APPENDIX 7-C. LCC ENERGY USE CALCULATIONS

TABLE OF CONTENTS

7-C.1 INTRODUCTION ....................................................................................................... 7-C-2

7-C.2 ROOM AIR CONDITIONERS ................................................................................... 7-C-2

7-C.2.1 General Approach ...................................................................................... 7-C-2

7-C.2.2 Operating Hours......................................................................................... 7-C-3

7-C.2.2.1 Residential.................................................................................................. 7-C-3

7-C.2.2.2 Commercial................................................................................................ 7-C-7

7-C.3 CLOTHES DRYERS................................................................................................. 7-C-17

7-C.3.1 Number of Cycles .................................................................................... 7-C-18

7-C.3.2 Energy Use Calculation ........................................................................... 7-C-19

LIST OF TABLES

Table 7-C.2.1 RECS Vintage Bins for Room Air Conditioner......................................... 7-C-4 Table 7-C.2.2 Fraction of Shipments of Room Air Conditioner by Product Class .......... 7-C-6 Table 7-C.2.3 Average Room Air Conditioner EER by Product Class and Year Sold .... 7-C-7 Table 7-C.2.4 Average Room Air Conditioner EER by Product Class and Year Sold .. 7-C-12 Table 7-C.2.5 Regression Equations............................................................................... 7-C-14 Table 7-C.2.6 Building Type and Abbreviation ............................................................. 7-C-15 Table 7-C.2.7 Building Schedules and Abbreviation ..................................................... 7-C-15 Table 7-C.2.8 Room Air Conditioner Operating Hour Equations By Building Type

and Schedule ............................................................................................ 7-C-15 Table 7-C.2.9 Room Air Conditioner Operating Hour Equations By Building Type and Schedule (Desert).............................................................................. 7-C-16

Table 7-C.2.10 CBECS 2003 Building Code Match to Room Air Conditioner Equation Building Type........................................................................... 7-C-17 Table 7-C.3.1 Number of Loads Washed per Week Based on RECS Sample ............... 7-C-18 Table 7-C.3.2 RECS Sample Clothes Dryer Usage........................................................ 7-C-18 Table 7-C.3.3 RECS Sample Clothes Dryers Utilization ............................................... 7-C-19

LIST OF FIGURES

Figure 7-C.2.1 1972–2008 Average Shipment Weighted EER for Room Air

Conditioners............................................................................................... 7-C-5 Figure 7-C.2.2 ANSI/SHRAE Standard 55-2004: Thermal Environmental Conditions for Human Occupancy ............................................................................... 7-C-8 Figure 7-C.2.3 National Solar Radiation Database (NSRDB) Stations ............................. 7-C-9 Figure 7-C.2.4 Hours Above Comfort Zone in Palm Springs (1991) .............................. 7-C-11 Figure 7-C.2.5 Hours Above the Standard 55 Comfort Zone Compared to CLDD......... 7-C-12 Figure 7-C.2.6 Hours Above the Standard 55 Comfort Zone versus CLDD with Different Regions Highlighted................................................................. 7-C-13 Figure 7-C.2.7 Hours Above ANSI/ASHRAE Standard 55-2004 as a Function of Cooling Degree-Days............................................................................... 7-C-14

7-C-iAPPENDIX 7-C. LCC ENERGY USE CALCULATIONS

7-C.1 INTRODUCTION

This appendix contains the calculation methodology for calculating the energy use of room air conditioners (RAC) and clothes dryers in the life-cycle cost (LCC) analysis.

7-C.2 ROOM AIR CONDITIONERS

7-C.2.1 General Approach

DOE calculated the annual energy consumption of a room air conditioner using the following equation:

Capacity ∗ OH RAC = ENERGY IEER

Where:

RAC ENERGY = Room air conditioner annual energy consumption (kWh/year), Capacity = rated capacity in Btu/h,

OH = operating hours per year,

IEER = Integrated Energy Efficiency Ratio in Btu/h/W.

DOE used the same representative capacities for each product class (PC) as it did in the engineering analysis: 5 kBtu/h for < 6000 Btu/h product classes (PC 3 and 8), 8 and 12 kBtu/h for 8000–13,999 Btu/hr product class (PC 1) a , and 24 kBtu/h product class (PC 5). The IEER is also determined in the engineering analysis and is a new energy factor descriptor that incorporates standby power. The IEER is calculated as capacity times active mode hours (equal to 750) divided by the sum of active mode annual energy use and inactive mode annual energy use. The number of hours associated with this standby mode for room air conditioners is 5,115 hours per year. See chapter 5 for details.

For residential room air conditioners, the operating hours of the RAC are determined using the data reported by RECS 2005 on the annual energy consumption (field energy consumption) for room air conditioning, as well as assumed EER and capacity values for the existing room air conditioner. For commercial-sector room air conditioners, CBECS does not report annual energy consumption for room air conditioning, so DOE estimated the energyconsumption using variables specific to each building in the sample and data on cooling degreedays. The following section provides a detailed explanation of the methodology for estimating the number of room air conditioner operating hours for each household or commercial building in the samples.

a The fraction of 8 and 12 kBtu/h units was assumed to be equal, so each are assigned to a specific household 50 percent of the time.

7-C-27-C.2.2 Operating Hours

7-C.2.2.1 Residential

DOE calculated the annual room air conditioner operating hours for each residential sample unit using the following formula:

FEC ∗ EER RECS RECS OH = Capacity

Where:

OH = operating hours per year,

FEC RECS = field energy consumption for a room air conditioner

EER RECS = the estimated EER of the room air conditioner in the sample home, Capacity = the room air conditioner capacity in Btu/h.

DOE used the same representative capacities for each class as it did in the engineering analysis. b

To estimate the energy consumption of a single room air conditioner, referred to as

FEC RECS, DOE divided the RECS 2005 reported annual energy consumption (field energy consumption) for room air conditioning, referred to as FEC(all) RECS , by the reported number of room air conditioners. Although in reality the utilization of each of the room air conditioners in a home may vary, DOE has no way to estimate such variation. The reported RECS 2005 end-use quantities were not based on metering of individual appliances, rather, EIA used a regression technique to estimate how much of the total annual electricity consumption for each household can be attributed to each end-use category. c The reported field energy consumption refers to the consumption of all of the room air conditioners in a home. RECS also reports the number of room air conditioners in the home. Of all homes that use a room air conditioner, 35 percent have two room air conditioners and 14 percent have three or more room air conditioners.

DOE investigated whether the 2005 heating season covered by RECS reflects representative climate. DOE found that the number of cooling degree-days (CDD) in 2005 was 12 percent higher than the 30-year average (1971–2000). DOE believes, however, that this year is a reasonable proxy for climate over the forecast period beginning in 2014. The AEO2008

b In conducting the analysis of energy use by-products that would meet some future standard, DOE effectively substituted the room air conditioners in the sample residential and commercial buildings with a new product of identical product class (capacity) that the household or building owner would purchase if their room air conditioner

failed.

c The desire to use a large number of independent variables without using a large number of interaction terms and the desire to adapt the regression procedures to account for heteroscedastic error terms led to the use of a nonlinear regression technique. For more information, see: http://www.eia.doe.gov/pub/consumption/residential/append_c.pdf

7-C-3includes a forecast of CDD that shows an increasing trend from 2010 to 2020. d The climate in 2005 is close to the average in the AEO the climate forecast.

In RECS 2005, some households are identified as having purchased ENERGY STAR air conditioners in the last 4 years. For these households, DOE applied the appropriate ENERGY STAR EER. For the rest of the sample, DOE estimated the EER of the existing room air conditioner in each sample household by matching the age of the room air conditioner given by RECS with the average EER for the specific product class in the year of its vintage. In RECS, the age of a room air conditioner is given in one of the five bins shown in Table 7-C.2.1. DOE assumed a uniform distribution within each vintage bin and assigned an age to the room air conditioner in each sample household. Once the vintage year was determined, DOE assigned an EER to the unit equal to the average EER for the appropriate capacity for that year.

Table 7-C.2.1 RECS Vintage Bins for Room Air Conditioner

Bin Age of unit

1 Less than 2 years old

2 2 to 4 years old

3 5 to 9 years old

4 10 to 19 years old

5 20 years or older

To derive a time series of average EER by capacity, DOE began with data from AHAM on total shipment-weighted average EER for 1972–2008 (See Figure 7-C.2.1). AHAM also provided average EER data by product class (capacity) for 2005–2007. 1 To develop the EER values by product class (capacity) for earlier years, DOE first assumed that all of the products shipped in each product class had the minimum efficiency required by the standard in each particular year.

d http://www.eia.doe.gov/oiaf/archive/aeo08/issues.html

7-C-4EER 10 11Average Shipment Weighted

9

8

7

1990 1995 2000 2005 2010

Year

Figure 7-C.2.1	 1972–2008 Average Shipment Weighted EER for

Room Air Conditioners

DOE then estimated the shares of total shipments by product class in each year using data for 1989, 1992, and 2005–2007, and calculated a total shipment-weighted EER (See Table 7­C.2.2). DOE then calculated scalars for each year from the ratio of the actual total shipmentweighted EER to the calculated EER, and then applied the scalars to the minimum efficiency required for each product class in each year. 6

5

1970 1975 1980 1985

7-C-5Table 7-C.2.2 Fraction of Shipments of Room Air Conditioner by Product Class

Product Class 2007 2006 2005 1992 1989

1

Without reverse cycle and with
louvered sides Less than 6,000 Btu/h 32.0% 23.0% 37.0% 26.7% 27.7%

2 6,000 to 7,999 Btu/h 16.0% 19.0% 19.0% 14.4% 17.7%

3 8,000 to 13,999 Btu/h 36.0% 34.0% 30.0% 32.8% 29.7%

4 14,000 to 19,999 Btu/h 6.0% 5.5% 3.0% 13.1% 13.2%

5 20,000 Btu/h and more 2.6% 3.9% 2.0% 6.3% 7.0%

6

Without reverse cycle and without

louvered sides Less than 6,000 Btu/h

7.0% 12.0% 7.0% 7 6,000 to 7,999 Btu/h 2.1% 3.2%

8 8,000 to 13,999 Btu/h 2.1%

9 14,000 to 19,999 Btu/h

10 20,000 Btu/h and more

11 With reverse cycle and with
louvered sides Less than 20,000 Btu/h ** 1.0% 0.7% 2.1% 1.5%

12 20,000 Btu/h and more 0.1%

13 With reverse cycle and without

louvered sides Less than 14,000 Btu/h ** 0.6% 0.4% 0.5%

14 14,000 Btu/h and more

15 Casement Casement Only 0.4% 0.6% 0.4% 16 Casement Slider

Table 7-C.2.3 shows the AHAM data on total shipment-weighted average EER and the average EER estimated for the representative product classes.

7-C-6Table 7-C.2.3 Average Room Air Conditioner EER by Product Class and Year Sold

Year Shipment Weighted EER Derived Average EER*

< 6000

Btu/h 8000

– 13,999

Btu/hr (PC 3) ≥ 20,000

Btu/hr 8000

– 13,999

Btu/hr (PC 8)

2007 9.81 9.80 10.10 9.10 9.50

2006 10.02 9.80 10.40 9.20 9.50

2005 9.95 9.80 10.10 9.10 9.40

2004 9.71 9.70 9.86 8.83 9.15

2003 9.75 9.70 9.92 8.89 9.21

2002 9.75 9.70 9.92 8.88 9.21

2001 9.63 9.70 9.80 8.50 8.73

2000** 9.3 9.03 9.70 8.50 8.73

1999 9.07 8.56 9.63 8.50 8.73

1998 NA 8.56 9.63 8.50 8.73

1997 9.09 8.57 9.64 8.50 8.73

1996 9.08 8.55 9.62 8.50 8.73

1995 9.03 8.49 9.55 8.50 8.73

1994 8.97 8.42 9.47 8.50 8.73

1993 9.05 8.50 9.56 8.50 8.73

1992 8.88 8.31 9.35 8.50 8.73

1991 8.8 8.24 9.27 8.45 8.73

1990** 8.73 8.18 9.20 8.39 8.69

1989 8.48 7.95 8.95 8.15 8.45

1988 8.23 7.72 8.68 7.91 8.20

1987 8.06 7.56 8.51 7.75 8.03

1986 7.8 7.32 8.23 7.50 7.77

1985 7.7 7.22 8.13 7.40 7.67

1984 7.48 7.02 7.89 7.19 7.45

1983 7.29 6.84 7.69 7.01 7.27

1982 7.14 6.70 7.53 6.86 7.12

1981 7.06 6.62 7.45 6.79 7.04

1980 7.02 6.58 7.41 6.75 7.00

1978 6.72 6.44 7.25 6.60 6.85

1972 5.98 6.30 7.09 6.46 6.70

* Shaded area values were provided by AHAM 1

** Years in which standards became effective

7-C.2.2.2 Commercial

DOE calculated the annual operating hours for each sample commercial-sector room air conditioner by establishing a relationship between cooling degree-days and operating hours for a

7-C-7number of building type and building schedule combinations. DOE assumed that the room air conditioner is operated when the outdoor air conditions are above the comfort zone described by ANSI/ASHRAE Standard 55-2004 Thermal Environmental Conditions for Human Occupancy (see figure 7-C.2.2). 2 To estimate how often this occurs, DOE used the following general equation:

OH55 = (a * CDD) + b

Where:

OH55 = Average annual hours when the outdoor air conditions are above the ASHRAE Standard 55 comfort zone;

CDD = the number of annual cooling degree-days (65 F) for a given location;

a and b are linear fit parameters.

Figure 7-C.2.2	 ANSI/SHRAE Standard 55-2004: Thermal Environmental Conditions for Human Occupancy

ANSI/ASHRAE Standard 55 assumes that metabolic rates of 1.1 met, (engaged in near sedentary physical activity), 0.5 clo of clothing insulation, insulation levels typical of clothing worn when the outdoor environment is warm, air speeds are not greater than 0.20 m/s (40 ft/min), upper recommended humidity limit, and 0.012 humidity ratio. The range of operative temperatures presented in Figure 7-C.2.2 are for 80 percent occupant acceptability. This is based on a 10 percent dissatisfaction criteria for general (whole body) thermal comfort based on the PMV-PPD index, plus an additional 10 percent dissatisfaction that may occur on average from local (partial body) thermal discomfort. Predicted mean vote (PMV) index is an index that predicts the mean value of the votes of a large group of persons on the seven point thermal

7-C-8sensation scale. The predicted percentage of dissatisfied (PPD) index is an index that establishes a quantitative prediction of the percentage of thermally dissatisfied people determined from PMV. The room air conditioner is assumed to operate if the outdoor conditions are outside comfort zone if W (humidity ratio)>0.012 or T>Tcomf for that humidity ratio. Tcomf is given by the following equation: Tcomf =

− 117.7081 × W + 28.25491422 , where W is the humidity ratio

at the outdoor conditions for that hour.

DOE used data on cooling degree-days from the National Solar Radiation Database
(NSRDB). 3 The 1991–2005 NSRDB is an update of the 1961–1990 NSRDB. This updated NSRDB dataset is an hourly ground-based data set of solar and meteorological fields for 1454 stations, which are subdivided into three classes of stations (see figure 7-C.2.3). A total of 858 sites have a complete 15-year period of record.

Figure 7-C.2.3	 National Solar Radiation Database (NSRDB)

Stations

Stations are identified with a USAF number as follows:

• Class I Stations have a complete period of record (all hours 1991–2005) for solar and key meteorological fields and have the highest-quality solar modeled data (221 sites).

• Class II Stations have a complete period of record but significant periods of interpolated, filled, or otherwise lower-quality input data for the solar models (637 sites).

• Class III Stations have some gaps in the period of record but have at least 3 years of data that might be useful for some applications (596 sites).

7-C-9The NSRDB has complete measured hourly Dry Bulb Temperature, Dew Point Temperature, Relative Humidity, and Atmospheric Pressure for all Class I & Class II Stations. The Dry Bulb Temperature, Relative Humidity, and Atmospheric Pressure fields were used to calculate the humidity ratio for each hour. The humidity ratio was calculated using procedures from the 2005 ASHRAE Handbook-Fundamentals, Chapter 6 Psychrometrics. Under the section on Numerical Calculation of Moist Air Properties, Situation 3 describes the process to calculate humidity ratio (W) from Dry Bulb Temperature, Relative humidity, and Pressure. The saturation pressure for the dry bulb temperature is calculated using the following equation:

C 8 2 3 ln( Pws ) = + C 9 + C 10 × T + C 11 × T + C 12 × T + C 13 × ln( T ) T

where:

C8 = -5.8002206 E+03

C9 = 1.3914993 E+00

C10 = -4.8640239 E-02

C11 = 4.1764768 E-05

C12 = -1.4452093 E-08

C13 = 6.5459673 E+00 Pws = saturation pressure, Pa T = absolute temperature, K = °C + 273.15

The water vapor partial pressure is the saturation pressure multiplied by the relative humidity.

Pw = φ × Pws

The humidity ratio, W, is defined as the ratio of the mass of water vapor to the mass of dry air contained in the sample. It can be calculated from the pressure and the water vapor partial pressure as:

Pw W = 0.62198 × 

## ( P

- Pw 

## )

The testing the conditions for that hour against the criteria from Std 55, we can determine if the room air conditioner would have operated during that hour.

Figure 7-C.2.4 shows the hours (2281 hours) in 1991 that were above the comfort zone for Palm Springs.

7-C-10Hours above comfort zone Palm Springs, 1991

0.03

0.025humidity ratio 100%RH 0.02 90%RH

80%RH

70%RH

60%RH 0.015 50%RH

40%RH

30%RH

0.01 20%RH

10%RH

0.005

0

0 5 10 15 20 25 30 35 40 45 50

dry bulb temperature
Figure 7-C.2.4 Hours Above Comfort Zone in Palm Springs (1991)

Figure 7-C.2.5 shows hours above the Standard 55 comfort zone compared to CLDD for 15 years (1991-2005) for all Class 1 & II weather stations.

Room AC Operating Hours

10000

9000

8000

7000hours above Std 55 6000

5000

4000

3000

2000

1000

0

0 500 1000 1500 2000 2500 3000 3500 4000

CLDD 65

7-C-11Figure 7-C.2.5	 Hours Above the Standard 55 Comfort Zone Compared to CLDD

The lower ‘branch’ in the ‘hours above Std 55’ vs ‘CLDD 65’ is from low desert locations. After examining the data, the following sites were classified as desert.

Table 7-C.2.4 Average Room Air Conditioner EER by Product Class and Year Sold

STATION ST

DAVIS MONTHAN AFB AZ

DEER VALLEY/PHOENIX AZ

DOUGLAS BISBEE-DOUGLAS INTL A AZ KINGMAN (AMOS) AZ

LUKE AFB AZ

PHOENIX SKY HARBOR INTL AP AZ

SCOTTSDALE MUNI AZ

TUCSON INTERNATIONAL AP AZ

YUMA INTL ARPT AZ

YUMA MCAS AZ

BAKERSFIELD MEADOWS FIELD CA

BLYTHE RIVERSIDE CO ARPT CA

CHINA LAKE NAF CA

DAGGETT BARSTOW-DAGGETT AP CA

EDWARDS AFB CA

IMPERIAL CA

LANCASTER GEN WM FOX FIELD CA

NEEDLES AIRPORT CA

PALM SPRINGS INTL CA

PALM SPRINGS THERMAL AP CA

PALMDALE AIRPORT CA

TWENTYNINE PALMS CA

CARLSBAD CAVERN CITY AIR TERM NM

DEMING MUNI NM

HOLLOMAN AFB NM

LAS CRUCES INTL NM

ROSWELL INDUSTRIAL AIR PARK NM

TRUTH OR CONSEQUENCES MUNI AP NM

LAS VEGAS MCCARRAN INTL AP NV MERCURY DESERT ROCK AP [SURFRAD] NV

NELLIS AFB NV EL PASO INTERNATIONAL AP [UT] TX SAINT GEORGE (AWOS) UT

In Figure 7-C.2.6, the desert and tropical sites are shown. The uppermost points on the original chart (Figure 7-C.2.5) represent data from stations in Hawaii, Guam and the Caribbean.

7-C-12Room AC Operating Hourshours above Std 55 10000

9000

8000

7000

6000

all

HI & Guam 5000 Caribbean

desert

4000

3000

2000

1000

0

0 500 1000 1500 2000 2500 3000 3500 4000

CLDD 65

Figure 7-C.2.6 Hours Above the Standard 55 Comfort Zone versus CLDD with Different Regions Highlighted

After removing the sites in Hawaii, Guam, and the Caribbean islands, regressions were done to predict the hours per year above Standard 55 from the number of cooling degree-days for each year. The data points and regression lines are shown in Figure 7-C.2.7 for all hours of the year. This represents 842 sites for 15 years each in the continental United States.

7-C-13hours/year above ASHRAE Std 55 CLDD vs #hours > ASHRAE Std55 all day, all year 1991-2005

10000

y = 2.7592x + 127.99 9000 2 R = 0.9224

8000

7000

6000

non-desert

desert 5000 Linear (non-desert)
Linear (desert)
4000

3000

y = 1.153x + 574.04
2000 2 R = 0.8714

1000

0

0 500 1000 1500 2000 2500 3000 3500

CLDD (base 65F)
Figure 7-C.2.7 Hours Above ANSI/ASHRAE Standard 55-2004 as a Function of Cooling Degree-Days

As can be seen in the graph above, the data patterns are different for desert locations, where humidity is not a present factor affecting comfort. The regression equations used to derive the average annual hours when the outdoor air conditions are above the ASHRAE Standard 55 comfort zone (OH55) are shown in Table 7-C.2.5.

Table 7-C.2.5 Regression Equations Region Equation R 2 # sites

Non-desert OH55 = 2.759 x CLDD + 127.99 0.9224 809

Desert OH55 = 1.153 x CLDD + 574.04 0.8714 33

The number of annual hours above the ASHRAE Standard 55 comfort zone varies by schedule, which refers to the time that a building is open. Thus, DOE performed the regression for a number of combinations of building type and building schedule, yielding somewhat different equations for each combination. The building types included are: Assembly, Education, Food Service, Office, Retail, and Warehouse. For each building type, DOE estimated operating hours for each of the following building schedules: (1) open 24 hours a day and seven days a week (24/7); (2) open business hours Monday through Friday; (3) open business hours Monday through Saturday; (4) open business hours Monday through Friday and Sunday; (5) open business hours all week. The building types and schedule abbreviations are shown in table 7­

C.2.6 and 7-C.2.7. An assumption was made that if the occupancy rate was greater than 20% of full occupancy, the room air-conditioner would operate if the outdoor air conditions were above

the ASHRAE standard 55 comfort zone.

7-C-14Table 7-C.2.6 Building Type and Abbreviation Building Type Abbreviation Assembly ASM

Education EDU

Food Service FDS Lodging LOD

Medical MED

Office OFF

Outdoor OUT

Retail RET

Warehouse WHS

Table 7-C.2.7 Building Schedules and Abbreviation Building Schedules Abbreviation

24/7 hours 247 Monday-Friday M-F Monday - Friday and Saturday and Sunday ALL

The equations to predict the hours per year the outdoor air conditions are above the ASHRAE Standard 55 comfort zone for various building types and schedules for non-desert

locations are shown table 7-C.2.8.

Table 7-C.2.8	 Room Air Conditioner Operating Hour Equations By Building Type and

Schedule
building

type open schedule equation R2

ALL 247 ROH55 = 2.759 x CLDD + 127.99 0.9224

OUT

OUT M_F

ALL ROH55 = 1.974 x CLDD + 93.29

ROH55 = 2.759 x CLDD + 127.99 0.9458

0.9430

ASM

ASM M_F

ALL ROH55 = 0.751 x CLDD + 119.67

ROH55 = 1.396 x CLDD + 169.18 0.9458

0.9430

EDU

EDU M_F

ALL ROH55 = 1.001 x CLDD + 117.11

ROH55 = 1.398 x CLDD + 163.52 0.9412

0.9424

FDS

FDS M_F

ALL ROH55 = 1.243 x CLDD + 112.91

ROH55 = 1.510 x CLDD + 166.44 0.9354

0.9408

LOD

LOD M_F

ALL ROH55 = 1.471 x CLDD + 17.11

ROH55 = 2.206 x CLDD + 40.94 0.9428

0.9408

MED

MED M_F

ALL ROH55 = 1.001 x CLDD + 128.06

ROH55 = 1.151 x CLDD + 148.72 0.9428

0.9408

OFF

OFF M_F

ALL ROH55 = 0.918 x CLDD + 119.76

ROH55 = 1.510 x CLDD + 166.44 0.9428

0.9408

RET

RET M_F

ALL ROH55 = 0.751 x CLDD + 119.67

ROH55 = 1.281 x CLDD + 170.57 0.9458

0.9450

WHS

WHS M_F

ALL ROH55 = 0.836 x CLDD + 109.17

ROH55 = 1.514 x CLDD + 178.06 0.9422

0.9419

7-C-15The highlighted rows are the same. This is because the occupancy rates were above 20 percent for 24 hours per day for all building types operating under the 24/7 schedule. The analysis does not account for differences in building operation schedules due to holidays.

The equations to predict the hours per year the outdoor air conditions are above the ASHRAE Standard 55 comfort zone for various building types and schedules for desert locations

are shown table 7-C.2.9.

Table 7-C.2.9	 Room Air Conditioner Operating Hour Equations By Building Type and Schedule (Desert)
building

type open schedule equation R2

ALL 247 ROH55 = 1.153 x CLDD + 574.04 0.9224

OUT

OUT M_F

ALL ROH55 = 1.974 x CLDD + 93.29

ROH55 = 2.759 x CLDD + 127.99 0.8353

0.8925

ASM

ASM M_F

ALL ROH55 = 0.289 x CLDD + 546.12

ROH55 = 0.600 x CLDD + 721.20 0.8353

0.8925

EDU

EDU M_F

ALL ROH55 = 0.409 x CLDD + 532.56

ROH55 = 0.572 x CLDD + 741.06 0.8723

0.8794

FDS

FDS M_F

ALL ROH55 = 0.553 x CLDD + 449.33

ROH55 = 0.663 x CLDD + 690.02 0.8914

0.8985

LOD

LOD M_F

ALL ROH55 = 0.642 x CLDD + 40.06

ROH55 = 0.951 x CLDD + 157.74 0.8260

0.8985

MED

MED M_F

ALL ROH55 = 0.402 x CLDD + 603.12

ROH55 = 0.458 x CLDD + 706.19 0.8260

0.8985

OFF

OFF M_F

ALL ROH55 = 0.353 x CLDD + 573.23

ROH55 = 0.663 x CLDD + 690.02 0.8260

0.8985

RET

RET M_F

ALL ROH55 = 0.289 x CLDD + 546.12

ROH55 = 0.534 x CLDD + 749.00 0.8353

0.8813

WHS

WHS M_F

ALL ROH55 = 0.317 x CLDD + 524.97

ROH55 = 0.612 x CLDD + 837.58 0.8087

0.8682

To estimate the room air conditioner operating hours for each of the buildings in the CBECS 2003 room air conditioner sample, DOE identified the building type (see Table 7­ C.2.10) and the building schedule using information provided by CBECS, and used the appropriate equation (non-desert or desert) combined with the number of cooling degree-days for the location of the building. It adjusted the results with a scaling factor to account for the difference between the number of building operating hours assumed to derive the equations and the actual building operating hours reported by CBECS.

7-C-16Table 7-C.2.10 CBECS 2003 Building Code Match to Room Air Conditioner Equation Building Type

CBECS

2003 PBA

Code Definition Building Type Match Fraction of

CBECS 2003 RAC Sample

1 Vacant Not Applicable

2 Office OFF 18.3%

4 Laboratory MED 0.2%

5 Nonrefrigerated warehouse WHS 5.9%

6 Food sales RET 2.9%

7 Public order and safety OFF 4.1%

8 Outpatient health care MED 0.6%

11 Refrigerated warehouse WHS 0.0%

12 Religious worship ASM 8.7%

13 Public assembly ASM 5.5%

14 Education EDU 12.7%

15 Food service FDS 4.5%

16 Inpatient health care MED 0.2%

17 Nursing MED 1.4%

18 Lodging LOD 3.5%

23 Strip shopping mall RET 0.0%

24 Enclosed mall RET 0.0%

25 Retail other than mall RET 11.8%

26 Service RET 17.3%

91 Other OFF 2.3%

The above approach provides a ‘best guess’ of the room air conditioner operating hours for a particular CBECS building. However, operating hours are affected by some factors not included in the analysis, such as interior heat gains from equipment or people and solar gains. To develop a distribution of the number of operating hours for each sample building, DOE added an error band to the value derived using the regression equation. The error band includes values that are ± 10% from the regression line for the appropriate building type/schedule combination.

The commercial sector operating hours were estimated based on the cooling climate in 2003. To match the residential analysis, which was based on 2005 climate, DOE increased the estimated commercial sector operating hours by 8 percent, as given by the ratio of CDD between

2005 and 2003.

7-C.3 CLOTHES DRYERS

DOE determined the annual energy consumption by-products that would meet a potential future standard by multiplying the number of cycles per year by the energy use per cycle.

7-C-177-C.3.1 Number of Cycles

DOE estimated the number of clothes dryer cycles per year for each sample home using data given by RECS on the number of laundry loads (clothes washer cycles) washed per week and the frequency of clothes dryer use. The responses in RECS fall into one of the bins shown in Tables 7-C.3.1 and 7-C.3.2. For each question, DOE assumed a uniform distribution within the boundaries of each bin and randomly assigned a value from within the appropriate range to each sample household.

Table 7-C.3.1 Number of Loads Washed per Week Based on RECS Sample

Bin Loads per Week Derived Loads per Year*

Min Max

1 1 load or less 0 78

2 2 to 4 loads 78 234

3 5 to 9 loads 234 494

4 10 to 15 loads 494 806

5 More than 15 loads 806 1118

* The ranges reflect the inclusion of values in between the given bin boundaries.

Table 7-C.3.2 RECS Sample Clothes Dryer Usage

Bin Description Fraction of Washer Cycles When Dryer is used

Min Max

1 Use it every time wash clothes 1 1

2 Use it for some, but not all, loads of

wash 0.50 1

3 Use it infrequently 0.00 0.50

The responses to the above questions vary among sample households using different clothes dryer products, so they yield somewhat different values for the average annual number of clothes dryer cycles for each product class (see Table 7-C.3.3).

7-C-18Table 7-C.3.3 RECS Sample Clothes Dryers Utilization

Product Class

Electric

Standard Gas Ventless Clothes Dryer

DOE Test

Procedure Assumption Clothes Washer

DOE Test

Procedure Assumption

Washer loads per

year 301 292 268 NA 392

Clothes dryer frequency* 0.95 0.93 0.94 NA 0.84**

Clothes dryer loads

per year 285 271 252 416 329

* Fraction of washer loads ** Accounts for fraction of households that have a clothes washer, but no clothes dryer

7-C.3.2 Energy Use Calculation

For each considered efficiency level, DOE derived the field energy use by separately estimating the active mode and standby mode energy use and then adding them together. The DOE test procedure calculates active mode energy consumption by dividing the weight (lbs) of clothes dried per cycle (7 lbs for standard and 3 lbs for compact clothes dryers) and by the Energy Factor (EF) (lbs/kWh). e DOE adjusted the test procedure energy use to reflect field conditions by making an adjustment for clothes dryer load weight and moisture removal factor.

For each household, DOE determined the field adjustment for clothes dryer energy use during active mode by using the following formula:

⎛ ⎛⎞ ⎟ ⎠

⎟ ∗ ⎞ ⎟ ⎠

⎟ ∗ avgLoadWeight
TP ∗ avgLoadWeight Field RMC Field CD EnergyUse CD Cycles = ⎜ ⎜ ⎝ ⎜ ⎜ ⎝ ActiveMode _ _ EF avgLoadWeight
TP RMC TP

Where:

avgLoadWeight TP = average load weight in the test procedure, lbs, avgLoadWeight Field = average load weight for each household, lbs,

RMC TP = remaining moisture content in the test procedure, percent,

RMC Field = remaining moisture content for the household, percent,

EF = efficiency of the clothes dryer during active mode, lbs per kWh, and CD_Cycles = clothes dryer cycles per year.

e See chapter 5 for more information on how to convert from IEF to EF. IEF assumes 416 cycles, 8156 hours of standby, and a standby power that varies by efficiency level.

7-C-19To assign an average load weight for each household, DOE developed a distribution of load weights by matching the listed tub sizes for models in the Dec. 22, 2008 California Energy Commission (CEC) directory with the correlations between tub size and average pounds in the DOE test procedure. The average load weights for standard-size units range from 5.1 lbs. to 10 lbs., with a mean value of 8.1 lbs. For comparison, the DOE test procedure uses a weight of 7 lbs

for standard-size units.

To assign a RMC value for each household, DOE used a distribution of values based on the number of models listed at each RMC in the Dec. 22, 2008 CEC directory. The RMC values range from 30 percent to 61 percent, with an average of 46 percent. The remaining moisture content (RMC) in the test procedure is 70 percent.

Using the above approach, DOE calculated a unique value for the clothes dryer annual active mode energy consumption for each sample household with electric clothes dryer using the number of dryer cycles specified for that household. For gas clothes dryers, DOE used a similar approach as for electric clothes dryers, but added an estimate of the energy use of electric components. An estimate of 200 kWh per cycle, which was derived from tests done by DOE, was applied for all efficiency levels except for the max-tech level. For the latter, which has a more efficient motor, the tests found a value of 187 kWh.

For each household, DOE determined the field-adjusted clothes dryer energy use during standby mode by using the following formula:

ClothesDryerEnergyUse S tan dby = ⎡ ⎢ ⎣ 8760

− CD

_ Cycles ∗ ⎛ ⎜ ⎝ ⎞ ⎟ ⎠ ⎤ CD

_ Time

∗ S tan dby

_ Power ⎥ ⎦ 60

Where:

8760 = number of hours in one year, hrs,
CD_Time = clothes dryer time to complete one cycle, min/cycle,

60 = number of minutes in one hour, min/hr, Standby_Power = standby power, kW, and CD_Cycles = clothes dryer cycles per year.

DOE assumed that clothes dryers take 60 minutes on average to complete a cycle. Standby power varies by efficiency level as discussed in chapter 5.

For vent-less clothes dryers, DOE considered the impact of the dryer on the home’s heating and cooling loads. A vent-less dryer releases heat to the surrounding environment. If the dryer is located indoors, dryer use will tend to slightly reduce the heating load during the heating season and slightly increase the cooling load during the cooling season. DOE believes that the effect is the same for all of the considered efficiency levels, and thus it did not include this factor in its analysis.

7-C-20REFERENCES

1. Association of Home Appliance Manufacturers, Trends in Energy Efficiency 2008 2008

2. American National Standards Institute & American Society of Heating, R., and AirConditioning Engineers, Inc.,, ANSI/ASHRAE 55-2004 Thermal Environmental Conditions for Human Occupancy , 2004.

3. National Renewable Energy Laboratory, National Solar Radiation Database 1991–2005 Update: User’s Manual, 2007. < http://www.nrel.gov/docs/fy07osti/41364.pdf >

7-C-21