PUBLIC DISCLOSURE 

Achievable Energy-Efficiency Potentials Assessment 

Submitted to Georgia Power Company 

Submitted By Nexant 

In partnership with: The Cadmus Group, Inc. 

January 31, 2012 
SECTION 1 PUBLIC DISCLOSURE Executive Summary 

Achievable Energy-Efficiency Potentials Assessment 2

CONTENTS

1 EXECUTIVE SUMMARY ........................................................................................................3

1.1 BACKGROUND ........................................................................................................................................... 3

1.2 ASSESSMENT APPROACH ............................................................................................................................. 3

1.3 DEFINITIONS OF ENERGY-EFFICIENCY POTENTIALS ............................................................................................ 4

1.4 SUMMARY RESULTS ................................................................................................................................... 5

1.4.1 Achievable Potentials by Sector .............................................................................................. 7

1.4.2 Achievable Potentials by End Use ........................................................................................... 8

1.5 ACHIEVABLE POTENTIAL COST-EFFECTIVENESS ................................................................................................ 9

1.6 CONCLUSIONS ......................................................................................................................................... 12

1.7 CAVEATS ................................................................................................................................................ 13

1.7.1 Uncertainties ........................................................................................................................ 13

1.7.2 Potential Reliability Impacts ................................................................................................. 13

1.7.3 Rate Impacts ......................................................................................................................... 13

2 STUDY APPROACH ............................................................................................................ 15

2.1 INTRODUCTION ....................................................................................................................................... 15

2.1.1 Background .......................................................................................................................... 15

2.1.2 Objectives ............................................................................................................................. 15

2.2 APPROACH ............................................................................................................................................. 15

3 ESTIMATES OF ENERGY-EFFICIENCY POTENTIALS................................................................ 20

3.1 INTRODUCTION ....................................................................................................................................... 20

3.2 SUMMARY OF ENERGY-EFFICIENCY POTENTIALS............................................................................................. 20

3.2.1 Technical and Economic Potentials ...................................................................................... 21

3.3 THEORETICALLY ACHIEVABLE POTENTIALS ..................................................................................................... 23

3.3.1 By Sector ............................................................................................................................... 24

3.3.2 By End Use ............................................................................................................................ 26

3.3.3 Cost-Effectiveness ................................................................................................................. 27

3.3.4 Detailed Analysis .................................................................................................................. 37

3.3.4.1 Residential Sector ................................................................................................................ 38

3.3.4.2 Commercial Sector .............................................................................................................. 44

3.3.4.3 Industrial Sector .................................................................................................................. 49

4 CONCLUSIONS .................................................................................................................. 55

APPENDIX A DETAILED METHODOLOGY ............................................................................ A-1

A.1 DEVELOPING A BASELINE FORECAST .......................................................................................................... A-2

A.1.1 Data Sources ....................................................................................................................... A-3

A.2 COMPILING ENERGY-EFFICIENCY TECHNOLOGY DATA ................................................................................... A-3

A.3 ESTIMATING TECHNICAL POTENTIAL .......................................................................................................... A-5

A.3.1 Non-Equipment Measures .................................................................................................. A-6

A.4 ESTIMATING ECONOMIC POTENTIAL .......................................................................................................... A-7

A.4.1 Benefit Components ........................................................................................................... A-8

A.4.2 Measure Cost Components................................................................................................. A-8

A.4.3 Caveats ............................................................................................................................... A-8

A.5 ESTIMATING ACHIEVABLE POTENTIAL ........................................................................................................ A-9

APPENDIX B BENEFIT-COST ANALYSIS ............................................................................... B-1
     

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Achievable Energy-Efficiency Potentials Assessment 3

1 EXECUTIVE SUMMARY

1.1 BACKGROUND 

As part of the 2013 Integrated Resource Plan (“IRP”) process, Georgia Power Company (“Georgia 

Power”) must complete an updated energy-efficiency technical, economic, and achievable 

potentials study, as described in the 2010 IRP Final Order (Dockets #31081 and #31082), per the 

Georgia Public Service Commission. This report details the results of the potentials study to be used 

as part of Georgia Power’s 2013 IRP filing. 

Georgia Power retained Nexant, Inc, subcontracting to The Cadmus Group, Inc., (“Cadmus”), to 

conduct an assessment of energy-efficiency potentials in the Georgia Power service area, building 

on results from the energy-efficiency measure screening and technical analyses, which Nexant had 

supported over the preceding months. Southern Company Services provided additional support with 

the study’s modeling analyses. 

1.2 ASSESSMENT APPROACH 

The achievable energy-efficiency potentials assessment used the following three sequential steps: 

• Organize input data: Nexant and Cadmus compiled final energy-efficiency measure 

screening results, effective useful life, incremental cost, and collected service area sales 

forecast data. Inputs included confidential data, such as: forecast of customer counts and 

floor space, end-use saturations, end-use unit energy consumption, and energy intensity. 

• Estimate energy-efficiency potentials impacts at the end-use level: Southern Company 

Services modeled individual energy-efficiency measures in EnerSim1 to create loadshapes, 

calculate electricity revenues, and evaluate any other utility impacts. The Profitability 

Reliability Incremental Cost Evaluation Model (“PRICEM”) used the EnerSim loadshapes to 

calculate the electric economics of energy-efficiency measures. Using energy savings and 

associated economic impacts (electric, gas, and water) for each of the 332 discrete 

measures, Cadmus analyzed groups of measures by facility type and end use. 

• Estimate theoretically achievable impacts: Following a review of energy-efficiency market 

potentials studies, reported Energy Information Agency (“EIA”) data, and observed program 

results, Cadmus applied plausible market penetration curves to each end use, estimating 

 

1 EnerSim—an hourly building energy simulation model, used to predict energy consumption in buildings based on 

construction characteristics, insulation, occupancy, orientation, local weather, and other attributes—was used to 

generate all energy usage profiles for weather-sensitive end uses examined for both residential and nonresidential 

measures. The U.S. Department of Energy, having certified and approved EnerSim, lists the model as a “Qualified 

Software” on its Website. 
     

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Achievable Energy-Efficiency Potentials Assessment 4

technically feasible, economically feasible, and potentially achievable energy-efficiency 

impacts. 

1.3 DEFINITIONS OF ENERGY-EFFICIENCY POTENTIALS 

Figure 1 shows types of potentials available in a utility’s territory, defined as follows: 

• Technical potential: The quantification of savings that can be realized if energy-efficiency 

measures passing the qualitative screening are applied in all feasible instances, regardless of 

cost. 

• Economic potential: A subset of technical potential, where measures are cost-effective from 

the Total Resource Cost (“TRC”) perspective, without regard to cross-subsidies. 

• Achievable potential: Energy savings that can feasibly be achieved through program and 

policy interventions. This study estimated theoretically achievable potential for three policy 

intervention scenarios corresponding to varying incentive levels provided to end-use 

consumers: 

o Low incentives: Monetary incentives to customers, equaling 25% of incremental costs of 

energy-efficiency improvements. 

o Moderate incentives: Monetary incentives to customers, equaling 50% of incremental 

costs of energy-efficiency improvements. 

o High incentives: Monetary incentives to customers, equaling 100% of incremental costs 

of energy-efficiency improvements. 

Figure 1. Illustration of Energy-Efficiency Potentials 

Note: Figure 1 is from the Environmental Protection Agency National Action Plan for Energy Efficiency (“EPANAPEE”) Guide for Conducting Energy Efficiency Potential Studies; for illustrative purpose only. 
     

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Each scenario included significant expenditures on incentives subsidizing energy-efficiency measure 

purchases. Note that this study has been based on a number of estimates, including penetration 

rate projections that attempt to describe human behaviors associated with program structures. One 

cannot know with certainty whether results can be obtained under the scenarios studied. 

1.4 SUMMARY RESULTS 

This section provides high-level results of achievable potential; the following section provides 

detailed results. The assessment period covers 2012–2023, with cumulative results shown below. 

Achievable potential ranged from 6.0% to 15.1% of 2023 electricity sales and 6.4% to 16.1% of 2023 

peak demand2, depending on incentive scenarios. Table 1 presents the 2023 potential and percent 

of load for the three incentive scenarios. Figure 2 and Figure 3 provide forecasts (electricity sales 

and peak demand, respectively) relative to Georgia Power’s baseline forecast3, based on the 

achievable potential scenarios over the study horizon. 

Table 1. Theoretically Achievable Potential Savings (Cumulative through 2023) 

Load Type 

Low Incentive Moderate Incentive High Incentive

Total 

Potential 

Percent of 

2023 Load 

Total 

Potential 

Percent of 

2023 Load 

Total 

Potential 

Percent of 

2023 Load 

Reduction in Electricity 

Sales (MWh) REDACTED 6.0% REDACTED 9.1% REDACTED 15.1% 

Reduction in Peak 

Demand (MW) REDACTED 6.4% REDACTED 9.7% REDACTED 16.1% 

 

2 Electricity sales are defined as electric energy at the customer’s meter. Peak Demand is defined as coincident 

peak at the customer’s meter. 

3 Baseline forecast is Georgia Power’s total forecast, excluding territorial wholesale customers. 
     

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Figure 2. Energy Forecasts for Theoretically Achievable Potential (Electricity Sales) 

 

Figure 3. Demand Forecasts for Theoretically Achievable Potential (Peak Demand) 

0

20,000,000

40,000,000

60,000,000

80,000,000

100,000,000

120,000,000

2012 2014 2016 2018 2020 2022

Electricty Sales (MWh)

Base Forecast

High Incentive

Moderate Incentive

Low Incentive

0

5,000

10,000

15,000

20,000

25,000

2012 2014 2016 2018 2020 2022

Peak Demand (MW)

Base Forecast

High Incentive

Moderate Incentive

Low Incentive

REDACTED

REDACTED
     

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1.4.1 Achievable Potentials by Sector 

Figure 4 and Figure 5 provide theoretically achievable energy and peak demand potential for 2023 

under the high incentive scenario by sector. 

Figure 4. 2023 Theoretically Achievable Potential by Sector (Electricity Sales) 

Figure 5. 2023 Theoretically Achievable Potential by Sector (Peak Demand) 

Commercial, 

60%

Industrial, 19%

Residential, 

21%

Commercial, 

67%

Industrial, 

13%

Residential, 

20%
     

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Achievable Energy-Efficiency Potentials Assessment 8

1.4.2 Achievable Potentials by End Use 

Figure 6 and Figure 7 provide energy and peak demand potential for 2023 under the high incentive 

scenario by end use (all sectors). 

Figure 6. 2023 Theoretically Achievable Potential by End Use (Electricity Sales) 

Com-HVAC 

Equipment, 2%

Com-HVAC Shell, 19%

Com-Lighting, 29%

Com-Miscellaneous, 

2%

Com-Office 

Com-Refrigeration, 1% Equipment, 6%

Com-Water 

Heating, 1%

Ind-HVAC 

Equipment, 

2%

Ind-Lighting, 2%

Ind-Other, 1%

Ind-Motors, 

5%

Ind-Process, 9%

Res-Appliances, 7%

Res-HVAC Equipment, 

4%

Res-HVAC Shell, 5%

Res-Lighting, 2% Res-Water Heating, 4%

Res-Plug Load, 0.3%

Res-Pool Pump, 1%
     

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Achievable Energy-Efficiency Potentials Assessment 9

Figure 7. 2023 Theoretically Achievable Potential by End Use (Peak Demand) 

1.5 ACHIEVABLE POTENTIAL COST-EFFECTIVENESS 

The following tables present cost-effectiveness indicators from Total Resource Cost (“TRC”), 

Ratepayer Impact Measure (“RIM”), and Participant Cost Test (“PCT”) perspectives, respectively, for 

achievable energy-efficiency impacts from 2012 through 2023. The tables present economic 

indicators for each scenario of theoretically achievable potential. Refer to Appendix B for a detailed

description of the methods used for calculating TRC, RIM, and PCT. Theoretically, TRC net benefits of 

between $2.6 and $6.4 billion can be achieved, at a RIM net cost of between $1.7 and $7.2 billion to 

electricity ratepayers. The RIM net cost indicates the amount electricity rates would have to 

Com-HVAC 

Equipment, 

5%

Com-HVAC Shell, 19%

Com-Lighting, 32%

ComMiscellaneous, 2%

Com-Office 

Equipment, 

7%

Com-Refrigeration, 1%

Com-Water 

Heating, 1%

Ind-HVAC 

Equipment, 1%

Ind-Lighting, 1%

Ind-Other, 1% Ind-Motors, 3%

Ind-Process, 6%

Res-Appliances, 2%

Res-HVAC 

Equipment, 4%

Res-HVAC Shell, 11%

Res-Lighting, 1%

Res-Water 

Heating, 0.4%

Res-Plug Load, 

0.04% Res-Pool Pump, 0.7%
     

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Achievable Energy-Efficiency Potentials Assessment 10

increase due to energy efficiency—over and above rate increases ordinarily expected.4

Theoretically, PCT net benefits of between $4.3 and $13.6 billion are available to participants. 

Table 2. Net Benefits and Benefit-to-Cost Ratio for TRC, RIM, and PCT Perspectives 

(Cumulative NPV through 2023) 

TRC RIM PCT 

Achievable 

Scenario 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Low Incentive $2,550 2.4 -$1,732 0.7 $4,283 3.9

Moderate Incentive $3,862 2.4 -$3,188 0.6 $7,050 4.1

High Incentive $6,409 2.4 -$7,163 0.5 $13,572 4.6

Figures 8, 9, and 10 illustrate the cost breakdowns for TRC, RIM, and PCT perspectives for each of 

the three scenarios. 

Figure 8. TRC Benefits and Costs by Scenario (Cumulative through 2023) 

 

4 This study does not estimate RIM benefits and costs from a gas and water utility perspective, when applicable. To 

the extent gas or water utility lost revenues exceed avoided gas or water supply costs, as would normally be 

expected, gas or water rates would be adversely affected, and would rise above otherwise anticipated increases. 

This assessment provides estimated net present value data for 2012 through 2023. 

$0

$2

$4

$6

$8

$10

$12

$14

$16

$18

Low Mod High

NPV ($ Billions)

Program Admin & 

Marketing

Participant Cost

Benefits (Other Utility 

Avoided Cost)

Benefits (Elec Avoided 

Cost)
     

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Achievable Energy-Efficiency Potentials Assessment 11

Figure 9. RIM Benefits and Costs by Scenario (Cumulative through 2023) 

Figure 10. PCT Benefits and Costs by Scenario (Cumulative through 2023) 

$0

$2

$4

$6

$8

$10

$12

$14

$16

$18

Low Mod High

NPV ($ Billions)

Program Incentives

Program Admin & 

Marketing

Electric Utility Lost 

Revenue

Benefits (Elec Avoided 

Cost)

$0

$2

$4

$6

$8

$10

$12

$14

$16

$18

Low Mod High

NPV ($ Billions)

Program Incentives

Participant Cost

Participant Bill Savings 

(Other Utility)

Participant Bill Savings 

(Electric)
     

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Achievable Energy-Efficiency Potentials Assessment 12

Table 3 illustrates program incentive and administrative costs for the three scenarios. 

Table 3. Energy Efficiency Program Expenditures (Cumulative NPV through 2023) 

Achievable Scenario Incentives ($MM) Administrative Costs ($MM) Total Costs ($MM) 

Low Incentive $373 $374 $747

Moderate Incentive $1,129 $566 $1,695

High Incentive $3,748 $939 $4,687

1.6 CONCLUSIONS 

This assessment identifies the potential for increased energy-efficiency investments by Georgia 

Power customers above the levels that would naturally occur but would require the significant 

incentives assumed in this analysis. These results will be useful in targeting energy-efficiency 

program planning efforts to areas with the highest market potential. 

Customers can reduce their energy consumption and peak power requirements by implementing 

energy-efficiency measures or actions, receiving economic benefits directly through reductions in 

their energy bills. Customers who participate could also benefit from financial incentives offered by 

programs intended to accelerate markets for purchase and installation of high-efficiency measures. 

At the same time, rates will rise for all customers. Non-participating customers will pay higher bills, 

in effect, subsidizing the costs of incentives and other program costs to the benefit of program 

participants. 

As in a similar 2007 assessment, this study examines scenarios of theoretically achievable energyefficiency potential associated with low incentives, moderate incentives, and high incentives. 

Economic benefits include: 

• Potential electric energy savings ranging from 6.0% of year 2023 forecast sales under a low 

incentive scenario to 15.1% under a high incentive scenario. 

• Incentives ranging from $25 million per year to more than $250 million per year in 2012, the 

study’s first year. 

• TRC benefits from energy-efficiency improvements could range as high as $2.6 billion to 

$6.4 billion. 

• Not including incentives, net participant cost benefits range from $3.9 billion to $9.8 billion. 
     

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Achievable Energy-Efficiency Potentials Assessment 13

However, these benefits come at substantial costs to ratepayers: 

• Net costs to electric utility ratepayers could range from $1.7 billion to $7.2 billion, over and 

above those associated with supply-side costs. 

• Program costs alone could increase electric ratepayer burden by a total of $750 million to 

$4.7 billion. 

1.7 CAVEATS 

In interpreting this study’s results (and, generally, all studies of this nature), readers should consider 

the following, important caveats. 

1.7.1 Uncertainties 

Market acceptance rate serves as a key determinant of the potential for achievable energyefficiency savings. However, market acceptance depends on behavioral factors that are hard to 

predict and involve a high level of uncertainty. The 2005 Georgia Environmental Facilities Authority 

(“GEFA”) study noted a similar caveat: “The greatest source of uncertainty in our projections of 

achievable potential are the estimates of market share growth under each policy scenario.” 

The estimated impacts of efficient technologies on energy consumption provide another key 

determinant of savings potential; yet, these inputs also present uncertainty. While efficient 

technology options can be reasonably well defined in the near term, customer behaviors and 

electricity usage patterns vary widely, and can differ significantly from assumptions made to model 

“typical” usage profiles. Future years may experience greater uncertainties due to insufficient 

information about future technology choices and future codes and standards improvement. 

Consequently, the availability and magnitude of future impacts must be considered inherently 

speculative. 

1.7.2 Potential Reliability Impacts 

The above-noted uncertainties could result in a deterioration of system reliability, if estimates of 

achievable energy savings are used to justify cancellation or deferral of Power Purchase Agreements 

(“PPAs”) and generation capacity construction programs. If expected energy and capacity savings do 

not materialize or sustain, planned PPAs and generation resource options—many of which require 

long lead times—might be insufficient to maintain system reliability until additional resource 

options can be secured. 

1.7.3 Rate Impacts 

Energy-efficiency programs could cause electricity rates to rise faster than they would ordinarily. 

The noted uncertainties could result in lower energy savings, without corresponding reductions in 

fixed program costs and, hence, adversely impact rates. Market acceptance rates failing to 

materialize, for example, reduce incentives and rebate processing costs, but do not reduce 
     

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Achievable Energy-Efficiency Potentials Assessment 14

marketing or other fixed program management and reporting costs. Moreover, if realized 

technology impacts prove less than estimated, impacts of all estimated costs for rebates, processing, 

marketing, and administration would remain, but with diminished supply cost savings. Thus, rate 

impacts could be more severe than those estimated in this study. 
PUBLIC DISCLOSURE 

Achievable Energy-Efficiency Potentials Assessment 15

2 STUDY APPROACH

2.1 INTRODUCTION 

This report presents findings from the electric energy-efficiency technical, economic, and achievable 

potentials study, supporting Georgia Power’s 2013 IRP filing. The study’s horizon covers 2012–2023, 

encompassing the residential, commercial, and industrial sectors. 

2.1.1 Background 

As part of the 2013 IRP process, Georgia Power must complete an updated energy-efficiency 

technical, economic, and achievable potentials study, as described in the 2010 IRP Final Order 

(Dockets #31081 and #31082), per the Georgia Public Service Commission. This report details the 

results of the potentials study to be used as part of Georgia Power’s 2013 IRP filing. 

Georgia Power retained Nexant, Inc, subcontracting to Cadmus, to conduct an assessment of 

energy-efficiency potentials in the Georgia Power service area, building on results from the energy 

efficiency measure screening and technical analyses, which Nexant had supported over the 

preceding months. Southern Company Services provided additional support with the study’s 

modeling analyses. 

2.1.2 Objectives 

This study includes the following key objectives: 

• Expanding the scope of energy efficiency measure screening and economic analyses to 

quantify theoretical technical and economic energy-efficiency potentials. 

• Assessing theoretically achievable energy-efficiency potential through scenario analyses, 

corresponding to potential policy settings, in which customers would be offered low, 

moderate, and high incentives. 

2.2 APPROACH 

The general methodology used can best be described as a hybrid “top-down/bottom-up” approach. 

As illustrated in Figure 11, it began by examining the current energy forecast, and then decomposing 

this into its constituent customer-class and end-use components. Effects for a range of energyefficiency approaches and practices for each end use could then be examined, while accounting for 

fuel shares, current market saturations, technical feasibility, and costs. These unique impacts were 

aggregated to produce resource potentials estimates at the end-use, customer-class, and system 

levels. 
     

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Achievable Energy-Efficiency Potentials Assessment 16

Figure 11. Potentials Assessment Methodology 

The following, detailed methodology for estimating energy-efficiency potentials remained consistent 

for all three sectors: 

• Develop a baseline forecast: The study created a baseline electric energy forecast, based on 

end-use consumption estimates, and calibrated to Georgia Power’s official electric energy 

forecast. This provided accurate consumption estimates by fuel, sector, customer segment, 

end use, and year. 

• Compile measure lists: All measures applicable to Georgia Power’s climate and customers 

were analyzed to best depict energy-efficiency potentials over a 12-year planning horizon 

(2012–2023). A qualitative screen was applied to the measure list using the following criteria 

for removal: 
     

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o Difficult to quantify savings 

o Current practice 

o Better measure available 

o Immature or unproven technology 

o Limited applicability 

o Poor customer acceptance 

o Health and environmental concerns 

o End-use service degradation 

• Collect cost and impact data for measures: For all measures passing the qualitative 

screening, market research and models were used to estimate costs, energy, and demand 

savings. 

o Nexant conducted market research to estimate measure costs and effective useful life. 

The cost data differentiated between the type of cost (capital, installation labor, 

maintenance, etc.) to separately evaluate different implementation modes: retrofit 

(capital plus installation labor plus incremental maintenance); new construction 

(incremental capital and maintenance); and burnout costs (incremental capital and 

maintenance). 

o Georgia Power and Southern Company Services conducted the economic analysis for 

energy-efficiency measures. All residential and commercial measures were analyzed 

using the EnerSim model, which simulated energy usage in homes and buildings using 

weather data specific to Georgia Power’s service area. Home and building prototypes 

were modeled for existing and new dwellings and facilities. The resulting EnerSim data 

included loadshapes, calculation of electricity impacts (revenues, energy, and demand), 

and gas and water impacts. Loadshapes and electricity revenue impacts provided inputs 

for PRICEM in calculating total electric utility avoided costs and electric utility revenue 

impacts. 

Nexant determined industrial energy-efficiency measure savings using the Industrial 

Assessment Centers (“IAC”) Database, and other sources Nexant had available. Georgia 

Power used BillGen5 for calculating electricity revenue impacts of industrial measures, 

with loadshapes either created using EnerSim or selected from an end-use database. As 

 

5 BillGen® is a data analysis and billing application system used to calculate utility bills and perform rate 

comparisons for residential, commercial, and industrial customers. BillGen is a registered trademark of ABB. 
     

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with residential and commercial, the loadshapes and electricity revenue impacts were 

then input into PRICEM for calculating total electric utility avoided costs and electric 

utility revenue impacts. 

• Estimate Potentials:

o Naturally occurring conservation refers to energy-efficiency gains occurring due to

normal market forces, such as technological changes, energy prices, market 

transformation efforts, and improved energy codes and standards. This analysis 

accounted for market effect components resulting from naturally occurring 

conservation by explicitly incorporating changes to codes and standards, and marginal 

efficiency shares in developing base-case forecasts. 

o Technical potential assumes all resource opportunities may be captured, regardless of 

their costs or market barriers. For energy-efficiency, technical potential is divided into 

two classes: retrofits and lost-opportunity resources. 

o Economic potential can be defined as technical potential measure proving costeffective, using the TRC test as the basis for an economic screen. Measures with a TRC 

benefit-cost ratio greater than one are included in the economic potential. 

o Achievable potential can be defined as the portion of economic potential that might be 

assumed achievable in the course of the planning horizon, given market barriers may 

impede customer participation in energy-efficiency programs; these achievable 

potential levels serve principally as planning guidelines. Ultimately, actual achievable 

opportunity levels depend on: customers’ willingness and ability to participate in energy 

efficiency programs; administrative constraints; and availability of an effective delivery 

infrastructure. Customers’ willingness to participate in energy efficiency programs also 

depends on the size of an incentive offered. As such, the study analyzed three incentive 

scenarios relative to their incremental cost: low (25% incentive); moderate (50% 

incentive); and high (100% incentive). 

The study classified measures used to assess potentials into the following four categories: 

• Existing retrofit represents retrofit opportunities in existing construction. An example is 

shell improvements (e.g., insulation, weather-stripping). This potential can be considered a 

“retrofit” as it would occur in existing building stock, and, theoretically, would be available 

any time during the study. 

• Existing equipment replacement refers to efficiency upgrades conducted during normal 

replacements of equipment in existing buildings. These include efficient end-use equipment, 

such as central air conditioners and ENERGY STAR® appliances. Equipment burnout rates 
     

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Achievable Energy-Efficiency Potentials Assessment 19

drive the availability of these resources: if an opportunity to upgrade is missed, it does not 

become available until the new equipment burns out (hence, is a lost opportunity). 

• New construction improvements represent the potential specific to retrofit measures in 

new construction. For some retrofit measures, costs and savings differ from existing 

construction due to an array of baseline conditions (building codes vs. existing conditions). 

Georgia’s new construction forecast drives this potential’s availability, and missed efficiency 

upgrades typically must wait until installed technologies are replaced (hence, a lost 

opportunity). 

• New construction equipment efficiency refers to efficiency equipment upgrades in new 

construction. These include efficient end-use equipment above existing efficiency standards 

for new construction. Similarly to new construction retrofit opportunities, the new 

construction forecast drives this potential, and efficient equipment must be installed as part 

of the construction process. Missed efficiency upgrades must be considered lost 

opportunities. 

The methodology used for estimating energy-efficiency potentials was based on standard 

industry practices. Appendix A provides a detailed discussion of this methodology. 
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Achievable Energy-Efficiency Potentials Assessment 20

3 ESTIMATES OF ENERGY-EFFICIENCY POTENTIALS

3.1 INTRODUCTION 

This assessment primarily sought to develop estimates of available energy-efficiency potentials to 

assist in targeting energy-efficiency programs in areas where the highest market potentials exist. To 

support these efforts, Cadmus performed an in-depth assessment of technical, economic, and 

achievable potentials on energy-efficiency measures in the residential, commercial, and industrial 

sectors. 

Data on measure costs, savings, and market size were collected at the most granular level possible. 

Within each sector, the study distinguished between customer segments or facility types, and their 

respective applicable end uses. Six residential segments (existing and new construction for singlefamily, multifamily, and manufactured homes), 24 commercial segments (12 building types within 

existing and new construction vintages), and 15 industrial segments were analyzed. 

The study included a comprehensive set of energy-efficiency measures, applicable to climate and 

customer characteristics in Georgia Power’s service territory, and drawn from measures used in a 

previous assessment, as well as new measures made commercially available since the last study. As 

shown in Table 4, analysis began by assessing technical potential for 332 unique energy-efficiency 

measures. In considering all permutations of these measures across all customer sectors and 

segments, customized data had to be compiled and analyzed for over 8,000 measures. 

Table 4. Energy-Efficiency Measure Counts by Sector

Sector Unique Measures Permutations 

Residential 118 1,703 

Commercial 144 5,485 

Industrial 70 822 

3.2 SUMMARY OF ENERGY-EFFICIENCY POTENTIALS 

This section presents detailed results of technical, economic, and achievable potential by sector. 

Table 5 and Table 6 provide the three potentials, by sector, for energy and demand savings, 

respectively, in 2023 (the study’s final year). Potentials are provided in absolute terms and as a 

percent of forecasted load. The achievable potential described in the summary represents the high 

scenario, which assumes incentives of 100% of incremental costs. 
     

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Achievable Energy-Efficiency Potentials Assessment 21

Table 5. Summary of Energy Potentials (Cumulative through 2023) by Sector 

Sector 

Technical Potential Economic Potential Achievable Potential

MWh 

Percent of 

2023 Load MWh 

Percent of 

2023 Load MWh 

Percent of 

2023 Load 

Residential REDACTED 22.6% REDACTED 14.7% REDACTED 9.5%

Commercial REDACTED 34.8% REDACTED 31.9% REDACTED 22.1%

Industrial REDACTED 16.2% REDACTED 15.8% REDACTED 11.4%

TOTAL REDACTED 25.8% REDACTED 21.9% REDACTED 15.1%

Table 6. Summary of Peak Demand Potentials (Cumulative through 2023) by Sector 

Sector 

Technical Potential Economic Potential Achievable Potential

MW 

Percent of 

2023 Load MW 

Percent of

2023 Load MW 

Percent of 

2023 Load 

Residential REDACTED 23.5% REDACTED 11.7% REDACTED 7.7%

Commercial REDACTED 44.5% REDACTED 39.9% REDACTED 26.7%

Industrial REDACTED 17.4% REDACTED 16.9% REDACTED 12.2%

TOTAL REDACTED 30.9% REDACTED 23.9% REDACTED 16.1%

3.2.1 Technical and Economic Potentials 

The technical and economic potential concepts, used by energy-efficiency practitioners since the 

late 1980s, often have identified sectors and end uses associated with the largest amounts of 

energy-savings potential. The concepts have not been used to represent how much potential could 

be achieved, but, rather, simply to focus research efforts on the sectors and end uses with higher 

savings potentials. 

To derive technical and economic potential estimates, technically and economically feasible 

measures are applied to all sectors and end uses. Economically feasible measures have a TRC 

benefit-to-cost ratio greater than or equal to 1.0. Appendix A provides further details on the 

methodology. 

Figure 12 and Figure 13 illustrate the residential and commercial sectors have the largest, technically 

feasible energy savings potential, followed by the industrial sector. The majority of technically 

feasible potential in each sector also proves economically feasible. 
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 22

Figure 12. Technically and Economically Feasible Potential by Sector (2023 Electricity Sales) 

 

Figure 13. Technically and Economically Feasible Potential by Sector (2023 Peak Demand) 

 

0

20,000,000

40,000,000

60,000,000

80,000,000

100,000,000

120,000,000

Sales Technical 

Potential

Economic 

Potential

Electricity Sales (MWh)

Residential

Industrial

Commercial

0

5,000

10,000

15,000

20,000

25,000

Sales Technical 

Potential

Economic 

Potential

Peak Demand (MW)

Residential

Industrial

Commercial

REDACTED

REDACTED
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 23

3.3 THEORETICALLY ACHIEVABLE POTENTIALS 

Table 7 provides the achievable potential in 2023 by incentive scenario. 

Table 7. Theoretically Achievable Potential Savings (Cumulative through 2023) 

Load Type 

Low Incentive Moderate Incentive High Incentive

Total 

Potential 

Percent of 

2023 Load 

Total 

Potential 

Percent of 

2023 Load 

Total 

Potential 

Percent of 

2023 Load 

Reduction in Electricity 

Sales (MWh) REDACTED 6.0% REDACTED 9.1% REDACTED 15.1% 

Reduction in Peak 

Demand (MW) REDACTED 6.4% REDACTED 9.7% REDACTED 16.1% 

Figure 14 and Figure 15 present energy forecasts if all theoretically achievable potential was 

realized, in energy sales and peak demand, by scenario over the planning horizon. These forecasts 

are produced by Cadmus using the methodology described in Appendix A. 

 Figure 14. Energy Forecasts for Theoretically Achievable Potential (Electricity Sales) 

 

0

20,000,000

40,000,000

60,000,000

80,000,000

100,000,000

120,000,000

2012 2014 2016 2018 2020 2022

Electricty Sales (MWh)

Base Forecast

High Incentive

Moderate Incentive

Low Incentive

REDACTED
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 24

Figure 15. Demand Forecasts for Theoretically Achievable Potential (Peak Demand) 

 

3.3.1 By Sector 

Figure 16 and Figure 17 show theoretically achievable energy and peak demand savings potential by 

sector for the high incentive scenario. The commercial sector accounts for more than half of the 

energy-savings potential, and almost two-thirds of the peak reduction potential. The residential and 

industrial sectors account for nearly equal portions of the remaining potential for electricity sales,

while the residential sector accounts for the majority of the remaining peak demand reduction. 

0

5,000

10,000

15,000

20,000

25,000

2012 2014 2016 2018 2020 2022

Peak Demand (MW)

Base Forecast

High Incentive

Moderate Incentive

Low Incentive

REDACTED
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 25

Figure 16. 2023 Theoretically Achievable Potential by Sector (Electricity Sales) 

Figure 17. 2023 Theoretically Achievable Potential by Sector (Peak Demand) 

Commercial, 

60%

Industrial, 19%

Residential, 

21%

Commercial, 

67%

Industrial, 13%

Residential, 

20%
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 26

3.3.2 By End Use 

A further understanding of theoretically achievable potential is aided by consideration of 

contributing end uses. Figure 18 and Figure 19 illustrate—in terms of potential savings under the 

high incentive scenario—commercial lighting (29% of potential energy savings) and commercial 

HVAC shell (19%) are the most significant end uses. 

Figure 18. 2023 Theoretically Achievable Potential by End Use (Electricity Sales) 

Com-HVAC 

Equipment, 2%

Com-HVAC Shell, 19%

Com-Lighting, 29%

Com-Miscellaneous, 

2%

Com-Office 

Com-Refrigeration, 1% Equipment, 6%

Com-Water 

Heating, 1%

Ind-HVAC 

Equipment, 

2%

Ind-Lighting, 2%

Ind-Other, 1%

Ind-Motors, 

5%

Ind-Process, 9%

Res-Appliances, 7%

Res-HVAC Equipment, 

4%

Res-HVAC Shell, 5%

Res-Lighting, 2% Res-Water Heating, 4%

Res-Plug Load, 0.3%

Res-Pool Pump, 1%
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 27

Figure 19. 2023 Theoretically Achievable Potential by End Use (Peak Demand) 

3.3.3 Cost-Effectiveness 

Theoretically achievable estimated energy savings potential has significant economic benefits to the 

general economy and many customers served by the Georgia Power. These economic benefits, 

however, require significant investment, which would cost all ratepayers. 

Participant and program costs associated with theoretically achievable potential scenarios include 

the following: 

• Net participant costs: Incremental costs to purchase, install, and maintain energy-efficiency 

measures less any incentive received. 

• Program incentives: Financial incentives paid by energy-efficiency programs to subsidize 

purchases of energy-efficiency measures. 

Com-HVAC 

Equipment, 

5%

Com-HVAC Shell, 19%

Com-Lighting, 32%

ComMiscellaneous, 2%

Com-Office 

Equipment, 

7%

Com-Refrigeration, 1%

Com-Water 

Heating, 1%

Ind-HVAC 

Equipment, 1%

Ind-Lighting, 1%

Ind-Other, 1% Ind-Motors, 3%

Ind-Process, 6%

Res-Appliances, 2%

Res-HVAC 

Equipment, 4%

Res-HVAC Shell, 11%

Res-Lighting, 1%

Res-Water 

Heating, 0.4%

Res-Plug Load, 

0.04% Res-Pool Pump, 0.7%
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 28

• Program administration: Administrative, marketing, promotional, and other costs 

associated with managing programs designed to achieve energy-efficiency savings. 

Table 8 lists estimated participant and program costs associated with the theoretically achievable 

scenarios. 

Table 8. Participant and Program Costs by Achievable Potential Scenario 

(NPV Thousands, Cumulative through 2023) 

Achievable Scenario Net Participant Costs Program Incentives Program Administration 

Low Incentive $1,117,725 $372,575 $374,375

Moderate Incentive $1,129,016 $1,129,016 $566,308

High Incentive $0 $3,748,332 $938,883

Benefits and costs can be expressed from three unique perspectives: TRC, RIM, and PCT. Further 

details on these perspectives can be found in Appendix B. 

Potentially achievable benefits, from programmatic efforts from 2012 through 2023, could range as 

high as $2.6 billion to $6.4 billion from a TRC perspective. Associated costs to electricity ratepayers 

could range from $1.7 billion to $7.2 billion from the RIM perspective. The RIM net cost indicates 

the amount electricity rates would have to increase due to energy-efficiency—over and above rate 

increases ordinarily expected.6 Figure 20, Figure 21, and Figure 22 show benefits and costs from 

TRC, RIM, and PCT perspectives for the theoretically achievable scenarios. 

 

6 This study does not estimate RIM benefits and costs from a gas and water utility perspective, when applicable. To 

the extent gas or water utility lost revenues exceed avoided gas or water supply costs, as would normally be 

expected, gas or water rates would be adversely affected, and would rise above otherwise anticipated increases. 

This assessment provides estimated net present value data for 2012 through 2023. 
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 29

Figure 20. TRC Benefits and Costs by Scenario (Cumulative through 2023) 

Figure 21. RIM Benefits and Costs by Scenario (Cumulative through 2023) 

$0

$2

$4

$6

$8

$10

$12

$14

$16

$18

Low Mod High

NPV ($ Billions)

Program Admin & 

Marketing

Participant Cost

Benefits (Other Utility 

Avoided Cost)

Benefits (Elec Avoided 

Cost)

$0

$2

$4

$6

$8

$10

$12

$14

$16

$18

Low Mod High

NPV ($ Billions)

Program Incentives

Program Admin & 

Marketing

Electric Utility Lost 

Revenue

Benefits (Elec Avoided 

Cost)
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 30

Figure 22. PCT Benefits and Costs by Scenario (Cumulative through 2023) 

From each perspective, Table 9 provides net benefits and benefit-to-cost ratios for each achievable 

potential scenario. 

Table 9. Net Benefits and Benefit-to-Cost Ratio from TRC, RIM, and PCT Perspectives 

(Cumulative NPV through 2023) 

TRC RIM PCT 

Achievable 

Scenario 

Net 

Benefits 

(Millions) 

Benefit/ 

Cost 

Net 

Benefits 

(Millions) 

Benefit/ 

Cost 

Net 

Benefits 

(Millions) 

Benefit/ 

Cost 

Low Incentive $2,550 2.4 -$1,732 0.7 $4,283 3.9

Moderate Incentive $3,862 2.4 -$3,188 0.6 $7,050 4.1

High Incentive $6,409 2.4 -$7,163 0.5 $13,572 4.6

$0

$2

$4

$6

$8

$10

$12

$14

$16

$18

Low Mod High

NPV ($ Billions)

Program Incentives

Participant Cost

Participant Bill Savings 

(Other Utility)

Participant Bill Savings 

(Electric)
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 31

Table 10 through Table 15 list similar economic indicators by sector and end use for each scenario. 

The PCT is given both with and without incentives.

Table 10. TRC and RIM Net Benefits and Benefit-to-Cost Ratio by End Use for All Sectors 

(Low Incentive Scenario, Cumulative NPV through 2023) 

TRC RIM 

End Use 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Res - Appliances $148 2.8 -$168 0.5 

Res - HVAC Equipment $72 1.7 -$116 0.5 

Res - HVAC Shell $426 1.7 -$286 0.5 

Res - Lighting $27 2.4 -$56 0.5 

Res - Plug Load $6 2.9 -$9 0.5 

Res - Pool Pump $13 3.6 -$9 0.7 

Res - Water Heating $51 1.4 -$111 0.5 

Com - HVAC Equipment $95 4.9 -$19 0.9 

Com - HVAC Shell $338 1.8 -$341 0.7 

Com - Lighting $755 3.8 -$368 0.7 

Com - Miscellaneous $165 3.8 -$56 0.6 

Com - Office Equipment $67 3.1 -$53 0.7 

Com - Refrigeration $23 7.8 -$10 0.7 

Com - Water Heating $28 3.2 -$20 0.6 

Ind - HVAC Equipment $46 7.9 -$11 0.8 

Ind - Lighting $47 4.3 -$7 0.9 

Ind - Motors $81 2.6 -$43 0.8 

Ind - Other $21 3.4 -$7 0.8 

Ind - Process $140 4.7 -$42 0.8 
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 32

Table 11. TRC and RIM Net Benefits and Benefit-to-Cost Ratio by End Use for All Sectors 

(Moderate Incentive Scenario, Cumulative NPV through 2023) 

TRC RIM 

End Use 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Res - Appliances $225 2.8 -$280 0.5 

Res - HVAC Equipment $108 1.6 -$208 0.5 

Res - HVAC Shell $646 1.7 -$614 0.4 

Res - Lighting $40 2.4 -$90 0.5 

Res - Plug Load $9 2.9 -$15 0.5 

Res - Pool Pump $20 3.6 -$16 0.6 

Res - Water Heating $77 1.4 -$203 0.5 

Com - HVAC Equipment $144 4.9 -$37 0.8 

Com - HVAC Shell $512 1.8 -$641 0.6 

Com - Lighting $1,143 3.8 -$638 0.7 

Com - Miscellaneous $250 3.8 -$103 0.5 

Com - Office Equipment $101 3.1 -$90 0.6 

Com - Refrigeration $35 7.8 -$16 0.7 

Com - Water Heating $43 3.2 -$34 0.6 

Ind - HVAC Equipment $70 7.9 -$19 0.8 

Ind - Lighting $72 4.3 -$15 0.9 

Ind - Motors $123 2.6 -$81 0.7 

Ind - Other $32 3.4 -$13 0.8 

Ind - Process $213 4.7 -$75 0.8 
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 33

Table 12. TRC and RIM Net Benefits and Benefit-to-Cost Ratio by End Use for All Sectors 

(High Incentive Scenario, Cumulative NPV through 2023) 

TRC RIM 

End Use 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Res - Appliances $373 2.8 -$548 0.4 

Res - HVAC Equipment $177 1.6 -$453 0.4 

Res - HVAC Shell $1,072 1.7 -$1,620 0.3 

Res - Lighting $67 2.4 -$170 0.4 

Res - Plug Load $15 2.9 -$28 0.5 

Res - Pool Pump $33 3.6 -$31 0.6 

Res - Water Heating $128 1.4 -$455 0.4 

Com - HVAC Equipment $240 4.9 -$85 0.8 

Com - HVAC Shell $849 1.8 -$1,476 0.5 

Com - Lighting $1,898 3.8 -$1,329 0.7 

Com - Miscellaneous $415 3.8 -$230 0.5 

Com - Office Equipment $168 3.1 -$182 0.6 

Com - Refrigeration $59 7.8 -$29 0.7 

Com - Water Heating $71 3.2 -$70 0.5 

Ind - HVAC Equipment $116 7.9 -$39 0.8 

Ind - Lighting $119 4.3 -$40 0.8 

Ind - Motors $204 2.6 -$186 0.6 

Ind - Other $53 3.4 -$31 0.7 

Ind - Process $353 4.7 -$162 0.7 
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 34

Table 13. PCT Net Benefits and Benefit-to-Cost Ratio by End Use for All Sectors 

(Low Incentive Scenario, Cumulative NPV through 2023) 

PCT (with incentives) PCT (no incentives) 

End Use 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Res - Appliances $316 5.7 $299 5.5 

Res - HVAC Equipment $188 3.1 $166 2.9 

Res - HVAC Shell $712 2.5 $592 2.2 

Res - Lighting $82 6.2 $78 6.0 

Res - Plug Load $15 7.0 $15 6.8 

Res - Pool Pump $23 6.6 $22 6.3 

Res - Water Heating $162 2.7 $138 2.5 

Com - HVAC Equipment $114 6.8 $110 6.6 

Com - HVAC Shell $679 3.1 $597 2.8 

Com - Lighting $1,122 6.2 $1,069 6.0 

Com - Miscellaneous $221 5.7 $209 5.5 

Com - Office Equipment $120 5.8 $114 5.5 

Com - Refrigeration $33 12.9 $32 12.7 

Com - Water Heating $48 5.6 $46 5.4 

Ind - HVAC Equipment $58 11.7 $56 11.5 

Ind - Lighting $54 5.7 $52 5.5 

Ind - Motors $124 4.0 $114 3.7 

Ind - Other $28 5.0 $26 4.8 

Ind - Process $182 7.0 $175 6.8 
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 35

Table 14. PCT Net Benefits and Benefit-to-Cost Ratio by End Use for All Sectors 

(Moderate Incentive Scenario, Cumulative NPV through 2023) 

PCT (with incentives) PCT (no incentives) 

End Use 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Res - Appliances $504 6.0 $453 5.5 

Res - HVAC Equipment $316 3.4 $249 2.9 

Res - HVAC Shell $1,260 2.7 $898 2.2 

Res - Lighting $131 6.5 $119 6.0 

Res - Plug Load $24 7.3 $22 6.8 

Res - Pool Pump $36 6.8 $33 6.3 

Res - Water Heating $280 3.0 $209 2.5 

Com - HVAC Equipment $181 7.1 $166 6.6 

Com - HVAC Shell $1,153 3.3 $905 2.8 

Com - Lighting $1,781 6.5 $1,619 6.0 

Com - Miscellaneous $353 6.0 $317 5.5 

Com - Office Equipment $192 6.0 $173 5.5 

Com - Refrigeration $51 13.2 $49 12.7 

Com - Water Heating $77 5.9 $69 5.4 

Ind - HVAC Equipment $89 12.0 $85 11.5 

Ind - Lighting $87 6.0 $78 5.5 

Ind - Motors $204 4.2 $172 3.7 

Ind - Other $45 5.3 $40 4.8 

Ind - Process $287 7.3 $264 6.8 
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 36

Table 15. PCT Net Benefits and Benefit-to-Cost Ratio by End Use for All Sectors 

(High Incentive Scenario, Cumulative NPV through 2023) 

PCT (with incentives) PCT (no incentives) 

End Use 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Res - Appliances $921 6.5 $753 5.5 

Res - HVAC Equipment $630 3.9 $410 2.9 

Res - HVAC Shell $2,692 3.2 $1,490 2.2 

Res - Lighting $237 7.0 $197 6.0 

Res - Plug Load $43 7.8 $37 6.8 

Res - Pool Pump $65 7.3 $55 6.3 

Res - Water Heating $583 3.5 $346 2.5 

Com - HVAC Equipment $325 7.6 $275 6.6 

Com - HVAC Shell $2,325 3.8 $1,502 2.8 

Com - Lighting $3,226 7.0 $2,688 6.0 

Com - Miscellaneous $645 6.5 $527 5.5 

Com - Office Equipment $350 6.5 $286 5.5 

Com - Refrigeration $88 13.7 $81 12.7 

Com - Water Heating $141 6.4 $115 5.4 

Ind - HVAC Equipment $155 12.5 $141 11.5 

Ind - Lighting $159 6.5 $130 5.5 

Ind - Motors $390 4.7 $286 3.7 

Ind - Other $84 5.8 $66 4.8 

Ind - Process $515 7.8 $439 6.8 
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 37

3.3.4 Detailed Analysis 

Congruent with Georgia Power’s 2007 study and with the 2005 GEFA study’s scope and detail, this 

section presents analytical results of estimated savings associated with each theoretically achievable

scenario, by sector. 

Table 16 lists theoretically achievable potential, in absolute terms and as a share of 2023 load, by 

sector. 

Table 16. Theoretically Achievable Potential Savings by Sector 

(Cumulative through 2023) 

Low Incentive 

Achievable Potential 

Moderate Incentive 

Achievable Potential 

High Incentive 

Achievable Potential 

Load Type 

Total 

Potential 

Percent of 

2023 Load 

Total 

Potential 

Percent of 

2023 Load 

Total 

Potential 

Percent of 

2023 Load 

Residential 

Reduction in Electricity 

Sales (MWh) REDACTED 3.9% REDACTED 5.8% REDACTED 9.5% 

Reduction in Peak 

Demand (MW) REDACTED 3.1% REDACTED 4.6% REDACTED 7.7% 

Commercial

Reduction in Electricity 

Sales (MWh) REDACTED 8.8% REDACTED 13.3% REDACTED 22.1% 

Reduction in Peak 

Demand (MW) REDACTED 10.6% REDACTED 16.1% REDACTED 26.7% 

Industrial

Reduction in Electricity 

Sales (MWh) REDACTED 4.5% REDACTED 6.9% REDACTED 11.4% 

Reduction in Peak 

Demand (MW) REDACTED 4.9% REDACTED 7.4% REDACTED 12.2% 

Total

Reduction in Electricity 

Sales (MWh) REDACTED 6.0% REDACTED 9.1% REDACTED 15.1% 

Reduction in Peak 

Demand (MW) REDACTED 6.4% REDACTED 9.7% REDACTED 16.1% 
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 38

3.3.4.1 Residential Sector 

Table 17 presents the residential sector’s achievable potential for the three incentive scenarios. 

Table 17. Theoretically Achievable Potential Savings for Residential Sector 

(Cumulative through 2023) 

Low Incentive 

Achievable Potential 

Moderate Incentive 

Achievable Potential 

High Incentive 

Achievable Potential 

Load Type 

Total 

Potential 

Percent of 

2023 Load 

Total 

Potential 

Percent of 

2023 Load 

Total 

Potential 

Percent of 

2023 Load 

Reduction in Electricity 

Sales (MWh) REDACTED 3.9% REDACTED 5.8% REDACTED 9.5% 

Reduction in Peak 

Demand (MW) REDACTED 3.1% REDACTED 4.6% REDACTED 7.7% 

Figure 23 and Figure 24 show the residential sector’s baseline forecast and forecasts by achievable 

potential scenario, for energy sales and peak demand forecast, respectively. 

Figure 23. Energy Forecasts for Theoretically Achievable Potential in Residential Sector (Electricity Sales) 

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

35,000,000

40,000,000

2012 2014 2016 2018 2020 2022

Electricity Sales (MWh)

Base Forecast

High Incentive

Moderate Incentive

Low Incentive

REDACTED
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 39

Figure 24. Demand Forecasts for Theoretically Achievable Potential in Residential Sector (Peak Demand)

 

Figure 25 and Figure 26 illustrate theoretically achievable residential savings under the high 

incentive scenario by end use for energy and peak demand, respectively. The potential electric 

energy savings concentrate in four end-use categories: appliances (30% of potential); HVAC shell 

(22%); HVAC equipment (17%); and water heating (17%). Lighting, which historically has been a large 

portion of the potential, has dropped in significance, in large part due to the new federal efficiency

standards. 

Figure 25. Residential - 2023 Theoretically Achievable Potential by End Use (Electricity Sales) 

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

2012 2014 2016 2018 2020 2022

Peak Demand (MW)

Base Forecast

High Incentive

Moderate Incentive

Low Incentive

Appliances, 

30%

HVAC 

Equipment, 

17% HVAC Shell, 

22%

Lighting, 10%

Water Heating, 

17%

Plug Load, 2% Pool Pump, 2%

REDACTED
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 40

Figure 26. Residential - 2023 Theoretically Achievable Potential by End Use (Peak Demand) 

The relative increase in the share for HVAC shell and equipment measures under the peak demand 

potential reflects the cooling savings from these measures. 

Potentially achievable residential sector benefits, from programmatic efforts from 2012 through 

2023, could range from $0.7 billion to $1.9 billion from a TRC perspective. Associated costs to 

ratepayers could range from $0.8 billion to $3.3 billion from the RIM perspective. 

Table 18 lists the net present value of participant and program costs associated with theoretically 

achievable potential scenarios. 

Table 19 lists benefits and costs from TRC, RIM, and PCT perspectives of theoretically achievable 

scenarios. 

Table 20, Table 21, and Table 22 list benefits and costs from TRC and RIM perspectives, by end use, 

for the scenarios. 

Table 23, Table 24, and Table 25 list benefits and costs from the PCT perspective by end use, with 

and without incentives, illustrating energy-efficiency measures’ economic attractiveness, even 

without utility incentives to subsidize initial measure costs. 

Appliances, 

12%

HVAC 

Equipment, 

23%

HVAC Shell, 

54%

Lighting, 5%

Water 

Heating, 2%

Plug Load, 0.2% Pool Pump, 

4%
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 41

Table 18. Participant and Program Costs by Achievable Potential Scenario for Residential Sector 

(NPV Thousands, Cumulative through 2023) 

Net Participant 

Costs Program Incentives 

Program 

Achievable Scenario Administration 

Low Incentive $561,553 $187,184 $188,984

Moderate Incentive $567,225 $567,225 $285,412

High Incentive $0 $1,883,187 $472,597

Table 19. Net Benefits and Benefit-to-Cost Ratio for TRC, RIM, and PCT Perspectives for Residential Sector 

(Cumulative NPV through 2023) 

TRC RIM PCT 

Achievable 

Scenario 

Net 

Benefits 

(Millions) 

Benefit/ 

Cost 

Net 

Benefits 

(Millions) 

Benefit/ 

Cost 

Net 

Benefits 

(Millions) 

Benefit/ 

Cost 

Low Incentive $744 1.8 -$755 0.5 $1,499 3.0

Moderate Incentive $1,125 1.8 -$1,425 0.5 $2,550 3.2

High Incentive $1,865 1.8 -$3,305 0.4 $5,171 3.7

Table 20. TRC and RIM Net Benefits and Benefit-to-Cost Ratio by End Use for Residential Sector 

(Low Incentive Scenario, Cumulative NPV through 2023) 

TRC RIM 

End Use 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Appliances $148 2.8 -$168 0.5

HVAC Equipment $72 1.7 -$116 0.5

HVAC Shell $426 1.7 -$286 0.5

Lighting $27 2.4 -$56 0.5

Plug Load $6 2.9 -$9 0.5

Pool Pump $13 3.6 -$9 0.7

Water Heating $51 1.4 -$111 0.5
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 42

Table 21. TRC and RIM Net Benefits and Benefit-to-Cost Ratio by End Use for Residential Sector 

(Moderate Incentive Scenario, Cumulative NPV through 2023) 

TRC RIM 

End Use 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Appliances $225 2.8 -$280 0.5

HVAC Equipment $108 1.6 -$208 0.5

HVAC Shell $646 1.7 -$614 0.4

Lighting $40 2.4 -$90 0.5

Plug Load $9 2.9 -$15 0.5

Pool Pump $20 3.6 -$16 0.6

Water Heating $77 1.4 -$203 0.5

Table 22. TRC and RIM Net Benefits and Benefit-to-Cost Ratio by End Use for Residential Sector 

(High Incentive Scenario, Cumulative NPV through 2023) 

TRC RIM 

End Use 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Appliances $373 2.8 -$548 0.4

HVAC Equipment $177 1.6 -$453 0.4

HVAC Shell $1,072 1.7 -$1,620 0.3

Lighting $67 2.4 -$170 0.4

Plug Load $15 2.9 -$28 0.5

Pool Pump $33 3.6 -$31 0.6

Water Heat $128 1.4 -$455 0.4

Table 23. PCT Net Benefits and Benefit-to-Cost Ratio by End Use for Residential Sector 

(Low Incentive Scenario, Cumulative NPV through 2023) 

PCT with Incentives PCT without Incentives 

End Use 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Appliances $316 5.7 $299 5.5

HVAC Equipment $188 3.1 $166 2.9

HVAC Shell $712 2.5 $592 2.2

Lighting $82 6.2 $78 6.0

Plug Load $15 7.0 $15 6.8

Pool Pump $23 6.6 $22 6.3

Water Heat $162 2.7 $138 2.5
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 43

Table 24. PCT Net Benefits and Benefit-to-Cost Ratio by End Use for Residential Sector 

(Moderate Incentive Scenario, Cumulative NPV through 2023) 

PCT with Incentives PCT without Incentives 

End Use 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Appliances $504 6.0 $453 5.5

HVAC Equipment $316 3.4 $249 2.9

HVAC Shell $1,260 2.7 $898 2.2

Lighting $131 6.5 $119 6.0

Plug Load $24 7.3 $22 6.8

Pool Pump $36 6.8 $33 6.3

Water Heat $280 3.0 $209 2.5

Table 25. PCT Net Benefits and Benefit-to-Cost Ratio by End Use for Residential Sector 

(High Incentive Scenario, Cumulative NPV through 2023) 

PCT with Incentives PCT without Incentives 

End Use 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

Appliances $921 6.5 $753 5.5

HVAC Equipment $630 3.9 $410 2.9

HVAC Shell $2,692 3.2 $1,490 2.2

Lighting $237 7.0 $197 6.0

Plug Load $43 7.8 $37 6.8

Pool Pump $65 7.3 $55 6.3

Water Heat $583 3.5 $346 2.5

 
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 44

3.3.4.2 Commercial Sector 

Table 26 presents commercial sector achievable potential for the three incentive scenarios. 

Table 26. Theoretically Achievable Potential Savings for Commercial Sector 

(Cumulative through 2023) 

Low Incentive 

Achievable Potential 

Moderate Incentive 

Achievable Potential 

High Incentive 

Achievable Potential 

Load Type 

Total 

Potential 

Percent of 

2023 Load 

Total 

Potential 

Percent of 

2023 Load 

Total 

Potential 

Percent of 

2023 Load 

Reduction in Electricity 

Sales (MWh) REDACTED 8.8% REDACTED 13.3% REDACTED 22.1% 

Reduction in Peak 

Demand (MW) REDACTED 10.6% REDACTED 16.1% REDACTED 26.7% 

Figure 27 and Figure 28 show commercial sector baseline and forecasts by achievable potential 

scenario, for energy sales and peak demand forecast, respectively. 

Figure 27. Energy Forecasts for Theoretically Achievable Potential in Commercial Sector (Electricity Sales) 

 

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

35,000,000

40,000,000

45,000,000

50,000,000

2012 2014 2016 2018 2020 2022

Electricity Sales (MWh)

Base Forecast

High Incentive

Moderate Incentive

Low Incentive

REDACTED
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 45

Figure 28. Demand Forecasts for Theoretically Achievable Potential in Commercial Sector (Peak Demand) 

Figure 29 and Figure 30 illustrates theoretically achievable commercial savings under the high 

incentive scenario by end use. Potential savings of electric energy concentrate in four end-use 

categories: lighting (49%); HVAC (shell and equipment at 35% of potential); and office equipment 

(10%). 

Figure 29. Commercial - 2023 Theoretically Achievable Potential by End Use (Electricity Sales) 

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

2012 2014 2016 2018 2020 2022

Peak Demand (MW)

Base Forecast

High Incentive

Moderate Incentive

Low Incentive

HVAC 

Equipment, 3%

HVAC Shell, 

32%

Lighting, 49%

Miscellaneous, 

3%

Office 

Equipment, 

10%

Refrigeration, 

2%

Water 

Heating, 2%

REDACTED
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 46

The potential peak demand savings concentrate much more in lighting (48% of potential) and HVAC 

(shell and equipment at 37%), with lesser amounts in office equipment (10%) and other end uses. 

Figure 30. Commercial - 2023 Theoretically Achievable Potential by End Use (Peak Demand) 

Potentially achievable benefits in the commercial sector, from programmatic efforts from 2012 

through 2023 could range from $1.5 billion to $3.7 billion from a TRC perspective. Associated costs 

to ratepayers could range from $0.9 billion to $3.4 billion from the RIM perspective. 

Table 27 lists the net present value of participant and programs costs associated with theoretically 

achievable potential scenarios. 

Table 28 lists the benefits and costs from TRC, RIM, and PCT perspectives of theoretically achievable 

scenarios. 

Table 29, Table 30, and Table 31 list benefits and costs from TRC and RIM perspectives, by end use, 

for the scenarios. 

Table 32, Table 33, and Table 34 list benefits and costs from the PCT perspective by end use, with 

and without incentives, illustrating energy-efficiency measures’ economic attractiveness, even 

without utility incentives to subsidize initial measure costs. 

HVAC 

Equipment, 8%

HVAC Shell, 

29%

Lighting, 48%

Miscellaneous, 

3%

Office 

Equipment, 

10%

Refrigeration, 

1%

Water 

Heating, 2%
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 47

Table 27. Participant and Program Costs by Achievable Potential Scenario for Commercial Sector 

(NPV Thousands, Cumulative through 2023) 

Achievable Scenario 

Net Participant 

Costs Program Incentives 

Program 

Administration 

Low Incentive $484,370 $161,457 $161,457

Moderate Incentive $489,263 $489,263 $244,631

High Incentive $0 $1,624,352 $406,088

Table 28. Net Benefits and Benefit-to-Cost Ratio for TRC, RIM, and PCT Perspectives for Commercial Sector 

(Cumulative NPV through 2023) 

Achievable 

Scenario 

TRC RIM PCT 

Net 

Benefits 

(Millions) 

Benefit/ 

Cost 

Net 

Benefits 

(Millions) 

Benefit/ 

Cost 

Net 

Benefits 

(Millions) 

Benefit/ 

Cost 

Low Incentive $1,471 2.8 -$867 0.7 $2,338 4.6

Moderate Incentive $2,228 2.8 -$1,559 0.7 $3,787 4.9

High Incentive $3,699 2.8 -$3,400 0.6 $7,099 5.4

Table 29. TRC and RIM Net Benefits and Benefit-to-Cost Ratio by End Use for Commercial Sector 

(Low Incentive Scenario, Cumulative NPV through 2023) 

End Use 

TRC RIM 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

HVAC Equipment $95 4.9 -$19 0.9

HVAC Shell $338 1.8 -$341 0.7

Lighting $755 3.8 -$368 0.7

Miscellaneous $165 3.8 -$56 0.6

Office Equipment $67 3.1 -$53 0.7

Refrigeration $23 7.8 -$10 0.7

Water Heat $28 3.2 -$20 0.6
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 48

Table 30. TRC and RIM Net Benefits and Benefit-to-Cost Ratio by End Use for Commercial Sector 

(Moderate Incentive Scenario, Cumulative NPV through 2023) 

End Use 

TRC RIM 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

HVAC Equipment $144 4.9 -$37 0.8

HVAC Shell $512 1.8 -$641 0.6

Lighting $1,143 3.8 -$638 0.7

Miscellaneous $250 3.8 -$103 0.5

Office Equipment $101 3.1 -$90 0.6

Refrigeration $35 7.8 -$16 0.7

Water Heat $43 3.2 -$34 0.6

Table 31. TRC and RIM Net Benefits and Benefit-to-Cost Ratio by End Use for Commercial Sector 

(High Incentive Scenario, Cumulative NPV through 2023) 

End Use 

TRC RIM 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

HVAC Equipment $240 4.9 -$85 0.8

HVAC Shell $849 1.8 -$1,476 0.5

Lighting $1,898 3.8 -$1,329 0.7

Miscellaneous $415 3.8 -$230 0.5

Office Equipment $168 3.1 -$182 0.6

Refrigeration $59 7.8 -$29 0.7

Water Heat $71 3.2 -$70 0.5

Table 32. PCT Net Benefits and Benefit-to-Cost Ratio by End Use for Commercial Sector 

(Low Incentive Scenario, Cumulative NPV through 2023) 

End Use 

PCT with Incentives PCT without Incentives 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

HVAC Equipment $114 6.8 $110 6.6

HVAC Shell $679 3.1 $597 2.8

Lighting $1,122 6.2 $1,069 6.0

Miscellaneous $221 5.7 $209 5.5

Office Equipment $120 5.8 $114 5.5

Refrigeration $33 12.9 $32 12.7

Water Heat $48 5.6 $46 5.4
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 49

Table 33. PCT Net Benefits and Benefit-to-Cost Ratio by End Use for Commercial Sector 

(Moderate Incentive Scenario, Cumulative NPV through 2023) 

End Use 

PCT with Incentives PCT without Incentives 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

HVAC Equipment $181 7.1 $166 6.6

HVAC Shell $1,153 3.3 $905 2.8

Lighting $1,781 6.5 $1,619 6.0

Miscellaneous $353 6.0 $317 5.5

Office Equipment $192 6.0 $173 5.5

Refrigeration $51 13.2 $49 12.7

Water Heat $77 5.9 $69 5.4

Table 34. PCT Net Benefits and Benefit-to-Cost Ratio by End Use for Commercial Sector 

(High Incentive Scenario, Cumulative NPV through 2023) 

End Use 

PCT with Incentives PCT without Incentives 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

HVAC Equipment $325 7.6 $275 6.6

HVAC Shell $2,325 3.8 $1,502 2.8

Lighting $3,226 7.0 $2,688 6.0

Miscellaneous $645 6.5 $527 5.5

Office Equipment $350 6.5 $286 5.5

Refrigeration $88 13.7 $81 12.7

Water Heat $141 6.4 $115 5.4

3.3.4.3 Industrial Sector 

Table 35 presents the industrial sector’s achievable potential for the three incentive scenarios. 

Table 35. Theoretically Achievable Potential Savings for Industrial Sector 

(Cumulative through 2023) 

Load Type 

Low Incentive 

Achievable Potential 

Moderate Incentive 

Achievable Potential 

High Incentive 

Achievable Potential 

Total 

Potential 

Percent of 

2023 Load 

Total 

Potential 

Percent of 

2023 Load 

Total 

Potential 

Percent of 

2023 Load 

Reduction in Electricity 

Sales (MWh) REDACTED 4.5% REDACTED 6.9% REDACTED 11.4% 

Reduction in Peak 

Demand (MW) REDACTED 4.9% REDACTED 7.4% REDACTED 12.2% 
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 50

Figure 31 and Figure 32 show industrial sector baseline and forecasts by achievable potential 

scenario, for energy sales and peak demand forecast, respectively. 

Figure 31. Energy Forecasts for Theoretically Achievable Potential in Industrial Sector (Electricity Sales) 

Figure 32. Demand Forecasts for Theoretically Achievable Potential in Industrial Sector (Peak Demand) 

 

Figure 33 illustrates theoretically achievable industrial energy savings under the high incentive 

scenario by end use. Potential electric energy savings concentrate in four end-use categories: 

process (46% of potential); motors (includes pumps and fans, 27%); HVAC (10%); and lighting (12%). 

Other end uses constitute the remaining savings. 

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

2012 2014 2016 2018 2020 2022

Electricity Sales (MWh)

Base Forecast

High Incentive

Moderate Incentive

Low Incentive

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

2012 2014 2016 2018 2020 2022

Peak Demand (MW)

Base Forecast

High Incentive

Moderate Incentive

Low Incentive

REDACTED

REDACTED
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 51

Figure 33. Industrial - 2023 Theoretically Achievable Potential by End Use (Electricity Savings) 

Figure 34 illustrates theoretically achievable industrial peak demand savings under the high 

incentive scenario by end use. The potential peak demand savings concentrate much more in the 

process (48% of potential) and motor (27%) end-use categories, with lesser amounts in other end 

uses. 

Figure 34. Industrial - 2023 Theoretically Achievable Potential by End Use (Peak Demand) 

HVAC 

Equipment, 

10%

Lighting, 12%

Other, 5%

Motors, 27%

Process, 46%

HVAC 

Equipment, 

11%

Lighting, 9%

Other, 5%

Motors, 27%

Process, 48%
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 52

Potentially achievable industrial sector benefits, from programmatic efforts from 2012 through 

2023, could range from $0.3 billion to $0.8 billion from a TRC perspective. Associated costs to 

ratepayers could range from $0.1 billion to $0.5 billion from the RIM perspective. 

Table 36 lists the net present value of participant and programs costs associated with theoretically 

achievable potential scenarios. 

Table 37 lists benefits and costs from TRC, RIM, and PCT perspectives of theoretically achievable 

scenarios. 

Table 38, Table 39, and Table 40 list benefits and costs from TRC and RIM perspectives, by end use, 

for the scenarios. 

Table 41, Table 42, and Table 43 lists benefits and costs from the PCT perspective by end use, with 

and without incentives, illustrating energy-efficiency measures’ economic attractiveness, even 

without utility incentives to subsidize initial measure costs. 

Table 36. Participant and Program Costs by Achievable Potential Scenario for Industrial Sector 

(NPV thousands, Cumulative through 2023) 

Achievable Scenario 

Net Participant 

Costs Program Incentives 

Program 

Administration 

Low Incentive $71,803 $23,934 $23,934

Moderate Incentive $72,528 $72,528 $36,264

High Incentive $0 $240,793 $60,198

Table 37. Net Benefits and Benefit-to-Cost Ratio for TRC, RIM, and PCT Perspectives for Industrial Sector 

(Cumulative NPV through 2023) 

Achievable 

Scenario 

TRC RIM PCT 

Net 

Benefits 

(Millions) 

Benefit/ 

Cost 

Net 

Benefits 

(Millions) 

Benefit/ 

Cost 

Net 

Benefits 

(Millions) 

Benefit/ 

Cost 

Low Incentive $336 3.8 -$110 0.8 $446 5.7

Moderate Incentive $509 3.8 -$203 0.8 $712 5.9

High Incentive $845 3.8 -$458 0.7 $1,303 6.4
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 53

Table 38. TRC and RIM Net Benefits and Benefit-to-Cost Ratio by End Use for Industrial Sector 

(Low Incentive Scenario, Cumulative NPV through 2023) 

End Use 

TRC RIM 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

HVAC Equipment $46 7.9 -$11 0.8

Lighting $47 4.3 -$7 0.9

Motors $81 2.6 -$43 0.8

Other $21 3.4 -$7 0.8

Process $140 4.7 -$42 0.8

Table 39. TRC and RIM Net Benefits and Benefit-to-Cost Ratio by End Use for Industrial Sector 

(Moderate Incentive Scenario, Cumulative NPV through 2023) 

End Use 

TRC RIM 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

HVAC Equipment $70 7.9 -$19 0.8

Lighting $72 4.3 -$15 0.9

Motors $123 2.6 -$81 0.7

Other $32 3.4 -$13 0.8

Process $213 4.7 -$75 0.8

Table 40. TRC and RIM Net Benefits and Benefit-to-Cost Ratio by End Use for Industrial Sector 

(High Incentive Scenario, Cumulative NPV through 2023) 

End Use 

TRC RIM 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

HVAC Equipment $116 7.9 -$39 0.8

Lighting $119 4.3 -$40 0.8

Motors $204 2.6 -$186 0.6

Other $53 3.4 -$31 0.7

Process $353 4.7 -$162 0.7
     

3 PUBLIC DISCLOSURE Estimates of Energy-Efficiency Potentials 

Achievable Energy-Efficiency Potentials Assessment 54

Table 41. PCT Net Benefits and Benefit-to-Cost Ratio by End Use for Industrial Sector 

(Low Incentive Scenario, Cumulative NPV through 2023) 

End Use 

PCT with Incentives PCT without Incentives

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

HVAC Equipment $58 11.7 $56 11.5

Lighting $54 5.7 $52 5.5

Motors $124 4.0 $114 3.7

Other $28 5.0 $26 4.8

Process $182 7.0 $175 6.8

Table 42. PCT Net Benefits and Benefit-to-Cost Ratio by End Use for Industrial Sector 

(Moderate Incentive Scenario, Cumulative NPV through 2023) 

End Use 

PCT with Incentives PCT without Incentives 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

HVAC Equipment $89 12.0 $85 11.5

Lighting $87 6.0 $78 5.5

Motors $204 4.2 $172 3.7

Other $45 5.3 $40 4.8

Process $287 7.3 $264 6.8

Table 43. PCT Net Benefits and Benefit-to-Cost Ratio by End Use for Industrial Sector 

(High Incentive Scenario, Cumulative NPV through 2023) 

End Use 

PCT with Incentives PCT without Incentives 

Net 

Benefits 

(Millions) Benefit/Cost 

Net 

Benefits 

(Millions) Benefit/Cost 

HVAC Equipment $155 12.5 $141 11.5

Lighting $159 6.5 $130 5.5

Motors $390 4.7 $286 3.7

Other $84 5.8 $66 4.8

Process $515 7.8 $439 6.8
PUBLIC DISCLOSURE 

Achievable Energy-Efficiency Potentials Assessment 55

4 CONCLUSIONS

This assessment identifies the potential for increased energy-efficiency investments by Georgia 

Power customers above the levels that would naturally occur but would require the significant 

incentives assumed in this analysis. These results will be useful in targeting energy-efficiency 

program planning efforts to areas with the highest market potential. 

Customers can reduce their energy consumption and peak power requirements by implementing 

energy-efficiency measures or actions, receiving economic benefits directly through reductions in 

their energy bills. Customers who participate could also benefit from financial incentives offered by 

programs intended to accelerate markets for purchase and installation of high-efficiency measures. 

At the same time, rates will rise for all customers. Non-participating customers will pay higher bills, 

in effect, subsidizing costs of incentives and other program costs, to the benefit of program 

participants. 

As in a similar 2007 assessment, this study examines scenarios of theoretically achievable energyefficiency potential associated with low incentives, moderate incentives, and high incentives. Each 

scenario in the study involves substantial expenditures on incentives, ranging from $25 million per 

year to more than $250 million per year in 2012, the study’s first year. 

Economic benefits from energy-efficiency improvements made by customers in Georgia Power’s 

service territory, as calculated by the TRC Test, could range as high as $2.6 billion to $6.4 billion. If 

implemented through electric utility programs, potential electric energy savings would range from 

6.0% of year 2023 forecast sales under a low incentive scenario to 15.1% under a high incentive 

scenario. However, these savings result in substantial costs to ratepayers. Net costs to electric utility 

ratepayers could range from $1.7 billion to $7.2 billion, over and above those costs associated with 

meeting customers’ energy and demand needs using supply-side options. Program costs alone could 

increase rates from $750 million to $4.7 billion. This study does not estimate costs to gas and water 

utility ratepayers, who could also experience adverse rate impacts. 

The study also demonstrates that customers can realize substantial benefits from increased energy 

efficiency, even without financial subsidies. Not including incentives, net participant benefits range

from $3.9 billion to $9.8 billion. For a variety of financial and structural reasons, however, customers 

may not make these energy-efficiency investments on their own. 
PUBLIC DISCLOSURE 

Achievable Energy-Efficiency Potentials Assessment A-1

Appendix A DETAILED METHODOLOGY

Energy-efficiency potentials can be determined through a sequential analysis of various energyefficiency measures in terms of technical feasibility (technical potential) and economic viability, 

based on standard cost-effectiveness criteria (economic potential) and market adoption criteria 

(achievable potential). This assessment follows two main steps: 

• Baseline forecasts determine future energy consumption by segment and end use, 

calibrated to the utility’s energy sales forecasts. Baseline forecasts reflect efficiency 

characteristics of current and pending codes and standards. 

• Estimation of forecasts based on technical, economic, and theoretically achievable 

potentials, reflect technical impacts of specific energy-efficiency measures, measures’ costeffectiveness, and market constraints, respectively. The difference in energy consumption 

between the baseline and individual, alternative forecasts represents the energy-efficiency 

potential. 

Figure A-1 illustrates these steps conceptually, showing a hypothetical baseline forecast, along with 

alternative forecasts associated with technical, economic, and achievable potential.7 These 

alternative forecasts represent consumption under different sets of assumptions, and the difference 

between the baseline and each alternative forecasts represents respective potential savings. For 

example, the technical potential forecast represents total consumption following incorporation of all 

measures, with total consumption for the technical potential forecast much lower than the baseline 

(which also indicates the greatest amount of potential). As respective benefit-cost and market 

acceptance constraints are added, forecasts for economic and achievable scenarios approach the 

baseline and the resulting potential savings decrease. 

This approach offers two advantages. First, it drives savings estimates by a baseline, calibrated to 

each utility’s energy sales forecasts and thus consistent with filings. The energy sales forecast serves 

as a “reality check,” helping control for possible errors. Other approaches simply may generate the 

total potential by summing estimated impacts of individual measures, resulting in total savings 

estimates representing unrealistically high percentages of baseline sales. 

Second, the approach maintains consistency among all assumptions underlying the baseline and 

theoretical forecasts. In the theoretical forecasts, relevant end-use level inputs change to reflect 

energy-efficiency measures’ impacts. As estimated savings represent the difference between the 

baseline and alternative forecasts, they can be directly attributed to specific changes made to 

analysis inputs. 

 

7 Figure A-1’s baseline and alternative forecasts serve purely as examples, and do not represent actual data 

underlying this assessment. 
  

  	  


A PUBLIC DISCLOSURE Detailed Methodology

Achievable Energy-Efficiency Potentials Assessment A-2

Figure A-1. Representation of an Alternative Forecast Approach for Estimating Energy-Efficiency Potentials 

 

A.1 DEVELOPING A BASELINE FORECAST 

Cadmus created the baseline forecast by combining all baseline data to obtain average consumption 

estimates by fuel, customer segment, construction vintage, and end use; this breakdown is summed 

up to the sector level. This method was then calibrated to Georgia Power’s B11 end-use forecast. 

This approach offered several key advantages: 

• Savings estimates were driven by a baseline, calibrated to official energy sales forecasts. 

This calibration required a great deal of scrutiny to ensure underlying inputs and 

assumptions remained consistent with known customer population characteristics. Other 

potentials study approaches could generate the total potentials by summing individual 

measures’ estimated impacts, resulting in total savings estimates representing unrealistically 

high baseline sales percentages. 

• The forecast incorporates the effects of known changes to equipment standards and 

naturally occurring efficiency improvements. Equipment standard changes and naturally 

occurring savings reduce energy use as customers retire lower-efficiency units and install 

higher-efficiency systems. Including these effects in the baseline forecast prevents from 

inflating potentials estimates. 
  

  	  


A PUBLIC DISCLOSURE Detailed Methodology

Achievable Energy-Efficiency Potentials Assessment A-3

• The same assumptions underlying baseline forecasts were used to develop energy-efficiency 

measure inputs, along with technical, economic, and achievable potential estimates, 

ensuring consistency across the study. 

A.1.1 Data Sources 

Creating a baseline forecast accurately reflecting Georgia Power’s customers’ consumption 

characteristics required many data inputs (Table A-1), including: 

• Energy sales and customer forecasts; 

• Customer counts by major customer segments (e.g., building type or industry); 

• End-use and equipment saturations, including fuel shares; 

• Efficiency shares (the percent of equipment below, at, and above code); and 

• Annual end-use consumption estimates, by efficiency level. 

Table A-1. Key Data Sources 

Data Source Key Variables 

Georgia Power B11 end-use consumption 

forecast 

Total electric sales by customer segment and end use, excluding 

energy-efficiency program activity. 

Georgia Power B11 customer forecast Number of customers by rate class, commercial square footage 

estimate. 

Georgia Power B11 saturations Residential and commercial equipment saturations. 

Residential and commercial saturation 

surveys 

Supplemental saturations and fuel share information. 

Manufacturing Energy Consumption 

Survey 

End-use breakout for industrial facilities 

EnerSim building simulations End-use equipment energy consumption estimate. 

A.2 COMPILING ENERGY-EFFICIENCY TECHNOLOGY DATA 

The Nexant/Cadmus team, along with input from members of the Demand Side Management 

Working Group (“DSMWG”), created a comprehensive catalog of energy-efficiency measures 

applicable to Georgia Power’s service territory, containing more than 332 unique measures. 

Expanding the measures to account for all appropriate combinations of segments, end uses, and 

construction types resulted in over 8,000 measure permutations, as shown in Table A-2. 
  

  	  


A PUBLIC DISCLOSURE Detailed Methodology

Achievable Energy-Efficiency Potentials Assessment A-4

Table A-2. Energy-Efficiency Measure Counts by Sector 

Sector Unique Measures Permutations 

Residential 118 1,703 

Commercial 144 5,485 

Industrial 70 822 

These measures required a number of inputs to accurately assess their potential and costeffectiveness, primarily using secondary local, regional, and national data, where appropriate. For 

example, the 2010 Georgia Power Residential Saturation Survey (“RSS”) provided inputs for the 

residential sector, and EIA’s Commercial Building Energy Consumption Survey (“CBECS”) provided 

inputs for the commercial sector. The industrial sector relied on EIA’s Manufacturing Energy 

Consumption Survey (“MECS”). Relevant inputs for each type of measure included the following: 

• End-use savings: Energy savings associated with a measure as a percentage of total end-use 

consumption, based primarily on EnerSim building simulation models for the residential and 

commercial sectors and the IAC database for the industrial sector. Calculating some building 

types’ measure energy savings by scaling simulated energy savings from a similar, proxy 

building type (e.g., manufactured home energy savings derived from a single-family home 

simulation) helped manage the number of building simulations required to estimate energy 

savings for each measure. 

• Measure costs: Per-unit costs (full or incremental, depending on the application) associated 

with measure installations. Sources included: RS Means, merchant Websites, and other 

secondary sources. As with energy savings, scaling costs from similar, proxy building types 

allowed measure costs to be calculated for some building types. 

• Measure life: A measure’s expected useful lifetime. Sources included the Database for 

Energy Efficient Resources (“DEER”), the American Society of Heating, Refrigerating and Air 

Conditioning Engineers (“ASHRAE”) Handbook, and other regional and national measure 

databases and energy-efficiency program evaluations. 

• Measure applicability: A general term encompassing an array of factors, including: fuel 

saturation, end-use saturation, technical feasibility of installation, and the measure’s current 

saturation as well as factors to allocate savings associated with competing measures. 

Information used primarily derived from data in current regional and national databases. 

These factors are described in Table A-3. 
  

  	  


A PUBLIC DISCLOSURE Detailed Methodology

Achievable Energy-Efficiency Potentials Assessment A-5

Table A-3. Measure Applicability Factors 

Measure 

Impact Explanation Sources 

End-Use 

Saturation 

The percentage of customers with the specific end use. (If not all 

commercial customers had a chiller unit, for example, end-use 

saturation would be less than 100%). 

RSS; CBECS; MECS; 

various secondary 

sources. 

Fuel Saturation Of customers with a given end use, the percentage using 

electricity to fuel a specific end use (e.g., water heat, space heat). 

RSS; CBECS; MECS; 

various secondary 

sources. 

Measure Share Used to distribute the percentage of market shares for competing 

measures (e.g., Cool Roofs and Green Roofs each have their own 

shares of the market), and to account for measure replacement at 

burnout or early replacement. 

Various secondary 

sources and engineering 

experience. 

Technical 

Feasibility 

Accounts for the percentage of buildings that can have the 

measure physically installed. Various factors may affect this 

percentage, including whether the building already has the 

baseline measure (e.g., dishwasher), and limitations on installation 

(e.g., size of unit and space available to install the unit). 

Various secondary 

sources and engineering 

experience. 

Measure 

Incomplete 

Factor 

Represents the percentage of buildings without the specific 

measure currently installed. 

RSS; CBECS; MECS; 

ENERGY STAR sales 

figures; and engineering 

experience. 

Measure 

Interaction 

Adjustment to measure savings due to interactions with other end 

uses. For example, increased lighting efficiency could increase 

space heating requirements. 

EnerSim modeling. 

A.3 ESTIMATING TECHNICAL POTENTIAL 

Once the measure database had been fully populated, Cadmus used measure-level inputs to 

estimate technical potential over the planning horizon. This required creating an alternate forecast, 

reducing consumption by installation of all technically feasible measures, and then subtracting this 

forecast from the baseline forecast to estimate technical potential by customer segment, vintage, 

end use, year, and measure. 

As noted, this approach ensured consistency with Georgia Power’s forecast, and ensured the 

technical potential accurately reflected Georgia Power’s customer characteristics, and represented a 

reasonable amount of projected sales. Further, the approach accounted for the following three 

interactive effects: 

• Equipment and non-equipment measures: Installing high-efficiency equipment, such as 

heat pumps, could reduce energy savings in absolute terms (kWh) associated with nonequipment measures, such as wall insulation. For example, installing a high-efficiency heat 

pump reducing heating and cooling consumption by 20% would reduce the baseline against 

which insulation would be applied, thus reducing savings associated with installing 

insulation. 
  

  	  


A PUBLIC DISCLOSURE Detailed Methodology

Achievable Energy-Efficiency Potentials Assessment A-6

• Non-equipment measure interactions: The “measure share”—as defined above—

accounted for competing measures, ensuring savings were not double-counted. This 

interaction occurred when two or more measures “competed” for the same end use. For 

example, a T-12 lamp could be replaced with a T-8 or T-5 lamp. 

• Inter-end-use interactions: Some measures could indirectly affect an end use. For example, 

installing more efficient lighting could increase heating loads. Where appropriate, the 

EnerSim simulation analysis captured these impacts.

Technical potential for equipment and non-equipment measures required different estimating 

techniques. For equipment measures, the study assumed consumers would install the most efficient 

unit available upon equipment burnout, generating savings over standard equipment. 

A.3.1 Non-Equipment Measures 

Estimating the potential for non-equipment (or “retrofit”) measures required assessing the 

collective impacts of many measures with interactive effects. For each segment and end-use 

combination, the analysis objective sought to estimate cumulative effects of the group of eligible 

measures, incorporating those impacts into the end-use model as a percentage adjustment to 

baseline end-use consumption. In other words, the approach estimated the percentage reduction in 

end-use consumption that could be saved in a “typical” structure (e.g., office buildings, retail 

building) by installing all available measures. This approach began by characterizing individual 

measure savings in terms of their percentage of end-use consumption, rather than their absolute 

energy savings. The following basic relationship estimated savings for each individual, nonequipment measure: 

SAVEijm = EUIije* PCTSAVijem* APPijem

where: 

SAVEijm = annual energy savings for measure m for end use j in customer segment i.

EUIije = calibrated annual end-use energy consumption for the equipment e for end use j and 

customer segment i. 

PCTSAVijem = the percentage savings of measure m relative to base usage for the equipment 

configuration ije, taking into account interactions among measures. 

APPijem = measure applicability, a fraction representing a combination of technical feasibility, 

existing measure saturation, end-use interaction, and adjustments to account for competing 

measures. 

A measure’s savings can be appropriately viewed in terms of its savings as a percentage of baseline 

end-use consumption, given its overall applicability. For example, if wall insulation had overall 

applicability of only 50%, 10% savings in space heating consumption would yield a final 5% savings 
  

  	  


A PUBLIC DISCLOSURE Detailed Methodology

Achievable Energy-Efficiency Potentials Assessment A-7

for this end use. This value would represent the percentage of baseline consumption the measure 

would save in an average commercial building. 

However, capturing all applicable measures required examining many instances where multiple 

measures affected a single end use. To avoid overestimating total savings, assessment of cumulative 

impacts accounted for interaction among various measures, a treatment known as “measure 

stacking.” Stacking effects can be accounted for primarily by establishing a rolling, reduced baseline, 

applied sequentially to measures in the stack, as shown in the equations below, which apply 

measures 1, 2, and 3 to the same end use: 

SAVEij1 = EUIije* PCTSAVije1*APPije1

SAVEij2 = (EUIije - SAVEij1) * PCTSAVije2 * APPije2

SAVEij3 = (EUIije - SAVEij1 - SAVEij2) * PCTSAVije3 * APPije3

Measures can be stacked using different criteria, such as total savings or cost-effectiveness. For this 

study, the TRC ratio determined the stacking order for measures within each end use. 

A.4 ESTIMATING ECONOMIC POTENTIAL 

Once the technical potential had been established, the economic (cost-effective) potential had to be 

determined. 

This study determined measure cost-effectiveness according to the TRC test, treating a measure’s 

benefits as the net present value of avoided utility costs, and costs incurred by the customer for 

installing the measure. If a measure had non-negative, net benefits, it could be considered costeffective. Expressed as an equation: 

1

TRC Costs

TRC Benefits ≥

Where: 





























= ∑ ∑ ×

=

measurelif e =

year

i

i

i i NPV impact avoided t

1

8760

TRC Benefits ( cos )

And: 

TRC Costs = Customer Cost 

TRC was calculated using estimated utility savings benefits (electric, gas, and water) and incremental

cost collected by Nexant/Cadmus. Hourly (electric) and monthly (gas and water) end-use loadshapes 

account for seasonal differences and system peak coincidence of different end uses. That is, a 

cooling measure using a greater amount of electric energy during peak periods would be more costeffective than a lighting measure with the same amount of savings, but lower peak coincidence. 
  

  	  


A PUBLIC DISCLOSURE Detailed Methodology

Achievable Energy-Efficiency Potentials Assessment A-8

A.4.1 Benefit Components 

Benefits used in the TRC calculation included the value of time-differentiated and seasonally 

differentiated electric avoided energy and capacity costs. 

A.4.2 Measure Cost Components 

The cost-benefit analysis’ cost component consisted of total installed measure costs and applicable 

operation and maintenance costs (or savings) associated with ensuring the measure is properly 

functioning over its expected life. Total measure benefits present values were calculated by 

discounting future streams at the designated discount rate. 

Upon screening all measures, impacts of measures deemed cost-effective to baseline consumption 

estimates could be applied, creating a separate forecast. Subtracting this new forecast from the 

baseline forecast provided the economic potential. 

A.4.3 Caveats 

Three important considerations should be noted in interpreting economic screening results, as they 

relate to assessment of energy-efficiency potentials: 

• As the analysis has been based on a societal perspective, assumptions have not been made 

regarding how measure costs split between utilities and participants in energy-efficiency 

programs. Achievable potential included that analysis level. This pure economic screen at 

the measure level did not assume program administration costs. 

• Screening procedure outcomes, described above, depended on assumptions that will likely 

change over time. Measure costs, for example, will likely decline over time, as demand for 

energy-efficient technologies increases. At the same time, costs of reaching each successive 

participant can often increase. Forecasted avoided costs will also likely change over time, 

and, as they change, so will the value of savings resulting from installation of energyefficient technologies (i.e., a measure failing the economic screen in earlier planning period 

years may become cost-effective in later years, if decrement values increase over the course 

of the planning horizon). 

• The economic analysis relied on assumptions intended to reflect an “average” or “typical” 

customer. Thus, while a measure may have passed the economic screen within the study’s 

context, the measure could fail the cost-effectiveness test in other instances. For example, a 

premium central air conditioner may be cost-effective in an average, single-family home, 

but, in a smaller home with less occupants, it could fail the economic screen due to 

decreased savings. 

Despite these caveats, the study’s underlying inputs, having been thoroughly reviewed, represent 

the best information available about specific conditions (regarding technical measure details and 

customer attributes) in Georgia at the time of the study. As with any study of this nature, as it 
  

  	  


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Achievable Energy-Efficiency Potentials Assessment A-9

becomes available, current information can be used to update key drivers, but the current study 

results sufficiently inform the resource planning and program delivery process. 

A.5 ESTIMATING ACHIEVABLE POTENTIAL 

In estimating long-run achievable potential, this study relied on secondary data to determine 

customers’ willingness to adopt energy-efficiency measures at a range of incentive levels, adopting a 

two-step approach: 

• Determining elasticity between incentive levels and savings from analysis of EIA Form 861 

data. These data included historical information on expenditures and savings from energyefficiency programs by utilities around the country. 

• Determining the base value by reviewing utility reports with available information on 

incentive levels and achievable percentages. 

Performing a regression analysis on EIA data allowed determination of the relative change in 

savings, based on differing incentives. Per these data, a 100% increase in the total utility incentive

equated to roughly a 65% increase in savings. Combined with findings from other publicly available 

assessments, this indicated roughly 50% of the economic potential can be achieved at an incentive 

level of 50% of incremental cost. This allows calculating the achievable percentage under the low 

and high scenarios, resulting in 34% of economic potential achievable at a 25% incentive (a low 

incentive scenario), and 83% of economic potential achievable at a 100% incentive (a high incentive 

scenario). Benchmarking these values against other potentials assessments ensured these estimates 

aligned with other jurisdictions. 

The above analysis provided an estimate for achievable potential at the end of the planning horizon. 

Resource acquisition, however, is measure specific, depending on product maturity. Wellestablished energy-efficiency measures (such as CFLs) experience fast ramp rates, while relatively 

new technologies (e.g., a variable refrigerant flow heat pump) will have a slow ramp rate. 

Annual utility and customer economic impacts were then estimated by applying the appropriate 

ramp rates for each measure, coupled with specific escalation rates on costs and discount rates. A 

single escalation rate was used to preserve the relative cost-effectiveness for both options, 

commonly done when conducting assessments of achievable potential. 

 
PUBLIC DISCLOSURE 

Achievable Energy-Efficiency Potentials Assessment B-1

Appendix B BENEFIT-COST ANALYSIS

When analyzing energy-efficiency measures, cost-effectiveness indicators are considered to account 

for perspectives of different stakeholders. The Participant Cost Test (“PCT”) addresses a participant 

perspective, which considers net benefits to those participating in an energy-efficiency program. The 

Total Resource Cost (“TRC”) addresses a societal perspective, which considers costs of an energyefficiency measure or program relative to the benefits of avoided utility supply costs. The Ratepayer 

Impact Measure (“RIM”) addresses an electric utility perspective, which considers the net impact on 

electric utility rates associated with a measure or energy-efficiency program. 

Descriptions follow of methods for allocating costs and benefits within each cost-effectiveness 

indicator (PCT, TRC, and RIM); the calculations remain consistent with the California Standard 

Practice Manual.8 

Table B-1. Components of Cost-Effectiveness Calculations 

Customer Incremental 

Costs 

All incremental costs incurred by the customer to purchase, install, and maintain an 

energy-efficiency measure 

Program Costs Administrative and marketing costs required to implement energy-efficiency programs 

Incentives Costs from the utility to the participant to encourage the purchase, installation, and 

maintenance of energy efficiency measures 

Table B-2. Participant Cost Test (PCT) 

Benefit Decrease in electric bill

Decrease in gas bill 

Decrease in water bill 

Customer incentives 

Cost Increase in electric bill

Increase in gas bill 

Increase in water bill 

Customer incremental costs (less any tax incentives) 

Table B-3. Total Resource Cost (TRC) 

Benefit Decrease in avoided electric utility supply costs

Decrease in avoided gas utility supply costs 

Decrease in avoided water utility supply costs 

Cost Increase in avoided electric utility supply costs

Increase in avoided gas utility supply costs 

Increase in avoided water utility supply costs 

Customer incremental costs (less any tax incentives) 

Program costs (excluding incentives) 

 

8 California Standard Practice Manual: Economic Analysis of Demand-Side Program and Projects. California Public 

Utilities Commission. San Francisco, CA. October 2001. 
  

  	  


B PUBLIC DISCLOSURE Benefit-Cost Analysis

Achievable Energy-Efficiency Potentials Assessment B-2

Table B-4. Ratepayer Impact Measure (RIM) 

Benefit Increase in electric revenues

Decrease in avoided electric utility supply costs 

Cost Decrease in electric revenues

Increase in avoided electric utility supply costs 

Program costs (including incentives) 
The Power of Experience 

Nexant, Inc.

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Cary, NC 27518-8119 USA 

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