CHAPTER 7. ENERGY USE ANALYSIS

TABLE OF CONTENTS

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

7.2 CUAC EQUIPMENT ENERGY SAVINGS DETERMINATION ................................. 7-1

7.2.1 Building Loads ..................................................................................................... 7-2

7.2.2 Modeling Equipment Energy Use ........................................................................ 7-6

7.2.2.1 Modeling of 7.5-Ton CUAC Equipment .................................................... 7-7

7.2.2.2 Modeling of 15-Ton CUAC Equipment ..................................................... 7-8

7.2.2.3 Modeling of 30-Ton CUAC Equipment ................................................... 7-10

7.2.2.4 Energy Consumption ................................................................................ 7-12

7.2.3 Energy Decrements ............................................................................................ 7-12

7.2.4 Results ................................................................................................................ 7-13

7.3 GENERALIZED BUILDING SAMPLE ....................................................................... 7-17

7.3.1 Data Sources ...................................................................................................... 7-17

7.3.2 Commercial Building Characteristics ................................................................ 7-17

7.3.3 Interpolation of Weights across Building Characteristics ................................. 7-21

7.3.4 Assigning Electricity Load Profiles to Generalized Buildings .......................... 7-22

7.3.5 CUAC Energy Use Results ................................................................................ 7-24

REFERENCES .......................................................................................................................... 7-26

LIST OF TABLES

Table 7.2.1 Description of Equipment and Calculation Methods for 7.5-ton 

Equipment at Various ELs ............................................................................. 7-7

Table 7.2.2 Calculated Equations for 7.5-Ton Equipment ............................................... 7-8

Table 7.2.3 Description of Equipment and Calculation Methods for 15-ton 

Equipment at Various ELs ............................................................................. 7-9

Table 7.2.4 Calculated Equations for 15-Ton Equipment .............................................. 7-10

Table 7.2.5 Description of Equipment and Calculation Methods for 30-ton 

Equipment at Various ELs ........................................................................... 7-11

Table 7.2.6 Calculated Equations for 30-Ton Equipment .............................................. 7-12

Table 7.3.1 Characteristics and Associated Values Used to Define the Generalized 

Building Sample........................................................................................... 7-18

Table 7.3.2 Floor Space by Region ................................................................................. 7-19

Table 7.3.3 Floor Space by Building Activity ................................................................ 7-19

Table 7.3.4 Floor Space by Size (Annual Energy Consumption) ................................... 7-20

Table 7.3.5 Floor Space Distribution by Size and Region .............................................. 7-20

Table 7.3.6 Floor Space by Vintage ................................................................................ 7-20

Table 7.3.7 Required capacity in tons per square foot for different regions and 

representative unit capacities ....................................................................... 7-22

Table 7.3.8 Factors used to represent relative changes in required cooling energy 

for vintage category 3. ................................................................................. 7-23

7-i 
Table 7.3.9 7.5-ton CUAC Equipment: Annual Energy Use Results by Efficiency 

Level ............................................................................................................ 7-24

Table 7.3.10 15-ton CUAC Equipment: Annual Energy Use Results by Efficiency 

Level ............................................................................................................ 7-25

Table 7.3.11 30-ton CUAC Equipment: Annual Energy Use Results by Efficiency 

Level ............................................................................................................ 7-25

LIST OF FIGURES

Figure 7.2.1 Capacity Ratio as a Function of Outdoor Dry-Bulb Temperature ................. 7-3

Figure 7.2.2 COP Ratio as a Function of Outdoor Dry-Bulb Temperature ....................... 7-3

Figure 7.2.3 Cumulative Fraction of Rated Capacity by Compressor Operating 

Hours .............................................................................................................. 7-5

Figure 7.2.4 Cumulative Fraction of Hour of Fan Run Time by Hours of Year ................ 7-6

Figure 7.2.5 Annual Cooling Energy Use by Efficiency Level for 7.5-ton 

Equipment .................................................................................................... 7-14

Figure 7.2.6 Annual Fan Energy Use by Efficiency Level for 7.5-ton Equipment.......... 7-14

Figure 7.2.7 Annual Cooling Energy Use by Efficiency Level for 15-ton Equipment .... 7-15

Figure 7.2.8 Annual Fan Energy Use by Efficiency Level for 15-ton Equipment........... 7-15

Figure 7.2.9 Annual Cooling Energy Use by Efficiency Level for 30-ton Equipment .... 7-16

Figure 7.2.10 Annual Fan Energy Use by Efficiency Level for 30-ton Equipment........... 7-16

Figure 7.3.1 Distribution of Floor Space in 2011 by PBA, Region, and Vintage ............ 7-21

Figure 7.3.2 Comparison of cooling degree days by state for TMY3 and TMY2 ........... 7-23

7-ii
CHAPTER 7. ENERGY USE ANALYSIS

7.1 INTRODUCTION

The building energy use analysis produced energy use estimates and end-use load shapes 

for commercial unitary air-cooled air conditioners (CUAC). The energy use estimates enabled 

evaluation of energy savings from the operation of small, large, and very large air-cooled CUAC 

equipment at various efficiency levels, while the end-use load shapes allowed evaluation of the 

impact on electricity demand from the operation of CUAC equipment. The analysis produced 

results from a variety of building types in multiple climate locations in order to capture some of 

the diversity of use, and performance, of CUAC equipment. 

DOE developed energy consumption estimates only for the CUAC equipment classes that 

have no heating or electric resistance heating. For equipment classes with all other types of 

heating, the incremental change in each efficiency level is identical to the incremental change in 

each efficiency level for the equipment classes with no heating or electric resistance heating. 

Therefore, DOE estimated that the energy savings for any efficiency level relative to the baseline 

would be identical for both sets of equipment classes. In turn, the energy savings estimates for 

the efficiency levels associated with the equipment classes that have no heating or electric 

resistance heating were used by DOE in the LCC and PBP analysis and the NIA to represent 

both sets of equipment classes. 

The energy use analysis described in this chapter consists of two related parts. In the first 

part (Section 7.2), DOE calculated energy savings for small, large, and very large air-cooled 

CUAC at the considered efficiency levels based on modifications to the energy use simulations 

conducted for the 2004 Advanced Notice of Proposed Rulemaking (ANOPR).1

 These building 

simulation data are based on the 1995 Commercial Building Energy Consumption Survey 

(CBECS).2 Because the simulation data reflects the building stock in 1995 that uses air-cooled 

CUAC equipment, in the second part (Section 7.3), DOE developed a “generalized building 

sample” to represent the current installation conditions for the equipment covered in this 

rulemaking. This part involved making adjustments to update the building simulation data and 

the building weights to reflect the building stock that uses air-cooled CUAC equipment in 2011. 

7.2 CUAC EQUIPMENT ENERGY SAVINGS DETERMINATION

This section describes the determination of energy savings for small, large, and very large 

air-cooled CUAC at the considered efficiency levels. Whole-building simulations are an 

excellent source of energy use and equipment operation data, so DOE determined, from the 2004 

ANOPR’s energy use simulations, hourly building cooling load profiles for each of the 1,033 

commercial buildings. Section 7.2.1 describes this process and appendix 7A further describes the 

simulations and updates made to the simulation methods used for the 2004 ANOPR. DOE then 

modeled the equipment introduced in Chapter 5 and simulated equipment energy use that would 

result from meeting the building cooling loads. Section 7.2.2 highlights this methodology. 

7-1 
Energy decrements can then be determined by comparing the equipment energy use at the 

baseline level and at a considered efficiency level, as described in Section 7.2.3. The decrements 

are shown in Section 7.2.4. 

7.2.1 Building Loads

DOE calculated hourly building cooling loads and hourly fan operation based on the 

compressor and fan energy consumptions derived from simulations of equipment at an energy 

efficiency rating (EER) of 11. The following expressions demonstrate how the conversion was 

conducted in order to arrive at hourly total cooling load for each building. 

First, the total input power for the CUACs serving the building was determined with the 

following equation for each hour: 

POWERCUAC(hr) = 

SYS_SIZECUAC × CapRatio

EERCUAC × COPratio

Eq. 7.1 

where:

POWERCUAC(hr) = total input power to the CUACs in an hour (in Watts), 

SYSSIZECUAC = system size of all CUACs serving the building (in Btu/hr), 

EERCUAC = efficiency of the CUACs (11 EER). 

CapRatio and COPratio are the capacity ratio and COP ratio, respectively. They are found for 

each hour using the hourly weather file from the building simulations and their relationships to 

dry bulb temperature, which are provided by the cooling system component of the building 

simulations. These relationships depicted in Figure 7.2.1 and Figure 7.2.2. 

7-2 
Figure 7.2.1 Capacity Ratio as a Function of Outdoor Dry-Bulb Temperature

Figure 7.2.2 COP Ratio as a Function of Outdoor Dry-Bulb Temperature

7-3 
Second, compressor input power for the CUACs serving the building was determined 

with the following equation for each hour: 

���������−����(��) = ���������(��)− ���������−���(��)

Eq. 7.2 

where:

POWERCUAC−COMP(hr) = compressor input power to the CUACs in an hour (in Watts), 

POWERCUAC−FAN(hr) = ventilation fan input power of the CUACs in an hour (in Watts).

 

In the above equation, the ventilation fan is assumed to run whenever the compressor is running 

and runs constant regardless of load or outdoor dry-bulb temperature. 

Third, the fraction of the hour that the CUAC compressors run was determined with the 

following equation for each hour: 

FRACHOURCUAC−COMP(hr) = 

ENERGYCUAC−COMP(hr)

POWERCUAC−COMP(hr)

Eq. 7.3 

where: 

FRACHOURCUAC−COMP(hr) = fraction of the hour the compressor runs each hour, 

ENERGYCUAC−COMP(hr) = energy used by the CUAC compressors. 

In the above equation, the compressor hourly energy is obtained from the building simulations.

Finally, hourly building loads were determined with the following expression: 

BldgLoad(hr)

= SYSSIZECUAC × CapRatio × FRACHOURCUAC−COMP(hr) − POWERCUAC−FAN(hr)

× ConvFactor

Eq. 7.4

where: 

BldgLoad(hr) = building load in each hour, 

ConvFactor = factor to convert watts into Btu/hr.

For most hours in all buildings, the compressor needs to supply only a fraction of its rated 

cooling capacity to meet the cooling load. Cooling systems for each building are sized to meet 

the expected peak load of the building. As a result, the system is oversized for almost all hours 

of the year. For each building, the number of CUAC units was calculated by dividing the 

modeled equipment’s rated capacity at 95 °F with the system size used in the building 

simulations. The method for determining the system size for each building for use in the 

simulation modeling is described in the 2004 ANOPR.2 Figure 7.2.3 shows the cumulative 

fraction of rated capacity by hours of compressor run time in a simulated year for each of the 

1,033 commercial buildings. 

7-4 
Figure 7.2.3 Cumulative Fraction of Rated Capacity by Compressor Operating Hours

Because the 11EER equipment modeled in the building simulations utilized a singlespeed fan, the fraction of each hour that the fan was on in the simulation is the ratio of that 

hour’s fan energy consumption to the maximum hourly fan energy consumption. The heat from 

the indoor fan was added to the cooling load created by the building. The heat created by the 

indoor fan for each hour was calculated by multiplying three variables: the power of the indoor 

fan, the fraction of the hour the fan operated in the building simulation, and the number of 

CUAC units in that building. The cooling load attributable solely to the building was calculated 

by subtracting the hourly fan energy consumption from the total hourly cooling provided by the 

compressor. In addition to distributing cooling from the CUAC equipment, the fans are run to 

provide ventilation for building occupants. Figure 7.2.4 shows the cumulative fraction of hour of 

fan run time for every hour of the year for all 1,033 commercial buildings. In all simulated 

buildings the fans run for the full hour for at least 2,700 hours per year. In some buildings the 

fans run continuously all year long. 

 

7-5 
Figure 7.2.4 Cumulative Fraction of Hour of Fan Run Time by Hours of Year 

7.2.2 Modeling Equipment Energy Use

DOE applied the hourly building cooling loads and hourly fan operating hours to the 

baseline equipment and to equipment at the various ELs. The energy consumption of equipment 

at baseline efficiency (EL0) and at four higher efficiency levels (EL1 through EL4) was 

determined for each hour of the year for the 1,033 commercial buildings. The energy 

consumption was calculated based on the required building cooling load and the fraction of fan 

run time for each hour. 

DOE used data specified per the AHRI rating standard to calculate the energy 

consumption of equipment at each efficiency level.3 Data per the AHRI rating standard identifies 

the net capacity, compressor power, condenser fan power, indoor fan power, control power, and 

EER at outdoor temperatures of 95, 81.5, 68, and 65 °F. DOE then developed equations to define 

the relationships between outdoor dry bulb temperature and the various components’ power. The 

CUAC equipment for which these relationships were developed are described in Tables 7-1, 7-3, 

and 7-5 for 7.5-, 15-, and 30-ton equipment, respectively. The relationships as a function of 

efficiency level are shown in Tables 7-2, 7-4, and 7-6 for 7.5-, 15-, and 30-ton equipment, 

respectively. 

7-6 
As noted above, for each building, the number of CUAC units was calculated by dividing 

the modeled equipment’s rated capacity at 95 °F with the system size used in the building 

simulations. For calculation purposes, the result was not necessarily an integer. 

7.2.2.1 Modeling of 7.5-Ton CUAC Equipment

Table 7.2.1 describes the baseline and four efficiency levels and the calculation methods 

used in the analysis of 7.5-ton CUAC equipment. At each EL, the description of the components 

of the equipment and the modeling methodology for the components are shown in the table 

below. Detailed descriptions of the CUAC equipment at each EL are provided in Chapter 5. 

Table 7.2.1 Description of Equipment and Calculation Methods for 7.5-ton Equipment at 

Various ELs 

Efficiency 

Level Description Calculation Method

EL0 

(baseline)

Single-stage compressor; 

constant-speed indoor fan 

Linear fit of net capacity (NetCap) and compressor power 

(Pc) to ambient temperature. Apply load fraction (LF) and 

cyclic degradation (CD).

EL1 Single-stage compressor; 

constant-speed indoor fan 

Linear fit of net capacity (NetCap) and compressor power 

(Pc) to ambient temperature. Apply load fraction (LF) and 

cyclic degradation (CD).

EL2

Two equal-sized fixedspeed compressors; 

constant-speed indoor fan

Linear fit of net capacity (NetCap) and compressor power 

(Pc) to ambient temperature. Apply load fraction (LF) and 

cyclic degradation (CD) to stage 1. If stage 1 is unable to 

meet load, stage 2 is added. Only LF, not CD, is applied to 

stage 2.

EL3

Two equal-sized fixedspeed compressors; 

variable-speed indoor fan

Linear fit of net capacity (NetCap) and compressor power 

(Pc) to ambient temperature. Apply load fraction (LF) and 

cyclic degradation (CD) to stage 1. If stage 1 is unable to 

meet load, stage 2 is added. Only LF, not CD, is applied to 

stage 2.

EL4

Two unequal-sized 

compressors; 3-stage 

operation: first compressor 

followed by second 

compressor, then both 

compressors; variablespeed indoor fan

Linear fit of net capacity (NetCap) and compressor power 

(Pc) to ambient temperature. Assume the same linear fit 

for each independently operating compressor. Apply load 

fraction (LF) and cyclic degradation (CD) when only 1 

compressor is on. Only LF is applied when both 

compressors are on.

The load fraction (LF) is the building load for one hour multiplied by the ratio of the net 

capacity at 95 °F to the net capacity at the actual ambient temperature at that hour. In other 

words, the LF is the fraction of the hour the last-stage compressor needs to run to cool the 

building and compensate for the fan energy. The coefficient of degradation (CD) equals -0.13 x 

LF + 1.13. 

7-7 
Table 7.2.2 shows the calculated equations as functions of outdoor dry-bulb temperature 

(TDB) for the parameters of the 7.5-ton CUAC equipment as applied to the simulated loads. The 

equipment for EL2, EL3, and EL4 has multiple stages. The equations differ depending on the 

number of stages that are operating. 

Table 7.2.2 Calculated Equations for 7.5-Ton Equipment

Efficiency 

Level

Net Capacity

(BTU/h)

Compressor Power

(W)

Condenser 

Fan Power 

(W)

Indoor Fan Power

(W)

Control 

Power

(W)

EL0 122985.509 -

343.683 × TDB

 927.645 + 63.197 × TDB 775.1 827.4 17

EL1 144651.652 -

527.517 × TDB

 905.559 + 61.059 × TDB 667 775.875 17

EL2.1 59581.333 -

112.833 × TDB

596.667 + 21.667 × TDB 608.17 642.5 20

EL2.2 110692.333 -

225.667 × TDB

1763.333 + 43.333 × TDB 587.2 642.5 24

EL3.1 92224.174 -

642.353 × TDB

27.522 + 32.940 × TDB 352.0 If (TDB <68, 207, 

-225.123 + 6.807 × TDB) 20

EL3.2 206316.161 -

1284.707 × TDB

-669.516 + 65.879 × TDB 702.7 If (TDB <68, 207, 

-225.123 + 6.807 × TDB) 24

EL4.1 127876.333 -

1311.667 × TDB

-1565.000 + 45.000 × TDB 177 68 55

EL4.2 248966.504 -

2184.080 × TDB

-5814.561 + 113.393 × TDB 297 -289.270 + 5.448 × TDB 55

EL4.3 423122.915 -

3495.746 × TDB

-8562.371 + 158.393 × TDB 443 -289.270 + 5.448 × TDB 55

7.2.2.2 Modeling of 15-Ton CUAC Equipment

Table 7.2.3 and Table 7.2.4 describe the ELs and equations for 15-ton CUAC equipment. 

15-ton equipment involves two or three compressor stages at every EL. 

7-8 
Table 7.2.3 Description of Equipment and Calculation Methods for 15-ton Equipment at 

Various ELs 

Efficiency 

Level Description Calculation Method

EL0 

(baseline)

Two equal-sized, fixedspeed compressors; 

constant-speed indoor fan; 

constant-speed condenser 

fan

Linear fit of net capacity (NetCap) and compressor 

power (Pc) to ambient temperature. Apply load fraction 

(LF) and cyclic degradation (CD) to stage 1. If stage 1 is 

unable to meet load, stage 2 is added. Only LF, not CD, 

is applied to stage 2.

EL1 

Two equal-sized, fixedspeed compressors; 

constant-speed indoor fan; 

constant-speed condenser 

fan

Linear fit of net capacity (NetCap) and compressor 

power (Pc) to ambient temperature. Apply load fraction 

(LF) and cyclic degradation (CD) to stage 1. If stage 1 is 

unable to meet load, stage 2 is added. Only LF, not CD, 

is applied to stage 2.

EL2 

Two equal-sized, fixedspeed compressors; two 

constant-speed indoor fans; 

constant-speed condenser 

fan

Linear fit of net capacity (NetCap) and compressor 

power (Pc) to ambient temperature. If stage 1 is unable 

to meet load, stage 2 is added. Apply load fraction (LF) 

and cyclic degradation (CD) to stage 1; only LF, not 

CD, is applied to stage 2. Indoor fans run 

simultaneously. Condenser fans run simultaneously.

EL3

Two equal-sized, fixedspeed compressors; two 

variable-speed indoor fans; 

two-stage condenser fan

Linear fit of net capacity (NetCap) and compressor 

power (Pc) to ambient temperature. If stage 1 is unable 

to meet load, stage 2 is added. Apply load fraction (LF) 

and cyclic degradation (CD) to stage 1; only LF, not 

CD, is applied to stage 2. Indoor fan power (Pif) 

constant below Tdb = 68 °F. Linear fit above that 

temperature. Indoor fans run simultaneously. Condenser 

fans run simultaneously in two stages.

EL4

Single-circuit, tandem, 

unequal-sized compressors; 

two variable-speed indoor 

fans; three-stage condenser 

fan

Linear fit of net capacity (NetCap) and compressor 

power (Pc) to ambient temperature. If stage 1 small 

compressor is unable to meet load, stage 2 large 

compressor is run. If stage 2 is unable to meet load, 

stage 3 is set by running both compressors 

simultaneously. Apply load fraction (LF) and cyclic 

degradation (CD) to stages 1 and 2; only LF, not CD, is 

applied to stage 3. Indoor fan power (Pif) constant 

below Tdb = 68 °F. Linear fit above that temperature. 

Indoor fans run simultaneously. Condenser fans run 

simultaneously in three stages.

7-9 
Table 7.2.4 Calculated Equations for 15-Ton Equipment

Efficiency 

Level

Net Capacity

(BTU/h)

Compressor Power

(W)

Condenser 

Fan Power 

(W)

Indoor Fan Power

(W)

Control 

Power

(W)

EL0.1 117432.152 -

345.372 × TDB

1445.449 + 51.932 × TDB 1494.100 1271.025 16.047

EL0.2 237731.514 -

690.743 × TDB

3774.821 + 103.864 × TDB 1494.100 1271.025 20.700

EL1.1 117963.541 -

333.994 × TDB

1376.236 + 51.227 × TDB 1116.000 1172.125 16.047

EL1.2 237859.169 -

667.989× TDB

3679.607 + 102.454 × TDB 1116.000 1172.125 20.700

EL2.1 143521.939 -

584.719 × TDB

1557.668 + 51.225 × TDB 839.563 1103.890 16.047

EL2.2 288512.667 -

1169.439 × TDB

3152.188 + 102.450 × TDB 839.563 1139.320 20.700

EL3.1 98877.313 -

23.722 × TDB

1115.286 + 58.329 × TDB 685.0 If (TDB <68, 507, 

9.120 + 7.530 × TDB) 16.047

EL3.2 181813.159 -

47.445 × TDB

1505.092 + 116.658 × TDB 914.000 If (TDB <68, 507, 

9.120 + 7.530 × TDB) 20.700

EL4.1 98757.855 -

278.582 × TDB

minimum of (-23.180 + 

36.587 × TDB, 0) 494.000 If (TDB <65, 376,-670.077 + 16.519 * TDB) 84.0

EL4.2 161042.867 -

437.377 × TDB

-1297.863 + 90.547 × TDB 742.000 If (TDB <65, 376,-

670.077 + 16.519 * TDB) 84.0

EL4.3 246466.937 + -

715.959 × TDB

-855.427 + 127.135 × TDB 989.000 If (TDB <65, 376,-

670.077 + 16.519 * TDB) 84.0

7.2.2.3 Modeling of 30-Ton CUAC Equipment

All the ELs for the 30-ton CUAC equipment have four scroll compressors on two 

circuits. EL0, EL1, and EL2 are two-stage systems associated with constant-speed indoor fans. 

EL0 has one single-speed, single-stage outdoor fan. EL1 has two single-speed outdoor fans 

operated in two stages. EL2 and EL3 have four stages and a variable-speed indoor fan. EL2 and 

EL3 have four single-speed outdoor fans operated in two stages. EL4 has six single-speed 

outdoor fans operated in four stages. 

Table 7.2.5 and Table 7.2.6 describe the ELs and equations for 30-ton CUAC equipment. 

30-ton equipment involves two or three compressor stages at every EL.

7-10 
Table 7.2.5 Description of Equipment and Calculation Methods for 30-ton Equipment at 

Various ELs 

Efficiency 

Level Description Calculation Method

EL0 

(baseline)

Four equal-sized, fixed-speed 

compressors operated in two 

stages; two constant-speed 

indoor fans; two constant-speed 

outdoor fans 

Linear fit of net capacity (NetCap) and compressor 

power (Pc) to ambient temperature. If stage 1 is 

unable to meet load, stage 2 is added. Apply load 

fraction (LF) and cyclic degradation (CD) to stage 1; 

only LF, not CD, is applied to stage 2. Indoor fans 

run simultaneously. Condenser fans run 

simultaneously in two stages.

EL1

Four equal-sized, fixed-speed 

compressors operated in two 

stages; two constant-speed 

indoor fans; two constant-speed 

outdoor fans 

Linear fit of net capacity (NetCap) and compressor 

power (Pc) to ambient temperature. If stage 1 is 

unable to meet load, stage 2 is added. Apply load 

fraction (LF) and cyclic degradation (CD) to stage 1; 

only LF, not CD, is applied to stage 2. Indoor fans 

run simultaneously. Condenser fans run 

simultaneously in two stages.

EL2 

Four equal-sized, fixed-speed 

compressors operated in two 

stages; two constant-speed 

indoor fans; four constantspeed outdoor fans

Linear fit of net capacity (NetCap) and compressor 

power (Pc) to ambient temperature. If stage 1 is 

unable to meet load, stage 2 is added. Apply load 

fraction (LF) and cyclic degradation (CD) to stage 1; 

only LF, not CD, is applied to stage 2. Indoor fans 

run simultaneously. Condenser fans run 

simultaneously in two stages.

EL3

Based on EL2 plus a variablespeed indoor blower; 

compressor operates in four 

stages

Linear fit of net capacity (NetCap) and compressor 

power (Pc) to ambient temperature. Indoor fan power 

(Pif) constant for first stage; linear fit with 

temperature above that. If stage 1 is unable to meet 

load, subsequent stages are added. Apply load 

fraction (LF) and cyclic degradation (CD) to stage 1; 

only LF, not CD, is applied beyond stage 1. 

Condenser fans run simultaneously in two stages.

EL4

Based on EL3 but with six

outdoor fans operating in four 

stages

Linear fit of net capacity (NetCap) and compressor 

power (Pc) to ambient temperature. Indoor fan power 

(Pif) constant for first stage; linear fit with 

temperature above that. If stage 1 is unable to meet 

load, subsequent stages are added. Apply load 

fraction (LF) and cyclic degradation (CD) to stage 1; 

only LF, not CD, is applied beyond stage 1. 

Condenser fans run simultaneously in four stages.

7-11 
Table 7.2.6 Calculated Equations for 30-Ton Equipment

Efficiency 

Level

Net Capacity

(BTU/h)

Compressor Power

(W)

Condenser 

Fan Power

(W)

Indoor Fan Power

(W)

Control 

Power

(W)

EL0.1 265285.091 -

931.394 × TDB

1865.195 + 93.691 × TDB 4052.667 4579.1 199

EL0.2 488939.755 -

1862.788 × TDB

8645.451 + 187.382 × TDB 3820.000 4579.1 67

EL1.1 263309.540 -

865.718 × TDB

1996.483 + 94.282 × TDB 1765.0 4443.0 199

EL1.2 493406.060 -

1731.435 × TDB

8428.729 + 188.564 × TDB 3313.0 4443.0 67

EL2.1 275458.577 -

955.357 × TDB

2026.693 + 91.105 × TDB 1119.810 4443.0 199

EL2.2 512342.957 + -

1910.714 × TDB

8956.395 + 182.209 × TDB 2331.630 4443.0 67

EL3.1 144563.535 -

531.824× TDB

minimum of (0, 1260.079 + 43.300 

× TDB) 1118.925 1839.210 250

EL3.2 276119.033 -

983.238 × TDB

1897.460 + 94.396 × TDB 1118.925 -3818.060 + 

86.565 × TDB

250

EL3.3 372354.679 -

1278.137 × TDB

1676.031 + 174.565 × TDB 2331.630 -3818.060 + 

86.565 × TDB

250

EL3.4 482780.770 -

1599.533 × TDB

-250.892 + 279.128 × TDB 2331.630 -3818.060 + 

86.565 × TDB

250

EL4.1 146357.810 -

536.064 × TDB

minimum of (0, 1209.806 + 43.485 

× TDB) 872.076 1042.246 250

EL4.2 268626.142 + -

952.497 × TDB

1768.857 + 93.981 × TDB 1003.000 -5806.649 + 

100.741× TDB

250

EL4.3 376527.857 -

1281.478 × TDB

1189.700 + 169.438 × TDB 1602.105 -5806.649 + 

100.741× TDB

250

EL4.4 473718.131 -

1563.307 × TDB

-576.808 + 264.766 × TDB 2466.602 -5806.649 + 

100.741× TDB

250

7.2.2.4 Energy Consumption 

The hourly energy consumption was calculated for each hour as the number of CUAC 

units multiplied by the power consumption derived from the equations for the components listed 

in the preceding tables. Powers for the compressor and condenser fan (where appropriate) were 

multiplied by LF and CD, much like the process used in the AHRI rating standard, to account for 

loading and cycling effects. The controls power was assumed to be constant for each stage. The 

indoor fan power was multiplied by the fraction of an hour of fan operation but not by LF or CD. 

7.2.3 Energy Decrements

DOE calculated the energy reduction provided by operating higher-efficiency CUAC 

equipment relative to baseline equipment as the difference in energy consumption for each hour. 

7-12 
The savings in cooling energy represent the combined energy savings of the compressor and the 

condenser fan. The fan and controls energy decrements are the difference between the energy use 

of the efficiency level and the baseline. The calculated hourly energy decrements are used in the 

calculations of operating costs, as described in chapter 8. 

7.2.4 Results

Provided here are results for the baseline and four ELs analyzed for the 7.5-, 15-, and 30-

ton CUAC equipment. Results are presented for the both the annual energy required for cooling 

and the annual energy use required for the ventilation or supply fan. 

Figure 7.2.5 and Figure 7.2.6 show the annual cooling and fan energy use results, 

respectively, for 7.5-ton CUAC equipment. Because results for all 1,033 buildings are being 

reported, buildings are ordered from highest to lowest annual energy use. Energy use scales with 

building size, so very large annual energy use corresponds to large building floor area. As the 

range of building size and annual energy use is very high, a logarithmic scale is used for the yaxis in each figure to report energy use. The primary purpose of the figures is to demonstrate 

that as EL increases, the annual energy use for both cooling and fan operation decrease as well. 

In the case of EL4, a 3-stage compressor system and a variable-speed fan are used to improve 

efficiency. The EL4 design has a more pronounced impact on improving part-load performance 

than the other ELs. As a result, the impact of EL4 on reducing annual energy use is more 

dependent on how often the CUAC equipment operates in part-load. As a result, the reduction in 

the annual energy use is more variable than the other ELs. 

Figure 7.2.7 and Figure 7.2.8 show the annual cooling and fan energy use results, 

respectively, for 15-ton CUAC equipment. Figure 7.2.9 and Figure 7.2.10 show the same for 30-

ton CUAC equipment. 

7-13 
Figure 7.2.5 Annual Cooling Energy Use by Efficiency Level for 7.5-ton Equipment

Figure 7.2.6 Annual Fan Energy Use by Efficiency Level for 7.5-ton Equipment

100

1000

10000

100000

1000000

10000000

Building Energy Use for Cooling (kWh/yr)

Building ID (from highest to lowest energy use)

Baseline

EL 1

EL 2

EL 3

EL 4

100

1000

10000

100000

1000000

10000000

Building Fan Energy Use (kWh/yr)

Building ID (from highest to lowest energy use)

Baseline

EL 1

EL 2

EL 3

EL 4

7-14 
Figure 7.2.7 Annual Cooling Energy Use by Efficiency Level for 15-ton Equipment

Figure 7.2.8 Annual Fan Energy Use by Efficiency Level for 15-ton Equipment 

1000

10000

100000

1000000

10000000

Building Energy Use for Cooling (kWh/yr)

Building ID (from highest to lowest energy use)

Baseline

EL 1

EL 2

EL 3

EL 4

1000

10000

100000

1000000

10000000

Building Fan Energy Use (kWh/yr)

Building ID (from highest to lowest energy use)

Baseline

EL 1

EL 2

EL 3

EL 4

7-15 
 Figure 7.2.9 Annual Cooling Energy Use by Efficiency Level for 30-ton Equipment

 Figure 7.2.10 Annual Fan Energy Use by Efficiency Level for 30-ton Equipment

1000

10000

100000

1000000

10000000

Building Energy Use for Cooling (kWh/yr)

Building ID (from highest to lowest energy use)

Baseline

EL 1

EL 2

EL 3

EL 4

1000

10000

100000

1000000

10000000

Buidling Fan Energy Use (kWh/yr)

Building ID (from highest to lowest energy use)

Baseline

EL 1

EL 2

EL 3

EL 4

7-16 
7.3 GENERALIZED BUILDING SAMPLE

DOE constructed a “generalized building sample” to represent the installation conditions 

for the equipment covered in this rulemaking. Only floor space cooled by the covered equipment 

is incorporated into the sample. Conceptually, the main difference between the generalized 

building sample (GBS) and the sample of specific commercial buildings compiled in CBECS is 

that the GBS aggregates all building floor space associated with a particular set of building 

characteristics into a single category.

7.3.1 Data Sources 

The generalized building sample was developed based on data from the U.S. Energy 

Information Administration’s (EIA’s) 2003 Commercial Buildings Energy Consumption Survey 

(CBECS) and from the Commercial Demand Module of the National Energy Modeling System 

(NEMS) version distributed with EIA’s Annual Energy Outlook 2013.4, 5, 6

The amount of floor space allocated to each category for buildings built in or before 2003 

was taken from the 2003 CBECS. CUAC-cooled commercial floor space was estimated by 

taking the CBECS entries with main cooling equipment identified as “packaged cooling.” To 

update the building floor space to 2013, the commercial building data included with the 2013 

version of NEMS were used. This dataset includes a historical component, starting in 2004, and 

provides both existing floor space and new floor space additions by year, census division and 

building activity. 

CBECS and NEMS differ somewhat in their estimate of the total building stock. In order 

to have a consistent baseline, DOE adjusted the NEMS floor space estimates to coincide with the 

CBECS estimate of total building stock. DOE projected 2004 floor space by Census division 

and building activity through linear regression of previous CBECS floor space data (1979, 1983, 

1986, 1989, 1992, 1995, 1999, 2003). By comparing the CBECS-based projections of 2004 floor 

space and historical 2004 NEMS floor space, DOE defined correction factors as a function of 

Census division and building activity. The cross product of the Census division and building 

activity correction factors were applied to NEMS data for 2004 – 2013, so the combined data set 

uses CBECS as a baseline. 

7.3.2 Commercial Building Characteristics

The set of characteristics that are used to define a category include all building features 

that are expected to influence either the cooling load and energy use, or the energy costs. The set 

of building characteristics, and the specific values these characteristics can take, are listed in

Table 7.3.1. 

7-17 
Table 7.3.1 Characteristics and Associated Values Used to Define the Generalized 

Building Sample 

Characteristic Number of Values Range of Values

Region 10 9 Census divisions with Pacific sub-divided into North 

and South

Building Activity 7 Assembly, Education, Food Service, Small Office, Large 

Office, Mercantile, Warehouse

Size (based on 

annual energy 

consumption)

3 

Small: < 100,000 kWh/yr

Medium: 100,000 to 1,000,000 kWh/yr 

Large: > 1,000,000 kwh/yr

Vintage (year of 

construction) 3 

Category 1: before 1950

Category 2: 1950-1979 

Category 3: 1980 and later

 

The region in which the building is located affects both the cooling loads (through the 

weather) and the cost of electricity. The building activity affects building schedules and 

occupancy, which in turn influence the demand for cooling and internal loads. The building 

activity categories used here are those defined in the NEMS commercial building energy demand 

module, limited to those building types that use the equipment covered in this rule. The building 

size influences the cost of electricity, because larger facilities tend to have lower marginal prices. 

The building vintage may influence shell characteristics that can affect the cooling loads. The 

combination of 10 regions, 7 building types, 3 sizes and 3 vintages leads to a set of 630 

independent categories in the GBS. Tables 7.3.2 -7.3.5 summarize various characteristics of

CUAC-cooled commercial floor space in each building category. 

Table 7.3.2 summarizes commercial floor space by Census division. The Pacific division 

is separated into North (WA and OR) and South (CA) sub-divisions based on climate zone, as 

defined in 2003 CBECS Floor space in climate zones 1, 2, and 3 are assigned to the North subdivision, and climate zones 4 and 5 are assigned to the South sub-division. The CBECS data set 

does not include HI and AK. 

 

7-18 
Table 7.3.2 Floor Space by Region 

Census Division or 

Region Number Region

Floor Space

(million sq.ft.)

Percent of

Floor Space

1 New England 872 3%

2 Middle Atlantic 4,769 16%

3 East North Central 5,126 18%

4 West North Central 2,567 9%

5 South Atlantic 5,391 19%

6 East South Central 1,537 5%

7 West South Central 3,283 11%

8 Mountain 1,603 5%

9.1 Pacific (North) 1,034 0%

9.2 Pacific (South) 2,738 4%

Source: CBECS 2003

Table 7.3.3 summarizes commercial floor space by primary building activity (PBA). The 

numerical labels associated with PBA are taken from the NEMS data set and differ from the 

numerical labels used in CBECS. Floor space is aggregated based on AEO 2013 building 

categories. 

Table 7.3.3 Floor Space by Building Activity 

PBA 

Number

Primary Building 

Activity

Floor Space 

(million sq.ft.)

Percent of Total 

Floor Space*

Percent of

Package-Cooled 

Floor Space*

1 Assembly 3,450 11% 12%

2 Education 4,217 14% 15%

4 Food Service 988 2% 3%

7 Large Office 2,921 8% 10%

8 Small Office 3,361 10% 12%

9 Mercantile 4,190 21% 14%

10 Warehouse 4,232 8% 15%

* Will not sum to 100% of floor space because there are other building activities that were excluded from analysis 

because they are not expected to use CUAC.

Source: CBECS 2003

Table 7.3.4 summarizes commercial floor space by annual energy consumption size bin 

and Table 7.3.5 shows the distribution of floor space by size and by region. Size bins were 

constructed based on annual energy consumption data included in 2003 CBECS. This definition 

of building size is chosen to be consistent with the way that utility companies assign consumers 

to tariffs, which is typically based on annual peak electricity demand. Annual electricity 

7-19 
consumptions correlates very strongly with annual peak demand, and as only consumption is 

included with the AEO commercial floor space data, it is used to segregate buildings by size.

Table 7.3.4 Floor Space by Size (Annual Energy Consumption) 

Size Bin

Annual Energy 

Consumption 

(kWh/yr)

Floor Space 

(million sq.ft.)

Percent of

Floor Space

Small < 100,000 18,856 28%

Medium 100,000 to 1,000,000 24,981 38%

Large > 1,000,000 22,595 34%

Source: CBECS 2003

Table 7.3.5 Floor Space Distribution by Size and Region 

Region Large Medium Small

1 29% 34% 37%

2 34% 35% 30%

3 36% 41% 24%

4 23% 40% 37%

5 39% 35% 26%

6 28% 40% 32%

7 33% 39% 28%

8 33% 40% 27%

9.1 31% 44% 25%

9.2 38% 33% 29%

Table 7.3.6 summarizes commercial floor space by construction vintage. These values 

were estimated by combining CBECS 2003 and AEO 2013 data as described above. 

Additionally, demolition since 2003 is accounted for in the older building stock bins. DOE 

estimated the rate of demolition based on the floor space attrition parameters published in the 

NEMS Commercial Demand Module documentation. 

Table 7.3.6 Floor Space by Vintage 

Vintage

Floor Space

(million sq.ft.)

Percent of

Floor Space

Pre – 1950 4,490 13%

1950 - 1979 11,356 32%

1980 - 2011 19,878 56%*

* 1980 – 2011 vintage bin is constructed using both CBECS and scaled AEO data.

Source: CBECS 2003, AEO 2013

The distribution of floor space by building activity, region and vintage is graphically 

represented in Figure 7.3.1. The figure columns show floor space in millions of square feet by 

vintage category and region. The distribution by PBA is represented by the different color 

7-20 
stacked bars in each column. Large (> 50,000 square feet) and small office spaces are shown 

separately. The health care category includes only inpatient facilities; outpatient health care floor 

space is aggregated into the office category. Warehouse floor space is non-refrigerated only. 

Figure 7.3.1 Distribution of Floor Space in 2011 by PBA, Region, and Vintage 

7.3.3 Interpolation of Weights across Building Characteristics 

The weighting used in the life-cycle cost and payback period analysis (chapter 8) is based 

on the relative probability that a piece of equipment of given capacity (a "unit") would see the 

specific operating conditions and energy prices associated with the size, region, building activity 

and vintage of a member of the generalized building sample. These probabilities are determined 

by estimating the total required cooling capacity for each of the generalized buildings in the 

sample. This total required capacity is equal to the required capacity per square foot times the 

total cooled floor space. The required capacity per square foot is an output of the simulations of 

the 1033 buildings that use the covered equipment. This value is calculated for the sample as a 

whole, and varies somewhat with equipment capacity, as shown in Table 7.3.7. The table also 

shows the capacity per square foot separately for warm and cool climates. Here the warm climate

is defined as regions 5 (South Atlantic), 6 (ESC), 7 (WSC) and 8 (Mountain). Although 

geographically region 8 includes several cool northern states, the population is located primarily 

in the warmer southern states. 

For building vintages earlier than 2003, the total cooled floor space as a function of 

region, size, PBA and vintage was estimated in a two-step process. First, the distribution of all 

7-21 
floor space as a function of these four variables was calculated by multiplying the total floor 

space times the percentage factors show in Table 7.3.2 though Table 7.3.6. Second, the amount 

of floor space cooled by packaged equipment was estimated by multiplying total floor space 

times a percentage factor that varies with building activity, shown in the last column of table 

Table 7.3.2. For vintages after 2004 which use the AEO data, the distribution of all floor space 

by region, vintage, size and PBA is determined in the same way. To estimate the floor space 

cooled by packaged equipment, the factors defined from the CBECS 2003 data and listed in 

Table 7.3.3 were used, as no comparable data were available from the AEO. In developing these 

floor space estimates, any buildings for which the required capacity was less than 90% of the 

capacity of the representative unit were removed from the sample.

Table 7.3.7 Required capacity in tons per square foot for different regions and 

representative unit capacities

Region 7.5 ton 15 ton 30 ton

US 0.00260 0.00273 0.00268

warm 0.00286 0.00298 0.00276

cool 0.00236 0.00252 0.00262

7.3.4 Assigning Electricity Load Profiles to Generalized Buildings

Load profiles for each of the 630 generalized buildings were developed from the 

simulation data described above in Section 7.2. For each capacity category, a subset of the 1,033 

buildings was used to develop the cooling energy use profiles. The subset was defined by 

excluding the buildings with a capacity requirement that is significantly smaller than the capacity 

of the representative unit. The building capacity lower bound is 5 tons for the 7.5 ton sample, 

12.5 tons for the 15-ton sample, and 27 tons for the 30-ton sample. For each GBS type, a 

weighted average energy use profile was compiled from the simulated building subset, with the 

weights defined as the required capacity for the building multiplied by the CBECS building 

weight. The average was taken over all buildings in the subset that have the same region, 

building type, size and vintage category as the GBS category. For some of the GBS categories, 

no simulation data were available. In these cases the weighted-average energy use profile for the 

same building type and a nearby region or vintage were used. 

Updating the sample to 2013 required some additional adjustments to the energy use data. 

The 1,033 building simulations used TMY2 weather data.7 The TMY2 weather data files were 

updated to TMY3 in 2008.8 A comparison of the two datasets showed that total annual cooling 

degree-days (CDD) have increased by 5% at all locations used in this analysis, as shown in 

Figure 7.3.2. The figure shows the cooling degree days (CDD) relative to 65 deg F computed 

from the TMY3 data vs. the CDD for TMY2. The calculation is done separately for day time (8 

am to 8pm) and night time hours Each point corresponds to a state; in cases where there are 

multiple stations in a single state the data are averaged. As the TMY3 data are considered to be 

more representative of current weather, the increase in CDD is accounted for by increasing the 

energy use (for all efficiency levels) by 5% at all locations. The maximum daily temperatures, 

which may affect equipment sizing, were also compared between TMY2 and TMY3. In this case 

7-22 
there is less than a 1% increase in the TMY3 data over TMY2, so no adjustments to equipment 

sizing were made.

Figure 7.3.2 Comparison of cooling degree days by state for TMY3 and TMY2 

Changes to building shell characteristics and internal loads in recent construction can lead 

to a change in the energy required to meet a given cooling load. The NEMS commercial demand 

module accounts for these trends by adjusting the cooling energy use by a factor that is a 

function of region and building activity. These factors can be either less than one indicating an 

relative decrease in energy consumption for cooling, or positive, indicating an increase. In the 

generalized building sample, these same factors are used to adjust the cooling energy use for 

floor space in the generalized buildings sample constructed after 1999 included in vintage 

category 3 (Table 7.3.8). These factors represent an average expected increase or decrease in 

required cooling energy, relative to the assumptions encoded in the 1033 simulation sample 

which was based on CBECS 1995 building characteristics. 

Table 7.3.8 Factors used to represent relative changes in required cooling energy for 

vintage category 3. 

PBA

Region

1 2 3 4 5 6 7 8 9.1 9.2

1 0.966 0.889 0.978 0.926 0.888 0.865 0.783 0.91 0.768 0.768

2 0.96 0.603 0.963 0.911 0.873 0.748 0.805 0.915 0.77 0.77

4 1.047 1.029 1.036 1.009 1.018 1.016 1.014 1.03 1.024 1.024

7 0.98 0.913 0.989 0.966 0.883 0.883 0.849 0.945 0.786 0.786

8 0.985 0.934 0.982 0.952 0.896 0.848 0.871 0.92 0.857 0.857

9 1.048 0.952 0.998 1.035 0.953 0.907 0.905 0.952 0.795 0.795

10 0.807 0.872 0.816 0.851 0.852 0.864 0.809 0.762 0.622 0.622

7-23 
7.3.5 CUAC Energy Use Results

Table 7.3.9 - Table 7.3.11 show the annual energy use results for 7.5-, 15-, and 30-ton 

CUAC equipment, respectively, by efficiency level. Each set of results are based on the GBS 

that was developed for each CUAC tonnage category. Because each GBS consists of 630 

independent categories or records, the energy use being reported for cooling, fan operation, and 

the total are weighted-averages across the entire GBS sample. The weighted-average calculation 

was performed based on the total capacity assigned to each GBS category. The energy use results 

are provided by cooling capacity (i.e., ton), square foot, and unit. 

The energy use for cooling and fan operation for each of the 630 independent categories 

in the GBSs are provided in the Microsoft Excel spreadsheet model developed for the life-cycle 

cost (LCC) and payback period (PBP) analysis. In the spreadsheet model, there are worksheets 

labeled “7.5 ton,” “15 ton,” and “30 ton” which contain the GBS for each CUAC equipment size. 

The Microsoft Excel spreadsheet is accessible over the Internet 

(http://www1.eere.energy.gov/buildings/appliance_standards/buildings/appliance_standards/prod

uct.aspx/productid/77). 

Table 7.3.9 7.5-ton CUAC Equipment: Annual Energy Use Results by Efficiency Level

Cooling Fan Total Cooling Fan Total Cooling Fan Total

Region EL IEER kWh/ton kWh/ton kWh/ton kWh/sq.ft. kWh/sq.ft. kWh/sq.ft. kWh/unit kWh/unit kWh/unit

U.S. Base 11.4 1,035 709 1,744 2.7 1.8 4.5 7,764 5,318 13,082

U.S. 1 12.9 886 640 1,526 2.3 1.7 4.0 6,647 4,796 11,443

U.S. 2 14.0 853 565 1,418 2.2 1.5 3.7 6,401 4,235 10,636

U.S. 3 14.8 653 244 898 1.7 0.6 2.3 4,899 1,833 6,732

U.S. 4 19.9 331 137 468 0.9 0.4 1.2 2,481 1,029 3,511

Warm Base 11.4 1,240 695 1,935 3.5 2.0 5.5 9,300 5,216 14,516

Warm 1 12.9 1,073 627 1,701 3.1 1.8 4.9 8,051 4,705 12,756

Warm 2 14.0 1,009 554 1,563 2.9 1.6 4.5 7,567 4,155 11,722

Warm 3 14.8 826 255 1,081 2.4 0.7 3.1 6,193 1,911 8,104

Warm 4 19.9 475 142 616 1.4 0.4 1.8 3,559 1,062 4,621

Cool Base 11.4 867 720 1,587 2.0 1.7 3.7 6,500 5,401 11,902

Cool 1 12.9 732 650 1,382 1.7 1.5 3.3 5,491 4,872 10,363

Cool 2 14.0 726 573 1,299 1.7 1.4 3.1 5,442 4,301 9,743

Cool 3 14.8 511 236 747 1.2 0.6 1.8 3,834 1,769 5,603

Cool 4 19.9 213 134 346 0.5 0.3 0.8 1,594 1,003 2,597

7-24 
Table 7.3.10 15-ton CUAC Equipment: Annual Energy Use Results by Efficiency Level

Cooling Fan Total Cooling Fan Total Cooling Fan Total

Region EL IEER kWh/ton kWh/ton kWh/ton kWh/sq.ft. kWh/sq.ft. kWh/sq.ft. kWh/unit kWh/unit kWh/unit

U.S. Base 11.2 1,000 523 1,523 2.7 1.4 4.2 15,005 7,845 22,850

U.S. 1 12.2 919 477 1,396 2.5 1.3 3.8 13,785 7,151 20,936

U.S. 2 13.2 797 443 1,240 2.2 1.2 3.4 11,955 6,645 18,600

U.S. 3 14.2 881 222 1,102 2.4 0.6 3.0 13,212 3,324 16,536

U.S. 4 18.4 594 231 825 1.6 0.6 2.3 8,916 3,463 12,379

Warm Base 11.2 1,186 512 1,698 3.5 1.5 5.1 17,784 7,679 25,463

Warm 1 12.2 1,093 467 1,559 3.3 1.4 4.7 16,389 6,999 23,389

Warm 2 13.2 960 434 1,394 2.9 1.3 4.2 14,402 6,511 20,914

Warm 3 14.2 1,034 223 1,257 3.1 0.7 3.8 15,514 3,346 18,860

Warm 4 18.4 731 242 972 2.2 0.7 2.9 10,960 3,624 14,584

Cool Base 11.2 848 532 1,380 2.1 1.3 3.5 12,718 7,982 20,700

Cool 1 12.2 776 485 1,261 2.0 1.2 3.2 11,643 7,276 18,918

Cool 2 13.2 663 450 1,113 1.7 1.1 2.8 9,941 6,755 16,696

Cool 3 14.2 755 220 975 1.9 0.6 2.5 11,318 3,306 14,624

Cool 4 18.4 482 222 704 1.2 0.6 1.8 7,234 3,331 10,565

Table 7.3.11 30-ton CUAC Equipment: Annual Energy Use Results by Efficiency Level

Cooling Fan Total Cooling Fan Total Cooling Fan Total

Region EL IEER kWh/ton kWh/ton kWh/ton kWh/sq.ft. kWh/sq.ft. kWh/sq.ft. kWh/unit kWh/unit kWh/unit

U.S. Base 10.1 869 913 1,782 2.3 2.4 4.8 26,067 27,404 53,471

U.S. 1 11.6 734 842 1,576 2.0 2.3 4.2 22,030 25,259 47,290

U.S. 2 12.5 663 837 1,500 1.8 2.2 4.0 19,881 25,117 44,997

U.S. 3 13.5 620 443 1,063 1.7 1.2 2.8 18,610 13,281 31,892

U.S. 4 15.5 575 304 879 1.5 0.8 2.4 17,264 9,110 26,373

Warm Base 10.1 1,053 889 1,941 2.9 2.5 5.4 31,577 26,659 58,236

Warm 1 11.6 899 819 1,718 2.5 2.3 4.7 26,982 24,571 51,552

Warm 2 12.5 817 814 1,632 2.3 2.2 4.5 24,521 24,433 48,953

Warm 3 13.5 768 456 1,224 2.1 1.3 3.4 23,039 13,674 36,713

Warm 4 15.5 712 322 1,034 2.0 0.9 2.9 21,370 9,645 31,015

Cool Base 10.1 718 934 1,652 1.9 2.4 4.3 21,533 28,017 49,550

Cool 1 11.6 599 861 1,459 1.6 2.3 3.8 17,956 25,826 43,782

Cool 2 12.5 535 856 1,391 1.4 2.2 3.6 16,063 25,679 41,742

Cool 3 13.5 499 432 931 1.3 1.1 2.4 14,966 12,958 27,924

Cool 4 15.5 463 289 752 1.2 0.8 2.0 13,885 8,669 22,554

7-25 
REFERENCES

1. U.S. Department of Energy, Energy Conservation Program for Commercial and 

Industrial Equipment: Energy Conservation Standards for Commercial Unitary Air 

Conditioners and Heat Pumps Advance Notice of Proposed Rulemaking, Office of 

Energy Efficiency and Renewable Energy, Editor. 2004: Washington, D.C. 

http://www.regulations.gov/#!documentDetail;D=EERE-2006-STD-0103-0003

2. U.S. DEpartment of Energy, Technical Support Document: Energy Efficiency Program 

for Commercial and Industrial Equipment: Commercial Unitary Air Conditioners and 

Heat Pumps, Office of Energy Efficiency and Renewable Energy, Editor. 2004: 

Washington, D.C. http://www.regulations.gov/#!documentDetail;D=EERE-2006-STD0103-0078

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August, 2013.) <http://www.eia.gov/forecasts/aeo/>

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<http://www.eia.gov/consumption/commercial/data/2003/index.cfm?view=microdata>

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<http://www.eia.gov/forecasts/aeo/assumptions/pdf/commercial.pdf>

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Typical Meterological Year 2, <http://rredc.nrel.gov/solar/old_data/nsrdb/1961-

1990/tmy2/>

8. National Renewable Energy Laboratory, National Solar Radiation Data Base 1991-2005 

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2005/tmy3/>

7-26