adj **=**7

- F

- 4 Table 7

- F.2.1 Cooling Degree Day Adjustment Factors

Geographical Areas Average C DD 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 w as 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 ass ociated 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 cond itioning 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 percenta ge of cooling energy consumption attributable to room air conditioners. DOE7

- 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 (SEER
ex )

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, SEER res_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 residenc e 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 approx imately 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

bet ween 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 coolin g SEER for each household using equipment vintage and average shipped efficiency for each vintage year. The latter was developed from AHRI data 3 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.

Powerofno n FanComponents = ( CoolingCapacity

SEER − 365

1000 ∗ 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

CoolingCap acity = cooling capacity of air conditioner, Btu/h (see Table 7

- F.2.4 )

.

7

- F.2.2.1 Cooling CFM and Cooling Capacity of 0 the 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.2.5 shows 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 2 018 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.