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CHAPTER 5: LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS

5.1 INTRODUCTION

This chapter describes the method for analyzing the economic impacts of possible standards

on individual consumers. The effect of standards on individual consumers include a change in

operating expense (usually decreased) and a change in purchase price (usually increased). This

chapter describes three metrics used in the consumer analysis to determine the effect of standards

on individual consumers:

• Life-cycle cost (LCC) captures the tradeoff between purchase price and operating

expenses for appliances.

• Payback period (PBP) measures the amount of time it takes consumers to recover

the assumed higher purchase expense of more energy-efficient equipment through

lower operating costs.

• Rebuttable Payback Period is a special case of PBP. Where LCC and PBP are

estimated over a range of inputs reflecting actual conditions, Rebuttable Payback

Period is based on laboratory conditions, specifically, DOE test procedure inputs.

These are discussed in sections 5.2, 5.3 and 5.4 of this chapter, respectively. Inputs and preliminary

results are presented for each metric. Key variables, current assumptions, and calculations are

presented for each metric. The calculations discussed here are performed on a series of Microsoft

Excel spreadsheets which are accessible over the Internet. Details and instructions for the

spreadsheets are discussed in section 5.5. A more complete set of results are presented in Appendix

E.

5.1.1 General Approach for LCC and PBP Analysis

In recognition that each building where air conditioners or heat pumps are used is unique,

variability and uncertainty is analyzed by performing the LCC and PBP calculations detailed here

for a representative sample of individual households and commercial buildings. The analysis takes

into account equipment use in commercial buildings based on the assumption that 10% of equipment

applications are in commercial buildings. The results are expressed as the number of buildings

experiencing economic impacts of different magnitudes. The LCC and PBP model was developed

using Microsoft Excel spreadsheets combined with Crystal Ball (a commercially available add-in).

The LCC and PBP analyses explicitly model both the uncertainty and the variability in the

model’s inputs using Monte Carlo simulation and probability distributions. A detailed explanation

of Monte Carlo simulation and the use of probability distributions is contained in Appendix A. 

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The LCC and PBP results are displayed as distributions of impacts compared to the baseline

conditions. Results are presented at the end of this chapter and are based on 10,000 samples per

Monte Carlo simulation run. A variety of graphic displays will be created to illustrate the

implications of the analysis. Examples would be: 1) a cumulative probability distribution showing

the percentage of consumers that would experience a net savings by owning a more energy efficient

appliance, and 2) a frequency chart depicting variation in life-cycle cost for each efficiency level

considered.

5.1.2 Overview of LCC, PBP, and Rebuttable PBP Inputs

LCC is the total consumer expense over the life of the appliance, including purchase expense

and operating costs (including energy expenditures). Future operating costs are discounted to the

time of purchase and summed over the lifetime of the appliance. The PBP is the change in purchase

expense due to an increased efficiency standard divided by the change in annual operating cost that

results from the standard. 

Inputs to the LCC and PBP analysis are categorized as follows: 1) inputs for establishing the

purchase expense, otherwise known as the total installed cost, and 2) inputs for calculating the

operating cost. 

The primary inputs for establishing the total installed cost are:

• Baseline manufacturer cost: The cost to manufacture equipment meeting existing

minimum efficiency standards.

• Standard-level manufacturer cost multiplier: The multiplicative factor used for

calculating the manufacturer cost associated with each standard-level.

• Markups and Sales Tax: The markups associated with converting the manufacturer

cost to a consumer price. Three sets of markups were assumed for the LCC and PBP

analysis: manufacturer markup – markup for converting the manufacturer cost to the

cost distributors or wholesalers pay for the equipment, distributor markup – markup

for converting the distributor or wholesaler cost to the cost contractors or dealers pay

for the equipment, dealer markup – markup for converting the dealer or contractor

cost to the price which builder or consumers pay for the equipment, and builder

markup – markup for converting the builder cost to the price which consumers pay

for the equipment (applies only to the new construction market). In addition to the

markups, a sales tax was developed.

• Installation price: The cost to the consumer of installing the equipment. The

installation price represents all costs required to install the equipment other than the

marked-up equipment cost. The installation price includes labor, overhead, and any

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miscellaneous materials and parts such as linesets. Thus, the total installed cost

equals the consumer equipment price (manufacturer cost multiplied by the various

markups plus sales tax) plus the installation price. 

The primary inputs for calculating the operating cost are:

• Annual energy consumption: For central air conditioners, the annual energy

consumption is the annual site energy use associated with providing space-cooling.

For heat pumps, the annual energy consumption is the annual site energy use

associated with providing both space-cooling and space-heating. For households, the

annual energy consumption is based on data from the 1997 Residential Energy

Consumption Survey (RECS). For those households surveyed in RECS with either

a central air conditioner or heat pump, the estimated annual energy consumption

corresponds to the household’s stock equipment, specifically its capacity and

efficiency. For equipment used in commercial buildings, the annual energy

consumption is determined through computer simulations of 77 nationally

representative commercial buildings based on assumptions similar to what were used

to develop the American Society of Heating, Refrigeration, and Air-Conditioning

Engineers’ (ASHRAE) Standard 90.1-99.

• Equipment efficiency: The seasonal energy efficiency ratio (SEER) is the efficiency

descriptor for central air conditioners. For heat pumps, the cooling efficiency is

represented with the SEER while the heating efficiency is represented with the

heating seasonal performance factor (HSPF). Central air conditioner and heat pump

efficiencies in existing households are primarily based on data from the 1997 RECS.

For equipment used in commercial buildings, all buildings were assumed to have

equipment efficiencies equal to existing minimum efficiency standards. To estimate

the annual energy consumption associated with a particular standard-level, the ratio

of the building’s stock efficiency to the standard-level efficiency is multiplied by the

buildings’s annual energy consumption. 

• Average electricity prices: The average price per kWh paid by each household for

electricity.

• Marginal electricity prices: The marginal price per kWh paid by each household for

electricity. 

• Electricity price trends: The Annual Energy Outlook 2000 (AEO00) was used to

forecast electricity prices into the future. For the results presented here, the AEO00

Reference case was used to forecast future electricity prices.

• Maintenance costs: The cost associated with maintaining the operation of the

equipment (e.g., cleaning heat exchanger coils, checking refrigerant charge levels).

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• Repair costs: The cost associated with repairing or replacing component failures. 

• Lifetime: The age at which the central air conditioner or heat pump is retired from

service. 

• Discount rate: The rate at which future expenditures are discounted to establish their

present value. 

Figure 5.1 graphically depicts the relationships between the installed cost and operating cost

inputs for the calculation of the LCC, PBP, and Rebuttable PBP. All of the inputs depicted in

Figure 5.1 that are needed for the determination of LCC, PBP, and Rebuttable PBP are discussed in

detail in Section 5.2.

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Baseline

Manufacturer Cost

Standard-Level

Manufacturer Cost

Multiplier

Distributor Markup

Dealer Markup

Sales Tax

Manufacturer

Markup

Installation Cost

Total Installed

Cost

Equipment

Efficiency

Average Electricity

Prices

Annual Energy

Consumption

(RECS or

Commercial)

Equipment Price

Marginal

Electricity Prices

Lifetime Operating

Expense

Annual Energy

Expense

(RECS or

Commercial)

Lifetime

Repair Cost

Discount Rate

Maintenance Cost

Electricity Price

Trend

Annual Operating

Expense

(RECS or

Commercial)

Payback Period

Life-Cycle Cost

Annual Energy

Consumption

(DOE test proc.)

Annual Energy

Expense

(DOE test proc.)

Annual Operating

Expense

(DOE test proc.)

Rebuttable

Payback Period

Builder Markup

Figure 5.1 Flow Diagram of LCC, PBP, and Rebuttable PBP Inputs

5.1.3 Use of Residential Energy Consumption Survey (RECS) in LCC and PBP Analysis

The LCC and PBP calculations detailed here are for a representative sample of individual

households and commercial buildings. Ninety percent of equipment applications are assumed to be

in households. For equipment used in households, the 1997 Residential Energy Consumption Survey

(RECS)1

 serves as the basis for determining the representative sample. The 1997 RECS is based on

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a

 The number of households actually used in the central air conditioner and heat pump LCC and PBP analyses

were 1218 and 308, respectively. Some central air-conditioned households were dropped from the analysis for one or

more of the following reasons: 1) the central air conditioner was not used, 2) a room air conditioner was present and used,

or 3) marginal energy prices could not be determined for the household. With regard to households with heat pumps,

they were dropped from the analysis for one or more of the following reasons: 1) the heat pump was not used or 2)

marginal energy prices could not be determined for the household.

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a sample of 5,900 households which were surveyed for information on their housing units, energy

consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior.

The information collected represents all households nationwide – approximately 101 million. 

RECS is conducted every three years directly form energy end users. The 1997 RECS is the

tenth survey of residential housing units conducted by the U.S Department of Energy’s (DOE)

Energy Information Administration (EIA). Previous RECS were conducted annually form 1978 to

1982 and triennially since 1984. The RECS consists of three parts:

• Personal interviews with households for information about energy used, how it is

used, energy-using appliances, structural features, energy efficiency measures, and

demographic characteristics of the household.

• Telephone interviews with rental agents for households that have any of their energy

use included in their rent. This information augments information collected from

those households that may not be knowledgeable about the fuels used for space

heating or water heating.

• Mail questionnaires sent to energy suppliers (after obtaining permission from

households) to collect the actual billing data on energy consumption and

expenditures.

Of the 5900 households surveyed in the 1997 RECS, 2003 households representing 37.6%

of the housing population have a central air conditioner while 579 households representing 11.1%

of housing population have an electric heat pumpa

. Using the households in RECS that utilize a

central air conditioner or heat pump, LCC and PBP analyses are performed on a household-byhousehold basis to determine whether an increase in the minimum efficiency standard is

economically justified. 

Of the inputs necessary for the LCC and PBP analysis, there are four inputs (as depicted in

Figure 5.1) which are based on data from the 1997 RECS; 1) space-conditioning annual energy

consumption (RECS-based), 2) equipment efficiency, 3) average electricity price, and 4) marginal

electricity price. All four of these inputs are used in determining the operating cost. With the

exception of the equipment efficiency, each household in RECS with a central air conditioner or heat

pump has a unique value for the space-conditioning annual energy consumption, the average

electricity price, and the marginal electricity price. In other words, the annual energy consumption,

average electricity price, and marginal electricity price associated with a particular RECS household

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are not uncertain and are, therefore, not expressed with probability distributions. Although the above

three input variables are not uncertain, they are extremely variable. Due to the vast number of

households considered in the LCC and PBP analysis (over 1200 for central air conditioners and over

300 for heat pumps), the range of annual energy use, average electricity price, and marginal

electricity price is quite large (the actual ranges are presented and discussed later in this chapter).

Thus, although the above three input variables are not uncertain for any particular household, their

variability across all households contributes significantly to the range of LCCs and PBPs calculated

for any particular standard-level.

5.1.4 Commercial Building Analysis 

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

applications are assumed to be in commercial buildings. A representative sample of commercial

buildings where this equipment may be applied was developed based on assumptions consistent with

the process to update ASHRAE Standard 90.1, Energy Efficient Design of New Buildings Except

Low-Rise Residential Buildings2

.

In updating ASHRAE 90.1, 77 nationally representative commercial buildings (consisting

of seven different commercial building types in eleven different regions of the country) were

developed. These same 77 buildings were used for the LCC and PBP allowing for a building-bybuilding approach to be utilized for determining whether an increase in the standard is economically

justified (e.g., similar to the approach described above for households from the 1997 RECS). The

weighting given to each building (i.e., the percentage each building represents of the commercial

building stock) were based on data from the 1992 and 1995 Commercial Building Energy

Consumption Survey (CBECS)3,4. 

As with the analysis of residential buildings, four inputs are necessary (as depicted in Figure

5.1) from the commercial building analysis in order to perform the LCC and PBP calculations: 1)

space-conditioning annual energy consumption, 2) equipment efficiency, 3) average electricity price,

and 4) marginal electricity price. 

The space-conditioning energy consumption associated with each of the 77 buildings were

determined through computer modeling performed at Pacific Northwest National Laboratory (PNNL)

using the Building Loads and Systems Thermodynamics (BLAST) simulation tool5. The procedure

for calculating space-conditioning energy consumption relied on the determination of full-load

equivalent operating hours (FLEOH) for each of the 77 buildings. The determination of spacecooling and space-heating FLEOHs assumed that a single type of equipment, in our case residentialtype space-conditioning equipment, were used to condition the building. Once the FLEOHs were

determined, the corresponding annual energy consumption was established using the calculation

procedure specified in the Department of Energy’s (DOE) test procedure for determining annual

energy use. In determining both space-cooling and space-heating annual energy use, the DOE test

procedure requires equipment efficiencies as well as cooling and heating capacities. For purposes

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of developing LCCs and PBPs, all of the 77 nationally representative buildings are assumed to have

equipment efficiencies equal to the standard-level being analyzed. Equipment capacities for both

cooling and heating are assumed to be 36,000 Btu/hr.

The average and marginal electricity prices were developed through a procedure of matching

building peak demand characteristics for each of the 77 nationally representative buildings

(determined from the computer modeling analysis for establishing FLEOHs) to actual modeled

commercial tariffs and then calculating customer bills. The methodology for matching commercial

building peak demands to modeled tariffs is explained in a 1999 DOE report on marginal energy

prices6

. Energy bills are calculated for a baseline case (10 SEER) and a standards cases. Average

electricity prices are determined by taking the bill for the baseline case and dividing it by the amount

of energy consumed. Marginal electricity prices are determined by taking the bill difference between

the baseline and standard cases (in dollars) and dividing it by the usage difference (in kWh) to give

a “marginal” rate of $/kWh for that increment. For purposes of simplifying the analysis, a standardlevel increase of 20% was only considered. Thus, the marginal rate developed for a 20% increase

in the standard was assumed to be applicable for all standards cases. Since several tariffs were

applied to each building, both the average and marginal rates calculated from each tariff were

weighted by the number of customers covered by the tariff to come up with a weighted-average

marginal and average rate for each building. The above procedure was used to develop spacecooling average and marginal rates. Since detailed building loads and demands were not available

for space-heating, average rather than marginal electricity prices were used to determine the energy

costs associated with the operation of heat pumps during the space-heating season.

As with the residential buildings from the RECS sample, the annual energy consumption,

average electricity price, and marginal electricity price associated with each of the 77 commercial

buildings are not uncertain and are, therefore, not expressed with probability distributions. Although

the above three input variables are not uncertain, they are variable. Due to the number of buildings

considered in the LCC and PBP analysis, the range of annual energy use, average electricity price,

and marginal electricity price is large (the actual ranges are presented and discussed later in this

chapter). Thus, although the above three input variables are not uncertain for any particular building,

their variability across all buildings contributes significantly to the range of LCCs and PBPs

calculated for any particular standard-level.

5.2 LIFE-CYCLE COST (LCC)

5.2.1 Definition

Life-cycle cost is the total consumer expense over the life of an appliance, including purchase

expense and operating costs (including energy expenditures). Future operating costs are discounted

to the time of purchase, and summed over the lifetime of the appliance. Life-cycle cost is defined

by the following equation:

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EQP MFG =⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ( ) MM MU MU MU STD MFG DISTR DEAL MUBUILD ST (5.3)

LCC IC

OC

r

t

= + t ( ) 1+

(5.1)

IC EQP INST = + (5.2)

Where,

LCC = life-cycle cost,

IC = total installed cost ($),

P = sum over the lifetime, from year 1 to year N, where N = lifetime of appliance

(years),

OC = operating cost ($),

r = discount rate, and

t = year for which operating cost is being determined.

We treat total installed cost, operating cost, lifetime, and discount rate in turn in the following

sections.

5.2.2 Total Installed Cost Inputs

The total installed cost to the consumer is defined by the following equation:

Where,

EQP = equipment price (i.e., consumer price for only the equipment) ($) and

INST = consumer price to install equipment (i.e., the cost for labor and materials) ($).

The equipment price is defined by the following equation:

Where,

MFG = manufacturing cost of baseline (10 SEER) equipment ($),

MMSTD = standard-level manufacturer cost multiplier,

MUMFG = manufacturer markup,

MUDISTR = distributer or wholesaler markup,

MUDEAL = dealer or contractor markup,

MUBUILD = builder markup, and

ST = sales tax.

The remainder of this section provides information about the variables and assumptions used

to calculate the total installed cost for central air conditioners and heat pumps. For each variable,

the discussion includes:

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• definition;

• approach; and

• current assumptions.

Inputs for the determination of total installed cost are shown in Table 5.1.

Table 5.1 Inputs for Total Installed Costs

Baseline manufacturer cost ($)

Standard-level manufacturer cost multipliers

Manufacturer markup

Distributor or wholesaler markup

Dealer or contractor markup

Sales tax

Installation cost ($)

5.2.2.1 Baseline Manufacturer Cost

Definition

The cost to the manufacturer of producing baseline or minimum efficiency equipment.

Approach

Baseline manufacturer costs were developed by Arthur D. Little (ADL) through a reverse

engineering approach. Refer to Chapter 4, Section 4.2, Manufacturing Costs, for details on how the

costs were developed.

Assumptions

The manufacturer costs for minimum efficiency (i.e., 10 SEER) split air conditioners, split

heat pumps, package air conditioners, and package heat pumps are summarized in Table 5.2.

Table 5.2 Baseline Manufacturer Costs

Baseline Manufacturer Cost

System Type Without Air Handler With Air Handler

Split Air Conditioner $367 $449

Split Heat Pump - $572

Package Air Conditioner - $511

Package Heat Pump - $593

Since the life-cycle cost analysis is performed on a building-by-building basis using housing

data from the 1997 RECS and a nationally representative set of commercial buildings, the

determination of what manufacturer cost to use for split air conditioners is based on whether a warm-

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air central furnace is present in the household. If the building has a fuel-fired (gas-, oil-, or LPGfired) furnace, the “without air handler”split air conditioner manufacturer cost is used. Otherwise,

the “with air handler” cost is used.

5.2.2.2 Standard-Level Manufacturer Cost Multipliers

Definition

The multiplicative factor used for calculating the manufacturer cost associated with each

standard-level. The factor is multiplied by the baseline manufacturer cost to arrive at the standardlevel manufacturer cost. For example, if the average manufacturer cost multiplier for 11 SEER split

system heat pumps is 1.10, its associated average manufacturer cost would equal the baseline

manufacturer cost of $572 multiplied by the average multiplier (1.10) or $629.

Approach

Data submittals from the Air Conditioning & Refrigeration Institute (ARI) were used for

developing the standard-level manufacturer cost multipliers. ARI collected data from its member

manufacturers and provided minimum, maximum, and weighted-mean values for each standard-level

and each product class. Please refer to Chapter 4, Section 4.2, Manufacturing Costs, for more details

on the ARI data submittal.

Assumptions

ARI provided minimum, maximum, and shipment weighted-mean values for each standardlevel. Because it was unknown as to how the ARI cost data were distributed, only the shipment

weighted-mean values were used in the LCC analysis. Table 5.3 provides the minimum, maximum,

and shipment weighted-mean values for only the standard-levels analyzed (11 through 13 SEER and

18 SEER (max tech)) for each product class. Of important note, since cost data were not provided

for the maximum technologically feasible standard-level (18 SEER), cost multipliers associated with

the highest efficiency level which data were provided (i.e., 15 SEER) were used as a proxy.

Table 5.3 ARI Standard-Level Manufacturer Cost Multipliers

Split A/C Split HP Package A/C Package HP

SEER Min Mean Max Min Mean Max Min Mean Max Min Mean Max

10 - 1.00 - - 1.00 - - 1.00 - - 1.00 -

11 1.03 1.16 1.30 1.05 1.10 1.15 1.03 1.19 1.27 1.06 1.14 1.25

12 1.09 1.36 1.55 1.11 1.24 1.35 1.15 1.30 1.40 1.06 1.28 1.50

13 1.30 1.63 1.90 1.17 1.44 1.66 1.40 1.63 1.75 1.45 1.60 1.90

18a 1.81 2.40 3.50 1.75 2.09 2.52 1.89 2.23 2.92 1.93 2.13 2.47

a

 Cost multipliers for 18 SEER are based on data for 15 SEER.

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0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.15 1.17 1.19 1.21 1.23 1.25 1.27 1.29 1.31 1.33 1.35 1.37 1.39 1.41 1.43 1.45

Manufacturer Markup

Probability

Figure 5.2 Distribution of Manufacturer Markups

5.2.2.3 Manufacturer Markup

Definition

The markup for converting the manufacturer cost to the cost which distributors or

wholesalers pay for space-conditioning equipment.

Approach

Manufacturer markups were developed by ADL. Please refer to Chapter 4, Section 4.3.2,

Determination of the Manufacturer Markup, for more details.

Assumptions

The manufacturer markups used in the LCC analysis were based on values of 1.18 and 1.41

which were assumed to be representative of 80% and 20% of the industry, respectively. A discrete

distribution consisting of the above two values was used in the analysis. Figure 5.2 shows the

distribution for the manufacturer markup. The weighted-average markup equals 1.23 (80% ] 1.18

+ 20% ] 1.41). 

The manufacturer markup was assumed to remain constant with increasing efficiency and

it was assumed to be applicable to all product classes. In addition, variations in the markup based

on market destination (i.e, whether the equipment would eventually be sold to the new construction

or replacement/retrofit market) were assumed to be negligible. In other words, the markup for the

new construction and replacement/retrofit markets were assumed to be identical.

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5.2.2.4 Distributor Markup

Definition

The markup for converting the distributor or wholesaler cost to the cost which contractors

or dealers pay for space-conditioning equipment.

Approach

Distributor markups were developed through an analysis of financial data for an average airconditioning wholesale business from data in the Air-conditioning & Refrigeration Wholesalers’

(ARW) 1998 Wholesaler Profit Survey Report. The results of the financial analysis were validated

with a econometric analysis of 1997 U.S. Census Bureau economic data of revenues and costs for

warm air heating and air conditioning equipment wholesalers. Please refer to Appendix D for more

details.

Assumptions

The analysis of distributor cost data revealed a measurable difference between the average

aggregate markup on the entire set of direct business costs and the incremental markup on only direct

equipment costs. In other words, for an incremental increase in the cost of the equipment, the

markup required to cover the incremental cost increase is distinctly different than the average

markup required to cover all business costs. From the financial analysis, the average aggregate

distributor markup was determined to be 1.36 and is assumed to cover the direct business costs that

are present at the current baseline (i.e., 10 SEER) level. The incremental distributor markup was

determined to be 1.11 and is assumed to cover incremental equipment cost increases, such as those

associated with increases in equipment efficiency. 

Because the econometric analysis provided a distribution of markup values rather than the

single-point values from the financial analysis, results from the econometric analysis were used to

represent the distributor markup. The econometric analysis yielded mean values for the average and

incremental markups which were only slightly different from the financial analysis (average and

incremental values of 1.37 and 1.09, respectively, as opposed to 1.36 and 1.11). The distribution

of incremental markups ranged from a minimum of 1.027 to a maximum of 1.155. Table 5.4 shows

the cumulative probabilities of the values pertaining to the incremental distributor markup. 

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Table 5.4 Cumulative Probability Distribution of Distributor/Wholesaler Markups

Distributor Markup Cumulative Probability

1.027 1%

1.056 10%

1.069 20%

1.077 30%

1.084 40%

1.091 50%

1.098 60%

1.105 70%

1.114 80%

1.126 90%

1.155 99%

Both the average and incremental distributor markups were assumed to apply to all product

classes. In addition, variations in the markup based on market destination (i.e, whether the

equipment would eventually be sold to the new construction or replacement/retrofit market) were

assumed to be negligible. In other words, the markup for the new construction and

replacement/retrofit markets were assumed to be identical.

5.2.2.5 Dealer Markup

Definition

The markup for converting the dealer or contractor cost to the price that either builders (for

equipment destined for the new construction market) or consumers (for equipment destined for the

replacement/retrofit market) pay for the space-conditioning equipment. 

Approach

Dealer markups were developed through an an analysis of financial data for an average

residential air-conditioning contractor from data in the Air Conditioning Contractor Association’s

(ACCA) Financial Analysis for the HVACR Contracting Industry, 1995 edition. The results of the

financial analysis were validated with an econometric analysis of 1997 U.S. Census Bureau

economic data of revenues and costs for the Heating, Ventilating, Air-Conditioning (HVAC)

contractor industry. Please refer to Appendix D for more details. 

Assumptions

The financial analysis of contractor cost data revealed a significant difference between the

markup required for covering labor and equipment expenses and the markup required for covering

only equipment expenses. The markup covering all business expenses was determined to be 1.53

while the markup for only equipment expenses was determined to have a mean value of 1.28.

Because the LCC analysis breaks out the contractor’s installation cost (i.e., the cost to install the

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equipment) from the cost which is charged for the equipment, only the markup value of 1.28 is

applicable for marking up the equipment. As with the distributor markup, a contractor markup

associated only with an incremental increase in equipment cost was also determined. Since the

incremental markup was shown to be close to the average value of 1.27, only the average markup

value was used in the analysis.

Because the econometric analysis provided a distribution of markup values rather than the

single-point values from the financial analysis, results from the econometric analysis were used to

represent the dealer markup. The econometric analysis yielded a mean value for the equipment

markup which was only slightly different from the financial analysis (1.27 as opposed to 1.28). As

with the distributor markup, a dealer markup associated only with an incremental increase in

equipment cost was also determined from the econometric analysis. Since the incremental markup

was shown to be close to the average value of 1.27, only the average markup value was used in the

analysis. The average dealer markups ranged from a minimum of 1.027 to a maximum of 1.155.

Table 5.5 shows the cumulative probabilities of the values pertaining to the incremental distributor

markup. 

Table 5.5 Cumulative Probability Distribution of Dealer/Contractor Markups

Distributor Markup Cumulative Probability

1.050 1%

1.150 10%

1.190 20%

1.219 30%

1.244 40%

1.267 50%

1.290 60%

1.314 70%

1.343 80%

1.384 90%

1.483 99%

The contractor markup of 1.27 was assumed to apply to all product classes. In addition,

variations in the markup based on market destination (i.e, whether the equipment would eventually

be sold to the new construction or replacement/retrofit market) were assumed to be negligible. In

other words, the markup for the new construction and replacement/retrofit markets were assumed

to be identical.

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5.2.2.6 Builder Markup

Definition

The markup for converting the builder cost to the price that consumers pay for the spaceconditioning equipment as part of their new home purchase. 

Approach

Buidler markups were developed by ADL. Please refer to Chapter 4, Section 4.3.4,

Determination of Builder Markup, for more details.

Assumptions

The builder markups range uniformly from a minimum of 1.20 to a maximum of 1.32. Thus,

the weighted-average markup is equal to the average value of 1.26. The builder markup was

assumed to remain constant with increasing efficiency and applicable to all product classes.

Builder markups do not pertain to the replacement/retrofit market as they are only applicable

for the new construction market. Based on data from the Air-Conditioning, Heating, and

Refrigeration News7

, 34% of equipment shipped are sold to the new construction market while the

remaining 66% are sold for the replacement/retrofit market. Thus, the weighted-average builder

markup for the entire air-conditioning and heat pump market is 1.088 (34% ] 1.26 + 66% ] 1.00).

5.2.2.7 Sales Tax

Definition

State and local sales taxes. Used as a multiplicative factor to increase equipment price.

Approach

Sales taxes were developed by ADL. Please refer to Chapter 4, Section 4.3.5, Determination

of Sales Tax, for more details.

Assumptions

The sales tax rates essentially range from a minimum of 5% to a maximum of 8% with a

mean value of 6.7% and apply only to the replacement/retrofit market. The sales tax was assumed

to remain constant with increasing efficiency. In addition, the sales tax was assumed to be applicable

to all product classes. Figure 5.3 shows the distribution for the sales tax.

 EE-RM-STD-98-440 COMMENT 311
5-17

0%

5%

10%

15%

20%

25%

30%

35%

40%

5% 6% 7% 8%

Sales Tax

Probabilit

y

Figure 5.3 Sales Tax Distribution for the Replacement/Retrofit Market

No sales taxes were assumed for equipment bought for the new construction market as

consumers do not purchase the equipment directly. As stated earlier, 34% of equipment shipped are

sold to the new construction market while the remaining 66% are sold to the replacement/retrofit

market. Thus, the weighted-average sales tax for the entire air-conditioning and heat pump market

is 1.044 (34% ] 1.00 + 66% ] 1.067).

5.2.2.8 Installation Cost

Definition

The cost to the consumer of labor and materials (other than the actual equipment) needed to

install a central air conditioner or heat pump. 

Approach

Installation costs were based on typical figures for total installed costs that were collected

from public sources and phone calls to HVAC contractors. The installation price was determined

by subtracting the derived equipment price from the typical total installed cost.

Assumptions

The installation cost to install a minimum efficiency (i.e., 10 SEER) split air conditioner, split

heat pump, package air conditioner, and package heat pump are provided below. The costs vary by

product class and were based on data on total installed costs collected by Lawrence Berkeley

National Laboratory (LBNL) from public8,9 and private10 sources.

 EE-RM-STD-98-440 COMMENT 311
5-18

0

0.01

0.02

0.03

0.04

0.05

0.06

$1,023 $1,279 $1,535

Installation Cost

Probability

Figure 5.4 Probability Distribution of Split A/C Installation Cost

Table 5.6 Baseline Installation Costs

Split AC Split HP Package AC Package HP

$1,279 $2,280 $1,367 $2,160

Due to the large variability in installation costs, the representative cost for each product class was

assumed to vary by ±20%. A triangular distribution was created for each product class assuming low

and high values that were -20% less and +20% greater, respectively, than the representative

installation cost. Probabilities of 0% were assigned for the low and high installation cost values.

For example, the Figure 5.4 shows the distribution of values that were used for split air conditioners.

The low and high values ($1023 and $1535) are -20% less and +20% greater than the typical cost.

For all product classes, the installation cost is assumed to stay constant as efficiency increases.

5.2.2.9 Weighted-Average Total Installed Costs

As presented in Eqn. 5.2 and 5.3, the total installed cost is the summation of the equipment

price and the installation cost. The equipment price is derived by multiplying the baseline

manufacturer cost by the appropriate manufacturer cost multiplier and the appropriate markups and

sales tax. Because several of the markups, the sales tax, and the installation cost are represented by

probability distributions, the resulting total installed cost for a particular standard-level will not be

a single-point value, but rather, a distribution of values. With this said, the weighted-average total

installed costs are presented for each standard-level and product class to provide an indication of the

increase in the total installed cost due to an efficiency increase.

 EE-RM-STD-98-440 COMMENT 311
5-19

MFG MFG PERC MFG PERC SAC s SAC w o AH SAC w o AH SAC w AH SAC w AH −− − − − = ⋅ +⋅

=⋅ +⋅

=

Re / / / /

$367 . $449 .

$388

74 3% 257%

MFG MFG MFG SAC SAC s SAC Comm = ⋅+ ⋅

= ⋅+ ⋅

=

− − Re

$388 $449

$394

90% 10%

90% 10%

The derivation of the total installed cost is relatively straight forward. The baseline

manufacturer cost is the starting point for determining the total installed cost, and for split system

heat pumps, single package air conditioners, and single package heat pumps, this value is taken

directly from Table 5.2. But for split system air conditioners, the weighted-average baseline

manufacturer cost is dependent on whether an air handler is required. Data from the 1997 RECS

is used to determine the percentage of households requiring an air handler. For the households in

the 1997 RECS utilizing a central air conditioner, additional information is provided indicating the

presence of a gas-fired forced-air furnace. If a forced-air furnace is present, it is assumed that an air

handler is not required. For the households with air conditioners analyzed in the LCC analysis (1218

households), 74.3% (by population weight) had a forced-air furnace while 25.7% did not. Thus, the

residential split system air conditioner weighted-average baseline manufacturer cost is:

Since the LCC analysis takes into account equipment use in commercial buildings based on the

assumption that 10% of equipment applications are in commercial buildings, the weighted-average

baseline manufacture cost must reflect split system air conditioner use in commercial buildings. It

is assumed that split air conditioners used in commercial buildings will always require an air handler.

Thus, the representative baseline manufacturer cost for commercial applications is $449. Based on

the assumption that 10% of equipment applications are in commercial buildings, the split system air

conditioner weighted-average baseline manufacturer cost is:

With the issue of the weighted-average baseline manufacturer cost resolved for split system

air conditioners, both baseline and standard-level weighted-average total installed costs can now be

presented. Table 5.7 summarizes all of the weighted-average costs and markups necessary for

determining the weighted-average baseline and standard-level total installed costs. 

Table 5.7 Costs and Markups for Determination of Weighted-Average Total Installed Costs

Variable Weighted-Average Value

Baseline Manufacturer Cost Split A/C = $394; Split HP = $572; Package A/C = $511; Package HP = $593

Manufacturer Cost Multiplier Refer to Mean Values in Table 5.3 for each product class

Manufacturer Markup 1.23

Distributor Markup 1.37 for all direct business costs; 1.09 for incremental equipment cost increases

Dealer Markup 1.27

Builder Markup 1.088

Sales Tax 1.044

Installation Cost Split A/C = $1279; Split HP = $2280; Package A/C = $1367; Package HP = $2160

 EE-RM-STD-98-440 COMMENT 311
5-20

ICSAC Baseline − = ⋅⋅⋅⋅ ⋅ +

= +

=

$394 . . . . . $1279

$957 $1279

$2236

123 137 127 1088 1044

IC EQP EQP INST SAC SEER SAC Baseline SAC Baseto SEER SAC −− − =+ +

= + ⋅− ⋅⋅⋅⋅ ⋅ +

= ++

=

11 11

116 123 109 127 1088 1044

∆

$957 ($394 . $394) . . . . . $1279

$957 $121 $1279

$2357

To illustrate the derivation of the weighted-average total installed cost, the calculation is

presented below for baseline (i.e., 10 SEER) and 11 SEER split system air conditioners. For

baseline split system air conditioners, the calculation of the total installed cost (ICSAC-Baseline) is as

follows:

The calculation of the 11 SEER split system air conditioner total installed cost includes the use of

a manufacturer cost multiplier. In addition, since a separate distributor markup was derived based

on incremental equipment cost changes, the derivation of the 11 SEER total installed cost is based

on determining the change in equipment price over the baseline cost. The calculation of the 11

SEER total installed cost (ICSAC-11 SEER) is as follows:

Table 5.8 presents the weighted-average total installed costs for each of the four product class

at each standard-level.

Table 5.8 Weighted-Average Total Installed Costs for Central Air Conditioners

and Heat Pumps

Split A/C Package A/C Split HP Package HP

SEER 1998$ 1998$ 1998$ 1998$

10 $2,236 $2,607 $3,668 $3,599

11 $2,357 $2,795 $3,779 $3,760

12 $2,510 $2,903 $3,933 $3,920

13 $2,715 $3,229 $4,155 $4,287

18 $3,302 $3,822 $4,873 $4,894

5.2.3 Operating Cost Inputs

The operating cost is determined for households using data from the 1997 Residential Energy

Consumption Survey (RECS)11. The operating cost for commercial buildings is based on computer

modeling of 77 nationally representative commercial buildings based on assumptions similar to what

were used to develop ASHRAE Standard 90.1-9912. For the LCC analysis of central air conditioners

(either split or package systems), the LCC of an increased efficiency level is calculated for those

residential and commercial buildings that are determined to have a central air conditioner. For heat

pumps (either split or package systems), the LCC of an increased efficiency level is calculated for

those buildings that are determined to have a central heat pump. After the LCC analysis is

 EE-RM-STD-98-440 COMMENT 311
5-21

OC =++ EC RC MC (5.4)

performed, a distribution of LCC differences (i.e., the LCC difference between the baseline

equipment and equipment with a higher efficiency level) is generated to determine the mean LCC

difference, as well as the percentage of buildings analyzed that have positive LCC savings associated

with the more-efficient equipment.

The operating cost is defined by the following equation:

Where,

EC = energy expenditure associated with operating the equipment,

RC = the repair cost associated with component failure, and

MC = the service cost for maintaining equipment operation.

Of the above inputs to the operating cost, the energy cost or energy expense is the most

complicated to determine. As discussed at the beginning of this chapter in sections 5.1.3 and 5.1.4,

the determination of the energy cost is dependent on several input variables from either RECS (for

the analysis of households) or the commercial building analysis. The figures below show the

relationship between the input variables drawn from RECS or the commercial building analysis and

the determination of the energy cost for a particular standard-level. There are two sets of figures:

one set for the determination of the standard-level annual space-cooling and space-heating energy

expense for households while the other set is for commercial buildings. In Figures 5.5 and 5.6 for

households, the boxes labeled with “RECS” designate those input variables being drawn from

RECS. One box in Figures 5.5 and 5.6 (Shipments disaggregated by efficiency) is labeled as “ARI”

designating that the source of this data is from the Air-Conditioning and Refrigeration Institute

(ARI). In Figures 5.7 and 5.8 for commercial buildings, the boxes labeled with “Commercial”

designate those input variables being drawn from the computer modeling of the 77 nationally

representative buildings. Figures 5.5 and 5.7 show the flow diagram for the determination of the

annual space-cooling energy cost associated with a particular central air conditioner or heat pump

SEER standard-level while Figures 5.6 and 5.8 show the flow diagram for the determination of the

annual space-heating energy cost associated with a particular heat pump HSPF standard-level.

 EE-RM-STD-98-440 COMMENT 311
5-22

RECS

Age of Stock

Household

Central A/C or

Heat Pump

ARI

Shipments

disaggregated by

SEER

RECS

Stock Household

Space-Cooling

Annual Energy Use

Standard-Level

Annual SpaceCooling Energy

Use

SEER of Baseline

Central A/C or

Heat Pump

(10 SEER)

SEER of Stock

Household Central

A/C or Heat Pump

Baseline Annual

Space-Cooling

Energy Use

SEER of

Standard-Level

Central A/C or

Heat Pump

RECS

Average Electricity

Price

Baseline Annual

Space-Cooling

Energy Expense

RECS

Marginal

Electricity Price

Standard-Level

Annual SpaceCooling Energy

Expense SAVINGS

Standard-Level

Annual SpaceCooling Energy

Expense

Figure 5.5 Flow Diagram for the Determination of the Standard-Level Annual SpaceCooling Energy Cost for Households

RECS

Age of Stock

Household

 Heat Pump

ARI

Shipments

disaggregated by

HSPF

RECS

Stock Household

Space-Heating

Annual Energy Use

Standard-Level

Annual SpaceHeaing Energy Use

HSPF of Baseline

Heat Pump

(6.8 HSPF)

HSPF of Stock

Household

Heat Pump

Baseline Annual

Space-Heating

Energy Use

HSPF of

Standard-Level

 Heat Pump

RECS

Average Electricity

Price

Baseline Annual

Space-Heating

Energy Expense

RECS

Marginal

Electricity Price

Standard-Level

Annual SpaceHeating Energy

Expense SAVINGS

Standard-Level

Annual SpaceHeating Energy

Expense

Figure 5.6 Flow Diagram for the Determination of the Standard-Level Annual SpaceHeating Energy Cost for Households

 EE-RM-STD-98-440 COMMENT 311
5-23

Commercial

Space-Cooling

FLEOHs

Standard-Level

Annual SpaceCooling Energy

Use

SEER of Baseline

Central A/C or

Heat Pump

(10 SEER)

Baseline Annual

Space-Cooling

Energy Use

SEER of

Standard-Level

Central A/C or

Heat Pump

Average Electricity

Price

Baseline Annual

Space-Cooling

Energy Expense

Marginal

Electricity Price

Standard-Level

Annual SpaceCooling Energy

Expense SAVINGS

Standard-Level

Annual SpaceCooling Energy

Expense

Commercial

Electric Utility

Tariffs

Figure 5.7 Flow Diagram for the Determination of the Standard-Level Annual SpaceCooling Energy Cost for Commercial Buildings

Commercial

Space-Heating

FLEOHs

Standard-Level

Annual SpaceHeating Energy

Use

HSPF of Baseline

Heat Pump

(6.8 HSPF)

Baseline Annual

Space-Heating

Energy Use

HSPF of

Standard-Level

Heat Pump

Average Electricity

Price

Baseline Annual

Space-Heating

Energy Expense

Standard-Level

Annual SpaceHeating Energy

Expense SAVINGS

Standard-Level

Annual SpaceHeating Energy

Expense

Commercial

Electric Utility

Tariffs

Figure 5.8 Flow Diagram for the Determination of the Standard-Level Annual SpaceHeating Energy Cost for Commercial Buildings

 EE-RM-STD-98-440 COMMENT 311
5-24

EC = + EC EC cool heat (5.5)

EC UEC EL UEC UEC EL cool base c avg base c std c = ⋅− − ⋅ _ __ ( ) marg (5.6)

EC UEC EL UEC UEC EL heat base h avg base h std h = ⋅− − ⋅ _ __ ( ) marg (5.7)

With the above figures clarifying the relationship between RECS input variables and the

energy cost, the following equation is now presented for the energy cost:

Where,

ECcool = energy expenditure associated with operating central air conditioners and heat

pumps during the cooling season, and

ECheat = energy expenditure associated with operating heat pumps during the heating

season.

The energy cost for space-cooling is defined by the following equation:

Where,

UECbase_c = annual space-cooling energy use associated with the baseline efficiency level

(i.e., 10 SEER),

UECstd_c = annual space-cooling energy use associated with an increased efficiency level,

ELECavg = average electricity price, and

ELECmrg = marginal electricity price.

For the case where the energy cost is being determined only for the baseline unit, the second

expression within Eqn. 5.6, (UECbase_c - UECstd_c)^ELmarg, is ignored. It is also worth noting that the

annual energy savings associated with an increased efficiency level is multiplied by the marginal

electricity price rather than the household’s average electricity price. An in-depth discussion of the

marginal electricity price and its determination is presented later.

The expression for determining the energy cost for space-heating is identical to that for space-cooling

and is defined by the following equation:

Where,

UECbase_h = annual space-heating energy use associated with the baseline efficiency level

(i.e., 10 SEER),

UECstd_h = annual space-heating energy use associated with an increased efficiency level,

As with the determination of the space-cooling energy cost, for the case where the space-heating

energy cost is being determined only for the baseline unit, the second expression within Eqn. 5.7,

(UECbase_h - UECstd_h)^ELmarg, is ignored.

The remainder of this section provides information about the variables and assumptions used

 EE-RM-STD-98-440 COMMENT 311
5-25

to calculate the operating cost for central air conditioners and heat pumps. For each variable, the

discussion includes:

• definition;

• approach; and

• assumptions.

Inputs for the determination of operating cost are shown in Table 5.9. Note that although the

lifetime, discount rate, and effective date of the standard are not needed for determining the operating

cost, they are required for establishing the operating cost’s present value. The base case and standard

case designs define the efficiency levels of the design of interest (standard case design) and what

design (base case design) it is being judged against.

Table 5.9 Inputs for Operating Costs

Baseline annual space-cooling energy use

Standard-level annual space-cooling energy use

Baseline annual space-heating energy use

Standard-level annual space-heating energy use

Average electricity price ($)

Marginal electricity price ($)

Electricity price trend

Repair cost ($)

Maintenance cost ($)

Lifetime

Discount rate

Effective date of standard

Base case design

Standard case design

5.2.3.1 Baseline Annual Space-Cooling Energy Use

Definition

The annual space-cooling energy use associated with baseline (i.e., 10 SEER) air

conditioning or heat pump equipment. For households, the baseline annual energy use is directly

proportional to the energy use associated with the stock air-conditioning or heat pump equipment

in the specific RECS household being analyzed. For commercial buildings, it is calculated using the

DOE test procedure’s annual energy use equation for central air conditioners based on the number

of full-load equivalent operating hours (FLEOH) the equipment is assumed to operate. 

 EE-RM-STD-98-440 COMMENT 311
5-26

UEC

CAP

SEER comm base c FLEOH cool

base _ _ = ⋅ cool (5.9)

res base c res stock c

res stock

base

UEC UEC

SEER

SEER __ _ _

_ = ⋅ (5.8)

Approach

Residential

For household air conditioners and the cooling-performance of heat pumps, the baseline

annual space-cooling energy use (UECres_base_c) is defined by the following equation:

Where,

UECres_stock_c = annual space-cooling energy use associated with the stock equipment in the

RECS household,

SEERres_stock = the SEER associated with the stock equipment in the RECS household, and

SEERbase = the SEER associated with the baseline equipment (i.e., 10 SEER).

Thus, the approach for determining the annual baseline space-cooling energy use for households

requires that the UECstock_c and SEERstock first be determined.

Commercial

For commercial building air conditioners and the cooling-performance heat pumps, the

baseline annual space-cooling energy use (UECcomm_base_c) is defined by the following equation taken

from the DOE test procedure:

Where,

CAPcool = cooling capacity of equipment (assumed to be 36,000 Btu/hr),

SEERbase = the SEER associated with the baseline equipment (i.e., 10 SEER), and 

FLEOHcool = the full-load equivelent operating hours for space-cooling.

In order to be consistent with the cost data provided by manufacturers, the cooling capacity of the

equipment is assumed to be 36,000 Btu/hr (3-ton). All manufacturer cost data provided by ARI are

based on a system with a 3-ton cooling capacity.

Assumptions

Residential

The following discusses the assumptions for determining the residential stock annual spacecooling energy use and the residential stock space-cooling efficiency. Both are needed for

calculating the residential baseline annual space-cooling energy use.

 EE-RM-STD-98-440 COMMENT 311
5-27

UEC UEC

CDD

CDD res stock c res stock c non adj

yr avg

res stock _ _ _ __ _

= ⋅ −

30

(5.10)

Stock Annual Space-Cooling Energy Use (UECres_stock_c)

The stock annual space-cooling energy consumption is based on data from the 1997 RECS.

For each household with a central air conditioner and heat pump, RECS estimates the equipment’s

annual energy consumption from the household’s energy bills. It is important to note that the

estimated annual energy consumption corresponds to the household’s stock equipment, specifically

its capacity and efficiency.

In order to mitigate the effect of annual weather fluctuations on the annual energy

consumption values in the 1997 RECS, the household stock annual energy use values are adjusted

based on 30-year average cooling degree day (CDD) data13. In the 1997 RECS, although the 30-year

(1961-1990) average CDD data are not provided for each household, the household’s location is

specified at the Census Division level. In addition, its state-level location is specified if it resides

in either one of the following large states: California, Florida, New York, and Texas. Thus, with 30-

year average CDD values for each Census Division and each of the large states, the household annual

energy use values can at least be adjusted on a regional basis. The calculation to adjust the

household energy use value is straight forward and is represented by the following equation:

Where,

UECres_stock_c = weather-adjusted annual space-cooling energy use associated with the

stock equipment in the RECS household,

UECres_stock_c_non-adj = annual space-cooling energy use associated with the stock equipment

in the RECS household,

CDDres_stock = the CDD associated with the stock equipment in the RECS household,

and

CDD30 yr avg = the 30-year average CDD for the specific Census Division or state

location of the RECS household.

Table 5.10 shows the 30-year average CDD values for each of the nine Census Divisions and

the four large states. For those Census Divisions encompassing a large state, the calculation of the

average CDD excludes the state. Each CDD value was determined through a shipment/population

weighting (i.e., taking into where air-conditioning equipment is shipped and the population of the

areas where the equipment is being shipped to). Appendix E provides a detailed description of this

weighting procedure.

 EE-RM-STD-98-440 COMMENT 311
5-28

Table 5.10 Census Division and Four Large State 30-year Average CDD

Census Division States 30-year average CDD

New England Maine, New Hampshire, Vermont, Massachusetts, 

Rhode Island, Connecticut 587

Middle Atlantic Pennsylvania, New Jersey 1035

East North Central Michigan, Wisconsin, Illinois, Indiana, Ohio 733

West North Central Minnesota, Iowa, Missouri, Kansas, North Dakota, 

South Dakota, Nebraska 1156

South Atlantic West Virginia, Virginia, Georgia, South Carolina, 

North Carolina, District of Columbia 1563

East South Central Kentucky, Tennessee, Alabama, Mississippi 1788

West South Central Oklahoma, Arkansas, Louisiana 2209

Mountain Montana, Idaho, Wyoming, Nevada, Utah, Arizona, 

New Mexico, Colorado 2595

Pacific Washington, Oregon, Alaska, Hawaii 324

- New York 842

- Florida 3179

- Texas 2664

- California 1287

Figure 5.9 depicts the weighted distribution of the weather-adjusted stock annual spacecooling energy use for those RECS households with a central air conditioner. Of the 5900

households surveyed in RECS, 1218 were determined to have a central air conditioner. The range

of the space-cooling energy is quite wide. The minimum value is 57 kWh/yr while the maximum

value is 16,286 kWh/yr. The weighted-average value is 2132 kWh/yr.

 EE-RM-STD-98-440 COMMENT 311
5-29

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

0

100020003000400050006000700080009000

10000110001200013000140001500016000

Annual Space-Cooling Electricity Use (kWh/yr)

Percent of Households

Figure 5.9 Percent of Households with Central A/C by Weather-Adjusted

Annual Space-Cooling Energy Consumption (Source: U.S. DOE-EIA,

1997 RECS)

Figure 5.10 depicts the weighted distribution of the weather-adjusted stock annual spacecooling energy use for those RECS households with a heat pump. Of the 5900 households surveyed

in RECS, 308 were to determined to have heat pumps. Similar to central air conditioners, the range

of the space-cooling energy use is quite wide. The minimum value is 0 kWh/yr while the maximum

value is 11,756 kWh/yr. The weighted-average value is 2585 kWh/yr. As indicated in the figure

below, the weighted percentage of households without space cooling energy consumption (over 5%)

is quite high. This situation arises from the fact that several of the RECS households with heat

pumps were determined not to use their equipment for space-cooling purposes.

 EE-RM-STD-98-440 COMMENT 311
5-30

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

0

100020003000400050006000700080009000

1000011000

Annual Space-Cooling Electricity Consumption (kWh/yr)

Percent of Households

Figure 5.10 Percent of Households with Heat Pumps by Weather-Adjusted

Annual Space-Cooling Energy Consumption (Source: U.S. DOE-EIA,

1997 RECS)

Stock Space-Cooling Efficiency (SEERres_stock)

As indicated in the baseline annual space-cooling energy use equation (Eqn. 5.8), the SEER

of the stock equipment is necessary for determining the annual space-cooling energy use associated

with minimum (10 SEER) efficiency equipment. 

In order to establish the SEER of the stock equipment, the age of the equipment as indicated

by the 1997 RECS is first established. For each household surveyed with an air conditioner or heat

pump, RECS provides an age index for the space-conditioning equipment. Each index value

corresponds to a range of equipment ages. Figures 5.11 and 5.12 show the distribution of age indices

for central air conditioners and heat pumps in RECS, respectively. A table is imbedded within each

figure showing the corresponding range of ages for each index. Each value in the range of ages that

correspond to a particular age index is assumed to have an equal probability of occurring.

 EE-RM-STD-98-440 COMMENT 311
5-31

0%

5%

10%

15%

20%

25%

30%

35%

1234569

Age Index

Percent of Households

Figure 5.11 Distribution of Age Indices for RECS households with a

Central A/C (Source: U.S. DOE-EIA, 1997 RECS)

0%

5%

10%

15%

20%

25%

30%

35%

1234569

Age Index

Percent of Households

Figure 5.12 Distribution of Age Indices for RECS households with a

Heat Pump (Source: U.S. DOE-EIA, 1997 RECS)

Index Age (years)

1 0 to 2

2 2 to 4

3 5 to 9

4 10 to 19

5 20 and over

6 5 to 15

9 5 to 15

Index Age (years)

1 0 to 2

2 2 to 4

3 5 to 9

4 10 to 19

5 20 and over

6 5 to 15

9 5 to 15

 EE-RM-STD-98-440 COMMENT 311
5-32

Once the age of the equipment is established, disaggregated shipments data provided by ARI are

used to determine the efficiency of the equipment. For the years 1976 through 1997, ARI provided

data that disaggregates unitary air conditioner and heat pump shipments by efficiency, thus,

providing an efficiency distribution for each year. The shipment weighted-average efficiencies by

year for both central air conditioners and heat pumps are provided below14. It should be noted that

due to the year in which RECS was conducted (1997), only efficiencies up to 1997 are utilized in

the LCC analysis.

Table 5.11 Shipment Weighted SEERs of Unitary Air Conditioners and Heat Pumps

Year a Unitary Air Conditioners Unitary Heat Pumps

1976 7.03 6.87

1977 7.13 6.89

1978 7.34 7.24

1979 7.47 7.34

1980 7.55 7.51

1981 7.78 7.70

1982 8.31 7.79

1983 8.43 8.23

1984 8.66 8.45

1985 8.82 8.56

1986 8.87 8.70

1987 8.97 8.93

1988 9.11 9.13

1989 9.25 9.26

1990 9.31 9.46

1991 9.49 9.77

1992 10.46 10.60

1993 10.56 10.86

1994 10.61 10.94

1995 10.68 10.97

1996 10.68 11.00

1997 10.66 10.97

a For the years 1976 to 1980, values are shipment weighted EERs.

For all the households in RECS with either a central air conditioner or heat pump, the

methodology for establishing the stock space-cooling efficiency of space-conditioning equipment

yields a weighted-average stock efficiency of 9.13 SEER for central air conditioners and a weightedaverage stock efficiency of 9.32 SEER for heat pumps.

 EE-RM-STD-98-440 COMMENT 311
5-33

CAC base c CAC stock c

CAC stock

base

kWh yr wght avg wght avg

wght avg UEC UEC

SEER

SEER − −

−

__ _ _ = ⋅ =⋅ = _

/ .

. 2132

913

10 00 1947

FLEOH

Load

CAP cool

cool

cool

= (5.11)

HP base c HP stock c

HP stock

base

kWh yr wght avg wght avg

wght avg UEC UEC

SEER

SEER − −

−

__ _ _ = ⋅ =⋅ = _

/ .

. 2585

9 32

10 00 2409

Baseline Annual Space-Cooling Energy Use (UECres_base_c)

A baseline annual space-cooling energy use is determined for each RECS household with a

central air conditioner and heat pump based on the household’s stock energy use and equipment

efficiency. The resulting baseline energy use values for these RECS households have a large range.

To provide an indication of the magnitude of the baseline energy use for central air conditioners and

heat pumps, weighted-average values are calculated and provided below.

Based on the use of the RECS weighted-average stock space-cooling energy use and

weighted-average efficiency for central air conditioners, the weighted-average baseline spacecooling annual energy use for central air conditioners for households is: 

Based on the use of the RECS weighted-average stock space-cooling energy use and weightedaverage efficiency for heat pumps, the weighted-average baseline space-cooling annual energy use

for heat pumps is: 

Commercial

The following discusses the assumptions for determining the space-cooling FLEOHs and,

in turn, how they are used for calculating the commercial baseline annual space-cooling energy use.

Full-Load Equivalent Operating Hours (FLEOH)

The space-cooling FLEOH is effectively the number of hours that a system would have to

run at full capacity to serve a total load equal to the annual load on the equipment. FLEOH is

calculated as:

Where,

Loadcool = annual equipment load for space-cooling.

FLEOH is strictly defined as being related to the equipment capacity, not the peak load of

the system. Because FLEOH is used to generate annual cooling loads irrespective of equipment size,

it is assumed that the equipment is sized based on the design-day peak equipment load with no

explicit oversizing. Thus equation 5.10 becomes:

 EE-RM-STD-98-440 COMMENT 311
5-34

FLEOH

Load

Peak Load cool

cool

cool

= (5.12)

Where,

Peak Loadcool = design-day peak cooling load.

The FLEOH for a piece of equipment is a function of the relative annual load to the peak

building load. In general, this ratio will vary depending on building construction, building internal

loads, building schedules, and orientation an exposure of the zone that the equipment serves. It was

assumed that for any given building type, the internal-load characteristics and building schedules are

constant across the building.

FLEOHs were determined for a set of 77 nationally representative commercial buildings.

The 77 buildings are comprised of seven different types of commercial buildings located in eleven

different geographic regions of the U.S. consistent with assumptions used to develop ASHRAE 90.1-

1999. In conducting the computer modeling of the buildings, it was assumed that a single type of

equipment, in our case residential-type space-conditioning equipment, were used to condition the

building. Additionally, it was assumed that the equipment did not use economizers but did operate

with setback theromstats. Table 5.12 presents the FLEOHs for each of the 77 commercial building

which were modeled.

Table 5.12 Space-Cooling FLEOHs for Commercial Buildings utilizing Residential-Size

Space-Cooling Equipment (hours)

Census Division /

Region

Building Type

Assembly Education Food

Service Lodging Office Retail Warehouse

New England 1059 773 1524 1210 1118 1239 1015

Mid-Atlantic 1059 773 1524 1210 1118 1239 1015

East N. Central 984 676 1422 1106 1041 1147 927

West N. Central 1020 709 1443 1136 1057 1127 971

South Atlantic 2278 1519 2921 2496 2083 2360 1794

East S. Central 1906 1281 2532 2104 1811 2066 1581

West S. Central 2237 1494 2873 2471 2054 2341 1739

Mountain-North 1193 829 1765 1434 1347 1419 1296

Mountain-South 2850 2001 3492 3238 2602 2903 2539

Oregon-Wash 843 574 1494 985 1093 1274 1194

California 1720 1176 2801 2051 1937 2340 1392

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Baseline Annual Space-Cooling Energy Use (UECcomm_base_c)

Using Eqn. 5.9, baseline annual space-cooling energy use values can be calculated for each

of the 77 nationally representative commercial buildings by using the space-cooling FLEOHs in

Table 5.12. The baseline space-cooling energy use values pertain to commercial building equipped

with either central air conditioners or heat pumps. Table 5.13 shows the calculated energy use

values.

Table 5.13 Baseline Annual Space-Cooling Energy Use for Commercial Buildings utilizing

Residential-Size Space-Cooling Equipment (kWh/year)

Census Division /

Region

Building Type

Assembly Education Food Lodging Office Retail Warehouse

New England 3814 2782 5488 4356 4026 4461 3653

Mid-Atlantic 3814 2782 5488 4356 4026 4461 3653

East N. Central 3541 2435 5119 3982 3747 4129 3336

West N. Central 3673 2552 5196 4091 3805 4058 3497

South Atlantic 8202 5470 10514 8984 7499 8497 6458

East S. Central 6862 4610 9116 7575 6521 7437 5690

West S. Central 8054 5379 10343 8896 7395 8426 6262

Mountain-North 4294 2985 6355 5163 4850 5107 4665

Mountain-South 10262 7203 12571 11656 9368 10452 9140

Oregon-Wash 3035 2067 5379 3545 3934 4586 4297

California 6192 4233 10083 7384 6973 8426 5010

Proper allocation of the shipments is necessary in order to obtain the proper representation

or weighting for each of the building types. The allocation of the number of shipments to each of

the 77 nationally representative commercial buildings is based on data from the 1992 and 1995

CBECS using a methodology developed by PNNL. Table 5.14 presents the percentage of shipments

allocated to each of the 77 building types. 

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0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

0

100020003000400050006000700080009000

100001100012000

Baseline Annual Space-Cooling Energy Use (kWh/hr)

Percentage of Commercial Buildings

Figure 5.13 Percent of Commercial Buildings by Baseline Annual SpaceCooling Energy Consumption

Table 5.14 Fraction of Building Stock utilizing Residential-Size Space-Cooling Equipment

Census Division /

Region

Building Type

Assembly Education Food Lodging Office Retail Warehouse

New England 0.371% 0.790% 0.071% 0.333% 1.024% 1.502% 0.497%

Mid-Atlantic 1.005% 1.790% 0.230% 0.278% 2.993% 3.660% 1.844%

East N. Central 1.340% 2.014% 0.862% 0.960% 3.050% 3.847% 2.919%

West N. Central 0.771% 1.071% 0.124% 0.387% 1.515% 2.272% 0.635%

South Atlantic 1.640% 2.367% 0.578% 1.401% 4.532% 5.487% 2.501%

East S. Central 1.059% 0.799% 0.302% 0.659% 1.206% 3.121% 1.528%

West S. Central 1.268% 2.325% 0.490% 0.515% 2.200% 3.480% 1.275%

Mountain-North 0.677% 0.245% 0.147% 0.340% 1.601% 0.920% 0.239%

Mountain-South 0.775% 0.436% 0.068% 0.267% 0.825% 0.574% 0.536%

Oregon-Wash 0.208% 0.101% 0.118% 0.111% 0.820% 0.630% 0.120%

California 1.936% 1.457% 0.442% 0.710% 3.432% 3.191% 2.187%

Figure 5.13 depicts for the 77 nationally represented commercial buildings, the weighted

distribution of the stock baseline annual space-cooling energy use. As with the residential building

stock, the range of the space-cooling energy is quite wide. The minimum value is 2067 kWh/yr

while the maximum value is 12,571 kWh/yr. The weighted-average value is 5824 kWh/yr.

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UEC

CAP

SEER comm std c FLEOH cool

std _ _ cool = ⋅ (5.14)

res std c res stock c

res stock

std

UEC UEC

SEER

SEER __ _ _

_ = ⋅ (5.13)

5.2.3.2 Standard-Level Annual Space-Cooling Energy Use

Definition

The annual space-cooling energy use associated with air conditioning or heat pump

equipment at a specific standard-level. For both residential and commercial buildings, the approach

for calculating the standard-level energy use is identical to that for the baseline annual energy use.

For households, the standard-level annual energy use is directly proportional to the energy use

associated with the stock air-conditioning or heat pump equipment in the specific RECS household

being analyzed. For commercial buildings, it is calculated using the DOE test procedure’s annual

energy use equation for central air conditioners based on the number of full-load equivalent

operating hours (FLEOH) the equipment is assumed to operate. 

Approach

Residential

For household air conditioners and the cooling-performance of heat pumps, the standard-level

annual space-cooling energy use (UECres_std_c) is defined by the following equation:

Where,

UECres_stock_c = annual space cooling energy use associated with the stock equipment in the

RECS household,

SEERres_stock = the SEER associated with the stock equipment in the RECS household, and

SEERstd = the SEER associated with the increased efficiency level or standard.

The above equation for determining the standard-level annual space-cooling energy use is

identical to that for the baseline annual space-cooling energy use, with the exception that the SEER

associated with the increased standard is used in place of the baseline efficiency (i.e., 10 SEER).

Thus, the determination of the standard-level annual space-cooling energy use is based upon the

same information as used for the baseline energy use, namely, the stock annual space-cooling energy

use and efficiency. 

Commercial

For commercial building air conditioners and the cooling-performance of heat pumps, the

standard-level annual space-cooling energy use (UECcomm_std_c) is defined by the following equation

taken from the DOE test procedure:

 EE-RM-STD-98-440 COMMENT 311
5-38

Where,

CAPcool = cooling capacity of equipment (assumed to be 36,000 Btu/hr),

SEERstd = the SEER associated with the increased efficiency level or standard, and 

FLEOHcool = the full-load equivelent operating hours for space-cooling.

In order to be consistent with the cost data provided by manufacturers, the cooling capacity of the

equipment is assumed to be 36,000 Btu/hr (3-ton). All manufacturer cost data provided by ARI are

based on a system with a 3-ton cooling capacity.

The above equation for determining the standard-level annual space-cooling energy use is

identical to that for the baseline annual space-cooling energy use, with the exception that the SEER

associated with the increased standard is used in place of the baseline efficiency (i.e., 10 SEER).

Thus, the determination of the standard-level annual space-cooling energy use is based upon the

same information as used for the baseline energy use, namely, the FLEOHs.

Assumptions

Residential

The assumptions for determining the residential stock annual space-cooling energy use and

the stock space-cooling efficiency have been discussed in the previous section (Section 5.2.3.1). For

central air conditioners, the weighted-average stock annual space-cooling energy use and the

weighted-average stock efficiency are 2132 kWh/yr and 9.13 SEER, respectively. For heat pumps,

the weighted-average stock annual space-cooling energy use and the weighted-average stock

efficiency are 2585 kWh/yr and 9.32 SEER, respectively.

Based on the above weighted-average values and the use of Eqn 5.13, weighted-average

standard-level annual space-cooling energy use values can be determined. Table 5.15 shows the

weighted-average annual space-cooling energy use values for standard-levels of 11 through 13 SEER

and 18 SEER for both central air conditioners and heat pumps. It is worth reiterating that the values

shown in Table 5.15 are the weighted-average values associated with each standard-level. In the

course of conducting the LCC analysis with Crystal Ball, the energy use due to a particular standardlevel is determined for each household in RECS based on the unique age and space-cooling energy

use associated with that household. As a point of reference, the weighted-average stock annual

space-cooling energy use and the weighted-average stock efficiency are included in Table 5.15. Also

provided are the weighted-average baseline space-cooling energy use and efficiency values. 

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Table 5.15 Residential Central Air Conditioner and Heat Pump Annual Space-Cooling

Energy Use scaled to SEER

Standard-Level Central Air Conditioners Heat Pumps

SEER (Btu/W]hr) kWh/yr kWh/yr

survey 9.13a

 (CAC), 9.32a (HP) 2132a 2585a

scaled 10 1947 2409

11 1770 2190

12 1622 2008

13 1497 1853

18 1081 1338

a

 RECS-based weighted-average values for household equipment in use in 1997.

Commercial

The assumptions for determining the space-cooling FLEOHs necessary for determining the

commercial baseline annual space-cooling energy use have been discussed in the previous section

(Section 5.2.3.1). The both central air conditioners and the cooling-performance of heat pumps, the

weighted-average baseline annual space-cooling energy use is 5824 kWh/yr. 

Rather than using Eqn. 5.14, weighted-average standard-level space-cooling energy use

values can be determined by simply by multiplying the baseline energy use by the ratio of the

baseline efficiency (i.e., 10 SEER) to the standard-level efficiency. Table 5.16 shows the weightedaverage annual space-cooling energy use values for standard-levels of 11 through 13 SEER and 18

SEER It is worth reiterating that the values shown in Table 5.16 are only the weighted-average

values associated with each standard-level. In the course of conducting the LCC analysis with

Crystal Ball, the energy use due to a particular standard-level is determined for each commercial

building. 

Table 5.16 Commercial Building Central Air Conditioner and Heat Pump Annual SpaceCooling Energy Use scaled to SEER

Standard-Level Space-Cooling Energy Use

SEER (Btu/W]hr) kWh/yr

Baseline 10 5824

Scaled 11 5295

12 4853

13 4480

18 3236

Weighted-average annual space-cooling energy use values for the entire building stock are

based on the same scaling method used for determining the weighted-average residential and

commercial energy use values. For coming up with the overall energy use values, the overall stock

 EE-RM-STD-98-440 COMMENT 311
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space-cooling energy use values and efficiencies for central air conditioners and heat pumps are first

determined. Based on the assumption that 90% of the central air-conditioning and heat pump stock

reside in households (with the remaining 10% residing in commercial buildings), the overall energy

use and efficiency values are determined by multiplying the residential and commercial values by

90% and 10%, respectively, and then summing the result. In lieu of having stock energy use values

and efficiencies for commercial equipment, the baseline (i.e., 10 SEER) energy use and efficiency

are used. Thus, the resulting overall weighted-average stock space-cooling energy use values are

2501 kWh/yr for central air conditioners and 2950 kWh/yr for heat pumps. The resulting overall

weighted-average stock efficiencies are 9.22 SEER for central air conditioners and 9.39 for heat

pumps. Table 5.17 summarizes the overall weighted-average annual space-cooling energy use

values for each standard-level. Again, it is must be emphasized that the values shown in Table 5.17

are only the weighted-average values associated with each standard-level. In the course of

conducting the LCC analysis with Crystal Ball, the energy use due to a particular standard-level is

determined for each residential and commercial building.

Table 5.17 Overall Central Air Conditioner and Heat Pump Annual Space-Cooling

Energy Use scaled to SEER

Standard-Level Central Air Conditioners Heat Pumps

SEER (Btu/W]hr) kWh/yr kWh/yr

stock 9.22 (CAC), 9.39 (HP) 2501 2950

scaled 10 2305 2769

11 2096 2517

12 1921 2307

13 1773 2130

18 1281 1538

5.2.3.3 Baseline Annual Space-Heating Energy Use

Definition

The annual space-heating energy use associated with baseline (i.e., 6.8 HSPF) heat pump

equipment. For households, the baseline annual energy use is directly proportional to the energy use

associated with the stock heat pump equipment in the specific RECS household being analyzed. For

commercial buildings, it is calculated using the DOE test procedure’s annual energy use equation

for heat pumps based on the number of full-load equivalent operating hours (FLEOH) the equipment

is assumed to operate. 

Approach

Residential

For the household heating-performance of heat pumps, the baseline annual space-heating

energy use (UECres_base_h) is defined by the following equation:

 EE-RM-STD-98-440 COMMENT 311
5-41

UEC

DHR

HSPF comm base h FLEOH

base _ _ heat =⋅ ⋅ 0 77 . (5.16)

res base h res stock h

res stock

base

UEC UEC

HSPF

HSPF __ _ _

_ = ⋅ (5.15)

Where,

UECres_stock_h = annual space-heating energy use associated with the stock equipment in the

RECS household,

HSPFres_stock = the HSPF associated with the stock equipment in the RECS household, and

HSPFbase = the HSPF associated with the baseline equipment (i.e., 6.8 HSPF).

Thus, the approach for determining the annual baseline space-heating energy use requires that the

UECstock_h and HSPFstock first be determined.

Commercial

For the commercial building heating-performance of heat pumps, the baseline annual spaceheating energy use (UECcomm_base_h) is defined by the following equation taken from the DOE test

procedure:

Where,

DHR = standardized design heating requirement nearest to the heating capacity of the

system,

HSPFbase = the HSPF associated with the baseline equipment (i.e., 6.8 HSPF),

FLEOHheat = the full-load equivelent operating hours for space-heating, and

0.77 = factor to adjust the calculated design heating requirement and heat load hours

to the actual load experienced by a heating system.

In order to be consistent with the cost data provided by manufacturers, the heating capacity of the

equipment is assumed to be 36,000 Btu/hr resulting in the DHR being set to 36,000 Btu/hr. All

manufacturer cost data provided by ARI are based on a system with a 3-ton cooling capacity with

a corresponding heating capacity of 36,000 Btu/hr.

Assumptions

Residential

The following discusses the assumptions for determining the stock annual space-heating

energy use and the stock space-heating efficiency. Both are needed for calculating the residential

baseline annual space-heating energy use.

 EE-RM-STD-98-440 COMMENT 311
5-42

UEC UEC

HDD

HDD res stock h res stock h non adj

yr avg

res stock _ _ _ __ _

= ⋅ −

30

(5.17)

Stock Annual Space-Heating Energy Use (UECres_stock_h)

The stock annual space-heating energy consumption is based on data from the 1997 RECS.

For each household with a heat pump, RECS estimates the equipment’s annual energy consumption

from the household’s energy bills. It is important to note that the estimated annual energy

consumption corresponds to the household’s stock equipment, specifically its capacity and

efficiency.

In order to mitigate the effect of annual weather fluctuations on the annual energy

consumption values in the 1997 RECS, the household stock annual energy use values are adjusted

based on 30-year average heating degree day (HDD) data15. In the 1997 RECS, although the 30-year

(1961-1990) average HDD data are not provided for each household, the household’s location is

specified at the Census Division level. In addition, its state-level location is specified if it resides

in either one of the following large states: California, Florida, New York, and Texas. Thus, with 30-

year average HDD values for each Census Division and each of the large states, the household

annual energy use values can at least be adjusted on a regional basis. The calculation to adjust the

household energy use value is straight forward and is represented by the following equation:

Where,

UECres_stock_h = weather-adjusted annual space-heating energy use associated with the

stock equipment in the RECS household,

UECres_stock_c_non-adj = annual space-heating energy use associated with the stock equipment

in the RECS household,

HDDres_stock = the HDD associated with the stock equipment in the RECS household,

and

HDD30 yr avg = the 30-year average HDD for the specific Census Division or state

location of the RECS household.

Table 5.18 shows the 30-year average HDD values for each of the nine Census Divisions and

the four large states. For those Census Divisions encompassing a large state, the calculation of the

average HDD excludes the state. Each HDD value was determined through a shipment/population

weighting (i.e., taking into where air-conditioning equipment is shipped and the population of the

areas where the equipment is being shipped to). Appendix E provides a detailed description of this

weighting procedure.

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Table 5.18 Census Division and Four Large State 30-year Average HDD

Census Division States 30-year average CDD

New England Maine, New Hampshire, Vermont, Massachusetts, 

Rhode Island, Connecticut 6187

Middle Atlantic Pennsylvania, New Jersey 5676

East North Central Michigan, Wisconsin, Illinois, Indiana, Ohio 6371

West North Central Minnesota, Iowa, Missouri, Kansas, North Dakota, 

South Dakota, Nebraska 6009

South Atlantic West Virginia, Virginia, Georgia, South Carolina, 

North Carolina, District of Columbia 3432

East South Central Kentucky, Tennessee, Alabama, Mississippi 3314

West South Central Oklahoma, Arkansas, Louisiana 2756

Mountain Montana, Idaho, Wyoming, Nevada, Utah, Arizona, 

New Mexico, Colorado 3248

Pacific Washington, Oregon, Alaska, Hawaii 4801

- New York 4116

- Florida 961

- Texas 2045

- California 2020

Figure 5.14 depicts the weighted distribution of the weather-adjusted stock annual spaceheating energy use for those RECS households with a heat pump. As discussed earlier, of the5900

households surveyed in RECS, 308 were to determined to have heat pumps. The space heating

energy use ranges from a minimum value of 174 kWh/yr to a maximum value of 17,272 kWh/yr.

The weighted-average value is 3921 kWh/yr.

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5-44

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

0

100020003000400050006000700080009000

1000011000120001300014000150001600017000

Annual Space-Heating Electricity Consumption (kWh/yr)

Percent of Households

Figure 5.14 Percent of Households with Heat Pumps by Weather-Adjusted

Annual Space-Heating Energy Consumption (Source: U.S. DOEEIA, 1997 RECS)

Stock Space-Heating Efficiency (HSPFres_stock)

As indicated in the baseline annual space-heating energy use equation (Eqn. 5.15), the HSPF

of the stock equipment is necessary for determining the annual space-heating energy use associated

with minimum (6.8 HSPF) efficiency heat pump equipment. 

In order to establish the HSPF of the stock equipment, the age of the equipment as indicated

by the 1997 RECS is first established. For each household surveyed with a heat pump, RECS

provides an age index for the equipment. Each index value corresponds to a range of equipment

ages. The distribution of age indices for the heat pumps in RECS was shown previously in the

discussion of stock space-cooling efficiency (Figure 5.12). That figure is repeated below as Figure

5.15. A table is imbedded in the figure showing the corresponding range of ages for each index.

Each age in the range of values that correspond to a particular age index is assumed to have an equal

probability of occurring.

 EE-RM-STD-98-440 COMMENT 311
5-45

0%

5%

10%

15%

20%

25%

30%

35%

1234569

Age Index

Percent of Households

Figure 5.15 Distribution of Age Indices for RECS households with a Heat

Pump (Source: U.S. DOE-EIA, 1997 RECS)

Index Age (years)

1 0 to 2

2 2 to 4

3 5 to 9

4 10 to 19

5 20 and over

6 5 to 15

9 5 to 15

Once the age of the equipment is established, disaggregated shipments data provided by ARI

are used to determine the efficiency of the equipment. Unlike the data provided by ARI for the

SEER, shipments data disaggregated by HSPF are available only for a limited number of years (1987

through 1990). With this data, an efficiency distribution for each year from 1987 to 1990 can be

created. The shipment weighted-average efficiencies by year are shown in the table below (Table

5.19). For years preceding 1987 and extending past 1990 to 1993, an efficiency increase rate of 1.5%

per year is used to establish the shipment weighted HSPF (the resulting values are presented in Table

5.19). This rate of increase is the average rate of increase exhibited by the shipment weighted HSPF

from 1987 to 1990. For the years 1994 through 1997, the efficiency is assumed to remain constant.

Efficiency distributions for those years in which data were not provided were assumed to have the

same distributional shape as the years (1987 through 1990) in which data were provided.

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Table 5.19 Shipment Weighted HSPFs of Unitary Heat Pumps

Year Unitary Heat Pumps a

1976 5.66

1977 5.74

1978 5.83

1979 5.91

1980 6.00

1981 6.09

1982 6.18

1983 6.28

1984 6.37

1985 6.47

1986 6.56

1987 6.66

1988 6.81

1989 6.87

1990 6.98

1991 7.08

1992 7.19

1993 7.30

1994 7.30

1995 7.30

1996 7.30

1997 7.30 a 1987-1990: HSPFs are actual shipment weighted values from ARI shipments data. Years prior to 1987 and from 1991-1993:

HSPFs based on efficiency rate increase of 1.5%. 1994-1997: Efficiency frozen at 1993 HSPF.

For all the households in RECS with a heat pump, the methodology for establishing the stock

space-heating efficiency yields a weighted-average stock efficiency of 6.77 HSPF.

Baseline Annual Space-Heating Energy Use (UECres_base_h)

A baseline annual space-heating energy use is determined for each RECS household with a

heat pump based on the household’s stock energy use and equipment efficiency. The resulting

baseline energy use values for these RECS households have a large range. To provide an indication

of the magnitude of the baseline energy use for heat pumps, weighted-average values are calculated

and provided below.

Based on the use of the RECS weighted-average stock space-heating energy use and

weighted-average efficiency for heat pumps, the weighted-average baseline space-heating annual

energy use is: 

 EE-RM-STD-98-440 COMMENT 311
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FLEOH

Load

CAP heat

heat

heat

= (5.18)

FLEOH

Load

Peak Load heat

heat

heat

= (5.19)

HP base h HP stock h

HP stock

base wght avg wght avg

wght avg UEC UEC

HSPF

HSPF kWh yr − −

−

__ _ _ = ⋅ = ⋅= _ .

. 3921 /

6 77

680 3904

Commercial

The following discusses the assumptions for determining the space-heating FLEOHs and,

in turn, how they are used for calculating the commercial baseline annual space-heating energy use.

Full-Load Equivalent Operating Hours (FLEOH)

The space-heating FLEOH is effectively the number of hours that a system would have to

run at full capacity to serve a total load equal to the annual load on the equipment. FLEOH is

calculated as:

Where,

Loadheat = annual equipment load for space-heating.

FLEOH is strictly defined as being related to the equipment capacity, not the peak load of

the system. Because FLEOH is used to generate annual heating loads irrespective of equipment size,

it is assumed that the equipment is sized based on the design-day peak equipment load with no

explicit oversizing. Thus equation 5.10 becomes:

Where,

Peak Loadheat = design-day peak heating load.

The FLEOH for a piece of equipment is a function of the relative annual load to the peak

building load. In general, this ratio will vary depending on building construction, building internal

loads, building schedules, and orientation an exposure of the zone that the equipment serves. It was

assumed that for any given building type, the internal-load characteristics and building schedules are

constant across the building.

FLEOHs were determined for a set of 77 nationally representative commercial buildings.

The 77 buildings are comprised of seven different types of commercial buildings located in eleven

different geographic regions of the U.S. consistent with assumptions used to develop ASHRAE 90.1-

1999. In conducting the computer modeling of the buildings, it was assumed that a single type of

equipment, in our case residential-type space-heating equipment, were used to condition the

building. Additionally, it was assumed that the equipment did not use economizers but did operate

 EE-RM-STD-98-440 COMMENT 311
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with setback theromstats. Table 5.20 presents the FLEOHs for each of the 77 commercial building

which were modeled.

Table 5.20 Space-Heating FLEOHs for Commercial Buildings utilizing Residential-Size

Space-Heating Equipment (hours)

Census Division /

Region

Building Type

Assembly Education Food

Service Lodging Office Retail Warehouse

New England 1898 816 1388 1523 597 493 889

Mid-Atlantic 1907 849 1388 1523 674 598 887

East N. Central 2044 964 1575 1683 780 655 1056

West N. Central 2014 926 1507 1690 851 759 1157

South Atlantic 1144 493 817 666 289 171 512

East S. Central 1352 582 949 839 341 276 308

West S. Central 1103 448 810 596 242 129 166

Mountain-North 1837 815 1282 1336 485 489 604

Mountain-South 965 322 722 349 178 34 32

Oregon-Wash 2363 1070 1589 1732 624 617 928

California 1317 528 781 521 214 94 18

Baseline Annual Space-Heating Energy Use (UECcomm_base_h)

Baseline annual space-heating energy use values can be calculated for each of the 77

nationally representative commercial buildings by using the space-heating FLEOHs in Table 5.20.

The baseline space-heating energy use values pertain to commercial building equipped with heat

pumps. Table 5.21 shows the calculated energy use values.

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Table 5.21 Baseline Annual Space-Heating Energy Use for Commercial Buildings utilizing

Residential-Size Space-Heating Equipment (kWh/year)

Census Division /

Region

Building Type

Assembly Education Food

Service Lodging Office Retail Warehouse

New England 7735 3325 5658 6208 2434 2008 3625

Mid-Atlantic 7775 3462 5658 6208 2748 2439 3618

East N. Central 8333 3930 6419 6862 3182 2668 4304

West N. Central 8210 3776 6145 6888 3467 3094 4715

South Atlantic 4662 2012 3331 2716 1178 699 2088

East S. Central 5512 2371 3870 3419 1390 1125 1257

West S. Central 4498 1827 3300 2428 985 526 676

Mountain-North 7488 3323 5225 5445 1977 1994 2461

Mountain-South 3934 1311 2943 1421 724 140 131

Oregon-Wash 9633 4360 6476 7060 2543 2516 3782

California 5368 2154 3184 2125 872 381 75

Proper allocation of the shipments is necessary in order to obtain the proper representation

or weighting for each of the building types. The allocation of the number of shipments to each of

the 77 nationally representative commercial buildings is based on data from the 1992 and 1995

CBECS using a methodology developed by PNNL. Table 5.22 presents the percentage of shipments

allocated to each of the 77 building types. The allocation is identical to that used for the spacecooling FLEOHs.

Table 5.22 Fraction of Building Stock utilizing Residential-Size Space-Cooling Equipment

Census Division /

Region

Building Type

Assembly Education Food Lodging Office Retail Warehouse

New England 0.371% 0.790% 0.071% 0.333% 1.024% 1.502% 0.497%

Mid-Atlantic 1.005% 1.790% 0.230% 0.278% 2.993% 3.660% 1.844%

East N. Central 1.340% 2.014% 0.862% 0.960% 3.050% 3.847% 2.919%

West N. Central 0.771% 1.071% 0.124% 0.387% 1.515% 2.272% 0.635%

South Atlantic 1.640% 2.367% 0.578% 1.401% 4.532% 5.487% 2.501%

East S. Central 1.059% 0.799% 0.302% 0.659% 1.206% 3.121% 1.528%

West S. Central 1.268% 2.325% 0.490% 0.515% 2.200% 3.480% 1.275%

Mountain-North 0.677% 0.245% 0.147% 0.340% 1.601% 0.920% 0.239%

Mountain-South 0.775% 0.436% 0.068% 0.267% 0.825% 0.574% 0.536%

Oregon-Wash 0.208% 0.101% 0.118% 0.111% 0.820% 0.630% 0.120%

California 1.936% 1.457% 0.442% 0.710% 3.432% 3.191% 2.187%

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0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

0

100020003000400050006000700080009000

Space-Heating Annual Energy Use (kWh/yr)

Percentage of Commercial Buildings

Figure 5.16 Percent of Commercial Buildings by Baseline Annual SpaceHeating Energy Consumption

Figure 5.16 depicts for the 77 nationally represented commercial buildings, the weighted

distribution of the stock baseline annual space-heating energy use. As with the residential building

stock, the range of the space-heating energy use is quite wide. The minimum value is 75 kWh/yr

while the maximum value is 9633 kWh/yr. The weighted-average value is 2654 kWh/yr.

5.2.3.4 Standard-Level Annual Space-Heating Energy Use

Definition

The annual space-heating energy use associated with heat pump equipment at a specific

standard-level. For both residential and commercial buildings, the approach for calculating the

standard-level energy use is identical to that for the baseline annual energy use. For households, the

standard-level annual energy use is directly proportional to the energy use associated with the stock

heat pump equipment in the specific RECS household being analyzed. For commercial buildings,

it is calculated using the DOE test procedure’s annual energy use equation for heat pumps based on

the number of full-load equivalent operating hours (FLEOH) the equipment is assumed to operate.

Approach

Residential

For the household heating-performance of heat pumps, the standard-level annual spaceheating energy use (UECres_std_h) is defined by the following equation:

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UEC

DHR

HSPF comm std h FLEOH

std _ _ heat =⋅ ⋅ 0 77 . (5.21)

res std h res stock h

res stock

std

UEC UEC

HSPF

HSPF __ _ _

_ = ⋅ (5.20)

Where,

UECres_stock_h = annual space-heating energy use associated with the stock equipment in the

RECS household,

HSPFres_stock = the HSPF associated with the stock equipment in the RECS household, and

HSPFstd = the HSPF associated with the increased efficiency level or standard.

The above equation for determining the standard-level annual space-heating energy use is

identical to that for the baseline annual space-heating energy use, with the exception that the HSPF

associated with the increased standard is used in place of the baseline efficiency (e.g., 6.8 SEER).

Thus, the determination of the standard-level annual space-heating energy use is based upon the

same information as used for the baseline energy use, namely, the stock annual space-heating energy

use and efficiency. 

Commercial

For the commercial building heating-performance of heat pumps, the standard-level annual

space-heating energy use (UECcomm_std_h) is defined by the following equation taken from the DOE

test procedure:

Where,

DHR = standardized design heating requirement nearest to the heating capacity of the

system,

HSPFstd = the HSPF associated with the increased efficiency level or standard,

FLEOHheat = the full-load equivelent operating hours for space-heating, and

0.77 = factor to adjust the calculated design heating requirement and heat load hours

to the actual load experienced by a heating system.

In order to be consistent with the cost data provided by manufacturers, the heating capacity of the

equipment is assumed to be 36,000 Btu/hr resulting in the DHR being set to 36,000 Btu/hr. All

manufacturer cost data provided by ARI are based on a system with a 3-ton cooling capacity with

a corresponding heating capacity of 36,000 Btu/hr.

The above equation for determining the standard-level annual space-heating energy use is

identical to that for the baseline annual space-heating energy use, with the exception that the HSPF

associated with the increased standard is used in place of the baseline efficiency (i.e., 6.8 HSPF).

Thus, the determination of the standard-level annual space-heating energy use is based upon the

same information as used for the baseline energy use, namely, the FLEOHs.

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Assumptions

Residential

The assumptions for determining the stock annual space-heating energy use and the stock

space-heating efficiency have been discussed in the previous section (Section 5.2.3.3). The

weighted-average stock annual space-heating energy use and weighted-average stock efficiency are

3921 kWh/yr and 6.77 HSPF, respectively. 

Based on the above weighted-average values and the use of Eqn 5.19, weighted-average

standard-level annual space-heating energy use values can be determined. Table 5.23 shows the

weighted-average annual space-heating energy use values for standard-levels of 7.1 through 7.7

HSPF and 8.8 HSPF. It is worth reiterating that the values shown in Table 5.23 are the weightedaverage values associated with each standard-level. In the course of conducting the LCC analysis

with Crystal Ball, the energy use due to a particular standard-level is determined for each household

in RECS based on the unique age and space-heating energy use associated with that household.

Table 5.23 Residential Heat Pump Weighted-Average Annual Space-Heating

Energy Use scaled to HSPF

Standard-Level Heat Pumps

HSPF (Btu/W]hr) kWh/yr

survey 6.77a 3921a

scaled 6.8 3904

7.1 3739

7.4 3603

7.7 3447

8.8 3016

a

 RECS-based weighted-average values for household equipment in use in 1997.

Commercial

The assumptions for determining the FLEOHs necessary for determining the commercial

baseline annual space-cooling energy use have been discussed in the previous section (Section

5.2.3.3). The weighted-average baseline annual space-heating energy use is 2654 kWh/yr. 

Rather than using Eqn. 5.19, weighted-average standard-level space-heating energy use

values can be determined by simply by multiplying the baseline energy use by the ratio of the

baseline efficiency (i.e., 6.8 HSPF) to the standard-level efficiency. Table 5.24 shows the weightedaverage annual space-cooling energy use values for standard-levels of 7.1 through 7.7 HSPF and 8.8

HSPF. It is worth reiterating that the values shown in Table 5.24 are only the weighted-average

values associated with each standard-level. In the course of conducting the LCC analysis with

Crystal Ball, the energy use due to a particular standard-level is determined for each commercial

building. 

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Table 5.24 Commercial Building Heat Pump Weighted-Average Annual Space-Heating

Energy Use scaled to HSPF

Standard-Level Space-Heating Energy Use

HSPF (Btu/W]hr) kWh/yr

Baseline 6.8 2654

Scaled 7.1 2542

7.4 2439

7.7 2344

8.8 2051

Weighted-average annual space-heating energy use values for the entire building stock are

based on the same scaling method used for determining the weighted-average residential and

commercial energy use values. For coming up with the overall energy use values, the overall stock

space-heating energy use values and efficiencies for heat pumps are first determined. Based on the

assumption that 90% of the heat pump stock reside in households (with the remaining 10% residing

in commercial buildings), the overall energy use and efficiency values are determined by multiplying

the residential and commercial values by 90% and 10%, respectively, and then summing the result.

In lieu of having stock energy use values and efficiencies for commercial equipment, the baseline

(i.e., 6.8 HSPF) energy use and efficiency are used. Thus, the resulting overall weighted-average

stock space-heating energy use value is 3794 kWh/yr. The resulting overall weighted-average stock

efficiency is 6.78 HSPF for heat pumps. Table 5.25 summarizes the overall weighted-average

annual space-heating energy use values for each standard-level. Again, it is must be emphasized that

the values shown in Table 5.25 are only the weighted-average values associated with each standardlevel. In the course of conducting the LCC analysis with Crystal Ball, the energy use due to a

particular standard-level is determined for each residential and commercial building.

Table 5.25 Overall Heat Pump Weighted-Average Annual Space-Heating Energy Use

scaled to HSPF

Standard-Level Heat Pumps

HSPF (Btu/W]hr) kWh/yr

stock 6.78 3794

scaled 6.8 3780

7.1 3621

7.4 3474

7.7 3339

8.8 2921

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5.2.3.5 Average Electricity Price

Definition

Average electricity price is the mean price paid for all electricity. For households, it is the

price paid by the 1997 RECS households examined. For commercial buildings, it is the price paid

by each of the 77 nationally representative buildings modeled.

Approach

Residential

Distributions of average electricity prices were prepared for groups of 1997 RECS

households with central air conditioners and with heat pumps. Because the average electricity price

reported in RECS is the average price for the local utility and not the household’s own average price,

average electricity prices were calculated directly from household billing data.

Commercial

The procedure for developing average electricity prices for the 77 nationally representative

commercial buildings matches each building’s space-conditioning load and demand (determined

from the computer modeling analysis for establishing FLEOHs) to actual modeled commercial

tariffs. Customer energy bills are then calculated for the building on a monthly basis. The monthly

bill (in 1998$) is divided by the monthly energy consumption (in kWh) to come up with an average

monthly electricity price (in $/kWh). An annual average electricity price is determined by averaging

the twelve monthly average electricity rates.

Since several tariffs were applied to each building, the average electricity price calculated

from each tariff was weighted by the number of customers covered by the tariff to come up with an

weighted-average average electricity rate for each building.

Assumptions

Residential

Figures 5.17 and 5.18 show the distributions of average electricity prices that were used in

the LCC analysis for those 1997 RECS households with central air conditioners and heat pumps,

respectively. The weighted-average average electricity price for central air conditioners is 8.90

¢/kWh while for heat pumps it is 7.39 ¢/kWh. Both electricity prices are for the year 1998 in 1998$.

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0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Average Electricity Price (cents/kWh)

Percent of Households

Figure 5.17 Percent of Households with Central Air Conditioners by

Average Electricity Prices (Source: U.S. DOE-EIA, 1997 RECS)

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Average Electricity Price (cents/kWh)

Percent of Households

Figure 5.18 Percent of Households with Heat Pumps by Average

Electricity Prices (Source: U.S. DOE-EIA, 1997 RECS)

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Commercial

Tariffs for the year 1997 were collected from 30 electric utilities through out the U.S. for

purposes of developing commercial building average electricity rates. Although most of the utilities

were investment owned utilities (IOU), six of the companies were municipal utilities and two were

rural cooperatives. Each utility has several tariffs which can be applied to their customers. The

customer’s peak power demand dictates which tariff is applicable. Thus, for the 77 nationally

representative buildings analyzed, only those utility tariffs which matched the building’s modeled

peak demand characteristics were applied to calculate an energy bill. The methodology for matching

building peak characteristics to tariffs is documented in a DOE report on marginal energy prices16.

As it turns out, only one tariff from each utility was applicable to a building’s modeled peak demand.

Thus, for each of the 77 commercial buildings, a total of 30 tariffs (one from each utility) were

applied. 

Table 5.26 summarizes the 30 electric utilities for which tariffs were collected. In Table 5.26

the number of customers covered by the tariffs which were modeled and applied to the 77

commercial buildings are provided. As can be seen from Table 5.26, 21.1% of the U.S. commercial

customer base are represented with the tariffs which were modeled and applied to the 77 buildings.

For each of the 77 buildings, the average electricity prices calculated from each tariff are weighted

by the number of customers represented by the tariff to come up with a customer weighted-average

average electricity price. 

Figure 5.19 show the distribution of average electricity prices for commercial buildings using

either central air conditioners or heat pumps. The weighted-average average electricity price is 7.95

¢/kWh. The electricity price is for the year 1998 in 1998$.

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Table 5.26 Characterization and Summary of Commercial Electric Utility Sample

Utility State Type

Number of Customers Covered

by Modeled Tariffs

Alabama Power AL IOU 76,417

Appalachian Power Company VA IOU 78,554

Arizona Public Service AZ IOU 73,663

Benton Public Utility Dept WA Muni 4,174

Boston Edison MA IOU 80,255

Central Power and Light TX IOU 74,107

City of Chattanooga TN Muni 19,563

City of Gillette WY Muni 4,239

City of Oxford MS Muni 854

Cleveland Electric Illuminatin OH IOU 63,161

Cleveland Utilities OH Muni 3,484

Commonwealth Edison Co IL IOU 291,143

Detroit Edison MI IOU 166,003

Douglas WA Co-op 1,115

Jersey Central Power & Light C NJ IOU 104,922

LADWP CA Muni 165,630

Madison G&E WI IOU 14,815

Niagara Mohawk Power Corp NY IOU 143,590

NSP (MN) MN IOU 110,807

NSP (WI) WI IOU 27,449

Ohio Power Company OH IOU 6,442

Pacific Gas and Electric CA IOU 352,776

Pennsylvania Power & Light Co PA IOU 143,849

PEPCO MD IOU 53,620

Poudre Valley CO Co-op 2,101

Seattle City Light WA IOU 40,794

SoCal Edison CA IOU 419,163

Union Electric Co. MO IOU 114,262

Virginia Power Company VA IOU 137,813

Wisconsin Electric Power Co WI IOU 85,735

Total Customers in Selected Tariffs 2,860,500

Total U.S. Commercial Customers 13,540,374

Percent Coverage with Selected Tariffs 21.1%

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0%

10%

20%

30%

40%

50%

60%

7.8 7.9 8 8.1

Average Electricity Price (cents/kWh)

Percentage of Commercial Buildings

Figure 5.19 Percent of Commercial Buildings with Space-Conditioning

Equipment by Average Electricity Prices

ELmarg marg marg = ⋅ +⋅ a EL _ _ sum win b EL (5.22)

5.2.3.6 Marginal Electricity Price

Definition

Marginal electricity prices are the prices faced by households or commercial buildings for

the last kWh of electricity purchased. A household’s or commercial building’s marginal price can

be higher or lower than its average price, depending on the relationship between the block rate price

structure facing the building and the size of customer charges and/or other charges included in the

buildings’s electricity bill.

Approach

Residential

Marginal electricity prices were estimated directly from RECS household data by calculating

the slopes of regression lines that relate customer bills and customer usage. The slopes of the

regressions for four “summer” months (June to September) and, separately, for the remaining

(“winter”) months were calculated17.

For purposes of conducting the LCC analysis, an annual marginal electricity price was

derived from the “summer” and “winter” marginal prices. The following expression was used for

the derivation:

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Where,

a = seasonal weighting factor for the “summer” marginal electricity price,

ELmarg_sum = “summer” marginal electricity price,

b = seasonal weighting factor for the “winter” marginal electricity price, and

ELmarg_win = “winter” marginal electricity price.

Because central air conditioners and heat pumps are seasonal household appliances that use

energy during specific times of the year, the “summer” and “winter” prices must be weighted

appropriately in order to reflect their seasonal energy use. Simulated household cooling and heating

loads based on the DOE-2 modeling of residential buildings were used to establish the appropriate

seasonal weighing factors18. 

Commercial

As presented in the discussion of average electricity prices, the procedure for developing

average electricity prices for the 77 nationally representative commercial buildings matches each

building’s space-conditioning load and demand (determined from the computer modeling analysis

for establishing FLEOHs) to actual modeled commercial tariffs. Customer energy bills are then

calculated for the building. The energy bill (in 1998$) is divided by the energy consumption (in

kWh) to come up with an average electricity price (in $/kWh). 

In the case of developing marginal electricity prices for space-cooling, energy bills for spacecooling are calculated for both the baseline case (i.e., 10 SEER) and a standards case. The

difference in the space-cooling energy bills (in dollars) is divided by the usage difference (in kWh)

to give a “marginal” rate of $/kWh for the increment of space-cooling energy saved. For purposes

of simplifying the analysis, only a standard-level increase of 20% (i.e., 12 SEER) was considered.

Thus, the space-cooling marginal rate developed for a 20% increase in the standard was assumed to

be applicable for all standard-level cases. 

Since detailed building loads and demands were not available for space-heating, marginal

electricity prices for space-heating could not be developed. Thus, average electricity prices were

used to determine the energy costs associated with the operation of heat pumps during the spaceheating season.

Since several tariffs were applied to each building, the marginal electricity price calculated

from each tariff was weighted by the number of customers covered by the tariff to come up with an

weighted-average marginal electricity rate for each building.

Assumptions

Residential

The DOE-2 modeling of U.S. residential buildings was conducted on a regional basis taking

into account the vintage of the housing stock. Prototypical homes were constructed by region and

vintage based on data from U.S. Census Bureau reports, the National Association of Home Builders

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(NAHB), and the F.W. Dodge Corporation19. Table 5.27 shows the housing characteristics of the

prototypical households with their location and vintage along with a breakdown of their cooling and

heating loads during the “summer” and “winter” seasons. The “summer” and “winter” seasons are

equivalent to the “summer” and “winter” months defined above. With regard to the breakdown of

building loads, the percentage signifies that portion of the building load which occurs during each

season. The percentage breakdowns under the “Cooling Only” columns specify that portion of the

cooling load which occurs during the “winter” and “summer” seasons. The breakdowns under the

“Heating Only” columns specify that portion of the heating load which occurs during each season.

And finally, the percentage breakdowns under the “Cooling and Heating” columns specify that

portion of the total space-conditioning load (heating and cooling) which occurs during the “summer”

and “winter” seasons. 

Based on the assumption that the seasonal building loads can be used as a proxy for actual

space-conditioning energy consumption, the percentage breakdowns provided in Table 5.27 become

the seasonal weighting factors which are used to calculate the annual marginal electricity price from

the “summer” and “winter” marginal prices. For those RECS households with central air

conditioners, the seasonal weighting factors are based upon the percentage breakdowns listed under

the “Cooling Only” columns while those RECS households with heat pumps use the percentage

breakdowns listed under the “Cooling and Heating” columns. The “Heating Only” columns in Table

5.27 are provided for informational purposes only.

In order to map the appropriate seasonal weighting factors from Table 5.27 to a RECS

household, the general geographic location of the household plus its age are required. For the

households surveyed, RECS specifies the household’s geographic location by Census Division or

large state age and the building’s age.

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le 5.27 Prototypical Household Characteristics and Building Load Seasonal Breakdowns

Building Load Seasonal Breakdown

Housing Characteristics Cooling Only Heating Only Cooling and Heating

Prototype Year Built No. of Stories Floor Area Window Area Wall Type Foundation Type Winter Summer Winter Summer Winter Summer

A pre 1940s 2 1440 280 Wood Basement 7% 93% 97% 3% 88% 12%

B 1950-1970 2 2220 430 Wood Basement 7% 93% 98% 2% 89% 11%C 1980s 2 2090 261 Wood Basement 6% 94% 98% 2% 89% 11%

D 1990s 2 2280 285 Wood Basement 6% 94% 98% 2% 87% 13%

A pre 1940s 2 1400 277 Wood Basement 8% 92% 99% 1% 85% 15%

B 1950-1970 2 1960 385 Wood Basement 8% 92% 99% 1% 86% 14%C 1980s 2 2090 243 Wood Basement 5% 95% 99% 1% 83% 17%

D 1990s 2 2280 265 Wood Basement 4% 96% 99% 1% 84% 16%

A pre 1940s 2 1580 300 Wood Basement 9% 91% 98% 2% 86% 14%

B 1950-1970 1 1380 264 Brick Basement 9% 91% 99% 1% 89% 11%C 1980s 2 2220 275 Alum Basement 9% 91% 99% 1% 87% 13%

D 1990s 2 2420 300 Alum Basement 10% 90% 99% 1% 84% 16%

A pre 1940s 1 1580 310 Wood Basement 15% 85% 98% 2% 73% 27%

B 1950-1970 1 1100 216 Wood Basement 14% 86% 99% 1% 74% 26%C 1980s 2 2220 282 Wood Basement 12% 88% 99% 1% 72% 28%

D 1990s 2 2420 307 Wood Basement 12% 88% 99% 1% 67% 33%

 A pre 1940s 1 1165 207 Wood Crawl 16% 84% 99% 1% 78% 22%

B 1950-1970 1 1415 249 Brick Crawl 16% 84% 99% 1% 79% 21%C 1980s 2 2180 288 Alum Basement 12% 88% 99% 1% 73% 27%

D 1990s 2 2390 316 Alum Basement 11% 89% 99% 1% 75% 25%

A pre 1940s 1 1165 207 Wood Crawl 21% 79% 99% 1% 72% 28%

B 1950-1970 1 1415 249 Brick Crawl 17% 83% 100% 0% 74% 26%C 1980s 2 2180 264 Wood Basement 17% 83% 100% 0% 62% 38%

D 1990s 2 2390 289 Wood Basement 16% 84% 100% 0% 62% 38%

A pre 1940s 1 1165 207 Wood Crawl 46% 54% 100% 0% 50% 50%

B 1950-1970 1 1415 249 Brick Crawl 44% 56% 100% 0% 47% 53%C 1980s 1 1620 214 Stucco Slab 44% 56% 100% 0% 45% 55%

D 1990s 1 1830 242 Stucco Slab 44% 56% 100% 0% 45% 55%

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27 Prototypical Household Characteristics and Building Load Seasonal Breakdowns (cont.)

Building Load Seasonal Breakdown

Housing Characteristics Cooling Only Heating Only Cooling and Heating

Prototype Year Built No. of Stories Floor Area Window Area Wall Type Foundation Type Winter Summer Winter Summer Winter Summer

A pre 1940s 1 1055 216 Wood Slab 18% 82% 100% 0% 56% 44%

B 1950-1970 1 1390 286 Brick Slab 15% 85% 100% 0% 54% 46%C 1980s 1 1620 214 Wood Slab 14% 86% 100% 0% 50% 50%

D 1990s 1 1830 242 Wood Slab 13% 87% 100% 0% 52% 48%

A pre 1940s 1 1055 216 Wood Slab 32% 68% 99% 1% 55% 45%

B 1950-1970 1 1390 286 Brick Slab 29% 71% 99% 1% 52% 48%C 1980s 1 1620 214 Brick Slab 26% 74% 99% 1% 47% 53%

D 1990s 1 1830 242 Brick Slab 25% 75% 99% 1% 48% 52%

A pre 1940s 1 975 177 Wood Basement 29% 71% 100% 0% 45% 55%

B 1950-1970 1 1080 196 Brick Slab 23% 77% 100% 0% 36% 64%C 1980s 1 1660 179 Stucco Slab 20% 80% 100% 0% 32% 68%

D 1990s 1 1880 203 Stucco Slab 20% 80% 100% 0% 32% 68%

A pre 1940s 1 1400 244 Wood Crawl 2% 98% 90% 10% 87% 13%

B 1950-1970 1 1390 242 Wood Crawl 2% 98% 91% 9% 89% 11%C 1980s 2 2070 383 Wood Crawl 2% 98% 93% 7% 88% 12%

D 1990s 2 2290 424 Wood Crawl 1% 99% 93% 7% 89% 11%

A pre 1940s 1 1400 244 Wood Crawl 29% 71% 93% 7% 80% 20%

B 1950-1970 1 1390 242 Stucco Crawl 34% 66% 93% 7% 84% 16%C 1980s 2 2070 325 Stucco Slab 42% 58% 92% 8% 81% 19%

D 1990s 2 2290 360 Stucco Slab 44% 56% 92% 8% 82% 18%

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0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Marginal Electricity Price (kWh/yr)

Percent of Households

Figure 5.20 Percent of Households with Central Air Conditioners by

Marginal Electricity Prices

Figures 5.20 and 5.21 show the distributions of annual marginal electricity prices that were

calculated for those RECS households with central air conditioners and heat pumps, respectively.

The weighted-average annual marginal electricity price for central air conditioners is 8.62 ¢/kWh

while the price for heat pumps is 6.86 ¢/kWh. Both electricity prices are for the year 1998 in 1998$.

The weighted-average marginal electricity prices for central air conditioners and heat pumps are

lower than their corresponding weighted-average average electricity prices of 8.90 ¢/kWh and 7.39

¢/kWh for central air conditioners and heat pumps, respectively. It is interesting to note that the

range of marginal electricity prices as depicted in Figures 5.20 and 5.21 are greater than those for

the average electricity prices (Figures 5.17 and 5.18).

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0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Marginal Electricity Price (cents/kWh)

Percent of Households

Figure 5.21 Percent of Households with Heat Pumps by Marginal

Electricity Prices

Commercial

As was discussed earlier for average electricity prices, tariffs for the year 1997 were collected

from 24 electric utilities through out the U.S. for purposes of developing commercial building

marginal electricity rates. Figure 5.22 show the distribution of marginal electricity prices for

commercial buildings using central air conditioners or heat pumps in the cooling-mode. The

weighted-average marginal electricity price is 8.08 ¢/kWh. The electricity price is for the year 1998

in 1998$. As noted earlier, marginal electricity prices for heat pumps during the heating season were

not developed and average electricity prices were used as a proxy.

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0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

7.7 7.8 7.9 8 8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9

Marginal Electricity Price (cents/kWh)

Percent of Commercial Buildings

Figure 5.22 Percent of Commercial Buildings with Space-Cooling

Equipment by Marginal Electricity Prices

5.2.3.7 Electricity Price Trend

Definition

The relative change in electricity prices for future years out to the year 2030.

Approach

Estimating future electricity rates is very difficult. In some states, the electricity supply

industry is undergoing restructuring. Previously, each household or commercial building customer

was assigned to a particular utility company, and the rates offered by that utility could be obtained

from surveys. In the future, with restructuring, households and commercial building customers will

be able to purchase electricity from a large set of suppliers. 

A projected trend in national average electricity prices is applied to each household’s and

commercial building’s energy prices, after accounting for “value of savings” (described above). In

the life-cycle cost (LCC) spreadsheets, the user can select from the following scenarios:

1) Constant energy prices at 1999 values

2) Energy Information Administration Annual Energy Outlook 2000, High Economic

Growth20

3) Energy Information Administration Annual Energy Outlook 2000, Reference Case21

4) Energy Information Administration Annual Energy Outlook 2000, Low Economic

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4

5

6

7

8

9

1995 2000 2005 2010 2015 2020 2025 2030

cent/kWh

High Growth

AEO 2000

GRI 1998

Low Growth

Figure 5.23 Electricity Price Trends

Growth22

5) Gas Research Institute 1998 Baseline Projection23

Figure 5.23 shows the trends for the last four of those projections. The values in later years

(i.e. after 2015 for GRI and after 2020 for all others) are interpolated from their relative sources.

Interpolation is needed because the sources used do not forecast beyond 2020 (or 2015 in the case

of the GRI forecast). To arrive at values for these later years electricity prices were held constant

at 2020 levels on the assumption that the transition to a restructured utility industry will have been

completed.. 

Assumptions

The current LCC analysis assumes the trend from the AEO2000 Reference Case. The LCC

spreadsheets have the capability to use the AEO2000 High and Low Growth price trends, the 1998

Gas Research Institute Baseline Projection, and constant energy prices.

5.2.3.8 Repair Cost

Definition

The repair cost is the cost to the consumer for replacing or repairing components which have

failed in the space-conditioning equipment. 

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RC EQP

LIFE = 05. ⋅ (5.23)

Approach

The assumed annualized repair cost for baseline efficiency central air-conditioning and heat

pump equipment (i.e., the cost the consumer pays annually for repairing the equipment) and

equipment with efficiencies of 13 SEER and greater are based on the following expression:

Where,

EQP = equipment price (consumer price for only the equipment), and

LIFE = the average lifetime of the equipment (18.4 years).

Equipment with efficiencies of 11 through 13 SEER were assumed to incur a 1% increase

in repair cost over the minimum efficiency level (10 SEER). 

Assumptions

The rationale for assuming essentially flat repair costs through efficiencies up to and

including 13 SEER pertains to the level of technology being used at these system efficiency levels.

Through 13 SEER, system technology generally does not incorporate sophisticated electronic

components which are believed to incur higher repair costs. Increases in SEER are generally

achieved through more efficient single-speed compressors or more efficient and/or larger heat

exchanger coils. Systems with efficiencies beyond 13 SEER start to incorporate modulating blowers

or compressors which are generally believed to be more susceptible to failure. 

Table 5.28 shows the average repair costs by standard-level for split and single package

central air conditioners and heat pumps. Since equipment prices are a function of variables which

are represented by distributions rather than single point-values (e.g., manufacturer, distributor,

dealer, and builder markups, installation costs, and sales tax), repair costs are actually represented

by a distribution of values rather than just the average values shown in Table 5.28.

Table 5.28 Central Air Conditioner and Heat Pump Average Repair Costs

SEER Split System A/C Single Package A/C Split System HP Single Package HP

Btu/W^hr ARI ARI ARI ARI

10 $26 $34 $38 $39

11 $26 $34 $38 $39

12 $27 $34 $38 $40

13 $27 $35 $39 $40

18 $55 $67 $70 $74

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0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

$0

$10$20$30$40$50$60$70$80$90

$100$110$120$130

Annual Maintenance Cost

Probablit

y

Figure 5.24 Distribution of Annual Maintenance Costs

5.2.3.9 Maintenance Cost

Definition

The maintenance cost is the cost to the consumer of maintaining equipment operation. The

maintenance cost is not the cost associated with the replacement or repair of components which have

failed. Rather, the maintenance cost is associated with general maintenance (e.g., checking and

maintaining refrigerant charge levels and cleaning heat exchanger coils). 

Approach

Data from Service Experts24, an HVAC service company, were used to establish service

costs.

Assumptions

Figure 5.24 shows the distribution of maintenance costs which are assumed in the LCC

analysis. As the figure shows, 73% of consumers are assumed to incur no service cost while 27%

of consumers are assumed to incur an annual service cost of $135. The weighted-average

maintenance cost from this distribution is $36. The distribution of maintenance costs depicted in

Figure 5.24 are assumed to apply to all product types (split or package systems, air conditioners or

heat pumps). 

The maintenance cost is assumed not to change with increased efficiency. The rationale

being that the general maintenance of more efficient products should not be impacted by the more

sophisticated components that they contain. In other words, general maintenance such as the

checking of refrigerant charge levels and the cleaning of heat exchanger coils should be the same

regardless of the sophistication level of the system components.

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5.2.3.10 Lifetime and Compressor Replacement Cost

Definition

The lifetime is the age at which the central air conditioner or heat pump is retired from

service. 

Approach

A literature search was conducted to determine the most relevant and accurate lifetime data

for central air conditioners and heat pumps.

Assumptions

In choosing a value for lifetimes of central air conditioners and heat pumps, a variety of

sources were reviewed. These studies on air conditioner and heat pump lifetime indicate that there

is a wide range of values. Table 5.29 summarizes the sources of lifetime information with their

respective mean or median lifetime value. 

Table 5.29 Central Air Conditioner and Heat Pump Mean and Median Lifetimes

Central AC Heat Pump

Source years a years a

Appliance Magazineb. The Life Expectancy/Replacement Picture, Sept. 1998 25 13 14

National Association of Home Builders. Housing Facts c

, Figures, and Trends, 1998 26 15 15

1995 ASHRAE Applications Handbook d 27 15 15

M.E. Bucher et al, American Electric Power Service Corp. 1990. “Heat Pump Life and

Compressor Longevity in Diverse Climates” 28 - 19 e

K.A. Pientka, Commonwealth Edison Co. 1987. “Heat Pump Service Life and

Compressor Longevity in a Northern Climate” 29 - 15 to 16 e

C.C. Hiller, EPRI and N.C. Lovvorn, Alabama Power Co. 1987. “Heat Pump

Compressor Life in Alabama” 30 - 20 e

J.E. Lewis, Easton Consultants. 1987. “Survey of Residential Air-to-Air Heat Pump

Service Life and Maintenance Issues” 31 12.1 10.9

MTSC, Inc.f

 Energy Capital in the U.S. Economy, prepared for the Office of Policy,

Planning, and Evaluation, U.S. Department of Energy, Nov. 1980 32 12 12

a Mean lifetimes except where noted.

b

 Based on first-owner use. Central AC min life = 8, max life = 18. Heat Pump min life = 10, max life = 17. 

c

 Sources: Air Conditioning and Refrigeration Institute; Air Conditioning, Heating, and Refrigeration News; Air Movement and

Control Association; American Gas Association; American Society of Gas Engineers; ASHRAE

d

 Source for Central A/C: Akalin, M.T. 1978. “Equipment life and maintenance cost survey”, ASHRAE Transactions 84(2):94-106.

Source for Heat Pump: ASHRAE Technical Committee 1.8, 1986.

e

 Median lifetime.

f

 Based on retirement function.

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0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 5 10 15 20 25

Age (year)

% Surviving

Figure 5.25 Retirement Function for Central Air Conditioners and

Heat Pumps

The above sources report mean and median lifetimes ranging from 10.9 to 20 years. The 1990

ASHRAE technical paper by Bucher, et al, has the most recent and most detailed information on heat

pump life available, based on a survey performed for the Electric Power Research Institute of 2,184

heat pump installations in a seven-state region of the United States. The sources that report shorter

average lifetimes are based on data of a lesser quality, and are therefore considered less reliable. For

example, in the case of Appliance Magazine, the reported lifetime values are based on expert opinion

rather than empirical data.

Central air conditioners and heat pumps produced at some future date may have different

lifetimes than those in the same class produced in the past. The projections of lifetimes and other

parameters used in the analysis should be based on observed empirical trends, as well as expert

knowledge of likely changes in the industry, since future changes are not always straight-line

projections of past trends. While expert judgement is crucial, however, it must have a strong

empirical basis. With this in mind, it is felt that the value for lifetimes in the Bucher paper are the

most sound, given available evidence of past performance and recent trends.

Figure 5.25 shows the retirement function that was developed from the Bucher paper. It

should be noted that the retirement function developed from the survey covered the first 19 years of

the product’s life. In order to complete the entire retirement function, an extrapolation was used

based on estimates performed by others.33 Although the survey was conducted only on heat pumps,

the retirement function was used as the basis for estimating central air conditioner product lifetime

in addition to the lifetime of heat pumps. The retirement function depicted in Figure 5.21 yields a

weighted-average lifetime of 18.4 years. 

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The heat pump survey also indicates that essentially all heat pump owners replace their original

compressor once in the lifetime of system. In accordance with the survey data, we have assumed the

compressor to be replaced in the 14th year of the system’s life. Because more efficient systems tend

to use more efficient and, thus, more expensive compressors, the compressor replacement cost is

assumed to increase as system efficiency increases. Table 5.30 shows the manufacturer cost, average

consumer price, and the present value of the consumer price (discounted based on an average rate

of 5.6%). It is important to note that the compressor replacement price is the price for the

compressor only. The labor cost associated with the compressor’s installation is assumed to remain

constant as system efficiency increases.

Table 5.30 Compressor Replacement Costs

Split System and Single Package A/C Split System and Single Package Heat Pump

Efficiency Manufacturer

Cost

Consumer Price Manufacturer

Cost

Consumer Price

SEER In year replaced Present Value In year replaced Present Value

10 $122 $278 $131 $124 $283 $133

11 $152 $332 $156 $153 $335 $157

12 $153 $334 $157 $153 $335 $157

13 $167 $360 $169 $169 $364 $171

18 $221 $458 $215 $279 $564 $265

5.2.3.11 Discount Rate

Definition

The rate at which future expenditures are discounted to establish their present value.

Approach

Past methodologies for establishing discount rates have relied upon defining the share of

various finance methods that are used for purchasing an appliance and then determining the

associated interest rates for each of the finance methods. This method focuses on establishing the

type of financing utilized at the time of purchase. For equipment financed through the purchase of

a new home, a second mortgages, or a home equity lines of credit, this approach is reasonable. But

for equipment purchased to replace old or failed equipment where cash or some form of credit is

used to finance the acquisition, it is more appropriate to establish how the purchase affects a

consumer’s overall household financial situation. For example, even though the purchase might be

financed through a dealer loan or some other short-term financing vehicle, the more probable effect

of the purchase is to either cause the consumer to incur additional credit card debt or forego

investment in some type of savings-related asset. Cash that was once available to either pay for

household expenses or to invest in an asset like the stock market or a savings account now must be

earmarked to pay off the equipment purchase, thus either causing the consumer to incur additional

credit card debt or to lose the opportunity to earn income from their assets. 

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Assumptions

With regard to equipment obtained through the purchase of a new home, data from the Air

Conditioning, Heating, and Refrigeration News34 indicate that 34% of central air conditioner and

heat pump shipments went to new homes. Thus, we assumed that 34% of equipment purchases are

financed through new home mortgages. 

Of the remaining 66% of shipments, a portion were assumed to be financed with second

mortgages. We assumed that the remaining shipments were purchased with methods that impacted

the homeowner’s finances by either increasing their credit card debt or reducing investment. The

methodology for determining the specific share captured by each finance method relied upon

determining those households in the Federal Reserve Board’s 1998 Survey of Consumer Finances

(SCF)35 with second mortgages, credit card debt, and holdings in various assets (i.e., stocks, mutual

funds, bonds, savings bonds, certificate of deposits, and transaction accounts (e.g., savings or

checking accounts)). These specific shares or percentages are shown in Table 5.31. Table 5.31

demonstrates how each finance method share was normalized to arrive at the percentages used in the

discount rate analysis (it is the last column in Table 5.31 which is used to represent the share

captured by each finance method).

Table 5.31 Finance Method Shares

Finance Method

1998 SCF: Percent

of Households with

Finance Method

Assets Normalized

to Total a 91%

Share

Finance Methods w/o

New Home

Normalized to Total

100%

All Finance

Methods

Normalized to

Total 100%

New Home - - - 34%a

Second Mortgage 44% 44% 32% 21%

Credit Card 5% 5% 3% 2%

All Assets 91% 91% 65% 43%

Transaction Accounts 91% 50% 36% 24%

CD 15% 9% 6% 4%

Savings Bonds 19% 11% 8% 5%

Bonds 3% 2% 1% 1%

Stocks 19% 11% 8% 5%

Mutual Funds 17% 9% 7% 4%

a Based on data from the Air Conditioning, Heating, and Refrigeration News.

After establishing the share captured by each finance method, the range of interest rates due

to each method were established. The 1998 SCF was used to establish the range of interest rates for

new home mortgages, second mortgages, and credit cards. A variety of sources were used to

establish the interest rates for the various assets described above. 

Figures 5.26 through 5.28 show the distribution of nominal (non-adjusted) interest rates

drawn from the 1998 SCF for new home mortgages, second mortgages, and credit cards,

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0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

0%1%2%3%4%5%6%7%8%9%

10%11%12%13%14%15%16%17%18%19%20%

Nominal Interest Rate

Probability

Figure 5.26 Distribution of New Home Mortgage Nominal Interest Rates

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

0%1%3%4%4%5%7%7%8%9%

10%11%12%13%14%15%16%17%18%19%20%21%22%

Nominal Interest Rate

Probability

Figure 5.27 Distribution of Second Mortgage Nominal Interest Rates

respectively. The range of after-tax rates for new home and second mortgages were derived

assuming a tax of 28% and a 1998 inflation rate of 1.56%. Credit card nominal interest rates were

adjusted to real interest rates by using the 1998 inflation rate of 1.56%.

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0%

2%

4%

6%

8%

10%

12%

14%

16%

0%2%4%6%8%

10%12%14%16%18%20%22%24%26%28%30%32%34%36%38%40%

Nominal Interest Rate

Probability

Figure 5.28 Distribution of Credit Card Nominal Interest Rates

Rates of return on certificates of deposit, savings bonds, and bonds were based on historical interest

rates associated with six-month, secondary market CDs (1964-1999)36, one-year Treasury Bills

(1959-1999)37, and Moody’s AAA Corporate Bonds (1976-1999)38, respectively. Historical stock

and mutual fund interest rate data were based on historical returns from the Standard & Poor 500

(1950-1999)39 and the Nasdaq stock market (1985-1999)40, respectively. For each of the above

assets, the historical data provided a distribution of interest rates where each year’s corresponding

rate of return was weighted equally. Transaction account real interest rates were assumed to range

from zero to 4%. Table 5.32 shows the historical annual real interest rates associated for each of the

above assets. 

Table 5.32 Annual Real Interest Rates for Various Financial Assets

Year Mutual Funds Stocks Bonds CDs Savings Bonds

1999 13% 60% 5% 3% 3%

1998 24% 34% 5% 4% 3%

1997 21% 12% 5% 3% 3%

1996 14% 19% 4% 3% 2%

1995 28% 36% 5% 3% 3%

1994 -7% -9% 5% 2% 2%

1993 3% 9% 4% 0% 0%

1992 4% 6% 5% 1% 1%

1991 17% 37% 5% 2% 1%

1990 -5% -16% 4% 3% 2%

1989 14% 9% 4% 4% 3%

1988 4% 7% 6% 4% 3%

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Table 5.32 Annual Real Interest Rates for Various Financial Assets (cont.)

Year Mutual Funds Stocks Bonds CDs Savings Bonds

1987 -14% -19% 6% 3% 3%

1986 12% 2% 7% 5% 4%

1985 14% 13% 8% 5% 4%

1984 -2% - 8% 6% 6%

1983 10% - 9% 6% 6%

1982 11% - 8% 6% 5%

1981 -16% - 4% 5% 3%

1980 5% - -2% -1% -3%

1979 -3% - -2% 0% -2%

1978 0% - 1% 1% 0%

1977 -13% - 2% -1% -1%

1976 1% - 3% 0% 0%

1975 8% - - -2% -3%

1974 -40% - - -1% -3%

1973 -22% - - 3% 1%

1972 10% - - 2% 2%

1971 2% - - 1% 0%

1970 3% - - 2% 1%

1969 -16% - - 2% 1%

1968 8% - - 2% 1%

1967 8% - - 2% 2%

1966 -16% - - 3% 2%

1965 4% - - 3% 2%

1964 9% - - 3% 2%

1963 12% - - - 2%

1962 -9% - - - 2%

1961 15% - - - 2%

1960 3% - - - 2%

1959 7% - - - 4%

1958 30% ----

1957 -14% ----

1956 5% ----

1955 25% ----

1954 37% ----

1953 -7% ----

1952 8% ----

1951 2% ----

1950 18% ----

Table 5.33 summarizes the real interest rates associated with each of the finance methods.

Also provided is the weighted-average discount rate of 5.6% that is calculated from the mean interest

rates for each finance method. It should also be noted that real interest rates below 0% were not

considered. Since negative real interest rates represent approximately 7% of the entire distribution

of interest rates, an equal percentage of excessively high interest rates were removed from the

distribution. This had the effect of eliminating real interest rates in excess of 18%.

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Table 5.33 Real Interest Rates associated with each Finance Method

Real Interest Rates a

Finance Method Share Minimum Maximum Mean

New Home Mortgages (after tax) 34% -1.6% 12.8% 4.2%

Second Mortgages (after tax) 2% -1.6% 14.3% 5.9%

Credit Card 21% -1.6% 37.4% 12.0%

Transaction Accounts 24% 0.0% 4.0% 2.0%

Certificates of Deposit 4% -2.2% 6.4% 2.4%

Savings Bonds 5% -3.3% 5.6% 1.8%

Bonds 1% -1.7% 8.8% 4.5%

Stocks 5% -19.4% 60.2% 13.3%

Mutual Funds 4% -40.0% 37.2% 4.5%

Weighted-Average 5.6%

a Real interest rates below 0% and exceeding 18% were not considered in the LCC analysis.

5.2.3.12 Effective Date of Standard

Definition

This is the year at which a new standard is expected to become effective.

Approach

The LCC is calculated for all households as if they each purchase a new central air

conditioner or heat pumps in the year the standard takes affect. The cost of the equipment are based

on this year, however, all dollar values are expressed in 1998 dollars. Annual energy prices are

included for the life of the central air conditioner or heat pump.

Assumption

The new energy efficiency standard for central air conditioners and heat pumps is assumed

to take effect in the year 2006.

5.2.3.13 Base Case Design

Definition

This is the cost and efficiency of the starting point to which different improvement levels of

central air conditioners and heat pumps are compared.

Approach

As detailed earlier, cost data were supplied a baseline (i.e., 10 SEER) and higher efficiency

levels. In the LCC spreadsheets, the user can select any standard-level against which to compare

higher efficiency levels. 

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Assumption

The default assumption for the base case design for both central air conditioners and heat

pumps is the baseline design option (i.e., 10 SEER).

5.2.3.14 Standard Case Design

Definition

The improved efficiency level for comparison with the base case design.

Approach

The LCC spreadsheet user selects the level for the analysis.

Assumption

Analysis is done for all levels for which data were provided. 

5.2.4 LCC Results

This section presents results for LCC for the efficiency improvement levels specified in the

Engineering Analysis (Chapter 4). Results presented here are based on the inputs described in

sections 5.2.2 and 5.2.3. 

As has been detailed in the previous sections, the value of most inputs are uncertain and are

represented by a distribution of values rather than a single point-value. Thus, the LCC results will

also be a distribution of values. But before proceeding with the presentation of the distributional

LCC results, it is worth showing how, on an average basis, the installed consumer costs, annual

operating expenses, and, finally, the life-cycle costs vary with efficiency for each of the four product

classes. 

5.2.4.1 LCC Breakdown based upon Average Input Values

For each product class, Figures 5.29 through 5.40 show how, on an average basis, the

installed consumer costs, annual operating expenses, and life-cycle costs vary with efficiency.

Figures 5.29 through 5.31 pertain to split system air conditioners, Figures 5.32 through 5.34 pertain

to split system heat pumps, Figures 5.35 through 5.37 pertain to single package air conditioners, and

Figures 5.38 through 5.40 pertain to single package heat pumps. 

The figures for installed cost are segmented into equipment and installation price. The figures

for annual operating expense are segmented into annual electricity, repair, maintenance, and

compressor replacement costs. The figures for life-cycle cost are segmented into installed consumer

cost and lifetime operating expense. Although the following figures are based on mean or average

values rather than results from the Crystal Ball analysis, they serve to demonstrate how the various

inputs ultimately impact life-cycle cost.

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$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

10 11 12 13 18

SEER

Installed Consumer Cost

Equipment Price

Installation Price

Figure 5.29 Split A/C: Mean Installed Consumer Costs

$0

$1,000

$2,000

$3,000

$4,000

$5,000

10 11 12 13 18

SEER

Installed Consumer Cost

Equipment Price

Installation Price

Figure 5.32 Split HP: Mean Installed Consumer Costs

$0

$50

$100

$150

$200

$250

$300

$350

10 11 12 13 18

SEER

Annual Operating Cost

Electricity

Compr.

Repair

Maint.

Figure 5.30 Split A/C: Mean Annual Operating Costs

$0

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

10 11 12 13 18

SEER

Life-Cycle Cost

Installed Consumer Cost

Lifetime Operating Cost

Figure 5.34 Split HP: Mean Life-Cycle Costs

$0

$100

$200

$300

$400

$500

$600

$700

10 11 12 13 18

SEER

Annual Operating Cost

Electricity

Compr.

Repair

Maint.

Figure 5.33 Split HP: Mean Annual Operating Costs

$0

$1,000

$2,000

$3,000

$4,000

$5,000

$6,000

$7,000

10 11 12 13 18

SEER

Life-Cycle Cost

Installed Consumer Cost

Lifetime Operating Cost

Figure 5.31 Split A/C: Mean Life-Cycle Costs

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$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

10 11 12 13 18

SEER

Installed Consumer Cost

Equipment Price

Installation Price

Figure 5.35 Pack A/C: Mean Installed Consumer Costs

$0

$1,000

$2,000

$3,000

$4,000

$5,000

10 11 12 13 18

SEER

Installed Consumer Cost

Equipment Price

Installation Price

Figure 5.38 Pack HP: Mean Installed Consumer Costs

$0

$1,000

$2,000

$3,000

$4,000

$5,000

$6,000

$7,000

10 11 12 13 18

SEER

Life-Cycle Cost

Installed Consumer Cost

Lifetime Operating Cost

Figure 5.37 Pack A/C: Mean Life-Cycle Costs

$0

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

10 11 12 13 18

SEER

Life-Cycle Cost

Installed Consumer Cost

Lifetime Operating Cost

Figure 5.40 Pack HP: Mean Life-Cycle Costs

$0

$50

$100

$150

$200

$250

$300

$350

10 11 12 13 18

SEER

Annual Operating Cost

Electricity

Compr.

Repair

Maint.

Figure 5.36 Pack A/C: Mean Annual Operating Costs

$0

$100

$200

$300

$400

$500

$600

$700

10 11 12 13 18

SEER

Annual Operating Cost

Electricity

Compr.

Repair

Maint.

Figure 5.39 Pack HP: Mean Annual Operating Costs

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In reviewing the installed consumer cost results in Figure 5.29 for split system air

conditioners, Figure 5.32 for split system heat pumps, Figure 5.35 for single package air

conditioners, and Figure 5.38 for single package heat pumps, the largest contributor to increased

consumer cost is the equipment price since the installation price remains constant across efficiency.

With regard to annual operating expense, Figure 5.30 for split system air conditioners, Figure

5.33 for split system heat pumps, Figure 5.36 for single package air conditioners, and Figure 5.39

for single package heat pumps show that the largest contributor to the overall operating cost at any

efficiency level is the annual electricity cost. Of course, as efficiency increases, the electricity cost

decreases. At an efficiency of 18 SEER for all product classes, the jump in repair cost that occurs

at this efficiency level negates the reduction in electricity cost that is realized from higher efficiency.

This is especially true for split system and single package air conditioners. Note that for air

conditioning systems, the repair cost is a larger percentage of the overall operating cost than that for

heat pumps. Because the maintenance cost is assumed to remain constant across all efficiency levels,

the overall operating cost is not impacted by the maintenance cost as efficiency increases.

The life-cycle cost results in Figure 5.31 for split system air conditioners, Figure 5.34 for split

system heat pumps, Figures5.37 for single package air conditioners, and Figure 5.40 for single

package heat pumps reveal that as efficiency increases, the installed consumer cost has more of an

impact on the life-cycle cost than the lifetime operating cost. Even in the case of split system and

single package heat pumps where the lifetime operating cost contributes more to the overall lifecycle cost, as efficiency increases, the increase in the installed consumer cost tends to negate any

reduction in life-cycle cost realized from lower lifetime operating costs.

It is worth reiterating that the results shown in Figures 5.29 through 5.40 are based upon

average input values and not input distributions. Thus, although observations can be made as to how

the various inputs impact life-cycle cost and, in turn, how the resulting life-cycle costs change with

efficiency, conclusions should only be drawn from the distribution of life-cycle cost results that are

presented later (Section 5.2.4.3).

5.2.4.2 Baseline LCC Distributions

As stated earlier, the Monte Carlo method of analysis relying on Crystal Ball (i.e., random

sampling from distributions) was used to conduct the LCC analysis. The following results presented

here are based on 10,000 samples per Monte Carlo run.

The first step in developing LCC results is to develop the baseline LCC for each of the four

product classes. For this analysis, the baseline LCC is based on average electricity prices (Section

5.2.3.5) from each RECS household or modeled commercial building. The change in LCC for

various efficiency levels (to be presented later) is based on marginal electricity prices (Section

5.2.3.6). 

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0%

1%

2%

3%

4%

5%

6%

$0

$1,000$2,000$3,000$4,000$5,000$6,000$7,000$8,000$9,000

$10,000$11,000$12,000$13,000$14,000$15,000$16,000$17,000$18,000$19,000$20,000$21,000

Life-Cycle Cost

Percent of Buildings

Figure 5.41 Split A/C: Percent of Buildings by Life-Cycle Cost, Baseline

Figures 5.41 through 5.44 show the frequency chart for the baseline LCC for the four product

classes. A frequency chart shows the distribution of LCCs with its corresponding probability of

occurrence. As discussed earlier, the baseline efficiency level is assumed to equal the existing

minimum energy efficiency standards. For split system and single package air conditioners, this

means the baseline efficiency level is set to 10 SEER. For split system and single package heat

pumps, the baseline efficiency levels are set to 10 SEER for the cooling performance and 6.8 HSPF

for the heating performance. Table 5.34 summarizes the baseline distributions depicted in Figures

5.41 through 5.44 by showing the mean, median, minimum, and maximum LCCs.

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0%

1%

2%

3%

4%

5%

6%

$0

$2,000$4,000$6,000$8,000

$10,000$12,000$14,000$16,000$18,000$20,000$22,000$24,000$26,000$28,000$30,000$32,000$34,000$36,000

Life-Cycle Cost

Percent of Buildings

Figure 5.42 Split HP: Percent of Buildings by Life-Cycle Costs, Baseline

0%

1%

2%

3%

4%

5%

6%

$0

$1,000$2,000$3,000$4,000$5,000$6,000$7,000$8,000$9,000

$10,000$11,000$12,000$13,000$14,000$15,000$16,000$17,000$18,000$19,000$20,000$21,000$22,000$23,000$24,000

Life-Cycle Cost

Percent of Buildings

Figure 5.43 Package A/C: Percent of Buildings by Life-Cycle Costs, Baseline

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0%

1%

2%

3%

4%

5%

6%

$0

$2,000$4,000$6,000$8,000

$10,000$12,000$14,000$16,000$18,000$20,000$22,000$24,000$26,000$28,000$30,000$32,000$34,000$36,000$38,000$40,000

Life-Cycle Cost

Percent of Buildings

Figure 5.44 Package HP: Percent of Buidlings by Life-Cycle Costs, Baseline

Table 5.34 Baseline LCC: Mean, Median, Minimum, and Maximum Values

Product Class Minimum Median Mean Maximum

Split A/C $2,026 $4,637 $5,170 $21,508

Split Heat Pump $3,521 $8,464 $9,679 $36,901

Package A/C $2,535 $5,126 $5,629 $24,781

Package Heat Pump $3,282 $9,164 $9,626 $41,377

5.2.4.3 Change in LCC Results

The change in LCC results are presented as differences in the LCC relative to the baseline

central air conditioner or heat pump design. As mentioned previously, the LCC differences are

depicted as a distribution of values. The primary results are presented in two types of charts within

Crystal Ball: 1) a frequency chart showing the distribution of LCC differences with its corresponding

probability of occurrence and 2) a cumulative chart showing the cumulative distribution of LCC

differences along with the corresponding probability of occurrence. In each chart, the mean LCC

difference is provided along with the percent of the population for which the LCC will decrease. 

In the explanation below, the two charts depicting the case for an 11 SEER efficiency level

 EE-RM-STD-98-440 COMMENT 311
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Frequency Chart

Certainty is 45.52% from -Infinity to $0 $

Mean = ($44)

.000

.012

.024

.036

.048

0

120

240

360

480

($600) ($375) ($150) $75 $300

10,000 Trials 239 Outliers

Forecast: LCC Difference

Figure 5.45 Split A/C: Frequency Chart of LCC Differences for 11 SEER Efficiency

Level

are used (Figures 5.45 and 5.46). In either chart (frequency or cumulative), the mean change

(reduction of $44 in the examples here) is shown in a text box next to a vertical line at that value on

the x-axis. The phrase “Certainty is 45.52% from -Infinity to $0” means that 45.52% of households

will have reduced LCC with the increased efficiency level compared to the baseline efficiency level

(i.e., 10 SEER). 

Figure 5.45 is an example of a frequency chart. The y-axes show the number of households

(“Frequency” at right y-axis) and percent of all households (“Probability” at left y-axis). In this

example, 10,000 households were examined (“10,000 trials”) and all the almost all the results are

displayed (“182 outliers”). The x-axis is the difference in LCC between a baseline efficiency level

and a higher efficiency level (in this example, 11 SEER). The x-axis begins with negative values

on the left, which indicate that standards for those households provide savings (reduced LCC).

Reduced LCC occurs when reduced operating expenses more than compensate for increased

purchase expense. In Figure 5.45, going from the baseline efficiency level (10 SEER) to the 11

SEER efficiency level provides buildings with an average LCC reduction of $44, and range from

reductions of $600 (at the left) to increases of $210 (at the right) depending upon the building. (The

minimum and maximum values cannot be read with precision from the graph, but rather, the

program provides them in a statistical summary. It should be noted that in this example, reductions

in LCC extend to $15 but, because they are considered outliers, are not shown.)

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Cumulative Chart

Certainty is 45.52% from -Infinity to $0 $

Mean = ($44)

.000

.250

.500

.750

1.000

0

10000

($600) ($375) ($150) $75 $300

10,000 Trials 239 Outliers

Forecast: LCC Difference

Figure 5.46 Split A/C: Cumulative Chart of LCC Differences for 11 SEER Efficiency

Level

The vertical axis in Figure 5.46 is the cumulative probability (left axis) or frequency (right axis) that

the LCC difference will be less than the value on the horizontal axis. Starting at the left, there is a

0% probability that a household will have a reduction in LCC larger than $600 in absolute value

(excluding outliers). At the right, there is a 100% probability that a household will have either a

decrease in LCC or an increase in LCC of less than $210.

Appendix E contains the frequency and cumulative charts for all the efficiency levels. These

charts provide more complete information than summary statistics, but a summary of the change in

LCC from the baseline by percentile groupings (i.e., of the distribution of results) are provided below

in Tables 5.35 through 5.38 for each of the product classes. The mean and the percent of LCCs that

are reduced for each standard-level are also shown. 

As an example of how to interpret the information in Tables 5.35 through 5.38, the 11 SEER

efficiency level for split system air conditioners based is reviewed. The 11 SEER efficiency level

in Table 5.35 (row 1) shows that the maximum (zero percentile column) change in LCC is savings

of $1,542. (Negative values are net savings.) For 90% of the cases studied (90th percentile), the

change in LCC is a cost of $101 or less. The largest increase in LCC is $210 (100th percentile). The

mean change in LCC is a net savings of $44. The last column shows that 45% of the sample have

reduced LCC (i.e., change in LCC less than or equal to zero). 

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Table 5.35 Summary of LCC Results for Split System Air Conditioners

Change in LCC from Baseline

Shown by Percentiles of the Distribution of Results (values in 1998$)

Percent of

Households

with reduced

LCC

10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Mean

$-267 $-134 $-60 $-15 $15 $39 $59 $78 $101 $210 $-44 45%$-430 $-194 $-75 $2 $54 $98 $141 $178 $222 $450 $-45 40%$-530 $-198 $-26 $90 $170 $236 $294 $347 $414 $774 $29 32%

$-465 $146 $454 $639 $768 $880 $996 $1,129 $1,301 $2,653 $555 17%

Table 5.36 Summary of LCC Results for Split System Heat Pumps

Change in LCC from Baseline

Shown by Percentiles of the Distribution of Results (values in 1998$)

Percent of

Households

with reduced

LCC

10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Mean

$-429 $-271 $-192 $-137 $-89 $-50 $-19 $13 $48 $181 $-150 76%$-748 $-480 $-314 $-213 $-127 $-59 $5 $64 $132 $405 $-242 69%$-943 $-537 $-327 $-177 $-57 $38 $128 $216 $311 $659 $-215 56%

$-1,068 $-324 $87 $358 $563 $719 $877 $1,033 $1,251 $2,452 $276 27%

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Table 5.37 Summary of LCC Results for Single Package Air Conditioners

Change in LCC from Baseline

Shown by Percentiles of the Distribution of Results (values in 1998$)

Percent of

Households

with reduced

LCC

10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Mean

$-206 $-75 $-1 $45 $78 $105 $127 $148 $173 $285 $20 31%

 $-443 $-201 $-64 $20 $80 $129 $171 $209 $250 $415 $-29 37%

$-403 $-64 $123 $244 $327 $393 $450 $504 $573 $899 $175 23%

$-328 $295 $632 $820 $974 $1,095 $1,214 $1,350 $1,536 $2,377 $741 14%

Table 5.38 Summary of LCC Results for Single Package Heat Pumps

Change in LCC from Baseline

Shown by Percentiles of the Distribution of Results (values in 1998$)

Percent of

Households

with reduced

LCC

10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Mean

$-440 $-269 $-178 $-118 $-69 $-30 $6 $40 $84 $244 $-134 68%$-831 $-516 $-344 $-230 $-138 $61 $12 $84 $166 $491 $-254 68%$-921 $-469 $-246 $-78 $45 $152 $252 $359 $486 $1,032 $-112 45%

$-1,164 $-395 $57 $348 $573 $770 $954 $1,155 $1,416 $2,580 $296 28%

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5.2.4.4 LCC Results based on ±2% Threshold

The results in Tables 5.35 through 5.38 show the percent of households with reduced LCC.

But considering that the baseline LCC for each product class is significantly greater than the LCC

differences shown in Tables 5.35 through 5.38, it is more useful to demonstrate which consumers

experience significant net LCC savings or costs due to a higher standard-level. We define significant

as those consumers experiencing net LCC savings or costs which are greater than 2% of the baseline

LCC. For central air conditioners, this translates to an LCC increase of approximately $100 or an

annual expense of approximately $5 over the lifetime of the system. Table 5.39 summarizes the

baseline LCCs for split system and single package central air conditioners and heat pumps and also

provides the 2% threshold at which consumers are considered to be significantly impacted by a

standard-level.

Table 5.39 Baseline Life-Cycle Costs and Threshold for Significant Impacts

Product Class Baseline Life-Cycle Cost

Threshold for Adverse Impacts:

2% of Baseline LCC

Split Air Conditioners $5,170 $103

Split Heat Pumps $9,679 $194

Single Package Air Conditioners $5,629 $113

Single Package Heat Pumps $9,626 $193

Tables 5.40 through 5.43 and Figures 5.47 through 5.54 depict the LCC results for split

system and single package central air conditioners and heat pumps based on the above defined 2%

threshold. The tables show the average LCC values for the baseline level (10 SEER) and the various

standard-levels analyzed. As presented earlier in Tables 5.35 through 5.38, Tables 5.40 through 5.43

also provide for each product class the difference in LCC at each efficiency level relative to the

baseline. The differences represent either an LCC savings or an LCC cost increase. In addition, each

table shows the subset of consumers (both residential and commercial) at each efficiency level who

are impacted in one of three ways: consumers who achieve significant net LCC savings (i.e., LCC

savings greater than 2% of the baseline LCC), consumers who are impacted in an insignificant

manner by having either a small reduction or small increase in LCC (i.e., within ±2% of the baseline

LCC), or consumers who achieve a significant net LCC increase (i.e., an LCC increase exceeding

2% of the baseline LCC). Accompanying each percentage value is the average LCC savings or

increase that corresponds to each subset of consumers. For example, in the case of the 12 SEER

efficiency level for split system air conditioners (Table 5.40), the percentage of consumers with

significant net savings is 27% and the corresponding average LCC savings for those consumers is

$457. 

For each product class, two figures are presented; one showing the mean LCC by efficiency

level and the other showing the percentage of consumers for each efficiency level that fall within the

three consumer subsets (i.e., net savings, no significant impacts, or net costs). For the figure

presenting the percentage of consumers with net savings, no significant impacts, and net costs, the

corresponding average LCC savings or increase is also presented.

 EE-RM-STD-98-440 COMMENT 311
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Average Percent of consumers with

LCC (Savings) 

Costs

Net Savings 

(>2%) 

Avg LCC 

(Save) Cost

No significant 

impact

Avg LCC 

(Save) Cost

Net Costs 

(>2%)

Avg LCC 

(Save) Cost

- - - -

($44) 23% ($304) 68% ($82) 9% $127

($45) 27% ($457) 34% $17 39% $188

$29 25% ($602) 17% $11 58% $313

$555 15% ($1,072) 4% $6 81% $880

Table 5.40 LCC Results for Split System Central Air Conditioners

$5,126 $5,125 $5,199

$5,725

11 12 13 18

Efficiency (SEER)

Cs for Split System Central Air Conditioners

15%

($1072)

25%

($602)

27%

($457)

23%

($304)

4% $6

17%

$11

34%

$17

68%

($82)

81%$880

39%$188

9% $127

58%$313

0%

10%20%30%40%50%60%70%80%90%

100%

11 12 13 18

Efficiency (SEER)

Percent of consumers Net Costs (>2%) No significant impact Net Savings (>2%) 

Figure 5.48 Percent of Split System Central A/C Consumers with Net

Costs, No Significant Impacts, and Net Savings

 EE-RM-STD-98-440 COMMENT 311
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Average Percent of consumers with

LCC (Savings) 

Costs

Net Savings 

(>2%) 

Avg LCC 

(Save) Cost

No significant 

impact

Avg LCC 

(Save) Cost

Net Costs 

(>2%)

Avg LCC 

(Save) Cost

- - - -

($150) 30% ($44) 70% ($40) 0% $0

($242) 42% ($592) 55% ($2) 3% $234($215) 39% ($748) 39% $15 22% $312

$276 23% ($1,280) 11% $20 66% $850

Table 5.41 LCC Results for Split System Heat Pumps

$9,529 $9,437 $9,464 $9,955

11 12 13 18

Efficiency (SEER)

Cs for Split System Heat Pumps

23%

($1280)

39%

($748)

42%

30% ($592)

($44)

11% $20

39%

$15

55%

($2) 70%($40) 66%$850

22%$312

0% 3% $234

0%

10%20%30%40%50%60%70%80%90%

100%

11 12 13 18

Efficiency (SEER)

Percent of consumers Net Costs (>2%) No significant impact Net Savings (>2%) 

Figure 5.50 Percent of Split System Heat Pump Consumers with Net

Costs, No Significant Impacts, and Net Savings

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Average Percent of consumers with

LCC (Savings) 

Costs

Net Savings 

(>2%) 

Avg LCC 

(Save) Cost

No significant 

impact

Avg LCC 

(Save) Cost

Net Costs 

(>2%)

Avg LCC 

(Save) Cost

- - - -

$20 16% ($318) 47% $31 37% $157

($29) 26% ($482) 30% $18 44% $206

$175 18% ($660) 11% $10 71% $413$741 12% ($1,147) 4% $10 84% $1,052

Table 5.42 LCC Results for Single Package Central Air Conditioners

$5,649 $5,600 $5,804

$6,370

11 12 13 18

Efficiency (SEER)

Cs for Single Package Central Air

s

12% ($1147)

18%

($660)

26%

16% ($482) ($318)

4% $10

11% $10

30%

$18

47%

$31

84%

$1052

71%$413

44%$206

37%$157

0%

10%20%30%40%50%60%70%80%90%

100%

11 12 13 18

Efficiency (SEER)

Percent of consumers Net Costs (>2%) No significant impact Net Savings (>2%) 

Figure 5.52 Percent of Single Package Central A/C Consumers with

Net Costs, No Significant Impacts, and Net Savings

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Average Percent of consumers with

LCC (Savings) 

Costs

Net Savings 

(>2%) 

Avg LCC 

(Save) Cost

No significant 

impact

Avg LCC 

(Save) Cost

Net Costs 

(>2%)

Avg LCC 

(Save) Cost

- - - -

($134) 28% ($431) 72% ($19) 0% $213($254) 44% ($623) 49% ($1) 7% $256($112) 33% ($810) 31% $19 36% $407

$296 24% ($1,342) 10% $15 66% $936

Table 5.43 LCC Results for Single Package Heat Pumps

$9,492 $9,372 $9,514 $9,922

11 12 13 18

Efficiency (SEER)

Cs for Single Package Heat Pumps

0%

24%

($1342)

33%

($810)

44%

28% ($623)

($431)

10% $15

31%

$19

49%

($1) 72%($19) 66%$936

36%$407

7% $256

0%

10%20%30%40%50%60%70%80%90%

100%

11 12 13 18

Efficiency (SEER)

Percent of consumers Net Costs (>2%) No significant impact Net Savings (>2%) 

Figure 5.54 Percent of Single Package Heat Pump Consumers with Net

Costs, No Significant Impacts, and Net Savings

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5.2.4.5 LCC Scenarios

Two of the key assumptions for the LCC analysis pertain to the manufacturer costs and the

system lifetime. Two scenarios are investigated where lower estimates of the manufacturer costs and

system lifetime are analyzed.

Manufacturer Cost Scenario

An LCC scenario in which manufacturer cost estimates based on the reverse engineering

analysis (Chapter 4) are substituted for the estimates provided by ARI. Table 5.44 compares the ARI

shipment-weighted mean and reverse engineering mean manufacturer cost multipliers. 

Table 5.44 ARI Shipment-Weighted Mean and Revised Reverse Engineering Mean

Manufacturer Cost Multipliers

Product Class

Efficiency Level Split A/C Split Heat Pump Package A/C Package Heat Pump

SEER ARI Rev Eng ARI Rev Eng ARI Rev Eng ARI Rev Eng

11 1.16 1.12 1.10 1.05 1.19 1.09 1.14 1.08

12 1.36 1.28 1.24 1.13 1.30 1.16 1.28 1.13

13 1.63 1.44 1.44 1.30 1.63 1.43 1.60 1.38

18a 2.40 1.99 2.09 1.94 2.23 1.87 2.13 1.86

a

 Cost Multipliers for 18 SEER based on data for 15 SEER.

Tables 5.45 through 5.48 and Figures 5.55 through 5.62 show the LCC results for each of the

product classes under the scenario of replacing the ARI manufacturer cost estimates with those from

the reverse engineering analysis. The following results are presented in the same manner as the

previous LCC results where average LCC savings or costs and the percentage of consumers with net

savings, insignificant impacts, and net costs are presented for each efficiency level. Note that since

manufacturer cost multipliers were not available for the 18 SEER efficiency levels, 15 SEER cost

multipliers were used for all 18 SEER calculations resulting in 18 SEER LCC results which

underestimate their true cost level.

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Average Percent of consumers with

LCC (Savings) 

Costs

Net Savings 

(>2%) 

Avg LCC 

(Save) Cost

No significant 

impact

Avg LCC 

(Save) Cost

Net Costs 

(>2%)

Avg LCC 

(Save) Cost

- - - -

($75) 28% ($305) 70% ($10) 2% $118

($113) 35% ($453) 40% $18 25% $158($113) 34% ($589) 27% $11 39% $217

$137 25% ($1,045) 7% $5 68% $584

LCC Results for Split System A/C – LCC Scenario with Reverse Engineering Manufacturer Costs

$5,095 $5,057 $5,057 $5,307

11 12 13 18

Efficiency (SEER)

Cs for Split A/C – LCC Scenario with Rev Eng

er Costs

25%

($1045)

34%

($589)

35%

($453) 28% ($305)

7% $5

27%

$11

40%

$18

70%

($10)

68%$584

39%$217

25%$158

2% $118

0%

10%20%30%40%50%60%70%80%90%

100%

11 12 13 18

Efficiency (SEER)

Percent of consumers Net Costs (>2%) No significant impact Net Savings (>2%) 

Figure 5.56 Percent of Split A/C Consumers with Net Costs, No

Significant Impacts, and Net Savings – LCC Scenario withRev Eng Manufacturer Costs

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Average Percent of consumers with

LCC (Savings) 

Costs

Net Savings 

(>2%) 

Avg LCC 

(Save) Cost

No significant 

impact

Avg LCC 

(Save) Cost

Net Costs 

(>2%)

Avg LCC 

(Save) Cost

- - - -

($209) 40% ($409) 60% ($77) 0% $0($365) 58% ($591) 42% ($58) 0% $216

($372) 52% ($742) 42% ($2) 6% $259

$41 28% ($1,295) 15% $11 57% $712

CC Results Split System Heat Pump – LCC Scenario with Reverse Engineering Manufacturer Costs

$9,470 $9,314 $9,307 $9,720

11 12 13 18

Efficiency (SEER)

Cs for Split HP – LCC Scenario with Rev Eng

er Costs

0% 0%

28%

($1295)

52%

($742)

58%

($591) 40%

($409)

15%

$11

42%

($2)

42%

($58) 60%

($77)

57%$712

6% $259

0%

10%20%30%40%50%60%70%80%90%

100%

11 12 13 18

Efficiency (SEER)

Percent of consumers Net Costs (>2%) No significant impact Net Savings (>2%) 

Figure 5.58 Percent of Split HP Consumers with Net Costs, No

Significant Impacts, and Net Savings – LCC Scenario withRev Eng Manufacturer Costs

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Average Percent of consumers with

LCC (Savings) 

Costs

Net Savings 

(>2%) 

Avg LCC 

(Save) Cost

No significant 

impact

Avg LCC 

(Save) Cost

Net Costs 

(>2%)

Avg LCC 

(Save) Cost

- - - -

($78) 27% ($313) 72% $9 1% $120

($163) 40% ($460) 51% $13 9% $140

($29) 28% ($632) 20% $16 52% $275

$276 21% ($1,101) 6% $8 73% $690

CC Results for Single Package A/C – LCC Scenario with Reverse Engineering Manufacturer Costs

$5,551 $5,466 $5,600 $5,905

11 12 13 18

Efficiency (SEER)

Cs for Single Pakcage A/C – LCC Scenario

g Manufacturer Costs

21%

($1101)

28%

($632)

40%

27% ($460)

($313)

6% $8

20%

$16

51%

$13

72%

$9

73%$690

52%$275

9%

$140

1% $120

0%

10%20%30%40%50%60%70%80%90%

100%

11 12 13 18

Efficiency (SEER)

Percent of consumers Net Costs (>2%) No significant impact Net Savings (>2%) 

Figure 5.60 Percent of Single Package A/C Consumers with Net Costs,

No Significant Impacts, and Net Savings – LCC Scenariowith Rev Eng Manufacturer Costs

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Average Percent of consumers with

LCC (Savings) 

Costs

Net Savings 

(>2%) 

Avg LCC 

(Save) Cost

No significant 

impact

Avg LCC 

(Save) Cost

Net Costs 

(>2%)

Avg LCC 

(Save) Cost

- - - -

($207) 39% ($426) 61% ($65) 0% $0($421) 66% ($606) 34% ($62) 0% $214

($353) 50% ($775) 38% ($1) 12% $299($166) 37% ($1,344) 15% $13 48% $683

CC Results for Single Package HP – LCC Scenario with Reverse Engineering Manufacturer Costs

$9,419 $9,205 $9,273 $9,460

11 12 13 18

Efficiency (SEER)

Cs for Single Package HP – LCC Scenario

g Manufacturer Costs

0% 0%

37%

($1344)

50%

($775)

66%

($606)

39%

($426)

15%

$13

38%

($1)

34%

($62)

61%

($65)

48%$683

12%$299

0%

10%20%30%40%50%60%70%80%90%

100%

11 12 13 18

Efficiency (SEER)

Percent of consumers Net Costs (>2%) No significant impact Net Savings (>2%) 

Figure 5.62 Percent of Single Package HP Consumers with Net Costs, No

Significant Impacts, and Net Savings – LCC Scenario withRev Eng Manufacturer Costs

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Lifetime Scenario

A lifetime scenario is considered based on a retirement function yielding an average lifetime

of 14 years in which no compressor replacement occurs. The shorter lifetime is based on the

assumption that most, if not all, consumers when faced with replacing a failed compressor would

choose to replace the entire system rather than replace the compressor in a relatively old system.

Tables 5.49 through 5.52 and Figures 5.63 through 5.70 show the LCC results for each of the

product classes under the 14 year lifetime, no compressor replacement scenario. The following

results are presented in the same manner as the previous LCC results where average LCC savings

or costs and the percentage of consumers with net savings, insignificant impacts, and net costs are

presented for each efficiency level. 

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Average Percent of consumers with

LCC (Savings) 

Costs

Net Savings 

(>2%) 

Avg LCC 

(Save) Cost

No significant 

impact

Avg LCC 

(Save) Cost

Net Costs 

(>2%)

Avg LCC 

(Save) Cost

- - - -

($32) 22% ($252) 69% $20 9% $113

($10) 24% ($392) 31% $16 45% $178

$87 21% ($498) 15% $14 64% $296

$654 12% ($928) 3% $11 85% $893

le 5.49 LCC Results for Split System A/C – LCC Scenario with 14 year average Lifetime

$4,650 $4,672 $4,769

$5,336

11 12 13 18

Efficiency (SEER)

Cs for Split A/C – LCC Scenario with 14 year

time

12% ($928)

21%

($498)

24%

($392)

22%

($252)

3% $11

15%

$14

31%

$16

69%

$20

85%$893

64%$296

45%$178

9%

$113

0%

10%20%30%40%50%60%70%80%90%

100%

11 12 13 18

Efficiency (SEER)

Percent of consumers Net Costs (>2%) No significant impact Net Savings (>2%) 

Figure 5.64 Percent of Split A/C Consumers with Net Costs, No

Significant Impact, and Net Savings – LCC Scenario with 14year average Lifetime

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Average Percent of consumers with

LCC (Savings) 

Costs

Net Savings 

(>2%) 

Avg LCC 

(Save) Cost

No significant 

impact

Avg LCC 

(Save) Cost

Net Costs 

(>2%)

Avg LCC 

(Save) Cost

- - - -

($124) 27% ($362) 73% ($33) 0% $0($160) 35% ($505) 58% $9 7% $214

($117) 33% ($645) 37% $16 30% $300

$437 18% ($1,079) 9% $11 73% $862

50 LCC Results for Split System Heat Pump – LCC Scenario with 14 year avearge Lifetime

$8,623 $8,587 $8,630 $9,184

11 12 13 18

Efficiency (SEER)

Cs for Split HP – LCC Scenario with 14 year

time

0%

18%

($1079)

33%

($645)

35%

($505) 27% ($362)

9% $11

37%

$16

58%

$9

73%

($33)

73%$862

30%$300

7% $214

0%

10%20%30%40%50%60%70%80%90%

100%

11 12 13 18

Efficiency (SEER)

Percent of consumers Net Costs (>2%) No significant impact Net Savings (>2%) 

Figure 5.66 Percent of Split HP Consumers with Net Costs, No

Significant Impacts, and Net Savings – LCC Scenario with 14year average Lifetime

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Average Percent of consumers with

LCC (Savings) 

Costs

Net Savings 

(>2%) 

Avg LCC 

(Save) Cost

No significant 

impact

Avg LCC 

(Save) Cost

Net Costs 

(>2%)

Avg LCC 

(Save) Cost

- - - -

$32 14% ($286) 46% $31 40% $144

$7 22% ($428) 29% $18 49% $199

$228 14% ($564) 10% $12 76% $406

$861 9% ($953) 3% ($4) 88% $1,082

e 5.51 LCC Results for Single Package A/C – LCC Scenario with 14 year average Lifetime

$5,182 $5,157 $5,378

$6,011

11 12 13 18

Efficiency (SEER)

Cs for Single Package A/C – LCC Scenario

 average Lifetime

9% ($953)

14%

($564)

22%

($428)

14%

($286)

3% ($4)

10% $12

29%

$18

46%

$31

88%

$1082

76%$406

49%$199

40%$144

0%

10%20%30%40%50%60%70%80%90%

100%

11 12 13 18

Efficiency (SEER)

Percent of consumers Net Costs (>2%) No significant impact Net Savings (>2%) 

Figure 5.68 Percent of Single Package A/C Consumers with Net Costs,

No Significant Impact, and Net Savings – LCC Scenario with14 year average Lifetime

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Average Percent of consumers with

LCC (Savings) 

Costs

Net Savings 

(>2%) 

Avg LCC 

(Save) Cost

No significant 

impact

Avg LCC 

(Save) Cost

Net Costs 

(>2%)

Avg LCC 

(Save) Cost

- - - -

($98) 25% ($369) 75% ($11) 0% $185

($167) 37% ($533) 51% $8 12% $236

$12 26% ($687) 27% $18 47% $399

$484 18% ($1,146) 8% $14 74% $933

52 LCC Results for Single Package Heat Pump – LCC Scenario with 14 year aveage Lifetime

$8,597 $8,528 $8,707

$9,179

11 12 13 18

Efficiency (SEER)

Cs for Single Package HP – LCC Scenario

 average Lifetime

0%

18%

($1146)

26%

($687)

37%

25% ($533)

($369)

8% $14

27%

$18

51%

$8

75%

($11)

74%$933

47%$399

12%$236

0%

10%20%30%40%50%60%70%80%90%

100%

11 12 13 18

Efficiency (SEER)

Average Life-Cycle Cost Net Costs (>2%) No significant impact Net Savings (>2%) 

Figure 5.70 Percent of Single Package HP Consumers with Net Costs, No

Significant Impacts, and Net Savings – LCC Scenario with 14year average Lifetime

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PAY

P

O = ∆∆ (5.24)

5.3 DISTRIBUTION PAYBACK PERIOD

5.3.1 Metric

The payback period (PBP) measures the amount of time it takes the consumer to recover the

assumed higher purchase expense of more energy-efficient equipment through lower operating costs.

Numerically, the PBP is the ratio of the increase in purchase expense (i.e., from a less efficient

design to a more efficient design) to the decrease in annual operating expenditures. This type of

calculation is known as a “simple” payback period, because is does not take into account changes

in operating expense over time or the time value of money, that is, the calculation is done at an

effective discount rate of 0%. 

 PBP is found by solving the equation:

for PAY, where FP = difference in purchase expense between the more efficient and the less efficient

design options, and FO = difference in annual operating expenses. PBPs are expressed in years.

PBPs greater than the life of the product mean that the increased purchase expense is not recovered

in reduced operating expenses.

5.3.2 Inputs

The data inputs to PBP are the purchase expense (otherwise known as the total installed

consumer cost) for each design option and the annual (first year) operating expenditures for each

design option. The inputs to the purchase expense are the equipment price and the installation price.

The inputs to the operating costs are the annual energy savings, the energy price, the annual repair

cost savings, and the annual maintenance cost savings. The Distribution PBP uses the same inputs

as the LCC analysis described in section 5.2 except for a few exceptions described below. 

Since this is a “simple” payback the electricity rate used is only for the year the standard takes

effect, assumed here to be the year 2006. The price of electricity is that projected for that year.

Discount rates are not used for the payback calculation.

5.3.3 Payback Period Results

Figure 5.71 is an example of a chart showing the distribution of payback periods for the 11

SEER efficiency level for split system air conditioners. The chart is the result of 10,000 Monte Carlo

runs or in other words, 10,000 samples from each of the distribution inputs.

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Frequency Chart

Certainty is 99.33% from -Infinity to 100.0

.000

.020

.039

.059

.079

0

196.2

392.5

588.7

785

0.0 25.0 50.0 75.0 100.0

10,000 Trials 67 Outliers

Forecast: Payback (years)

Figure 5.71 Frequency Chart of Payback Periods for 11 SEER Efficiency Level for Split

Air Conditioners

Tables 5.53 through 5.56 summarize the payback period results for each of the four primary

product classes. Results are summarized for the payback period by percentile groupings (i.e.,

percentile of the distribution of results). The mean payback period for each standard-level are also

shown. 

Figures 5.72 through 5.75 graphically display the payback period results. The first figure for

each product class shows the median (50th percentile) payback periods while the second figure shows

the mean payback periods. In must be noted that in the figures, payback periods exceeding 35 years

are represented graphically as a 35 year payback.

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0

5

10

15

20

25

30

35

10 11 12 13 14 15 16 17 18

SEER

Payback Period (years)

Median

Mean

Figure 5.72 Split A/C: Median and Mean Payback Periods

Table 5.53 Summary of Payback Period Results for Split Air Conditioners

Efficiency Level

(SEER)

Payback Period in Years

Shown by Percentiles of the Distribution of Results

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Mean

11 1 4 5 7 9 11 13 16 21 31 681 16

12 1 5 6 8 10 13 15 19 26 39 622 19

13 1 6 8 10 13 16 20 24 33 50 >1000 24

18 2 8 12 18 25 36 55 106 1000 1000 >1000 451

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0

5

10

15

20

25

30

35

10 11 12 13 14 15 16 17 18

SEER

Payback Period (years)

Median

Mean

Figure 5.73 Split HP: Median and Mean Payback Periods

Table 5.54 Summary of Payback Period Results for Split Heat Pumps

Efficiency Level

(SEER / HSPF)

Payback Period in Years

Shown by Percentiles of the Distribution of Results

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Mean

11 / 7.1 1 2 3 4 5 6 7 8 10 13 >1000 9

12 / 7.4 1 3 4 5 6 7 8 10 12 17 1000 10

13 / 7.7 1 4 6 7 8 9 11 13 16 22 1000 13

18 / 8.8 2 6 9 11 14 17 22 29 44 102 >1000 135

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0

5

10

15

20

25

30

35

10 11 12 13 14 15 16 17 18

SEER

Payback Period (years)

Median

Mean

Figure 5.74 Package A/C: Median and Mean Payback Periods

Table 5.55 Summary of Payback Period Results for Single Package Air Conditioners

Efficiency 

Level

(SEER)

Payback Period in Years

Shown by Percentiles of the Distribution of Results

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Mean

11 1 5 8 10 13 16 20 25 34 52 596 24

12 1 5 7 9 11 14 17 22 30 45 927 22

13 2 7 10 14 18 22 26 33 46 69 >1000 33

18 2 9 14 21 32 49 84 237 1000 1000 >1000 378

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0

5

10

15

20

25

30

35

10 11 12 13 14 15 16 17 18

SEER

Payback Period (years)

Median

Mean

Figure 5.75 Package HP: Median and Mean Payback Periods

Table 5.56 Summary of Payback Period Results for Single Package Heat Pumps

Efficiency Level

(SEER / HSPF)

Payback Period in Years

Shown by Percentiles of the Distribution of Results

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Mean

11 / 7.1 1 4 5 6 7 8 9 11 14 19 1000 11

12 / 7.4 1 4 5 6 7 9 10 12 15 21 1000 13

13 / 7.7 2 6 8 10 11 13 16 18 23 32 >1000 19

18 / 8.8 2 7 10 12 16 19 25 34 53 160 >1000 114

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UEC

CAP

SEER

Hours cool b PBP

cool

Re = ⋅ (5.25)

UEC

DHR

HSPF

Hours heat b PBP Re = ⋅⋅ 0 77 . (5.26)

5.4 REBUTTABLE PAYBACK PERIOD

Rebuttable PBP’s are presented in order to provide the legally established rebuttable

presumption that a energy efficiency standard is economically justified if the additional product costs

attributed to the standard are less than three times the value of the first year energy cost savings (42

U.S.C. §6295 (o)(2)(B)(iii)).

5.4.1 Metric

The basic equation for Rebuttable PBP is the same as that shown in section 5.3 (Eqn. 5.24).

Unlike the analyses in sections 5.2 and section 5.3, the Rebuttable PBP is not based on distributions

and does not utilize the Crystal Ball option in the spreadsheet model. Rather than using

distributions, the Rebuttable PBP is based on discrete single-pont values. For example, where a

probability distribution of electricity prices are used in the distributional Payback Analysis, only the

weighted-average value from the probability distribution of electricity prices is used for the

determination of the Rebuttable PBP.

Other than the use of single point-values, the most notable difference between the

Distribution PBP and the Rebuttable PBP is the latter’s reliance on the DOE test procedure to

determine a central air conditioner’s or heat pump’s annual energy consumption41. In the case of

central air conditioners and the cooling seasonal performance of heat pumps, the DOE test procedure

uses the following expression to calculate the annual space-cooling energy consumption:

Where,

UECcool Reb PBP = annual space-cooling energy use based on the DOE test procedure,

CAPcool = the cooling capacity of the equipment at 95°F, and

SEER = the SEER of the equipment, and

Hours = 1000, the assumed annual operational hours.

For the heating seasonal performance of heat pumps, the DOE test procedure uses the following

expression to calculate the annual space-heating energy consumption:

Where,

UECheat Reb PBP = annual space-heating energy use based on the DOE test procedure,

DHR = the design heat requirement (which for 3-ton cooling capacity heat pumps

is typically 35,000 Btu/hr),

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5-110

HSPF = the HSPF of the equipment, and

Hours = 2080, the assumed annual operational hours.

As will be shown later (Section 5.4.3), based on the use of the DOE test procedure equations,

the calculated annual space-cooling and heating energy consumption are on the order of 50% greater

than the weighted-average values from the 1997 RECS. This means that for any standard-level

being analyzed, the Rebuttable PBP value will be significantly lower than the average payback value

from the distributional analysis.

5.4.2 Inputs

Inputs differ from the Distribution PBP in that discrete values are used rather than

distributions for inputs. The following describe the single point-values which were used in the

determination of the Rebuttable PBP. All dollar values are in 1998$.

• Manufacturer costs are based on mean values as presented in Table 5.3 for the ARI

cost data.

• All markups and sales taxes are based on mean values.

• Installation prices are based on mean values for split and single package air

conditioners and for split and single package heat pumps.

• Annual energy consumption is based on the DOE test procedure as presented in

Eqns. 5.25 and 5.26. In determining the annual space-cooling energy use, the

assumed cooling capacity is 3-tons (36,000 Btu/hr). In determining the annual spaceheating energy use for heat pumps, the assumed design heating requirement is 35,000

Btu/hr.

• Electricity rates for both average and marginal prices are based on weighted-average

values for the year the standard takes effect, i.e., AEO projections for the year 2006.

• An average discount rate or lifetime is not required in this calculation.

• Effective data of standard is assumed to be 2006. 

5.4.3 Rebuttable Payback Period Results

Rebuttable payback periods are calculated between the new standard-level being analyzed

and each central air conditioner or heat pump efficiency being sold in the year 2006. Based on the

most recently available shipments data from ARI (from 1994), Table 5.57 depicts the markets shares

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5-111

by efficiency level for each of the four product classes. 

Table 5.57 Efficiency Level Market Shares for 1994

SEER Split A/C Split HP Single Package A/C Single Package HP

10 78.7% 59.3% 82.3% 64.2%

11 5.4% 15.0% 9.7% 13.6%

12 12.0% 19.7% 6.8% 22.2%

13 3.6% 4.5% 1.2% 0.0%

14 0.1% 1.0% 0.0% 0.0%

15 0.2% 0.5% 0.0% 0.0%

Because the shipment weighted efficiencies of unitary air conditioners and heat pumps have

remained essentially flat over the four year period from 1994 to 1997, the above market shares in

Table 5.57 for 1994 are assumed to be representative of those in the year new standards are assumed

to become effective (2006).

After the payback periods are determined against each efficiency level sold in the year 2006,

they are weighted and averaged according to the percentage of each equipment efficiency sold

before a new standard is enacted. As described earlier, rather than being based on probability

distributions, single point-values are used for the input variables. Annual energy use values are

defined by inputs (e.g., operating hours) and expressions found in the DOE test procedure. The

result is a single-value of payback and not a probability distribution. The payback is calculated for

the expected effective year of the standard (e.g., 2006). 

Tables 5.58 through 5.61 show the Rebuttable PBPs for the four primary product classes.

Two tables are presented for each product class; one based on the ARI manufacturer cost data and

other based on the reverse engineering cost data. In each table the primary inputs used in the

determination of Rebuttable PBP are presented. Of special note are the two columns of data that

show the weighted-average installed consumer cost and weighted-average annual operating expense.

For each standard-level, the weighted-average consumer cost and weighted-average operating

expense are the baseline values which the standard-level is referenced against. Both of these values

are based upon the normalized percentage of each equipment efficiency sold that precedes the

particular efficiency level of interest. This approach of calculating Rebuttable PBP is equivalent to

weighting and averaging the payback against each efficiency level. 

To illustrate the weighted-average concept of calculating Rebuttable PBP, the weightedaverage installed cost and operating expense values are calculated here for the 12 SEER efficiency

level for split system air conditioners (Table 5.58). For the 12 SEER efficiency level, the weightedaverage installed consumer cost is calculated with the following expression:

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5-112

( ) ( ) IC12SEER wt avg

78 7%

78 7% 54%

54%

78 7% 54% = ⋅ +

 + ⋅ +





  $2236 = . . . $2357 . . . $2243

( ) ( ) OC12 SEER wt avg

78 7%

78 7% 54%

54%

78 7% 54% = ⋅ +

 + ⋅ +





  $357 = . . . $331 . . . $355

( )

( ) PBP years Rebutt

$2510 $2236

$355 $310 = . −

− = 58

The weighted-average operating expense is calculated with the following expression:

Finally, the Rebuttable PBP is calculated as follows:

Table 5.58 Summary of Rebuttable PBPs and Inputs for Split System Air Conditioners

Weighted-Avg of Units

Sold below Effc’y

Installed Annual Annual Annual Annual Assumed Installed Annual Rebutt.

Effc’y Consumer Energy Repair Maint. Operating 2006 Consumer Operating Payback

Level Cost Use Cost Cost Expense Effc’y Cost Expense Period

SEER 1998$ kWh/yr 1998$ 1998$ 1998$ Distr. 1998$ 1998$ years

10 $2,236 3,600 $26 $36 $357 78.7% - - -

11 $2,357 3,273 $26 $36 $331 5.4% $2,236 $357 4.7

12 $2,510 3,000 $27 $36 $310 12.0% $2,243 $355 5.8

13 $2,715 2,769 $27 $36 $292 3.6% $2,277 $350 7.6

18 $3,302 2,000 $55 $36 $259 0.2% $2,294 $347 11.3

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5-113

Table 5.59 Summary of Rebuttable PBPs and Inputs for Split System Heat Pumps

Weighted-Avg of

Units Sold below

Effc’y

Installed Annual Annual Annual Annual Assumed Installed Annual Rebutt.

Effc’y Consumer Energy Repair Maint. Operating 2006 Consumer Operating Payback

Level Cost Use Cost Cost Expense Effc’y Cost Expense Period

SEER/HSPF 1998$ kWh/yr 1998$ 1998$ 1998$ Distr. 1998$ 1998$ years

10 /6.8 $3,668 11,844 $38 $36 $894 59.3% - - -

11 / 7.1 $3,779 11,168 $38 $36 $850 15.0% $3,668 $894 2.5

12 / 7.4 $3,933 10,575 $38 $36 $812 19.7% $3,691 $885 3.3

13 / 7.7 $4,155 10,049 $39 $36 $778 4.5% $3,741 $870 4.5

18 / 8.8 $4,873 8,370 $70 $36 $701 0.5% $3,772 $864 6.8

Table 5.60 Summary of Rebuttable PBPs and Inputs for Single Package Air Conditioners 

Weighted-Avg of Units

Sold below Effc’y

Installed Annual Annual Annual Annual Assumed Installed Annual Rebutt.

Effc’y Consumer Energy Repair Maint. Operating 2006 Consumer Operating Payback

Level Cost Use Cost Cost Expense Effc’y Cost Expense Period

SEER 1998$ kWh/yr 1998$ 1998$ 1998$ Distr. 1998$ 1998$ years

10 $2,607 3,600 $34 $36 $365 82.3% - - -

11 $2,795 3,273 $34 $36 $339 9.7% $2,607 $365 7.3

12 $2,903 3,000 $34 $36 $318 6.8% $2,627 $362 6.2

13 $3,229 2,769 $35 $36 $300 1.2% $2,646 $359 9.8

18 $3,822 2,000 $67 $36 $270 0.0% $2,653 $358 13.3

Table 5.61 Summary of Rebuttable PBPs and Inputs for Single Package Heat Pumps

Weighted-Avg of

Units Sold below

Effc’y

Installed Annual Annual Annual Annual Assumed Installed Annual Rebutt.

Effc’y Consumer Energy Repair Maint. Operating 2006 Consumer Operating Payback

Level Cost Use Cost Cost Expense Effc’y Cost Expense Period

SEER/HSPF 1998$ kWh/yr 1998$ 1998$ 1998$ Distr. 1998$ 1998$ years

10 / 6.8 $3,599 11,844 $39 $36 $895 64.2% - - -

11 / 7.1 $3,759 11,168 $39 $36 $852 13.6% $3,599 $895 3.7

12 / 7.4 $3,920 10,575 $40 $36 $814 22.2% $3,627 $888 4.0

13 / 7.7 $4,286 10,049 $40 $36 $780 0.0% $3,692 $871 6.5

18 / 8.8 $4,893 8,370 $74 $36 $705 0.0% $3,692 $871 7.2

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5.5 USER INSTRUCTIONS FOR SPREADSHEETS

It is possible to examine and reproduce the detailed results obtained in this part of the

analysis using a Microsoft Excel spreadsheet available on the U.S. Department of Energy Office of

Codes and Standards website at: http://www.eren.doe.gov/buildings/codes_standards/. 

There are currently two LCC spreadsheets; one for central air conditioners (lcc_cac.xls) and

another for heat pumps (lcc_hp.xls). Each spreadsheet allows the user to perform LCC analyses of

either split or single package systems. To execute the spreadsheets fully requires both Mircosoft

Excel and Crystal Ball software. Both applications are commercially available. Crystal ball is

available at http://www.decisioneering.com.

The spreadsheets posted on the DOE website represent the latest versions of the applicable

models, and have been tested with Excel 2000 and earlier versions of Excel. Each LCC spreadsheet

or workbook consists of the following worksheets:

Instructions contains the instructions for using the spreadsheet.

LCC (Sample Calc) contains the input selections and a summary table of energy use,

operating costs, LCC and Payback.

 

LCC (Simulations) contains the input selections as in the LCC (Sample Calc) sheet. If

Crystal Ball is running, the energy, cost, LCC, and payback data are

from the current sample. If Crystal Ball has finished running, the

data are from the final sample.

Engineering contains the manufacturer costs submitted by ARI for split systems

and single package systems at each efficiency level. Also included

are the manufacturer, distributor, and dealer markups, the sales tax,

the installation price, and the repair and maintenance costs.

RECS HH Data for each sample household from the 1997 RECS, contains average

and marginal electricity prices, annual space-cooling energy

consumption (and space-heating energy consumption for heat

pumps), the station (i.e., geographic) location, the year the

household was built, and the equipment’s age index.

COMM Data for each sample building, for each sample building, contains

average and marginal electricity prices, and annual space-cooling

energy consumption (and space-heating energy consumption for

heat pumps).

Energy Price contains projections of future energy prices from various sources.

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SEER Dist contains historical shipment weighted efficiency data by year; this

is used for determining the probable SEER of existing spaceconditioning equipment based on age.

HSPF Dist contains historical shipment weighted efficiency data by year; this

is used for determining the probable HSPF of existing heat pump

based on age. (This worksheet is included only in the LCC

spreadsheet for heat pumps (lcc_hp.xls)).

Seasonal Allocation Factors contains seasonal (i.e., summer and non-summer) allocation factors

of annual cooling (or heating) energy which indicate the fraction

used by season. The seasonal allocation factors are based on the

age and the geographic location of the household. The factors are

used for determining the annual marginal electricity rate. Summer

and non-summer allocation factors are multiplied by summer and

non-summer marginal rates, respectively, and then summed to

arrive at the annual marginal rate.

drate dist contains data from which an average discount rate and a distribution

of discount rates are determined.

Lifetime contains the survival function for central air conditioners and heat

pumps and the average central air conditioner and heat pump

lifetime in years.

Setup this is used as an interface between user inputs and the rest of the

worksheets -- do not modify this sheet.

The following provides basic instructions for operating the LCC spreadsheets:

1. Once the LCC spreadsheets have been downloaded from the website, open either file

using Microsoft Excel. At the bottom, click on the tab for either the worksheet LCC

(Sample Calc) or LCC (Simulations). 

2. Use Microsoft Excel’s commands at the top View/Zoom to change the size of the

display to make it fit your monitor.

3. The user interacts with the spreadsheet by clicking choices or entering data using the

graphical interface that comes with the spreadsheet. Choices can be selected from

the box labeled List Inputs on either of the two worksheets LCC (Sample Calc) or

LCC (Simulations). A change in either worksheet also changes the other. In the

box titled List Inputs select choices from the selection boxes for (1) energy price

 EE-RM-STD-98-440 COMMENT 311
b

 Because of the nature of the program, there is some variation in results due to random sampling when Monte

Carlo or Latin Hypercube sampling is used.

5-116

projection, (2) start year, (3) base case design, and (4) standard case design. Also

included are options for selecting different markups and manufacturer cost

multipliers. Outside the upper right hand corner of the List Inputs box is an option

for selecting the system type (split or single package). A new discount rate or

lifetime can also be entered if a value other than the default value or default

distribution is wanted, however, this would change the code and we do not

recommend saving the spreadsheet after the code is changed.

4. To change assumptions on List Inputs click on the assumption you wish to change,

and click on the new assumption from the menu. 

5. This spreadsheet gives the user two methods of running the spreadsheet. 

a. If the LCC (Sample Calc) sheet is chosen, then all calculations are

performed for single input values, usually an average. The new results are

shown on the same sheet as soon as the new values are entered.

b. Alternately, if the LCC (Simulations) sheet is used, the spreadsheet

generates results that are distributions. Some of the inputs are also

distributions. The results from the LCC distribution are shown as single

values and refer only to the results from the last Monte Carlo sample and are

therefore not meaningful. To run the distribution version of the spreadsheet

the Microsoft Excel add-in software called Crystal Ball must be enabled.

To produce sensitivity results using Crystal Ball, simply select Run from the Run menu (on

the menu bar). To make basic changes in the run sequence, including altering the number of trials,

select Run Preferences from the Run menu. After each simulation run, the user needs to select

Reset (also from the Run menu) before Run can be selected again. Once Crystal Ball has completed

its run sequence it will produce a series of distributions. Using the menu bars on the distribution

results it is possible to obtain further statistical information. The time taken to complete a run

sequence can be reduced by minimizing the Crystal Ball window in Microsoft Excel. A step by step

summary of the procedure for running a distribution analysis is outlined below:

1. Find the Crystal Ball toolbar (at top of screen)

2. Click on Run from the menu bar

3. Select Run Preferences and choose from the following choices:

a. Monte Carlob

b. Latin Hypercube (recommended)

c. Initial seed choices and whether you want it to be constant between runs

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d. Select number of Monte Carlo Trials (we suggest 10,000).

4. To run the simulation, follow the following sequence (on the Crystal Ball toolbar)

Run

Reset

Run

5. Now wait until the program informs you that the simulation is completed.

The following instructions are provided to view the output generated by Crystal Ball.

6. After the simulation has finished, to see the distribution charts generated, click on the

Windows tab bar that is labeled Crystal Ball.

 

7. The life-cycle cost savings and payback periods are defined as Forecast cells. The

frequency charts display the results of the simulations, or trials, performed by Crystal

Ball. Click on any chart to bring it into view. The charts show the low and high

endpoints of the forecasts. The View selection on the Crystal Ball toolbar can be

used to specify whether you want cumulative or frequency plots shown.

8. To calculate the probability of that LCC savings will occur, either type 0 in the box

by the right arrow, or move the arrow key with the cursor to 0 on the scale. The

value in the Certainty box shows the likelihood that the LCC savings will occur. To

calculate the certainty of payback period being below a certain number of years,

choose that value as the high endpoint.

9. To generate a printout report, select Create Report from the Run menu. The toolbar

choice of Forecast Windows allows you to select the charts and statistics you are

interested in. For further information on Crystal Ball outputs, please refer to

Understanding the Forecast Chart in the Crystal Ball manual.

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1. U.S. Department of Energy-Energy Information Administration, A Look at Residential

Energy Consumption in 1997, 1999. Washington, DC. Report No. DOE/EIA-0632(97).

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2. American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc., Energy

Efficient Design of New Buildings Except Low-Rise Residential Buildings, 1999. Atlanta,

GA. Standard 90.1-1999.

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4. U.S. Department of Energy-Energy Information Administration, 1995 Commercial Building

Energy Consumption and Expenditures (CBECS), 1995. Public Use Data, Micro-data file

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.pdf>

7. Air Conditioning, Heating, and Refrigeration News, December, 12, 1998.

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California. Telephone conversations with Gregory Rosenquist, LBNL, November 1998.

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Energy Consumption in 1997, 1999. Washington, DC. Report No. DOE/EIA-0632(97).

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