Connecticut Natural Gas Commercial and Industrial Energy-Efficiency Potential Study

Transcription

1 Connecticut Natural Gas Commercial and Industrial Energy-Efficiency Potential Study Final Report Experience you can trust.

2 Copyright 2009, KEMA, Inc. The information contained in this document is the exclusive, confidential and proprietary property of KEMA, Inc. and is protected under the trade secret and copyright laws of the U.S. and other international laws, treaties and conventions. No part of this work may be disclosed to any third party or used, reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying and recording, or by any information storage or retrieval system, without first receiving the express written permission of KEMA, Inc. Except as otherwise noted, all trademarks appearing herein are proprietary to KEMA, Inc. Experience you can trust.

3 Table of Contents 1. Executive Summary Scope and Approach Limitations of the Study Results Aggregate Results Results by Sector Introduction Overview Study Approach Layout of the Report Methods and Scenarios Characterizing the Natural Gas Energy-Efficiency Resource Defining Natural Gas Energy-Efficiency Potential Summary of Analytical Steps Used in this Study DSM ASSYST Analytical Steps Total Economic, Total Achievable and Instantaneous Program Achievable Analytical Steps Baseline Data and Results Overview Commercial Industrial DSM Potential Results Technical and Economic Potential Energy-Efficiency Supply Curves Key Measures Total Economic, Achievable and Instantaneous Program Achievable Potential Program Funding Scenarios Comparison of Potential Results List of Exhibits: Table 1-1 Summary of Energy and Peak Demand Savings for Potentials and Program Funding Scenarios Instantaneous and in Connecticut Natural Gas i

4 Table of Contents Table 1-2 Comparison Between 2009 Program Plan and Program Funding Scenario Results1-9 Table 4-1 Commercial Baseline Consumption Summary Table 4-2 Industrial Baseline Consumption Summary Table 5-1 Commercial Existing Top Twenty Measures by Economic Potential (Dth) Table 5-2 Industrial Top Twenty Measures by Economic Potential (Dth) Table 5-3 Values for Adjustment Factors Applied to Economic Potential Table 5-4 Comparison Between 2009 Program Plan and Program Funding Scenarios Table 5-5 Summary of Program Funding Scenario Potential Results Table 5-6 Measure-specific Potential Results for Commercial Sector (Cumulative to 2018) Annual Dth Table 5-7 Measure-specific Potential Results for Industrial Sector (Cumulative to 2018) Annual Dth Table 5-8 Instantaneous Savings Potential Annual Dth Table 5-9 Peak Day Demand Savings Dth per day Figure 1-1 Cumulative Energy Savings Potentials and Program Funding Scenario Savings in 2018 Dth per year Figure 1-2 Achievable Energy Savings: All Sectors Figure 1-3 Benefits and Costs of Energy-Efficiency Savings * Figure 1-4 Net Achievable Energy Savings by 2018 by Sector Dth per Year Figure 1-5 Commercial Economic Gas Savings Potential by End Use (2018) Current Funding Scenario Figure 1-6 Industrial Economic Gas Savings Potential by End Use (2018) Current Funding Scenario Figure 3-1 Conceptual Framework for Estimates of Fossil Fuel Resources Figure 3-2 Conceptual Relationship among Energy-Efficiency Potential Definitions Figure 3-3 Conceptual Overview of Study Process Figure 4-1 Firm Natural Gas Usage Breakdown Connecticut Figure 4-2 Commercial Natural Gas Usage by Building Type Figure 4-3 Commercial Natural Gas Usage by End Use Figure 4-4 Distribution of Heating Systems by Building Type Figure 4-5 Applicability of Commercial Heating Energy Efficiency Measures Figure 4-6 Saturations of Commercial Water Heating Energy Efficiency Measures Connecticut Natural Gas ii

5 Table of Contents Figure 4-7 Industrial Natural Gas Consumption by Industry Figure 4-8 Industrial Natural Gas Consumption by End Use Figure 4-9 Industrial Other Natural Gas Energy Use Detail Figure 5-1 Technical and Economic Potential by Sector (2018) Cumulative Dth per year Figure 5-2 Cumulative Technical and Economic Potential by Sector (2018) Percentage of Current Funding Scenario Energy Use Figure 5-3 Commercial Economic Gas Savings Potential by End Use (2018) Figure 5-4 Industrial Economic Gas Savings Potential by End Use (2018) Figure 5-5 Natural Gas Supply Curve Figure 5-6 Comparison of Potentials Based on Existing/New Construction Mix in First Year of Program Figure 5-7 Comparison of Potentials Based on Existing/New Construction Mix in Tenth Year of Program Figure 5-8 Program Funding Scenario Energy Savings: All Sectors Figure 5-9 Benefits and Costs of Energy-Efficiency Savings * Figure 5-10 Program Funding Scenario Energy Savings: Commercial Sector Existing Buildings Figure 5-11 Program Funding Scenario Energy Savings: Commercial Sector New Construction Figure Figure Figure 5-14 Program Funding Scenario Potential Energy Savings: Industrial Sector Figure 5-15 Industrial Net Energy Savings Potential - End Use Shares (2018) Current Funding Scenario Figure Figure 5-17 Instantaneous Savings Potential Annual Dth Figure 5-18 Energy Savings Based on Mix of Existing and New Construction in 2018 Annual Dth Figure 5-19 Peak Day Demand Savings Based on Mix of Existing and New Construction in 2018 Dth per day Connecticut Natural Gas iii

6 1. Executive Summary This study assesses the natural gas energy-efficiency potential for the commercial and industrial sectors in Connecticut, served by Yankee Gas Services Company (Yankee Gas), the Southern Connecticut Gas Company (Southern Connecticut Gas) and Connecticut Natural Gas Corporation. The major objective of this study was to identify and characterize the remaining cost-effective natural gas efficiency-potential in Connecticut and to estimate the amount of savings achievable through energy efficiency programs. 1.1 Scope and Approach In the study, seven levels of energy-efficiency potential are estimated: Technical Potential, defined as the complete penetration of all measures analyzed in applications where they were deemed technically feasible; Initial Economic Potential, defined as the technical potential of those energy-efficiency measures that are cost-effective when compared to supply-side alternatives, given current technologies and costs; Total Economic Potential is an estimate of the technical potential of energy-efficiency measures that are expected to be cost-effective taking into account emerging technologies and reductions in measure costs that occur as technologies become more mainstream; Achievable Potential, which is an estimate of maximum energy efficiency savings from all sources; Instantaneous Program Achievable Potential, which is an estimate of how much energy efficiency programs can save, taking into account the simultaneous effects of building codes, standards, and outside of program savings. Two levels of Program Funding Scenario Savings, the amount of savings that would occur in response to specific program funding and measure incentive levels. Program interventions include end user awareness and education activities and various types of funding to reduce the cost of energy efficiency measures in order to encourage investment in these efficient equipment and practices. We estimate program scenario savings for a Current Program Funding Scenario that approximates the 2009 Program Plan budget in its first year; and Connecticut Natural Gas 1-1

7 an Expanded Program Funding Scenario that comes as close as possible, subject to the limitations of stock turnover and the absence of emerging technologies, to the instantaneous program achievable potential. In addition, we calculate the Naturally Occurring Potential, which refers to the amount of savings estimated to occur as a result of normal market forces. That is, in the absence of any utility or governmental intervention. Achievable potentials and program scenario savings are presented net of naturally occurring potential, which we refer to as Net Savings. We explicitly present naturally occurring potential only when presenting gross savings potential. The study estimates both energy savings and peak day demand savings for each of these potential scenarios. Peak Day Demand is defined as the maximum daily quantity of gas delivered to customers over a consecutive period of 24 hours. The scope of this study includes new and existing commercial buildings and existing industrial buildings. The focus of the study was on the ten-year, period. Given the near to mid-term focus, the study was restricted to energy-efficiency measures that are presently commercially available. The method used for estimating potential is a bottom-up approach in which energy efficiency costs and savings are assessed at the customer segment and energy-efficiency measure level. Cost effectiveness is based on the Total Resource Cost Test (TRC test), a benefit-cost test that compares the value of avoided energy costs to the costs of energy-efficiency measures (a full definition of the TRC test is provided in Appendix A, section 1.3). For cost-effective measures, program savings potential is estimated as a function of measure economics, incentive levels, and program marketing and education efforts. The modeling approach was implemented using KEMA s DSM ASSYST TM model. This model allows for efficient integration of large quantities of measure, building, and economic data in the determination of energy efficiency potential. In order to conduct the energy efficiency potential study many different types of data are required, including: measure data (such as costs, savings, and current saturation levels), building/market data (such as building stocks and end use saturation and consumption levels), and economic data (such as avoided costs, inflation rates, and discount rates). These data were developed from a number of different secondary sources, including natural gas usage and avoided cost data provided by the three Connecticut gas utilities, program data for Connecticut, the U.S. DOE Commercial Building Energy Consumption Survey (CBECS), the California Commercial End Use Survey (CEUS), the California Database for Energy Efficiency Resources Connecticut Natural Gas 1-2

8 (DEER), the Connecticut Department of Labor, the Economic Census, Energy Trust of Oregon, the New York State Energy Research and Development Authority (NYSERDA), and various technology-specific internet sources. 1.2 Limitations of the Study This report is not a program implementation plan. It does not contain a marketing plan, training and outreach plan, evaluation plan, staffing estimates, or detailed program budgets. The focus of the program scenarios is not on next year (2010), but on the full ten-year forecast period. The results represent a good initial estimate of the savings that can be achieved at different budget levels, but the report does not lay out how to achieve those savings. The scenarios are neither a prediction of nor a recommendation for future program budgets. However, the scenarios can serve as a starting point for a detailed analysis by program planners in the process of developing a program implementation plan. While the DSM ASSYST model simulates program interventions, it is still a model. That is, it is a simplified mathematical representation of the real world, based on the best available data. While it is designed to provide a general, aggregate forecast of potential savings, and to highlight measures with high savings potentials for possible inclusion in a program, it should not be taken to be an infallible prediction of the conditions that implementers will encounter under actual program conditions. Among other factors: Measure costs may be higher or lower than modeled due to regional cost variations or unidentified hidden costs Market barriers 1 may be higher or lower than modeled Implementers may target their marketing dollars differently than the model does (e.g. by targeting specific types of contractors) Evaluations may find that the actual savings for promising measures are less than estimated (e.g. due to takeback 2 ). 1 For more details on market barriers, see Appendix A, Table One example of takeback is if demand-controlled ventilation (DCV) were installed in an existing building where the existing ventilation system did not meet code for air changes per hour (ACH). With DCV, the ventilation rate would be increased, reducing savings and possibly even increasing total energy use (while improving air quality). Connecticut Natural Gas 1-3

9 1.3 Results The following results are based on avoided gas costs from the report Avoided Energy Supply Costs in New England: 2007 Final Report, prepared by Synapse Energy Economics, Inc. This report was provided to KEMA by representative of Yankee Gas and Southern Connecticut Gas to be used as the source for avoided costs for this study. Avoided costs begin at $1.13 per therm in Aggregate Results Technical potential is estimated at 11,600,000 dekatherms (Dth) per year. Eighty-one percent of this potential, 9,400,000 Dth per year, is estimated to be economically viable. Net savings in 2018 for the current program funding scenario is 1,140,000 Dth per year, representing the results of program activity for the entire period. Under the expanded program funding scenario, net savings in 2018 reaches 5,730,000 Dth per year. Figure 1-1 compares the estimates of efficiency potential created for this report, including technical, initial and total economic, total achievable, instantaneous program achievable, and two alternate program funding scenarios. 3 Comparisons are made based on the mix of existing and new construction in the tenth year of the program by weighting the instantaneous program potentials. Table 1-1 shows both the unweighted (2009 instantaneous) and the weighted 2018 savings. The program funding scenario results are included with the weighted 2018 results. Figure 1-2 shows our estimates of savings for the program funding scenarios over time. This figure shows naturally occurring savings that are expected to proceed in the absence of programs, and incremental savings from each of the two program scenarios that were developed for the study. As shown, savings potential tends to increase at a decreasing rate, over time. In the early years, programs can target the most cost-effective and easy-to-achieve measures and markets. Over time, the supply of these opportunities is expected to decline (in the absence of significant new technologies), and the programs must penetrate harder-to-reach markets and influence end users to adopt less attractive measures. 3 Because the achievable and program potentials are shown net of naturally occurring potential, naturally occurring potential is not explicitly included in the chart. Connecticut Natural Gas 1-4

10 Figure 1-1 Cumulative Energy Savings Potentials and Program Funding Scenario Savings in 2018 Dth per year 12,000,000 11,568,192 Potential Dth/yr Savings by ,000,000 8,000,000 6,000,000 4,000,000 2,000, ,396,208 10,100,924 8,585,785 Technical Economic Total Economic Total Achievable 6,626,397 Program Achievable 5,729,716 Expanded Funding Scenario 1,137,157 Current Funding Scenario Note: The expanded funding scenario and current funding scenario savings are savings potential in 2018 due to program activity from Other potentials are instantaneous potentials (that is, they assume that all of the floorspace that is going to convert under the scenario converts instantaneously) but have been adjusted to represent 10 years of new construction and decay of the existing building stock. Technical savings refers to the complete penetration of all measures analyzed in applications where they were deemed technically feasible from an engineering perspective. Initial economic savings includes savings for all measures found to be cost effective in the application analyzed. Total economic savings includes initial economic savings plus 7.5 percent, to account for emerging technologies and measure cost reductions not captured in the model. Total achievable savings reduces total economic savings by 15 percent to account for savings that are not achievable. Program achievable savings excludes savings due to building codes (35% in new construction) and outside-of-program savings. The expanded funding scenario sets incentives to 100 percent of incremental measure costs with a first-year budget of $26,800,938. The first year of the current funding scenario approximates the Connecticut 2009 Gas Program Plan as explained in section 5.3. Connecticut Natural Gas 1-5

11 Sector Table 1-1 Summary of Energy and Peak Demand Savings for Potentials and Program Funding Scenarios Instantaneous and in 2018 Base Gas Use & Peak Day Demand a Savings Potential if All Floorspace that was Going to Convert Under the Scenario Converted Simultaneously Technical Potential b Initial Economic Potential c Total Economic Potential d Total Achievable Potential e Program Achievable Potential f 2009 Instantaneous Turnover Potential Total Energy Savings (Dth/yr) 41,644,310 12,161,300 9,776,986 10,510,260 8,933,721 7,312,757 Savings % of Base 29% 23% 25% 21% 18% Savings % of Tech. - 80% 86% 73% 60% Savings % of Total Economic % 70% Cumulative Annual Net Savings in 2018 from 10 Years of Program Activities ( ) Expanded Funding Scenario Current Funding Scenario Total Peak Day Demand Savings 311,989 93,707 73,991 79,541 67,610 53,175 (Dth/Day) Savings % of Base 30% 23% 24% 21% 17% Savings % of Tech. - 75% 81% 69% 58% Savings % of Total Economic % 72% Potential in 2018 (Instantaneous potentials weighted to reflect 2018 mix of new & existing) Total Energy Savings (Dth/yr) 39,717,492 11,568,192 9,396,208 10,100,924 8,585,785 6,626,397 5,729,716 1,137,157 Savings % of Base 29% 24% 25% 22% 17% 14% 3% Savings % of Tech. - 81% 87% 74% 57% 50% 10% Savings % of Total Economic % 66% 57% 11% Savings % of Program Achievable % 17% Total Peak Day Demand Savings 297,194 89,264 70,483 75,769 64,403 50,653 43,704 7,512 (Dth/Day) Savings % of Base 30% 24% 25% 22% 17% 15% 3% Savings % of Tech. - 79% 85% 72% 57% 49% 8% Savings % of Total Economic % 67% 58% 10% Savings % of Program Achievable % 15% a Base excludes industrial CHP use. Base energy and peak demand are lower in the 2018 weighted case because industrial new construction is not included in the analysis. b Technical saving refers to the complete penetration of all measures analyzed in applications where they were deemed technically feasible from an engineering perspective. c Initial economic savings includes savings for all measures found to be cost effective in the application analyzed. d Total economic savings includes initial economic savings plus 7.5 percent, to account for emerging technologies and measure cost reductions not captured in the model. e Total achievable savings reduces total economic savings by 15 percent to account for savings that are not achievable. f Program achievable savings excludes savings due to building codes (35% in new construction) and outside-of-program savings. Connecticut Natural Gas 1-6

12 Figure 1-2 Achievable Energy Savings: All Sectors 7,000,000 Cumulative Annual Dth 6,000,000 5,000,000 4,000,000 3,000,000 2,000,000 1,000,000 Expanded Funding Scenario Current Funding Scenario Naturally Occurring Figure 1-3 depicts costs and benefits for the two program funding scenarios for the period. For the current program funding scenario, the present value of program costs (including administration, marketing, and incentives) is $36.2 million. The present value of total avoidedcost benefits is $112.7 million. The present value of net avoided-cost benefits, i.e., the difference between total avoided-cost benefits and total costs (which include participant costs in addition to program costs), is $65.9 million. For the expanded funding scenario, the present value of program costs is $248 million, the present value of total avoided cost benefits is $593 million, and the present value of net avoided-cost benefits is $302 million. The current funding scenario has a TRC of 2.4 and the expanded funding scenario has a TRC of 2.0 both of which are cost effective under the test used in this study to determine program cost effectiveness. Program cost-effectiveness declines somewhat with increasing program effort, reflecting penetration of more measures with lower cost-effectiveness levels. This result reflects the assumption that the most cost-effective measures are targeted first, both by the programs and by end users who are seeking to lower their natural gas utility bills in the most cost-effective manner. Key results of our efficiency scenario forecasts are summarized in Table 1-2. The table compares 2009 budget and savings from the current funding scenario with the 2009 Program Connecticut Natural Gas 1-7

13 Plan (the scenario is designed to approximate Program savings in its first year). Average annual budget and savings for the full10 year analysis period are presented for both the current program funding scenario and the expanded program funding scenario, as well as cumulative energy and demand savings for program activity from 2009 to Figure 1-3 Benefits and Costs of Energy-Efficiency Savings * $700 Present Value in $ Millions $600 $500 $400 $300 $200 Total Avoided Cost Benefits Participant Costs Program Incentives Program Admin and Marketing $593.4 Net Benefits: $302.1 Million $42.9 $186.8 $100 $0 $112.7 Current Funding Scenario Net Benefits: $65.9 Million $10.6 $29.5 $6.7 $61.6 Expanded Funding Scenario * Present value of benefits and costs over normalized 20-year measure lives; nominal discount rate is 7.09 percent, inflation rate is 2.3 percent. Connecticut Natural Gas 1-8

14 Table 1-2 Comparison Between 2009 Program Plan and Program Funding Scenario Results 2009 Program Plan Current Funding Scenario Expanded Funding Scenario 2009 Annual Budget and Savings Administrative Budget $237,400 $237,400 Marketing Budget $511,880 $511,880 Incentive Budget $2,790,720 $2,557,426 Total Budget $3,540,000 $3,306,706 Net Energy Savings (Dth) 66,393 86,977 Net Energy Savings, % of Base Use 0.17% 0.22% Net Peak Day Demand Savings (Dth/day) Net Peak Day Demand Savings, % of Base Demand 0.23% 0.19% $/net therm $5.33 $ Savings as a Multiple of Program Goals 1.3 TRC Year Average Annual Budget and Savings Administrative Budget (2009$) $306,354 $1,272,120 Marketing Budget (2009$) $511,880 $6,210,557 Incentive Budget (2009$) $3,675,307 $22,332,171 Total Budget (2009$) $4,493,541 $29,814,848 Net Energy Savings (Dth) 113, ,972 Net Energy Savings, % of Base Use 0.28% 1.4% Net Peak Day Demand Savings (Dth/day) 789 4,589 Net Peak Day Demand Savings, % of Base Demand 0.25% 1.5% $/net therm $3.95 $5.20 TRC Cumulative Savings Due to Program Activity Net Energy Savings (Dth) 11,371,568 57,297,161 Net Energy Savings, % of Base Use 2.8% 14% Net Peak Day Demand Savings (Dth/day) 7,512 43,704 Net Peak Day Demand Savings, % of Base Demand 2.5% 15% Results by Sector Cumulative net achievable potential estimates sectors for the period are presented in Figure 1-4 for the commercial and industrial sectors. This figure shows results for each funding scenario. Under the program assumptions developed for this study, achievable energy savings are highest for the commercial sector under all scenarios, reflecting the fact that the commercial sector consumes the larger share of firm natural gas and also has the largest economic potential (7,680,000 Dth for commercial versus 1,720,000 Dth for industrial in 2018). Connecticut Natural Gas 1-9

15 Figure 1-4 Net Achievable Energy Savings by 2018 by Sector Dth per Year Cumulative Savings by Dth/Year 5,000,000 4,500,000 4,000,000 3,500,000 3,000,000 2,500,000 2,000,000 1,500,000 1,000, ,000 0 Expanded Funding Scenario Current Funding Scenario 1,232, ,653 Industrial 4,496, ,503 Commercial Figure 1-5 shows the end-use distribution of commercial energy savings potential by 2018 under the current funding scenario. Space heating contributes most to the energy savings potential, resulting from measures such as EMS installation, high-efficiency furnaces and boilers, and clock/programmable thermostats. Cooking shows the next largest potential, reflecting Energy Star steamer and fryer savings. Water heating is also significant, reflecting savings from tank insulation, tankless water heaters, and condensing water heaters. Figure 1-6 shows the end-use distribution of industrial energy savings potential by 2018 under the current funding scenario. Boilers contribute most to the energy savings potential, resulting from measures such as boiler insulation, steam trap maintenance, and load control. Process heat shows the next largest potential, reflecting savings from process controls and management, efficient burners, and combustion controls. A small share of HVAC savings potential is also present, reflecting ceiling insulation and high efficiency furnaces. Connecticut Natural Gas 1-10

16 Figure 1-5 Commercial Economic Gas Savings Potential by End Use (2018) Current Funding Scenario Water Heating 10% Cooking 21% Heating 69% Figure 1-6 Industrial Economic Gas Savings Potential by End Use (2018) Current Funding Scenario Process Heat 39% Boiler 56% HVAC 5% Connecticut Natural Gas 1-11

17 2. Introduction 2.1 Overview For this project, we used KEMA DSM Assyst Model to develop technical potential, initial economic potential, and program funding scenario savings estimates for energy efficiency measures and programs in Connecticut. We also calculate a total economic, a total achievable and a total program achievable outside the model. These terms are defined in detail in the executive summary, section 1.1. Key questions addressed in the study included: How much cost-effective natural gas efficiency resource is available in Connecticut? What levels of program savings are available? Data for the study come from a number of different sources, including natural gas usage and avoided cost data provided by the three Connecticut gas utilities, program data for Connecticut, the U.S. DOE Commercial Building Energy Consumption Survey (CBECS), the California Commercial End Use Survey (CEUS), the California Database for Energy Efficiency Resources (DEER), the Connecticut Department of Labor, the Economic Census, Energy Trust of Oregon, the New York State Energy Research and Development Authority (NYSERDA), and various technology-specific internet sources. 2.2 Study Approach This study involved identification and development of baseline end-use and measure data and development of estimates of future energy-efficiency impacts under varying levels of program effort. The baseline characterization allowed KEMA to identify the types and approximate sizes of the various market segments that are the most likely sources of energy-efficiency potential in Connecticut. These characteristics then served as inputs to a modeling process that incorporated energy cost parameters and specific energy-efficiency measure characteristics (such as costs, savings, and existing penetration estimates) to provide more detailed potential estimates. To aid in the analysis, KEMA utilized the KEMA DSM ASSYST model. This model provides a thorough, clear, and transparent documentation database, as well as an extremely efficient data processing system for estimating technical, economic, and achievable potential. We estimated Connecticut Natural Gas 2-12

18 technical potential, economic potential, achievable potential, program achievable potential and program funding scenario savings for the commercial and industrial sectors, with a focus on energy-efficiency impacts over the next 10 years. 2.3 Layout of the Report The remainder of this report is organized as follows: Section 3 discusses the methodology and concepts used to develop the technical and economic potential estimates. Section 4 provides baseline data and results developed for the study. Section 5 discusses the results of the DSM potential analysis by sector and over time. In addition, the report contains the following appendices: Appendix A: Detailed Methodology and Model Description Further detail of what was discussed in Section 3. Appendix B: Measure Descriptions Describes the measures included in the study. Appendix C: Economic Inputs Provides avoided cost, natural gas rate, discount rate, and inflation rate assumptions used for the study. Appendix D: Building and time-of-use (TOU) Factor Inputs Shows the base square footage estimates for commercial building types, and base energy use by industrial segment. This appendix also includes TOU factors by sector and end-use. Appendix E: Measure Inputs Lists the measures included in the model with the costs, estimated savings, applicability, and estimated current saturation factors. Appendix F: Non-Additive Measure Level Results Shows energy-efficiency potential for each measure independent of any other measure. Appendix G: Supply Curve Data Shows the data behind the energy supply curves provided in Section 4 of the report. Appendix H: Program Funding Scenario Results Provides the forecasts for the two program funding scenarios. Connecticut Natural Gas 2-13

19 3. Methods and Scenarios This section provides a brief overview of the concepts and methods used to conduct this study. Additional methodological details are provided in Appendix A. 3.1 Characterizing the Natural Gas Energy-Efficiency Resource Energy-efficiency has been characterized for some time now as an alternative to energy supply options, such as conventional power plants that produce electricity from fossil or nuclear fuels. In the early 1980s, researchers developed and popularized the use of a conservation supply curve paradigm to characterize the potential costs and benefits of energy conservation and efficiency. Under this framework, technologies or practices that reduced energy use through efficiency were characterized as liberating supply for other energy demands and therefore could be thought of as a resource and plotted on an energy supply curve. The energy-efficiency resource paradigm argued simply that the more energy-efficiency or nega-watts produced, the fewer new plants would be needed to meet end users power demands Defining Natural Gas Energy-Efficiency Potential Like any resource, there are a number of ways in which the energy-efficiency resource can be estimated and characterized. Definitions of energy-efficiency potential are similar to definitions of potential developed for finite fossil fuel resources, like coal, oil, and natural gas. For example, fossil fuel resources are typically characterized along two primary dimensions: the degree of geological certainty with which resources may be found and the likelihood that extraction of the resource will be economic. This relationship is shown conceptually in Figure 2-1. Connecticut Natural Gas 3-1

20 Figure 3-1 Conceptual Framework for Estimates of Fossil Fuel Resources Decreasing Certainty of Existence Possible and Economically Feasible Known and Economically Feasible Possible but not Economically Feasible Known but not Economically Feasible Decreasing Economic Feasibility Somewhat analogously, this energy-efficiency potential study defines several different types of energy-efficiency potential, namely, technical, initial and total economic, total achievable, program achievable, program funding scenarios, and naturally occurring, as defined in section 1.1. These potentials are shown conceptually in Figure 3-2. The chart splits the potentials into two groupings. The first includes technical potential, initial economic potential, the expanded program funding scenario, the current program funding scenario, and naturally occurring potential. For this study, these potentials were estimated using the DSM ASSYST model and are based on currently available technologies and current measure costs. The second grouping includes total economic potential, total achievable potential, and instantaneous program achievable potential. Total economic potential is greater than initial economic potential: it includes the effects of emerging technologies and future cost reductions for current energy efficiency measures. Total achievable potential and instantaneous program achievable potential are calculated from total economic potential and therefore also include these effects. Connecticut Natural Gas 3-2

21 Figure 3-2 Conceptual Relationship among Energy-Efficiency Potential Definitions Technical Initial economic Expanded program funding case Current program funding case Naturally occurring Growth due to emerging technologies and measure cost reductions Total economic Total achievable Instantaneous program achievable 3.2 Summary of Analytical Steps Used in this Study Two parallel sets of analyses were used to generate the results in this report. The technical potential, initial economic potential, and program funding scenario savings were estimated using KEMA s DSM ASSYST model, which was developed for conducting energy-efficiency potential studies. The total economic potential, total achievable potential and instantaneous program achievable potential were estimated outside the ASSYST model using an approach that allowed us to take into account explicitly the impacts of projected building codes and standards, new technologies and changes in measure cost. Figure 3-3 illustrates the combined steps in the study and how the two approaches relate to one another. The DSM ASSYST approach and outside-of-model approach are described below. Connecticut Natural Gas 3-3

22 Figure 3-3 Conceptual Overview of Study Process Economic Data Measure Data Building Data Technical Potential New Technologies Measure Cost Reduction Initial Economic Potential Total Economic Potential Building Codes Not Achievable Program Data Costs and Savings Standards Outside of Program Total Achievable Potential Modeled Program Scenarios Program Achievable DSM ASSYST Analytical Steps The crux of the DSM ASSYST approach involves carrying out a number of basic analytical steps to produce estimates of the energy-efficiency potentials introduced above. The bulk of the analytical process for this was carried out within the DSM ASSYST model. Details on the steps employed and analyses conducted are described in Appendix A. The model used, DSM ASSYST, is a Microsoft Excel -based model that integrates technology-specific engineering and customer behavior data with utility market saturation data, load shapes, rate projections, and marginal costs into an easily updated data management system. Connecticut Natural Gas 3-4

23 The key steps implemented in this approach were: Step 1: Develop Initial Input Data Develop a list of energy-efficiency measure opportunities to include in scope. In this step, an initial draft measure list was developed and circulated among utilities and stakeholders. The final measure list was developed after incorporating comments. Gather and develop technical data (costs and savings) on efficient measure opportunities. Data on measures was gathered from a variety of sources. Measure descriptions are provided in Appendix B, and detail on measure inputs is provided in Appendix E. Gather, analyze, and develop information on building characteristics, including total square footage or total number of households, natural gas consumption and intensity by end use, market shares of key gas consuming equipment, and market shares of energyefficiency technologies and practices. Section 3 of this report describes the baseline data developed for this study. Collect data on economic parameters: avoided costs, natural gas rates, discount rates, and inflation rate. These inputs are provided in Appendix C of this report. Step 2: Estimate Technical Potential and Develop Supply Curves Match and integrate data on efficient measures to data on existing building characteristics to produce estimates of technical potential and energy-efficiency supply curves. Step 3: Estimate Economic Potential Match and integrate measure and building data with economic assumptions to produce indicators of costs from different viewpoints (e.g., societal and consumer). Estimate total economic potential. Step 4: Estimate Program and Naturally Occurring Potentials Screen initial measures for inclusion in the program analysis. This screening may take into account factors such as cost effectiveness, potential market size, non-energy benefits, market barriers, and potentially adverse effects associated with a measure. For this study measures were screened using the total resource cost (TRC) test, while considering only natural gas avoided-cost benefits. Connecticut Natural Gas 3-5

24 Gather and develop estimates of program costs (e.g., for administration and marketing) and historic program savings. Develop estimates of customer adoption of energy-efficiency measures as a function of the economic attractiveness of the measures, barriers to their adoption, and the effects of program intervention. Estimate achievable program and naturally occurring potentials Total Economic, Total Achievable and Instantaneous Program Achievable Analytical Steps For this study we modified our typical approach to attempt to reflect more carefully the changes in the market that are not captured in the Demand Side Assyst model as typically implemented. We wanted an approach that allowed us to take into account explicitly: new technologies; reductions in measure cost; the impacts of projected building codes; the impact of standards. To this end, this approach created new categories of potential, including Total economic potential, which is an estimate of the potential of cost-effective energy efficiency measures, taking into account the effects of new technologies on technical potential and reductions to measure costs on cost effectiveness; Achievable potential, which is an estimate of maximum energy efficiency savings from all sources; and Instantaneous program achievable potential, which is an estimate of how much energy efficiency programs can save, taking into account the simultaneous effects of building codes, standards, and outside-of-program savings. These three potentials are calculated from the initial economic potential output, which is an output of the DSM ASSYST model. The key steps implemented in this approach were: Connecticut Natural Gas 3-6

25 Step 1: Develop economic savings adjustment factors Estimate a factor to estimate economic potential that will develop due to the development of emerging technologies or cost reductions in technologies that are not currently cost effective. Estimate the not achievable portion of the economic potential; that is, what portion will not adopt energy efficiency measures, regardless of program intervention Estimate the effect of changes to building codes on energy efficiency in new construction Estimate the impacts of federal minimum efficiency standards for equipment. Estimate additional outside of program effects, including non-free-rider naturally occurring savings, as well as the effects of any interventions not captured by the building codes and standards (such as a federal tax credit for high efficiency equipment). Step 2: Estimate Total Economic Potential The economic potential growth factor is applied to the initial economic potential produced by the DSM ASSYST model to estimate total economic potential, taking into account innovation and measure cost reductions. Total Economic Potential = Initial Economic Potential x (1 + Economic Potential Growth Factor) Step 3: Estimate Achievable Potential The not achievable portion of total economic savings is calculated and netted out to yield achievable potential. Achievable savings includes savings from all sources, including naturally occurring, building codes, standards, and efficiency programs. Total Achievable Potential = Total Economic Potential x (1 - Not Achievable Factor) Step 3: Instantaneous Program Achievable Potential The effects of building codes, standards, and other outside-of-program effects are netted out to yield the instantaneous achievable program potential. We refer to this potential as instantaneous because it is not associated with a specific program time frame, and therefore not limited by the turnover of replace-on-burnout measures. The program funding scenario savings we developed, in contrast, are based on a 10-year program and limited by the natural turnover of long-lived measures, such as boilers (20 years). Instantaneous Program Achievable Potential = Total Achievable Potential x (1 - Outside of Program Factor - Standards Factor) - Total Achievable Potential NC x (1 - Building Codes Factor) Connecticut Natural Gas 3-7

26 where Total Achievable Potential NC is the total achievable potential for new construction. 4. Baseline Data and Results 4.1 Overview Estimating the potential for energy-efficiency improvements requires a comparison of the energy impacts of standard-efficiency technologies with those of alternative high-efficiency equipment. This, in turn, dictates a relatively detailed understanding of the energy characteristics of the marketplace. Baseline data that were required for each studied market segment included: Total count of energy-consuming units (floor space of commercial buildings and industrial base energy consumption) Annual energy consumption for each end use studied (both in terms of total consumption in Dth and normalized for intensity on a per-unit basis, e.g., therms/ft2) The saturation of gas end uses (for example, the fraction of total commercial floor space with gas heating) The market share of each base equipment type (for example, the fraction of total commercial floor space served by gas furnaces) Market share for each energy-efficiency measure in scope (for example, the fraction of total commercial floor space already served by condensing furnaces). Data for the baseline analysis comes from a number of sources, including U.S. Department of Energy studies, a utility-provided breakdown of gas sales by industry, and other secondary sources. Baseline data sources vary by sector and are described further below. Figure 4-1 shows the overall breakdown of firm gas usage by sector for Connecticut. 4 Residential accounts for the largest share of energy usage, followed by the commercial and industrial sectors. This report addresses energy efficiency only in the commercial and industrial sectors. 4 Includes firm sales and firm transportation by the Connecticut utilities. Connecticut Natural Gas 4-8

27 Figure 4-1 Firm Natural Gas Usage Breakdown Connecticut Industrial 16% Residential 50% Commercial 34% Source: 2007 firm sales data 4.2 Commercial The primary sources of commercial data for Connecticut were the U.S. DOE Commercial Building Energy Consumption Survey (CBECS), billed consumption data for the three Connecticut gas utilities, and a breakdown of Yankee Gas 2008 sales by North American Industry Classification System (NAICS) code. CBECS data were used to develop end-use saturations. In order to get regionally applicable saturations (the fraction of commercial floorspace that has a particular end use), KEMA looked at buildings in the Northeast census region. End-use energy intensities were somewhat more problematic. We turned to California s Commercial End-use Survey (CEUS) as a starting point because this relied on calibrated DOE- 2 analysis of over 2,500 buildings. While absolute energy intensities would differ significantly between California and Connecticut, especially for heating, we believed that the California data, combined with additional data on Connecticut heating loads, would provide the most accurate predictor of variations in energy intensities between building types and among the end-uses within a given building types. Monthly load data, provided by the utilities, were used to divide Connecticut Natural Gas 4-9

28 gas use into heating and non-heating components, under the assumption that non-heating energy would be fairly constant throughout the year. We used sales data provided by Yankee Gas to divide energy use by building type. Yankee Gas sales represent about 45 percent of Connecticut firm commercial sales. Ideally, we would have had complete breakdowns for all three utilities, but lacking that, we used the Yankee Gas data and relied on a careful review by the other utilities to identify any inaccuracies. No changes were required. The Yankee Gas breakdown, combined with the CEUS data, let us calculate the end-use energy intensities. Table 4-1 shows total estimated floorspace for gas customers, which was estimated using data from CBECS, the Connecticut Department of Labor, and the utilities. We first divided total gas customers (provided by the utilities) into building types based on the distribution of building types in CBECS (using the Northeast census region data). Estimates of average building floorspace by building type were taken from the CBECS. The results were adjusted up or down for some building types in order to yield plausible 5 end-use intensities when combined with gas sales data. Figure 4-2 shows commercial energy consumption by building type. The building types with the largest estimated usage are offices, restaurants, health care, schools, and other (which includes facilities such as laundries, health clubs, churches, and auditoriums). Figure 4-3 shows commercial energy consumption by end use. The largest end use is space heating, followed by water heating. The small other category includes items such as pool heating, cooling, and process uses. Table 4-1 summarizes the commercial baseline energy consumption results developed for the study. 5 End-use intensities were vetted by utility representatives. Connecticut Natural Gas 4-10

29 Figure 4-2 Commercial Natural Gas Usage by Building Type Other Lodging Lodging 2% Other 18% Office 31% Health Care College Schools Warehouse Health Care 10% Grocery Restaurant College 1% Schools 9% Warehouse 8% Grocery 5% Retail 6% Restaurant 10% Retail Office billion cf Figure 4-3 Commercial Natural Gas Usage by End Use Water Heating 10% Cooking 10% Other 3% Other Cooking Water Heating Heating 77% Heating billion cubic feet Connecticut Natural Gas 4-11

30 Table 4-1 Commercial Baseline Consumption Summary Saturation Office Retail Restaurant Grocery Warehouse School College Health Lodging Other Heating 78% 100% 60% 95% 93% 55% 37% 67% 40% 69% Water Heating 57% 71% 83% 71% 36% 74% 79% 70% 88% 66% Cooking 26% 9% 100% 74% 1% 52% 23% 70% 69% 41% Other 8% 10% 5% 0% 1% 2% 9% 13% 7% 9% EUI = CF/sq ft Office Retail Restaurant Grocery Warehouse School College Health Lodging Other Heating Water Heating Cooking Other (1000 sq ft) Office Retail Restaurant Grocery Warehouse School College Health Lodging Other Total Floorspace 251,601 58,823 11,491 20,673 95,874 69,377 7,861 56,162 9, , ,487 Connecticut Natural Gas 4-12

31 CBECS provided data on saturations of gas heating equipment and gas water heating for gasserved building. For new buildings, we reviewed Connecticut s commercial building code to understand required minimum efficiency practices for new construction. The following figures highlight some of the information developed for the commercial sector. Figure 4-4 shows the distribution of heating systems by building type. Overall, ducted furnaces are the most popular heating type, followed by boilers. Unit heaters were broken out only for warehouses (for other building types they are included with other heating systems). Figure 4-4 Distribution of Heating Systems by Building Type Other Lodging Hospital College School Warehouse Grocery Restauarnt Retail Office 0% 20% 40% 60% 80% 100% Furnace Boiler Unit Heater Other Figure 4-5 shows the estimated saturations for commercial space heating energy efficiency measures. For the most part, shell measures have high saturations, while equipment-oriented measures show somewhat lower saturations. Connecticut Natural Gas 4-13

32 Figure 4-5 Applicability of Commercial Heating Energy Efficiency Measures Retrocommissioning Refrigeration heat recovery - space cond. Demand controlled ventilation (DCV) Hot w ater temperature reset Radiant heater (Warehouse) Condensing unit heaters (Warehouse) Stack Heat Exchanger High Efficiency Furnace/Boiler Air Side Heat Recovery Systems Heat Recovery from AC EMS Optimization Energy Management Systems Clock / Programmable Thermostat Boiler Tune-Up Insulation of Pipes Duct Insulation Duct Repair and Sealing Insulation (w all) Insulation (ceiling) High Efficiency Window s 0% 20% 40% 60% 80% 100% Connecticut Natural Gas 4-14

33 Figure 4-6 shows the estimated saturations of commercial water heating energy efficiency measures. High efficiency pre-rinse spray valves have the highest saturation, followed by insulation measures. To date, there appear to be few tankless gas water heaters or condensing water heaters. The thermally activated heat pump/chiller is an emerging technology that has made some inroads in industrial applications, but is not established in commercial applications. Figure 4-6 Saturations of Commercial Water Heating Energy Efficiency Measures Pre-Rinse Spray Valve Hot Water Pipe Insulation Water Heater Tank Blanket/Insulation Demand controlled circulating systems Tankless Water Heater Condensing Water Heater Thermally activated heat pump/chiller 0% 20% 40% 60% 80% 4.3 Industrial For the industrial analysis, we relied on the Department of Energy s Manufacturing Energy Consumption Survey (MECS). The survey provided, at the U.S. level, energy consumption by industry classification and end use. These data were used to develop initial industrial end use saturations, which were modified to reflect Connecticut s firm sales (described below). Yankee Gas provided detailed sales data by industry classification. Because Yankee Gas has the lion s share of Connecticut s industrial sales (60 percent of total and 87 percent of firm), we had a high degree of confidence in applying Yankee Gas distribution to the whole state. The Connecticut Natural Gas 4-15