Assessment of energy efficiency potential in Georgia : final report

Georgia Environmental Facilities Authority
Assessment of Energy Efficiency Potential in Georgia
Final Report
May 5, 2005
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Georgia Environmental Facilities Authority
Assessment of Energy Efficiency Potential in Georgia
Final Report
May 5, 2005
Prepared for: Division of Energy Resources Georgia Environmental Facilities Authority 2090 Equitable Building 100 Peachtree Street, NW Atlanta, Georgia 30303
Prepared by: Val Jensen and Eric Lounsbury ICF Consulting 60 Broadway San Francisco, CA 94111 (415) 677-7100
This publication was prepared with the support of the Georgia Environmental Facilities Authority (GEFA) under U.S. Department of Energy Grant Number DE-FG44-00R410761. However, any opinions, findings, conclusions, or recommendations expressed herein are those of the author(s) and do not necessarily reflect the views of GEFA. Reference to any trade names, manufacturer, specific commercial products, process, or service is for information or example only and does not constitute an endorsement or recommendation for use. Neither GEFA, ICF Consulting, nor any of their employees, nor any of their contractors or subcontractors, nor any technical sources referenced in this report makes any warranty or representation, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed or represents that its use would not infringe on privately owned rights.
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Table of Contents

Table of Contents
1. Executive Summary ............................................................................................................. 1-1
1.1. Introduction ................................................................................................................................ 1-1 1.2. Overall Structure of the Assessment .......................................................................................... 1-1 1.3. Energy Efficiency Potential Defined ........................................................................................... 1-2 1.4. Energy Efficiency Potential Results............................................................................................ 1-3
1.4.1. Achievable Potential by Sector.......................................................................................................... 1-5 1.4.2. Achievable Potential by End Use...................................................................................................... 1-6 1.4.3. Achievable Potential Cost-Effectiveness........................................................................................ 1-7 1.4.4. Power Sector Impacts........................................................................................................................... 1-8 1.4.5. Public Benefits of Energy Efficiency .............................................................................................. 1-10
2. Introduction and Approach ................................................................................................. 2-1
2.1. Introduction ................................................................................................................................ 2-1 2.1.1. Background .............................................................................................................................................. 2-1 2.1.2. Objectives ................................................................................................................................................. 2-1
2.2. Approach.................................................................................................................................... 2-2 2.2.1. Data Collection........................................................................................................................................ 2-5 2.2.2. Estimate Achievable Energy Efficiency Potential and Related Impacts .............................. 2-8 2.2.3. Estimate Public Benefits of Energy Efficiency............................................................................ 2-15 2.2.4. Review Public Policy Options........................................................................................................... 2-16
2.3. Caveats .................................................................................................................................... 2-16
3. Estimates of Energy Efficiency Potential........................................................................... 3-1
3.1. Introduction ................................................................................................................................ 3-1 3.2. Technical and Economic Potential ............................................................................................. 3-2
3.2.1. Technical and Economic Potential by Sector ............................................................................... 3-3 3.3. Achievable Potential................................................................................................................... 3-5
3.3.1. Achievable Potential by Sector.......................................................................................................... 3-7 3.3.2. Achievable Potential by End Use...................................................................................................... 3-8 3.3.3. Achievable Potential Cost-Effectiveness...................................................................................... 3-12 3.3.4. Achievable Potential in Depth .......................................................................................................... 3-21
4. Power Sector Impacts .......................................................................................................... 4-1
4.1. Impacts on Generation, Emissions, and Capacity...................................................................... 4-1 4.1.1. Overview ................................................................................................................................................... 4-1 4.1.2. Generation and Emissions Impacts by State................................................................................ 4-5
4.2. Impacts on Prices and Compliance Costs.................................................................................. 4-8 4.3. Alternative "Risk Management" Analyses Reflecting Price of Emissions ................................. 4-10
4.3.1. Introduction............................................................................................................................................. 4-10 4.3.2. Wholesale Price Impacts ................................................................................................................... 4-12 4.3.3. Energy Efficiency Potential Impacts............................................................................................... 4-13

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5. The Public Benefits of Energy Efficiency .......................................................................... 5-1
5.1. Public Health Impacts................................................................................................................. 5-1 5.1.1. Introduction............................................................................................................................................... 5-1 5.1.2. Emissions Impacts in Context............................................................................................................ 5-2
5.2. Impacts on Water Consumption ................................................................................................. 5-3 5.3. Economic Development Impacts................................................................................................ 5-4
5.3.1. Introduction............................................................................................................................................... 5-4 5.3.2. Results ....................................................................................................................................................... 5-5 5.3.3. Summary of Economic Impact Analyses from Other States & Regions .............................. 5-8
6. Conclusions .......................................................................................................................... 6-1
6.1. An Untapped Resource .............................................................................................................. 6-1 6.2. Challenges ................................................................................................................................. 6-1
List of Figures
Figure 1. Achievable Potential (Electricity Sales) ............................................................................................................................................................................... 1-4 Figure 2. Achievable Potential (Peak Demand) ................................................................................................................................................................................. 1-4 Figure 3. Achievable Potential (Gas Sales)........................................................................................................................................................................................ 1-4 Figure 4. 2010 Achievable Potential by Sector (Electricity Sales) ...................................................................................................................................................... 1-5 Figure 5. 2010 Achievable Potential by Sector (Peak Demand) ........................................................................................................................................................ 1-5 Figure 6. 2010 Achievable Potential by Sector (Gas Sales)............................................................................................................................................................... 1-5 Figure 7. 2010 Achievable Potential by End Use (Electricity Sales)................................................................................................................................................... 1-6 Figure 8. 2010 Achievable Potential by End Use (Peak Demand) ..................................................................................................................................................... 1-6 Figure 9. 2010 Achievable Potential by End Use (Gas Sales) ........................................................................................................................................................... 1-6 Figure 10. TRC Benefits and Costs for Achievable Potential Scenarios ............................................................................................................................................ 1-7 Figure 11. 2015 Employment Impacts from Achievable Potential Scenarios ................................................................................................................................... 1-13 Figure 12. 2015 Personal Income Impacts from Achievable Potential Scenarios ............................................................................................................................ 1-13 Figure 13. Overall Structure of the Assessment................................................................................................................................................................................. 2-4 Figure 14. Georgia Climate Zones ..................................................................................................................................................................................................... 2-7 Figure 15. Establishing the Market Baseline ...................................................................................................................................................................................... 2-9 Figure 16. Projected Market Adoption Curves Under a Range of Scenarios ................................................................................................................................... 2-10 Figure 17. Hourly Savings for 2010 Moderately Aggressive Scenario ............................................................................................................................................. 2-13 Figure 18. Technical & Economic Potential by Sector (Electricity Sales) ........................................................................................................................................... 3-3 Figure 19. Technical & Economic Potential by Sector (Peak Demand).............................................................................................................................................. 3-3 Figure 20. Technical & Economic Potential by Sector (Gas Sales).................................................................................................................................................... 3-3 Figure 21. Achievable Potential (Electricity Sales) ............................................................................................................................................................................. 3-6 Figure 22. Achievable Potential (Peak Demand) ............................................................................................................................................................................... 3-6 Figure 23. Achievable Potential (Gas Sales)...................................................................................................................................................................................... 3-6 Figure 24. 2010 Achievable Potential by Sector (Electricity Sales) .................................................................................................................................................... 3-7 Figure 25. 2010 Achievable Potential by Sector (Peak Demand) ...................................................................................................................................................... 3-7 Figure 26. 2010 Achievable Potential by Sector (Gas Sales)............................................................................................................................................................. 3-7

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Figure 27. 2010 Achievable Potential by End Use (Electricity Sales)................................................................................................................................................. 3-8 Figure 28. 2010 Achievable Potential by End Use (Peak Demand) ................................................................................................................................................... 3-8 Figure 29. 2010 Achievable Potential by End Use (Gas Sales) ......................................................................................................................................................... 3-8 Figure 30. 2010 Achievable Potential by Sector and End Use (Electricity Sales) .............................................................................................................................. 3-9 Figure 31. 2010 Achievable Potential by Sector and End Use (Peak Demand)............................................................................................................................... 3-10 Figure 32. 2010 Achievable Potential by Sector and End Use (Gas Sales) ..................................................................................................................................... 3-11 Figure 33. TRC Benefits and Costs for Achievable Potential Scenarios .......................................................................................................................................... 3-13 Figure 34. PCT Benefits and Costs for Achievable Potential Scenarios .......................................................................................................................................... 3-14 Figure 35. UCT Benefits and Costs for Achievable Potential Scenarios .......................................................................................................................................... 3-15 Figure 36. RIM Benefits and Costs for Achievable Potential Scenarios ........................................................................................................................................... 3-16 Figure 37. Residential Achievable Potential (Electricity Sales) ........................................................................................................................................................ 3-24 Figure 38. Residential Achievable Potential (Peak Demand) ........................................................................................................................................................... 3-24 Figure 39. Residential Achievable Potential (Gas Sales) ................................................................................................................................................................. 3-24 Figure 40. Residential Potential by End Use (Electricity Sales) ....................................................................................................................................................... 3-25 Figure 41. Residential Potential by End Use (Peak Demand) .......................................................................................................................................................... 3-25 Figure 42. Residential Potential by End Use (Gas Sales) ................................................................................................................................................................ 3-25 Figure 43. Commercial Achievable Potential (Electricity Sales) ....................................................................................................................................................... 3-31 Figure 44. Commercial Achievable Potential (Peak Demand) ......................................................................................................................................................... 3-31 Figure 45. Commercial Achievable Potential (Gas Sales)................................................................................................................................................................ 3-31 Figure 46. Commercial Potential by End Use (Electricity Sales) ...................................................................................................................................................... 3-32 Figure 47. Commercial Potential by End Use (Peak Demand) ........................................................................................................................................................ 3-32 Figure 48. Commercial Potential by End Use (Gas Sales)............................................................................................................................................................... 3-32 Figure 49. Commercial Potential by Building Type (Electricity Sales) .............................................................................................................................................. 3-33 Figure 50. Commercial Potential by Building Type (Peak Demand)................................................................................................................................................. 3-33 Figure 51. Commercial Potential by Building Type (Gas Sales)....................................................................................................................................................... 3-33 Figure 52. Industrial Achievable Potential (Electricity Sales) ........................................................................................................................................................... 3-40 Figure 53. Industrial Achievable Potential (Peak Demand) .............................................................................................................................................................. 3-40 Figure 54. Industrial Achievable Potential (Gas Sales) .................................................................................................................................................................... 3-40 Figure 55. Industrial Potential by End Use (Electricity Sales) .......................................................................................................................................................... 3-41 Figure 56. Industrial Potential by End Use (Peak Demand) ............................................................................................................................................................. 3-41 Figure 57. Industrial Potential by End Use (Gas Sales) ................................................................................................................................................................... 3-41 Figure 58. Industrial Potential by NAICS Code (Electricity Sales).................................................................................................................................................... 3-42 Figure 59. Industrial Potential by NAICS Code (Peak Demand) ...................................................................................................................................................... 3-42 Figure 60. Industrial Potential by NAICS Code (Gas Sales) ............................................................................................................................................................ 3-42 Figure 61. Changes in 2010 and 2015 Generation by State .............................................................................................................................................................. 4-6 Figure 62. Changes in 2010 and 2015 CO2 Emissions by State ........................................................................................................................................................ 4-6 Figure 63. Changes in 2010 and 2015 SO2 Emissions by State ........................................................................................................................................................ 4-7 Figure 64. Changes in 2010 and 2015 NOx Emissions by State ........................................................................................................................................................ 4-7 Figure 65. Range of Achievable Potential Outcomes for Emissions Control Scenarios (Electricity Sales) ...................................................................................... 4-13 Figure 66. Range of Achievable Potential Outcomes for Emissions Control Scenarios (Peak Demand) ......................................................................................... 4-13 Figure 67. Impacts on Net Annual Employment Relative to Base Case Forecast (Average of All Funding Scenarios) ..................................................................... 5-6

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List of Tables
Table 1. 2010 Achievable Potential--Total Potential and Percent of 2010 Load ............................................................................................................................... 1-3 Table 2. TRC Explained & TRC Net Benefits and Benefit-Cost Ratios .............................................................................................................................................. 1-7 Table 3. Total 2015 Southern Region Capacity Reductions Resulting from Achievable Potential Scenarios .................................................................................... 1-8 Table 4. Generation Reductions from Achievable Potential Scenarios--GWh in Georgia, National GWh, and Percent of National GWh in Georgia....................... 1-9 Table 5. 2010 Generation and Emissions Reductions Within Georgia from Achievable Potential Scenarios--Total and Percent of State Power Sector ................. 1-9 Table 6. Changes in Southern Region Electricity Wholesale Prices from Achievable Potential Scenarios ........................................................................................ 1-9 Table 7. Changes in Georgia Electricity and Gas Average Revenue (LRIRIM)--Total One-Time Increase and Percent of Estimated 2005 Average Revenue ....... 1-10 Table 8. Reductions in Power Sector and End Use Water Consumption in Georgia ....................................................................................................................... 1-11 Table 9. Changes in Power Sector Water Withdrawals and Consumption in Georgia and Total Southern Region ......................................................................... 1-12 Table 10. ICF Consulting Demand-Side and Supply-Side Modeling Tools ........................................................................................................................................ 2-3 Table 11. Technical and Economic Potential--Total Potential and Percent of 2004 Load................................................................................................................. 3-2 Table 12. Technical and Economic Potential by Sector--Total Potential and Percent of 2004 Load................................................................................................. 3-4 Table 13. 2010 Achievable Potential--Total Potential and Percent of 2010 Load ............................................................................................................................. 3-5 Table 14. Net Present Value (Thousands) of Participant, Program Incentive, and Program Administrative Costs .......................................................................... 3-12 Table 15. Total Resource Cost Test (TRC) Explained ..................................................................................................................................................................... 3-13 Table 16. Participant Cost Test (PCT) Explained............................................................................................................................................................................. 3-14 Table 17. Utility Cost Test (UCT) Explained..................................................................................................................................................................................... 3-15 Table 18. Ratepayer Impact Measure (RIM) Explained ................................................................................................................................................................... 3-16 Table 19. Net Benefits (Billions) and Benefit-Cost Ratios for Achievable Potential Scenarios......................................................................................................... 3-17 Table 20. Net Benefits (Millions) and Benefit-Cost Ratios for Achievable Potential by Sector and End Use (Minimally Aggressive) .............................................. 3-18 Table 21. Net Benefits (Millions) and Benefit-Cost Ratios for Achievable Potential by Sector and End Use (Moderately Aggressive)............................................ 3-19 Table 22. Net Benefits (Millions) and Benefit-Cost Ratios for Achievable Potential by Sector and End Use (Very Aggressive) ...................................................... 3-20 Table 23. 2010 Achievable Potential by Sector--Total Potential and Percent of 2010 Load ........................................................................................................... 3-21 Table 24. 2010 Residential Achievable Potential--Total Potential and Percent of 2010 Load......................................................................................................... 3-22 Table 25. Net Present Value (Thousands) of Participant, Program Incentive, and Program Administrative Costs (Residential) ..................................................... 3-26 Table 26. Net Benefits (Billions) and Benefit-Cost Ratios for Residential Sector Achievable Potential Scenarios ........................................................................... 3-26 Table 27. Net Benefits (Millions) and Benefit-Cost Ratios for Residential Achievable Potential by End Use (Minimally Aggressive Scenario) ............................... 3-27 Table 28. Net Benefits (Millions) and Benefit-Cost Ratios for Residential Achievable Potential by End Use (Moderately Aggressive Scenario) ............................ 3-27 Table 29. Net Benefits (Millions) and Benefit-Cost Ratios for Residential Achievable Potential by End Use (Very Aggressive Scenario)....................................... 3-28 Table 30. 2010 Commercial Achievable Potential--Total Potential and Percent of 2010 Load ....................................................................................................... 3-29 Table 31. Net Present Value (Thousands) of Participant, Program Incentive, and Program Administrative Costs (Commercial).................................................... 3-34 Table 32. Net Benefits (Billions) and Benefit-Cost Ratios for Commercial Sector Achievable Potential Scenarios ......................................................................... 3-34 Table 33. Net Benefits (Millions) and Benefit-Cost Ratios for Commercial Achievable Potential by End Use (Minimally Aggressive Scenario).............................. 3-35 Table 34. Net Benefits (Millions) and Benefit-Cost Ratios for Commercial Achievable Potential by End Use (Moderately Aggressive Scenario) ........................... 3-36 Table 35. Net Benefits (Millions) and Benefit-Cost Ratios for Commercial Achievable Potential by End Use (Very Aggressive Scenario) ..................................... 3-37 Table 36. 2010 Industrial Achievable Potential--Total Potential and Percent of 2010 Load............................................................................................................ 3-38 Table 37. Net Present Value (Thousands) of Participant, Program Incentive, and Program Administrative Costs (Industrial) ........................................................ 3-43 Table 38. Net Benefits (Billions) and Benefit-Cost Ratios for Industrial Sector Achievable Potential Scenarios .............................................................................. 3-43 Table 39. Net Benefits (Millions) and Benefit-Cost Ratios for Industrial Achievable Potential by End Use (Minimally Aggressive Scenario) .................................. 3-44 Table 40. Net Benefits (Millions) and Benefit-Cost Ratios for Industrial Achievable Potential by End Use (Moderately Aggressive Scenario) ............................... 3-44 Table 41. Net Benefits (Millions) and Benefit-Cost Ratios for Industrial Achievable Potential by End Use (Very Aggressive Scenario).......................................... 3-45

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Table 42. Total 2015 Southern Region Capacity Reductions Resulting from Achievable Potential Scenarios .................................................................................. 4-1 Table 43. Generation Reductions from Achievable Potential Scenarios--GWh in Georgia, National GWh, and Percent of National GWh in Georgia ..................... 4-2 Table 44. 2010 Generation and Emissions Reductions Within Georgia from Achievable Potential Scenarios--Total and Percent of State Power Sector ............... 4-2 Table 45. 2010 Generation and Emissions Reductions Within Southern Region from Achievable Potential Scenarios--Total and Percent of Regional
Power Sector ................................................................................................................................................................................................................ 4-2 Table 46. 2010 Generation and Emissions Reductions Within Georgia from Achievable Potential by Fuel Type (Minimally Aggressive)......................................... 4-3 Table 47. 2010 Generation and Emissions Reductions Within Georgia from Achievable Potential by Fuel Type (Moderately Aggressive) ...................................... 4-3 Table 48. 2010 Generation and Emissions Reductions Within Georgia from Achievable Potential by Fuel Type (Very Aggressive) ................................................ 4-4 Table 49. Changes in Southern Region Electricity Wholesale Prices from Achievable Potential Scenarios ...................................................................................... 4-8 Table 50. Changes in Georgia Electricity and Gas Average Revenue (LRIRIM)--Total One-Time Increase and Percent of Estimated 2005 Average
Revenue ....................................................................................................................................................................................................................... 4-8 Table 51. Estimated Changes in Allowances Prices Due to Achievable Potential Scenarios ............................................................................................................ 4-9 Table 52. Percentage Change in 2010 and 2015 Southern Region Wholesale Power Prices for Emissions Control Scenarios Relative to Base Case ................. 4-12 Table 53. Percentage Increases in 2010 and 2015 Achievable Potential for Emissions Control Scenarios Relative to Base Case ................................................ 4-14 Table 54. 2010 Emissions Reductions for CAIR and Very Aggressive Scenario (Thousand Tons) ................................................................................................... 5-2 Table 55. Reductions in Power Sector and End Use Water Consumption in Georgia ....................................................................................................................... 5-3 Table 56. Changes in Power Sector Water Withdrawals and Consumption in Georgia and Total Southern Region ......................................................................... 5-4 Table 57. Economic Development Impacts (Average of All Funding Scenarios) ............................................................................................................................... 5-7 Table 58. Comparison of Economic Development Impacts Results for Several Recent Energy Efficiency Potential Studies............................................................ 5-8

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Executive Summary

1. Executive Summary
1.1. Introduction
In recent decades, many energy utilities and public agencies have made strong and sustained efforts to promote energy efficiency through programs and standards. These efforts have brought significant economic benefits to energy customers and have contributed to ongoing initiatives to enhance the environment and improve public health nationwide.
However, the state of Georgia has not invested in energy efficiency as vigorously as most other states. In fact, Georgia is one of a small number of states in which energy efficiency programs are barely in evidence.
For this reason, there is now great opportunity to seize energy efficiency as a large untapped source of economic and environmental benefits for the state of Georgia. Building upon the successes and failures of a wide range of other energy efficiency efforts, Georgia is in an excellent position to stimulate greater investment in energy efficiency.
In order to quantify the benefits that such investment might have, the Georgia Environmental Facilities Authority (GEFA) retained ICF Consulting to evaluate Georgia's potential for cost-effective and achievable energy efficiency in the residential, commercial, and industrial sectors. This report summarizes the results of that study and seeks to answer several core questions:
How much cost-effective energy efficiency is available to be tapped in Georgia?
What impacts would the capture of this energy efficiency have?
How could state policymakers prudently act in order to realize these energy efficiency improvements?
1.2. Overall Structure of the Assessment
The project was structured in four substantive tasks. See Section 2.2 for a full description of the project approach.
Collect Data--Data characterizing Georgia electricity and gas load, wholesale and retail costs of energy, and end use efficiency technologies were collected to develop a detailed end use profile of energy use in Georgia.
Estimate Achievable Energy Efficiency Potential and Related Impacts--ICF then used its Energy Efficiency Potential Model (EEPM) to estimate Georgia's technically feasible, economically viable, and realistically achievable potential for energy efficiency.
Estimate Public Benefits of Energy Efficiency--Next, ICF employed its Integrated Planning Model (IPM) to assess the direct impacts of this energy efficiency potential on generation, generating capacity, and wholesale electricity prices. ICF also estimated the projected potential's effects on pollutant emissions, public health, water consumption, and economic development.

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Executive Summary
Review Public Policy Options--Finally, ICF reviewed an array of state public policies for their likely efficacy and cost-effectiveness in capturing untapped achievable energy efficiency potential in Georgia. The results of this policy review are summarized in a complementary document--Strategies for Capturing Georgia's Energy Efficiency Potential.
1.3. Energy Efficiency Potential Defined
Energy efficiency potential may be expressed in several ways: Technical Potential--Technical potential is a quantification of the savings that could be realized if energy efficiency measures were applied in all technically feasible instances, regardless of cost. Economic Potential--Economic potential is the subset of technical potential that is cost-effective. Achievable Potential--Achievable potential represents energy savings that can be realistically achieved through program and policy interventions. In order to estimate achievable potential, it is necessary to consider not only what is technically and economically feasible, but the extent to which policy interventions could increase the adoption of energy efficiency technologies. Two concepts are important in order to put estimates of achievable potential in the proper context: Naturally Occurring Conservation--Due to improvements in efficiency standards, natural market adoption of efficiency equipment, and existing program intervention, some amount of conservation will occur without any additional policy intervention. Energy Efficiency Policy Target--The energy efficiency policy target represents the achievable potential that exists above and beyond naturally occurring conservation. All estimates of achievable potential in this report are expressed as energy efficiency policy targets-- achievable potential less naturally occurring conservation.

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Executive Summary

1.4. Energy Efficiency Potential Results
The results presented in this report are our projections of current technical and economic potential and of achievable potential for the 2005-2015 period. See Section 3 for a complete presentation of the results.
By 2010, we project achievable potential of between 2.3% and 8.7% of electricity sales, 1.7% and 6.1% of electricity peak demand, and 1.8% and 5.5% of natural gas sales (See Table 1). The actual achieved savings within these ranges will depend on the intensity of policy intervention. Three intervention scenarios have been modeled: Minimally Aggressive, Moderately Aggressive, and Very Aggressive.
The figures on the next page show our projections of achievable potential in the context of Georgia baseline energy forecasts. For the Minimally, Moderately, and Very Aggressive scenarios, we have plotted revised forecasts that reflect the impacts of energy efficiency policy interventions.

Table 1. 2010 Achievable Potential--Total Potential and Percent of 2010 Load

Load Type Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf)

Minimally Aggressive

3,338,924

2.3%

447

1.7%

7,041

1.8%

Moderately Aggressive

8,704,577

6.0%

1,149

4.4%

16,972

4.4%

Very Aggressive

12,546,554

8.7%

1,608

6.1%

21,343

5.5%

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Executive Summary

Electricity Sales (MWh)

Figure 1. Achievable Potential (Electricity Sales)

180,000,000

160,000,000

140,000,000

120,000,000 100,000,000
80,000,000 60,000,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

40,000,000

20,000,000

0 2002

2004

2006

2008

2010

2012

2014

2016

Peak Demand (MW)

Figure 2. Achievable Potential (Peak Demand)
35,000

30,000

25,000 20,000 15,000 10,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

5,000

0 2002

2004

2006

2008

2010

2012

2014

2016

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Natural Gas Sales (MMcf)

Figure 3. Achievable Potential (Gas Sales)

450,000

400,000

350,000

300,000 250,000 200,000 150,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

100,000

50,000

0 2002

2004

2006

2008

2010

2012

2014

2016

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Executive Summary
1.4.1. Achievable Potential by Sector
Achievable potential is relatively evenly distributed across the residential, commercial, and industrial sectors, though there are a few important observations about the relative importance of the sectors to total potential (See figures below). Residential sector potential is significant in electricity and gas sales savings, but nonresidential sectors dominate peak demand potential. The commercial sector plays the largest role in electricity sales and peak demand potential, but the smallest role in gas sales potential. Industrial sector potential is most pronounced for gas sales.

Figure 4. 2010 Achievable Potential by Sector (Electricity Sales)

Figure 5. 2010 Achievable Potential by Sector (Peak Demand)

Figure 6. 2010 Achievable Potential by Sector (Gas Sales)

Industrial 24%

Residential 33%

Industrial 29%

Residential 24%

Industrial 36%

Residential 35%

Commercial 43%

Commercial 47%

Commercial 29%

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Executive Summary
1.4.2. Achievable Potential by End Use
A handful of end uses make up the majority of total potential. Please note that industrial heating, ventilation, and air conditioning end uses are combined and included in the space heat end use in the figures below. Electricity Sales--Lighting comprises the largest share of electricity sales savings potential, making up 43% of total savings. Air conditioning is the next most significant end use with a 13% share. Commercial office equipment (12%) and a combination of all industrial process end uses (19%) also contribute substantially to total potential (See Figure 7). Peak Demand--Air conditioning makes up 37% of total peak demand savings, reflecting the significance of cooling loads at the time of the electricity grid's summer peak. Lighting accounts for an additional 28% of potential, though because of residential lighting usage patterns, most of this savings is found in the nonresidential sectors. Industrial process end uses (21%) are also significant sources of peak savings (See Figure 8). Gas Sales--Space heat, industrial processes, and domestic hot water make up 44%, 32%, and 24% of gas savings potential, respectively, with minor savings in other end uses (See Figure 9).

Figure 7. 2010 Achievable Potential by End Use (Electricity Sales)

Industrial Process
19%
Office Equipment
12%

Space Heat 7% Ventilation 1%
Air Conditioning
13%

Appliances 0.04%

Hot Water 4% Refrigeration 1%

Lighting 43%

Figure 8. 2010 Achievable Potential by End Use (Peak Demand)

Office Equipment
4%

Industrial Process
21%

Industrial HVAC 6%
Ventilation 1%

Appliances 0.04%

Hot Water 2%
Refrigeration 1%

Lighting 28%

Air Conditioning
37%

Figure 9. 2010 Achievable Potential by End Use (Gas Sales)

Industrial Process
32%
Appliances 0.01%
Hot Water 24%

Space Heat 44%
Air Conditioning
0.1%

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Executive Summary

1.4.3. Achievable Potential Cost-Effectiveness
The achievable energy efficiency potential identified in this study has significant direct net economic benefits for the state of Georgia. From a "Total Resource Cost" or TRC perspective, the total net benefits to the state from energy efficiency improvements implemented from
2005-2015 in each of the policy intervention scenarios are between $0.9 billion and $1.6 billion in net present value dollars.
The benefit-cost ratios for the three intervention scenarios are between 1.5 and 2.2. Benefits and costs are measured in the following way from a TRC perspective:
Benefits are measured as the reductions in costs utilities experience as a result of reduced demand for electricity or gas. Costs include all costs incurred in order to purchase, install, and maintain efficiency technologies plus any administrative costs required to
implement energy efficiency programs.

Table 2. TRC Explained & TRC Net Benefits and Benefit-Cost Ratios

Scenario

Net Benefits (Billions) Benefit-Cost Ratio

Minimally Aggressive

$0.9

2.2

Moderately Aggressive

$1.6

1.8

Very Aggressive

$1.5

1.5

In essence, the TRC test measures whether it is more expensive to generate and deliver a given amount of energy or to implement programs to save that energy.

In Figure 10, the blue (left) bars show how much it would cost to provide the energy that could be saved through efficiency programs. This cost includes elements such as fuel costs at power plants, the cost of building new power plants, the cost of using power lines or pipelines to deliver electricity or gas, and any other costs that the energy utility could avoid by reducing the amount of energy they need to provide.

The other bar shows how much it would cost to save that same amount of energy, including the total cost of energy-saving equipment and any administrative costs required to implement energy efficiency programs. The cost of efficient equipment can be paid by any combination of program participant out-of-pocket expenses and financial incentives provided by the program.

Net Present Value (Billions of Dollars)

Figure 10. TRC Benefits and Costs for Achievable Potential Scenarios
$5 Total Benefits (Utility Avoided Costs) Program Admin & Marketing Program Incentives
$4 Participant Costs Less Incentives
$3

$2

$1

$0 Minimally Aggressive

Moderately Aggressive

Very Aggressive

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Executive Summary

1.4.4. Power Sector Impacts
Using ICF's Integrated Planning Model (IPM), we simulated the effects of projected energy efficiency potential on electric power system capacity and costs. IPM models the operations of every boiler and generator in the nation in order to develop forecasts for plant dispatch, capacity expansion, and power prices under a range of possible environmental, transmission, energy demand, and other constraints.
IPM reflects the regional markets making up the nation's power system. Taking into account all appropriate constraints, the model projects a least-cost mix of regional generation options to meet the demand for power in Georgia. Therefore, changes in Georgia's electricity demand do not necessarily impact instate generation proportionately.1
The IPM analysis allows us to draw several important conclusions about the impact of projected energy efficiency potential:
Realization of projected energy efficiency potential would yield measurable differences in capacity expansion for the Southern power region by 2015 (See Table 3). Because of the regional nature of power markets, it is not possible to determine whether these capacity reductions would occur within Georgia.
The overwhelming majority of reduced power production would come from natural gas generators.
A large majority of generation reductions would come from units outside of Georgia. This finding reflects relatively low costs of generation in Georgia--generators in Georgia are not the marginal resources (See Table 4).
The percentage reductions in pollutant emissions in 2010 are smaller than percentage reductions in generation (See Table 5).
Each achievable potential scenario would cause a measurable reduction in Southern region wholesale electricity prices (See Table 6).
Based on avoided wholesale energy costs, the costs of implementing energy efficiency programs, and reductions in utility revenues resulting from lower sales, we estimated overall long-term impacts on required average utility revenue within Georgia (See Table 7).

Table 3. Total 2015 Southern Region Capacity Reductions Resulting from Achievable Potential Scenarios

Scenario Minimally Aggressive Moderately Aggressive Very Aggressive

2015 Capacity Change (MW) 679 1,410 1,425

1 IPM relies on data and information on the electric generation system and key drivers to derive wholesale energy prices and other IPM model outputs. These assumptions were based on "EPA Base Case 2004." They are fully documented in EPA Modeling Applications Using the Integrated Planning Model (http://www.epa.gov/airmarkets/epa-ipm).

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Table 4. Generation Reductions from Achievable Potential Scenarios--GWh in Georgia, National GWh, and Percent of National GWh in Georgia

Scenario
Minimally Aggressive Moderately Aggressive Very Aggressive

Georgia GWh 1,207 2,874 4,749

2010 National GWh
3,457 9,023 13,065

% GWh in Georgia 35% 32% 36%

Georgia GWh 2.021 2,714 2,805

2015 National GWh
5,926 10,577 11,166

% GWh in Georgia 34% 26% 25%

Table 5. 2010 Generation and Emissions Reductions Within Georgia from Achievable Potential Scenarios--Total and Percent of State Power Sector

Scenario Minimally Aggressive Moderately Aggressive Very Aggressive

Generation (GWh)

1,207

0.7%

2,874

1.8%

4,749

2.9%

NOx (Thousand Tons)

0.5

0.3%

1.8

1.2%

2.7

1.9%

SO2 (Thousand Tons)

1.1

0.2%

4.8

0.8%

7.6

1.3%

CO2 (Thousand Tons)

634

0.6%

1,692

1.5%

2,710

2.4%

Table 6. Changes in Southern Region Electricity Wholesale Prices from Achievable Potential Scenarios

Scenario
Minimally Aggressive Moderately Aggressive Very Aggressive

Wholesale Prices (Southern Region)

2010

2015

-0.4%

-0.5%

-0.7%

-3.8%

-1.8%

-3.9%

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Table 7. Changes in Georgia Electricity and Gas Average Revenue (LRIRIM)--Total One-Time Increase and Percent of Estimated 2005 Average Revenue2

Scenario
Minimally Aggressive Moderately Aggressive Very Aggressive

Electricity

$/kWh

Percent

$0.001

0.9%

$0.002

2.5%

$0.003

3.9%

Natural Gas

$/Thm

Percent

$0.007

0.8%

$0.018

2.2%

$0.030

3.7%

1.4.5. Public Benefits of Energy Efficiency
Public Health Impacts
Using the EPA's National Co-Benefits Risk Assessment Model (COBRA), we estimated the likely effects of the projected emissions changes on public health in Georgia.
Using more sophisticated atmospheric modeling techniques would allow for a more precise assessment of health impacts. However, based on our COBRA analysis, it is clear that the health benefits related to emissions changes will be small.

2 The lifecycle revenue impact (LRIRIM) represents the one-time change in average revenues required to match utility revenues to revenue requirements over the life of a program. It is calculated by dividing the utility's net costs of a program over energy sales for the full life of the program, yielding the average revenue per unit of energy (i.e., $/kWh or $/Thm) required to meet increased costs.

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Water Consumption Impacts
Energy efficiency can also contribute to reductions in state water usage in two possible ways: Implementation of efficiency measures that also reduce end user water consumption (e.g., low-flow showerheads) Reducing the amount of water required to cool electric power generators
We assessed the impacts of both of these factors and have projected the effects on Georgia water consumption (See Table 8 and Table 9).

Table 8. Reductions in Power Sector and End Use Water Consumption in Georgia

Scenario
Power Sector Minimally Aggressive Moderately Aggressive Very Aggressive
End Use Minimally Aggressive Moderately Aggressive Very Aggressive
Total Minimally Aggressive Moderately Aggressive Very Aggressive

Consumption (Million Gallons per Day)

2010

2015

58

121

123

155

224

159

3

3

8

4

10

4

61

124

131

159

234

164

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Table 9. Changes in Power Sector Water Withdrawals and Consumption in Georgia and Total Southern Region

Scenario
Georgia Minimally Aggressive Moderately Aggressive Very Aggressive
Southern Region Minimally Aggressive Moderately Aggressive Very Aggressive

Withdrawals

2010

2015

-1.3% -3.5% -6.0%

-2.0% -2.6% -2.6%

-0.8% -2.1% -3.8%

-1.2% -1.5% -1.5%

Consumption

2010

2015

-2.9% -6.1% -11.1%

-4.8% -6.2% -6.4%

-2.8% -5.9% -10.8%

-4.5% -5.8% -5.9%

Economic Development Impacts
To assess economic development impacts, we subcontracted with the University of Georgia's Carl Vinson Institute of Government to use the Georgia Economic Modeling System (GEMS), a regional simulation model for the Georgia economy. Provided with several inputs on the costs of energy efficiency equipment, customer energy bill savings, and program administrative and incentive costs, GEMS yielded findings on the economic impacts of the achievable potential scenarios:
Relative to the GEMS baseline economic forecast, each scenario would result in long-term net employment increases in Georgia. By 2015, GEMS projects that these increases would range between 1,500 and 4,200 jobs.
Each scenario would also produce increases in personal income relative to the baseline forecast. GEMS projects that these increases would be between $48 million and $157 million by 2015.

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Figure 11. 2015 Employment Impacts from Achievable Potential Scenarios

Net Change in Employment

4,500 4,000

3,323

3,500

3,000

2,500 2,000

1,487

1,500

1,000

500

0 Minimally Aggressive Moderately Aggressive

4,159 Very Aggressive

Figure 12. 2015 Personal Income Impacts from Achievable Potential Scenarios

Millions of Dollars

$180

$160

$140

111

$120

$100

$80

48

$60

$40

$20

$0 Minimally Aggressive Moderately Aggressive

157 Very Aggressive

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Introduction and Approach

2. Introduction and Approach
2.1. Introduction
2.1.1. Background
A number of sophisticated analyses prepared over the past several years document large untapped potential for cost-effective energy efficiency improvements. These studies have been conducted in a number of states across the US: Wisconsin--ICF Consulting, 2003 and 2004 California--KEMA-XENERGY, 2002 and 2003 Arizona, Colorado, Nevada, New Mexico, Utah, Wyoming--Southwest Energy Efficiency Project (SWEEP) et al, 2002 New Jersey--KEMA-XENERGY, 2004 Connecticut--GDS Associates and Quantum Consulting, 2004
Capture of this potential can yield a variety of benefits including: Lower consumer energy bills Reduced emissions from power plants with associated health benefits Increased local economic activity
2.1.2. Objectives
In an effort to better understand the magnitude of cost-effective and achievable energy efficiency potential in Georgia, the Georgia Environmental Facilities Authority (GEFA) commissioned ICF Consulting to perform a study of the Techno-Economic Potential for Energy Efficiency in the state.
GEFA had several core objectives when commissioning this analysis: Quantify Economic Potential--Assess how much energy efficiency would be economical compared with the total resource costs of supplying and delivering the electricity and natural gas that would otherwise be required. Assess Achievable Potential--Given current market barriers, estimate how much of total economic potential is realistically achievable. Of this achievable potential, determine what portion is naturally occurring--likely to occur as a result of natural market forces and existing energy efficiency programs. The difference between total achievable potential and naturally occurring conservation defines the energy efficiency policy target.

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Evaluate Public Policies--Determine which state policies would be most successful and cost-effective in achieving the energy efficiency policy target.3
Estimate "Environmental Dividends"--Project the public benefits that would flow from realizing achievable energy efficiency potential in terms of air pollutant emission reductions, public health benefits, and economic development impacts.
2.2. Approach
To accomplish the objectives of this project, ICF sought to unite demand-side energy efficiency modeling (EEPM) with supply-side power generation modeling (IPM) and environmental policy and regulation analysis. The goal of this synergistic approach was to comprehensively answer the questions: How much cost-effective energy efficiency is available to be tapped in Georgia? What impacts would the capture of this energy efficiency have? How could state policymakers prudently act in order to realize these energy efficiency improvements?
The study was structured in four substantive tasks, each of which is described in detail later in this section. See Figure 13 for an illustration of the overall structure of the assessment. Collect Data--Data characterizing Georgia electricity and gas load, wholesale and retail costs of energy, and end use efficiency technologies were collected to develop a detailed end use profile of energy use in Georgia. Estimate Achievable Energy Efficiency Potential and Related Impacts--ICF then used its Energy Efficiency Potential Model (EEPM) to estimate Georgia's technically feasible, economically viable, and realistically achievable potential for energy efficiency. Estimate Public Benefits of Energy Efficiency--Next, ICF employed its Integrated Planning Model (IPM) to assess the direct impacts of this energy efficiency potential on generation, generating capacity, and wholesale electricity prices. ICF also estimated the projected potential's effects on pollutant emissions, public health, water consumption, and economic development. Review Public Policy Options--Finally, an array of state public policies were reviewed for their likely efficacy and cost-effectiveness in capturing untapped achievable energy efficiency potential in Georgia.
Below is a description of the demand-side (EEPM) and supply-side (IPM) modeling tools used for this analysis.

3 For a complete discussion of public policy options, see the accompanying report--Strategies for Capturing Georgia's Energy Efficiency Potential.

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Introduction and Approach

Table 10. ICF Consulting Demand-Side and Supply-Side Modeling Tools

DEMAND-SIDE: ENERGY EFFICIENCY POTENTIAL MODEL (EEPM)
ICF Consulting actively develops and maintains a sophisticated measure-based Energy Efficiency Potential Model (EEPM) that projects the technical, economic, and achievable potential of a wide range of gas and electric efficiency upgrades under several market intervention scenarios.
EEPM utilizes several types of input data to project this potential:
Base case load forecasts segmented by sector, subsector (i.e. building type or SIC/NAICS code), end use, and technology type
Savings and cost information for demand-side efficiency technologies
Retail and wholesale energy cost forecasts
Saturation of efficient end use equipment already installed and penetration of high-efficiency equipment in current equipment sales
The final results of the modeling process include extensive data on which sectors, markets, building types, industries, end uses, and measures promise the greatest opportunities for energy efficiency improvements. In addition, EEPM projects annual equipment, administrative, and monetary incentive costs required to purchase efficient equipment and to finance programs to stimulate the purchase of that equipment.

SUPPLY-SIDE: INTEGRATED PLANNING MODEL (IPM)
ICF's Integrated Planning Model (IPM) is a detailed engineeringeconomic capacity expansion and production-costing model of the power sector supported by an extensive database of every boiler and generator in the nation.
The model uses a dynamic linear programming approach to develop a least-cost forecast of plant dispatch and capacity expansion given demand for electricity; environmental requirements; transmission capacity; fuel prices; and operational, financing, and reserve margin constraints. The model forecasts over the entire study horizon and outputs capacity and generation forecasts, wholesale power price forecasts, emissions projections, and fuel prices.
IPM's applications include:
Wholesale power market price forecasting and analysis
Generating unit asset valuation and dispatch assessments
Emissions projections of SO2, NOx, CO2, and Hg
Allowance prices for capped pollutants
Fuel market forecasting and analysis
Grid operations including transmission
Cogeneration market analysis

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Introduction and Approach

Figure 13. Overall Structure of the Assessment

Customer Load Data Saturation & Market Share Data
EE Measure Data
EE Measure Database

EEPM

Applicability and Interactivity Matrix

Segmented Load Forecast

Avoided Costs & Retail Cost Forecast

Technical Potential
Measure Assessment (RIM, TRC, PCT)
Economic Potential
Market Share Projections Achievable Potential

Review Policy Options

Naturally Occurring

Net Achievable Potential

EE Program Costs

IPM
Pollutant Emissions Wholesale Price Effects Capacity Changes Compliance Costs

Retail Price Effects Public Benefits
o Water o Health o Economic

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Introduction and Approach

2.2.1. Data Collection
The complexity and difficulty of data collection activities was significantly increased by our inability to gain access to critical Georgia-specific information already collected as a part of Georgia Power's 2004 integrated resource plan (IRP). The following redacted 2004 Georgia Power IRP data, had they been available, would have contributed significantly to the efficient and timely completion of data collection for this assessment. Future demand-side analysis efforts would benefit greatly from increased transparency and availability of these data.
End Use Load Forecasts--The 2004 Georgia Power IRP contained sophisticated long-term end use electricity sales forecasts for the residential, commercial, and industrial sectors--the type of end use segmented forecast required for this type of end use demand-side analysis.
Utility Avoided Costs--In the same IRP, Georgia Power used its projected avoided costs of generation to screen nearly 200 demand-side measures for cost-effectiveness. Such estimates of avoided costs are necessary to screen demand-side measures for their economic viability. This type of screening is a critical component of any assessment of energy efficiency potential and any demand-side program design and analysis.
Though other utilities often make such data publicly available, Georgia Power considers them a trade secret and not appropriate for public disclosure. Citing concerns that these data could be exposed directly or reverse-engineered from final results, Georgia Power was also unwilling to provide them under a confidentiality agreement for this study. Ultimately, we were unable to reach a compromise that sufficiently allayed these concerns. Credible substitutes for these data were developed for this assessment, but increased disclosure could improve the quality and consistency of demand-side analyses conducted for the state.
Though it would have been useful to incorporate the results of other Georgia-specific studies into this analysis, the US Department of Energy does maintain a large collection of up-to-date data and long-term forecasts on how energy is consumed in various sectors, subsectors, and end uses across the country. These data and forecasts are the most comprehensive, consistent, and reliable sources of public energy information in the country and are highly suitable for studies such as this. The principal drawback of these data is that they lack state-level resolution. For that reason, we have characterized energy consumption in Georgia based on profiles of several states in the Southeast region of the country.
Data collection activities consisted of three basic subtasks, described in detail below.
In summary, our principle sources of data were as follows:
Department of Energy (DOE) Energy Information Administration (EIA)
Database for Energy Efficiency Resources (DEER)
Building energy consumption simulations conducted by ICF using DOE-2 software Base Case IPM projections
ENERGY STAR sales and market share tracking data

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Collect Georgia Load and Utility Cost Data
At the core of our assessment of energy efficiency potential are load and utility cost data. These data were used to characterize the types of customers using energy, how they are using it, and what it costs to supply it. We collected three types of data to complete this subtask:
Customer Load Data--In lieu of using the long-term end use forecasts in Georgia Power's IRP, ICF collected forecast customer electricity and gas sales data disaggregated by sector, subsector, end use, and technology type from the EIA's 2004 Annual Energy Outlook. This forecast, obtained by request from the EIA, offered fully disaggregated projections of electricity and gas sales through 2025 for the South Atlantic Census Division. For the industrial sector, ICF collected some additional data from the EIA's most recent Manufacturing Energy Consumption Survey (MECS).
Avoided Cost Data--Because Georgia-specific electricity avoided cost data were not available, ICF estimated avoided costs from Base Case IPM runs for the Southern region. This region includes Georgia and portions of Florida, Alabama, and Mississippi. ICF obtained natural gas avoided costs from the EIA.
Load Shapes--ICF obtained Itron's eShapes product a collection of load shapes specific to Georgia sectors, subsectors, and end uses for use in development of disaggregated peak demand forecasts and hourly achievable potential results for input into IPM.

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Introduction and Approach

Refine Efficiency Measure Data
ICF maintains a comprehensive database of several hundred energy efficiency measures for use in achievable potential analyses and DSM program design.
To ensure that all measure data were up-to-date and applicable to the Georgia market, we made the following refinements to the database:
As necessary, measure cost and savings data were reviewed and updated in the context of changing energy efficiency standards.
In order to strengthen our analysis of energy savings potential for industrial process end uses, we conducted an extensive review of facility audit data collected in the DOE Industrial Assessment Centers (IAC) Database. This database holds thousands of recommendations made to individual facilities seeking to reduce high energy consumption and costs. Cost and savings data were compiled and added to our measure database for measures impacting the process heating, process cooling, and process machine drive end uses.
Weather-sensitive measures applicable to heating, ventilation, and air conditioning end uses were modeled using DOE-2 building simulations. These simulations were conducted for two residential building types and ten non-residential building types for each of the climate zones in Georgia. The final climate zone savings characteristics of the measures considered were compiled as population-weighted averages for the entire state. Figure 14 illustrates Georgia's climate zones.

Figure 14. Georgia Climate Zones

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Introduction and Approach

Compile Energy Efficiency Market Share Data
Though market share data for energy efficiency measures are generally scarce, several sources provided some insight into the current state of the market for energy efficiency equipment in Georgia. ENERGY STAR sales and market share tracking data offered Georgia-specific market shares for efficient appliances. Market share tracking projects based in California showed time series of market shares for several HVAC, lighting, and appliance end use technologies. Though these data were not Georgia-specific, they are some of the only domestic estimates available.
2.2.2. Estimate Achievable Energy Efficiency Potential and Related Impacts
With the required data in hand, we utilized EEPM to estimate technical, economic, and achievable potential.
After this analysis was complete, ICF projected the related impacts of achievable energy efficiency.
This portion of the analysis consisted of several steps, detailed below.
Establish Market Baseline
The market baseline characterizes the baseline forecast of energy use in Georgia for electricity sales, peak demand, and gas sales disaggregated by sector, subsector, end use, and technology type. See Figure 15 for an illustration of the derivation of the baseline Georgia forecast.
This baseline forecast includes all customer load data collected from the EIA, offering a view of how total load is broken down to a fine level of detail.
Because each sector is modeled separately, the most basic load split is by sector. Within each sector, the load is further divided into the appropriate subsectors, end uses, and technology types. Technology types in the lighting end use, for example, could include exit signs and linear fluorescent fixtures.
We developed the Georgia market baseline as follows: First, we scaled the EIA disaggregated forecasts to match Georgia's actual level of sales in each sector. Georgia 2003 sales data were provided by EIA. Next, subsector, end use, and technology type disaggregations were developed by dividing the scaled Georgia sales forecasts in the same proportions as the EIA's South Atlantic forecast. Peak demand forecasts were developed by utilizing end use load shapes from Itron in conjunction with the disaggregated electricity sales forecasts.

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Introduction and Approach

Figure 15. Establishing the Market Baseline
Total Load

Residential
End Uses Technology Types

Commercial Building Types
End Uses Technology Types

Industrial NAICS Codes
End Uses Technology Types

Assess Energy Efficiency Measures
Using the refined efficiency measure database, we evaluated the cost-effectiveness of measures and measure bundles using the Total Resource Cost (TRC), Participant Cost (PCT), and Ratepayer Impact Measure (RIM) tests. Measures with a TRC benefit-cost ratio of 1.0 or greater were considered for inclusion in economic and achievable potential.
Estimate Technical, Economic, and Achievable Potential
Technical potential quantifies the savings that could be realized if energy efficiency measures were applied in all technically feasible instances, regardless of cost.
Applicability factors, which represent a measure's applicability to a specific end use, were used in conjunction with measure savings factors to estimate technical potential.
Measures are combined within each end use to construct savings potential for the end use as a whole. It is important that measures in the same end use be considered together to avoid over-counting of savings. For example, if two non-exclusive lighting measures are installed, one saving 10% of lighting electricity use and the other saving 25%, the savings of the two measures installed together does not equal the sum of the percentage savings (35%). Instead, the first measure installed saves 10% and the second saves 25% of the usage remaining after installation of the first measure, yielding total savings of 32.5%.

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Economic potential is the subset of technical potential that is cost-effective from a TRC perspective. To project achievable potential, EEPM estimates the adoption of cost-effective energy efficiency measures over time. The derivation of
achievable potential involves several stages: Starting with initial market share data, EEPM projects the market penetration of energy efficiency measures along the characteristic S-shaped
adoption curve. The steepness of that curve is controlled by a parameter called the "adoptive influence" or "A," which can be varied between zero and one to simulate various policy intervention scenarios. For reference, the diffusion of VCRs into the market, known as a quickly adopted technology, progressed along an S-shaped curve with an A value of approximately 0.44. Figure 16 shows market adoption curves under a range of possible A values.

Figure 16. Projected Market Adoption Curves Under a Range of Scenarios

80%

0.8

70%

0.7

0.6

60%

0.5

0.4

0.3

50%

0.2

0.1

40%

0.05

Market Share

30%

20%

10%

0% 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

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EEPM also tracks the turnover of energy consuming equipment.
As existing equipment reaches the end of its useful life and is replaced, new equipment is purchased at either a base or high-efficiency level as determined by the projected market shares for high-efficiency equipment.
Replace-on-fail measures are only available for implementation as older equipment is replaced, but retrofit measures may be implemented at any time. Retrofit measures include:
Measures that do not replace any existing equipment (e.g., pipe insulation added to non-insulated pipes).
Measures that replace existing equipment but are cost-effective even when the full cost of the new high-efficiency equipment is considered. For example, the incremental cost of a high-efficiency 15 SEER residential central air conditioning unit is the difference in cost between a 15 SEER unit and a standard 13 SEER unit. For an equipment replacement such as this, cost-effectiveness for replaceon-fail is calculated based on this incremental cost and the incremental savings achieved by selecting a 15 SEER over a 13 SEER unit. However, if the incremental savings achieved by the 15 SEER unit were enough to overcome the full cost of the equipment and installation, the existing unit may be replaced by the 15 SEER at any time.
Once the penetrations of measures are projected for a given scenario, the resulting energy savings can be calculated using an applicability and interactivity analysis similar to that used to estimate technical and economic potential.
Based on our research of historical energy efficiency program influence on market shares, we have calibrated EEPM's market adoption curves to several scenarios:
Naturally Occurring--This scenario reflects efficiency gains from turnover of older equipment to current standard equipment and the adoption of high-efficiency equipment due to natural market forces and existing energy efficiency programs.
Minimally Aggressive--This scenario is consistent with a portfolio of energy efficiency programs offering modest financial incentives (~25% of incremental costs) with limited marketing and outreach.
Moderately Aggressive--This scenario is consistent with a portfolio of energy efficiency programs offering more generous financial incentives (~50% of incremental costs) with more extensive marketing and outreach.
Very Aggressive--This scenario is consistent with a portfolio of energy efficiency programs offering highly aggressive incentives (~100% of incremental costs) with extensive marketing and outreach efforts. This type of scenario is considered to reflect the maximum possible achievable potential. Efficiency potential in the Very Aggressive case still does not capture all economic potential. Even with financial incentives covering the full cost of efficient equipment, some customers will not be influenced to invest in energy efficiency.
As a final step, EEPM estimates the costs of achieving each level of achievable potential. Three basic types of costs are considered:
Incremental Costs--The cost of purchasing, installing, and maintaining the high-efficiency equipment over and above what would be paid for standard-efficiency equipment.

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Incentive Costs--Monetary incentives paid to program participants for the installation of high-efficiency equipment. As described above, these costs are assigned as a percentage of incremental costs.
Administrative, Marketing, and Outreach Costs--Additional costs associated with engaging program participants, stimulating their investment in energy efficiency, and back office support for programs. Each of these cost categories is calculated as a percentage of incentive costs.
Estimate Effects on Electricity Generation and Capacity
In order to assess the capacity, generation, and emissions impacts of the energy efficiency scenarios, EEPM's estimates of hourly load impacts were provided as inputs to IPM. Figure 17 illustrates our hourly savings estimates in 2010 for the Moderately Aggressive Scenario.
By using these time-specific load decrements, impacts on-peak were distinguished from impacts in off-peak hours, and the system peak could be adjusted to reflect the projected energy efficiency. Electricity transmission and distribution losses were also calculated based on IPM's projected difference between reductions in generation requirements and reductions in electricity sales.
Though the projected end use energy efficiency impacts are specific to Georgia, power markets are largely regional. Therefore, energy efficiency improvements in Georgia would impact generation throughout the Southern region.
IPM modeled each achievable potential scenario for the 2007-2025 period, with energy efficiency load impacts beyond 2015 assumed to be equal to those in 2015.
Impacts on the generating system were estimated for each scenario by comparing the achievable potential IPM scenario results to a Base Case scenario of energy demand. All inputs and assumptions were the same between runs except the level of electricity sales in Georgia. Comparisons between these IPM runs revealed differences in capacity, generation, and emissions within the state of Georgia, in the Southern region, and across the nation.
As noted above, reductions in electricity sales in Georgia would be expected to have impacts on generation outside of Georgia. This would be true, for example, if Georgia had low-cost generating resources that would continue to supply the region, despite reduced demand for electricity in Georgia. Customers of Georgia retail subsidiaries would see the benefits of energy efficiency, and perhaps, depending on ratemaking rules and procedures, benefits from increased power sales outside the region.
Changes in capacity additions; generation by unit type; and in emissions of NOx, SO2, Hg, and CO2 were identified and recorded. Note that because there is a national SO2 cap and trade program in place, no total changes in SO2 emissions are expected. Small temporal or regional shifts may occur, though generally reductions in electricity sales do not yield changes in emissions when an emissions cap is in place. Instead, generating units take advantage of the opportunity brought about by lower compliance requirements to reduce compliance costs. To assess the impact of this phenomenon, we recorded the reductions in emission allowances prices associated with each achievable potential scenario.

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Introduction and Approach Figure 17. Hourly Savings for 2010 Moderately Aggressive Scenario

Savings (MW)

1,750 1,500 1,250 1,000
750 500
1 3 5 7 9 11 13 15 17 19 21 23 Hour

500-750

750-1000

1000-1250

1250-1500

1500-1750

December November October September August July June May April March February January

Month

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Assess Impacts on Average Revenue
Though IPM produces estimates of wholesale prices as one of its standard outputs, average revenues are influenced by many factors in addition to the wholesale price. We have estimated the influence of energy efficiency on long-term average revenue based on the lifecycle revenue impact (LRIRIM), which represents the one-time change in average revenues required to match revenues to revenue requirements over the life of a program. We have calculated these changes in average revenue to establish an overview of the likely impacts of energy efficiency rather than a precise forecast. The Ratepayer Impact Measure (RIM) and other cost-effectiveness perspectives will be described in greater detail in the results. Equation 1 illustrates the formula for calculating the lifecycle revenue impact.

Equation 1. Derivation of Lifecycle Revenue Impact

LRI RIM

= CRIM

- BRIM E

Where the terms are defined as follows:
CRIM equals discounted costs from a Ratepayer Impact Measure (RIM) perspective
BRIM equals discounted benefits from a RIM perspective
E equals discounted energy sales
Perform Alternative "Risk Management" Analyses Reflecting Cost of Emissions
The analyses described above evaluated the role of energy efficiency in the context of air regulations and policies in place and in force today. Specifically, these Base Case regulations include the Acid Rain provisions (Title IV) of the Clean Air Act (CAA), which limit annual emissions of SO2 nationally, and the NOx SIP Call, which limits emissions of NOx during the ozone season in 22 eastern states and the District of Columbia (DC). For this subtask, GEFA sought to uncover the impact of possible future emissions control scenarios on the cost-effectiveness of energy efficiency. We considered several emissions scenarios and modeled the impacts of these scenarios on wholesale electricity prices using IPM. These new wholesale price projections were then used as inputs to EEPM, and achievable potential was reassessed for each emissions scenario. The following emissions regulations were considered:
Clean Air Interstate Rule (CAIR)--The recently adopted CAIR limits NOx and SO2 emissions in 28 eastern states and the District of Columbia. These regional limits to SO2 are in addition to those national limits imposed by Title IV of the CAA.

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Introduction and Approach
CAIR & Clean Air Mercury Rule (CAMR)--This scenario includes, in addition to CAIR, the recently adopted Clean Air Mercury Rule (CAMR), which establishes a national mercury emissions cap applicable to all of the Nation's coal-fired boilers over 25 MW. When fully implemented, CAMR, in addition to the impacts of the CAIR, will limit mercury emissions to 15 tons a year, a reduction of about 70 percent from historic levels based on EPA estimates.
CAIR, CAMR, & CO2 Cap--In addition to capturing the impacts of recently promulgated regulations, we examined the potential impact of a hypothetical mandatory carbon emissions policy on the cost-effectiveness of energy efficiency. In order to assess these potential impacts, we modeled a national level carbon emissions cap on the power sector.
2.2.3. Estimate Public Benefits of Energy Efficiency
Under this task we estimated the direct, indirect, and ancillary effects of deploying energy efficiency.
Pollutant Emissions
Pollutant emissions from power plants are a direct output of IPM. Thus, we recorded the change in emissions relative to the Base Case for each of the achievable potential scenarios.
Consumptive Water Use Savings and Cost Savings
Changes in generation outputs also cause changes in the quantities of water withdrawn and consumed in the production of electricity. Based on IPM's projections of power plants' changes in generation and data from the EIA on each plant's water withdrawals and consumption
per unit of electricity generated, we calculated the changes in power sector water withdrawals and consumption associated with each achievable potential scenario. In addition, based on the water saving characteristics of some energy efficiency measures, we assessed each scenario's impact on end user water consumption.
Public Health Benefits
We assessed the impacts of pollutant emissions changes on public health in Georgia using the EPA's National Co-Benefits Risk Assessment Model (COBRA).
Our projections of pollutant emissions changes were input into the COBRA model for each of the three policy intervention scenarios. COBRA's outputs include county-level impacts on a wide range of pollutant-related health problems. COBRA estimated only slight health benefits for each scenario, so the full quantitative results are not presented in this report.

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Introduction and Approach
Economic Development Impacts
To estimate economic development impacts, we subcontracted with the Regional Dynamics to use their GEMS regional simulation model for the Georgia economy. To support this analysis, we provided several important inputs: Direct expenditures on energy efficiency measures Direct cost savings to consumers from reduced energy bills Incentive and administrative costs associated with implementation of energy efficiency programs
Using these input data, GEMS projected the impacts of the achievable potential scenarios on a variety of important economic metrics including employment, gross state product, and government revenues.
2.2.4. Review Public Policy Options
We conducted an extensive review of the public policy options available to realize our projections of achievable potential. Our analysis evaluated alternative frameworks for the administration and funding of a statewide portfolio of energy efficiency programs. In addition, we developed several program design templates to illustrate some of the important components of a successful and cost-effective program portfolio.
The full results of this policy review are contained in an accompanying report--Strategies for Capturing Georgia's Energy Efficiency Potential.
2.3. Caveats
Because of data limitations and the nature of modeling any complex system, there are several important caveats to be aware of when reading and interpreting the results of this study. System Dynamics--EEPM models the likely impacts of policy interventions on the adoption of energy efficiency equipment as a simple causal system. However, energy efficiency programs operate within the greater dynamic systems of the energy industry and the regional economy. Investment in energy efficiency has effects on the entire system, and we have captured some of these effects by assessing economic development and power sector impacts. What is not modeled are the possible feedbacks from the economy and power sector on the adoption of energy efficiency equipment. For instance, IPM shows that wholesale power prices are lowered because of energy efficiency improvements. But in turn, EEPM does not consider what effect those price changes have on the cost-effectiveness of energy efficiency measures--a possible balancing feedback within the system. Such feedbacks could be explored in greater detail with a more complex modeling effort but are only implicitly incorporated into this study. Aggregation Bias--Energy efficiency measures are represented with average savings and cost values. However, the cost-effectiveness of each measure may vary for different applications depending on the efficacy of the measure for the chosen application, consumer energy use

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Introduction and Approach
patterns, and actual purchase prices for the measures. Variations from the selected average values are limited to some extent by subsector disaggregations, but all deviations from the average are not completely captured.
Emerging Technologies--The measures modeled in EEPM are all currently commercially available. In the future, new energy efficiency technologies will be available, yielding new opportunities for cost-effective energy efficiency. As those opportunities emerge, achievable potential will likely exist in excess of what we have projected in this study. For that reason, our estimates of potential in later years should be considered conservative.
Baseline Forecasts--All baseline forecasts used in this study were appropriately scaled to match actual Georgia energy sales. However, it is not clear how closely the regional EIA forecasts collected for this study reflect top-line growth trends or subsector and end use load disaggregations for Georgia. The fully disaggregated residential and commercial baseline forecasts from the EIA were originally developed for the South Atlantic Census Division. This Division includes Georgia, Florida, South Carolina, North Carolina, Virginia, West Virginia, Maryland, Delaware, and Washington D.C. As noted above, industrial load was disaggregated based on the EIA's MECS survey. NAICS subsector load segmentations were available for the South Census Region, which includes all of the South Atlantic Division plus Kentucky, Tennessee, Mississippi, Alabama, Texas, Louisiana, Arkansas, and Oklahoma. The percentage end use segmentations within each NAICS code are from national level data. Though we cannot know exactly how well these regional forecasts and segmentations approximate Georgia load, they are the best available information available in lieu of Georgia-specific data.
Consumer Adoption--Perhaps the greatest source of uncertainty in our projections of achievable potential are the estimates of market share growth under each policy scenario. Consumer response to energy efficiency programs is inherently complex, and there are very few historical Georgia-specific data on which to base our estimates of market penetrations for the state. Moreover, policy strategies and the quality of program design and implementation can all vary widely, with similarly disparate results.

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Estimates of Energy Efficiency Potential
3. Estimates of Energy Efficiency Potential
3.1. Introduction
Below are our estimates of current technical and economic potential as well as projections of achievable potential over the 2005-2015 period. Our technical and economic potential estimates show total gross potential, including some potential that may be achieved due to naturally occurring conservation in the future. These assessments represent the full extent of technically feasible and economically viable energy efficiency potential in Georgia. Achievable potential is presented as the net of naturally occurring potential, showing only what is achievable above and beyond naturally occurring conservation. These projections may be viewed as energy efficiency policy targets--incremental energy efficiency improvements attainable through policy intervention.
Because this study considers currently available energy efficiency technologies, the projections of achievable potential are most accurate over the short- to medium-term--from present through about 2010. The intent is to identify latent energy efficiency potential that can be readily captured through policy interventions in the next five to ten years. Towards the later years of our projections (2010-2015), new energy efficiency technologies will be developed that supplement and/or replace the commercially available technologies we have modeled. As these technologies emerge, cost-effective and achievable potential will likely exist in excess of what we estimate here.

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Estimates of Energy Efficiency Potential

3.2. Technical and Economic Potential
Before considering the magnitude of energy efficiency improvements that could realistically be achieved through policy intervention, it is useful to formally quantify what is technically and economically possible--technical and economic potential.
Technical and economic potential estimates, as we have presented them here, have no time dimension; it is assumed that all energy efficiency technologies are installed instantaneously. To accomplish this, measure savings factors are applied to all technically or economically feasible applications for which energy efficiency upgrades have not yet been completed.
Technical potential ranges from about 20% to 30% of overall 2004 Georgia load for electricity sales, peak demand, and gas sales. Economic potential ranges from approximately 10% to 20% of 2004 load (See Table 11). Economic potential includes only those measures with a TRC benefit-cost ratio of 1.0 or greater.
For electricity sales, peak demand, and gas sales, the majority of technically feasible energy efficiency is also cost-effective. This is particularly true for electricity sales, where nearly 70% of technical potential is also economic.
Table 11 shows our estimates of technical and economic potential both in absolute terms and as a percentage of 2004 load.

Table 11. Technical and Economic Potential--Total Potential and Percent of 2004 Load

Load Type Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf)

Technical Potential

35,492,561

29%

7,703

33%

63,341

19%

Economic Potential

24,709,395

20%

4,199

18%

36,048

11%

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3.2.1. Technical and Economic Potential by Sector
The residential sector has the greatest technical and economic potential, followed by the commercial and industrial sectors. A very high proportion of what is technically feasible in the industrial sector is also cost-effective, whereas technical potential in the residential
sector far exceeds economic potential. The figures below show our estimates of technical and economic potential by sector, presented in the context of 2004 load. Table 12 presents
technical and economic potential by sector both as absolute potential and as a percentage of 2004 load.

Electricity Sales (MWh) Peak Demand (MW)
Natural Gas Sales (MMcf)

Figure 18. Technical & Economic Potential by Sector (Electricity Sales)

140,000,000 120,000,000 100,000,000

Residential Commercial Industrial

80,000,000

60,000,000

40,000,000

20,000,000

0 2004 Load

Technical

Economic

Figure 19. Technical & Economic Potential by Sector (Peak Demand)

25,000 20,000

Residential Commercial Industrial

15,000

10,000

5,000

0 2004 Load

Technical

Economic

Figure 20. Technical & Economic Potential by Sector (Gas Sales)

400,000 350,000 300,000

Residential Commercial Industrial

250,000

200,000

150,000

100,000

50,000

0 2004 Load

Technical

Economic

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Estimates of Energy Efficiency Potential

Table 12. Technical and Economic Potential by Sector--Total Potential and Percent of 2004 Load

Load Type Residential
Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf) Commercial Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf) Industrial Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf) Total Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf)

Technical Potential

Economic Potential

15,884,676

33% 10,396,499

21%

3,836

41%

1,882

20%

41,292

31%

17,833

13%

13,480,921

33%

8,947,117

22%

2,602

33%

1,432

18%

15,492

28%

11,747

21%

6,126,964

17%

5,365,779

15%

1,265

21%

885

15%

6,557

4%

6,468

4%

35,492,561

29% 24,709,395

20%

7,703

33%

4,199

18%

63,341

19%

36,048

11%

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Estimates of Energy Efficiency Potential

3.3. Achievable Potential
Our estimates of achievable potential represent energy efficiency savings that could be realistically achieved through policy interventions in the 2005-2015 time period.
As described earlier, we have calibrated EEPM's market adoption curves to several scenarios:
Naturally Occurring--This scenario reflects efficiency gains from turnover of older equipment to current standard equipment and the adoption of high-efficiency equipment due to natural market forces and existing energy efficiency programs.
Minimally Aggressive--This scenario is consistent with a portfolio of energy efficiency programs offering modest financial incentives (~25% of incremental costs) with limited marketing and outreach.
Moderately Aggressive--This scenario is consistent with a portfolio of energy efficiency programs offering more generous financial incentives (~50% of incremental costs) with more extensive marketing and outreach.
Very Aggressive--This scenario is consistent with a portfolio of energy efficiency programs offering highly aggressive incentives (~100% of incremental costs) with extensive marketing and outreach efforts. This type of scenario is considered to reflect the maximum possible achievable potential. Efficiency potential in the Very Aggressive case still does not capture all economic potential. Even with financial incentives covering the full cost of efficient equipment, some customers will not be influenced to invest in energy efficiency.
All achievable potential estimates presented here are net of naturally occurring conservation and therefore represent the incremental savings that may be gained through targeted policy intervention.
By 2010, we project achievable potential of between 2.3% and 8.7% of electricity sales, 1.7% and 6.1% of peak demand, and 1.8% and 5.5% of gas sales (See Table 13).

Table 13. 2010 Achievable Potential--Total Potential and Percent of 2010 Load

Load Type Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf)

Minimally Aggressive

3,338,924

2.3%

447

1.7%

7,041

1.8%

Moderately Aggressive

8,704,577

6.0%

1,149

4.4%

16,972

4.4%

Very Aggressive

12,546,554

8.7%

1,608

6.1%

21,343

5.5%

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Estimates of Energy Efficiency Potential

Electricity Sales (MWh)

Figure 21. Achievable Potential (Electricity Sales)

180,000,000

160,000,000

140,000,000

120,000,000 100,000,000
80,000,000 60,000,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

40,000,000

20,000,000

0 2002

2004

2006

2008

2010

2012

2014

2016

Peak Demand (MW)

Figure 22. Achievable Potential (Peak Demand)
35,000

30,000

25,000 20,000 15,000 10,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

5,000

0 2002

2004

2006

2008

2010

2012

2014

2016

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Natural Gas Sales (MMcf)

Figure 23. Achievable Potential (Gas Sales)

450,000

400,000

350,000

300,000 250,000 200,000 150,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

100,000

50,000

0 2002

2004

2006

2008

2010

2012

2014

2016

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Estimates of Energy Efficiency Potential
3.3.1. Achievable Potential by Sector
Achievable potential is relatively evenly distributed across the residential, commercial, and industrial sectors, though there are a few important observations about the relative importance of the sectors to total potential (See figures below). Residential sector potential is significant in electricity and gas sales savings, but nonresidential sectors dominate peak demand potential. The commercial sector plays the largest role in electricity sales and peak demand potential, but the smallest role in gas sales potential. Industrial sector potential is most pronounced for gas sales.

Figure 24. 2010 Achievable Potential by Sector (Electricity Sales)

Industrial 24%

Residential 33%

Commercial 43%

Figure 25. 2010 Achievable Potential by Sector (Peak Demand)

Industrial 29%

Residential 24%

Commercial 47%

Figure 26. 2010 Achievable Potential by Sector (Gas Sales)

Industrial 36%

Residential 35%

Commercial 29%

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Estimates of Energy Efficiency Potential

3.3.2. Achievable Potential by End Use
A handful of end uses make up the majority of total potential. Please note that industrial heating, ventilation, and air conditioning end uses are combined and included in the space heat end use in the figures below.
Electricity Sales--Lighting comprises the largest share of electricity sales savings potential, making up 43% of total savings. Air conditioning is the next most significant end use with a 13% share. Commercial office equipment (12%) and a combination of all industrial process end uses (19%) also contribute substantially to total potential (See Figure 27).
Peak Demand--Air conditioning makes up 37% of total peak demand savings, reflecting the significance of cooling loads at the time of the electricity grid's summer peak. Lighting accounts for an additional 28% of potential, though because of residential lighting usage patterns, most of this savings is found in the nonresidential sectors. Industrial process end uses (21%) are also significant sources of peak savings (See Figure 28).
Gas Sales--Space heat, industrial processes, and domestic hot water make up 44%, 32%, and 24% of gas savings potential, respectively, with minor savings in other end uses (See Figure 29).
The figures on the following pages present 2010 achievable potential by sector and end use, providing an overall context for the contribution of each sector and end use to total potential.

Figure 27. 2010 Achievable Potential by End Use (Electricity Sales)

Industrial Process
19%
Office Equipment
12%

Space Heat 7% Ventilation 1%
Air Conditioning
13%

Appliances 0.04%

Hot Water 4% Refrigeration 1%

Lighting 43%

Figure 28. 2010 Achievable Potential by End Use (Peak Demand)

Office Equipment
4%

Industrial Process
21%

Industrial HVAC 6%
Ventilation 1%

Appliances 0.04%

Hot Water 2%
Refrigeration 1%

Lighting 28%

Air Conditioning
37%

Figure 29. 2010 Achievable Potential by End Use (Gas Sales)

Industrial Process
32%
Appliances 0.01%
Hot Water 24%

Space Heat 44%
Air Conditioning
0.1%

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Estimates of Energy Efficiency Potential

Figure 30. 2010 Achievable Potential by Sector and End Use (Electricity Sales)

Ind. Machine Drive 8%
Ind. Process Cool 3%

Res. Heat 3%

Ind. Process Heat 9%

Com. Heat 2%

Ind. HVAC 2% Com. Ventilation 1%
Res. Central AC 6%
Res. Room AC 0.2%

Com. Office Equipment 12%

Com. AC 7%

Res. Clothes Washer 0.03%
Res. Dryer 0.01%
Res. Dishwasher 0.002%
Res. Hot Water 4%
Com. Refrigeration 1%
Res. Freezer 0.02%
Res. Refrigeration 0.1% Ind. Exterior Lighting 1%

Ind. Interior Lighting 2%
Com. Exterior Lighting 4%

Res. Lighting 20%
Com. Interior Lighting 15%

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Estimates of Energy Efficiency Potential

Figure 31. 2010 Achievable Potential by Sector and End Use (Peak Demand)

Com. Office Equipment 4%
Res. Clothes Washer 0.02%
Res. Dryer 0.01%

Ind. Machine Drive Ind. HVAC

Ind. Process Cool

8%

6%

3%

Ind. Process Heat 9%

Res. Dishwasher 0.001%
Res. Hot Water 2%
Com. Refrigeration 1%

Res. Freezer 0.02%
Res. Refrigeration 0.1%
Ind. Exterior Lighting 0.01%
Com. Exterior Lighting 0.3% Ind. Interior Lighting 3%

Com. Interior Lighting 19%

Res. Lighting 6%

Com. Ventilation 1% Res. Central AC 15%
Res. Room AC 1%
Com. AC 22%

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Estimates of Energy Efficiency Potential

Figure 32. 2010 Achievable Potential by Sector and End Use (Gas Sales)

Ind. Process Cool 0.2%
Ind. Process Heat 32%

Ind. Machine Drive 0.3%
Res. Heat 22%

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Res. Dryer 0.01%
Com. Hot Water 11%

Com. Heat 18%

Ind. HVAC 4%

Res. Hot Water 13%

Com. AC 0.1%

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Estimates of Energy Efficiency Potential

3.3.3. Achievable Potential Cost-Effectiveness4
The achievable energy efficiency potential identified in this study has significant direct net economic benefits for the state of Georgia.
From a "Total Resource Cost" or TRC perspective, the total net benefits to the state from energy efficiency improvements implemented from 2005-2015 in each of the policy intervention scenarios are between $0.9 billion and $1.6 billion in net present value dollars.
The TRC benefit-cost ratios for the three intervention scenarios are between 1.5 and 2.2.
Figures on the following pages assess the cost-effectiveness of each policy intervention scenario from a variety of perspectives. With each figure, there is a description of the benefit-cost perspective presented. Subsequent to these figures are three tables detailing the costeffectiveness of each sector and end use. Each of the three tables reflects the cost-effectiveness of one policy intervention scenario.
For all cost-effectiveness tests, dollars are presented in net present value terms, showing what future costs and savings are worth today. To clarify, money spent or saved some number of years in the future is less valued than money spent or saved today. To account for this, we have discounted future expenditures and savings at an annual rate of 8.15%.
Table 14 shows the costs associated with each achievable potential scenario. Several types of costs are included:
Participant Costs--Incremental capital, installation, and maintenance costs incurred for energy efficiency equipment.
Program Incentives--Monetary incentives paid through energy efficiency programs to encourage the adoption of efficient equipment.
Program Administration--Any administrative, marketing, or outreach costs required to run the programs and engage customers.

Table 14. Net Present Value (Thousands) of Participant, Program Incentive, and Program Administrative Costs

Scenario Minimally Aggressive Moderately Aggressive Very Aggressive

Participant Costs $655,860 $1,463,379 $1,825,967

Program Incentives $163,965 $731,690 $1,825,967

Program Administration $89,192 $501,035
$1,000,910

4 California Public Utilities Commission. California Standard Practice Manual: Economic Analysis of Demand-Side Programs and Projects, October 2001.

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Estimates of Energy Efficiency Potential

Total Resource Cost Test (TRC)
The Total Resource Cost Test assesses the costs of an energy efficiency program relative to other energy supply options.
Benefits--TRC benefits include avoided energy supply costs.
Costs--TRC costs include the total costs of the energy efficiency measures installed plus any program administrative costs. Measure costs may be paid by any combination of program participant expenditures and program incentives.
Figure 33 compares avoided energy supply costs with the sum of program administrative and measure costs (comprised of a combination of participant costs and program incentives).

Table 15. Total Resource Cost Test (TRC) Explained
In essence, the TRC test measures whether it is more expensive to generate and deliver a given amount of energy or to implement programs to save that energy.
In Figure 33, the blue (left) bars show how much it would cost to provide the energy that could be saved through efficiency programs. This cost includes elements such as fuel costs at power plants, the cost of building new power plants, the cost of using power lines or pipelines to deliver electricity or gas, and any other costs that the energy utility could avoid by reducing the amount of energy they need to provide.
The other bars show how much it would cost to save that same amount of energy, including the total cost of energy-saving equipment and any administrative costs required to implement energy efficiency programs. The cost of efficient equipment can be paid by any combination of program participant out-of-pocket expenses and financial incentives provided by the program.
As is the case for each of the cost-effectiveness tests, the difference between the bars represents net benefits--benefits minus costs. Any program or efficiency measure for which benefits are greater than costs is considered cost-effective and passes the TRC test. These cost-effective measures and programs yield benefits to Georgia in excess of the costs of investment even without considering any additional environmental or secondary economic benefits. The TRC test does not identify specifically who will benefit from the programs, but any program or measure that passes the test will benefit customers overall.

Net Present Value (Billions of Dollars)

Figure 33. TRC Benefits and Costs for Achievable Potential Scenarios
$5 Total Benefits (Utility Avoided Costs) Program Admin & Marketing Program Incentives
$4 Participant Costs Less Incentives
$3

$2

$1

$0 Minimally Aggressive

Moderately Aggressive

Very Aggressive

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Participant Cost Test (PCT)
The Participant Cost Test quantifies benefits and costs from the perspective of program participants. Benefits--PCT benefits include participant energy bill savings plus any program incentives paid to the participant. Costs--PCT costs include the total costs of the energy efficiency measures installed.
Figure 34 compares the sum of participant energy bill savings and program incentives with total measure costs paid by the participant.

Table 16. Participant Cost Test (PCT) Explained
The PCT test measures how much program participants benefit from taking part in an energy efficiency program.
In Figure 34, the left bars show the financial benefits that participants receive as a result of taking part in energy efficiency programs. These benefits include energy bill savings resulting from installed efficient equipment and any financial incentives paid by the programs to encourage the adoption of that equipment.
The right bars show the additional costs participants must pay in order to purchase, install, and maintain high-efficiency equipment. In many instances, high-efficiency equipment costs more than its standard efficiency counterpart. This incremental cost is what participants must pay in order to achieve energy savings.
As is the case for each of the cost-effectiveness tests, the difference between the bars represents net benefits--benefits minus costs. Any program or efficiency measure for which benefits are greater than costs is considered cost-effective from a PCT perspective and passes the PCT test.
The PCT test is a reasonable estimate of the quantifiable benefits to participants in energy efficiency programs. However, because customers are also influenced by a range of unquantifiable factors, the PCT test cannot balance all of the criteria on which customers make their decisions to participate in a program.

Figure 34. PCT Benefits and Costs for Achievable Potential Scenarios

$10

Participant Bill Savings

$9

Program Incentives

$8

Participant Costs

Net Present Value (Billions of Dollars)

$7

$6

$5

$4

$3

$2

$1

$0 Minimally Aggressive

Moderately Aggressive

Very Aggressive

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Utility Cost Test (UCT)
The Utility Cost Test, sometimes called the Program Administrator Cost Test, measures the costs of administering an energy efficiency program relative to energy supply options. Benefits--UCT benefits include avoided energy supply costs. Costs--UCT costs include all costs incurred by the utility or program administrator--program administrative costs plus program incentives.
Figure 35 compares avoided energy supply costs with the sum of program incentive and administrative costs.

Table 17. Utility Cost Test (UCT) Explained
The UCT test measures whether it is more costly for a utility to generate and deliver a given amount of energy or to implement programs to save that energy.
In Figure 35, the blue (left) bars show how much it would cost to provide the energy that could be saved through efficiency programs. This cost is identical to that used for the TRC test and includes elements such as fuel costs at power plants, the cost of building new power plants, the cost of using power lines or pipelines to deliver electricity or gas, and any other costs that the energy utility could avoid by reducing the amount of energy they need to provide.
The other bars show how much the utility would have to pay to implement programs to save that same amount of energy. This cost includes financial incentives paid to program participants to encourage the purchase of efficient equipment and any administrative costs required to implement the programs.
As is the case for each of the cost-effectiveness tests, the difference between the bars represents net benefits--benefits minus costs. Any program or efficiency measure for which benefits are greater than costs is considered cost-effective and passes the UCT test.

Figure 35. UCT Benefits and Costs for Achievable Potential Scenarios

$5

Total Benefits (Utility Avoided Costs)

Program Admin & Marketing

$4

Program Incentives

Net Present Value (Billions of Dollars)

$3

$2

$1

$0 Minimally Aggressive

Moderately Aggressive

Very Aggressive

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Ratepayer Impact Measure (RIM)
The Ratepayer Impact Measure assesses the impacts of an energy efficiency program on utility revenues in relation to utility avoided energy supply costs. Benefits--RIM benefits include avoided energy supply costs. Costs--RIM costs include program administrative and incentive costs plus utility lost revenues due to customer energy bill savings.
Figure 36 compares avoided energy supply costs with the sum of program incentive/administrative costs and utility lost revenues.

Table 18. Ratepayer Impact Measure (RIM) Explained
The RIM measures the amount that utility average revenue (i.e., $/kWh or $/Thm) would have to change in order to cover the costs of an energy efficiency program.
In Figure 36, the light blue (left) bars show how much it would cost to provide the energy that could be saved through efficiency programs. This cost is identical to that used for the TRC and UCT tests and includes elements such as fuel costs at power plants, the cost of building new power plants, the cost of using power lines or pipelines to deliver electricity or gas, and any other costs that the energy utility could avoid by reducing the amount of energy they need to provide.
The other bars show the cost to implement programs to save that same amount of energy and the utility sales revenue lost as a result of customer bill savings. The program implementation cost includes financial incentives paid to program participants to encourage the purchase of efficient equipment and any administrative costs required to implement the programs. Utility lost revenues are the reductions in utility bills that customers experience due to energy savings.
As is the case for each of the cost-effectiveness tests, the difference between the bars represents net benefits--benefits minus costs. Unlike other costeffectiveness metrics, however, RIM is typically used as a program design tool for minimizing rate impacts rather than a test for screening programs or measures. For this reason, RIM is best viewed not as a cost-effectiveness test per se, but rather as an indication of how a utility's average revenue would need to change to meet its revenue requirement, all else being equal.

Net Present Value (Billions of Dollars)

Figure 36. RIM Benefits and Costs for Achievable Potential Scenarios

$12 Total Benefits (Utility Avoided Costs)

Participant Bill Savings (Utility Lost Revenues)

$10

Program Admin & Marketing

Program Incentives

$8

$6

$4

$2

$0 Minimally Aggressive

Moderately Aggressive

Very Aggressive

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Table 19 shows net economic benefits and benefit-cost ratios for each achievable potential scenario from a variety of cost perspectives. The tables on the following pages show this same information for each sector and end use.
As for all estimates of economic and achievable potential, each end use includes savings and costs from measures with TRC benefit-cost ratios of 1.0 or greater.
These end use groupings approximate the pieces that would make up a comprehensive portfolio of energy efficiency programs across all sectors.

Scenario
Minimally Aggressive Moderately Aggressive Very Aggressive

Table 19. Net Benefits (Billions) and Benefit-Cost Ratios for Achievable Potential Scenarios

TRC

Net Benefits

BC Ratio

$0.9

2.2

$1.6

1.8

$1.5

1.5

PCT

Net Benefits

BC Ratio

$2.3

4.5

$5.4

4.7

$7.6

5.2

UCT

Net Benefits

BC Ratio

$1.4

6.5

$2.3

2.9

$1.5

1.5

RIM

Net Benefits

BC Ratio

-$1.4

0.5

-$3.8

0.5

-$6.1

0.4

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Estimates of Energy Efficiency Potential

Table 20. Net Benefits (Millions) and Benefit-Cost Ratios for Achievable Potential by Sector and End Use (Minimally Aggressive)

Scenario
Residential Space Heat Residential Central A/C Residential Room A/C Residential Lighting Residential Hot Water Commercial Heating Commercial Ventilation Commercial Cooling Commercial Interior Lighting Commercial Exterior Lighting Commercial Refrigeration Commercial Office Equipment Commercial Hot Water Industrial HVAC Industrial Process Cooling Industrial Process Heating & Boiler Fuel Industrial Interior Lighting Industrial Exterior Lighting Industrial Process Machine Drive Total

TRC

Net Benefits

BC Ratio

$54

2.1

$70

3.5

$2

1.6

$161

1.8

$50

2.7

$44

2.5

$8

1.8

$54

3.0

$59

1.4

$31

2.3

$4

2.1

$31

2.3

$14

1.5

$13

1.7

$31

5.0

$187

4.8

$15

1.8

$4

2.1

$79

4.6

$911

2.2

PCT

Net Benefits

BC Ratio

$172

5.1

$174

8.2

$6

3.8

$570

4.2

$141

6.5

$111

5.3

$27

3.8

$131

6.7

$297

3.0

$87

5.0

$12

4.7

$100

5.9

$53

3.2

$23

2.4

$38

6.6

$227

6.3

$25

2.4

$6

3.0

$96

6.0

$2,296

4.5

UCT

Net Benefits

BC Ratio

$85

6.1

$88

10.1

$3

4.5

$293

5.2

$69

7.7

$64

7.2

$15

5.8

$71

8.7

$173

4.2

$48

6.5

$7

6.1

$46

6.7

$32

4.3

$25

4.9

$36

14.5

$219

13.8

$28

5.4

$7

6.1

$93

13.2

$1,403

6.5

RIM

Net Benefits

BC Ratio

-$118

0.5

-$104

0.5

-$5

0.5

-$409

0.5

-$91

0.5

-$66

0.5

-$18

0.5

-$77

0.5

-$237

0.5

-$56

0.5

-$8

0.5

-$69

0.4

-$39

0.5

-$10

0.8

-$7

0.9

-$40

0.9

-$10

0.8

-$2

0.8

-$18

0.9

-$1,385

0.5

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Estimates of Energy Efficiency Potential

Table 21. Net Benefits (Millions) and Benefit-Cost Ratios for Achievable Potential by Sector and End Use (Moderately Aggressive)

Scenario
Residential Space Heat Residential Central A/C Residential Room A/C Residential Lighting Residential Hot Water Commercial Heating Commercial Ventilation Commercial Cooling Commercial Interior Lighting Commercial Exterior Lighting Commercial Refrigeration Commercial Office Equipment Commercial Hot Water Industrial HVAC Industrial Process Cooling Industrial Process Heating & Boiler Fuel Industrial Interior Lighting Industrial Exterior Lighting Industrial Process Machine Drive Total

TRC

Net Benefits

BC Ratio

$92

1.7

$144

2.8

$2

1.3

$273

1.4

$91

2.2

$79

2.1

$14

1.6

$98

2.5

$49

1.1

$50

1.8

$7

1.7

$48

1.9

$16

1.2

$19

1.4

$61

4.1

$367

4.0

$20

1.5

$7

1.7

$157

3.7

$1,594

1.8

PCT

Net Benefits

BC Ratio

$397

5.3

$426

8.2

$16

4.0

$1,580

4.4

$322

6.6

$246

5.5

$62

4.0

$284

6.8

$630

3.1

$179

5.2

$28

4.9

$201

6.1

$119

3.4

$56

2.6

$82

6.8

$496

6.6

$55

2.6

$14

3.2

$218

6.2

$5,412

4.7

UCT

Net Benefits

BC Ratio

$139

2.7

$174

4.4

$5

2.0

$508

2.3

$120

3.4

$107

3.2

$24

2.6

$122

3.9

$197

1.9

$71

2.9

$10

2.7

$67

2.9

$41

2.0

$36

2.2

$68

6.4

$412

6.3

$38

2.4

$10

2.7

$178

5.8

$2,326

2.9

RIM

Net Benefits

BC Ratio

-$305

0.4

-$282

0.4

-$14

0.4

-$1,307

0.4

-$231

0.4

-$167

0.5

-$48

0.5

-$186

0.5

-$581

0.4

-$130

0.5

-$21

0.4

-$154

0.4

-$103

0.4

-$38

0.6

-$22

0.8

-$128

0.8

-$35

0.7

-$8

0.7

-$61

0.8

-$3,818

0.5

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Estimates of Energy Efficiency Potential

Table 22. Net Benefits (Millions) and Benefit-Cost Ratios for Achievable Potential by Sector and End Use (Very Aggressive)

Scenario
Residential Space Heat Residential Central A/C Residential Room A/C Residential Lighting Residential Hot Water Commercial Heating Commercial Ventilation Commercial Cooling Commercial Interior Lighting Commercial Exterior Lighting Commercial Refrigeration Commercial Office Equipment Commercial Hot Water Industrial HVAC Industrial Process Cooling Industrial Process Heating & Boiler Fuel Industrial Interior Lighting Industrial Exterior Lighting Industrial Process Machine Drive Total

TRC

Net Benefits

BC Ratio

$89

1.5

$162

2.3

$1

1.1

$125

1.1

$97

1.8

$85

1.7

$14

1.4

$108

2.1

-$13

1.0

$47

1.6

$6

1.4

$46

1.6

$6

1.1

$13

1.2

$73

3.5

$443

3.4

$16

1.2

$6

1.5

$189

3.1

$1,512

1.5

PCT

Net Benefits

BC Ratio

$576

5.7

$598

8.6

$23

4.4

$2,077

4.8

$452

7.1

$356

5.9

$93

4.5

$395

7.3

$948

3.6

$250

5.6

$41

5.4

$274

6.5

$182

3.9

$96

3.1

$115

7.2

$694

7.0

$90

3.0

$22

3.7

$311

6.6

$7,592

5.2

UCT

Net Benefits

BC Ratio

$89

1.5

$162

2.3

$1

1.1

$125

1.1

$97

1.8

$85

1.7

$14

1.4

$108

2.1

-$13

1.0

$47

1.6

$6

1.4

$46

1.6

$6

1.1

$13

1.2

$73

3.5

$443

3.4

$16

1.2

$6

1.5

$189

3.1

$1,512

1.5

RIM

Net Benefits

BC Ratio

-$487

0.4

-$435

0.4

-$22

0.3

-$1,953

0.3

-$355

0.4

-$270

0.4

-$79

0.4

-$287

0.4

-$962

0.3

-$202

0.4

-$34

0.4

-$228

0.4

-$177

0.4

-$83

0.5

-$42

0.7

-$251

0.7

-$74

0.5

-$16

0.6

-$123

0.7

-$6,080

0.4

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Estimates of Energy Efficiency Potential

3.3.4. Achievable Potential in Depth
To assist more directly in any future energy efficiency program design strategies, we have modeled the potential for energy efficiency in each sector separately and assessed the subsectors and end uses in which the greatest potential lies.
Below are the complete results of the EEPM modeling effort for each sector. Table 23 shows 2010 achievable potential by sector both in absolute terms and as a percentage of 2010 load.

Table 23. 2010 Achievable Potential by Sector--Total Potential and Percent of 2010 Load

Load Type Residential
Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf) Commercial Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf) Industrial Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf) Total Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf)

Minimally Aggressive

Moderately Aggressive

Very Aggressive

806,010

1.5%

2,908,146

5.3%

5,157,717

9.4%

78

0.8%

280

2.7%

487

4.8%

2,378

1.6%

5,947

3.9%

7,523

4.9%

1,654,957

3.3%

3,725,692

7.5%

4,763,509

9.6%

229

2.4%

537

5.7%

698

7.4%

2,167

3.4%

4,928

7.7%

6,100

9.5%

877,957

2.2%

2,070,740

5.2%

2,625,327

6.6%

140

2.1%

333

4.9%

423

6.3%

2,496

1.5%

6,097

3.6%

7,720

4.6%

3,338,924

2.3%

8,704,577

6.0% 12,546,554

8.7%

447

1.7%

1,149

4.4%

1,608

6.1%

7,041

1.8%

16,972

4.4%

21,343

5.5%

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Estimates of Energy Efficiency Potential
Residential Sector Achievable Potential
OVERVIEW
By 2010, we project achievable potential in the residential sector of between 1.5% and 9.4% of residential electricity sales, 0.8% and 4.8% of residential peak demand, and 1.6% and 4.9% of residential gas sales (See Table 24).
Unlike the commercial and industrial sectors, the residential sector was not modeled in segregated subsectors (i.e., single- or multi-family housing). Because of the overall dominance of single-family housing to residential energy consumption, single-family energy profiles were used wherever there was a known difference between single- and multi-family measure savings characteristics.
Because residences have a lower occupancy rate on the type of summer weekday afternoon that characterizes electricity system peak, residential sector peak demand savings are lower than electricity sales savings would seem to suggest.
Significant natural gas savings in the space heating and hot water end uses make the residential sector a large source of gas sales potential overall.

Table 24. 2010 Residential Achievable Potential--Total Potential and Percent of 2010 Load

Load Type Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf)

Minimally Aggressive

806,010

1.5%

78

0.8%

2,378

1.6%

Moderately Aggressive

2,908,146

5.3%

280

2.7%

5,947

3.9%

Very Aggressive

5,157,717

9.4%

487

4.8%

7,523

4.9%

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Estimates of Energy Efficiency Potential

RESIDENTIAL SECTOR ACHIEVABLE POTENTIAL BY END USE
Below are descriptions of the main end uses contributing to residential savings potential. Figures on the following pages show projections of residential achievable potential and the relative shares of each end use.
Electricity Sales
Electricity sales savings potential is dominated by the lighting end use, making up 59% of total potential. The primary measure influencing this potential is the replacement of highly inefficient but common incandescent light bulbs with compact fluorescent lights (CFLs), which use approximately 25% of the energy consumed by incandescent bulbs.
The central air conditioning and room air conditioning end uses follow lighting as the next most significant sources of electricity sales savings, with a combined share of 19%. Most geographical regions can gain peak demand savings from air conditioning measures, but Georgia's warm climate also makes air conditioning measures highly important to energy sales potential.
Water heating (13%) and space heating (9%) also contribute notable shares to total residential potential. Many households utilize natural gas as fuel for these energy services, but these end uses also make up a significant portion of residential electricity usage and savings potential.
Absent from this list of significant end uses are residential appliances. The high-efficiency appliances reviewed for this assessment, including refrigerators, freezers, clothes dryers, clothes washers, and dishwashers, were not cost-effective on a TRC basis and therefore were not included in policy-driven achievable potential scenarios. Some appliance savings result from an increased replacement rate of older appliances to current standard efficiency units.
Peak Demand
Central air conditioning (61%) and room air conditioning (4%) make up the clear majority of peak demand potential. Because system peak demand typically occurs on a summer weekday afternoon, air conditioning makes up a very large proportion of total residential peak demand and savings potential.
Lighting plays a substantial but lesser role in peak demand savings, with a 24% share of potential. This result also reflects residential electricity usage patterns on a typical peak summer afternoon. Residential lighting is not as extensively used during this time period, so its contribution to peak demand potential is less than its contribution to energy sales potential.
Water heating holds a sizable portion of peak demand potential (10%), but space heating has no impact on peak demand savings.
Gas Sales
Space heating makes up the majority of gas sales potential, with a 62% share. Programmable thermostats and infiltration reduction measures are the most important contributors to this potential.
Water heating accounts for nearly all other gas sales potential, contributing 38% to the total. This potential consists of measures reducing heat loss (e.g., pipe and tank insulation) and measures restricting hot water usage (e.g., faucet aerators and low flow showerheads).

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Estimates of Energy Efficiency Potential

Figure 37. Residential Achievable Potential (Electricity Sales)
70,000,000

60,000,000

Electricity Sales (MWh)

50,000,000 40,000,000 30,000,000 20,000,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

10,000,000

0 2002

2004

2006

2008

2010

2012

2014

2016

Figure 38. Residential Achievable Potential (Peak Demand)
12,000

10,000

Peak Demand (MW)

8,000 6,000 4,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

2,000

0 2002

2004

2006

2008

2010

2012

2014

2016

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Figure 39. Residential Achievable Potential (Gas Sales)

180,000

160,000

140,000

Natural Gas Sales (MMcf)

120,000 100,000
80,000 60,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

40,000

20,000

0 2002

2004

2006

2008

2010

2012

2014

2016

Georgia Environmental Facilities Authority May 5, 2005

Estimates of Energy Efficiency Potential

Figure 40. Residential Potential by End Use (Electricity Sales)

Water Heat 13%
Freezer 0.1%
Refrigerator 0.4%

Clothes Washer

0.1%

Space Heat

9%

Central A/C 18%

Room A/C 0.6%

Lighting 59%

Figure 42. Residential Potential by End Use (Gas Sales)
Clothes Dryer 0.02%

Water Heat 38%

Space Heat 62%

Figure 41. Residential Potential by End Use (Peak Demand)

Water Heat 10%
Freezer 0.1%
Refrigerator 0.5%

Clothes Washer 0.1%

Lighting 24%

Room A/C 4.3%

Central A/C 61%

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Estimates of Energy Efficiency Potential

RESIDENTIAL SECTOR ACHIEVABLE POTENTIAL COST-EFFECTIVENESS
From a TRC perspective, the total net benefits to the state from energy efficiency improvements implemented from 2005-2015 in the residential sector are between $0.3 billion and $0.6 billion in net present value dollars.
The TRC benefit-cost ratios for the three intervention scenarios are between 1.4 and 2.1.
Table 25 shows the net present value of costs associated with residential sector programs.
Table 26 shows the direct net benefits and benefit-cost ratios for each intervention scenario from a range of cost perspectives.
The tables on the following pages present the net benefits and cost-effectiveness for each end use contributing to overall residential achievable potential.

Table 25. Net Present Value (Thousands) of Participant, Program Incentive, and Program Administrative Costs (Residential)

Scenario Minimally Aggressive Moderately Aggressive Very Aggressive

Participant Costs $271,147 $683,568 $834,206

Program Incentives $67,787 $341,784 $834,206

Program Administration $39,372 $247,718 $484,278

Table 26. Net Benefits (Billions) and Benefit-Cost Ratios for Residential Sector Achievable Potential Scenarios

Scenario
Minimally Aggressive Moderately Aggressive Very Aggressive

TRC

Net Benefits

BC Ratio

$0.3

2.1

$0.6

1.6

$0.5

1.4

PCT

Net Benefits

BC Ratio

$1.1

4.9

$2.7

5.0

$3.7

5.5

UCT

Net Benefits

BC Ratio

$0.5

6.0

$0.9

2.6

$0.5

1.4

RIM

Net Benefits

BC Ratio

-$0.7

0.5

-$2.1

0.4

-$3.3

0.4

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Estimates of Energy Efficiency Potential

Table 27. Net Benefits (Millions) and Benefit-Cost Ratios for Residential Achievable Potential by End Use (Minimally Aggressive Scenario)

Scenario
Residential Space Heat Residential Central A/C Residential Room A/C Residential Lighting Residential Hot Water Total

TRC

Net Benefits

BC Ratio

$54

2.1

$70

3.5

$2

1.6

$161

1.8

$50

2.7

$336

2.1

PCT

Net Benefits

BC Ratio

$172

5.1

$174

8.2

$6

3.8

$570

4.2

$141

6.5

$1,063

4.9

UCT

Net Benefits

BC Ratio

$85

6.1

$88

10.1

$3

4.5

$293

5.2

$69

7.7

$539

6.0

RIM

Net Benefits

BC Ratio

-$118

0.5

-$104

0.5

-$5

0.5

-$409

0.5

-$91

0.5

-$728

0.5

Table 28. Net Benefits (Millions) and Benefit-Cost Ratios for Residential Achievable Potential by End Use (Moderately Aggressive Scenario)

Scenario
Residential Space Heat Residential Central A/C Residential Room A/C Residential Lighting Residential Hot Water Total

TRC

Net Benefits

BC Ratio

$92

1.7

$144

2.8

$2

1.3

$273

1.4

$91

2.2

$603

1.6

PCT

Net Benefits

BC Ratio

$397

5.3

$426

8.2

$16

4.0

$1,580

4.4

$322

6.6

$2,741

5.0

UCT

Net Benefits

BC Ratio

$139

2.7

$174

4.4

$5

2.0

$508

2.3

$120

3.4

$945

2.6

RIM

Net Benefits

BC Ratio

-$305

0.4

-$282

0.4

-$14

0.4

-$1,307

0.4

-$231

0.4

-$2,138

0.4

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Estimates of Energy Efficiency Potential

Table 29. Net Benefits (Millions) and Benefit-Cost Ratios for Residential Achievable Potential by End Use (Very Aggressive Scenario)

Scenario
Residential Space Heat Residential Central A/C Residential Room A/C Residential Lighting Residential Hot Water Total

TRC

Net Benefits

BC Ratio

$89

1.5

$162

2.3

$1

1.1

$125

1.1

$97

1.8

$474

1.4

PCT

Net Benefits

BC Ratio

$576

5.7

$598

8.6

$23

4.4

$2,077

4.8

$452

7.1

$3,726

5.5

UCT

Net Benefits

BC Ratio

$89

1.5

$162

2.3

$1

1.1

$125

1.1

$97

1.8

$474

1.4

RIM

Net Benefits

BC Ratio

-$487

0.4

-$435

0.4

-$22

0.3

-$1,953

0.3

-$355

0.4

-$3,252

0.4

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Estimates of Energy Efficiency Potential

Commercial Sector Achievable Potential

OVERVIEW

By 2010, we project achievable potential in the commercial sector of between 3.3% and 9.6% of commercial electricity sales, 2.4% and 7.4% of commercial peak demand, and 3.4% and 9.5% of commercial gas sales (See Table 30).

As noted above, the commercial sector is by far the most significant source of total electricity sales (43%) and peak demand (47%) potential. The sector's importance to overall gas potential is much less, representing only 29% of the total.

The commercial sector has been segregated into eleven subsectors, defined by building type. These building types are the same as those defined in the EIA's energy consumption forecasts:

Education

Health Care

Mercantile/Service

Assembly

Lodging

Warehouse

Food Sales

Office Large

Other

Food Service

Office Small

The large office, small office, and mercantile/service building types dominate electricity sales and peak demand potential, but natural gas savings potential is more evenly distributed among subsectors.

Table 30. 2010 Commercial Achievable Potential--Total Potential and Percent of 2010 Load

Load Type Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf)

Minimally Aggressive

1,654,957

3.3%

229

2.4%

2,167

3.4%

Moderately Aggressive

3,725,692

7.5%

537

5.7%

4,928

7.7%

Very Aggressive

4,763,509

9.6%

698

7.4%

6,100

9.5%

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Estimates of Energy Efficiency Potential
COMMERCIAL SECTOR ACHIEVABLE POTENTIAL BY SUBSECTOR AND END USE
Below are descriptions of the main end uses and building types contributing to commercial savings potential. Figures on the following pages show projections of commercial achievable potential and the relative shares of each end use and building type.
Electricity Sales The large office (22%), small office (13%), and mercantile/service (24%) subsectors are the principal sources of electricity savings potential. Interior lighting is the largest portion of electricity sales potential, with a 35% share. These savings are derived from the installation of highefficiency technologies in the linear fluorescent, incandescent, high-intensity discharge, and exit lighting technology types. Significant savings also exist in exterior lighting applications, which hold a 10% share of total potential. Office equipment is the next most important segment of potential, making up 28% of the total. Measures for this end use principally include technologies designed to reduce electricity consumption when computers, monitors, printers, copiers, and other equipment are not in use. Cooling (air conditioning) also makes up a significant percentage of potential, contributing 17% to the total.
Peak Demand Large office (16%), small office (14%), and mercantile/service (26%) building types also hold the most peak potential, though significant cooling savings in the lodging subsector propel it to a notably large share of potential as well (13%). As is the case in the residential sector, cooling comprises the dominant share of peak demand potential, with 47% of the total. In contrast to the residential sector, commercial interior lighting is used extensively during peak hours and contributes 41% to total commercial peak demand potential. Despite a large contribution to overall peak usage, office equipment does not have as significant peak savings potential (8%). Because most office equipment measures save energy by reducing energy consumption while the equipment is not in use, savings potential during the peak period is small relative to overall electricity sales potential.
Gas Sales Gas sales potential is more evenly distributed among building types, with notable shares in the warehouse (16%), mercantile/service (15%), lodging (14%), and health care (14%) subsectors. As in the residential sector, heating makes up the majority of gas savings potential, comprising 63% of the total. A variety of hot water measures make up the remaining 37% of potential, with a negligible portion attributable to gas space cooling measures (0.4%).

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Estimates of Energy Efficiency Potential

Figure 43. Commercial Achievable Potential (Electricity Sales)
70,000,000

60,000,000

Electricity Sales (MWh)

50,000,000 40,000,000 30,000,000 20,000,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

10,000,000

0 2002

2004

2006

2008

2010

2012

2014

2016

Figure 44. Commercial Achievable Potential (Peak Demand)
12,000

10,000

Peak Demand (MW)

8,000 6,000 4,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

2,000

0 2002

2004

2006

2008

2010

2012

2014

2016

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Figure 45. Commercial Achievable Potential (Gas Sales)
80,000

70,000

Natural Gas Sales (MMcf)

60,000

50,000 40,000 30,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

20,000

10,000

0 2002

2004

2006

2008

2010

2012

2014

2016

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Estimates of Energy Efficiency Potential

Figure 46. Commercial Potential by End Use (Electricity Sales)

Office Equipment 28%

Heating 5%

Ventilation 3%

Cooling 17%

Refrigeration 2%
Exterior Lighting 10%

Interior Lighting 35%

Figure 48. Commercial Potential by End Use (Gas Sales)

Water 37%
Cooling 0.4%

Heating 63%

Figure 47. Commercial Potential by End Use (Peak Demand)

Office Equipment

Refrigeration

8%

Ventilation 2%

1%

Exterior Lighting 1%

Interior Lighting 41%

Cooling 47%

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Estimates of Energy Efficiency Potential

Figure 49. Commercial Potential by Building Type (Electricity Sales)

Other 3%
Warehouse 6%

Education 4% Assembly 7%

Food Sales 2%

Food Service 5%

Merc/Service 24%

Health Care 7%
Lodging 7%

Office - Small 13%

Office - Large 22%

Figure 50. Commercial Potential by Building Type (Peak Demand)

Other 2%
Warehouse 5%

Education 3% Assembly 5% Food Sales
2%

Food Service 8%

Merc/Service 26%

Health Care 6%

Office - Small 14%

Lodging 13%
Office - Large 16%

Figure 51. Commercial Potential by Building Type (Gas Sales)

Warehouse 16%

Other Education

4%

8%

Assembly 5%
Food Sales 1%
Food Service 5%

Merc/Service 15%

Health Care 14%

Office - Small 7%

Office - Large 11%

Lodging 14%

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Estimates of Energy Efficiency Potential

COMMERCIAL SECTOR ACHIEVABLE POTENTIAL COST-EFFECTIVENESS
From a TRC perspective, the total net benefits to the state from energy efficiency improvements implemented from 2005-2015 in the commercial sector are between $0.2 billion and $0.4 billion in net present value dollars.
The TRC benefit-cost ratios for the three intervention scenarios are between 1.3 and 1.8.
Table 31 shows the net present value of costs associated with commercial sector programs.
Table 32 shows the direct net benefits and benefit-cost ratios for each intervention scenario from a range of cost perspectives.
The tables on the following pages present the net benefits and cost-effectiveness for each end use contributing to overall commercial achievable potential.

Table 31. Net Present Value (Thousands) of Participant, Program Incentive, and Program Administrative Costs (Commercial)

Scenario Minimally Aggressive Moderately Aggressive Very Aggressive

Participant Costs $278,819 $557,833 $703,990

Program Incentives $69,705 $278,917 $703,990

Program Administration $34,829 $174,565 $353,116

Table 32. Net Benefits (Billions) and Benefit-Cost Ratios for Commercial Sector Achievable Potential Scenarios

Scenario
Minimally Aggressive Moderately Aggressive Very Aggressive

TRC

Net Benefits

BC Ratio

$0.2

1.8

$0.4

1.5

$0.3

1.3

PCT

Net Benefits

BC Ratio

$0.8

3.9

$1.7

4.1

$2.5

4.6

UCT

Net Benefits

BC Ratio

$0.5

5.4

$0.6

2.4

$0.3

1.3

RIM

Net Benefits

BC Ratio

-$0.6

0.5

-$1.4

0.4

-$2.2

0.4

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Estimates of Energy Efficiency Potential

Table 33. Net Benefits (Millions) and Benefit-Cost Ratios for Commercial Achievable Potential by End Use (Minimally Aggressive Scenario)

Scenario
Commercial Heating Commercial Ventilation Commercial Cooling Commercial Interior Lighting Commercial Exterior Lighting Commercial Refrigeration Commercial Office Equipment Commercial Hot Water Total

TRC

Net Benefits

BC Ratio

$44

2.5

$8

1.8

$54

3.0

$59

1.4

$31

2.3

$4

2.1

$31

2.3

$14

1.5

$246

1.8

PCT

Net Benefits

BC Ratio

$111

5.3

$27

3.8

$131

6.7

$297

3.0

$87

5.0

$12

4.7

$100

5.9

$53

3.2

$818

3.9

UCT

Net Benefits

BC Ratio

$64

7.2

$15

5.8

$71

8.7

$173

4.2

$48

6.5

$7

6.1

$46

6.7

$32

4.3

$456

5.4

RIM

Net Benefits

BC Ratio

-$66

0.5

-$18

0.5

-$77

0.5

-$237

0.5

-$56

0.5

-$8

0.5

-$69

0.4

-$39

0.5

-$571

0.5

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Estimates of Energy Efficiency Potential

Table 34. Net Benefits (Millions) and Benefit-Cost Ratios for Commercial Achievable Potential by End Use (Moderately Aggressive Scenario)

Scenario
Commercial Heating Commercial Ventilation Commercial Cooling Commercial Interior Lighting Commercial Exterior Lighting Commercial Refrigeration Commercial Office Equipment Commercial Hot Water Total

TRC

Net Benefits

BC Ratio

$79

2.1

$14

1.6

$98

2.5

$49

1.1

$50

1.8

$7

1.7

$48

1.9

$16

1.2

$361

1.5

PCT

Net Benefits

BC Ratio

$246

5.5

$62

4.0

$284

6.8

$630

3.1

$179

5.2

$28

4.9

$201

6.1

$119

3.4

$1,750

4.1

UCT

Net Benefits

BC Ratio

$107

3.2

$24

2.6

$122

3.9

$197

1.9

$71

2.9

$10

2.7

$67

2.9

$41

2.0

$640

2.4

RIM

Net Benefits

BC Ratio

-$167

0.5

-$48

0.5

-$186

0.5

-$581

0.4

-$130

0.5

-$21

0.4

-$154

0.4

-$103

0.4

-$1,389

0.4

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Estimates of Energy Efficiency Potential

Table 35. Net Benefits (Millions) and Benefit-Cost Ratios for Commercial Achievable Potential by End Use (Very Aggressive Scenario)

Scenario
Commercial Heating Commercial Ventilation Commercial Cooling Commercial Interior Lighting Commercial Exterior Lighting Commercial Refrigeration Commercial Office Equipment Commercial Hot Water Total

TRC

Net Benefits

BC Ratio

$85

1.7

$14

1.4

$108

2.1

-$13

1.0

$47

1.6

$6

1.4

$46

1.6

$6

1.1

$299

1.3

PCT

Net Benefits

BC Ratio

$356

5.9

$93

4.5

$395

7.3

$948

3.6

$250

5.6

$41

5.4

$274

6.5

$182

3.9

$2,538

4.6

UCT

Net Benefits

BC Ratio

$85

1.7

$14

1.4

$108

2.1

-$13

1.0

$47

1.6

$6

1.4

$46

1.6

$6

1.1

$299

1.3

RIM

Net Benefits

BC Ratio

-$270

0.4

-$79

0.4

-$287

0.4

-$962

0.3

-$202

0.4

-$34

0.4

-$228

0.4

-$177

0.4

-$2,240

0.4

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Estimates of Energy Efficiency Potential

Industrial Sector Achievable Potential

OVERVIEW

By 2010, we project achievable potential in the industrial sector of between 2.2% and 6.6% of industrial electricity sales, 2.1% and 6.3% of industrial peak demand, and 1.5% and 4.6% of industrial gas sales (See Table 36).

The industrial sector has been segregated into eleven subsectors, defined by NAICS code. These subsectors include the ten largest electricity consumers, according to EIA South Census Region data, and a compilation of all other load in other manufacturing and non-manufacturing industries:

325-Chemicals

311-Food

336-Transportation Equipment

331-Primary Metals

324-Petroleum and Coal Products

332-Fabricated Metal Products

322-Paper

326-Plastics and Rubber Products

Other/Non-Manufacturing

313-Textile Mills

327-Nonmetallic Mineral Products

The chemical and primary metals industries are the most significant contributors to electricity sales and peak demand potential. The chemical industry is most dominant as a part of gas sales potential, comprising a 38% share of the total.

Table 36. 2010 Industrial Achievable Potential--Total Potential and Percent of 2010 Load

Load Type Reduction in Electricity Sales (MWh) Reduction in Peak Demand (MW) Reduction in Gas Sales (MMcf)

Minimally Aggressive

877,957

2.2%

140

2.1%

2,496

1.5%

Moderately Aggressive

2,070,740

5.2%

333

4.9%

6,097

3.6%

Very Aggressive

2,625,327

6.6%

423

6.3%

7,720

4.6%

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Estimates of Energy Efficiency Potential
INDUSTRIAL SECTOR ACHIEVABLE POTENTIAL BY SUBSECTOR AND END USE
Below are descriptions of the main end uses and NAICS codes contributing to industrial savings potential. Figures on the following pages show projections of industrial achievable potential and the relative shares of each end use and NAICS code.
Mirroring the custom nature of industrial processes, the measures considered for the process end uses in the industrial sector do not represent specific technologies or practices. Rather, based on extensive audit data collected from facilities targeted for their high energy consumption, the process measures modeled are designed to reflect a range of typical estimated implementation costs to achieve one unit of energy savings (i.e., $/kWh or $/Therm) in a certain end use.
Electricity Sales The chemical and primary metals industries, which are also the two largest industrial electricity consumers in Georgia according to EIA data for the South Census Region, make up the greatest single portions of electricity sales potential, with 17% and 15% shares respectively. The process heating and boiler fuel (36%), process machine drive (32%), and process cooling (12%) end uses make up most of electricity savings potential in the industrial sector. Non-process end uses including interior lighting (10%), HVAC (7%), and exterior lighting (3%) also contribute notably to total potential.
Peak Demand Peak demand savings potential is split among NAICS codes very similarly to electricity sales potential, with the chemical and primary metals industries making up 16% and 13% of total potential respectively. End use distributions are also very similar to those in electricity sales potential. The HVAC end use, driven primarily by air conditioning savings, makes up a notable 19% of peak demand savings potential.
Gas Sales The chemical and petroleum/coal products industries contribute the most to total industrial gas sales savings potential, comprising 38% and 12% of potential respectively. The process heating and boiler fuel end use makes up the vast majority of gas savings potential, with an 87% share. Most of the remaining potential is derived from the HVAC end use, primarily heating, accounting for 11% of the total.

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Estimates of Energy Efficiency Potential

Figure 52. Industrial Achievable Potential (Electricity Sales)

50,000,000

45,000,000

40,000,000

Electricity Sales (MWh)

35,000,000

30,000,000 25,000,000 20,000,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

15,000,000

10,000,000

5,000,000

0 2002

2004

2006

2008

2010

2012

2014

2016

Figure 53. Industrial Achievable Potential (Peak Demand)
8,000

7,000

6,000

Peak Demand (MW)

5,000 4,000 3,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

2,000

1,000

0 2002

2004

2006

2008

2010

2012

2014

2016

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Natural Gas Sales (MMcf)

Figure 54. Industrial Achievable Potential (Gas Sales)

200,000

180,000

160,000

140,000

120,000 100,000
80,000

Base Forecast Minimally Aggressive Moderately Aggressive Very Aggressive

60,000

40,000

20,000

0 2002

2004

2006

2008

2010

2012

2014

2016

Georgia Environmental Facilities Authority May 5, 2005

Estimates of Energy Efficiency Potential

Figure 55. Industrial Potential by End Use (Electricity Sales)

Process Machine Drive 32%

HVAC 7%

Process Cooling 12%

Figure 57. Industrial Potential by End Use (Gas Sales)

Process Machine

Drive 1%

HVAC 11%

Process Cooling 1%

Exterior Lighting 3%
Interior Lighting 10%

Process Heating & Boiler Fuel 36%

Figure 56. Industrial Potential by End Use (Peak Demand)

Process Heating & Boiler Fuel 87%

Process Machine Drive 27%
Exterior Lighting 0.03%
Interior Lighting 9%

HVAC 19%
Process Cooling 12%
Process Heating & Boiler Fuel 33%

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Estimates of Energy Efficiency Potential

Figure 58. Industrial Potential by NAICS Code (Electricity Sales)

Figure 60. Industrial Potential by NAICS Code (Gas Sales)

Other/Non Manufacturing
31%

325 Chemicals 17%
331 Primary Metals 15%

332 Fabricated Metal Products
3%
336 Transportation Equipment 4%
327 Nonmetallic Mineral Products
5%

326 Plastics and Rubber Products
5%

322 Paper 5%
313 Textile Mills 6%
311 Food 6%
324 Petroleum and Coal Products 3%

Figure 59. Industrial Potential by NAICS Code (Peak Demand)

Other/Non Manufacturing
31%
332 Fabricated Metal Products
1%

336 Transportation Equipment 1%

327 Nonmetallic Mineral Products
3%
326 Plastics and Rubber Products
1%

324 Petroleum and

Coal Products 311 Food

12%

3%

325 Chemicals 38%
331 Primary Metals 4%
322 Paper 5%
313 Textile Mills 1%

325 Chemicals 16%

Other/Non Manufacturing
36%

331 Primary Metals 13%

332 Fabricated Metal Products
3%
336 Transportation Equipment 4%
327 Nonmetallic Mineral Products
4%

322 Paper 4%

313 Textile Mills 6%

326 Plastics and Rubber Products
5%

311 Food 6%
324 Petroleum and Coal Products 3%

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Estimates of Energy Efficiency Potential

INDUSTRIAL SECTOR ACHIEVABLE POTENTIAL COST-EFFECTIVENESS
From a TRC perspective, the total net benefits to the state from energy efficiency improvements implemented from 2005-2015 in the industrial sector are between $0.3 billion and $0.7 billion in net present value dollars.
The TRC benefit-cost ratios for the three intervention scenarios are between 2.6 and 3.7.
Table 36 shows the net present value of costs associated with industrial sector programs.
Table 38 shows the direct net benefits and benefit-cost ratios for each intervention scenario from a range of cost perspectives.
The tables on the following pages present the net benefits and cost-effectiveness for each end use contributing to overall industrial achievable potential.

Table 37. Net Present Value (Thousands) of Participant, Program Incentive, and Program Administrative Costs (Industrial)

Scenario Minimally Aggressive Moderately Aggressive Very Aggressive

Participant Costs $105,893 $221,978 $287,771

Program Incentives $26,473 $110,989 $287,771

Program Administration $14,991 $78,752 $163,516

Table 38. Net Benefits (Billions) and Benefit-Cost Ratios for Industrial Sector Achievable Potential Scenarios

Scenario
Minimally Aggressive Moderately Aggressive Very Aggressive

TRC

Net Benefits

BC Ratio

$0.3

3.7

$0.6

3.1

$0.7

2.6

PCT

Net Benefits

BC Ratio

$0.4

4.9

$0.9

5.1

$1.3

5.6

UCT

Net Benefits

BC Ratio

$0.4

10.8

$0.7

4.9

$0.7

2.6

RIM

Net Benefits

BC Ratio

-$0.09

0.8

-$0.3

0.8

-$0.6

0.7

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Estimates of Energy Efficiency Potential

Table 39. Net Benefits (Millions) and Benefit-Cost Ratios for Industrial Achievable Potential by End Use (Minimally Aggressive Scenario)

Scenario
Industrial HVAC Industrial Process Cooling Industrial Process Heating & Boiler Fuel Industrial Interior Lighting Industrial Exterior Lighting Industrial Process Machine Drive Total

TRC

Net Benefits

BC Ratio

$13

1.7

$31

5.0

$187

4.8

$15

1.8

$4

2.1

$79

4.6

$329

3.7

PCT

Net Benefits

BC Ratio

$23

2.4

$38

6.6

$227

6.3

$25

2.4

$6

3.0

$96

6.0

$415

4.9

UCT

Net Benefits

BC Ratio

$25

4.9

$36

14.5

$219

13.8

$28

5.4

$7

6.1

$93

13.2

$408

10.8

RIM

Net Benefits

BC Ratio

-$10

0.8

-$7

0.9

-$40

0.9

-$10

0.8

-$2

0.8

-$18

0.9

-$86

0.8

Table 40. Net Benefits (Millions) and Benefit-Cost Ratios for Industrial Achievable Potential by End Use (Moderately Aggressive Scenario)

Scenario
Industrial HVAC Industrial Process Cooling Industrial Process Heating & Boiler Fuel Industrial Interior Lighting Industrial Exterior Lighting Industrial Process Machine Drive Total

TRC

Net Benefits

BC Ratio

$19

1.4

$61

4.1

$367

4.0

$20

1.5

$7

1.7

$157

3.7

$630

3.1

PCT

Net Benefits

BC Ratio

$56

2.6

$82

6.8

$496

6.6

$55

2.6

$14

3.2

$218

6.2

$921

5.1

UCT

Net Benefits

BC Ratio

$36

2.2

$68

6.4

$412

6.3

$38

2.4

$10

2.7

$178

5.8

$741

4.9

RIM

Net Benefits

BC Ratio

-$38

0.6

-$22

0.8

-$128

0.8

-$35

0.7

-$8

0.7

-$61

0.8

-$291

0.8

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Estimates of Energy Efficiency Potential

Table 41. Net Benefits (Millions) and Benefit-Cost Ratios for Industrial Achievable Potential by End Use (Very Aggressive Scenario)

Scenario
Industrial HVAC Industrial Process Cooling Industrial Process Heating & Boiler Fuel Industrial Interior Lighting Industrial Exterior Lighting Industrial Process Machine Drive Total

TRC

Net Benefits

BC Ratio

$13

1.2

$73

3.5

$443

3.4

$16

1.2

$6

1.5

$189

3.1

$739

2.6

PCT

Net Benefits

BC Ratio

$96

3.1

$115

7.2

$694

7.0

$90

3.0

$22

3.7

$311

6.6

$1,328

5.6

UCT

Net Benefits

BC Ratio

$13

1.2

$73

3.5

$443

3.4

$16

1.2

$6

1.5

$189

3.1

$739

2.6

RIM

Net Benefits

BC Ratio

-$83

0.5

-$42

0.7

-$251

0.7

-$74

0.5

-$16

0.6

-$123

0.7

-$589

0.7

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Power Sector Impacts

4. Power Sector Impacts
4.1. Impacts on Generation, Emissions, and Capacity
4.1.1. Overview
The IPM analysis allows us to draw several important conclusions about the impact of projected energy efficiency potential: Realization of projected energy efficiency potential would yield measurable differences in capacity expansion for the Southern power region by 2015 (See Table 42). This region includes almost the entirety of Georgia and portions of Florida, Alabama, and Mississippi. Because of the regional nature of power markets, it is unclear whether these capacity changes will occur in Georgia itself. The overwhelming majority of reduced power production would come from natural gas generators. See the tables on the next pages for a detailed account of which generation fuel types experience the greatest changes in generation and emissions. A large majority of generation reductions would come from units outside of Georgia. This finding reflects relatively low costs of generation in Georgia--generators in Georgia are not the marginal resources (See Table 43).

Table 42. Total 2015 Southern Region Capacity Reductions Resulting from Achievable Potential Scenarios

Scenario Minimally Aggressive Moderately Aggressive Very Aggressive

2015 Capacity Change (MW) 679 1,410 1,425

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Power Sector Impacts

Table 43. Generation Reductions from Achievable Potential Scenarios--GWh in Georgia, National GWh, and Percent of National GWh in Georgia

Scenario
Minimally Aggressive Moderately Aggressive Very Aggressive

Georgia GWh 1,207 2,874 4,749

2010 National GWh
3,457 9,023 13,065

% GWh in Georgia 35% 32% 36%

Georgia GWh 2.021 2,714 2,805

2015 National GWh
5,926 10,577 11,166

% GWh in Georgia 34% 26% 25%

Table 44. 2010 Generation and Emissions Reductions Within Georgia from Achievable Potential Scenarios--Total and Percent of State Power Sector

Scenario Minimally Aggressive Moderately Aggressive Very Aggressive

Generation (GWh)

1,207

0.7%

2,874

1.8%

4,749

2.9%

NOx (Thousand Tons)

0.5

0.3%

1.8

1.2%

2.7

1.9%

SO2 (Thousand Tons)

1.1

0.2%

4.8

0.8%

7.6

1.3%

CO2 (Thousand Tons)

634

0.6%

1,692

1.5%

2,710

2.4%

Table 45. 2010 Generation and Emissions Reductions Within Southern Region from Achievable Potential Scenarios--Total and Percent of Regional Power Sector

Scenario Minimally Aggressive Moderately Aggressive Very Aggressive

Generation (GWh)

1,616

0.6%

5,432

1.9%

8,707

3.1%

NOx (Thousand Tons)

0.5

0.2%

2.1

0.7%

3.2

1.1%

SO2 (Thousand Tons)

2.2

0.2%

6.0

0.6%

9.5

0.9%

CO2 (Thousand Tons)

805

0.4%

2,790

1.3%

4,510

2.1%

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Power Sector Impacts

Table 46. 2010 Generation and Emissions Reductions Within Georgia from Achievable Potential by Fuel Type (Minimally Aggressive)

Fuel Coal Gas Hydro Renewable/Other Nuclear Total

Generation (GWh)

142

0.1%

1,052

4.3%

-

-

13

2.0%

-

-

1,207

0.7%

NOx (Thousand Tons)

0.3

0.2%

0.2

8.0%

-

-

-

-

-

-

0.5

0.3%

SO2 (Thousand Tons)

1.1

0.2%

-

-

-

-

-

-

-

-

1.1

0.2%

CO2 (Thousand Tons)

145

0.1%

490

4.7%

-

-

-

-

-

-

634

0.6%

Table 47. 2010 Generation and Emissions Reductions Within Georgia from Achievable Potential by Fuel Type (Moderately Aggressive)

Fuel Coal Gas Hydro Renewable/Other Nuclear Total

Generation (GWh)

653

0.7%

2,208

9.0%

-

-

13

2.0%

-

-

2,874

1.8%

NOx (Thousand Tons)

1.4

1.0%

0.4

16.6%

-

-

-

-

-

-

1.8

1.2%

SO2 (Thousand Tons)

4.8

0.8%

-

-

-

-

-

-

-

-

4.8

0.8%

CO2 (Thousand Tons)

663

0.6%

1,029

9.0%

-

-

-

-

-

-

1,692

1.5%

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Power Sector Impacts

Table 48. 2010 Generation and Emissions Reductions Within Georgia from Achievable Potential by Fuel Type (Very Aggressive)

Fuel Coal Gas Hydro Renewable/Other Nuclear Total

Generation (GWh)

1,020

1.0%

3,716

15.1%

-

-

13

2.0%

-

-

4,749

2.9%

NOx (Thousand Tons)

2.2

1.6%

0.5

23.6%

-

-

-

-

-

-

2.7

1.9%

SO2 (Thousand Tons)

7.6

1.3%

-

-

-

-

-

-

-

-

7.6

1.3%

CO2 (Thousand Tons)

1,035

1.0%

1,675

16.1%

-

-

-

-

-

-

2,710

2.4%

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Power Sector Impacts
4.1.2. Generation and Emissions Impacts by State
The tables above show modest reductions in generation and CO2 emissions by 2010, with somewhat smaller reductions in SO2 and NOx. These results highlight a few important dynamics of the wholesale power sector:
Unlike SO2 and NOx emissions, which can be controlled by technologies specifically designed to reduce their release to the atmosphere, CO2 is an inevitable product of fossil fuel combustion. As a result, CO2 emissions closely mirror changes in generation, while changes in SO2 and NOx do not. Instead, SO2 and NOx are determined mostly by emission control regulations and technologies.
Because of existing cap and trade regulations, we do not expect overall reductions in electricity sales to impact SO2 and NOx emissions in the long term. Under the current SO2 and NOx cap and trade systems, regulators set an overall emissions cap for the power sector and allow power producers to trade emissions allowances to meet that cap cost-effectively. Emissions controls requirements are not specified for individual emitters. Instead, the power sector is permitted to trade allowances in order to meet an overall emissions cap in the way that is least expensive to the industry. If electricity sales are reduced as we have modeled here, emissions may fall temporarily, but power producers will eventually adjust and emit up to the allowed cap.
Moreover, cap and trade systems will only impact those states and regions that fall under the regulation. Wholesale electricity sales do not follow these boundaries, however. As a result, states not restricted by a particular emissions regulation may sell electricity to regulated states, possibly leading to greater emissions in the unregulated states. This "leakage" is particularly relevant to the Southern regional power market in which Georgia sits. The Southern region includes many emissions sources impacted by the NOx SIP Call regulations5 but is bordered by Florida, which is outside this regulated region. This issue in particular underscores the importance of regional approaches to energy efficiency and emissions regulation.

5 For this analysis and for others conducted for the EPA, IPM assumes that the NOx SIP Call applies in Georgia. However, note that though Georgia falls within the NOx SIP Call region for Phase II, two legal challenges are currently delaying its implementation. Nonetheless, the current NOx reductions in Georgia's non-attainment regions have achieved the vast majority of the emissions reductions that would be required under the NOx SIP Call. Also note that both Georgia and Florida will be covered by the recently adopted Clean Air Interstate Rule (CAIR), altering the applicable NOx regulations for both states.

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As we extend the time horizon to 2015, each of these issues becomes strongly evident. The figures below show 2010 and 2015 changes in generation and power sector emissions for the Minimally, Moderately, and Very Aggressive energy efficiency potential scenarios. The states individually represented are Georgia, Florida, Tennessee, South Carolina, Mississippi, and Alabama. Reductions for all other states are summed and presented in the "Other" category.
Each graph shows changes in generation or emissions as stacked bars, with the full stack representing the national total change. Some states show increases in generation or emissions, represented by bars extending above zero. The total net national change is the total positive state changes minus negative state changes--increases minus reductions. If the sum of decreases is greater than the sum of increases, there is a net national reduction in generation or emissions, and vice versa.
Figure 61 shows generation changes, which follow the reductions in energy sales for each achievable potential scenario. The states making up these reductions change substantially from 2010 to 2015, with Florida in particular reducing very little generation in 2010 and a great deal in 2015. Figure 62 shows CO2 emissions changes, which closely mirror reductions in generation. However, note that in Florida these CO2 emissions reductions are relatively smaller than generation reductions. The underlying cause of this is related to another point to be discussed below.

Generation (GWh) CO2 Emissions (Thousand Tons)

Figure 61. Changes in 2010 and 2015 Generation by State

2,000

2010 2015

2010 2015

0

-2,000

-4,000

-6,000

-8,000 -10,000 -12,000 -14,000

GA FL AL MS SC TN Other
Minimally Aggressive

Moderately Aggressive

2010 2015
Very Aggressive

Figure 62. Changes in 2010 and 2015 CO2 Emissions by State

1,000

2010 2015

2010 2015

2010 2015

0

-1,000

-2,000

-3,000

-4,000 -5,000 -6,000 -7,000

GA FL AL MS SC TN Other
Minimally Aggressive

Moderately Aggressive

Very Aggressive

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Figure 63 shows SO2 emissions changes. Reflecting what we would expect under the existing cap and trade system, there are some reductions in 2010, but these reductions are essentially zero by 2015.
Figure 64 shows NOx emissions changes. Note that there are national net NOx reductions in 2010 for all scenarios, but by 2015 there is a national net increase in emissions for all achievable potential scenarios. This phenomenon is the result of some of the issues presented above:
As noted earlier, most generation reductions occur outside of Georgia, meaning that Georgia is exporting electricity to neighboring states rather than backing down generation. Figure 61 (above) shows that Florida in particular is able to reduce generation by 2015.
By 2015, IPM projects that the reduction in Florida generation requirements would delay the construction of new combined cycle natural gas generating capacity. As a result, a portion of the generation that would have come from this new capacity is made up by older oil/gas steam generation. The newer combined cycle capacity would have a very low rate of NOx emissions per unit of generation, but the older oil/gas capacity emits at a much higher rate. Therefore, there is an overall increase in emissions for Florida relative to the Base Case in 2015.
Note that within the NOx SIP Call region, the net change in NOx emissions is essentially zero. Thus, the national increase in emissions is due to this "leakage" outside of the regulated area to Florida, highlighting the regional nature of power markets and the importance of corresponding regional approaches to energy efficiency and emissions regulation.

SO2 Emissions (Thousand Tons) NOx Emissions (Thousand Tons)

Figure 63. Changes in 2010 and 2015 SO2 Emissions by State

2010 2015
15

2010 2015

2010 2015

10

5

0

-5

GA

FL

-10

AL

MS

-15

SC

TN

Other -20

Minimally Aggressive Moderately Aggressive

Very Aggressive

Figure 64. Changes in 2010 and 2015 NOx Emissions by State

2010 2015
4

2010 2015

3

2

1

0

-1

GA

-2

FL

AL

-3

MS

SC

-4

TN

Other -5

Minimally Aggressive Moderately Aggressive

2010 2015
Very Aggressive

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4.2. Impacts on Prices and Compliance Costs
Each achievable potential scenario would cause a measurable reduction in Southern region wholesale electricity prices. Table 49 shows these percentage reductions for each scenario.
Based on avoided wholesale energy costs, the costs of implementing energy efficiency programs, and reductions in utility revenues resulting from lower sales, we estimated overall long-term impacts on average utility revenues within Georgia (See Table 50). We estimated this change in long-term average revenue based on the lifecycle revenue impact (LRIRIM), which represents the one-time change in average revenues required to match revenues to revenue requirements over the life of a program.
Note that despite lower wholesale prices and generation requirements, average revenues will still likely need to go up. Reduced costs from lower wholesale prices are offset by both the costs of implementing DSM programs and lost revenues associated with reduced energy sales.
Table 51 shows the effect of each achievable potential scenario on emissions allowances prices. As the table shows, there are very modest reductions in prices for the Moderately and Very aggressive scenarios and no impacts for the Minimally Aggressive scenario.

Table 49. Changes in Southern Region Electricity Wholesale Prices from Achievable Potential Scenarios

Scenario
Minimally Aggressive Moderately Aggressive Very Aggressive

Wholesale Prices (Southern Region)

2010

2015

-0.4%

-0.5%

-0.7%

-3.8%

-1.8%

-3.9%

Table 50. Changes in Georgia Electricity and Gas Average Revenue (LRIRIM)--Total One-Time Increase and Percent of Estimated 2005 Average Revenue

Scenario
Minimally Aggressive Moderately Aggressive Very Aggressive

Electricity

$/kWh

Percent

$0.001

0.9%

$0.002

2.5%

$0.003

3.9%

Natural Gas

$/Thm

Percent

$0.007

0.8%

$0.018

2.2%

$0.030

3.7%

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Table 51. Estimated Changes in Allowances Prices Due to Achievable Potential Scenarios

Minimally Aggressive SO2 Title IV Shadow Price NOx SIP Call Shadow Price
Moderately Aggressive SO2 Title IV Shadow Price NOx SIP Call Shadow Price
Very Aggressive SO2 Title IV Shadow Price NOx SIP Call Shadow Price

2010
-
-0.35%
-0.08% -0.35%

2015
-
-
-0.09% -

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4.3. Alternative "Risk Management" Analyses Reflecting Price of Emissions
4.3.1. Introduction
For this subtask, GEFA sought to uncover the impact of planned and potential emissions control scenarios on the cost-effectiveness of energy efficiency. We considered several emissions scenarios and modeled the impacts of these scenarios on wholesale electricity prices using IPM. These new wholesale price projections were compared to our Base Case wholesale prices and used as inputs to EEPM in order to reassess achievable potential for each emissions scenario.6 The following emissions regulations were considered:
Clean Air Interstate Rule (CAIR)--The recently adopted CAIR limits NOx and SO2 emissions in 28 eastern states and the District of Columbia. These regional reductions in SO2 are in addition to those reductions required by Title IV of the CAA. Finalized on March 10, 2005, CAIR is designed to reduce emissions of sulfur dioxide (SO2) and nitrogen oxides (NOx), contributors to the formation of fine particulates (PM2.5) and ground level ozone. The final CAIR requires annual SO2 and NOx reductions in 23 states and the District, while 25 states and DC are also subject to a NOx cap specifically for the ozone season. The rule establishes emissions budgets for NOx of 1.5 million tons in 2010, and for SO2 of 2.6 million tons, with further reductions required in 2015. Emissions banking is allowed, so actual emissions could differ from this level. Under CAIR, the states can achieve their required emission reductions either by requiring their power plants to participate in an EPA administered interstate cap-and-trade system or by implementing their own measures, including those that may target other sectors. For purposes of modeling however, it is assumed that all effected states participate in the regional trading program.
CAIR & Clear Air Mercury Rule (CAMR)--In addition to issuing the CAIR rule, on March 15, 2005, EPA finalized the Clean Air Mercury Rule (CAMR), implementing a cap and trade program for mercury emissions from utility power plants. Unlike the CAIR rule, the Mercury Rule is national in scope, setting a national level emissions cap applicable to all of the Nation's coal-fired boilers over 25 MW. When fully implemented, the Mercury Rule, in addition to CAIR's impacts, will limit mercury emissions to 15 tons a year, a reduction of about 70 percent from historic levels based on EPA estimates. Like CAIR, EPA has assigned each state and two tribes an emissions budget. Each state may choose how to meet the budget, including participating in a Federal trading program, implementing an in-state trading program, or facility-byfacility limits. For purposes of modeling, we assumed universal participation in the national trading program.
CAIR, CAMR, & CO2 Cap--GEFA also wanted to examine the potential implications of a mandatory carbon policy on the utility sector. No such policy has been proposed by the Bush Administration or EPA, though others have sponsored legislation including carbon cap-and-trade provisions. Nearly 100 legislative proposals have been introduced in Congress that specifically address global climate change and greenhouse gas emissions. In the current 109th Congress, several bills have been introduced. Some of these include:

6 Within EEPM, as projected avoided wholesale prices go up, more energy efficiency measures pass the cost-effectiveness screening. As a result, economic and achievable potential also increase.

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S.366: The Clean Power Act of 2003, which would require reductions of CO2, SO2, NOx, and mercury emissions from electric power plants. CO2 emissions would be reduced to 1990 levels by 2009. (See H.R.2042.) Sponsor: Sen. James M. Jeffords (I-VT) (19 cosponsors).
S.485: The Clear Skies Act of 2003, which would require reductions of power plant emissions of SO2, NOx, and mercury, but not CO2. This act would also exempt new power plants from the current requirement that they disclose their CO2 emissions. (See S.1844 and H.R.999.) Sponsor: Sen. James M. Inhofe (R-OK) (1 cosponsor). Introduced at the request of the Administration.
S.843: The Clean Air Planning Act of 2003, which would require reductions in CO2, SO2, NOx, and mercury emissions from electric power plants. CO2 emissions would be reduced to 2006 levels by 2009 and to 2001 levels by 2013. (See H.R.3093.) Sponsor: Sen. Thomas R. Carper (D-DE) (3 cosponsors).
H.R.2042: The Clean Smokestacks Act of 2003, which would require reductions of CO2, SO2, NOx, and mercury emissions from electric power plants. CO2 emissions would be reduced to 1990 levels by 2009. (See S.366.) Sponsor: Rep. Henry A. Waxman (D-CA) (97 cosponsors).
In the 109th Congress, the Clean Smokestacks Act of 2005 (introduced in House) [H.R.1451.IH] and the Clean Power Act of 2005 (introduced in Senate) [S.150.IS] have been reintroduced.
In order to assess the potential impact of a carbon program, ICF analyzed a hypothetical carbon policy. For this analysis, we evaluated the requirement that CO2 emissions from the power sector be capped at current or near-term year levels by 2009, and be brought down to some past historic level in the future. Specifically, we examined a policy where emissions are limited to 2007 levels beginning in 2009 and to 2001 levels by the year 2013.
This policy was not intended to represent any particular bill or proposal, though it does reflect the general level of carbon reduction levels that have been proposed in some bills in the past. For example, this policy is similar to those called for under the Clean Air Planning Act. Despite the relationship to aspects of past legislative proposals, it is important to note that we have not attempted to model some of the detailed provisions of this or other acts. For example, the Clean Air Planning Act allows that off-system emissions reductions can be used to satisfy the reductions required under the cap. This provision could have a significant impact on the costs of the policy, as some low cost offset emission reduction options are available. Moreover, the proposal calls for output-based allocation of permits for carbon, which could also impact the cost and price impacts of the policy. We did not model these details, but simply imposed the emissions caps noted above and required that emission reductions come from the power sector.
Projected avoided energy costs from this analysis were examined and input into EEPM to assess the potential impact of each emissions policy scenario on the cost-effectiveness of energy efficiency.

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4.3.2. Wholesale Price Impacts
As noted above, we modeled a hypothetical carbon policy requiring that CO2 emissions in 2009 return to 2007 levels. This represents a 6.5 percent reduction relative to a scenario without CAIR or CAMR and a 5.6 percent reduction relative to a scenario with CAIR and CAMR. The policy also requires that emissions return to their 2001 levels by 2013. This 2013 target requires a greater level of reductions. By 2015, the regulation requires a 12.7 percent reduction relative to a scenario without CAIR or CAMR, and an 11.6 percent reduction relative to a scenario including CAIR and CAMR. Note that in both years, CAIR and CAMR rules reduce carbon emissions by about 1 percent.
Nationally, the primary means of meeting the reductions is to shift generation away from coal-fired resources to lower emitting natural gas-fired resources. In 2015, for example, coal-fired generation declines from 50 percent of the generation mix in the Base Case to 40 percent of the mix under the CAIR, CAMR, and CO2 policy run. Conversely, gas-fired generation increases to 32 percent of the mix under the CAIR, CAMR, and CO2 policy from 23 percent in the Base Case.
This increased reliance on natural gas-fired generation increases marginal energy prices. This is a result of increases in the amount of time that gas-fired generation is on the margin (and therefore setting the price) and also changes in the cost of capacity. The net effects are substantial increases in marginal energy costs. For example, on a national level, we estimate that 2010 marginal "all-in" energy prices would increase by 47 percent. Note that this is not a direct indication of the increase in retail electricity prices that customers would experience. Wholesale prices are only one component of total electricity prices, thus the retail rate impact would likely be smaller. Wholesale price effects dampen over time, with a 36 percent increase in wholesale prices in 2015.
The Southern power market region, within which Georgia sits, experiences similar increases--slightly higher in the first year of the policy (51 percent) and lower in 2015 (28 percent). This result reflects the region's slightly greater dependence on coal relative to the nation as a whole. Table 52 shows our projections of Southern region wholesale price changes associated with each emissions control scenario relative to the Base Case.

Table 52. Percentage Change in 2010 and 2015 Southern Region Wholesale Power Prices for Emissions Control Scenarios Relative to Base Case

Scenario CAIR CAIR & CAMR CAIR, CAMR, & CO2 Cap

2010 3.1% 3.3% 50.5%

2015 2.3% 2.7% 27.5%

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4.3.3. Energy Efficiency Potential Impacts
The wholesale price increases resulting from the emissions controls scenarios described above have a modest but notable impact on our projections of achievable potential (See figures below and Table 53 on the following page):
CAIR--The CAIR scenario yields increases in 2010 electricity sales savings potential of between 1.2 and 2.2 percent and increases in 2010 peak demand savings potential of between 4.5 and 8.9 percent relative to the Base Case.
CAIR & CAMR--The CAIR & CAMR emissions scenario has an essentially identical impact on achievable potential.
CAIR, CAMR, & CO2 Cap--The CAIR, CAMR, and CO2 cap scenario causes a somewhat larger increase in achievable potential, with increases of between 5.4 and 5.7 percent of 2010 electricity sales savings potential and between 8.4 and 12.1 percent of 2010 peak demand potential relative to the Base Case.
As illustrated in previous figures in this report, the figures below show our projections of achievable potential in the context of Georgia baseline energy forecasts. The bands below the baseline forecasts represent the full range of energy efficiency potential estimates under the Base Case and the three alternative emissions control scenarios. In general, the upper bound of each range reflects the Base Case emissions scenario, and the lower bound reflects the CAIR, CAMR, & CO2 cap scenario.

Electricity Sales (MWh) Peak Demand (MW)

Figure 65. Range of Achievable Potential Outcomes for Emissions Control Scenarios (Electricity Sales)

165,000,000 160,000,000 155,000,000 150,000,000

Minimally Aggressive Moderately Aggressive Very Aggressive Base Forecast

145,000,000

140,000,000

135,000,000

130,000,000

125,000,000

120,000,000 2003

2005

2007

2009

2011

2013

2015

Figure 66. Range of Achievable Potential Outcomes for Emissions Control Scenarios (Peak Demand)

29,500 28,500 27,500

Minimally Aggressive Moderately Aggressive Very Aggressive Base Forecast

26,500

25,500

24,500

23,500

22,500 2003

2005

2007

2009

2011

2013

2015

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Two results in particular stand out in the detailed results (See Table 53):
The effect of the emissions scenarios are more pronounced for peak demand savings potential. Coincidentally, many of the energy efficiency measures that fail the cost-effectiveness screen by a small margin for the Base Case avoided costs scenario impact the air conditioning end use. Thus, when avoided costs increase for the various emissions controls scenarios, these air conditioning measures pass the screen and yield substantial peak impacts.
By 2015, the projected increases in peak demand savings potential associated with the emissions scenarios are large relative to achievable potential for the Base Case--between 20 and 45 percent. This result also reflects the nature of the measures that pass the cost-effectiveness screen under the emissions controls scenarios. Many of the air conditioning measures noted above are larger pieces of equipment such as 15 SEER residential air conditioners and commercial high-efficiency chillers. These types of equipment have large peak impacts but are typically installed only when old equipment is replaced, explaining the relatively larger impacts in later years.

Table 53. Percentage Increases in 2010 and 2015 Achievable Potential for Emissions Control Scenarios Relative to Base Case

Scenario
CAIR Minimally Aggressive Moderately Aggressive Very Aggressive
CAIR & CAMR Minimally Aggressive Moderately Aggressive Very Aggressive
CAIR, CAMR, and CO2 Cap Minimally Aggressive Moderately Aggressive Very Aggressive

Electricity Sales

2010

2015

1.2%

4.3%

1.7%

6.7%

2.2%

8.0%

1.2%

4.3%

1.7%

6.7%

2.2%

8.0%

5.4%

6.1%

5.7%

7.6%

5.7%

8.6%

Peak Demand

2010

2015

4.5%

20.8%

6.7%

36.1%

8.9%

43.4%

4.5%

20.8%

6.7%

36.1%

8.9%

43.4%

8.4% 10.4% 12.1%

22.0% 36.3% 43.3%

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The Public Benefits of Energy Efficiency
5. The Public Benefits of Energy Efficiency
5.1. Public Health Impacts
5.1.1. Introduction
A variety of human and environmental effects have been associated with power sector emissions: Nitrogen Oxides (NOx) Contribute to ground-level ozone, acid rain, and particulate formation. Ozone and particulates are responsible for a host of respiratory problems. Ozone can damage vegetation and reduce crop yields. Acid rain damages fish habitat and causes deterioration of exposed structures. Particulates contribute to haze. Contribute to water quality deterioration, as increased nitrogen loading in bodies of water alters the chemical balance of nutrients vital to plant and animal life. The problem is particularly acute for estuaries. Contribute to global warming. Form toxic chemicals in the air as NOx reacts with a variety of organic compounds. Sulfur Dioxide (SO2) Contributes to acid rain and particulate formation. Contributes to respiratory and cardiovascular problems. Carbon Dioxide (CO2) Contributes to global warming.
The geographical distribution of pollutants' health impacts are difficult to predict given the complex atmospheric interactions that determine formation and ambient concentrations of ozone and particulates in any specific region. Tracing the impacts of emissions changes from power plants typically requires the use of sophisticated air quality models.

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Quantification of health effects involves a number of inputs, including epidemiological effect estimates, baseline incidence and prevalence rates, potentially impacted populations, and estimates of changes in ambient concentrations of air pollution. Although there are limitations to its capability, we used US EPA's current Beta version of the COBRA model to estimate public health impacts. These estimates were based on the changes in emissions resulting from achievable energy efficiency for the Base Case emissions scenario and COBRA's internal structure for translating these emissions changes into impacts on public health.
5.1.2. Emissions Impacts in Context
The results of the COBRA analysis indicate that health benefits resulting from the projected pollutant emissions reductions are likely to be slight.
This conclusion is not surprising if one considers the magnitude of our projected emissions impacts relative to those estimated for other types of policy interventions. Table 54 shows projected emissions reductions under the Very Aggressive scenario and from implementation of the Clean Air Interstate Rule (CAIR), formerly known as the Interstate Air Quality Rule (IAQR). The table shows 2010 Very Aggressive scenario reductions for Georgia both in absolute terms and as a percentage of total projected 2010 CAIR emissions reductions. Note that our COBRA-based estimates of health impacts are not dissimilar from what we would approximate by simply scaling down EPA's projected health impacts under CAIR to fit our achievable potential scenario emissions reductions.

Table 54. 2010 Emissions Reductions for CAIR and Very Aggressive Scenario (Thousand Tons)

NOx

SO2

CAIR Georgia

90

200

Achievable Potential Georgia

2.8

7.6

Achievable Potential % of CAIR Georgia

3.3%

3.8%

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5.2. Impacts on Water Consumption
We have considered two important connections water has to energy efficiency:
Water is withdrawn in large quantities from various bodies of water to cool electric power generators. In fact, this use is the one of the greatest contributors to water withdrawals in the US. Much of the water withdrawn is returned to its source at a higher temperature, but a proportion is consumed through evaporation.
Some energy efficiency measures, such as low-flow showerheads and efficient dishwashers, also reduce domestic water consumption.
Table 55 shows the impacts of both of these effects on water consumption in Georgia. Table 56 details the influence of energy efficiency on power sector water withdrawals and consumption, where consumption is the difference between water withdrawals and discharges.

Table 55. Reductions in Power Sector and End Use Water Consumption in Georgia

Scenario
Power Sector Minimally Aggressive Moderately Aggressive Very Aggressive
End Use Minimally Aggressive Moderately Aggressive Very Aggressive
Total Minimally Aggressive Moderately Aggressive Very Aggressive

Consumption (Million Gallons per Day)

2010

2015

58

121

123

155

224

159

3

3

8

4

10

4

61

124

131

159

234

164

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Table 56. Changes in Power Sector Water Withdrawals and Consumption in Georgia and Total Southern Region

Scenario
Georgia Minimally Aggressive Moderately Aggressive Very Aggressive
Southern Region Minimally Aggressive Moderately Aggressive Very Aggressive

Withdrawals

2010

2015

-1.3% -3.5% -6.0%

-2.0% -2.6% -2.6%

-0.8% -2.1% -3.8%

-1.2% -1.5% -1.5%

Consumption

2010

2015

-2.9% -6.1% -11.1%

-4.8% -6.2% -6.4%

-2.8% -5.9% -10.8%

-4.5% -5.8% -5.9%

5.3. Economic Development Impacts
5.3.1. Introduction
Investment in energy efficiency typically represents an economic stimulus. This stimulus is the result of direct spending on energy efficiency measures and the increase in net consumer disposable income generated by energy savings. Moreover, these direct impacts tend to have a multiplying effect so that $1 spent on an energy efficiency measure translates into a greater benefit as the impact ripples through the economy.
Efficiency measures requiring local labor for installation tend to have positive local economic effects. Purchases of energy-efficient technologies such as high-efficiency air conditioners have less of a beneficial impact since the equipment often is produced outside of the local economy.
However, energy efficiency programs also can impose some costs on the state economy. The reduction in sales of electricity and natural gas slow the growth of the utility sector. In addition, the costs of energy efficiency programs require a funding source. Though benefits of the programs outweigh costs over the entire study period, these program costs are incurred at the time energy efficiency measures are implemented, while savings gradually accumulate over time. The need to pay these upfront costs, in effect, reduces other spending and investment. These negative impacts also ripple through the economy with similar amplifying effects.

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The economic impacts of the three energy efficiency scenarios were simulated by the University of Georgia's Carl Vinson Institute of Government using the Georgia Economic Modeling System (GEMS). This model is one of the most sophisticated regional economic models available and provides the ability to estimate the investment response of the economy to changes in direct spending.
We modeled the economic impacts of the three energy efficiency scenarios under a variety of program funding assumptions. While the magnitude of the resulting impacts varied for each set of assumptions, GEMS projected a net increase in employment and personal income over the study period for all assumptions.
5.3.2. Results
The following set of charts and tables summarizes the results of the GEMS analysis. These results should be considered illustrative and not definitive given that economic impacts are quite sensitive to both input assumptions and choices regarding how inputs should be represented within the GEMS model.
Employment and Personal Income
The GEMS analysis suggests that, relative to the base case forecast, employment and personal income would grow less rapidly in the early years of the efficiency programs and more rapidly in later years. This phenomenon is typical of investment programs in which costs are incurred immediately, while benefits accrue over time. Employment and personal income effects turn positive as the stimulus from the re-spending of consumer net savings begins to outweigh the drag caused by the need to pay for the programs and utility lost revenues. By the end of the study period in 2015, the efficiency investments would generate between roughly 1,500 and 4,200 additional jobs.
Sectors expected to experience the largest increase in employment include construction and retail. Sectors that likely would see the greatest drag on employment include public utilities and wholesale.
The employment impacts should be read as the equivalent of net person-years of employment per year and are not additive over time. More importantly, note that none of the scenarios cause Georgia to lose jobs. The negative net annual employment figures in the early years of the analysis do reduce the rate of job growth, but this early effect is more than offset as the benefits from energy efficiency investments come to fruition and cause increased employment (See Figure 67).

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Gross State Product and State Revenue
Because energy efficiency replaces a market activity (the purchase of energy resources) with a fundamentally non-market activity (energy conservation), investment in energy efficiency tends to slightly reduce the rate of increase in gross state product.
Note that the projected impact on state product growth is negative even as the employment impact turns positive. This dichotomy is due to an underlying change to the composition of the Georgia economy. Specifically, economic activities that involve a great deal of capital in production, primarily within the utility industry itself, are being replaced with economic activities that involve more human capital but use less capital and produce less output.
Revenue impacts for state and local governments are also projected to be negative. However, the hypothetical energy efficiency programs also cause a reduction in government expenditures that is more than enough to offset all revenue decreases throughout the forecast period.

Figure 67. Impacts on Net Annual Employment Relative to Base Case Forecast (Average of All Funding Scenarios)

6,000

4,000

Net Annual Employment

2,000

0

-2,000

-4,000 -6,000 -8,000

Minimally Aggressive Moderately Aggressive Very Aggressive

-10,000 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

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Table 57. Economic Development Impacts (Average of All Funding Scenarios)

Minimally Aggressive Employment Personal Income (Millions of Dollars) Gross State Product (Millions of Dollars)
Moderately Aggressive Employment Personal Income (Millions of Dollars) Gross State Product (Millions of Dollars)
Very Aggressive Employment Personal Income (Millions of Dollars) Gross State Product (Millions of Dollars)

2006
-650 -$33 -$37
-2,432 -$118 -$134
-5,197 -$242 -$279

2010
222 -$17 -$101
-693 -$108 -$341
-1,491 -$168 -$546

2015
1,487 $48 -$160
3,323 $111 -$342
4,159 $157 -$396

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The Public Benefits of Energy Efficiency

5.3.3. Summary of Economic Impact Analyses from Other States & Regions
A number of other studies of energy efficiency potential prepared over the past several years have attempted to provide estimates of the economic impacts of energy efficiency investments. The methods used to estimate macroeconomic impacts vary considerably. Some have relied on basic input-output models such as IMPLAN to provide estimates of impacts, while others have used regional economic simulation models such as REMI.
We reviewed several studies for which comparable net energy cost savings and employment impact estimates were available in an effort to place the GEMS estimates in context. Based on our comparison of a simple index of employment impact per dollar of net benefits, we find that the GEMS estimates provided here are in line with those generated by other studies. Table 58 compares the range of GEMS results for the 2015 Moderately Aggressive scenario to the results of two similar studies. The range of GEMS results presented covers Cases 1-3 described above.
Note that the SWEEP and ACEEE analyses were prepared using IMPLAN, an input-output model that does not contain many of the elements of a regional simulation model such as GEMS. Nevertheless, the results are quite similar and suggest that the proportional employment benefits of energy efficiency in Georgia would be not unlike those projected for other regions.

Table 58. Comparison of Economic Development Impacts Results for Several Recent Energy Efficiency Potential Studies

Study
Assessment of Energy Efficiency Potential in Georgia SWEEP 20027 ACEEE-Illinois 19988

Employment Impact Per $ Million Net Benefit
1.6 - 2.8 2.07 1.54

7 Southwest Energy Efficiency Project, The New Mother Lode: The Potential for More Efficient Electricity Use in the Southwest, November 2002.
8 Marshall Goldberg, Martin Kushler, Steven Nadel, Skip Laitner, Neal Elliott and Martin Thomas, Energy Efficiency and Economic Development in Illinois, American Council for an Energy Efficient Economy, December 1998.

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Conclusions

6. Conclusions
Overall, the potential for increased energy efficiency in Georgia is large, with a wide range of associated positive impacts on the economy and environment.
Prudently pursuing this energy efficiency will be a complex challenge. Our goal in completing this study has been to explore the nuances of capturing Georgia's achievable energy efficiency potential. To that end, we hope that our findings will be a valuable guide as stakeholders balance the benefits and costs of various energy efficiency strategies.
6.1. An Untapped Resource
The results of this study allow us to draw the following core conclusions: Significant opportunity exists to motivate greater investment in energy efficiency across all Georgia market sectors over the next decade. Capture of this energy efficiency would cost Georgia less than supplying the same amount of energy. Energy efficiency would reduce the number of electric power plants required to meet Georgia's electricity demand. Energy efficiency would have a moderate positive impact on the environment due to reduced pollutant emissions and water consumption. Increasing investment in energy efficiency would have modest positive impacts on Georgia's long-term employment growth and modest negative impacts on gross state product.
6.2. Challenges
Though significant cost-effective energy efficiency potential exists, implementing policies and programs to realize that potential will require dedicated efforts from multiple stakeholders sustained over many years. As noted above, we have assessed a number of possible approaches to meeting this challenge and summarized the results in an accompanying report--Strategies for Capturing Georgia's Energy Efficiency Potential.
There are several overarching questions that Georgia will face as it considers further investment in energy efficiency: What are appropriate energy efficiency goals for Georgia? This study should provide valuable guidance on this question, but the state's ultimate goals will need to balance the concerns and interests of a wide range of stakeholders.
What is the best organizational structure for funding and administering these energy efficiency programs? A wide spectrum of alternative strategies for program administration has developed across the country. Forging the optimal or most practicable solution for Georgia will require careful consideration of several issues and factors: Proven effectiveness of various organizational structures for reaching energy efficiency goals

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Conclusions
Current energy regulatory and utility market structure in Georgia Aspects of administrative and funding structures that will make them attractive to Georgia ratepayers, utilities, and regulators How will program implementers design programs that effectively engage energy customers in Georgia? A wealth of knowledge and experience has developed around how programs can cost-effectively bring energy efficiency to a wide range of customer markets. Nonetheless, program implementers will need to exhibit great flexibility and ingenuity to design and implement effective energy efficiency programs in a market unaccustomed to such interventions. It is clear that none of these questions will have a simple answer. All stakeholders will need to voice their concerns and be prepared to compromise in order to develop strategies that appropriately balance the needs of all Georgians. However, based on the experiences of other states, it is also clear that such a process can succeed in delivering the benefits of energy efficiency to a multiplicity of parties. If Georgia elects to more aggressively pursue energy efficiency, the state will stand to realize many of those benefits.

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