New Jersey Energy Efficiency 

Market Potential Assessment

Report Number 1401

Volume 2: Report

EnerNOC Utility Solutions Consulting

500 Ygnacio Valley Road

Suite 450

Walnut Creek, CA 94596

925.482.2000

www.enernoc.com

Prepared for:

Rutgers, The State University of New Jersey

Presented on:

October 17, 2012

EnerNOC Utility Solutions Consulting iii

This report was prepared by

EnerNOC Utility Solutions Consulting

500 Ygnacio Valley Blvd., Suite 450

Walnut Creek, CA 94596

I. Rohmund, Project Director

D. Costenaro, Project Manager

EnerNOC Utility Solutions Consulting v

CONTENTS

1 INTRODUCTION .................................................................................................... 1-1

Background ...................................................................................................................1-1

Objectives .....................................................................................................................1-1

Report Organization .......................................................................................................1-1

Definitions of Potential ...................................................................................................1-1

Abbreviations and Acronyms...........................................................................................1-2

2 ANALYSIS APPROACH AND DATA DEVELOPMENT................................................ 2-1

Analysis Approach..........................................................................................................2-1

LoadMAP Model .................................................................................................2-2

Market Characterization......................................................................................2-3

Market Profiles...................................................................................................2-9

Baseline Forecast .............................................................................................2-10

Energy Efficiency Measure Analysis ...................................................................2-10

Energy-Efficiency Potential ...............................................................................2-14

Alternative Avoided Cost Scenario .....................................................................2-14

Fuel Switching Analysis ....................................................................................2-14

Conclusions and Recommendations...................................................................2-15

Data Development .......................................................................................................2-15

Data Sources ...................................................................................................2-15

Data Application...............................................................................................2-17

3 MARKET CHARACTERIZATION AND MARKET PROFILES ...................................... 3-1

Energy Use Summary .....................................................................................................3-1

Residential Sector ..........................................................................................................3-2

Commercial Sector.........................................................................................................3-8

Industrial Sector ..........................................................................................................3-15

4 BASELINE FORECAST ............................................................................................ 4-1

Residential Sector ..........................................................................................................4-1

Commercial Sector.........................................................................................................4-5

Industrial Sector ............................................................................................................4-9

Baseline Forecast Summary ..........................................................................................4-10

5 ENERGY EFFICIENCY MEASURES.......................................................................... 5-1

List of Energy Efficiency Measures...................................................................................5-1

Results of the Economic Screen ....................................................................................5-17

6 OVERALL ENERGY EFFICIENCY POTENTIAL ......................................................... 6-1

Electric Energy Efficiency – Overall Results ......................................................................6-3

Natural Gas Energy Efficiency – Overall Results ...............................................................6-5

Overview of Energy Efficiency Potential by Sector and Fuel...............................................6-6
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7 ENERGY EFFICIENCY POTENTIAL BY SECTOR ..................................................... 7-1

Residential Electricity Potential........................................................................................7-1

Residential Electric Potential by Market Segment..................................................7-2

Residential Electric Potential by End Use..............................................................7-3

Residential Natural Gas Potential.....................................................................................7-5

Residential Natural Gas Potential by Market Segment...........................................7-6

Residential Natural Gas Potential by End Use .......................................................7-7

Commercial Electricity Potential ......................................................................................7-9

Commercial Electric Potential by Market Segment ..............................................7-11

Commercial Electric Potential by End Use ..........................................................7-12

Commercial Natural Gas Potential .................................................................................7-14

Commercial Natural Gas Potential by Market Segment........................................7-15

Commercial Natural Gas Potential by End Use....................................................7-17

Industrial Electricity Potential........................................................................................7-18

Industrial Electric Potential by Market Segment..................................................7-19

Industrial Electric Potential by End Use..............................................................7-20

Industrial Natural Gas Potential.....................................................................................7-22

Industrial Natural Gas Potential by Market Segment ...........................................7-24

Industrial Natural Gas Potential by End Use .......................................................7-24

8 ALTERNATE AVOIDED COST SCENARIO ............................................................... 8-1

9 FUEL SWITCHING ANALYSIS................................................................................ 9-1

Technical Potential and Fuel Switching ................................................................9-1

Economic Potential and Fuel Switching ................................................................9-1

Achievable Potential and Fuel Switching ..............................................................9-1

10 CONCLUSIONS AND RECOMMENDATIONS......................................................... 10-1

General Recommendations ...........................................................................................10-1

Residential Recommendations.......................................................................................10-1

Commercial and Industrial Recommendations ................................................................10-2

11 COMPARISON TO RECENT REGIONAL POTENTIAL STUDIES ............................. 11-1

12 ENERGY EFFICIENCY POTENTIAL BEYOND 2016............................................... 12-1

Electric Energy Efficiency – Overall Results ....................................................................12-3

Natural Gas Energy Efficiency – Overall Results .............................................................12-5

Overview of Energy Efficiency Potential by Sector and Fuel.............................................12-6
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CONTENTS

LIST OF FIGURES

Figure 2-1 Overview of Analysis Approach ..............................................................................2-2

Figure 2-2 LoadMAP Analysis Framework................................................................................2-3

Figure 2-3 Approach for Measure Assessment.......................................................................2-11

Figure 3-1 Sector-Level Electricity Use, 2010 ..........................................................................3-1

Figure 3-2 Sector-Level Natural Gas Use, 2010 .......................................................................3-2

Figure 3-3 Residential Market Segmentation by Housing Type – Percent of Households ............3-3

Figure 3-4 Residential Market Segmentation by Housing Type – Percent of Energy Use.............3-3

Figure 3-5 Residential Electricity and Natural Gas Use by End Use (2010), All Homes ................3-5

Figure 3-6 Residential Electricity Intensity by End Use and Segment (kWh/household, 2010) ....3-6

Figure 3-7 Breakdown of Residential Electricity Use by End Use and Segment (2010) ...............3-7

Figure 3-8 Residential Natural Gas Intensity by End Use and Segment (therm/hh, 2010) ..........3-7

Figure 3-9 Breakdown of Residential Natural Gas Use by End Use and Segment (2010) ............3-8

Figure 3-10 Commercial Market Segmentation by Building Type – Percent of Energy Use............3-9

Figure 3-11 Commercial Electricity and Natural Gas Use by End Use (2010), All Buildings..........3-11

Figure 3-12 Commercial Electricity Intensity by End Use and Segment (kWh/sq ft, 2010)..........3-12

Figure 3-13 Breakdown of Commercial Electricity Consumption by End Use & Segment (2010)..3-13

Figure 3-14 Commercial Natural Gas Intensity by End Use and Segment (therms/sq ft, 2010)...3-13

Figure 3-15 Breakdown of Commercial Natural Gas Use by End Use and Segment (2010) .........3-14

Figure 3-16 Industrial Market Segmentation – Percentage of Energy Use .................................3-15

Figure 3-17 Industrial Electricity and Natural Gas Use by End Use (2010), All Industries ...........3-17

Figure 3-18 Industrial Electricity Use by End Use and Segment (GWh, 2010)............................3-17

Figure 3-19 Breakdown of Industrial Electricity Use by End Use and Segment (2010)................3-18

Figure 3-20 Industrial Natural Gas Use by End Use and Segment (million therms, 2010)...........3-19

Figure 3-21 Breakdown of Industrial Natural Gas Use by End Use and Segment (2010) ............3-19

Figure 4-1 Residential Electricity Baseline Forecast by End Use ................................................4-2

Figure 4-2 Residential Baseline Electricity Use per Household by End Use.................................4-2

Figure 4-3 Residential Natural Gas Baseline Forecast by End Use .............................................4-4

Figure 4-4 Residential Baseline Natural Gas Use per Household by End Use..............................4-5

Figure 4-5 Commercial Electricity Baseline Forecast by End Use...............................................4-6

Figure 4-6 Commercial Natural Gas Baseline Forecast by End Use............................................4-8

Figure 4-7 Industrial Electricity Baseline Forecast by End Use ..................................................4-9

Figure 4-8 Industrial Natural Gas Baseline Forecast by End Use .............................................4-10

Figure 4-9 Electricity Baseline Forecast Summary (GWh).......................................................4-11

Figure 4-10 Natural Gas Baseline Forecast Summary (million therms) ......................................4-11

Figure 6-1 Summary of Combined Electric and Natural Gas Energy Savings ..............................6-2

Figure 6-2 Combined Electric and Natural Gas Potential Forecasts (million BTU) .......................6-3

Figure 6-3 Summary of Electric Energy Savings ......................................................................6-4

Figure 6-4 Electric Potentials Forecasts (GWh)........................................................................6-4

Figure 6-5 Summary of Natural Gas Energy Savings................................................................6-5
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Figure 6-6 Natural Gas Potential Forecasts (1000 therms) .......................................................6-6

Figure 6-7 Achievable Low Electric Potential by Sector (GWh)..................................................6-7

Figure 6-8 Achievable High Electric Potential by Sector (GWh).................................................6-7

Figure 6-9 Achievable Low Natural Gas Potential by Sector (mmTherms) .................................6-8

Figure 6-10 Achievable High Natural Gas Potential by Sector (mmTherms).................................6-9

Figure 7-1 Residential Electric Energy Efficiency Potential Savings............................................7-2

Figure 7-2 Residential Electric Achievable Low Potential by End Use in 2016.............................7-5

Figure 7-3 Residential Natural Gas Potential Savings ...............................................................7-6

Figure 7-4 Residential Natural Gas Achievable Low Potential by End Use in 2016 ......................7-9

Figure 7-5 Commercial Energy Efficiency Potential Savings ....................................................7-10

Figure 7-6 Commercial Achievable Low Potential Electricity Savings by End Use in 2016..........7-14

Figure 7-7 Commercial Natural Gas Potential Savings ............................................................7-15

Figure 7-8 Commercial Natural Gas Achievable Low Potential Savings by End Use in 2016.......7-18

Figure 7-9 Industrial Electric Potential Savings......................................................................7-19

Figure 7-10 Industrial Achievable Low Electricity Potential Savings by End Use in 2016 .............7-22

Figure 7-11 Industrial Natural Gas Potential Savings ...............................................................7-23

Figure 7-12 Industrial Natural Gas Achievable Low Potential Savings by End Use in 2016..........7-25

Figure 9-1 Space Heating – Number of Fuel Switching Units, Achievable Low Case ...................9-3

Figure 9-2 Space Heating – Number of Fuel Switching Units, Achievable High Case ..................9-3

Figure 9-3 Water Heating – Number of Fuel Switching Units, Achievable Low Case ...................9-4

Figure 9-4 Water Heating – Number of Fuel Switching Units, Achievable High Case ..................9-5

Figure 11-1 Comparison with recent regional potential studies ................................................11-2

Figure 12-1 Summary of Combined Electric and Natural Gas Energy Savings ............................12-2

Figure 12-2 Combined Electric and Natural Gas Potential Forecasts (million BTU) .....................12-3

Figure 12-3 Summary of Electric Energy Savings ....................................................................12-4

Figure 12-4 Electric Potentials Forecasts (GWh)......................................................................12-4

Figure 12-5 Summary of Natural Gas Energy Savings..............................................................12-5

Figure 12-6 Natural Gas Potential Forecasts (1000 therms) .....................................................12-6

Figure 12-7 Achievable Low Electric Potential by Sector (GWh)................................................12-7

Figure 12-8 Achievable High Electric Potential by Sector (GWh)...............................................12-7

Figure 12-9 Achievable Low Natural Gas Potential by Sector (million Therms)...........................12-9

Figure 12-10 Achievable High Natural Gas Potential by Sector (million Therms)..........................12-9
EnerNOC Utility Solutions Consulting ix

LIST OF TABLES

Table 1-1 Explanation of Abbreviations and Acronyms............................................................1-3

Table 2-1 Overview of Segmentation Scheme for Potentials Modeling .....................................2-4

Table 2-2 Residential Electric End Uses and Technologies ......................................................2-5

Table 2-3 Residential Natural Gas End Uses and Technologies ................................................2-5

Table 2-4 Commercial Electric End Uses and Technologies .....................................................2-7

Table 2-5 Commercial Natural Gas End Uses and Technologies...............................................2-8

Table 2-6 Industrial Electric End Uses and Technologies.........................................................2-9

Table 2-7 Industrial Natural Gas End Uses and Technologies ..................................................2-9

Table 2-8 Sample Equipment Measures for Central Air Conditioning – Single Family Home .....2-12

Table 2-9 Sample Non-Equipment Measures – Single Family Home, Existing .........................2-13

Table 2-10 Economic Screen Results for Selected Residential Equipment Measures..................2-14

Table 2-11 Data Applied for the Market Profiles .....................................................................2-18

Table 2-12 Data Needs for the Baseline Forecast and Potentials Estimation in LoadMAP...........2-19

Table 2-13 Residential Electric Equipment Standards Applicable to New Jersey........................2-20

Table 2-14 Commercial Electric Equipment Standards Applicable to New Jersey ......................2-21

Table 2-15 Residential Gas Appliance Standards Applicable to New Jersey ..............................2-22

Table 2-16 Commercial Gas Appliance Standards Applicable to New Jersey .............................2-22

Table 2-17 Data Needs for the Measure Characteristics in LoadMAP .......................................2-23

Table 3-1 Residential Sector Energy Usage and Intensity by Segment Type, 2010 ...................3-2

Table 3-2 Electric Market Profile for the Residential Sector .....................................................3-4

Table 3-3 Natural Gas Market Profile for the Residential Sector...............................................3-5

Table 3-4 Residential Electricity Use by End Use and Segment (kWh/HH/year, 2010)...............3-6

Table 3-5 Residential Natural Gas Use by End Use and Segment (therm/HH/year, 2010) .........3-8

Table 3-6 Commercial Market Segmentation by Building Type, Base Year 2010 .......................3-9

Table 3-7 Commercial Sector Composite Electric Market Profile, 2010 ...................................3-10

Table 3-8 Commercial Sector Composite Natural Gas Market Profile, 2010.............................3-11

Table 3-9 Commercial Electricity Intensity by End Use and Segment (kWh/sq ft, 2010)..........3-12

Table 3-10 Commercial Natural Gas Intensity by End Use and Segment (therms/sq ft, 2010)...3-14

Table 3-11 Industrial Market Segmentation by Industry Type, Base Year 2010 ........................3-15

Table 3-12 Industrial Sector Composite Electric Market Profile, 2010 ......................................3-16

Table 3-13 Industrial Sector Composite Natural Gas Market Profile, 2010................................3-16

Table 3-14 Industrial Electricity Use by End Use and Segment (GWh, 2010)............................3-18

Table 3-15 Industrial Natural Gas Use by End Use and Segment (million therms, 2010)...........3-19

Table 4-1 Residential Electricity Consumption by End Use (GWh)............................................4-1

Table 4-2 Residential Electricity Baseline Forecast by End Use and Technology (GWh).............4-3

Table 4-3 Residential Natural Gas Consumption by End Use (million therms)...........................4-4

Table 4-4 Residential Natural Gas Baseline Forecast by End Use and Tech (million therms)......4-5

Table 4-5 Commercial Electricity Consumption by End Use (GWh) ..........................................4-6

Table 4-6 Commercial Baseline Electricity Forecast by End Use and Technology (GWh)............4-7
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Table 4-7 Commercial Natural Gas Consumption by End Use (million therms)..........................4-8

Table 4-8 Commercial Baseline Electricity Forecast by End Use and Technology (GWh)............4-8

Table 4-9 Industrial Electricity Consumption by End Use (GWh)..............................................4-9

Table 4-10 Industrial Natural Gas Consumption by End Use (million therms)...........................4-10

Table 4-11 Electricity Baseline Forecast Summary (GWh).......................................................4-10

Table 4-12 Natural Gas Baseline Forecast Summary (million therms) ......................................4-11

Table 5-1 Summary of Residential Equipment Measures .........................................................5-2

Table 5-2 Summary of Residential Non-Equipment Measures..................................................5-5

Table 5-3 Summary of Commercial Equipment Measures........................................................5-6

Table 5-4 Summary of Commercial Non-Equipment Measures ..............................................5-10

Table 5-5 Summary of Industrial Equipment Measures .........................................................5-12

Table 5-6 Summary of Industrial Non-Equipment Measures..................................................5-15

Table 5-7 Number of Measures Evaluated ...........................................................................5-17

Table 6-1 Summary of Combined Electric and Natural Gas Energy Efficiency Potential .............6-2

Table 6-2 Summary of Electric Energy Efficiency Potential ......................................................6-3

Table 6-3 Summary of Natural Gas Energy Efficiency Potential ...............................................6-5

Table 6-4 Electric Achievable Potential by Sector (GWh).........................................................6-6

Table 6-5 Natural Gas Achievable Potential by Sector (million therms) ....................................6-8

Table 7-1 Electricity Energy Efficiency Potential for the Residential Sector ...............................7-2

Table 7-2 Residential Electric Potential by Market Segment, 2016 ...........................................7-3

Table 7-3 Res. Electric Achievable Low Potential by End Use & Market Segment, 2016 (GWh)..7-3

Table 7-4 Residential Electric Savings by End Use and Potential Type (GWh)...........................7-3

Table 7-5 Natural Gas Energy Efficiency Potential for the Residential Sector............................7-6

Table 7-6 Residential Natural Gas Potential by Market Segment, 2016 (1000 therms) ..............7-7

Table 7-7 Res Achievable Potential Low by End Use & Market Segment, 2016 (1000 therms)...7-7

Table 7-8 Residential Natural Gas Savings by End Use and Potential Type (million therms) ......7-7

Table 7-9 Electricity Efficiency Potential for the Commercial Sector .......................................7-10

Table 7-10 Commercial Electric Potential by Market Segment, 2016........................................7-11

Table 7-11 Com Electric Achievable Low Potential by End Use & Market Segment, 2016 (GWh)7-12

Table 7-12 Commercial Potential by End Use and Potential Type (GWh) .................................7-13

Table 7-13 Natural Gas Efficiency Potential for the Commercial Sector....................................7-15

Table 7-14 Commercial Natural Gas Potential by Market Segment, 2016 .................................7-16

Table 7-15 Commercial Natural Gas Achievable High Potential by End Use & Market Segment, 

2016 (million therms)..........................................................................................7-16

Table 7-16 Commercial Natural Gas Potential by End Use and Potential Type (million therms)..7-17

Table 7-17 Electric Efficiency Potential for the Industrial Sector..............................................7-19

Table 7-18 Industrial Electric Potential by Market Segment, 2016 ...........................................7-20

Table 7-19 Industrial Electric Achievable Potential Low by End Use & Market Segment, 2016 ...7-20

Table 7-20 Industrial Electric Potential by End Use and Potential Type (GWh) .........................7-21

Table 7-21 Natural Gas Efficiency Potential for the Industrial Sector .......................................7-23

Table 7-22 Industrial Natural Gas Potential by Market Segment, 2016 ....................................7-24

Table 7-23 Industrial Natural Gas Achievable Potential Low by End Use & Market Segment, 2016 

(million therms)..................................................................................................7-24

Table 7-24 Industrial Natural Gas Potential by End Use and Potential Type (thousand therms).7-25

Table 8-1 Alternate Avoided Cost Scenario, Count of Measures Passing Economic Screen.........8-1
EnerNOC Utility Solutions Consulting xi

Table 8-2 Alternate Avoided Cost Scenario, 2016 Achievable Low Potential (GWh savings).......8-1

Table 8-3 Alternate Avoided Cost Scenario, 2016 Achievable Low Potential (million therm savings)

...........................................................................................................................8-2

Table 9-1 Converting to kBTU for Switching Comparison ........................................................9-1

Table 9-2 Switching Options and Directionality ......................................................................9-2

Table 9-3 Space Heating – Number of Fuel Switching Units ....................................................9-4

Table 9-4 Water Heating – Number of Fuel Switching Units ....................................................9-5

Table 11-1 Comparison to other studies (average annual savings vs. baseline forecast)...........11-1

Table 12-1 Summary of Combined Electric and Natural Gas Energy Efficiency Potential ...........12-2

Table 12-2 Summary of Electric Energy Efficiency Potential ....................................................12-3

Table 12-3 Summary of Natural Gas Energy Efficiency Potential .............................................12-5

Table 12-4 Electric Achievable Potential by Sector (GWh).......................................................12-6

Table 12-5 Natural Gas Achievable Potential by Sector (million therms) ..................................12-8

EnerNOC Utility Solutions Consulting 1-1

INTRODUCTION

Background

The New Jersey Board of Public Utilities (BPU or the Board) is commencing a proceeding to 

examine the appropriate funding level for energy efficiency (EE) programs over the next four 

years, 2013 through 2016. Pursuant to the 1999, Electric Discount and Energy Competition Act, 

this will be the BPU’s fourth comprehensive resource analysis (CRA). 

The BPU has contracted with EnerNOC to conduct a market assessment and energy efficiency

potential study to assess the potential statewide impacts from energy efficiency resources for 

this time period. 

Toward this end, EnerNOC conducted a detailed, bottom-up assessment of the New Jersey 

market to deliver forecasts of both electric and natural gas energy use, as well as forecasts of 

the electric and natural gas energy savings achievable through energy efficiency measures. The

potential study addresses the residential, commercial, and industrial sectors. 

Objectives

The study addresses energy efficiency potential and informs the CRA process in the following 

ways:

 Determines markets to address with EE programs 

 Finds the potential for energy savings for the 2013–2016 period

 Provides high-level recommendations regarding programs

Report Organization

This report is presented in 3 volumes as outlined below. This document is Volume 2: Report.

 Volume 1, Executive Summary

 Volume 2, Report

 Volume 3, Appendices 

Definitions of Potential

In this study, we estimate the potential for energy efficiency savings. The savings estimates 

represent gross savings1 developed into three types of potential: technical potential, economic 

potential, and achievable potential. Technical and economic potential are both theoretical limits 

to efficiency savings. Achievable potential embodies a set of assumptions about the decisions 

consumers make regarding the efficiency of the equipment they purchase, the maintenance 

activities they undertake, the controls they use for energy-consuming equipment, and the 

elements of building construction. Because estimating achievable potential involves the inherent 

uncertainty of predicting human behaviors and responses to market conditions , we developed 

low and high achievable potential as boundaries for a likely range. The various levels are 

described below.

 

1

Savings in “gross” terms instead of “net” terms means that the baseline forecast does not include naturally occurring efficiency. In 

other words, the baseline assumes that energy efficiency levels remain fixed as they are today. This rule holds true except in cases 

where enactment of future codes and standards were on the books before January 2012, e.g. the effects of the EISA 2007 lighting 

efficiency standard.

CHAPTER 1
Introduction

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 Technical potential is defined as the theoretical upper limit of energy efficiency potential. 

It assumes that customers adopt all feasible measures regardless of their cost. At the time of 

existing equipment failure, customers replace their equipment with the most efficient option 

available. In new construction, customers and developers also choose the most efficient 

equipment option. Examples of measures that make up technical potential for electricity in 

the residential sector include:

o Ductless mini-split air conditioners with variable refrigerant flow 

o Ground source (or geothermal) heat pumps 

o LED lighting 

Technical potential also assumes the adoption of every other available measure, where 

applicable. For example, it includes installation of high-efficiency windows in all new 

construction opportunities and air conditioner maintenance in all existing buildings with 

central and room air conditioning. These retrofit measures are phased in over a number of 

years, which is longer for higher-cost and complex measures. 

 Economic potential represents the adoption of all cost-effective energy efficiency 

measures. In this analysis, the cost effectiveness is measured by the total resource cost 

(TRC) test, which compares lifetime energy and capacity benefits to the incremental cost of 

the measure. If the benefits outweigh the costs (that is, if the TRC ratio is greater than 1.0), 

a given measure is considered in the economic potential. Customers are then assumed to 

purchase the most cost-effective option applicable to them at any decision juncture.

 Achievable High potential estimates customer adoption of economic measures when 

delivered through efficiency programs under ideal market, implementation, and customer 

preference conditions. Information channels are assumed to be established and efficient for 

marketing, educating consumers, and coordinating with trade allies and delivery partners. 

Achievable High potential establishes a maximum target for the EE savings that an 

administrator can hope to achieve through its EE programs and involves incentives that 

represent a substantial portion of the incremental cost combined with high administrative 

and marketing costs. 

 Achievable Low potential reflects expected program participation given significant barriers 

to customer acceptance, non-ideal implementation conditions, and limited program budgets. 

This represents a lower bound on achievable potential.

Abbreviations and Acronyms

Throughout the report we use several abbreviations and acronyms. Table 1-1 shows the 

abbreviation or acronym, along with an explanation.
Introduction

EnerNOC Utility Solutions Consulting 1-3

Table 1-1 Explanation of Abbreviations and Acronyms

Acronym Explanation

ACS American Community Survey

AEO Annual Energy Outlook forecast developed annual by the Energy 

Information Administration of the DOE

AHAM Association of Home Appliance Manufacturers 

B/C Ratio Benefit to cost ratio

BEST EnerNOC’s Building Energy Simulation Tool

CEEEP Rutgers University’s Center for Energy, Economic and Environmental 

Policy

CAC Central air conditioning

C&I Commercial and industrial

CFL Compact fluorescent lamp

DEEM EnerNOC’s Database of Energy Efficiency Measures

DEER State of California Database for Energy-Efficient Resources

DSM Demand side management

DR Demand response

EE Energy efficiency

EIA Energy Information Administration

EISA Energy Efficiency and Security Act of 2007

EPACT Energy Policy Act of 2005

EPRI Electric Power Research Institute

EUEA Efficient Use of Energy Act

EUI Energy-use index

HH Household

HID High intensity discharge lamps

HPWH Heat pump water heater

LED Light emitting diode lamp

LoadMAP EnerNOC’s Load Management Analysis and PlanningTM tool

NJCEP New Jersey Clean Energy Program

NJOCE New Jersey Office of Clean Energy

NWPCC Northwest Power and Conservation Council

RTU Roof top unit

Sq. ft. Square feet

TRC Total resource cost

UEC Unit energy consumption

EnerNOC Utility Solutions Consulting 2-1

ANALYSIS APPROACH AND DATA DEVELOPMENT

This section describes the analysis approach taken for the study and the data sources used to 

develop the potential estimates.

Analysis Approach

To perform the energy efficiency analysis, EnerNOC used a bottom-up analysis approach as 

shown in Figure 2-1. This involved the following steps.

1. Held a meeting with the client project team to refine the objectives of the project in detail. 

This resulted in a work plan for the study.

2. Performed a market characterization to describe sector-level electricity and natural gas use 

for the residential, commercial, and industrial sectors for the base year, 2010. This included 

using existing information contained in prior New Jersey studies, in EnerNOC’s own 

databases and tools, and in other secondary data sources such as the American Community 

Survey (ACS) and the Energy Information Administration (EIA).

3. Developed a baseline electricity and natural gas forecast by sector, segment, and end use for 

2013 through 2024. Results presented in this volume focus on the upcoming four-year 

implementation cycle of 2013 through 2016. Results beyond 2016 are available in the 

Appendices and are given at a high level in Chapter 12 of this document.

4. Identified several hundred measures and estimated their effects in four levels of energy -

efficiency potential: Technical, Economic, Achievable High, and Achievable Low.

5. Reviewed the current programs offered in New Jersey in light of the study findings to make 

strategic program recommendations for achieving savings. 

These steps are described in further detail throughout the remainder of this chapter.

CHAPTER 2
Analysis Approach and Data Development

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Figure 2-1 Overview of Analysis Approach

LoadMAP Model

We used EnerNOC’s Load Management Analysis and Planning tool (LoadMAPTM) version 3.0 to 

develop both the baseline forecast and the estimates of energy efficiency potential. EnerNOC

developed LoadMAP in 2007 and has enhanced it over time, using it for the EPRI National 

Potential Study and numerous utility-specific forecasting and potential studies. Built in Excel, the 

LoadMAP framework (see Figure 2-2) is both accessible and transparent and has the following 

key features.

 Embodies the basic principles of rigorous end-use models (such as EPRI’s REEPS and 

COMMEND) but in a more simplified, accessible form. 

 Includes stock-accounting algorithms that treat older, less efficient appliance/equipment 

stock separately from newer, more efficient equipment. Equipment is replaced according to 

the measure life and appliance vintage distributions defined by the user.

 Balances the competing needs of simplicity and robustness by incorporating important 

modeling details related to equipment saturations, efficiencies, vintage, and the like, where 

market data are available, and treats end uses separately to account for varying importance 

and availability of data resources. 

 Isolates new construction from existing equipment and buildings and treats purchase 

decisions for new construction and existing buildings separately. 
Analysis Approach and Data Development

EnerNOC Utility Solutions Consulting 2-3

 Uses a simple logic for appliance and equipment decisions. Other models available for this 

purpose embody complex decision choice algorithms or diffusion assumptions, and the model 

parameters tend to be difficult to estimate or observe and sometimes produce anomalous 

results that require calibration or even overriding. The LoadMAP approach allows the user to 

drive the appliance and equipment choices year by year directly in the model. This flexible 

approach allows users to import the results from diffusion models or to input individual 

assumptions. The framework also facilitates sensitivity analysis. 

 Includes appliance and equipment models customized by end use. For example, the logic for 

lighting is distinct from refrigerators and freezers. 

 Can accommodate various levels of segmentation. Analysis can be performed at the sector 

level (e.g., total residential) or for customized segments within sectors (e.g., housing type or 

income level).

Consistent with the segmentation scheme and the market profiles we describe below, the 

LoadMAP model provides forecasts of baseline energy use by sector, segment, end use , and 

technology for existing and new buildings. It also provides forecasts of total energy use and 

energy-efficiency savings associated with the four types of potential.2

Figure 2-2 LoadMAP Analysis Framework

Forecast Data

Market Profiles

Market size

Equipment saturation

Fuel shares

Technology shares

Vintage distribution

Unit energy consumption

Coincident demand

Base-year Energy

Consumption

by technology,

end use, segment, 

vintage & sector

Economic Data

Customer growth

Energy prices

Exogenous factors

Elasticities

Energy-efficiency

analysis

Forecast Results

List of measures

Saturations

Adoption rates

Avoided costs

Cost-effectiveness 

screening

Baseline forecast

Savings

Estimates

(Annual & peak)

Technical potential

Economic potential

Achievable potential

Customer segmentation Energy-efficiency 

forecasts:

Technical

Economic 

Achievable

Technology Data

Efficiency options

Codes and standards

Purchase shares

Market Characterization

In order to estimate the savings potential from energy-efficient measures, it is necessary to 

understand how much energy is used today and what equipment is currently being used. This 

characterization begins with a segmentation of New Jersey’s energy footprint to quantify energy 

use by sector, segment, fuel, end-use application, and the current set of technologies used. We 

incorporate information from the secondary research sources to advise the market 

characterization. 

 

2

The model computes energy and peak-demand forecasts for each type of potential for each end use as an intermediate calculation. 

Annual-energy and peak-demand savings are calculated as the difference between the value in the baseline forecast and the value in 

the potential forecast (e.g., the technical potential forecast).
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Segmentation for Modeling Purposes

The market assessment first defined the market segments (building types, end uses and other 

dimensions) that are relevant in New Jersey. The segmentation scheme for this project is 

presented in Table 2-1. 

Table 2-1 Overview of Segmentation Scheme for Potentials Modeling

Market 

Dimension Segmentation Variable Dimension Examples

1 Sector Residential, commercial, industrial

2 Building type

Residential (housing type, income level, ownership) 

Commercial (Office, Restaurant, Retail, etc.)

Industrial (Chemicals & Pharmaceuticals, Paper 

Products, Food Products, and Other industrial)

3 Vintage Existing and new construction 

4 Fuel Electricity, natural gas

5 End uses Cooling, lighting, water heat, motors, etc. (as 

appropriate by sector)

6

Appliances/end uses and 

technologies

Technologies such as lamp type, air conditioning 

equipment, motors by application, etc. 

7

Equipment efficiency levels for 

new purchases

Baseline and higher-efficiency options as appropriate 

for each technology

Following this scheme, the residential sector was segmented as described below, starting with 

customer segments by building type:

 Single family (including duplexes)

 Limited income single family (including duplexes)

 Multi family renters

 Limited income multi family renters

 Multi family owners

 Limited income multi family owners

For the purposes of this study, Limited Income refers to homes having income below $35,000 

per year, or approximately twice the federal poverty level.3

In addition to segmentation by housing type, we identified the set of end uses and technologies 

that are appropriate for New Jersey. These are shown in Table 2-2 and Table 2-3.

 

3 This definition aligns with categories in available data sources from the US Department of Energy. It is also similar to the 

qualification criteria for households to participate in the New Jersey Comfort Partners program, which are currently set at 

225% of the federal poverty level, and change based on household size. See: 

http://www.njcleanenergy.com/residential/programs/comfort-partners/comfort-partners
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Table 2-2 Residential Electric End Uses and Technologies

End Use Technology

Cooling Central Air Conditioning (CAC)

Cooling Room Air Conditioning (RAC)

Cooling/Heating Air-Source Heat Pump

Cooling/Heating Geothermal Heat Pump

Space Heating Electric Resistance

Space Heating Electric Furnace

Water Heating Water Heater <= 55 gal

Water Heating Water Heater > 55 gal

Interior Lighting Screw-in Lamps

Interior Lighting Linear Fluorescent Lamps

Exterior Lighting Screw-in Lamps

Appliances Clothes Washer 

Appliances Clothes Dryer 

Appliances Dishwasher

Appliances Refrigerator

Appliances Freezer 

Appliances Second Refrigerator

Appliances Stove

Appliances Microwaves

Electronics Personal Computers

Electronics Monitor

Electronics Laptops

Electronics TVs

Electronics Printer/Fax/Copier 

Electronics Set-top Boxes/DVR

Electronics Devices and Gadgets

Miscellaneous Pool Pump

Miscellaneous Pool Heater

Miscellaneous Hot Tub / Spa

Miscellaneous Well Pump

Miscellaneous Furnace Fan

Miscellaneous Miscellaneous

Table 2-3 Residential Natural Gas End Uses and Technologies

End Use Technology

Space Heating Furnace

Space Heating Boiler

Space Heating Other Heating

Water Heating Water Heater <= 55 gal

Water Heating Water Heater > 55 gal

Appliances Clothes Dryer

Appliances Stove/Oven

Miscellaneous Pool Heater

Miscellaneous Hot Tub / Spa

Miscellaneous Miscellaneous
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For the commercial sector, it is useful to analyze the segments based on the unique 

characteristics of the building type. For this study, we used the following building types.

 Small Office—all types of offices, including medical/dental offices

 Large Office—all types of offices, including large government facilities

 Restaurant—fast-food, sit-down and cafeteria-style restaurants

 Retail—retail establishments such as small boutiques, and large box retailers

 Grocery—convenience stores, small markets, and supermarkets

 College—colleges, universities and technical colleges

 School—primary and secondary schools

 Health—hospitals and nursing homes

 Lodging—motels, hotels, resorts and small inns

 Warehouse—storage facilities, refrigerated and unrefrigerated

 Miscellaneous—all remaining building types, such as police stations, parking garages, public 

assembly, amusement parks, etc.

In addition to segmentation by building type, we identified the set of end uses and technologies 

that are appropriate for New Jersey. Table 2-4 and Table 2-5 list the end uses and technologies 

used in this study.
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Table 2-4 Commercial Electric End Uses and Technologies

End Use Technology

Cooling Air-Cooled Chiller

Cooling Water-Cooled Chiller

Cooling Roof top AC

Cooling Other Cooling

Cooling/Heating Air-Source Heat Pump

Cooling/Heating Geothermal Heat Pump

Heating Electric Room Heat

Heating Electric Furnace

Ventilation Ventilation

Water Heating Water Heater

Interior Lighting Screw-in

Interior Lighting High-Bay Fixtures

Interior Lighting Linear Fluorescent

Exterior Lighting Screw-in

Exterior Lighting HID

Exterior Lighting Linear Fluorescent

Refrigeration Walk-in Refrigerator

Refrigeration Reach-in Refrigerator

Refrigeration Glass Door Display

Refrigeration Open Display Case

Refrigeration Icemaker

Refrigeration Vending Machine

Food Preparation Oven

Food Preparation Fryer

Food Preparation Dishwasher

Food Preparation Hot Food Container

Office Equipment Desktop Computer

Office Equipment Laptop

Office Equipment Server

Office Equipment Monitor

Office Equipment Printer/Copier/Fax

Office Equipment POS Terminal

Miscellaneous Non-HVAC Motors

Miscellaneous Pool Pump

Miscellaneous Pool Heater

Miscellaneous Miscellaneous
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Table 2-5 Commercial Natural Gas End Uses and Technologies

End Use Technology

Heating Furnace

Heating Boiler

Heating Other Heating

Water Heating Water Heater

Food Preparation Oven

Food Preparation Fryer

Food Preparation Broiler

Food Preparation Griddle

Food Preparation Range

Food Preparation Steamer

Miscellaneous Pool Heater

Miscellaneous Miscellaneous

For the industrial sector, the study isolated the top few industries in New Jersey by energy 

consumption, which accounted for 57% of the total 2010 industrial electricity sales and 65% of 

natural gas sales. The remaining group of industrial customers is considered in aggregate as 

“other industrial.” While the commercial sector has a relatively small set of building types that 

have relatively uniform characteristics, the sheer number of unique industry types makes it 

infeasible to perform a deep dive into all but the largest ones. This results in larger “other” or 

“miscellaneous” segment than that which exists in the commercial sector. Nonetheless, these 

“other” industries typically have energy use characteristics that are similar enough to perform an 

accurate potential assessment. 

The resulting segmentation is as follows:

 Chemical and Pharmaceutical Products (analyzed together due to similar allocation of energy 

within end uses and processes)

 Paper Products

 Food Products

 Other Industrial 

In addition to segmentation by industry, we identified the set of end uses and technologies that 

are appropriate for New Jersey. These are shown in Table 2-6 and Table 2-7.
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Table 2-6 Industrial Electric End Uses and Technologies

End Use Technology

Cooling Air-Cooled Chiller

Cooling Water-Cooled Chiller

Cooling Roof top AC

Cooling Other Cooling

Cooling/Heating Air-Source Heat Pump

Cooling/Heating Geothermal Heat Pump

Heating Electric Room Heat

Heating Electric Furnace

Ventilation Ventilation

Water Heating Water Heater

Interior Lighting Screw-in

Interior Lighting High-Bay Fixtures

Interior Lighting Linear Fluorescent

Exterior Lighting Screw-in

Exterior Lighting HID

Exterior Lighting Linear Fluorescent

Motors Pumps

Motors Fans & Blowers

Motors Compressed Air

Motors Material Handling

Motors Material Processing

Motors Other Motors

Process Process Heating

Process Process Cooling and Refrigeration

Process Electro-Chemical Processes

Process Other Process

Miscellaneous Miscellaneous

Table 2-7 Industrial Natural Gas End Uses and Technologies

End Use Technology

Heating Furnace

Heating Boiler

Heating Other Heating

Process Process Heating

Process Process Boiler

Process Process Cooling

Process Other Process

Miscellaneous Miscellaneous

With the segmentation scheme defined, we then performed a high-level market characterization 

of electricity and natural gas sales in the base year to allocate sales to each customer segment. 

We used various data sources to identify the annual sales in each customer segment, as well as 

the market size for each segment. This information provided control totals at a sector level for 

calibrating the LoadMAP model to known data for the base-year. 

Market Profiles

The next step was to develop market profiles for each sector, customer segment, end use , and 

technology. A market profile includes the following elements:
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 Market size is a representation of the number of customers in the segment. For the 

residential sector, it is number of households. In the commercial sector, it is floor space 

measured in square feet. For the industrial sector, it is number of employees. 

 Saturations define the fraction of homes and square feet with the various technologies. 

(e.g., homes with electric space heating, commercial floor space with gas water heating). 

 UEC (unit energy consumption) or EUI (energy-use index) describes the amount of 

energy consumed in 2010 by a specific technology in buildings that have the technology. For 

electricity, UECs are expressed in kWh/household for the residential sector, and EUIs are 

expressed in kWh/square foot or kWh/employee for the commercial and industrial sectors, 

respectively.

 Intensity for the residential sector represents the average energy use for the technology 

across all homes in 2010. It is computed as the product of the saturation and the UEC and is 

defined as kWh/household for electricity. For the commercial and industrial sectors, intensity, 

computed as the product of the saturation and the EUI, represents the average use for the 

technology across all floor space or all employees in 2010.

 Usage is the annual energy use by a technology/end use in the segment. It is the product of 

the market size and intensity and is quantified in GWh for electricity and MMTherms for 

natural gas. 

The market assessment results and the market profiles are presented in Chapter 3.

Baseline Forecast

The next step was to develop the baseline forecast of annual electricity and natural gas usage

for 2010 through 2016 by customer segment and end use without new utility programs or 

naturally occurring efficiency. The end-use forecast does include the relatively certain impacts of 

codes and standards that will unfold over the study timeframe. All such mandates tha t were 

defined as of January 2012 are included in the baseline. The baseline forecast is the foundation 

for the analysis of savings from future EE efforts as well as the metric against which potential 

savings are measured.

Inputs to the baseline forecast include:

 Current economic growth forecasts (i.e., customer growth, income growth)

 Electricity and natural gas price forecasts

 Trends in fuel shares and equipment saturations 

 Existing and approved changes to building codes and equipment standards

We present the results of the baseline forecast development in Chapter 4.

Energy Efficiency Measure Analysis

This section describes the framework used to assess the savings, costs, and other attributes of 

energy-efficiency measures. These characteristics form the basis for measure-level costeffectiveness analyses as well as for determining measure-level savings. For all measures, 

EnerNOC assembled information to reflect equipment performance, incremental costs, and 

equipment lifetimes. We used this information, along with New Jersey’s avoided costs data, in 

the economic screen to determine economically feasible measures. Figure 2-3 outlines the 

framework for measure analysis.
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EnerNOC Utility Solutions Consulting 2-11

Figure 2-3 Approach for Measure Assessment

Economic 

screen

Measure characterization

Measure 

descriptions

Energy 

savings Costs

Lifetime Saturation and 

applicability

EnerNOC 

universal 

measure list

Building 

simulations

EnerNOC measure 

data library

Client measure data 

library 

(TRMs, evaluation 

reports, etc)

Avoided costs, 

discount rate, 

delivery losses

Client review / 

feedback

Inputs Process

The framework for assessing savings, costs, and other attributes of energy efficiency measures 

involves identifying the list of energy efficiency measures to include in the analysis, deter mining 

their applicability to each market sector and segment, fully characterizing each measure, and 

performing cost-effectiveness screening. 

We compiled a robust list of energy efficiency measures for each customer sector, drawing upon 

the New Jersey program experience and protocols, EnerNOC’s own measure databases and 

building simulation models, and secondary sources. This universal list of EE measures covers all 

major types of end-use equipment, as well as devices and actions to reduce energy consumption. 

If considered today, some of these measures would not pass the economic screens initially, but 

may pass in future years as a result of lower projected equipment costs or higher avoided costs.

The selected measures are categorized into two types according to the LoadMAP taxonomy: 

equipment measures and non-equipment measures.

 Equipment measures are efficient energy-consuming pieces of equipment that save energy 

by providing the same service with a lower energy requirement than a standard unit. An 

example is an ENERGY STAR refrigerator that replaces a standard efficiency refrigerator. For 

equipment measures, many efficiency levels may be available for a given technology, ranging 

from the baseline unit (often determined by code or standard) up to the most efficient 

product commercially available. For instance, in the case of central air conditioners, this list 

begins with the current federal standard SEER 13 unit and spans a broad spectrum up to a 

maximum efficiency of a SEER 21 unit.

 Non-equipment measures save energy by reducing the need for delivered energy, but do 

not involve replacement or purchase of major end-use equipment (such as a refrigerator or 

air conditioner). An example would be a programmable thermostat that is pre-set to run 

heating and cooling systems only when people are home. Non-equipment measures can 
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apply to more than one end use. For instance, addition of wall insulation will affect the 

energy use of both space heating and cooling. Non-equipment measures typically fall into 

one of the following categories: 

 Building shell (windows, insulation, roofing material)

 Equipment controls (thermostat, energy management system)

 Equipment maintenance (cleaning filters, changing setpoints)

 Whole-building design (building orientation, passive solar lighting)

 Lighting retrofits (included as a non-equipment measure because retrofits are performed 

prior to the equipment’s normal end of life)

 Displacement measures (ceiling fan to reduce use of central air conditioners)

 Commissioning and retrocommissioning

We developed a preliminary list of EE measures, which was distributed to the BPU and CEEEP for 

review. The list was finalized after incorporating comments, and can be found in Chapter 5 of 

this report.

Once we assembled the list of EE measures, the project team assessed their energy-saving 

characteristics. For each measure we also characterized incremental cost, service life, and other 

performance factors. Following the measure characterization, we performed an economic 

screening of each measure, which serves as the basis for developing the economic and 

achievable potential. 

Representative Measure Data Inputs

To provide an example of the measure data, Table 2-8 and Table 2-9 present samples of the 

detailed data inputs behind both equipment and non-equipment measures, respectively, for the 

case of residential CAC in single-family homes. Table 2-8 displays the various efficiency levels 

available as equipment measures, as well as the corresponding useful life, energy usage, and 

cost estimates. The columns labeled On Market and Off Market reflect equipment availability due 

to codes and standards or the entry of new products to the market.

Table 2-8 Sample Equipment Measures for Central Air Conditioning – Single Family Home

Efficiency Level Useful Life Equipment 

Cost

Energy 

Usage(kWh/yr)

On 

Market

Off 

Market

SEER 13 15 $1,640 2,483 2010 n/a

SEER 14 (ENERGY STAR) 15 $1,766 2,278 2010 n/a

SEER 15 (CEE Tier 2) 15 $1,892 2,202 2010 n/a

SEER 16 (CEE Tier 3) 15 $2,018 2,137 2010 n/a

SEER 17 (Ductless Mini-split) 15 $3,863 2,083 2010 n/a

SEER 21 15 $3,784 1,686 2010 n/a

Table 2-9 lists some of the non-equipment measures applicable to CAC in an existing singlefamily home. All measures are evaluated for cost effectiveness based on the lifetime benefits 

relative to the cost of the measure. The total savings and costs are calculated for each year of 

the study and depend on the base year saturation of the measure, the applicability 4 of the 

measure, and the savings as a percentage of the relevant energy end uses. 

 

4

The applicability factors take into account whether the measure is applicable to a particular building type and whether it is feasible to 

install the measure. For instance, attic fans are not applicable to homes where there is insufficient space in the attic or there is no attic 

at all.
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Table 2-9 Sample Non-Equipment Measures – Single Family Home, Existing

End Use Measure Saturation 

in 20105

ApplicabilityLifetime 

(yrs)

Measure 

Installed 

Cost

Energy 

Savings (%)

Cooling Central AC - Maintenance 37% 100% 4 $125 9.9%

Cooling Repair and Sealing –

Ducting 16% 50% 18 $500 8.8%

Cooling Insulation - Ceiling 16% 72% 20 $1000 15.5%

Cooling Windows – Install Reflective 

Film 20% 45% 10 $895 26.2%

Cooling Windows - ENERGY STAR 47% 90% 25 $7500 7.2%

Cooling Thermostat -

Clock/Programmable 54% 56% 12 $73 7.3%

Screening Measures for Cost-Effectiveness 

Only measures that are cost-effective are included in economic and achievable potential.

Therefore, for each individual measure, LoadMAP performs an economic screen. This study uses 

the TRC test that compares the lifetime energy benefits (and peak demand for electricity) of 

each applicable measure with its incremental installed cost, including material and labor. There is 

no program administration cost considered in this analysis, and therefore, no specific program 

delivery methods or mechanisms are assumed. The lifetime benefits are calculated by multiplying 

the annual energy and demand savings for each measure by all appropriate avoided costs for 

each year, and discounting the dollar savings to the present value equivalent. The analysis uses 

each measure’s values for savings, costs, and lifetimes that were developed as part of the 

measure characterization process described above. 

The LoadMAP model performs this screening dynamically, taking into account changing savings 

and cost data over time. Thus, some measures pass the economic screen for some — but not all 

— of the years in the forecast. 

It is important to note the following about the economic screen: 

 The economic evaluation of every measure in the screen is conducted relative to a baseline 

condition. For instance, in order to determine the kilowatt-hour (kWh) savings potential of a 

measure, kWh consumption with the measure applied must be compared to the kWh 

consumption of a baseline condition. 

 The economic screening was conducted only for measures that are applicable to each 

building type and vintage; thus if a measure is deemed to be irrelevant to a particular 

building type and vintage, it is excluded from the respective economic screen.

Table 2-10 shows the results of the economic screen for CAC and select other measures. 

Throughout the time frame shown, the most cost-effective CAC option is SEER 16. For pool 

heaters, the heat pump unit becomes cost effective in 2015 due to changing market conditions 

and avoided costs, and eclipses the electric resistance unit as the highest effic iency economic 

unit. For refrigerators, however, the AHAM federal efficiency standards cause existing Energy 

Star units to become unavailable in 2014. Units compliant with AHAM 2014 thus become the new 

minimum efficiency baseline and are therefore assigned a benefit-to-cost (B/C) ratio of 1. Since 

there is not a more efficient, cost-effective unit available, they become the economic unit by 

default. If the measure passes the screen (has a B/C ratio greater than or equal to 1), the 

measure is included in economic potential. Otherwise, it is screened out for that year. If multiple 

 

5 Note that saturation levels reflected for the base year change over time as more measures are adopted. 
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equipment measures have B/C ratios greater than or equal to 1.0, the most efficient technology 

is selected by the economic screen. 

Table 2-10 Economic Screen Results for Selected Residential Equipment Measures

Technology 2013 2014 2015 2016

Central AC SEER 16 SEER 16 SEER 16 SEER 16

Pool Heater Electric 

Resistance

Electric 

Resistance

Heat Pump 

(COP = 5.0)

Heat Pump 

(COP = 5.0)

Refrigerator Energy Star AHAM (2014) AHAM (2014) AHAM (2014)

Energy-Efficiency Potential

The approach we used for this study adheres to the approaches and conventions outlined in the 

National Action Plan for Energy-Efficiency (NAPEE) Guide for Conducting Potential Studies 

(November 2007).6The NAPEE Guide represents the most credible and comprehensive industry 

practice for specifying energy-efficiency potential. As described in Chapter 1, four types of 

potentials were developed as part of this effort: Technical potential, Economic potential, 

Achievable High potential and Achievable Low potential

The calculation of Technical and Economic potential is a straightforward algorithm. To develop 

estimates for Achievable potential, we develop market adoption rates for each measure that 

specify the percentage of customers that will select the highest–efficiency economic option. The 

Achievable High adoption rates are based on the ramp rates from the Northwest Power & 

Conservation Council’s Sixth Plan as a starting point. The NWPCC has been running programs in 

the Pacific Northwest for many years, and the portfolio of programs reflects a similar profile of 

market maturity. The ramp rates are then adjusted with actual New Jersey program history and 

information from program evaluations. The Achievable Low adoption rates start with the 

Achievable High rates and decrement them by 40% to 75% based on where measures lie in the 

time horizon of the study or whether they are already familiar inclusions in existing programs. 

Finally, reasonableness checks are applied by comparing the adoption rates to those from other 

relevant potential studies and market research. 

The overall energy efficiency potential results are available in Chapter 6, and the results by 

sector are given in Chapter 7.

Alternative Avoided Cost Scenario 

To observe the sensitivity of study results to changes in forecast market prices of electricity and 

natural gas, we ran a scenario in which the avoided costs for each fuel in each year of the study 

were increased by 20%. The models were then re-run with all other variables held constant. The 

results of this review are presented in Chapter 8.

Fuel Switching Analysis

Typically, energy-efficiency potential studies may not explore the effects of switching 

technologies between system types and fuel types. In this context, where both electricity and 

natural gas are being studied on a statewide basis, we investigate these effects, including the 

switch from fuel oil furnaces to natural gas furnaces, which is particularly relevant to the New 

Jersey market. 

The equipment stock accounting inside the LoadMAP modeling tool supports fuel switching, and 

this analysis has been incorporated for the residential sector. The switching forecast is integrated 

with the traditional potential analysis, and operates on the same principles to calculate technical, 

economic, and achievable cases in turn. Several important adjustments are made to account for 

 

6 National Action Plan for Energy Efficiency (2007). National Action Plan for Energy Efficiency Vision for 2025: Developing a Framework 

for Change. www.epa.gov/eeactionplan.
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EnerNOC Utility Solutions Consulting 2-15

comparison of technical potential on a same-fuel, BTU basis; to account for increased switching 

costs; and to account for the increased complexity of the market decision and corresponding 

decreased customer adoption rates. These factors and the results are discussed and presented in 

Chapter 9.

Conclusions and Recommendations

In this final step, we review the potential estimates by measure, customer segment, and sector 

to develop a set of conclusions and recommendations to guide program efforts toward optimal 

pursuit of energy efficiency savings. The results of this review are presented in Chapter 10.

Data Development

This section details the data sources used in this study, followed by a discussion of how these 

sources were applied. In general, data were adapted to local conditions, for example, by using 

local sources for measure data and local weather for building simulations.

Data Sources

The data sources are organized into the following categories:

 New Jersey data

 EnerNOC’s databases and analysis tools

 Other secondary data and reports

New Jersey Data

Our highest priority data sources for this study were those that were specific to New Jersey. 

 Residential Energy Consumption Survey (RECS). In the most recent RECS survey 

conducted by the U.S. DOE, New Jersey was one of a handful of states singled out for a 

larger sample size and State-level estimates. We used these data extensively to develop 

residential market profiles as described below. 

http://www.eia.gov/consumption/residential/data/2009/

 American Community Survey: The US Census American Community Survey is an ongoing 

survey that provides data every year on household characteristics. Data for New Jersey were 

available for this study. http://www.census.gov/acs/www/

 EIA-826 data and EIA-176 forms from New Jersey utilities: These data sets were 

used to determine the state-wide current electricity and natural gas use for the study. 

http://www.eia.gov/electricity/sales_revenue_price/ and 

http://www.eia.gov/dnav/ng/ng_cons_sum_dcu_SNJ_a.htm

 New Jersey Clean Energy Library: The NJOCE website provides a comprehensive library 

of past research reports, program results, and evaluation studies, which were used to inform 

program recommendations and provide updated information on measure adoption and 

penetration. http://www.njcleanenergy.com/library

 New Jersey Economic Projections: Projections of key economic indicators were obtained 

from the Rutgers Economic Advisory Service (R/ECON). http://policy.rutgers.edu/cupr/recon/ 

Employment forecasts were obtained from the US Bureau of Labor Statistics. http://bls.gov/ 

Forecasts of avoided costs were obtained from a 2012 analysis performed by the New Jersey 

Rate Counsel.

 New Jersey Weather Data: Weather from NOAA’s National Climatic Data Center for 

Hightstown, NJ was used as the basis for building simulations.
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EnerNOC Databases, Analysis Tools, and Reports

EnerNOC maintains several databases and modeling tools that we use for forecasting and 

potential studies. 

 EnerNOC Energy Market Profiles: For more than 10 years, EnerNOC staff have 

maintained profiles of end-use consumption for the residential, commercial, and industrial 

sectors. These profiles include market size, fuel shares, unit consumption estimates, and 

annual energy use by fuel (electricity and natural gas), customer segment and end use for 10 

regions in the U.S. The Energy Information Administration surveys (RECS, CBECS and MECS) 

as well as state-level statistics and local customer research provide the foundation for these 

regional profiles.

 Building Energy Simulation Tool (BEST). EnerNOC’s BEST is a derivative of the DOE 2.2 

building simulation model, used to estimate base-year UECs and EUIs, as well as measure 

savings for the HVAC-related measures.

 EnerNOC’s EnergyShapeTM: This database of load shapes includes the following: 

Residential – electric load shapes for 10 regions, 3 housing types, 13 end uses; Commercial –

electric load shapes for 9 regions, 54 building types, 10 end uses; Industrial – electric load 

shapes, whole facility only, 19 2-digit SIC codes, as well as various 3-digit and 4-digit SIC 

codes 

 EnerNOC’s Database of Energy Efficiency Measures (DEEM): EnerNOC maintains an 

extensive database of measure data for our studies. Our database draws upon reliable 

sources including the California Database for Energy Efficient Resources (DEER), the EIA 

Technology Forecast Updates – Residential and Commercial Building Technologies –

Reference Case, RS Means cost data, and Grainger Catalog Cost data.

 Recent studies. EnerNOC has conducted numerous studies of EE potential in the last five 

years. We checked our input assumptions and analysis results against the results from these 

other studies, which include AmerenUE, Los Angeles Department of Water and Power, 

Consolidated Edison of New York, Avista Utilities, the State of New Mexico, Tennessee Valley 

Authority, and Seattle City Light. In addition, we used the information about impacts of 

building codes and appliance standards from a recent report for the Institute for Energy 

Efficiency.7

Other Secondary Data and Reports

Finally, a variety of secondary data sources and reports were used for this study. The main 

sources are identified below. 

 New Jersey and regional data from past EnerNOC projects: EnerNOC referenced data 

from our project with MISO, as well as regional data from similar studies for Con Edison of 

NY, PECO Energy, and the Connecticut Energy Efficiency Board (CEEB).

 California Statewide Surveys. The Residential Appliance Saturation Survey (RASS) and 

the Commercial End Use Survey (CEUS) are comprehensive market research studies 

conducted by the California Energy Commission. These databases provide a wealth of 

information on appliance use in homes and businesses. RASS is based on information from 

almost 25,000 homes and CEUS is based on information from a stratified random sample of 

almost 3,000 businesses in California. 

 Annual Energy Outlook. The Annual Energy Outlook (AEO), conducted each year by the 

U.S. Energy Information Administration (EIA), presents yearly projections and analysis of 

energy topics. For this study, we used data from the 2011 AEO. 

 

7

“Assessment of Electricity Savings in the U.S. Achievable through New Appliance/Equipment Efficiency Standards and Building 

Efficiency Codes (2010 – 2025).” Global Energy Partners, LLC for the Institute for Electric Efficiency, May 2011. 

http://www.edisonfoundation.net/iee/reports/IEE_CodesandStandardsAssessment_2010-2025_UPDATE.pdf
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EnerNOC Utility Solutions Consulting 2-17

 Electric Power Research Institute – Assessment of Achievable Potential from 

Energy Efficiency and Demand Response Programs in the U.S., also known as the 

EPRI National Potential Study (2009). In 2009, EPRI hired EnerNOC to conduct an 

assessment of the national potential for energy efficiency, with estimates derived for the four 

DOE regions (including the Mid Atlantic region that includes New Jersey).

 EPRI End-Use Models (REEPS and COMMEND). These models provide the elasticities we 

apply to electricity prices, household income, home size and heating and cooling.

 Database for Energy Efficient Resources (DEER). The California Energy Commission 

and California Public Utilities Commission (CPUC) sponsor this database, which is designed to 

provide well-documented estimates of energy and peak demand savings values, measure 

costs, and effective useful life (EUL) for the state of California. We used the DEER database 

to cross check the measure savings we developed using BEST and DEEM.

 Northwest Power and Conservation Council Sixth Plan workbooks. To develop its 

Power Plan, the Council maintains workbooks with detailed information about measures. 

 Other relevant regional sources: These include reports from the Consortium for Energy 

Efficiency, the Northeast Energy Efficiency Partnership, the EPA, and the American Council 

for an Energy-Efficient Economy.

Data Application

We now discuss how the data sources described above were used for each step of the study.

Data Application for Market Characterization

To construct the high-level market characterization of electricity use and households/floor space 

for the residential, commercial, and industrial sectors, we applied the following data sources: 

 RECS 2009 and the American Community Survey to allocate residential customers by housing 

type

 EIA, AEO 2011 and our Energy Market Profiles Database to allocate sales and square footage 

by building type for the commercial sector

 EIA data on energy use by industry type, Bureau of Labor Statistics and AEO 2011 data to 

allocate sales and employment for the industrial sector 

Data Application for Market Profiles

The specific data elements for the market profiles, together with the key data sources, are 

shown in Table 2-11. To develop the market profiles for each segment, we used the following 

approach: 

1. Developed control totals for each segment. These include market size, segment-level annual 

electricity use, and annual intensity. 

2. Used RECS 2009 and the American Housing Survey to incorporate information on existing 

appliance saturations, appliance and equipment characteristics, and building characteristics. 

3. Incorporated secondary data sources to supplement and corroborate the data from items 1 

and 2 above.

4. Compared and cross-checked with regional data obtained as part of the EPRI National 

Potential Study and with the Energy Market Profiles Database.

5. Ensured calibration to control totals for annual electricity and natural gas sales in each sector 

and segment.

6. Worked with BPU and CEEEP staff to vet the data against their knowledge and experience.
Analysis Approach and Data Development

2-18 www.enernoc.com

Table 2-11 Data Applied for the Market Profiles

Model Inputs Description Key Sources

Market size 

Base-year residential dwellings 

commercial floor space, and industrial 

employment

 EIA Form 826 and 176 data 

 American Community Survey 

 Energy Market Profiles

 AEO 

Annual intensity

Residential: Annual energy use 

(kWh/household)

Commercial: Annual energy use 

(kWh/sq ft)

Industrial: Annual energy use 

(kWh/employee)

 Energy Market Profiles 

 AEO

 Previous studies

Appliance/equipment 

saturations

Fraction of dwellings with an 

appliance/technology

Percentage of C&I floor 

space/employment with 

equipment/technology

 RECS 2009

 Energy Market Profiles

UEC/EUI for each 

end-use technology

UEC: Annual electricity use for a 

technology in dwellings that have the 

technology

EUI: Annual electricity use per square 

foot/employee for a technology in 

floor space that has the technology

 HVAC uses: BEST simulations using 

prototypes developed for NJ 

 Engineering analysis

 DEEM

 Previous EnerNOC studies 

 California RASS and CEUS

Appliance/equipment 

vintage distribution Age distribution for each technology  RECS 2009

 Previous EnerNOC studies

Efficiency options for 

each technology

List of available efficiency options and 

annual energy use for each technology

 DEEM

 DEER

 NWPCC workbooks

 Annual Energy Outlook

 Previous studies

Peak factors Share of technology energy use that 

occurs during the peak hour  EnergyShape database

Data Application for Baseline Forecast

Table 2-12 summarizes the LoadMAP model inputs required for the baseline forecast. These inputs 

are required for each segment within each sector, as well as for new construction and existing 

dwellings/buildings. 
Analysis Approach and Data Development

EnerNOC Utility Solutions Consulting 2-19

Table 2-12 Data Needs for the Baseline Forecast and Potentials Estimation in LoadMAP

Model Inputs Description Key Sources

Customer growth forecasts Forecasts of new construction in 

residential and C&I sectors

 AEO 2011 growth forecast

 R/ECON

 US BLS 

Equipment purchase shares for 

baseline forecast

For each equipment/technology, 

purchase shares for each 

efficiency level; specified 

separately for existing

equipment replacement and new 

construction

 Shipments data from AEO 

 AEO 2011 regional forecast 

assumptions8

 Appliance/efficiency standards 

analysis

 NJOCE program results and 

evaluation reports

Electricity and natural gas prices

Forecast of average energy and 

capacity avoided costs and retail 

prices

 CEEEP July 2012 analysis

 AEO 2011 

Utilization model parameters

Price elasticities, elasticities for 

other variables (income, 

weather)

 EPRI’s REEPS and COMMEND 

models

 AEO 2011

 NOAA data for normal cooling 

& heating degree days for 

Hightstown, NJ

The avoided cost forecasts implemented in the models, sourced from a 2012 CEEEP analysis, are 

available in Appendix G. The discount rate used for NPV analysis is a nominal rate of 8%, the 

same rate used in the 2012 CEEEP analysis and the previous EE potential studies done for the 

State of New Jersey. When adjusted for an average inflation rate of 2.92%, the discount rate is

4.94% in real terms.

We also implemented assumptions for known future equipment standards as of January, 2012, 

as shown in the tables below.

 

8 We developed baseline purchase decisions using the Energy Information Agency’s Annual Energy Outlook report (2011), which utilizes 

the National Energy Modeling System (NEMS) to produce a self-consistent supply and demand economic model. We calibrated 

equipment purchase options to match manufacturer shipment data for recent years and then held values constant for the study period. 

This removes any effects of naturally occurring conservation or effects of future DSM programs that may be embedded in the AEO 

forecasts. 
EnerNOC Utility Solutions Consulting 2-20

Table 2-13 Residential Electric Equipment Standards Applicable to New Jersey

Today's Efficiency or Standard Assumption 1st Standard (relative to today's standard)

2nd Standard (relative to today's standard)

End Use Technology 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 

Central AC

Room AC

Evaporative Central AC

Evaporative Room AC

Cooling/Heating Heat Pump

Space Heating Electric Resistance

Water Heater (<=55 gallons)

Water Heater (>55 gallons)

Screw-in/Pin Lamps

Linear Fluorescent

Refrigerator/2nd Refrigerator

Freezer

Dishwasher

Clothes Washer

Clothes Dryer

Range/Oven

Microwave

Personal Computer

Monitor

Laptop Computer

TV

Copier/Printer/Fax

DVD/VCR/Audio

Devices and Gadgets

Pool Pump

Well Pump

Furnace Fan

Miscellaneous

Conventional

Conventional

Conventional

SEER 13

Conventional

Conventional

Electronics

Conventional/Energy Star

Conventional

Conventional/Energy Star

Conventional/Energy Star

Conventional

Conventional

Conventional

Conventional (355 

kWh/yr)

14% more efficient (307 kWh/yr)

Conventional (MEF 1.26 for top loader) MEF 1.72 for top loader MEF 2.0 for top loader

Conventional (EF 3.01) 5% more efficient (EF 3.17)

Lighting

Incandescent Advanced Incandescent - tier 1 Advanced Incandescent - tier 2

T8 

Appliances

NAECA Standard 25% more efficient 

NAECA Standard 25% more efficient 

SEER 13.0/HSPF 7.7 SEER 14.0/HSPF 8.0

Electric Resistance

Water Heating

EF 0.90 EF 0.95

EF 0.90 Heat Pump Water Heater

Cooling

EER 9.8 EER 11.0

Conventional

Conventional
Analysis Approach and Data Development

EnerNOC Utility Solutions Consulting 2-21

Table 2-14 Commercial Electric Equipment Standards Applicable to New Jersey

Today's Efficiency or Standard Assumption 1st Standard (relative to today's standard)

2nd Standard (relative to today's standard)

End Use Technology 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 

Chillers

Roof Top Units

Packaged Terminal AC/HP EER 9.8

Cooling/Heating Heat Pump

Electric Resistance

Electric Furnace

Ventilation Ventilation

Screw-in/Pin Lamps

Linear Fluorescent T12

High Intensity Discharge

Water Heating Water Heater

Walk-in Refrigerator/Freezer

Reach-in Refrigerator

Glass Door Display EPACT 2005 

Standard

Open Display Case EPACT 2005 

Standard

Vending Machines EPACT 2005 

Standard

Icemaker

Desktop Computer

Laptop Computer

Non-HVAC Motors

Commercial Laundry

Miscellaneous

Incandescent Advanced Incandescent - tier 1

T8

EISA 2007 Standard

MEF 1.26 MEF 1.6

62.3% Efficiency 70% Efficiency

EF 0.97

Office Equipment

Refrigeration

EPACT 2005 Standard

42% more efficient

18% more efficient

33% more efficient

2010 Standard

Conventional/Energy Star

Conventional/Energy Star

Cooling

Space Heating

Lighting

2007 ASHRAE 90.1

EER 11.0/11.2

EER 11.0

EER 11.0/COP 3.3

Advanced Incandescent - tier 2

Electric Resistance

Electric Furnace

Constant Air Volume/Variable Air Volume

Metal Halide
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Table 2-15 Residential Gas Appliance Standards Applicable to New Jersey

Today's Efficiency or Standard Assumption

Next Standard (relative to today's standard)

2nd Standard (relative to today's standard)

End Use Technology 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 

Furnace

Boiler

Water Heater (<=55 gallons)

Water Heater (>55 gallons)

Clothes Dryer

Range/Oven Conventional

Miscellaneous Pool Heater Conventional EF 0.82

Space Heating

EF 0.81 EF 0.82

Water Heating

EF 0.59 EF 0.62

EF 0.59 Condensing Technology

AFUE 90% -Nonweatherized AFUE 80% AFUE 90% -Weatherized

Appliances

Conventional 5% more efficient

No Standing Pilot Light

Table 2-16 Commercial Gas Appliance Standards Applicable to New Jersey

Today's Efficiency or Standard Assumption

Next Standard (relative to today's standard)

End Use Technology 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 

Furnace

Boiler EF 0.76

Water Heating Water Heater 

Miscellaneous Pool Heater

Space Heating

AFUE 76%

EF 0.82

EF 0.80

Conventional EF 0.82
EnerNOC Utility Solutions Consulting 2-23

Energy Efficiency Measure Data Application

Table 2-17 details the data sources used for measure characterization.

Table 2-17 Data Needs for the Measure Characteristics in LoadMAP

Model Inputs Description Key Sources

Energy Impacts

The annual reduction in consumption attributable 

to each specific measure. Savings were developed 

as a percentage of the energy end use that the 

measure affects.

 BEST

 DEEM

 DEER

 NWPCC workbooks

 Other secondary sources

Peak Demand Impacts

Savings during the peak demand periods are 

specified for each electric measure. These impacts 

relate to the energy savings and depend on the 

extent to which each measure is coincident with 

the system peak.

 BEST

 EnergyShape

Costs

Equipment Measures: Includes the full cost of 

purchasing and installing the equipment on a perhousehold, per-square-foot, or per employee basis 

for the residential, commercial, and industrial

sectors, respectively.

Non-equipment measures: Existing buildings – full 

installed cost. New Construction - the costs may be 

either the full cost of the measure, or as 

appropriate, it may be the incremental cost of 

upgrading from a standard level to a higher 

efficiency level.

 DEEM

 DEER

 NWPCC workbooks

 RS Means

 Other secondary sources

Measure Lifetimes

Estimates derived from the technical data and 

secondary data sources that support the measure 

demand and energy savings analysis.

 DEEM

 DEER

 NWPCC workbooks

 Other secondary sources

Applicability

Estimate of the percentage of either dwellings in 

the residential sector or square feet/employment

in the C&I sectors where the measure is applicable 

and where it is technically feasible to implement.

 DEEM

 DEER

 NWPCC workbooks

 Other secondary sources

On Market and Off 

Market Availability

Expressed as years for equipment measures to 

reflect when the equipment technology is available 

or no longer available in the market.

 EnerNOC appliance 

standards and building 

codes analysis

Data Application for Cost-effectiveness Screening

To perform the cost-effectiveness screening, a number of economic assumptions were needed. 

All cost and benefit values were analyzed as real 2010 dollars. A discount rate of 8% in nominal 

terms was used, as developed in the CEEEP 2008 cost-effectiveness analysis. This is equivalent 

to a 4.93% discount rate in real terms when adjusting for 2.92% inflation. 9 As mentioned above, 

avoided costs were obtained from an analysis performed by the New Jersey Rate Counsel.

Electric delivery losses of 7.6% were obtained from an EIA 10-year New Jersey average10, 

whereas natural gas delivery losses of 1.4% are based on an EIA engineering estimate, as the 

gas distribution system is not tracked and monitored as rigorously as the electric system.11

 

9

Inflation adjuster of 2.92% based on the average annual growth forecast in US Consumer Price Index from the 2012 Annual Energy 

Outlook for 2010-2035.

10 http://www.eia.gov/electricity/state/newjersey

11 http://www.eia.gov/pub/itg/ghgp9.htm
Analysis Approach and Data Development

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Achievable Potential Estimation

To estimate achievable potentials, three sets of parameters were required to account for the 

decision making behavior of humans in the efficiency marketplace.

 Adoption curves for non-equipment measures. Equipment measures are installed when 

existing units fail. Non-equipment measures do not have this natural periodicity, so rather 

than installing all available non-equipment measures in the first year of the forecast 

(instantaneous potential), they are phased in according to adoption schedules that vary 

based on cost and complexity. The adoption rates used in this analysis take several factors 

into account to determine how quickly the market can absorb these measures. Typically, 

measures that cause disruption to the building, such as wall insulation in existing buildings, 

receive longer adoption curves, while those with drop-in installations, such as programmable 

thermostats in new buildings, receive shorter ones. High capital cost measures will also 

receive longer adoption curves than ones with low capital cost. These adoption rates are 

used within LoadMAP to generate the Technical and Economic potentials. In general, the 

rates align with the diffusion of similar equipment measures.

 Achievable High adoption rates. These factors are applied to Economic potential to 

estimate the upper bound: Achievable High. These estimate customer adoption of economic 

measures when delivered through efficiency programs under ideal market, implementation, 

and customer preference conditions. Information channels are assumed to be established 

and efficient for marketing, educating consumers, and coordinating with trade allies and 

delivery partners. The Achievable High adoption rates are based on the ramp rates from the 

Northwest Power & Conservation Council’s Sixth Plan as a starting point. The NWPCC has 

been running programs in the Pacific Northwest for many years, and the portfolio of 

programs reflects a similar profile of market maturity. The ramp rates are then adjusted wit h 

actual New Jersey program history and information from program evaluations. Achievable

High potential establishes a maximum target for the EE savings that an administrator can 

hope to achieve through its EE programs and involves incentives that represent a substantial 

portion of the incremental cost combined with high administrative and marketing costs. 

 Achievable Low adoption rates. These factors are applied to Achievable High potential to 

calculate Achievable Low potential, decrementing them by a range of 40% to 75% based on 

where measures lie in the time horizon of the study or whether they are already familiar 

inclusions in existing programs. These rates reflect expected program participation given 

significant barriers to customer acceptance, non-ideal implementation conditions, and limited 

program budgets. This represents a lower bound on achievable potential.

Achievable Low and Achievable High adoption rates are presented in Appendix E.
EnerNOC Utility Solutions Consulting 3-1

CHAPTER 3

MARKET CHARACTERIZATION AND MARKET PROFILES

In this section, we describe how customers in New Jersey use electricity and natural gas in the 

base year of the study, 2010. It begins with a high-level summary of energy use by sector and 

then delves into each sector in detail.

Energy Use Summary

Total electricity use for the residential, commercial and industrial sectors for New Jersey in 2010

was 78,859 GWh.12 As shown in Figure 3-1, the largest sector is commercial, accounting for 51%, 

or 40,123 GWh. The remaining use is split between the residential and industrial sectors, at 

30,307 GWh and 8,429 GWh respectively.

Figure 3-1 Sector-Level Electricity Use, 2010

Residential

38%

Commercial

51%

Industrial

11%

Total natural gas use for all sectors in 2010 was 4,619 million therms.

13 As shown in Figure 3-2, 

the largest sector is residential, accounting for 49%, or 2,255 million therms. The remaining use 

is split between the commercial and industrial sectors, at 1,867 million therms and 497 million 

therms respectively.

 

12 Energy given “at-the-meter,” i.e. does not include line losses.

13 Energy given “at-the-meter,” i.e. does not include line losses.
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Figure 3-2 Sector-Level Natural Gas Use, 2010

Residential

49%

Commercial

40%

Industrial

11%

Residential Sector

The total number of households, electric sales, and natural gas sales for the State of New Jersey 

were obtained for the year 2010 from the US DOE Energy Information Administration website. In 

2010, there were 3.45 million households in New Jersey. They used 30.3 TWh of electricity 14 and 

2.25 billion therms of natural gas. 15 We allocated these totals into the six residential segments 

based on survey data from the DOE’s latest Residential Energy Consumption Survey (RECS 

2009), which has an oversample for New Jersey. The values are shown in Table 3-1 below, and 

referred to throughout the study as the control totals to which all energy usage is calibrated in 

the base year of the study.

Table 3-1 Residential Sector Energy Usage and Intensity by Segment Type, 2010

Segment No. of 

Households

Electricity 

Use (GWh)

Electricity 

Avg Use

(kWh/hh)

Natural Gas 

Use (million 

therms)

Natural Gas 

Avg Use 

(therms/hh)

Single Family 1,682,988 17,946 10,663 1,286 764

Single Family LI 579,087 4,540 7,840 346 598

Multi Family Rent 500,082 3,785 7,570 307 614

Multi Family Rent LI 429,995 2,464 5,731 206 478

Multi Family Own 222,199 1,380 6,212 92 415

Multi Family Own LI 40,489 191 4,729 18 437

Total 3,454,840 30,307 8,772 2,255 653

 

14 U.S. DOE Energy Information Administration, See Table 2, http://www.eia.gov/electricity/sales_revenue_price/

15 U.S. DOE Energy Information Administration, http://205.254.135.7/dnav/ng/ng_cons_sum_dcu_nus_a.htm
Market Characterization and Market Profiles

EnerNOC Utility Solutions Consulting 3-3

Figure 3-3 and Figure 3-4 show the size of each of the segments as a percentage of customers 

and percentage of residential sector energy use.

Figure 3-3 Residential Market Segmentation by Housing Type – Percent of Households

Figure 3-4 Residential Market Segmentation by Housing Type – Percent of Energy Use

As we describe in the previous chapter, the market profiles provide the foundation upon which 

we develop the baseline forecast. The market profile for the residential sector as a whole is 

presented in Table 3-2 and Table 3-3. The residential market profiles for each housing segment 

are presented in Appendix A.
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Table 3-2 Electric Market Profile for the Residential Sector

UEC Intensity Usage

(kWh) (kWh/HH) (GWh)

Cooling Central AC 58.5% 2,356 1,379 4,764.3

Cooling Room AC 34.6% 1,176 407 1,406.8

Cooling Air-Source Heat Pump 0.5% 2,408 13 44.3

Cooling Geothermal Heat Pump 0.0% 0 0 0.0

Heating Electric Resistance 2.6% 8,182 214 738.6

Heating Electric Furnace 1.7% 7,518 129 447.3

Heating Air-Source Heat Pump 0.5% 7,068 38 130.2

Heating Geothermal Heat Pump 0.0% 0 0 0.0

Water Heating Water Heater <=55 gal 13.7% 2,419 331 1,142.4

Water Heating Water Heater > 55 gal 0.7% 3,152 22 74.9

Interior Lighting Screw-in 100.0% 1,050 1,050 3,627.0

Interior Lighting Linear Fluorescent 100.0% 131 131 453.4

Interior Lighting Specialty 100.0% 547 547 1,889.3

Exterior Lighting Screw-in 100.0% 253 253 875.1

Appliances Clothes Washer 78.4% 109 86 296.4

Appliances Clothes Dryer 33.1% 822 272 939.9

Appliances Dishwasher 68.6% 416 285 986.2

Appliances Refrigerator 100.0% 778 778 2,688.1

Appliances Freezer 20.8% 616 128 443.3

Appliances Second Refrigerator 30.5% 918 280 966.4

Appliances Stove 22.6% 469 106 366.4

Appliances Microwave 94.8% 133 126 435.8

Electronics Personal Computers 75.1% 283 212 733.1

Electronics Monitor 75.1% 56 42 145.9

Electronics Laptops 70.4% 116 82 282.9

Electronics TVs 286.1% 160 459 1,584.9

Electronics Printer/Fax/Copier 109.9% 41 46 157.4

Electronics Set-top Boxes/DVR 238.8% 110 262 903.9

Electronics Devices and Gadgets 100.0% 102 102 351.5

Miscellaneous Pool Pump 11.4% 1,500 171 590.6

Miscellaneous Pool Heater 0.6% 4,981 30 102.7

Miscellaneous Hot Tub / Spa 4.2% 950 40 136.8

Miscellaneous Well Pump 10.4% 561 59 202.1

Miscellaneous Furnace Fan 54.0% 396 214 739.0

Miscellaneous Miscellaneous 100.0% 480 480 1,659.8

 8,772 30,307.0

Average Market Profiles - Electricity

Total

End Use Technology Saturation
Market Characterization and Market Profiles

EnerNOC Utility Solutions Consulting 3-5

Table 3-3 Natural Gas Market Profile for the Residential Sector

UEC Intensity Usage

(therm) (therm/HH) (MMtherm)

Heating Furnace 52.3% 475 249 858.6

Heating Boiler 30.0% 649 195 673.0

Heating Other Heating 1.0% 411 4 14.8

Water Heating Water Heater <=55 gal 76.7% 151 116 401.4

Water Heating Water Heater > 55 gal 4.9% 196 10 33.2

Appliances Clothes Dryer 42.4% 34 14 49.6

Appliances Stove/Oven 75.6% 52 39 135.7

Miscellaneous Pool Heater 4.9% 154 8 26.0

Miscellaneous Hot Tub / Spa 7.6% 36 3 9.6

Miscellaneous Miscellaneous 100.0% 15 15 53.1

 653 2,255.0

Average Market Profiles - Natural Gas

End Use Technology Saturation

Total

Figure 3-5 shows the distribution of electricity and natural gas energy consumption by end use 

for all homes. Three main electricity end uses — cooling, lighting, and appliances — account for 

over 60% of total use. The remaining energy is allocated to space heating, water heating, 

electronics (computers, televisions, video game consoles, etc.) and miscellaneous. The 

miscellaneous category includes furnace fans, pool pumps, and other “plug” loads (hair dryers, 

power tools, coffee makers, etc.). Within the appliance category, 58% of electricity is used by 

refrigerators and freezers.

Natural gas usage is dominated by space heating (69%) and water heating (19%), with small 

amounts in appliances for cooking or clothes drying, as well as miscellaneous uses such as pool 

heaters. 

Figure 3-5 Residential Electricity and Natural Gas Use by End Use (2010), All Homes

New Jersey has high saturations of natural gas heating equipment, resulting in an average 

annual electricity intensity that is relatively low at 8,772 kWh per household. Meanwhile, the 

natural gas intensity is 653 therms per household16. 

Figure 3-6 and Table 3-4 present the electricity intensities by end-use and housing type, as well 

as all homes on average. Figure 3-7 shows the same data as a percentage of total energy use.

 

16 This is average natural gas use across all homes, including both those with natural gas and those without. 
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Figure 3-6 Residential Electricity Intensity by End Use and Segment (kWh/household, 2010)

Table 3-4 Residential Electricity Use by End Use and Segment (kWh/HH/year, 2010)

End Use Single 

Family

Single 

Family LI

Multi 

Family 

Rent

Multi 

Family 

Rent LI

Multi 

Family 

Own

Multi 

Family 

Own LI

All 

Homes

Cooling 2,286 1,467 1,454 1,020 1,456 716 1,799

Space Heating 408 352 597 94 373 85 381

Water Heating 367 94 350 684 255 479 352

Interior Lighting 1,965 1,778 1,732 1,224 926 866 1,728

Exterior Lighting 273 260 238 232 176 164 253

Appliances 2,497 1,968 1,571 1,405 1,517 1,335 2,062

Electronics 1,503 1,056 1,093 696 1,047 772 1,230

Miscellaneous 1,363 865 536 375 463 313 967

Total 10,663 7,840 7,570 5,731 6,212 4,729 8,772
Market Characterization and Market Profiles

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Figure 3-7 Breakdown of Residential Electricity Use by End Use and Segment (2010)

Figure 3-8 and Table 3-5 present the natural gas intensities by end-use and housing type, as well 

as all homes on average. Figure 3-9 shows the same data as a percentage of total energy use.

Figure 3-8 Residential Natural Gas Intensity by End Use and Segment (therm/household, 

2010)
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Table 3-5 Residential Natural Gas Use by End Use and Segment (therm/HH/year, 2010)

End Use Single 

Family

Single 

Family LI

Multi 

Family 

Rent

Multi 

Family 

Rent LI

Multi 

Family 

Own

Multi 

Family 

Own LI

All 

Homes

Space Heating 516 373 458 364 284 332 448

Water Heating 149 137 105 72 81 63 126

Appliances 62 69 36 29 40 30 54

Miscellaneous 36 20 15 14 10 13 26

Total 764 598 614 478 415 437 653

Figure 3-9 Breakdown of Residential Natural Gas Use by End Use and Segment (2010)

Commercial Sector

The total electric energy consumed by commercial customers in New Jersey in 2010 was 40,123 

GWh17 and the total natural gas energy consumed was 1,867 million therms. 18 We used 

EnerNOC’s database of Energy Market Profiles for the Mid-Atlantic region to allocate this energy 

usage to the various building types according to regional average square footage and energy 

intensity data. The values are shown in Table 3-6 below, and referred to throughout the study as 

the control totals to which all energy usage is calibrated in the base year of the study.

 

17 U.S. DOE Energy Information Administration, See Table 2, http://www.eia.gov/electricity/sales_revenue_price/

18 U.S. DOE Energy Information Administration, http://205.254.135.7/dnav/ng/ng_cons_sum_dcu_nus_a.htm
Market Characterization and Market Profiles

EnerNOC Utility Solutions Consulting 3-9

Table 3-6 Commercial Market Segmentation by Building Type, Base Year 2010

Segment

Floor Space

(million sq. ft.)

Electricity

2010 Use

(GWh)

Natural Gas

2010 Use

(million therms)

Small Office 384 4,470 196

Large Office 433 6,054 152

Restaurant 52 1,971 103

Retail 551 7,985 318

Grocery 97 4,421 61

College 209 2,188 109

School 325 2,011 149

Health 198 4,084 302

Lodging 100 1,113 64

Warehouse 365 2,640 102

Miscellaneous 407 3,187 311

Total 3,121 40,123 1,867

Figure 3-10 shows the size of each of the building-types as a percentage of commercial sector 

energy sales.

Figure 3-10 Commercial Market Segmentation by Building Type – Percent of Energy Use

Table 3-7 shows the market profile for electricity of the commercial sector as a whole, 

representing a composite of all the building types. Overall, about 55% of commercial floor space 

is cooled. Only about 13% of commercial floor space is heated using electric equipment, either 

some form of resistance heating or heat pumps. Linear fluorescent lighting and screw-in lamps 

are the largest energy-consuming technologies in the commercial sector, followed by ventilation 

and roof top AC units. 

Table 3-8 shows the natural gas market profile for the commercial sector as a whole. Boilers are 

the largest natural gas-consuming technology, followed by water heaters, and furnaces.

Market profiles for each building type are presented in Appendix A.
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Table 3-7 Commercial Sector Composite Electric Market Profile, 2010

EUI Intensity Usage

(kWh) (kWh/Sqft) (GWh)

Cooling Air-Cooled Chiller 4.5% 4.22 0.19 598

Cooling Water-Cooled Chiller 3.6% 4.57 0.17 520

Cooling Roof top AC 27.5% 3.83 1.06 3,295

Cooling Air-Source Heat Pump 5.0% 3.83 0.19 593

Cooling Geothermal Heat Pump 1.2% 2.56 0.03 99

Cooling Other Cooling 12.9% 3.10 0.40 1,247

Heating Air-Source Heat Pump 5.0% 4.88 0.24 755

Heating Geothermal Heat Pump 1.2% 3.25 0.04 126

Heating Electric Room Heat 0.6% 4.51 0.03 90

Heating Electric Furnace 5.8% 4.73 0.27 854

Ventilation Ventilation 100.0% 1.20 1.20 3,760

Water Heating Water Heating 36.2% 1.07 0.39 1,207

Interior Lighting Screw-in 100.0% 1.69 1.69 5,280

Interior Lighting High-Bay Fixtures 100.0% 0.60 0.60 1,868

Interior Lighting Linear Fluorescent 100.0% 1.85 1.85 5,767

Exterior Lighting Screw-in 100.0% 0.18 0.18 576

Exterior Lighting HID 100.0% 0.52 0.52 1,633

Exterior Lighting Linear Fluorescent 100.0% 0.05 0.05 149

Refrigeration Walk-in Refrigerator 48.5% 0.77 0.38 1,172

Refrigeration Reach-in Refrigerator 48.5% 0.08 0.04 127

Refrigeration Glass Door Display 48.5% 1.02 0.49 1,545

Refrigeration Open Display Case 48.5% 0.46 0.22 697

Refrigeration Icemaker 48.5% 0.17 0.08 263

Refrigeration Vending Machine 48.5% 0.17 0.08 263

Food Preparation Oven 28.5% 0.26 0.07 227

Food Preparation Fryer 28.5% 0.34 0.10 302

Food Preparation Dishwasher 28.5% 0.48 0.14 428

Food Preparation Hot Food Container 28.5% 0.12 0.03 108

Office Equipment Desktop Computer 100.0% 0.62 0.62 1,927

Office Equipment Laptop 100.0% 0.09 0.09 291

Office Equipment Server 100.0% 0.28 0.28 881

Office Equipment Monitor 100.0% 0.11 0.11 357

Office Equipment Printer/Copier/Fax 100.0% 0.08 0.08 261

Office Equipment POS Terminal 47.3% 0.04 0.02 65

Misc Non-HVAC Motors 53.9% 0.10 0.05 166

Misc Pool Pump 1.9% 0.01 0.00 0

Misc Pool Heater 0.5% 0.02 0.00 0

Misc Misc 100.0% 0.84 0.84 2,622

Total 12.85 40,123

Average Market Profiles - Electricity

End Use Technology Saturation
Market Characterization and Market Profiles

EnerNOC Utility Solutions Consulting 3-11

Table 3-8 Commercial Sector Composite Natural Gas Market Profile, 2010

EUI Intensity Usage

(therm) (thrm/Sqft) (MMthrm)

Heating Furnace 22.0% 0.34 0.07 231

Heating Boiler 28.6% 0.93 0.27 834

Heating Other Heating 15.7% 0.34 0.05 166

Water Heating Water Heating 46.1% 0.29 0.13 421

Food Preparation Oven 27.0% 0.03 0.01 22

Food Preparation Fryer 27.0% 0.04 0.01 33

Food Preparation Broiler 27.0% 0.04 0.01 33

Food Preparation Griddle 27.0% 0.04 0.01 33

Food Preparation Range 27.0% 0.04 0.01 33

Food Preparation Steamer 27.0% 0.04 0.01 33

Misc Pool Heater 0.6% 0.11 0.00 2

Misc Misc 5.9% 0.15 0.01 28

Total 0.60 1,867

Average Market Profiles - Natural Gas

End Use Technology Saturation

Figure 3-11 shows the distribution of electricity and natural gas energy consumption by end use 

for all commercial buildings. Electric usage is dominated by lighting, with interior and exterior 

varieties accounting for over one third of consumption. After lighting, the largest end uses are 

cooling, refrigeration, ventilation, and office equipment. The remaining end uses comprise 7% or 

less of total usage: miscellaneous, space heating, water heating, and food preparation. 

Natural gas usage is dominated by space heating (66%) and water heating (22%), with a small 

amount in food preparation and miscellaneous.

Figure 3-11 Commercial Electricity and Natural Gas Use by End Use (2010), All Buildings

Figure 3-12 and Table 3-9 present the electricity intensity in kWh per square foot by end use and 

building type. Figure 3-13 shows the same data as a percentage of total energy use for each 

segment.
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3-12 www.enernoc.com

Figure 3-12 Commercial Electricity Intensity by End Use and Segment (kWh/sq ft, 2010)

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0

Small Office

Large Office

Restaurant

Retail

Grocery

College

School

Health

Lodging

Warehouse

Miscellaneous

Intensity (kWh/sq. ft.)

Cooling

Heating

Ventilation

Water Heating

Interior Lighting

Exterior Lighting

Refrigeration

Food Preparation

Office Equipment

Miscellaneous

Table 3-9 Commercial Electricity Intensity by End Use and Segment (kWh/sq ft, 2010)

End Use Small Office Large Office Restaurant Retail Grocery College

Cooling 2.20 2.00 5.31 2.52 4.84 1.84

Heating 0.60 0.64 0.66 0.84 0.97 0.77

Ventilation 0.81 1.94 2.65 1.33 2.16 1.21

Water Heating 0.27 0.29 2.03 0.46 0.95 0.56

Interior Lighting 3.49 3.77 7.03 5.99 8.25 3.49

Exterior Lighting 0.91 0.49 2.30 0.79 1.22 0.68

Refrigeration 0.03 0.15 10.13 0.91 24.82 0.12

Food Preparation 0.18 0.20 5.67 0.32 1.04 0.14

Office Equipment 2.21 3.58 0.72 0.49 0.38 1.02

Misc 0.94 0.90 1.41 0.84 0.92 0.64

Total 11.63 13.98 37.92 14.48 45.55 10.48

End Use School Health Lodging Warehouse Misc. All Buildings

Cooling 0.65 5.32 2.14 0.48 1.16 2.04

Heating 0.17 1.23 0.88 0.28 0.20 0.58

Ventilation 0.57 3.23 1.08 0.32 0.56 1.20

Water Heating 0.19 0.30 0.74 0.13 0.40 0.39

Interior Lighting 2.92 4.86 3.97 3.25 3.07 4.14

Exterior Lighting 0.48 0.46 0.57 0.73 1.02 0.76

Refrigeration 0.32 0.60 0.54 0.48 0.19 1.30

Food Preparation 0.17 0.96 0.24 0.01 0.09 0.34

Office Equipment 0.46 0.86 0.13 0.94 0.37 1.21

Misc 0.24 2.83 0.88 0.62 0.79 0.89

Total 6.18 20.63 11.16 7.24 7.83 12.85
Market Characterization and Market Profiles

EnerNOC Utility Solutions Consulting 3-13

Figure 3-13 Breakdown of Commercial Electricity Consumption by End Use and Segment (2010)

Figure 3-14 and Table 3-10 present the natural gas intensity in therms per square foot by end 

use and building type. Figure 3-15 shows the same data as a percentage of total energy use for 

each segment.

Figure 3-14 Commercial Natural Gas Intensity by End Use and Segment (therms/sq ft, 2010)

0.0 0.5 1.0 1.5 2.0 2.5

Small Office

Large Office

Restaurant

Retail

Grocery

College

School

Health

Lodging

Warehouse

Miscellaneous

Intensity (therm/sq. ft.)

Heating

Water Heating

Food Preparation

Miscellaneous
Market Characterization and Market Profiles

3-14 www.enernoc.com

Table 3-10 Commercial Natural Gas Intensity by End Use and Segment (therms/sq ft, 2010)

End Use Small 

Office

Large 

Office Restaurant Retail Grocery College

Heating 0.425 0.262 0.378 0.439 0.422 0.367

Water Heating 0.081 0.067 0.506 0.086 0.143 0.134

Food Preparation 0.002 0.019 1.082 0.046 0.059 0.013

Misc 0.004 0.002 0.008 0.006 0.001 0.010

Total 0.511 0.351 1.973 0.576 0.625 0.524

End Use School Health Lodging Warehouse Misc. All 

Buildings

Heating 0.295 0.727 0.218 0.259 0.537 0.394

Water Heating 0.108 0.542 0.352 0.019 0.149 0.135

Food Preparation 0.055 0.244 0.065 0.001 0.033 0.059

Misc 0.001 0.012 0.008 0.001 0.046 0.010

Total 0.458 1.524 0.643 0.281 0.765 0.598

Figure 3-15 Breakdown of Commercial Natural Gas Use by End Use and Segment (2010)
Market Characterization and Market Profiles

EnerNOC Utility Solutions Consulting 3-15

Industrial Sector

The total electric energy consumed by industrial customers in New Jersey in 2010 was 8,429 

GWh19 and the total natural gas energy consumed was 497 million therms. 20 To allocate this 

energy usage to the various industries, we used energy per employee data from our internal 

Energy Market Profiles for the Mid-Atlantic region in combination with employee data from the 

Bureau of Labor Statistics. The resulting allocations are shown in Table 3-11 and referred to 

throughout the study as the control totals to which all energy usage is calibrated in the base year 

of the study.

Table 3-11 Industrial Market Segmentation by Industry Type, Base Year 2010

Segment Employees Electricity 2010 

Use (GWh)

Natural Gas 2010 

Use (million 

therms)

Chemical and Pharmaceutical 88,800 2,830 180

Paper 11,500 1,166 76

Food 30,000 783 68

Miscellaneous 126,900 3,651 173

Total 257,200 8,429 497

Figure 3-16 shows the size of each of the segments as a percentage of industrial sector energy 

sales.

Figure 3-16 Industrial Market Segmentation – Percentage of Energy Use

As with the residential and commercial sectors, the industrial market profiles characterize 

electricity use in terms of end use and technology for the base year 2010. Table 3-12 and Table 

3-13 show the composite market profiles for the industrial sector. 

 

19 U.S. DOE Energy Information Administration, See Table 2, http://www.eia.gov/electricity/sales_revenue_price/

20 U.S. DOE Energy Information Administration, http://205.254.135.7/dnav/ng/ng_cons_sum_dcu_nus_a.htm
Market Characterization and Market Profiles

3-16 www.enernoc.com

Table 3-12 Industrial Sector Composite Electric Market Profile, 2010

EUI Intensity Usage

(kWh) (kWh/Employee) (GWh)

Cooling Air-Cooled Chiller 2.5% 16,285 407 105

Cooling Water-Cooled Chiller 2.5% 15,806 395 102

Cooling Roof top AC 5.6% 15,747 879 226

Cooling Air Source Heat Pump 1.2% 14,235 164 42

Cooling Geothermal Heat Pump 0.3% 9,495 27 7

Cooling Other Cooling 3.1% 12,065 369 95

Heating Air Source Heat Pump 1.2% 37,385 431 111

Heating Geothermal Heat Pump 0.3% 24,936 72 18

Heating Electric Room Heat 0.2% 44,627 77 20

Heating Electric Furnace 1.6% 46,859 730 188

Ventilation Ventilation 100.0% 1,505 1,505 387

Interior Lighting Screw-in 100.0% 569 569 146

Interior Lighting High-Bay Fixtures 100.0% 2,222 2,222 572

Interior Lighting Linear Fluorescent 100.0% 506 506 130

Exterior Lighting Screw-in 100.0% 0 0 0

Exterior Lighting HID 100.0% 309 309 79

Exterior Lighting Linear Fluorescent 100.0% 1 1 0

Motors Pumps 100.0% 3,396 3,396 873

Motors Fans & Blowers 100.0% 2,060 2,060 530

Motors Compressed Air 100.0% 2,646 2,646 681

Motors Matl Handling 100.0% 1,511 1,511 389

Motors Matl Processing 100.0% 4,434 4,434 1,140

Motors Other Motors 100.0% 642 642 165

Process Process Heating 100.0% 3,912 3,912 1,006

Process Process Cooling and Refrigeration 100.0% 2,660 2,660 684

Process Electro-Chemical Processes 100.0% 1,231 1,231 317

Process Other Process 100.0% 280 280 72

Miscellaneous Miscellaneous 100.0% 1,335 1,335 343

Total 32,772 8,429

Average Market Profiles - Electricity

End Use Technology Saturation

Table 3-13 Industrial Sector Composite Natural Gas Market Profile, 2010

EUI Intensity Usage

(kWh) (kWh/Employee) (GWh)

Heating Furnace 24.0% 814 195 50

Heating Boiler 5.5% 1,463 80 21

Heating Other Heating 18.4% 814 150 39

Process Process Heating 100.0% 465 465 120

Process Process Boiler 100.0% 890 890 229

Process Process Cooling 100.0% 5 5 1

Process Other Process 100.0% 35 35 9

Miscellaneous Miscellaneous 100.0% 111 111 29

Total 1,931 497

Average Market Profiles - Natural Gas

End Use Technology Saturation

Figure 3-17 shows the distribution of electricity and natural gas energy consumption by end use 

for all industrial customers. Motors are clearly the largest overall end use for the industrial 

sector, accounting for 45% of energy use. Note that this end use includes a wide range of 

industrial equipment, such as air compressors and refrigeration compressors, pumps, conveyor 

motors, and fans. The process end use accounts for 25% of energy use, which includes heating, 
Market Characterization and Market Profiles

EnerNOC Utility Solutions Consulting 3-17

cooling, refrigeration, and electro-chemical processes. Lighting is the next highest, followed by

cooling, space heating, ventilation, and miscellaneous. 

Natural gas usage is dominated by process usage at 72%, most particularly process heating. 

Space heating (22%) and miscellaneous (6%) comprise the remainder of the sector’s energy 

usage. 

Figure 3-17 Industrial Electricity and Natural Gas Use by End Use (2010), All Industries

Figure 3-18 and Table 3-14 present the electric consumption by end-use and industry type. 

Figure 3-19 shows the same data as a percentage of total energy use for each segment.

Figure 3-18 Industrial Electricity Use by End Use and Segment (GWh, 2010)
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3-18 www.enernoc.com

Table 3-14 Industrial Electricity Use by End Use and Segment (GWh, 2010)

End Use Chemical & 

Pharmaceutical Paper Food Misc. All Industries Combined

Cooling 90 26 32 429 577

Heating 53 15 19 250 337

Interior Lighting 124 53 59 613 848

Exterior Lighting 12 5 6 58 80

Motors 1,559 839 316 1,063 3,778

Process 845 182 294 758 2,079

Misc. 88 27 36 192 343

Totals 2,830 1,166 783 3,651 8,429

Figure 3-19 Breakdown of Industrial Electricity Use by End Use and Segment (2010)

Figure 3-20 and Table 3-15 present the natural gas consumption by end-use and industry type. 

Figure 3-21 shows the same data as a percentage of total energy use.
Market Characterization and Market Profiles

EnerNOC Utility Solutions Consulting 3-19

Figure 3-20 Industrial Natural Gas Use by End Use and Segment (million therms, 2010)

Table 3-15 Industrial Natural Gas Use by End Use and Segment (million therms, 2010)

End Use Chemical & 

Pharmaceutical Paper Food Misc. All Industries Combined

Heating 4.6 2.8 3.5 98.5 109.4

Process 167.7 65.5 61.2 64.2 358.6

Misc. 8.1 7.1 3.2 10.2 28.6

Totals 180.3 75.5 67.9 172.8 496.6

Figure 3-21 Breakdown of Industrial Natural Gas Use by End Use and Segment (2010)

EnerNOC Utility Solutions Consulting 4-1

CHAPTER 4

BASELINE FORECAST

Prior to developing estimates of energy-efficiency potential, a baseline end-use forecast was 

developed to quantify what the consumption is likely to be in the future in absence of new 

efficiency programs and naturally occurring efficiency. The baseline forecast serves as the metric 

against which energy efficiency potentials are measured. This chapter presents the baseline 

forecast for electricity and gas for each sector.

Residential Sector 

The baseline forecast incorporates assumptions about economic growth, electricity prices, and 

appliance/equipment standards and building codes that are already mandated as described in 

Chapter 2. 

Table 4-1 and Figure 4-1 present the baseline forecast for electricity at the end-use level for the 

residential sector as a whole. Overall, residential use decreases slightly from 30,307 GWh in 2010 

to 29,502 GWh in 2016, a decrease of 2.7%, or an average reduction of 0.4% per year. This 

reflects the impact of the EISA lighting standard, additional appliance standards adopted in 2011, 

and modest customer growth. Figure 4-2 presents the forecast of use per household. Most 

noticeable is that lighting use decreases significantly throughout the time period as the lighting 

efficiency standards from EISA come into effect.

Table 4-1 Residential Electricity Consumption by End Use (GWh)

End Use 2010 2013 2014 2015 2016 %Change

Avg. 

Growth 

Rate

Cooling 6,215 6,210 6,250 6,300 6,372 3% 0.4%

Heating 1,316 1,364 1,385 1,407 1,432 9% 1.4%

Water Heating 1,217 1,198 1,202 1,204 1,207 -1% -0.1%

Interior Lighting 5,970 6,245 5,576 5,183 4,923 -18% -3.2%

Exterior Lighting 875 800 675 603 555 -37% -7.6%

Appliances 7,123 6,350 6,158 5,996 5,872 -18% -3.2%

Electronics 4,160 4,539 4,688 4,837 5,016 21% 3.1%

Miscellaneous 3,431 3,737 3,859 3,986 4,126 20% 3.1%

Total 30,307 30,442 29,793 29,515 29,502 -2.7% -0.4%
Baseline Forecast

4-2 www.enernoc.com

Figure 4-1 Residential Electricity Baseline Forecast by End Use

-

5,000 

10,000 

15,000 

20,000 

25,000 

30,000 

35,000 

2010 2013 2014 2015 2016

Annual Use (GWh)

Cooling

Heating

Water Heating

Interior Lighting

Exterior Lighting

Appliances

Electronics

Miscellaneous

Figure 4-2 Residential Baseline Electricity Use per Household by End Use

-

1,000 

2,000 

3,000 

4,000 

5,000 

6,000 

7,000 

8,000 

9,000 

10,000 

2010 2013 2014 2015 2016

Annual Use per Household (kWh)

Table 4-2 shows the end-use forecast at the technology level. Specific observations include:

1. The primary reason for the reduction in the baseline forecast beginning in 2012 is the federal 

lighting standards. The standard phases general service incandescent lamps out of the 

market over a three-year period, causing a decline in interior screw-in lighting use by 37.6% 

over the forecast period. 
Baseline Forecast

EnerNOC Utility Solutions Consulting 4-3

2. Appliance energy use decreases markedly, reflecting efficiency gains from standards.

3. Growth in use in electronics is substantial and reflects an increase in the saturation of 

electronics and the trend toward higher-powered computers. 

4. Growth in miscellaneous use is also substantial. This use includes various plug loads not 

elsewhere classified (e.g., hair dryers, power tools, coffee makers, etc.). This end use has 

grown consistently in the past and we incorporate future growth assumptions that are 

consistent with the Annual Energy Outlook. 

Table 4-2 Residential Electricity Baseline Forecast by End Use and Technology (GWh)

End Use Technology 2010 2013 2014 2015 2016 % 

Change

Avg. 

Growth 

Rate

Cooling

Central AC 4,764 4,765 4,804 4,851 4,916 3.2% 0.5%

Room AC 1,407 1,400 1,401 1,404 1,409 0.2% 0.0%

Air-Source Heat Pump 44 45 45 46 46 4.3% 0.7%

Geothermal Heat Pump - - - - - 0.0% 0.0%

Heating

Electric Room Heat 739 768 781 793 808 9.3% 1.5%

Electric Furnace 447 465 472 480 488 9.1% 1.5%

Air-Source Heat Pump 130 131 133 134 136 4.6% 0.7%

Geothermal Heat Pump - - - - - 0.0% 0.0%

Water Heating

Water Heater <=55 gal 1,142 1,123 1,128 1,131 1,136 -0.5% -0.1%

Water Heater > 55 gal 75 74 75 73 71 -5.8% -1.0%

Interior 

Lighting

Screw-in 3,627 3,525 2,878 2,509 2,265 -37.6% -7.9%

Linear Fluorescent 453 475 484 493 503 10.8% 1.7%

Specialty 1,889 2,245 2,214 2,181 2,156 14.1% 2.2%

Ext. Lighting Screw-in 875 800 675 603 555 -36.5% -7.6%

Appliances

Clothes Washer 296 250 240 228 218 -26.3% -5.1%

Clothes Dryer 940 835 816 800 789 -16.1% -2.9%

Dishwasher 986 854 829 807 790 -19.9% -3.7%

Refrigerator 2,688 2,372 2,273 2,189 2,119 -21.2% -4.0%

Freezer 443 389 374 362 354 -20.2% -3.8%

Second Refrigerator 966 826 792 766 747 -22.7% -4.3%

Stove 366 380 385 391 397 8.3% 1.3%

Microwave 436 445 449 453 458 5.1% 0.8%

Electronics

Personal Computers 733 803 826 843 870 18.7% 2.9%

Monitor 146 156 161 166 172 17.9% 2.7%

Laptops 283 309 315 324 334 18.1% 2.8%

TVs 1,585 1,715 1,768 1,822 1,882 18.7% 2.9%

Printer/Fax/Copier 157 154 154 154 153 -2.5% -0.4%

Set-top Boxes/DVR 904 1,012 1,059 1,106 1,164 28.8% 4.2%

Devices and Gadgets 352 390 406 422 440 25.1% 3.7%

Miscellaneous

Pool Pump 591 616 627 638 651 10.1% 1.6%

Pool Heater 103 103 104 105 106 3.3% 0.5%

Hot Tub / Spa 137 143 145 148 151 10.1% 1.6%

Well Pump 202 211 215 218 222 10.1% 1.6%

Furnace Fan 739 771 784 798 813 10.0% 1.6%

Miscellaneous 1,660 1,893 1,984 2,079 2,183 31.5% 4.6%

Total 30,307 30,369 29,731 29,459 29,448 -2.8% -0.5%
Baseline Forecast

4-4 www.enernoc.com

Table 4-3 and Figure 4-3 present the residential sector baseline forecast for natural gas at the 

end use level. Natural gas use increases from 2,255 million therms in 2010 to 2,352 million 

therms in 2016, an overall increase of 4.3% and an average growth of 0.7% per year. Figure 4-4

shows that natural gas usage grows slightly, reflecting lower fuel prices.

Table 4-3 Residential Natural Gas Consumption by End Use (million therms)

End Use 2010 2013 2014 2015 2016 % 

Change

Avg. 

Growth 

Rate

Heating 1,546 1,592 1,607 1,619 1,634 6% 0.9%

Water Heating 435 429 430 429 429 -1% -0.2%

Appliances 185 179 178 178 178 -4% -0.7%

Miscellaneous 89 99 103 107 111 25% 3.8%

Total 2,255 2,300 2,319 2,333 2,352 4.3% 0.7%

Figure 4-3 Residential Natural Gas Baseline Forecast by End Use

-

500 

1,000 

1,500 

2,000 

2,500 

2010 2013 2014 2015 2016

Annual Use (mmTherm)

Heating

Water Heating

Appliances

Miscellaneous
Baseline Forecast

EnerNOC Utility Solutions Consulting 4-5

Figure 4-4 Residential Baseline Natural Gas Use per Household by End Use

-

100 

200 

300 

400 

500 

600 

700 

2010 2013 2014 2015 2016

Annual Use per Household (therm)

Heating

Water Heating

Appliances

Miscellaneous

Table 4-4 shows the end use forecast for natural gas at the technology level. Gas water heating 

has a high saturation relative to other areas around the country, but grows only modestly over 

the forecast period.

Table 4-4 Residential Natural Gas Baseline Forecast by End Use and Technology (million 

therms)

End Use Technology 2010 2013 2014 2015 2016 % 

Change

Avg. 

Growth 

Rate

Heating Furnace 859 880 886 891 897 4.5% 0.7%

Boiler 673 696 705 712 721 7.1% 1.1%

Other Heating 15 16 16 16 17 11.5% 1.8%

Water Heating Water Heater <=55 gal 401 396 397 397 397 -1.1% -0.2%

Water Heater > 55 gal 33 33 33 32 32 -4.2% -0.7%

Appliances Clothes Dryer 50 40 38 37 35 -28.7% -5.6%

Stove 136 138 140 141 142 5.0% 0.8%

Miscellaneous Pool Heater 26 28 28 29 29 12.3% 1.9%

Hot Tub / Spa 10 10 10 11 11 12.3% 1.9%

Miscellaneous 53 62 65 68 71 34.1% 4.9%

Total 2,255 2,300 2,319 2,333 2,352 4.3% 0.7%

Commercial Sector

Electricity use in the commercial sector shows a decline of 11% overall during the forecast 

horizon, an average of 1.9% per year. Usage starts at 40,123 GWh in 2010, and decreases to 

35,797 GWh in 2016. Table 4-5 and Figure 4-5 present the electricity baseline forecast at the 

end-use level for the commercial sector as a whole. Usage is generally declining due to a 

sluggish economic recovery and the phasing in of codes and standards. The EISA 2007 lighting 

standards and EPACT 2005 refrigeration standards are also showing significant effects.
Baseline Forecast

4-6 www.enernoc.com

Table 4-5 Commercial Electricity Consumption by End Use (GWh)

End Use 2010 2013 2014 2015 2016 % 

Change

Avg. 

Growth 

Rate

Cooling 6,353 6,212 6,185 6,088 6,082 -4% -0.7%

Heating 1,826 1,798 1,800 1,786 1,798 -2% -0.3%

Ventilation 3,760 3,665 3,634 3,506 3,463 -8% -1.4%

Water Heating 1,207 1,179 1,178 1,170 1,185 -2% -0.3%

Interior Lighting 12,915 11,719 10,981 10,190 9,948 -23% -4.3%

Exterior Lighting 2,359 2,243 2,181 2,064 2,020 -14% -2.6%

Refrigeration 4,067 3,847 3,666 3,346 3,178 -22% -4.1%

Food Preparation 1,066 1,049 1,054 1,043 1,063 0% -0.1%

Office Equipment 3,782 3,728 3,736 3,672 3,749 -1% -0.1%

Miscellaneous 2,788 2,842 2,939 3,099 3,310 19% 2.9%

Total 40,123 38,281 37,354 35,964 35,797 -11% -1.9%

Figure 4-5 Commercial Electricity Baseline Forecast by End Use

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

2010 2013 2014 2015 2016

Annual Use (1,000 MWh)

Cooling

Heating

Ventilation

Water Heating

Interior Lighting

Exterior Lighting

Refrigeration

Food Preparation

Office Equipment

Miscellaneous

Table 4-6 presents the commercial sector electricity forecast by technology. Interior screw-in 

lighting and refrigeration decrease significantly over the forecast period as a result of efficiency 

standards.
Baseline Forecast

EnerNOC Utility Solutions Consulting 4-7

Table 4-6 Commercial Baseline Electricity Forecast by End Use and Technology (GWh)

End Use Technology 2010 2013 2014 2015 2016 % 

Change

Avg. 

Growth 

Rate

Cooling

Air-Cooled Chiller 598 588 589 585 592 -1.1% -0.2%

Water-Cooled Chiller 520 512 513 511 517 -0.6% -0.1%

Roof top AC 3,295 3,204 3,173 3,099 3,068 -6.9% -1.2%

Air-Source Heat Pump 593 578 573 563 559 -5.8% -1.0%

Geothermal Heat Pump 99 98 99 99 101 2.3% 0.4%

Other Cooling 1,247 1,232 1,237 1,231 1,245 -0.1% 0.0%

Heating

Air-Source Heat Pump 755 740 738 731 731 -3.2% -0.5%

Geothermal Heat Pump 126 123 124 123 124 -1.1% -0.2%

Electric Room Heat 90 89 90 89 90 -0.2% 0.0%

Electric Furnace 854 845 848 843 853 -0.2% 0.0%

Ventilation Ventilation 3,760 3,665 3,634 3,506 3,463 -7.9% -1.4%

Water Heating Water Heater 1,207 1,179 1,178 1,170 1,185 -1.9% -0.3%

Interior 

Lighting

Screw-in 5,280 4,366 3,769 3,263 3,063 -42.0% -9.1%

High-Bay Fixtures 1,868 1,660 1,504 1,270 1,189 -36.4% -7.5%

Linear Fluorescent 5,767 5,693 5,708 5,656 5,697 -1.2% -0.2%

Exterior 

Lighting

Screw-in 576 545 533 507 480 -16.8% -3.1%

HID 1,633 1,547 1,494 1,397 1,364 -16.5% -3.0%

Linear Fluorescent 149 151 155 161 176 18.1% 2.8%

Refrigeration

Walk-in Refrigerator 1,172 1,037 938 787 699 -40.4% -8.6%

Reach-in Refrigerator 127 114 105 91 83 -34.3% -7.0%

Glass Door Display 1,545 1,509 1,444 1,329 1,265 -18.1% -3.3%

Open Display Case 697 689 690 677 681 -2.4% -0.4%

Icemaker 263 247 245 244 249 -5.0% -0.9%

Vending Machine 263 251 244 218 200 -23.8% -4.5%

Food 

Preparation

Oven 227 228 233 240 253 11.4% 1.8%

Fryer 302 303 309 318 333 10.2% 1.6%

Dishwasher 428 416 412 396 393 -8.3% -1.4%

Hot Food Container 108 103 99 90 84 -22.6% -4.3%

Office 

Equipment

Desktop Computer 1,927 1,919 1,927 1,888 1,911 -0.8% -0.1%

Laptop 291 292 296 295 304 4.8% 0.8%

Server 881 858 858 844 876 -0.6% -0.1%

Monitor 357 348 348 347 358 0.2% 0.0%

Printer/Copier/Fax 261 252 250 243 244 -6.6% -1.1%

POS Terminal 65 59 57 55 56 -12.7% -2.3%

Miscellaneous

Non-HVAC Motors 166 163 163 161 164 -1.2% -0.2%

Pool Pump 0 0 0 0 1 2.5% 0.4%

Pool Heater 0 0 0 0 0 2.1% 0.4%

Miscellaneous 2,622 2,679 2,776 2,937 3,145 20.0% 3.0%

Total 40,123 38,281 37,354 35,964 35,797 -10.8% -1.9%

Table 4-7 and Figure 4-6 show the baseline forecast for natural gas, which is expected to decline 

by 6% between 2010 and 2016. The sluggish economy and more efficient equipment in new

construction and normal equipment replacement cycles account for this decline.
Baseline Forecast

4-8 www.enernoc.com

Table 4-7 Commercial Natural Gas Consumption by End Use (million therms)

End Use 2010 2013 2014 2015 2016 % 

Change

Avg. 

Growth 

Rate

Heating 1,230.7 1,171 1,155 1,150 1,153 -6% -1.1%

Water Heating 421 386 383 382 385 -9% -1.5%

Food Preparation 185 184 184 185 187 1% 0.1%

Miscellaneous 30 31 31 31 31 4% 0.6%

Total 1,867 1,771 1,753 1,748 1,756 -6% -1.0%

Figure 4-6 Commercial Natural Gas Baseline Forecast by End Use

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

2010 2013 2014 2015 2016

Annual Use (mmTherm)

Heating

Water Heating

Food Preparation

Miscellaneous

Table 4-8 shows the commercial baseline gas forecast at the technology level. 

Table 4-8 Commercial Baseline Electricity Forecast by End Use and Technology (GWh)

End Use Technology 2010 2013 2014 2015 2016 % 

Change

Avg. 

Growth 

Rate

Heating

Furnace 231 229 228 227 229 -1.1% -0.2%

Boiler 834 814 798 769 766 -8.1% -1.4%

Other Heating 166 163 162 159 158 -4.4% -0.8%

Water Heating Water Heater 421 401 391 383 385 -8.6% -1.5%

Food Preparation

Oven 22 22 22 22 23 1.0% 0.2%

Fryer 33 32 32 32 33 1.1% 0.2%

Broiler 33 32 33 33 33 2.6% 0.4%

Griddle 33 32 32 33 33 2.0% 0.3%

Range 33 32 32 33 33 2.5% 0.4%

Steamer 33 32 32 31 31 -4.8% -0.8%

Miscellaneous

Pool Heater 2 2 2 2 2 0.2% 0.0%

Miscellaneous 28 28 28 28 29 3.9% 0.6%

Total 1,867 1,821 1,794 1,753 1,756 -6.0% -1.0%
Baseline Forecast

EnerNOC Utility Solutions Consulting 4-9

Industrial Sector

Table 4-9 and Figure 4-7 present the electricity baseline forecast at the end-use level for the 

industrial sector as a whole. Overall, industrial annual electricity use decreases from 8,429 GWh 

in 2010 to 7,732 GWh in 2016, an overall decrease of 8%, or 1.4% per year. This is largely 

driven by the economy and sluggish projections for recovery.

Table 4-9 Industrial Electricity Consumption by End Use (GWh)

End Use 2010 2013 2014 2015 2016 % 

Change

Avg. 

Growth 

Rate

Cooling 577 565 561 566 551 -4% -0.7%

Heating 337 340 340 345 338 0% 0.1%

Ventilation 387 372 365 364 352 -9% -1.6%

Interior Lighting 848 595 559 549 530 -38% -7.8%

Exterior Lighting 80 61 58 58 56 -30% -5.8%

Motors 3,778 3,536 3,588 3,626 3,531 -7% -1.1%

Process 2,079 1,978 1,999 2,026 1,967 -5% -0.9%

Miscellaneous 343 377 387 402 407 18% 2.8%

Total 8,429 7,822 7,858 7,937 7,732 -8% -1.4%

Figure 4-7 Industrial Electricity Baseline Forecast by End Use

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

2010 2013 2014 2015 2016

Annual Use (1,000 MWh)

Cooling

Heating

Ventilation

Interior Lighting

Exterior Lighting

Motors

Process

Miscellaneous

Table 4-10 and Figure 4-8 show a similar story for the industrial natural gas baseline forecast.

The overall decrease from 2010 to 2016 is 3%, with an average decline of 0.5% per year. 
Baseline Forecast

4-10 www.enernoc.com

Table 4-10 Industrial Natural Gas Consumption by End Use (million therms)

End Use 2010 2013 2014 2015 2016 % 

Change

Avg. 

Growth 

Rate

Heating 109,437 111,708 110,834 112,106 108,831 -1% -0.1%

Process 358,634 348,987 347,894 346,215 343,679 -4% -0.7%

Miscellaneous 28,576 28,391 28,437 28,615 28,388 -1% -0.1%

Total 496,647 489,086 487,165 486,936 480,898 -3% -0.5%

Figure 4-8 Industrial Natural Gas Baseline Forecast by End Use

0

100,000

200,000

300,000

400,000

500,000

600,000

2010 2013 2014 2015 2016

Annual Use (1,000 therm)

Heating

Process

Miscellaneous

Baseline Forecast Summary

Table 4-11 and Figure 4-9 provide a summary of the baseline forecast for electricity by sector for 

the State of New Jersey. Overall, the forecast shows a slight to moderate decline in electricity 

use, due to a challenging macroeconomic environment and codes and standards.

Table 4-11 Electricity Baseline Forecast Summary (GWh)

Sector 2010 2013 2014 2015 2016 % Change

Avg. 

Growth 

Rate

Residential 30,307 30,442 29,793 29,515 29,502 -2.7% -0.4%

Commercial 40,123 36,511 35,964 35,699 35,797 -10.8% -1.9%

Industrial 8,429 7,822 7,858 7,937 7,732 -8.3% -1.4%

Total 78,859 74,776 73,615 73,151 73,031 -7.4% -1.3%
Baseline Forecast

EnerNOC Utility Solutions Consulting 4-11

Figure 4-9 Electricity Baseline Forecast Summary (GWh)

-

10,000 

20,000 

30,000 

40,000 

50,000 

60,000 

70,000 

80,000 

90,000 

2010 2011 2012 2013 2014 2015 2016

Annual Use (GWh)

Residential

Commercial

Industrial

Table 4-12 and Figure 4-10 provide a summary of the natural gas baseline forecast by sector for 

New Jersey. Overall, the forecast is increasing slightly across all sectors. 

Table 4-12 Natural Gas Baseline Forecast Summary (million therms)

Sector 2010 2013 2014 2015 2016 % Change

Avg. 

Growth 

Rate

Residential 2,255 2,300 2,319 2,333 2,352 4.3% 0.7%

Commercial 1,867 1,771 1,753 1,748 1,756 -6.0% -1.0%

Industrial 497 489 487 487 481 -3.2% -0.5%

Total 4,619 4,560 4,559 4,568 4,589 -0.7% -0.1%

Figure 4-10 Natural Gas Baseline Forecast Summary (million therms)

-

500 

1,000 

1,500 

2,000 

2,500 

3,000 

3,500 

4,000 

4,500 

5,000 

2010 2011 2012 2013 2014 2015 2016

Annual Use (mmTherm)

Residential

Commercial

Industrial

EnerNOC Utility Solutions Consulting 5-1

CHAPTER 5

ENERGY EFFICIENCY MEASURES

List of Energy Efficiency Measures

The first step of the energy efficiency measure analysis is to identify the list of all relevant 

energy efficiency measures that should be considered for the New Jersey potential assessment. 

For this study, EnerNOC prepared a preliminary list of measures for BPU and CEEEP staff to 

review. After incorporating feedback, we populated the full databases for the three sectors. 

Sources for the measure assumptions were drawn from past New Jersey program experience, 

EnerNOC’s building simulation tool (BEST), EnerNOC’s measure database (DEEM), DEER, NWPCC 

workbooks, other secondary sources, and other data from EnerNOC’s previous studies and 

program work.

 Residential Measures. The residential measures span all end uses and vary significantly in 

the manner in which they impact energy consumption. Table 5-1shows the residential 

equipment measure options and the segments for which they were modeled. Table 5-2

shows the residential non-equipment measure options. All residential measures considered 

for this study are described in Appendix B.

 Commercial Measures. Table 5-3 and Table 5-4 present a summary of the commercial 

equipment and non-equipment measures, respectively. The measures shown were modeled 

for nearly all of the commercial building types, both new and existing, with only a few 

exceptions. For instance, hotel guestroom controls were only modeled for the lodging sector. 

All commercial measures considered for this study are described in Appendix C.

 Industrial Measures. Table 5-5 and Table 5-6 present a summary of the industrial 

equipment and non-equipment measures, respectively. All industrial measures considered for 

this study are described in Appendix D.
Energy Efficiency Measures

5-2 www.enernoc.com

Table 5-1 Summary of Residential Equipment Measures

End Use Fuel Technology Efficiency Option

Cooling Electric Central AC SEER 13

Cooling Electric Central AC SEER 14 (Energy Star)

Cooling Electric Central AC SEER 15 (CEE Tier 2)

Cooling Electric Central AC SEER 16 (CEE Tier 3)

Cooling Electric Central AC Ductless Minisplit

Cooling Electric Central AC SEER 21

Cooling Electric Room AC EER 9.8

Cooling Electric Room AC EER 10.8 (Energy Star)

Cooling Electric Room AC EER 11.0

Cooling Electric Room AC EER 11.5

Cooling Electric Room AC EER 12.0

Cooling/Heating Electric Air-Source Heat Pump SEER 13

Cooling/Heating Electric Air-Source Heat Pump SEER 14 (Energy Star)

Cooling/Heating Electric Air-Source Heat Pump SEER 15 (CEE Tier 2)

Cooling/Heating Electric Air-Source Heat Pump SEER 16 (CEE Tier 3)

Cooling/Heating Electric Air-Source Heat Pump Ductless Minisplit

Cooling/Heating Electric Geothermal Heat Pump EER 14.1, COP 3.3

Cooling/Heating Electric Geothermal Heat Pump EER 16, COP 3.5

Cooling/Heating Electric Geothermal Heat Pump EER 18, COP 3.8

Cooling/Heating Electric Geothermal Heat Pump EER 30, COP 5.0

Heating Electric Electric Room Heat Standard

Heating Electric Electric Furnace Standard

Water Heating Electric Water Heater <=55 gal EF 0.9

Water Heating Electric Water Heater <=55 gal EF 0.95

Water Heating Electric Water Heater <=55 gal EF 2.3 (HP)

Water Heating Electric Water Heater > 55 gal EF 0.9

Water Heating Electric Water Heater > 55 gal EF 0.95

Water Heating Electric Water Heater > 55 gal EF 2.3 (HP)

Interior Lighting Electric Screw-in Incandescent 

Interior Lighting Electric Screw-in Infrared Halogen

Interior Lighting Electric Screw-in Infrared Halogen (2020)

Interior Lighting Electric Screw-in CFL

Interior Lighting Electric Screw-in LED

Interior Lighting Electric Screw-in LED (2020)

Interior Lighting Electric Linear Fluorescent T12

Interior Lighting Electric Linear Fluorescent T8

Interior Lighting Electric Linear Fluorescent Super T8

Interior Lighting Electric Linear Fluorescent T5

Interior Lighting Electric Linear Fluorescent LED

Interior Lighting Electric Specialty Incandescent 

Interior Lighting Electric Specialty Infrared Halogen

Interior Lighting Electric Specialty Infrared Halogen (2020)

Interior Lighting Electric Specialty CFL

Interior Lighting Electric Specialty LED

Interior Lighting Electric Specialty LED (2020)

Exterior Lighting Electric Screw-in Incandescent 

Exterior Lighting Electric Screw-in Infrared Halogen

Exterior Lighting Electric Screw-in Infrared Halogen (2020)

Exterior Lighting Electric Screw-in CFL

Exterior Lighting Electric Screw-in LED

Exterior Lighting Electric Screw-in LED (2020)

Appliances Electric Clothes Washer Standard (1.26)

Appliances Electric Clothes Washer Energy Star (1.72)

Appliances Electric Clothes Washer AHAM (MEF 1.72)

Appliances Electric Clothes Washer Energy Star (MEF 2.0)
Energy Efficiency Measures

EnerNOC Utility Solutions Consulting 5-3

Table 5-1 Summary of Residential Equipment Measures (cont.)

End Use Fuel Technology Efficiency Option

Appliances Electric Clothes Washer AHAM (MEF 2.0)

Appliances Electric Clothes Washer Compact (MEF 2.79)

Appliances Electric Clothes Dryer Baseline

Appliances Electric Clothes Dryer High Efficiency

Appliances Electric Clothes Dryer Baseline (2015+)

Appliances Electric Clothes Dryer High Efficiency (2015+)

Appliances Electric Clothes Dryer HP (EF 4.52)

Appliances Electric Dishwasher Standard (EF 0.63)

Appliances Electric Dishwasher Energy Star (EF 0.69)

Appliances Electric Dishwasher Energy Star (EF 0.73)

Appliances Electric Dishwasher AHAM (EF 0.73)

Appliances Electric Dishwasher Ultra Efficient (EF 1.1)

Appliances Electric Refrigerator Standard

Appliances Electric Refrigerator Energy Star

Appliances Electric Refrigerator High Efficiency

Appliances Electric Refrigerator AHAM (2014)

Appliances Electric Refrigerator High Efficiency (2014)

Appliances Electric Freezer Standard

Appliances Electric Freezer Energy Star

Appliances Electric Freezer High Efficiency

Appliances Electric Freezer AHAM (2014)

Appliances Electric Freezer High Efficiency (2014)

Appliances Electric Second Refrigerator Standard

Appliances Electric Second Refrigerator Energy Star

Appliances Electric Second Refrigerator High Efficiency

Appliances Electric Second Refrigerator AHAM (2014)

Appliances Electric Second Refrigerator High Efficiency (2014)

Appliances Electric Stove Baseline

Appliances Electric Stove Convection

Appliances Electric Stove Halogen Burner

Appliances Electric Stove Induction

Appliances Electric Microwave Standard

Electronics Electric Personal Computers Standard

Electronics Electric Personal Computers Energy Star

Electronics Electric Monitor Standard

Electronics Electric Monitor Energy Star

Electronics Electric Laptops Standard

Electronics Electric Laptops Energy Star

Electronics Electric TVs Standard

Electronics Electric TVs Energy Star (3.1)

Electronics Electric TVs Energy Star (4.1)

Electronics Electric TVs Energy Star (5.1)

Electronics Electric Printer/Fax/Copier Standard

Electronics Electric Printer/Fax/Copier Energy Star

Electronics Electric Set-top Boxes/DVR Standard

Electronics Electric Set-top Boxes/DVR Energy Star (2009)

Electronics Electric Set-top Boxes/DVR Energy Star (2011)

Electronics Electric Devices and Gadgets Standard

Miscellaneous Electric Pool Pump Standard

Miscellaneous Electric Pool Pump High Efficiency

Miscellaneous Electric Pool Pump Two-Speed

Miscellaneous Electric Pool Heater Electric Resistance

Miscellaneous Electric Pool Heater Heat Pump (COP = 5.0)

Miscellaneous Electric Hot Tub / Spa Standard

Miscellaneous Electric Hot Tub / Spa Efficient Pumps
Energy Efficiency Measures

5-4 www.enernoc.com

Table 5-1 Summary of Residential Equipment Measures (cont.)

End Use Fuel Technology Efficiency Option

Miscellaneous Electric Hot Tub / Spa Improved Controls and Pumps

Miscellaneous Electric Well Pump Baseline (40% EF)

Miscellaneous Electric Well Pump High Efficiency (60% EF)

Miscellaneous Electric Furnace Fan Standard

Miscellaneous Electric Furnace Fan ECM

Miscellaneous Electric Miscellaneous Standard

Heating Natural Gas Furnace AFUE 80%

Heating Natural Gas Furnace AFUE 83%

Heating Natural Gas Furnace AFUE 90%

Heating Natural Gas Furnace AFUE 96%

Heating Natural Gas Boiler EF 0.81

Heating Natural Gas Boiler EF 0.82

Heating Natural Gas Boiler EF 0.85

Heating Natural Gas Boiler EF 0.95

Heating Natural Gas Other Heating Gas Fireplace

Water Heating Natural Gas Water Heater <=55 gal EF 0.59

Water Heating Natural Gas Water Heater <=55 gal EF 0.63

Water Heating Natural Gas Water Heater <=55 gal EF 0.74

Water Heating Natural Gas Water Heater <=55 gal EF 0.76

Water Heating Natural Gas Water Heater <=55 gal EF 0.86 (Condensing)

Water Heating Natural Gas Water Heater > 55 gal EF 0.59

Water Heating Natural Gas Water Heater > 55 gal EF 0.63

Water Heating Natural Gas Water Heater > 55 gal EF 0.74

Water Heating Natural Gas Water Heater > 55 gal EF 0.76

Water Heating Natural Gas Water Heater > 55 gal EF 0.86 (Condensing)

Appliances Natural Gas Clothes Dryer Standard

Appliances Natural Gas Clothes Dryer Standard (AHAM)

Appliances Natural Gas Clothes Dryer Efficient

Appliances Natural Gas Stove Standard (EF .399)

Appliances Natural Gas Stove Efficient (EF .42)

Miscellaneous Natural Gas Pool Heater EF .78

Miscellaneous Natural Gas Pool Heater EF .82

Miscellaneous Natural Gas Pool Heater EF .90

Miscellaneous Natural Gas Pool Heater EF .95

Miscellaneous Natural Gas Hot Tub / Spa EF .78

Miscellaneous Natural Gas Hot Tub / Spa EF .82

Miscellaneous Natural Gas Hot Tub / Spa EF .90

Miscellaneous Natural Gas Hot Tub / Spa EF .95

Miscellaneous Natural Gas Miscellaneous Standard

Heating Fuel Oil Furnace AFUE 81%

Heating Fuel Oil Furnace AFUE 83%

Heating Fuel Oil Furnace AFUE 85%

Heating Fuel Oil Furnace AFUE 95%

Heating Fuel Oil Boiler EF 0.81

Heating Fuel Oil Boiler EF 0.84

Heating Fuel Oil Boiler EF 0.85

Heating Fuel Oil Boiler EF 0.95

Water Heating Fuel Oil Water Heater <=55 gal EF 0.55

Water Heating Fuel Oil Water Heater <=55 gal EF 0.62

Water Heating Fuel Oil Water Heater <=55 gal EF 0.64

Water Heating Fuel Oil Water Heater <=55 gal EF 0.68

Water Heating Fuel Oil Water Heater > 55 gal EF 0.55

Water Heating Fuel Oil Water Heater > 55 gal EF 0.62

Water Heating Fuel Oil Water Heater > 55 gal EF 0.64

Water Heating Fuel Oil Water Heater > 55 gal EF 0.68
Energy Efficiency Measures

EnerNOC Utility Solutions Consulting 5-5

Table 5-2 Summary of Residential Non-Equipment Measures

Measure Existing New

Insulation - Ceiling X X

Insulation - Ducting X X

Insulation - Foundation X

Insulation - Infiltration Control X X

Insulation - Radiant Barrier X X

Insulation - Wall Cavity X X

Insulation - Wall Sheathing X X

Ducting - Repair and Sealing X X

Windows - High Efficiency/ENERGY STAR X X

Windows - Install Reflective Film X X

Doors - Storm and Thermal X X

Roofs - High Reflectivity X X

Attic Fan - Installation X X

Attic Fan - Photovoltaic - Installation X X

Whole-House Fan - Installation X X

Ceiling Fan - Installation X X

Thermostat - Clock/Programmable X X

Home Energy Management System X X

Central AC - Early Replacement X X

Central AC - Maintenance and Tune-Up X X

Central Heat Pump - Maintenance X X

Room AC - Removal of Second Unit X X

Boiler - Hot Water Reset X X

Boiler - Pipe Insulation X X

Boiler - Maintenance X X

Furnace - Maintenance X X

Water Heater - Drainwater Heat Recovery X X

Water Heater - Faucet Aerators X X

Water Heater - Low-Flow Showerheads X X

Water Heater - Pipe Insulation X X

Water Heater - Timer X X

Water Heater - Desuperheater X X

Water Heater - Solar System X X

Water Heater - Tank Blanket/Insulation X X

Interior Lighting - Occupancy Sensors X X

Exterior Lighting - Photosensor Control X X

Exterior Lighting - Photovoltaic Installation X X

Exterior Lighting - Timeclock Installation X X

Refrigerator - Early Replacement X X

Refrigerator - Maintenance X X

Refrigerator - Remove Second Unit X X

Freezer - Remove Second Unit X X

Freezer - Early Replacement X X

Freezer - Maintenance X X

Electronics - Smart Power Strips X X

Pool Pump - Timer X X

Pool Heater - Solar System X X

ENERGY STAR Home Design X

Behavioral Feedback Tools X X
Energy Efficiency Measures

5-6 www.enernoc.com

Table 5-3 Summary of Commercial Equipment Measures

End Use Fuel Technology Label

Cooling Electric Air-Cooled Chiller 1.5 kw/ton, COP 2.3

Cooling Electric Air-Cooled Chiller 1.3 kw/ton, COP 2.7

Cooling Electric Air-Cooled Chiller 1.26 kw/ton, COP 2.8

Cooling Electric Air-Cooled Chiller 1.0 kw/ton, COP 3.5

Cooling Electric Air-Cooled Chiller 0.97 kw/ton, COP 3.6

Cooling Electric Water-Cooled Chiller 0.75 kw/ton, COP 4.7

Cooling Electric Water-Cooled Chiller 0.60 kw/ton, COP 5.9

Cooling Electric Water-Cooled Chiller 0.58 kw/ton, COP 6.1

Cooling Electric Water-Cooled Chiller 0.55 kw/Ton, COP 6.4

Cooling Electric Water-Cooled Chiller 0.51 kw/ton, COP 6.9

Cooling Electric Water-Cooled Chiller 0.50 kw/Ton, COP 7.0

Cooling Electric Water-Cooled Chiller 0.48 kw/ton, COP 7.3

Cooling Electric Roof top AC EER 9.2

Cooling Electric Roof top AC EER 10.1

Cooling Electric Roof top AC EER 11.2

Cooling Electric Roof top AC EER 12.0

Cooling Electric Roof top AC Ductless Minisplit

Cooling Electric Air-Source Heat Pump EER 9.3

Cooling Electric Air-Source Heat Pump EER 10.3

Cooling Electric Air-Source Heat Pump EER 11.0

Cooling Electric Air-Source Heat Pump EER 11.7

Cooling Electric Air-Source Heat Pump EER 12.0

Cooling Electric Air-Source Heat Pump Ductless Minisplit

Cooling Electric Geothermal Heat Pump EER 14.1

Cooling Electric Geothermal Heat Pump EER 16

Cooling Electric Geothermal Heat Pump EER 18

Cooling Electric Geothermal Heat Pump EER 30

Cooling Electric Other Cooling EER 9.8

Cooling Electric Other Cooling EER 10.2

Cooling Electric Other Cooling EER 10.8

Cooling Electric Other Cooling EER 11

Cooling Electric Other Cooling EER 11.5

Heating Electric Air-Source Heat Pump EER 9.3

Heating Electric Air-Source Heat Pump EER 10.3

Heating Electric Air-Source Heat Pump EER 11.0

Heating Electric Air-Source Heat Pump EER 11.7

Heating Electric Air-Source Heat Pump EER 12.0

Heating Electric Air-Source Heat Pump Ductless Minisplit

Heating Electric Geothermal Heat Pump EER 14.1

Heating Electric Geothermal Heat Pump EER 16

Heating Electric Geothermal Heat Pump EER 18

Heating Electric Geothermal Heat Pump EER 30

Heating Electric Electric Room Heat Standard

Heating Electric Electric Furnace Standard

Ventilation Electric Ventilation Constant Volume
Energy Efficiency Measures

EnerNOC Utility Solutions Consulting 5-7

Table 5-3 Summary of Commercial Equipment Measures (continued)

End Use Fuel Technology Label

Ventilation Electric Ventilation Variable Air Volume

Water Heating Electric Water Heater EF .97

Water Heating Electric Water Heater EF .98

Water Heating Electric Water Heater EF 2.0

Water Heating Electric Water Heater EF 2.3

Water Heating Electric Water Heater EF 2.4

Interior Lighting Electric Screw-in Incandescent

Interior Lighting Electric Screw-in 90W Halogen PAR-38

Interior Lighting Electric Screw-in 70W HIR PAR-38

Interior Lighting Electric Screw-in CFL

Interior Lighting Electric Screw-in LED (2010)

Interior Lighting Electric Screw-in LED (2020)

Interior Lighting Electric High-Bay Fixtures Metal Halides

Interior Lighting Electric High-Bay Fixtures LED (2010)

Interior Lighting Electric High-Bay Fixtures T8

Interior Lighting Electric High-Bay Fixtures High Pressure Sodium

Interior Lighting Electric High-Bay Fixtures T5

Interior Lighting Electric High-Bay Fixtures Light Emitting Plasma

Interior Lighting Electric High-Bay Fixtures LED (2020)

Interior Lighting Electric Linear Fluorescent T12

Interior Lighting Electric Linear Fluorescent LED (2010)

Interior Lighting Electric Linear Fluorescent T8

Interior Lighting Electric Linear Fluorescent Super T8

Interior Lighting Electric Linear Fluorescent T5

Interior Lighting Electric Linear Fluorescent LED (2020)

Exterior Lighting Electric Screw-in Incandescent

Exterior Lighting Electric Screw-in 90W Halogen PAR-38

Exterior Lighting Electric Screw-in 70W HIR PAR-38

Exterior Lighting Electric Screw-in CFL

Exterior Lighting Electric Screw-in LED (2010)

Exterior Lighting Electric Screw-in LED (2020)

Exterior Lighting Electric HID Metal Halides

Exterior Lighting Electric HID LED (2010)

Exterior Lighting Electric HID T8

Exterior Lighting Electric HID High Pressure Sodium

Exterior Lighting Electric HID T5

Exterior Lighting Electric HID Light Emitting Plasma

Exterior Lighting Electric HID LED (2020)

Exterior Lighting Electric Linear Fluorescent T12

Exterior Lighting Electric Linear Fluorescent LED (2010)

Exterior Lighting Electric Linear Fluorescent T8

Exterior Lighting Electric Linear Fluorescent Super T8

Exterior Lighting Electric Linear Fluorescent T5

Exterior Lighting Electric Linear Fluorescent LED (2020)

Refrigeration Electric Walk-in Refrigerator 14600 kWh/yr
Energy Efficiency Measures

5-8 www.enernoc.com

Table 5-3 Summary of Commercial Equipment Measures (continued)

End Use Fuel Technology Label

Refrigeration Electric Walk-in Refrigerator 10800 kWh/yr

Refrigeration Electric Walk-in Refrigerator 10000 kWh/yr

Refrigeration Electric Walk-in Refrigerator 9000 kWh/yr

Refrigeration Electric Reach-in Refrigerator 3800 kWh/yr

Refrigeration Electric Reach-in Refrigerator 3100 kWh/yr

Refrigeration Electric Reach-in Refrigerator 2500 kWh/yr

Refrigeration Electric Reach-in Refrigerator 2400 kWh/yr

Refrigeration Electric Reach-in Refrigerator 1500 kWh/yr

Refrigeration Electric Glass Door Display 14480 kWh/yr

Refrigeration Electric Glass Door Display 11700 kWh/yr

Refrigeration Electric Glass Door Display 8400 kWh/yr

Refrigeration Electric Glass Door Display 6800 kWh/yr

Refrigeration Electric Open Display Case 6500 kWh/yr

Refrigeration Electric Open Display Case 5350 kWh/yr

Refrigeration Electric Open Display Case 5300 kWh/yr

Refrigeration Electric Open Display Case 4330 kWh/yr

Refrigeration Electric Icemaker 7.0 kWh/100 lbs

Refrigeration Electric Icemaker 6.3 kWh/100 lbs

Refrigeration Electric Icemaker 6.0 kWh/100 lbs

Refrigeration Electric Icemaker 5.5 kWh/100 lbs

Refrigeration Electric Vending Machine 3400 kWh/year

Refrigeration Electric Vending Machine 3000 kWh/year

Refrigeration Electric Vending Machine 2400 kWh/year

Refrigeration Electric Vending Machine 1700 kWh/year

Food Preparation Electric Oven Standard

Food Preparation Electric Oven Energy Star

Food Preparation Electric Fryer Standard

Food Preparation Electric Fryer Energy Star

Food Preparation Electric Dishwasher Standard

Food Preparation Electric Dishwasher Energy Star

Food Preparation Electric Hot Food Container Standard

Food Preparation Electric Hot Food Container Energy Star

Office Equipment Electric Desktop Computer Standard

Office Equipment Electric Desktop Computer Energy Star

Office Equipment Electric Laptop Standard

Office Equipment Electric Laptop Energy Star

Office Equipment Electric Server Standard

Office Equipment Electric Server Energy Star

Office Equipment Electric Monitor Standard

Office Equipment Electric Monitor Energy Star

Office Equipment Electric Printer/Copier/Fax Standard

Office Equipment Electric Printer/Copier/Fax Energy Star

Office Equipment Electric POS Terminal Standard

Office Equipment Electric POS Terminal Energy Star

Miscellaneous Electric Non-HVAC Motors Standard (EPAct)
Energy Efficiency Measures

EnerNOC Utility Solutions Consulting 5-9

Table 5-3 Summary of Commercial Equipment Measures (continued)

End Use Fuel Technology Label

Miscellaneous Electric Non-HVAC Motors Standard (EPAct 2015)

Miscellaneous Electric Non-HVAC Motors High Efficiency

Miscellaneous Electric Non-HVAC Motors High Efficiency (2015)

Miscellaneous Electric Non-HVAC Motors Premium (NEMA)

Miscellaneous Electric Non-HVAC Motors Premium (NEMA 2015)

Miscellaneous Electric Pool Pump Standard

Miscellaneous Electric Pool Pump High Efficiency

Miscellaneous Electric Pool Pump High Efficiency, Multi-Speed

Miscellaneous Electric Pool Heater Standard

Miscellaneous Electric Pool Heater Heat Pump

Miscellaneous Electric Miscellaneous Standard

Heating Natural Gas Furnace EF .76

Heating Natural Gas Furnace EF .80

Heating Natural Gas Furnace EF .83

Heating Natural Gas Furnace EF .90

Heating Natural Gas Boiler EF .76

Heating Natural Gas Boiler EF .80

Heating Natural Gas Boiler EF .82

Heating Natural Gas Boiler EF .85

Heating Natural Gas Boiler EF .96

Heating Natural Gas Other Heating AFUE .74

Heating Natural Gas Other Heating AFUE .75

Heating Natural Gas Other Heating AFUE .76

Heating Natural Gas Other Heating AFUE .77

Heating Natural Gas Other Heating AFUE .80

Water Heating Natural Gas Water Heater EF 0.77

Water Heating Natural Gas Water Heater EF 0.80

Water Heating Natural Gas Water Heater EF 0.94

Food Preparation Natural Gas Oven Standard

Food Preparation Natural Gas Oven Energy Star

Food Preparation Natural Gas Fryer Standard

Food Preparation Natural Gas Fryer Energy Star

Food Preparation Natural Gas Broiler Standard

Food Preparation Natural Gas Griddle Standard

Food Preparation Natural Gas Griddle Energy Star

Food Preparation Natural Gas Range Standard

Food Preparation Natural Gas Range High Efficiency

Food Preparation Natural Gas Steamer Standard

Food Preparation Natural Gas Steamer Energy Star

Miscellaneous Natural Gas Pool Heater EF .78

Miscellaneous Natural Gas Pool Heater EF .82

Miscellaneous Natural Gas Pool Heater EF .90

Miscellaneous Natural Gas Pool Heater EF .95

Miscellaneous Natural Gas Miscellaneous Standard
Energy Efficiency Measures

5-10 www.enernoc.com

Table 5-4 Summary of Commercial Non-Equipment Measures

Measure Existing New

Insulation - Ceiling X X

Insulation - Ducting X X

Insulation - Radiant Barrier X X

Insulation - Wall Cavity X X

HVAC - Duct Repair and Sealing X X

Doors - High Efficiency X X

Windows - High Efficiency X X

Windows - Install Reflective Film X X

Roof - High Reflectivity X X

Air-Cooled Chiller - Condenser Water Temperature Reset X X

Air-Cooled Chiller - Economizer X X

Air-Cooled Chiller - Thermal Energy Storage X X

Air-Cooled Chiller - VSD on Fans X X

Air-Cooled Chiller - Chilled Water Reset X X

Air-Cooled Chiller - Chilled Water Variable-Flow System X X

Air-Cooled Chiller - High Efficiency Cooling Tower Fans X X

Air-Cooled Chiller - Maintenance X X

Air-Cooled Chiller - Chiller Heat Recovery X X

Water-Cooled Chiller - Condenser Water Temperature Reset X X

Water-Cooled Chiller - Economizer X X

Water-Cooled Chiller - Thermal Energy Storage X X

Water-Cooled Chiller - VSD on Fans X X

Water-Cooled Chiller - Chilled Water Reset X X

Water-Cooled Chiller - Chilled Water Variable-Flow System X X

Water-Cooled Chiller - High Efficiency Cooling Tower Fans X X

Water-Cooled Chiller - Maintenance X X

Water-Cooled Chiller - Chiller Heat Recovery X X

RTU - Evaporative Precooler X X

RTU - Maintenance X X

Gas Boiler - High Efficiency Hot Water Circulation X X

Gas Boiler - Hot Water Reset X X

Gas Boiler - Combustion Controls (O2 Trim) X X

Gas Boiler - Condensate Return Lines X X

Gas Boiler - Condensing Economizer X X

Gas Boiler - Pipe Insulation X X

Gas Boiler - Steam Trap Maintenance X X

Gas Boiler - Maintenance X X

Gas Furnace - Maintenance X X

Space Heating - Heat Recovery Ventilator X X

Heat Pump - Maintenance X X

Ventilation - ECM on VAV Boxes X X

Ventilation - Variable Speed Control X X

Water Heater - Drainwater Heat Recovery X X

Water Heater - Faucet Aerators/Low Flow Nozzles X X

Water Heater - High Efficiency Circulation Pump X X

Water Heater - Desuperheater X X

Water Heater - Solar System X X

Water Heater - Install Timer X X

Water Heater - Pipe Insulation X X

Water Heater - Tank Blanket/Insulation X X

Water Heating - Booster Water Heater X X
Energy Efficiency Measures

EnerNOC Utility Solutions Consulting 5-11

Table 5-4 Summary of Commercial Non-Equipment Measures (continued)

Measure Existing New

Interior Lighting - Daylighting Controls X X

Interior Lighting - LED Exit Lighting X X

Interior Lighting - Occupancy Sensors X X

Interior Lighting - Timeclocks and Timers X X

Interior Lighting - Task Lighting X X

Interior Fluorescent - Bi-Level Fixture X X

Interior Fluorescent - Delamp and Install Reflectors X X

Exterior Lighting - Bi-Level Fixture X X

Exterior Lighting - Daylighting Controls X X

Exterior Lighting - Photovoltaic Installation X X

Refrigerator - Anti-Sweat Heater X X

Refrigerator - Decommissioning X X

Refrigerator - Demand Defrost X X

Refrigerator - Door Gasket Replacement X X

Refrigerator - Evaporator Fan Controls X X

Refrigerator - Floating Head Pressure X X

Refrigerator - Strip Curtain X X

Refrigerator - High Efficiency Compressor X X

Refrigerator - Variable Speed Compressor X X

Refrigerator - eCube X X

Vending Machine - Controller X X

Office Equipment - ENERGY STAR Power Supplies X X

Office Equipment - Plug Load Occupancy Sensors X X

Pool Heater - Solar X X

Pool Pump - Timer X X

Destratification Fans (HVLS) X X

Ventilation - CO2 Controlled X X

Non-HVAC Motors - Variable Speed Control X X

Energy Management System X X

Thermostat - Clock/Programmable X X

HVAC - Occupancy Sensors X X

Retrocommissioning - HVAC X

Retrocommissioning - Lighting X

Custom Measures X X

Commissioning - HVAC X

Commissioning - Lighting X

Advanced New Construction Designs X X

Data Center - Server Virtualization X X

Grocery - Display Case - LED Lighting X X

Grocery - Display Case Motion Sensors X X

Grocery - ECMs for Display Cases X X

Grocery - Open Display Case - Night Covers X X

Lodging - Guest Room Controls X X
Energy Efficiency Measures

5-12 www.enernoc.com

Table 5-5 Summary of Industrial Equipment Measures

End Use Fuel Technology Label

Cooling Electric Air-Cooled Chiller 1.5 kw/ton, COP 2.3

Cooling Electric Air-Cooled Chiller 1.3 kw/ton, COP 2.7

Cooling Electric Air-Cooled Chiller 1.26 kw/ton, COP 2.8

Cooling Electric Air-Cooled Chiller 1.0 kw/ton, COP 3.5

Cooling Electric Air-Cooled Chiller 0.97 kw/ton, COP 3.6

Cooling Electric Water-Cooled Chiller 0.75 kw/ton, COP 4.7

Cooling Electric Water-Cooled Chiller 0.60 kw/ton, COP 5.9

Cooling Electric Water-Cooled Chiller 0.58 kw/ton, COP 6.1

Cooling Electric Water-Cooled Chiller 0.55 kw/Ton, COP 6.4

Cooling Electric Water-Cooled Chiller 0.51 kw/ton, COP 6.9

Cooling Electric Water-Cooled Chiller 0.50 kw/Ton, COP 7.0

Cooling Electric Water-Cooled Chiller 0.48 kw/ton, COP 7.3

Cooling Electric Roof top AC EER 9.2

Cooling Electric Roof top AC EER 10.1

Cooling Electric Roof top AC EER 11.2

Cooling Electric Roof top AC EER 12.0

Cooling Electric Roof top AC Ductless Minisplit

Cooling Electric Air-Source Heat Pump EER 9.3

Cooling Electric Air-Source Heat Pump EER 10.3

Cooling Electric Air-Source Heat Pump EER 11.0

Cooling Electric Air-Source Heat Pump EER 11.7

Cooling Electric Air-Source Heat Pump EER 12.0

Cooling Electric Air-Source Heat Pump Ductless Minisplit

Cooling Electric Geothermal Heat Pump EER 14.1

Cooling Electric Geothermal Heat Pump EER 16

Cooling Electric Geothermal Heat Pump EER 18

Cooling Electric Geothermal Heat Pump EER 30

Cooling Electric Other Cooling EER 9.8

Cooling Electric Other Cooling EER 10.2

Cooling Electric Other Cooling EER 10.8

Cooling Electric Other Cooling EER 11

Cooling Electric Other Cooling EER 11.5

Heating Electric Air-Source Heat Pump EER 9.3

Heating Electric Air-Source Heat Pump EER 10.3

Heating Electric Air-Source Heat Pump EER 11.0

Heating Electric Air-Source Heat Pump EER 11.7

Heating Electric Air-Source Heat Pump EER 12.0

Heating Electric Air-Source Heat Pump Ductless Minisplit

Heating Electric Geothermal Heat Pump EER 14.1

Heating Electric Geothermal Heat Pump EER 16

Heating Electric Geothermal Heat Pump EER 18

Heating Electric Geothermal Heat Pump EER 30

Heating Electric Electric Room Heat Standard

Heating Electric Electric Furnace Standard

Ventilation Electric Ventilation Constant Volume

Ventilation Electric Ventilation Variable Air Volume

Interior Lighting Electric Screw-in Incandescent

Interior Lighting Electric Screw-in 90W Halogen PAR-38

Interior Lighting Electric Screw-in 70W HIR PAR-38

Interior Lighting Electric Screw-in CFL
Energy Efficiency Measures

EnerNOC Utility Solutions Consulting 5-13

Table 5-5 Summary of Industrial Equipment Measures (continued)

End Use Fuel Technology Label

Interior Lighting Electric Screw-in LED (2010)

Interior Lighting Electric Screw-in LED (2020)

Interior Lighting Electric High-Bay Fixtures Metal Halides

Interior Lighting Electric High-Bay Fixtures LED (2010)

Interior Lighting Electric High-Bay Fixtures T8

Interior Lighting Electric High-Bay Fixtures High Pressure Sodium

Interior Lighting Electric High-Bay Fixtures Induction

Interior Lighting Electric High-Bay Fixtures Light Emitting Plasma

Interior Lighting Electric High-Bay Fixtures T5

Interior Lighting Electric High-Bay Fixtures LED (2020)

Interior Lighting Electric Linear Fluorescent T12

Interior Lighting Electric Linear Fluorescent LED (2010)

Interior Lighting Electric Linear Fluorescent T8

Interior Lighting Electric Linear Fluorescent Super T8

Interior Lighting Electric Linear Fluorescent T5

Interior Lighting Electric Linear Fluorescent LED (2020)

Exterior Lighting Electric Screw-in Incandescent

Exterior Lighting Electric Screw-in 90W Halogen PAR-38

Exterior Lighting Electric Screw-in 70W HIR PAR-38

Exterior Lighting Electric Screw-in CFL

Exterior Lighting Electric Screw-in LED (2010)

Exterior Lighting Electric Screw-in LED (2020)

Exterior Lighting Electric HID Metal Halides

Exterior Lighting Electric HID LED (2010)

Exterior Lighting Electric HID T8

Exterior Lighting Electric HID Light Emitting Plasma

Exterior Lighting Electric HID High Pressure Sodium

Exterior Lighting Electric HID T5

Exterior Lighting Electric HID LED (2020)

Exterior Lighting Electric Linear Fluorescent T12

Exterior Lighting Electric Linear Fluorescent LED (2010)

Exterior Lighting Electric Linear Fluorescent T8

Exterior Lighting Electric Linear Fluorescent Super T8

Exterior Lighting Electric Linear Fluorescent T5

Exterior Lighting Electric Linear Fluorescent LED (2020)

Motors Electric Pumps Standard

Motors Electric Pumps High Efficiency

Motors Electric Fans & Blowers Standard

Motors Electric Fans & Blowers High Efficiency

Motors Electric Compressed Air Standard

Motors Electric Compressed Air High Efficiency

Motors Electric Matl Handling Standard

Motors Electric Matl Handling High Efficiency

Motors Electric Matl Processing Standard

Motors Electric Matl Processing High Efficiency

Motors Electric Other Motors Standard

Motors Electric Other Motors High Efficiency

Process Electric Process Heating Standard

Process Electric Process Cooling and Refrig Standard

Process Electric Electro-Chemical Processes Standard
Energy Efficiency Measures

5-14 www.enernoc.com

Table 5-5 Summary of Industrial Equipment Measures (continued)

End Use Fuel Technology Label

Process Electric Other Process Standard

Miscellaneous Electric Miscellaneous Standard

Heating Natural Gas Furnace EF .76

Heating Natural Gas Furnace EF .80

Heating Natural Gas Furnace EF .83

Heating Natural Gas Furnace EF .90

Heating Natural Gas Boiler EF .76

Heating Natural Gas Boiler EF .80

Heating Natural Gas Boiler EF .82

Heating Natural Gas Boiler EF .85

Heating Natural Gas Boiler EF .96

Heating Natural Gas Other Heating AFUE .74

Heating Natural Gas Other Heating AFUE .75

Heating Natural Gas Other Heating AFUE .76

Heating Natural Gas Other Heating AFUE .77

Heating Natural Gas Other Heating AFUE .80

Process Natural Gas Process Heating Standard

Process Natural Gas Process Boiler EF .76

Process Natural Gas Process Boiler EF .80

Process Natural Gas Process Boiler EF .82

Process Natural Gas Process Boiler EF .85

Process Natural Gas Process Boiler EF .96

Process Natural Gas Process Cooling Standard

Process Natural Gas Other Process Standard

Miscellaneous Natural Gas Miscellaneous Standard
Energy Efficiency Measures

EnerNOC Utility Solutions Consulting 5-15

Table 5-6 Summary of Industrial Non-Equipment Measures

Measure Existing New

Insulation - Ceiling X X

Insulation - Ducting X X

Insulation - Wall Cavity X X

HVAC - Duct Repair and Sealing X X

Air-Cooled Chiller - Economizer X X

Air-Cooled Chiller - Efficient Mechanical Layout X X

Air-Cooled Chiller - Maintenance X X

Air-Cooled Chiller - Chilled Water Reset X X

Air-Cooled Chiller - Chilled Water Variable-Flow System X X

Air-Cooled Chiller - Condenser Water Temperature Reset X X

Air-Cooled Chiller - High Efficiency Cooling Tower Fans X X

Air-Cooled Chiller - VSD on Fans X X

Water-Cooled Chiller - Economizer X X

Water-Cooled Chiller - Efficient Mechanical Layout X X

Water-Cooled Chiller - Maintenance X X

Water-Cooled Chiller - Chilled Water Reset X X

Water-Cooled Chiller - Chilled Water Variable-Flow System X X

Water-Cooled Chiller - Condenser Water Temperature Reset X X

Water-Cooled Chiller - High Efficiency Cooling Tower Fans X X

Water-Cooled Chiller - VSD on Fans X X

RTU - Maintenance X X

Heat Pump - Maintenance X X

Roofs - High Reflectivity X X

Energy Management System X X

Thermostat - Clock/Programmable X X

Interior Lighting - Occupancy Sensors X X

Interior Lighting - Skylights X X

Interior Lighting - Time Clocks and Timers X X

Interior Lighting - LED Exit Lighting X X

Interior Lighting - Daylighting Controls X X

Interior Screw-in - Task Lighting X X

Interior Fluorescent - Bi-Level Fixture X X

Interior Fluorescent - Delamp and Install Reflectors X X

Exterior Lighting - Bi-Level Fixture X X

Exterior Lighting - Daylighting Controls X X

Exterior Lighting - Photovoltaic Installation X X

Process - Conductivity Controls X X

Process - Controls on Fume Hoods X X

Process - Timers and Controls X X

Refrigeration - Floating Head Pressure X X

Refrigeration - System Controls X X

Refrigeration - System Maintenance X X

Refrigeration - System Optimization X X

Compressed Air - Air Usage Reduction X X
Energy Efficiency Measures

5-16 www.enernoc.com

Table 5-6 Summary of Industrial Non-Equipment Measures (continued)

Measure Existing New

Compressed Air - Compressor Replacement X X

Compressed Air - System Controls X X

Compressed Air - System Maintenance X X

Compressed Air - System Optimization and Improvements X X

Pumping System - Controls X X

Pumping System - Maintenance X X

Pumping System - Optimization X X

Pumps - Variable Speed Control X X

Pump Equipment Upgrade X X

Fan Equipment Upgrade X X

Fan System - Controls X X

Fan System - Maintenance X X

Fan System - Optimization X X

Fans - Variable Speed Control X X

Motors - Magnetic Adjustable Speed Drives X X

Motors - Efficient Rewind X X

Motors - Synchronous Belts X X

Motors - Variable Frequency Drive X X

Retrocommissioning - HVAC X

Retrocommissioning - Lighting X

Destratification Fans (HVLS) X X

Ventilation - CO2 Controlled X X

Process Boiler - High Efficiency Hot Water Circulation X X

Process Boilers - Hot Water Reset X X

Process Boiler - Combustion Controls (O2 Trim) X X

Process Boiler - Condensate Return Lines X X

Process Boiler - Condensing Economizer X X

Process Boiler - Pipe Insulation X X

Process Boiler - Steam Trap Maintenance X X

Process Boiler - Maintenance X X

Gas Boiler - High Efficiency Hot Water Circulation X X

Gas Boiler - Hot Water Reset X X

Gas Boiler - Combustion Controls (O2 Trim) X X

Gas Boiler - Condensate Return Lines X X

Gas Boiler - Condensing Economizer X X

Gas Boiler - Pipe Insulation X X

Gas Boiler - Steam Trap Maintenance X X

Gas Boiler - Maintenance X X

Gas Furnace - Maintenance X X

Transformer - High Efficiency X X

Custom Measures X X

Commissioning - HVAC X

Commissioning - Lighting X
Energy Efficiency Measures

EnerNOC Utility Solutions Consulting 5-17

Results of the Economic Screen

Table 5-7 summarizes the number of equipment and non-equipment measures evaluated for 

each segment within each sector.

Table 5-7 Number of Measures Evaluated

Residential Commercial Industrial

Total Number 

of Measures

Equipment Measures Evaluated 165 179 125 469

Non-Equipment Measures Evaluated 49 94 87 229

Total Measures Evaluated 214 273 212 699

Appendix B gives results for the economic screening process by segment, vintage, end use and 

measure for the residential sector. Appendices C and D shows the equivalent information for the 

commercial and industrial sectors, respectively.

EnerNOC Utility Solutions Consulting 6-1

CHAPTER 6

OVERALL ENERGY EFFICIENCY POTENTIAL

This chapter presents the overall results of the energy-efficiency analysis for the State of New 

Jersey. Key findings related to potentials are summarized below.

 Achievable Low potential forms a lower point on the range of achievable potential. Across 

all sectors, this metric is 5,678 BTU in 2013 and increases to 29,925 BTU by 2016. This 

represents 0.4% of the baseline forecast in 2013 and 2.3% in 2016. 

 Achievable High potential forms the upper bound on the range of achievable potential. It 

is 11,799 BTU in 2013, which represents 0.9% of the baseline forecast. By 2016, the 

cumulative savings are 57,144 BTU, 4.4% of the baseline forecast, for an annual average of 

just over 1% per year. 

 Economic potential, which reflects the savings when all cost-effective measures are taken, 

is 45,966 BTU in 2013. This represents 3.5% of the baseline energy forecast. By 2016, 

economic potential reaches 127,588 BTU, 9.9% of the baseline energy forecast. 

 Technical potential, which reflects the adoption of all energy efficiency measures 

regardless of cost-effectiveness, is a theoretical upper bound on savings. In 2013, energy 

savings are 62,293 BTU, or 4.8% of the baseline energy forecast. By 2016, technical 

potential reaches 177,410 BTU, 13.7% of the baseline energy forecast. 

Table 6-1 and Figure 6-1 summarize the energy-efficiency savings for the different levels of 

potential relative to the baseline forecast. Figure 6-2 displays the energy-efficiency forecasts. To 

combine the electric and natural gas energy efficiency potentials, kWhs and therms are both 

converted to a common unit, BTUs, in order to facilitate comparison. Table 9-1 in the fuel 

switching analysis chapter shows the conversion factors.

Because of the fuel switching analysis, we observe some interesting trends in the data. The 

technical potential case causes significant migration toward the electric technologies of 

geothermal heat pumps and heat pump water heaters. Due to their high capital costs and low 

natural gas prices, however, the economic potential case saw significant migration in the 

opposite direction- from electric space and water heating to high efficiency natural gas units. 

When viewed from the limited perspective of the residential electric analysis, for instance, this 

caused the technical potential case to use more energy than the economic case. When viewed 

from the total BTU content, however, this makes perfect sense. Because the geothermal heat 

pump is the most efficient heating technology in all cases, many units were switched and were 

added for technical potential, so the electric load actually grew while the total system was 

becoming more efficient. Meanwhile, the natural gas load dropped off considerably because of a 

corresponding loss of units. In the economic scenario, however, the tables were turned. The 

most efficient economic unit is the natural gas furnace; so many electric units were switching to 

natural gas. The number of consumers that actually adopted these measures, due to their 

complexity and added switching costs, is so minimal that effects to the achievable potential cases 

are virtually negligible at this time. Chapter 9 contains more details on fuel switching.
Overall Energy Efficiency Potential

6-2 www.enernoc.com

Table 6-1 Summary of Combined Electric and Natural Gas Energy Efficiency Potential

2013 2014 2015 2016

Baseline Forecast (million BTU) 1,308,205 1,294,830 1,290,496 1,291,174

Cumulative Savings (million BTU)

Achievable Low Potential 5,678 14,223 22,181 29,925

Achievable High Potential 11,799 28,680 43,780 57,144

Economic Potential 45,966 82,457 110,745 127,588

Technical Potential 62,293 109,714 148,625 177,410

Energy Savings (% of Baseline)

Achievable Low Potential 0.4% 1.1% 1.7% 2.3%

Achievable High Potential 0.9% 2.2% 3.4% 4.4%

Economic Potential 3.5% 6.4% 8.6% 9.9%

Technical Potential 4.8% 8.5% 11.5% 13.7%

Figure 6-1 Summary of Combined Electric and Natural Gas Energy Savings

0%

2%

4%

6%

8%

10%

12%

14%

16%

2013 2014 2015 2016

Energy Savings (% of Baseline Forecast)

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential
Overall Energy Efficiency Potential

EnerNOC Utility Solutions Consulting 6-3

Figure 6-2 Combined Electric and Natural Gas Potential Forecasts (million BTU)

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

Energy Consumption (million BTU)

Baseline Forecast

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential

Electric Energy Efficiency – Overall Results 

Table 6-2 and Figure 6-3 summarize the electric energy-efficiency savings for the different levels 

of potential relative to the baseline forecast. Figure 6-4 displays the electric energy-efficiency 

forecasts.

Table 6-2 Summary of Electric Energy Efficiency Potential

2013 2014 2015 2016

Baseline Forecast (GWh) 74,776 73,615 73,151 73,031

Cumulative Savings (GWh)

Achievable Low Potential 446 1,125 1,718 2,255

Achievable High Potential 918 2,251 3,368 4,277

Economic Potential 3,418 6,255 8,316 9,369

Technical Potential 3,695 6,638 8,779 9,870

Energy Savings (% of Baseline)

Achievable Low Potential 0.6% 1.5% 2.3% 3.1%

Achievable High Potential 1.2% 3.1% 4.6% 5.9%

Economic Potential 4.6% 8.5% 11.4% 12.8%

Technical Potential 4.9% 9.0% 12.0% 13.5%
Overall Energy Efficiency Potential

6-4 www.enernoc.com

Figure 6-3 Summary of Electric Energy Savings

0%

2%

4%

6%

8%

10%

12%

14%

16%

2013 2014 2015 2016

Energy Savings (% of Baseline Forecast)

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential

Figure 6-4 Electric Potentials Forecasts (GWh)

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

Energy Consumption (1,000 MWh)

Baseline Forecast

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential
Overall Energy Efficiency Potential

EnerNOC Utility Solutions Consulting 6-5

Natural Gas Energy Efficiency – Overall Results 

Table 6-3 and Figure 6-5 summarize the natural gas energy-efficiency savings for the different 

levels of potential relative to the baseline forecast. Figure 6-6 displays the natural gas energyefficiency forecasts.

Table 6-3 Summary of Natural Gas Energy Efficiency Potential

2013 2014 2015 2016

Baseline Forecast (1,000 therms) 4,560,186 4,558,750 4,568,218 4,588,711

Cumulative Savings (1,000 therms)

Achievable Low Potential 5,906 14,004 26,066 42,208

Achievable High Potential 13,420 30,291 54,007 83,980

Economic Potential 70,161 111,704 159,709 208,193

Technical Potential 201,774 340,611 485,779 649,293

Energy Savings (% of Baseline)

Achievable Low Potential 0.1% 0.3% 0.6% 0.9%

Achievable High Potential 0.3% 0.7% 1.2% 1.8%

Economic Potential 1.5% 2.5% 3.5% 4.5%

Technical Potential 4.4% 7.5% 10.6% 14.1%

Figure 6-5 Summary of Natural Gas Energy Savings

0%

2%

4%

6%

8%

10%

12%

14%

16%

2013 2014 2015 2016

Energy Savings (% of Baseline Forecast)

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential
Overall Energy Efficiency Potential

6-6 www.enernoc.com

Figure 6-6 Natural Gas Potential Forecasts (1000 therms)

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

Energy Consumption (1,000 therms)

Baseline Forecast

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential

Overview of Energy Efficiency Potential by Sector and Fuel

Table 6-4, Figure 6-7, and Figure 6-8 summarize the range of electric achievable potential by 

sector. The commercial sector accounts for the largest portion of the savings, followed by 

residential. The industrial sector contributes a relatively small amount of potential.

Table 6-4 Electric Achievable Potential by Sector (GWh)

2013 2014 2015 2016

Achievable Low Savings (GWh)

Residential 173 493 751 926

Commercial 251 585 889 1,217

Industrial 22 47 78 113

Total 446 1,125 1,718 2,255

Achievable High Savings (GWh)

Residential 352 994 1,488 1,769

Commercial 519 1,164 1,729 2,296

Industrial 46 93 150 212

Total 918 2,251 3,368 4,277
Overall Energy Efficiency Potential

EnerNOC Utility Solutions Consulting 6-7

Figure 6-7 Achievable Low Electric Potential by Sector (GWh)

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

2013 2014 2015 2016

Achievable Low Savings (1,000 MWh)

Residential

Commercial

Industrial

Figure 6-8 Achievable High Electric Potential by Sector (GWh)

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

2013 2014 2015 2016

Achievable High Savings (1,000 MWh)

Residential

Commercial

Industrial
Overall Energy Efficiency Potential

6-8 www.enernoc.com

Table 6-5, Figure 6-9 and Figure 6-10 present the range of natural gas achievable potential by 

sector. Again, like the electric analysis, the commercial sector accounts for the largest portion of 

the savings, followed by the residential and then the industrial sectors. 

Table 6-5 Natural Gas Achievable Potential by Sector (million therms)

2013 2014 2015 2016

Achievable Low Savings (million therms)

Residential 0.6 2.3 4.8 6.9

Commercial 5.2 11.4 20.6 34.3

Industrial 0.1 0.3 0.6 1.0

Total 5.9 14.0 26.1 42.2

Achievable High Savings (million therms) 

Residential 1.1 4.6 9.3 12.8

Commercial 12.0 25.1 43.5 69.2

Industrial 0.3 0.7 1.3 2.0

Total 13.4 30.3 54.0 84.0

Figure 6-9 Achievable Low Natural Gas Potential by Sector (mmTherms)

0

10

20

30

40

50

60

70

80

90

2013 2014 2015 2016

Achievable Low Savings (million therms)

Residential

Commercial

Industrial
Overall Energy Efficiency Potential

EnerNOC Utility Solutions Consulting 6-9

Figure 6-10 Achievable High Natural Gas Potential by Sector (mmTherms)

0

10

20

30

40

50

60

70

80

90

2013 2014 2015 2016

Achievable High Savings (million therms)

Residential

Commercial

Industrial

Year by year savings for electric energy, electric peak demand, and natural gas energy are 

available in Appendix F. Details for each sector are presented in Chapter 7.

EnerNOC Utility Solutions Consulting 7-1

CHAPTER 7

ENERGY EFFICIENCY POTENTIAL BY SECTOR

This chapter presents the results of the energy efficiency analysis at the sector level. First, the 

residential potential is presented, followed by the commercial, and lastly, industrial. Within each 

sector, electric results are presented first and natural gas results second. 

Residential Electricity Potential 

Table 7-1 presents estimates for the four types of potential for the residential electricity sector. 

Figure 7-1 depicts these potential energy savings estimates graphically.

 Achievable Low potential projects 173 GWh of energy savings in 2013, 0.6% of the 

baseline forecast. This increases to 926 GWh, 3.1% of the baseline forecast, in 2016.

 Achievable High potential is 352 GWh in 2013, which represents 1.2% of the baseline 

forecast. By 2016, the cumulative energy savings are 1,769 GWh, 6.0% of the baseline 

forecast.

 Economic potential, which reflects a theoretical limit to savings when all cost-effective 

measures are taken, is 1,329 GWh in 2013. This represents 4.4% of the baseline energy 

forecast. By 2016, economic potential reaches 4,234 GWh, 14.4% of the baseline energy 

forecast.

 Technical potential, which reflects the adoption of all energy efficiency measures 

regardless of cost, is a theoretical upper bound on savings. In 2013, energy savings are 

1,271 GWh, or 4.2% of the baseline energy forecast. By 2016, technical potential reaches 

3,809 GWh, 12.9% of the baseline energy forecast. 

The reason that electric technical potential savings are less than economic potential savings has 

to do with the fuel switching analysis that was applied to the residential sector. As discussed in 

the previous section, certain electric technologies were the most technically efficient option, 

while their corresponding natural gas technologies were the most economically efficient option. 

This caused customers to switch en masse to electric units in the technical potential case, while 

customers switched en mass to natural gas units in the economic potential case. When 

considering electric and natural gas on a total energy basis, the technical potential uses less 

energy than the economic potential, as one would expect. This is explained in more detail in 

Chapter 9. It should be noted that the effects of the fuel switching units are minimal in the 

achievable potential cases, as the adoption rates are so low that they put the number of 

statewide transactions in the hundreds and low thousands. 
Energy Efficiency Potential By Sector

7-2 www.enernoc.com

Table 7-1 Electricity Energy Efficiency Potential for the Residential Sector

2013 2014 2015 2016

Baseline Forecast (GWh) 30,442 29,793 29,515 29,502

Energy Savings (GWh)

Achievable Low Potential 173 493 751 926

Achievable High Potential 352 994 1,488 1,769

Economic Potential 1,329 2,935 3,987 4,234

Technical Potential 1,271 2,831 3,759 3,809

Energy Savings (% of Baseline)

Achievable Low Potential 0.6% 1.7% 2.5% 3.1%

Achievable High Potential 1.2% 3.3% 5.0% 6.0%

Economic Potential 4.4% 9.9% 13.5% 14.4%

Technical Potential 4.2% 9.5% 12.7% 12.9%

Figure 7-1 Residential Electric Energy Efficiency Potential Savings

0 %

2 %

4 %

6 %

8 %

10%

12%

14%

16%

2013 2014 2015 2016

Energy Savings (% of Baseline Forecast)

Achievable Potential Low 

Achievable Potential High 

Economic Potential 

Technical Potential 

Residential Electric Potential by Market Segment

Single-family homes in New Jersey account for the majority of this sector’s total sales in the base 

year and throughout the forecast. Similarly, single-family homes account for the largest share of 

potential savings by segment, as displayed in Table 7-2, which shows results for 2016.

Table 7-3 shows the Achievable Low savings by end use and market segment in 2016. The 

segments are similar in terms of the distribution of savings opportunities by end use, but there 

are a few notable differences. Single-family homes have more exterior lighting and so have more 

savings potential for this end use. Similarly, single-family homes are more likely to have 

swimming pools and therefore have more potential for savings in pool pumps (captured in the 

miscellaneous end use). Multi-family homes have a relatively larger opportunity in home 

electronics and air conditioning compared to single-family homes, reflecting an older appliance 

stock. 
Energy Efficiency Potential By Sector

EnerNOC Utility Solutions Consulting 7-3

Table 7-2 Residential Electric Potential by Market Segment, 2016

Single 

Family

Single 

Family LI

Multi 

Family 

Rent

Multi 

Family 

Rent LI

Multi 

Family 

Own

Multi 

Family 

Own LI

Baseline Forecast (GWh) 17,555 4,391 3,665 2,351 1,355 185

Energy Savings (GWh)

Achievable Low Potential 531 159 119 76 36 6

Achievable High Potential 1,013 304 227 147 68 11

Economic Potential 2,395 678 601 375 170 17

Technical Potential 2,187 598 552 305 152 16

Energy Savings as % of Baseline

Achievable Low Potential 3.0% 3.6% 3.2% 3.3% 2.6% 3.0%

Achievable High Potential 5.8% 6.9% 6.2% 6.2% 5.0% 5.7%

Economic Potential 13.6% 15.4% 16.4% 15.9% 12.5% 9.0%

Technical Potential 12.5% 13.6% 15.1% 13.0% 11.2% 8.7%

Table 7-3 Residential Electric Achievable Low Potential by End Use and Market Segment, 

2016 (GWh)

End Use Single 

Family

Single 

Family LI

Multi 

Family Rent

Multi 

Family Rent 

LI

Multi 

Family Own

Multi 

Family Own 

LI

Cooling 39.8 10.2 10.7 8.5 3.5 0.3

Heating 3.1 0.9 1.1 0.2 0.3 0.0

Water Heating 3.9 0.3 0.9 1.5 0.3 0.0

Interior Lighting 353.5 113.5 81.8 49.7 21.6 3.7

Exterior Lighting 41.9 13.9 10.3 8.6 3.8 0.6

Appliances 0.8 0.2 0.1 0.1 0.1 0.0

Electronics 84.5 19.7 13.7 8.0 6.0 0.8

Miscellaneous 3.3 0.3 0.0 - 0.0 -

Total 530.9 159.0 118.7 76.5 35.5 5.5

Residential Electric Potential by End Use

Table 7-4 provides estimates of savings for each end use and type of potential. The most 

significant savings opportunities come from the lighting end use. Negative savings in space 

heating and water heating for the technical potential case reflects the addition of geothermal 

heat pump and heat pump water heating units. This is due to the fuel switching analysis, as 

discussed in more detail in Chapter 9.

Table 7-4 Residential Electric Savings by End Use and Potential Type (GWh)

End Use Case 2013 2014 2015 2016

Cooling Achievable Low Potential 19.7 38.1 55.4 73.1
Energy Efficiency Potential By Sector

7-4 www.enernoc.com

Achievable High Potential 38.1 71.1 100.4 129.2

Economic Potential 132.5 192.4 254.7 311.5

Technical Potential 245.6 376.4 511.1 651.7

Heating

Achievable Low Potential 0.8 1.9 3.4 5.6

Achievable High Potential 1.5 3.6 6.3 10.0

Economic Potential 93.6 181.0 264.2 344.6

Technical Potential -315.6 -630.5 -940.5 -1,280.9

Water Heating

Achievable Low Potential 1.0 2.5 4.4 7.0

Achievable High Potential 2.2 5.1 8.6 13.2

Economic Potential 69.2 131.7 186.2 251.6

Technical Potential 75.8 140.9 198.0 266.9

Interior Lighting

Achievable Low Potential 105.8 342.9 523.0 623.7

Achievable High Potential 216.4 691.6 1,040.9 1,201.0

Economic Potential 728.5 1,873.6 2,521.5 2,442.2

Technical Potential 810.4 2,103.8 2,840.4 2,797.4

Exterior Lighting

Achievable Low Potential 13.8 46.1 69.6 79.1

Achievable High Potential 32.8 106.2 157.2 170.0

Economic Potential 84.5 210.1 276.0 253.4

Technical Potential 105.9 264.4 347.5 330.2

Appliances

Achievable Low Potential 18.7 29.2 34.0 36.2

Achievable High Potential 36.4 54.5 61.3 63.2

Economic Potential 95.9 97.2 102.0 104.9

Technical Potential 166.5 228.1 288.4 350.1

Electronics

Achievable Potential Low 12.6 32.0 59.3 97.8

Achievable Potential High 24.2 60.2 108.9 175.3

Economic Potential 120.8 241.1 363.0 496.4

Technical Potential 124.1 245.5 368.9 504.4

Miscellaneous

Achievable Low Potential 0.2 0.6 1.9 3.5

Achievable High Potential 0.6 1.4 4.3 7.6

Economic Potential 4.4 8.5 19.2 29.4

Technical Potential 46.9 89.1 128.8 169.2

Total

Achievable Low Potential 172.6 493.2 751.0 926.1

Achievable High Potential 352.1 993.6 1,487.9 1,769.5

Economic Potential 1,329.4 2,935.5 3,986.9 4,234.0

Technical Potential 1,259.5 2,817.7 3,742.6 3,789.0

Figure 7-2 focuses on the residential achievable potential in 2016. Lighting equipment 

replacement accounts for the highest portion of the savings in the near term as a result of the 

efficiency gap between CFL lamps and advanced incandescent lamps, even those that will meet 

the EISA 2007 standard. Electronics, cooling, and appliances also contribute significantly to the 

savings. Detailed measure information is available in Appendix B. The key measures comprising 

the potential are listed below: 
Energy Efficiency Potential By Sector

EnerNOC Utility Solutions Consulting 7-5

 Lighting: mostly CFL lamps and specialty bulbs

 Electronics (reduce standby wattage, televisions, set top boxes, PCs)

 Second refrigerator/ freezer removal

 HVAC: Removal of second room AC unit, efficient air conditioners, ducting repair/sealing, 

insulation, home energy management system and programmable thermostats

 Behavioral feedback tools

Figure 7-2 Residential Electric Achievable Low Potential by End Use in 2016 

Cooling

8 %

Heating

1 % Water Heating

1 %

Int Lighting

67%

Ext Lighting

8 %

Appliances

4 % Electronics

11%

Miscellaneous

0 %

Residential Natural Gas Potential

Table 7-5 presents estimates for the four types of potential for natural gas usage in the 

residential sector. Figure 7-3 depicts these potential energy savings estimates graphically. 

 Achievable Low potential projects 0.6 million therms (mmTherms) of energy savings in 

2013, 0.0% of the baseline forecast. This increases to 6.9 mmTherms, 0.3% of the baseline 

forecast, in 2016.

 Achievable High potential is 1.1 mmTherms in 2013, which represents 0.0% of the 

baseline forecast. By 2016, the cumulative energy savings are 12.8 mmTherms, 0.5% of the 

baseline forecast.

 Economic potential, which reflects a theoretical limit to savings when all cost-effective 

measures are taken, is 1.7 mmTherms in 2013. This represents 0.1% of the baseline energy 

forecast. By 2016, economic potential reaches 28.2 mmTherms, 1.2% of the baseline energy 

forecast.

 Technical potential, which reflects the adoption of all energy efficiency measures 

regardless of cost, is a theoretical upper bound on savings. In 2013, energy savings are 105

mmTherms, or 4.6% of the baseline energy forecast. By 2016, technical potential reaches 

394.1 mmTherms, 16.8% of the baseline energy forecast. 
Energy Efficiency Potential By Sector

7-6 www.enernoc.com

The reason that natural gas technical potential savings are so high relative to economic potential 

savings has to do with the fuel switching analysis that was applied to the residential sector. 

Certain electric technologies were the most technically efficient option, while their corresponding 

natural gas technologies were the most economically efficient option. This caused customers to 

switch en masse to electric units in the technical potential case, while customers switched en 

mass to natural gas units in the economic potential case. When considering electric and natural 

gas on a total energy basis, the technical potential uses less energy than the economic potential, 

as one would expect. This is explained in more detail in Chapter 9. 

Table 7-5 Natural Gas Energy Efficiency Potential for the Residential Sector

2013 2014 2015 2016

Energy Forecasts (million therms) 2,299.6 2,318.6 2,332.9 2,351.6

Cumulative Energy Savings (million therms)

Achievable Low Potential 0.6 2.3 4.8 6.9

Achievable High Potential 1.1 4.6 9.3 12.8

Economic Potential 1.7 12.7 24.0 28.2

Technical Potential 105.3 200.2 293.3 394.1

Energy Savings (% of Baseline Forecast)

Achievable Low Potential 0.0% 0.1% 0.2% 0.3%

Achievable High Potential 0.0% 0.2% 0.4% 0.5%

Economic Potential 0.1% 0.5% 1.0% 1.2%

Technical Potential 4.6% 8.6% 12.6% 16.8%

Figure 7-3 Residential Natural Gas Potential Savings

0 %

2 %

4 %

6 %

8 %

10%

12%

14%

16%

18%

2013 2014 2015 2016

Energy Savings (% of Baseline Forecast)

Achievable Potential Low 

Achievable Potential High 

Economic Potential 

Technical Potential 

Residential Natural Gas Potential by Market Segment

Single-family homes in New Jersey account for the majority of this sector’s total sales in the base 

year and throughout the forecast. Similarly, single-family homes account for the largest share of 

potential savings by segment, as displayed in Table 7-6, which shows results for 2016. The fuel 

switching analysis causes an influx of natural gas water heaters in the economic potential, which 
Energy Efficiency Potential By Sector

EnerNOC Utility Solutions Consulting 7-7

actually increases the load so much in the Single Family Low Income sector that it pushes the 

savings negative. It should be noted that the effects of the fuel switching units are minimal in 

the achievable potential cases, as the adoption rates are so low that they put the number of 

statewide transactions in the hundreds and low thousands. 

Table 7-7 shows the savings by end use and market segment in 2016. Heating and water heating 

comprise the lion share of savings. 

Table 7-6 Residential Natural Gas Potential by Market Segment, 2016 (thousand therms)

Single 

Family

Single 

Family LI

Multi 

Family 

Rent

Multi 

Family 

Rent LI

Multi 

Family 

Own

Multi 

Family

Own LI

Baseline Forecast (thousand therms) 1,334,761 358,074 324,636 218,574 96,860 18,739

Energy Savings (thousand therms)

Achievable Low Potential 4,185 1,116 830 534 216 40

Achievable High Potential 7,756 2,073 1,543 991 392 73

Economic Potential 11,984 -1,522 9,628 3,379 3,218 1,499

Technical Potential 232,232 60,617 49,533 35,027 13,268 3,439

Energy Savings as % of Baseline

Achievable Low Potential 0.3% 0.3% 0.3% 0.2% 0.2% 0.2%

Achievable High Potential 0.6% 0.6% 0.5% 0.5% 0.4% 0.4%

Economic Potential 0.9% -0.4% 3.0% 1.5% 3.3% 8.0%

Technical Potential 17.4% 16.9% 15.3% 16.0% 13.7% 18.4%

Table 7-7 Residential Achievable Potential Low by End Use and Market Segment, 2016 

(thousand therms)

End Use Single 

Family

Single 

Family LI

Multi 

Family Rent

Multi 

Family Rent 

LI

Multi 

Family Own

Multi 

Family Own 

LI

Heating 2,763 664 595 409 126 23

Appliances 1,368 447 236 126 90 16

Miscellaneous 0 0 0 0 0 0

Water Heating 54 5 0 0 0 0

Total 4,185 1,116 830 534 216 40

Residential Natural Gas Potential by End Use

Table 7-8 provides estimates of savings for each end use and type of potential. Negative savings 

in water heating for the economic potential case reflects the conversion of electric and fuel oil 

water heaters to high efficiency condensing natural gas fired units. This is due to the fuel 

switching analysis, as discussed in more detail in Chapter 9.

Table 7-8 Residential Natural Gas Savings by End Use and Potential Type (million therms)

End Use Case 2013 2014 2015 2016

Heating

Achievable Low Potential 0.4 1.4 2.9 4.6

Achievable High Potential 0.8 2.6 5.4 8.3

Economic Potential 5.5 15.1 25.8 33.4

Technical Potential 97.0 186.0 274.2 369.2
Energy Efficiency Potential By Sector

7-8 www.enernoc.com

Appliances

Achievable Low Potential 0.1 0.9 1.8 2.3

Achievable High Potential 0.3 1.9 3.7 4.4

Economic Potential -3.8 -2.6 -2.1 -5.7

Technical Potential 6.3 10.6 14.0 18.2

Miscellaneous

Achievable Low Potential 0.0 0.0 0.0 0.0

Achievable High Potential 0.0 0.0 0.0 0.0

Economic Potential 0.0 0.0 0.0 0.0

Technical Potential 0.6 1.3 1.9 2.5

Water Heating

Achievable Low Potential 0.0 0.0 0.0 0.1

Achievable High Potential 0.0 0.0 0.1 0.1

Economic Potential 0.0 0.2 0.3 0.5

Technical Potential 0.8 1.5 2.2 2.8

Total

Achievable Low Potential 0.6 2.3 4.8 6.9

Achievable High Potential 1.1 4.6 9.3 12.8

Economic Potential 1.7 12.7 24.0 28.2

Technical Potential 104.7 199.4 292.2 392.7

Figure 7-4 focuses on the range of residential achievable potential in 2016. As expected, space 

heating and water heating savings are the largest opportunities. Detailed measure information is 

available in Appendix B. The key measures comprising the potential are listed below: 

 Efficient furnaces & boilers, boiler hot water reset ,ducting repair/sealing, insulation, home 

energy management system & programmable thermostats

 Efficient water heaters, low-flow showerheads, faucet aerators, and water heater tank 

blankets

 Behavioral feedback tools.
Energy Efficiency Potential By Sector

EnerNOC Utility Solutions Consulting 7-9

Figure 7-4 Residential Natural Gas Achievable Low Potential by End Use in 2016 

Heating

66%

Water Heating

33%

Appliances

0 %

Misc

1 %

Commercial Electricity Potential

The baseline forecast for the commercial sector only grows slightly, which reflects the sluggish 

near-term economy and forthcoming codes and standards. Nevertheless, the opportunity for 

energy-efficiency savings is still significant for the commercial sector. Table 7-9 presents

estimates for the four types of potential for the residential electricity sector. Figure 7-5 depicts 

these potential energy savings estimates graphically.

 Achievable Low potential projects 251 GWh of energy savings in 2013, 0.7% of the 

baseline forecast. This increases to 1,217 GWh, 3.4% of the baseline forecast, in 2016.

 Achievable High potential is 519 GWh in 2013, which represents 1.4% of the baseline 

forecast. By 2016, the cumulative energy savings are 2,296 GWh, 6.4% of the baseline 

forecast.

 Economic potential, which reflects a theoretical limit to savings when all cost-effective 

measures are taken, is 1,883 GWh in 2013. This represents 5.2% of the baseline energy 

forecast. By 2016, economic potential reaches 4,670 GWh, 13.0% of the baseline energy 

forecast.

 Technical potential, which reflects the adoption of all energy efficiency measures 

regardless of cost, is a theoretical upper bound on savings. In 2013, energy savings are 

2,215 GWh, or 6.1% of the baseline energy forecast. By 2016, technical potential reaches 

5,541 GWh, 15.5% of the baseline energy forecast. 
Energy Efficiency Potential By Sector

7-10 www.enernoc.com

Table 7-9 Electricity Efficiency Potential for the Commercial Sector

2013 2014 2015 2016

Baseline Forecast (GWh) 36,511 35,964 35,699 35,797

Savings (GWh)

Achievable Low Potential 251 585 889 1,217

Achievable High Potential 519 1,164 1,729 2,296

Economic Potential 1,883 3,030 3,943 4,670

Technical Potential 2,215 3,500 4,598 5,541

Savings (% of Baseline)

Achievable Low Potential 0.7% 1.6% 2.5% 3.4%

Achievable High Potential 1.4% 3.2% 4.8% 6.4%

Economic Potential 5.2% 8.4% 11.0% 13.0%

Technical Potential 6.0% 9.7% 12.9% 15.5%

Figure 7-5 Commercial Energy Efficiency Potential Savings

0 %

2 %

4 %

6 %

8 %

10%

12%

14%

16%

18%

2013 2014 2015 2016

Energy Savings (% of Baseline Forecast)

Achievable Potential Low 

Achievable Potential High 

Economic Potential 

Technical Potential 
Energy Efficiency Potential By Sector

EnerNOC Utility Solutions Consulting 7-11

Commercial Electric Potential by Market Segment

Table 7-10 shows potential estimates by building type segment in 2016. Retail has the largest 

achievable- low savings potential in 2016, followed by grocery, large office, and small office. 

Table 7-10. Table 7-11 summarizes achievable potential for each segment and end use.

Table 7-10 Commercial Electric Potential by Market Segment, 2016

Small 

Office

Large 

Office

Restaura

nt

Retail Grocery College

Baseline Forecast 4,094 5,581 1,616 6,811 3,683 2,082

Energy Savings (1,000 MWh)

Achievable Low Potential 130 149 48 263 151 67

Achievable High Potential 249 295 91 489 285 126

Economic Potential 493 612 191 1,026 544 260

Technical Potential 590 728 236 1,206 691 299

Energy Savings (% of Baseline)

Achievable Low Potential 3.2% 2.7% 3.0% 3.9% 4.1% 3.2%

Achievable High Potential 6.1% 5.3% 5.6% 7.2% 7.7% 6.0%

Economic Potential 12.0% 11.0% 11.8% 15.1% 14.8% 12.5%

Technical Potential 14.4% 13.0% 14.6% 17.7% 18.8% 14.3%

School Health Lodging Warehouse Misc. Total

Baseline Forecast 1,814 4,126 915 2,197 2,877 35,797

Energy Savings (1,000 MWh)

Achievable Low Potential 72 111 30 97 99 1,217

Achievable High Potential 131 211 56 179 184 2,296

Economic Potential 252 444 110 355 384 4,670

Technical Potential 304 510 135 389 456 5,541

Energy Savings (% of Baseline)

Achievable Low Potential 3.9% 2.7% 3.3% 4.4% 3.5% 3.4%

Achievable High Potential 7.2% 5.1% 6.1% 8.2% 6.4% 6.4%

Economic Potential 13.9% 10.8% 12.1% 16.2% 13.3% 13.0%

Technical Potential 16.7% 12.4% 14.7% 17.7% 15.9% 15.5%
Energy Efficiency Potential By Sector

7-12 www.enernoc.com

Table 7-11 Commercial Electric Achievable Low Potential by End Use and Market Segment, 

2016 (GWh)

Segment Cooling Space 

Heating

Ventil

ation

Water 

Heat

Int. 

Lighting

Ext. 

Lighting

Food 

Prep

Refriger

ation

Office 

Equip Misc Total

Small Office 16.5 3.7 4.6 3.3 50.4 24.8 0.0 0.8 26.1 0.0 130.3

Large Office 16.9 4.0 22.4 3.6 49.2 15.2 0.0 1.9 36.1 0.0 149.3

Restaurant 4.3 0.5 4.3 4.5 11.0 9.4 0.6 11.9 1.3 0.0 47.8

Retail 23.2 9.7 25.4 9.7 132.7 41.1 1.3 10.7 9.0 0.0 262.8

Grocery 9.4 1.9 6.9 3.5 28.2 8.3 1.5 90.4 1.0 0.0 150.9

College 8.1 2.1 5.9 3.7 29.6 10.6 0.1 0.7 6.2 0.0 67.0

School 3.4 0.6 1.6 1.9 44.5 12.0 0.3 2.3 5.1 0.0 71.6

Health 7.0 1.1 2.5 2.5 29.4 6.6 0.1 2.4 4.8 0.0 56.5

Lodging 3.2 2.2 1.4 1.8 32.1 7.4 0.1 4.0 0.6 0.0 52.9

Warehouse 8.2 1.6 2.5 2.3 37.1 25.4 0.0 1.5 13.1 0.0 91.9

Miscellaneous 33.3 4.7 13.7 5.1 47.5 23.8 0.2 2.5 4.6 0.0 135.5

Total 133.6 32.3 91.3 41.7 491.7 184.6 4.3 129.1 107.8 0.1 1217

Commercial Electric Potential by End Use

Table 7-12 presents the commercial sector savings by end use and potential type. The end uses 

with the highest technical and economic potential are lighting, cooling, ventilation, and 

refrigeration.

Figure 7-6 focuses on achievable potential savings by end use. Not surprisingly, interior lighting 

delivers the highest achievable savings throughout the study period. In 2016, exterior lighting is 

second, and refrigeration is third. Regarding refrigeration, it is interesting to point out a 

relatively new control and sensing technology that vendors such as “eCube” are using to regulate 

the system energy. The technology consists of a solid, waxy food simulant that is fitted around 

a thermostat sensor that would otherwise measure air temperature. The refrigeration controls 

therefore attempt to regulate the temperature of food, which changes more slowly and gradually 

than air, thereby reducing the frequency of refrigeration on/off cycles. Refrigeration energy 

savings are then followed in descending order by cooling, ventilation, office equipment, and 

small amounts of the other end uses. 

Detailed measure information is available in the Appendix C. The key measures comprising the 

potential are listed below: 

 Lighting – CFLs, LED lamps, linear fluorescent, daylighting controls, occupancy sensors, and 

HID lamps for exterior lighting 

 Energy management systems & programmable thermostats

 Ventilation – variable speed control 

 Refrigeration – efficient equipment, control systems, decommissioning 

 Efficient office equipment – computers, servers
Energy Efficiency Potential By Sector

EnerNOC Utility Solutions Consulting 7-13

Table 7-12 Commercial Potential by End Use and Potential Type (GWh)

End Use Case 2013 2014 2015 2016

Cooling

Achievable Low Potential 23 46 82 134

Achievable High Potential 51 100 168 262

Economic Potential 257 342 449 585

Technical Potential 320 444 611 810

Heating

Achievable Low Potential 6 11 20 32

Achievable High Potential 14 25 42 66

Economic Potential 76 97 125 161

Technical Potential 91 118 156 204

Ventilation

Achievable Low Potential 12 28 53 91

Achievable High Potential 29 65 117 192

Economic Potential 211 354 505 668

Technical Potential 239 392 555 733

Water Heating

Achievable Low Potential 5 14 26 42

Achievable High Potential 12 30 55 87

Economic Potential 65 120 176 234

Technical Potential 80 140 201 266

Interior Lighting

Achievable Low Potential 126 295 399 492

Achievable High Potential 244 553 732 875

Economic Potential 752 1,278 1,565 1,700

Technical Potential 839 1,396 1,725 1,919

Exterior Lighting

Achievable Low Potential 30 79 133 185

Achievable High Potential 59 148 243 324

Economic Potential 156 294 403 465

Technical Potential 167 309 424 494

Refrigeration

Achievable Low Potential 32 60 90 126

Achievable High Potential 70 123 176 237

Economic Potential 260 307 360 422

Technical Potential 343 424 513 611

Food Preparation

Achievable Low Potential 1 3 5 7

Achievable High Potential 2 6 10 16

Economic Potential 10 20 30 41

Technical Potential 10 20 30 41

Office Equipment

Achievable Low Potential 16 49 82 108

Achievable High Potential 38 113 185 236

Economic Potential 96 219 329 393

Technical Potential 125 258 382 461

Miscellaneous

Achievable Low Potential 0 0 0 0

Achievable High Potential 0 0 0 0

Economic Potential 0 1 1 1

Technical Potential 0 1 1 1

Total

Achievable Low Potential 251 585 889 1,217

Achievable High Potential 519 1,164 1,729 2,296

Economic Potential 1,883 3,030 3,943 4,670

Technical Potential 2,215 3,500 4,598 5,541
Energy Efficiency Potential By Sector

7-14 www.enernoc.com

Figure 7-6 Commercial Achievable Low Potential Electricity Savings by End Use in 2016

Cooling

11%

Heating

3 %

Water Heating

3 %

Ventilation

8 %

Int. Lighting

40%

Ext. Lighting

15%

Refrigeration

10%

Food Prep

1 %

Office Equip

9 %

Misc

0 %

Commercial Natural Gas Potential

Table 7-13 and Figure 7-7 present the savings associated with each level of potential. The 

highlights from the potentials are described below.

 Achievable Low potential projects 5 million therms (mmTherms) of energy savings in 

2013, 0.3% of the baseline forecast. This increases to 34 mmTherms, 2.0% of the baseline 

forecast, in 2016.

 Achievable High potential is 12 mmTherms in 2013, which represents 0.7% of the 

baseline forecast. By 2016, the cumulative energy savings are 69 mmTherms, 3.9% of the 

baseline forecast.

 Economic potential, which reflects a theoretical limit to savings when all cost-effective 

measures are taken, is 67 mmTherms in 2013. This represents 3.8% of the baseline energy 

forecast. By 2016, economic potential reaches 175 mmTherms, 9.9% of the baseline energy 

forecast.

 Technical potential, which reflects the adoption of all energy efficiency measures 

regardless of cost, is a theoretical upper bound on savings. In 2013, energy savings are 87

mmTherms, or 4.9% of the baseline energy forecast. By 2016, technical potential reaches 

226 mmTherms, 12.9% of the baseline energy forecast. 
Energy Efficiency Potential By Sector

EnerNOC Utility Solutions Consulting 7-15

Table 7-13 Natural Gas Efficiency Potential for the Commercial Sector

2013 2014 2015 2016

Energy Forecasts (mmTherm) 1,771 1,753 1,748 1,756

Cumulative Energy Savings (mmTherm)

Achievable Low Potential 5.2 11.4 20.6 34.3 

Achievable High Potential 12.0 25.1 43.5 69.2 

Economic Potential 66.6 96.3 131.5 174.6 

Technical Potential 86.5 125.9 171.2 225.8 

Energy Savings (% of Baseline Forecast)

Achievable Low Potential 0.3% 0.7% 1.2% 2.0%

Achievable High Potential 0.7% 1.4% 2.5% 3.9%

Economic Potential 3.8% 5.5% 7.5% 9.9%

Technical Potential 4.9% 7.2% 9.8% 12.9%

Figure 7-7 Commercial Natural Gas Potential Savings

0 %

2 %

4 %

6 %

8 %

10%

12%

14%

2013 2014 2015 2016

Energy Savings (% of Baseline Forecast)

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential

Commercial Natural Gas Potential by Market Segment

Table 7-14 below shows natural gas potential estimates by segment in 2016. Table 7-15

summarizes the achievable potential for each segment by end use. 
Energy Efficiency Potential By Sector

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Table 7-14 Commercial Natural Gas Potential by Market Segment, 2016

Small Office Large Office Restaurant Retail Grocery College

Baseline Forecast 176,002 137,427 99,587 305,804 57,370 102,268

Energy Savings (thousand therms)

Achievable Low Potential 3,553 2,448 1,557 6,380 1,257 2,234

Achievable High Potential 7,225 4,981 3,259 12,967 2,565 4,443

Economic Potential 18,677 11,930 8,495 33,366 6,406 10,105

Technical Potential 26,360 18,767 9,216 39,950 7,251 13,481

Energy Savings (% of Baseline)

Achievable Low Potential 2.0% 1.8% 1.6% 2.1% 2.2% 2.2%

Achievable High Potential 4.1% 3.6% 3.3% 4.2% 4.5% 4.3%

Economic Potential 10.6% 8.7% 8.5% 10.9% 11.2% 9.9%

Technical Potential 15.0% 13.7% 9.3% 13.1% 12.6% 13.2%

School Health Lodging Warehouse Misc. Total

Baseline Forecast 140,064 285,802 58,486 96,759 296,601 1,756,171

Energy Savings (thousand therms)

Achievable Low Potential 1,588 5,425 778 1,804 7,258 34,281

Achievable High Potential 3,256 10,847 1,569 3,674 14,379 69,165

Economic Potential 8,737 26,464 4,118 10,620 35,641 174,559

Technical Potential 16,001 32,263 5,963 13,160 43,427 225,838

Energy Savings (% of Baseline)

Achievable Low Potential 1.1% 1.9% 1.3% 1.9% 2.4% 2.0%

Achievable High Potential 2.3% 3.8% 2.7% 3.8% 4.8% 3.9%

Economic Potential 6.2% 9.3% 7.0% 11.0% 12.0% 9.9%

Technical Potential 11.4% 11.3% 10.2% 13.6% 14.6% 12.9%

Table 7-15 Commercial Natural Gas Achievable High Potential by End Use and Market 

Segment, 2016 (million therms)

Segment Space Heating Water Heat Food Prep Misc. Total

Small Office 6.4 0.8 0.0 6.2 13.4

Large Office 4.2 0.6 0.2 4.2 9.1

Restaurant 0.7 1.1 1.5 1.4 4.7

Retail 10.6 1.7 0.7 11.0 24.0

Grocery 1.9 0.5 0.1 2.3 4.8

College 3.6 0.8 0.1 3.9 8.3

School 1.9 0.9 0.4 2.2 5.4

Health 6.7 2.8 1.3 8.5 19.3

Lodging 0.4 1.0 0.2 1.1 2.6

Warehouse 3.6 0.1 0.0 3.3 7.0

Misc. 12.8 1.2 0.4 12.9 27.2

Total 52.8 11.4 4.9 56.9 126.1
Energy Efficiency Potential By Sector

EnerNOC Utility Solutions Consulting 7-17

Commercial Natural Gas Potential by End Use

Table 7-16 presents the commercial sector savings by end use and potential type. The end uses 

with the highest technical and economic potential are heating, water heating, and food 

preparation. This study shows no savings available in the miscellaneous end use due to its

uncertain composition. 

Table 7-16 Commercial Natural Gas Potential by End Use and Potential Type (million therms)

End Use Case 2013 2014 2015 2016

Heating

Achievable Low Potential 4.0 8.8 15.8 26.3

Achievable High Potential 9.3 19.2 33.1 52.8

Economic Potential 50.7 71.7 97.3 129.5

Technical Potential 68.0 97.6 131.7 173.8

Water Heating

Achievable Low Potential 0.9 1.9 3.5 5.7

Achievable High Potential 1.9 4.1 7.3 11.4

Economic Potential 12.3 17.7 23.9 31.1

Technical Potential 15.0 21.4 29.1 38.1

Food Preparation

Achievable Low Potential 0.3 0.7 1.4 2.2

Achievable High Potential 0.7 1.7 3.1 4.9

Economic Potential 3.5 6.9 10.3 13.9

Technical Potential 3.5 6.9 10.3 13.9

Miscellaneous

Achievable Low Potential 0.0 0.0 0.0 0.0

Achievable High Potential 0.0 0.0 0.0 0.0

Economic Potential 0.0 0.0 0.0 0.1

Technical Potential 0.0 0.1 0.1 0.1

Total

Achievable Low Potential 5.2 11.4 20.6 34.3

Achievable High Potential 12.0 25.1 43.5 69.2

Economic Potential 66.6 96.3 131.5 174.6

Technical Potential 86.5 125.9 171.2 225.8

Figure 7-8 below shows achievable potential savings by end use. As expected, heating provides 

the largest share of the savings, with water heating and food preparation each successively 

smaller. Detailed measure information is available in Appendix C. The key measures comprising 

the potential are listed below: 

 Energy management systems, programmable thermostats, HVAC occupancy sensors

 Efficient boilers, boiler maintenance, steam trap repair and hot water reset

 Efficient water heaters

 Efficient food preparation equipment for the restaurant segment

 Insulation and high efficiency windows
Energy Efficiency Potential By Sector

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Figure 7-8 Commercial Natural Gas Achievable Low Potential Savings by End Use in 2016

Heating

77%

Water Heating

17%

Food Prep

6 %

Misc

0 %

Industrial Electricity Potential

The industrial sector in New Jersey only accounts for 11% of total energy consumption, but there 

are prime efficiency opportunities nonetheless. Table 7-17 and Figure 7-9 present the savings for 

the various types of potential considered in this study.

 Achievable Low potential projects 22 GWh of energy savings in 2013 and 113 GWh in 

2016. This corresponds to 0.3% of the baseline forecast in 2013 and 1.5% in 2016. 

 Achievable High potential is 46 GWh in 2013, which represents 0.6% of the baseline 

forecast. By 2016, the cumulative energy savings are 212 GWh, 2.7% of the baseline 

forecast. 

 Economic potential, which reflects the savings when all cost-effective measures are taken, 

is 205 GWh in 2013. This represents 2.6% of the baseline energy forecast. By 2016, 

economic potential reaches 464 GWh, 6.0% of the baseline energy forecast. 

 Technical potential, which reflects the adoption of all energy efficiency measures 

regardless of cost, is a theoretical upper bound on savings. In 2013, energy savings are 222

GWh, or 2.8% of the baseline energy forecast. By 2016, technical potential reaches 518

GWh, 6.7% of the baseline energy forecast. 
Energy Efficiency Potential By Sector

EnerNOC Utility Solutions Consulting 7-19

Table 7-17 Electric Efficiency Potential for the Industrial Sector

2013 2014 2015 2016

Energy Forecasts (GWh) 7,822 7,858 7,937 7,732

Cumulative Energy Savings (GWh)

Achievable Low Potential 22 47 78 113

Achievable High Potential 46 93 150 212

Economic Potential 205 290 386 464

Technical Potential 222 316 426 518

Energy Savings (% of Baseline Forecast)

Achievable Low Potential 0.3% 0.6% 1.0% 1.5%

Achievable High Potential 0.6% 1.2% 1.9% 2.7%

Economic Potential 2.6% 3.7% 4.9% 6.0%

Technical Potential 2.8% 4.0% 5.4% 6.7%

Figure 7-9 Industrial Electric Potential Savings

0 %

1 %

2 %

3 %

4 %

5 %

6 %

7 %

8 %

2013 2014 2015 2016

Energy Savings (% of Baseline Forecast)

Achievable Potential Low 

Achievable Potential High 

Economic Potential 

Technical Potential 

Industrial Electric Potential by Market Segment

Table 7-18 shows electric energy efficiency potential for the four industrial segments in 2016. 

Table 7-19 shows the Achievable Low savings by end use and market segment in 2016.
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Table 7-18 Industrial Electric Potential by Market Segment, 2016

Chemical and 

Pharmaceutical Paper Food Other Industrial Total

Baseline Forecast (GWh) 2,475 1,074 720 3,464 7,732

Energy Savings (GWh)

Achievable Low Potential 31.5 15.5 9.8 55.9 112.8

Achievable High Potential 58.8 28.7 18.2 106.0 211.7

Economic Potential 119.7 56.8 38.3 249.3 464.1

Technical Potential 128.1 58.7 43.3 287.6 517.6

Energy Savings as % of Baseline

Achievable Low Potential 1.3% 1.4% 1.4% 1.6% 1.5%

Achievable High Potential 2.4% 2.7% 2.5% 3.1% 2.7%

Economic Potential 4.8% 5.3% 5.3% 7.2% 6.0%

Technical Potential 5.2% 5.5% 6.0% 8.3% 6.7%

Table 7-19 Industrial Electric Achievable Potential Low by End Use and Market Segment, 2016

End Use Chemical and 

Pharmaceutical Paper Food Other Industrial Total

Cooling 2.09 0.66 0.79 11.58 15.12

Heating 0.57 0.18 0.21 3.09 4.05

Ventilation 0.74 0.23 0.28 3.84 5.09

Interior Lighting 2.46 1.14 1.25 13.95 18.79

Exterior Lighting 0.26 0.12 0.13 1.43 1.94

Motors 22.69 12.81 5.22 19.27 59.99

Process 2.71 0.39 1.93 2.76 7.79

Miscellaneous - - - - -

Grand Total 31.52 15.52 9.81 55.92 112.78

Industrial Electric Potential by End Use

Table 7-20 provides estimates of savings for each end use and type of potential. Not surprisingly, 

the largest savings opportunities are found in motors and drives.
Energy Efficiency Potential By Sector

EnerNOC Utility Solutions Consulting 7-21

Table 7-20 Industrial Electric Potential by End Use and Potential Type (GWh)

End Use Potential 2013 2014 2015 2016

Cooling

Achievable Low Potential 2.5 5.4 9.7 15.1

Achievable High Potential 5.7 11.4 19.8 29.6

Economic Potential 29.8 39.9 54.0 67.3

Technical Potential 38.1 53.2 74.0 92.4

Heating

Achievable Low Potential 0.7 1.4 2.5 4.1

Achievable High Potential 1.7 3.2 5.5 8.4

Economic Potential 9.2 11.8 15.2 18.8

Technical Potential 12.2 16.4 22.7 28.8

Ventilation

Achievable Low Potential 0.7 1.8 3.4 5.1

Achievable High Potential 1.7 4.1 7.6 11.1

Economic Potential 16.9 32.8 49.8 63.2

Technical Potential 18.2 34.3 51.4 65.1

Interior Lighting

Achievable Low Potential 3.8 8.5 14.1 18.8

Achievable High Potential 7.6 16.4 26.3 33.8

Economic Potential 34.8 55.0 71.8 74.5

Technical Potential 37.9 59.0 77.1 81.6

Exterior Lighting

Achievable Low Potential 0.5 1.1 1.7 1.9

Achievable High Potential 1.0 2.1 3.1 3.5

Economic Potential 2.8 4.4 5.6 5.4

Technical Potential 2.9 4.6 5.8 5.7

Motors

Achievable Low Potential 13.1 26.3 41.8 60.0

Achievable High Potential 26.9 51.9 79.9 111.2

Economic Potential 101.9 131.8 168.9 206.4

Technical Potential 97.7 125.9 160.6 197.4

Process

Achievable Low Potential 0.9 2.2 4.4 7.8

Achievable High Potential 1.9 4.2 8.2 14.0

Economic Potential 9.7 14.3 20.7 28.2

Technical Potential 12.4 18.3 26.7 36.4

Miscellaneous

Achievable Low Potential - - - -

Achievable High Potential - - - -

Economic Potential - - - -

Technical Potential - - - -

Total

Achievable Low Potential 22.3 46.7 77.6 112.8

Achievable High Potential 46.5 93.3 150.4 211.7

Economic Potential 205.1 290.0 385.9 464.0

Technical Potential 219.5 311.8 418.3 507.4

Figure 7-10 illustrates the achievable potential savings by electric end use in 2016 for the 

industrial sector. The largest shares of savings opportunities are in the motors and machine 

drives. Potential savings for straight equipment change-outs are diminishing due to the National 

Electrical Manufacturer’s Association (NEMA) standards, which now make premium efficiency 

motors the baseline efficiency level. As a result, potential savings are incrementally small to 
Energy Efficiency Potential By Sector

7-22 www.enernoc.com

upgrade to even more efficient levels. Many of the savings opportunities in this end use come 

from controls, timers, and variable speed drives, which improve system efficiencies where motors 

are utilized. 

Beyond the replacement of motors, there are large opportunities for savings in cooling, lighting, 

process, ventilation, and finally space heating. Detailed measure information is available in 

Appendix D. The key measures comprising the potential are listed below: 

 Motors – drives and controls

 Process – timers and controls

 Application optimization and control – fans, pumps, compressed air 

 Efficient high bay lighting

 Efficient ventilation systems

 Energy management systems & programmable thermostats

Figure 7-10 Industrial Achievable Low Electricity Potential Savings by End Use in 2016 

Cooling

13%

Heating

4 %

Ventilation

4 %

Int. Lighting

17%

Ext. Lighting

2 %

Motors

53%

Process

7 %

Misc

0 %

Industrial Natural Gas Potential

Table 7-21 and Figure 7-11 present the savings for the various types of potential considered in 

this study for the industrial sector.

 Achievable Low potential projects 0.1 million therms (mmTherms) of energy savings in 

2013, 0.0% of the baseline forecast. This increases to 1.0 mmTherms, 0.2% of the baseline 

forecast, in 2016.

 Achievable High potential is 0.3 mmTherms in 2013, which represents 0.1% of the 

baseline forecast. By 2016, the cumulative energy savings are 2.0 mmTherms, 0.4% of the 

baseline forecast.
Energy Efficiency Potential By Sector

EnerNOC Utility Solutions Consulting 7-23

 Economic potential, which reflects a theoretical limit to savings when all cost-effective 

measures are taken, is 1.9 mmTherms in 2013. This represents 0.4% of the baseline energy 

forecast. By 2016, economic potential reaches 5.4 mmTherms, 1.1% of the baseline energy 

forecast.

 Technical potential, which reflects the adoption of all energy efficiency measures 

regardless of cost, is a theoretical upper bound on savings. In 2013, energy savings are 10.0

mmTherms, or 2.0% of the baseline energy forecast. By 2016, technical potential reaches 

29.3 mmTherms, 6.1% of the baseline energy forecast. 

Table 7-21 Natural Gas Efficiency Potential for the Industrial Sector

2013 2014 2015 2016

Energy Forecasts (million therms) 489 487 487 481

Cumulative Energy Savings (million therms)

Achievable Low Potential 0.1 0.3 0.6 1.0

Achievable High Potential 0.3 0.7 1.3 2.0

Economic Potential 1.9 2.7 4.1 5.4

Technical Potential 10.0 14.5 21.3 29.3

Energy Savings (% of Baseline Forecast)

Achievable Low Potential 0.0% 0.1% 0.1% 0.2%

Achievable High Potential 0.1% 0.1% 0.3% 0.4%

Economic Potential 0.4% 0.5% 0.8% 1.1%

Technical Potential 2.0% 3.0% 4.4% 6.1%

Figure 7-11 Industrial Natural Gas Potential Savings

0 %

1 %

2 %

3 %

4 %

5 %

6 %

7 %

2013 2014 2015 2016

Energy Savings (% of Baseline Forecast)

Achievable Potential Low 

Achievable Potential High 

Economic Potential 

Technical Potential 
Energy Efficiency Potential By Sector

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Industrial Natural Gas Potential by Market Segment

Table 7-22 shows electric energy efficiency potential for the four industrial segments in 2016. 

Table 7-23 shows the Achievable Low savings by end use and market segment in 2016. A large 

portion of the savings comes from space heating improvements in the Other Industrial category. 

The largest industrial segments typically dedicate very little of their energy to space condition ing, 

so the smaller businesses that are grouped into the Other Industrial category will have more by 

comparison. 

Table 7-22 Industrial Natural Gas Potential by Market Segment, 2016

Chemical and 

Pharmaceutical Paper Food Other Industrial Total

Baseline Forecast (thousand therms) 165,316 73,008 66,053 176,521 480,898

Energy Savings (thousand therms)

Achievable Low Potential 88.4 51.7 50.0 815.5 1,005.5

Achievable High Potential 163.0 96.6 94.5 1,632.7 1,986.8

Economic Potential 494.7 311.7 279.5 4,361.4 5,447.2

Technical Potential 9,926.5 4,413.5 3,865.6 11,132.8 29,338.5

Energy Savings as % of Baseline

Achievable Low Potential 0.1% 0.1% 0.1% 0.5% 0.2%

Achievable High Potential 0.1% 0.1% 0.1% 0.9% 0.4%

Economic Potential 0.3% 0.4% 0.4% 2.5% 1.1%

Technical Potential 6.0% 6.0% 5.9% 6.3% 6.1%

Table 7-23 Industrial Natural Gas Achievable Potential Low by End Use and Market Segment, 

2016 (million therms)

End Use

Chemical and 

Pharmaceutic

al

Paper Food Other 

Industrial Total

Heating 32 22 27 795 876

Process 56 30 23 20 130

Miscellaneous 25 16 21 609 671

Total 114 68 71 1,425 1,677

Industrial Natural Gas Potential by End Use

Table 7-24 provides estimates of savings for each end use and type of potential. Since natural 

gas is chiefly used for heating, the number of end uses is more limited than the electricity 

analysis.
Energy Efficiency Potential By Sector

EnerNOC Utility Solutions Consulting 7-25

Table 7-24 Industrial Natural Gas Potential by End Use and Potential Type (thousand therms)

End Use Potential 2013 2014 2015 2016

Heating

Achievable Low Potential 140.4 291.7 558.9 875.9

Achievable High Potential 324.3 640.4 1,164.9 1,759.3

Economic Potential 1,887.1 2,613.3 3,722.7 4,670.3

Technical Potential 3,340.6 4,733.3 6,780.9 8,793.7

Process

Achievable Low Potential - 6.8 58.6 129.6

Achievable High Potential - 12.6 105.1 227.5

Economic Potential - 63.0 409.7 777.0

Technical Potential 6,486.8 9,539.7 14,068.8 19,827.2

Miscellaneous

Achievable Low Potential - - - -

Achievable High Potential - - - -

Economic Potential - - - -

Technical Potential - - - -

Total

Achievable Low Potential 140.4 298.5 617.5 1,005.5

Achievable High Potential 324.3 653.0 1,269.9 1,986.8

Economic Potential 1,887.1 2,676.4 4,132.4 5,447.2

Technical Potential 9,827.5 14,273.0 20,849.7 28,621.0

Figure 7-12 illustrates the achievable potential savings by natural gas end use in 2016 for the 

industrial sector. Space heating and process heating are the only opportunities to speak of.

Detailed measure information is available in Appendix D. The key measures comprising the 

potential are listed below: 

 Energy management systems & programmable thermostats

 Efficient boilers & furnaces

 Insulation

Figure 7-12 Industrial Natural Gas Achievable Low Potential Savings by End Use in 2016 

Heating

87%

Process

13%

Misc

0%

EnerNOC Utility Solutions Consulting 8-1

CHAPTER 8

ALTERNATE AVOIDED COST SCENARIO

To observe the sensitivity of study results to changes in forecast market prices of electricity and 

natural gas, we ran a scenario in which the avoided costs for each fuel in each year of the study 

were increased by 20%. The models were then re-run with all other variables held constant. 

The total number of measures passing the economic screen (with TRC benefit-to-cost ratio 

greater or equal to 1.0) increased from 6,343 to 6,578.21 This is an increase of only 3.7%, 

because only a fraction of measures are close to the marginal value of 1.0. Details can be seen 

below in Table 8-1.

Table 8-1 Alternate Avoided Cost Scenario, Count of Measures Passing Economic Screen

Sector

Count of All Measures with B/C ratio > 1.0, All Fuels

Reference Case:

Avoided Costs from New 

Jersey Rate Counsel

Alternate Case:

20% Higher Avoided

Costs

Delta

Residential 995 1,064 6.9%

Commercial 3,842 3,975 3.5%

Industrial 1,506 1,539 2.2%

Total 6,343 6,578 3.7%

With the newly passing measures migrating from technical potential into economic and 

achievable potential, the savings are increased by a small amount. The electric achievable low 

potential in 2016, for instance, only increased from 3.1% of the baseline forecast to 3.2%. This 

is a change of 66 GWh or 2.9% of total savings, as shown in Table 8-2

Table 8-2 Alternate Avoided Cost Scenario, 2016 Achievable Low Potential (GWh savings)

Sector

Reference Case: Avoided 

Costs from New Jersey 

Rate Counsel

Alternate Case:20% 

Higher Avoided Costs Delta

Residential 936 944 0.9%

Commercial 1,214 1,265 4.2%

Industrial 112 119 6.3%

Total 2,262 2,328 2.9%

The effects of the change are more pronounced for natural gas measures, as the savings 

potential in the reference case is already quite low. The natural gas achievable low potential in 

2016 increased from 1.0% to 1.2%. This is a change of 2.6 million therms or 12.3% of total 

savings in the reference case, as shown in Table 8-3.

 

21 The number of measures cited here includes all permutations of technologies and measures, as well as their 

inclusion in the various building segments. It should be noted that this is distinct from the measure count given 

in Chapter 5, which for simplicity of reporting does not consider the dimension of building segment. 
Alternate Avoided Cost Scenario

8-2 www.enernoc.com

Table 8-3 Alternate Avoided Cost Scenario, 2016 Achievable Low Potential (million therm 

savings)

Sector

Reference Case:

Avoided Costs from New 

Jersey Rate Counsel

Alternate Case:20% 

Higher Avoided Costs Delta

Residential 8.4 9.2 8.6%

Commercial 38.9 41.6 7.0%

Industrial 1.3 3.9 194.1%

Total 48.6 54.6 12.3%
EnerNOC Utility Solutions Consulting 9-1

CHAPTER 9

FUEL SWITCHING ANALYSIS

Energy efficiency potential studies have not traditionally explored the effects of switching 

technologies between system types and fuel types. In this context, where both electricity and 

natural gas are being studied on a statewide basis, one may wish to investigate the economic 

potential of switching from room air conditioning to central air conditioning technology. Or an 

example that is very relevant in the New Jersey market; will consumers switch from fuel oil 

furnaces to natural gas furnaces, and if so, how many?

The equipment stock accounting inside the LoadMAP modeling tool has the ability to support 

such a switching analysis, and has been activated and incorporated for the residential sector in 

all the results given above. The switching forecast is integrated with the traditional potential 

analysis, and operates on the same principles to calculate technical, economic, and achievable 

cases in turn. There are several important distinctions to the switching case, however, that 

should be discussed. 

Technical Potential and Fuel Switching

First, the technical potential must compare all eligible technologies on an apples -to-apples basis. 

Therefore, kWh, therms, gallons of fuel oil, or any other fuel source must be converted to BTUs 

so the most efficient option can be selected on a same-fuel basis. The conversion factors used in 

the study are shown in Table 9-1 below. It is important to note our assumption in this study that 

electric energy is considered at the system level rather than at the meter. To convert directly 

from a kWh to kBTU, the factor is 3.414. This was factored up by 3.34 to account for the energy 

expended at the generator and lost during transmission. 

Table 9-1 Converting to kBTU for Switching Comparison 

Fuel Value Units

Electricity 11.4 kBTU per kWh

Natural Gas 100.0 kBTU per Therm 

Fuel Oil 138.7 kBTU per Gallon

Economic Potential and Fuel Switching

The next consideration is that of economics. The lifetime benefits from energy saving are again 

compared to the incremental measure cost in the same way as the core potential analysis 

described above. The switching analysis, however, includes an additional switching cost between 

$280 and $462 depending on the technology, extra labor required, and additional parts or 

components required. If we revisit the example of switching from room AC to central AC, one 

would need to install ductwork, pour a concrete pad outside the home, and so on in order to 

enable the technology.

Achievable Potential and Fuel Switching

Finally, all economic decisions are decremented by the market adoption rates to arrive at 

achievable potential in the same manner as the core analysis. After this, the adoption is 

penalized by an additional factor to account for the fact that people very rarely choose fuel 

switching due to its inherently higher complexity. This factor, which we term “propensity,” has 

been set at 5% in this analysis for all years and all measures.
Fuel Switching Analysis

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The technologies made available for the switching analysis are shown below in Table 9-2, along 

with information regarding the directionality that they can be moved if the energy, economic, 

and adoption data align appropriately. For example, the analysis assumes that a customer may 

wish to switch away from a natural gas boiler to a geothermal heat pump, but never the 

opposite. 

Table 9-2 Switching Options and Directionality 

Fuel Technology Switchable Directionality

Electric Central AC TRUE Both Ways

Electric Room AC TRUE From Only

Electric Electric Room Heat TRUE From Only

Electric Electric Furnace TRUE From Only

Electric Air-Source Heat Pump TRUE To Only

Electric Geothermal Heat Pump TRUE To Only

Electric Water Heater <=55 gal TRUE Both Ways

Electric Water Heater > 55 gal TRUE Both Ways

Natural Gas Furnace TRUE Both Ways

Natural Gas Boiler TRUE From Only

Natural Gas Water Heater <=55 gal TRUE Both Ways

Natural Gas Water Heater > 55 gal TRUE Both Ways

Fuel Oil Furnace TRUE From Only

Fuel Oil Boiler TRUE From Only

Fuel Oil Water Heater <=55 gal TRUE From Only

Fuel Oil Water Heater > 55 gal TRUE From Only

The fuel switching analysis results for the achievable potential cases show that the market will 

likely support the migration of 3,177 to 5,713 space heating systems between 2013 and 2016. 

These will virtually all occur in the form of converting natural gas boilers, electric furnaces, and 

fuel oil systems to natural gas furnaces. 

During the same time period, the analysis also predicts that 1,118 to 2,434 water heaters will be 

switched, primarily from electric to gas water heaters, although some segments and niches have 

load profiles and economics that dictate switching in the opposite direction. The model does not 

predict any air conditioning or cooling technology switches.

These results can be viewed pictorially or in tables on the following pages. Figure 9-1and Figure 

9-2 show the achievable low and high potential cases for space heating, with all data in the 

positive y-axis representing a unit that has switched into a category. Each graph is symmetrical, 

therefore, with a corresponding unit along the negative y-axis that has been switched away from 

a category. Figure 9-3 and Figure 9-4 show the same information for water heating technologies. 

The unit counts are available in Table 9-3 and Table 9-4.
Fuel Switching Analysis

EnerNOC Utility Solutions Consulting 9-3

Figure 9-1 Space Heating – Number of Fuel Switching Units, Achievable Low Case 

-2,000

-1,500

-1,000

-500

0

500

1,000

1,500

2,000

2013 2014 2015 2016

Number of Units Switched

Negative = Outgoing - - - - - - - Positive = Incoming

Gas Furnace (in)

Air-Source Heat Pump (in)

Fuel Oil Furnace (out)

Fuel Oil Boiler (out)

Gas Furnace (out)

Gas Boiler (out)

Electric Room Heat (out)

Electric Furnace (out)

Figure 9-2 Space Heating – Number of Fuel Switching Units, Achievable High Case

-2,000

-1,500

-1,000

-500

0

500

1,000

1,500

2,000

2013 2014 2015 2016

Number of Units Switched

Negative = Outgoing - - - - - - - Positive = Incoming

Gas Furnace (in)

Air-Source Heat Pump (in)

Fuel Oil Furnace (out)

Fuel Oil Boiler (out)

Gas Furnace (out)

Gas Boiler (out)

Electric Room Heat (out)

Electric Furnace (out)
Fuel Switching Analysis

9-4 www.enernoc.com

Table 9-3 Space Heating – Number of Fuel Switching Units

Switching 

Direction Technology

Achievable Low Achievable High

2013 2014 2015 2016 2013 2014 2015 2016

Outgoing

Electric Furnace (out) -19 -28 -37 -20 -37 -52 -65 -34

Electric Room Heat (out) -32 -47 -60 -73 -62 -87 -108 -125

Gas Boiler (out) -301 -452 -603 -755 -579 -838 -1077 -1301

Gas Furnace (out) 0 0 0 0 0 0 -1 -1

Fuel Oil Boiler (out) -82 -124 -166 -208 -158 -230 -296 -359

Fuel Oil Furnace (out) -23 -35 -47 -64 -44 -64 -84 -110

Incoming

Air-Source Heat Pump (in) 0 0 0 0 0 1 1 1

Gas Furnace (in) 458 686 913 1,119 881 1,271 1,630 1,929

Figure 9-3 Water Heating – Number of Fuel Switching Units, Achievable Low Case 

-1,200

-1,000

-800

-600

-400

-200

0

200

400

600

800

1,000

1,200

2013 2014 2015 2016

Number of Units Switched

Negative = Outgoing - - - - - - - Positive = Incoming

Gas WH (in)

Elec WH (in)

Fuel Oil WH (out)

Gas WH (out)

Elec WH (out)
Fuel Switching Analysis

EnerNOC Utility Solutions Consulting 9-5

Figure 9-4 Water Heating – Number of Fuel Switching Units, Achievable High Case

-1,200

-1,000

-800

-600

-400

-200

0

200

400

600

800

1,000

1,200

2013 2014 2015 2016

Number of Units Switched

Negative = Outgoing - - - - - - - Positive = Incoming

Gas WH (in)

Elec WH (in)

Fuel Oil WH (out)

Gas WH (out)

Elec WH (out)

Table 9-4 Water Heating – Number of Fuel Switching Units

Switching 

Direction Technology

Achievable Low Achievable High

2013 2014 2015 2016 2013 2014 2015 2016

Outgoing

Electric WH (out) -108 -155 -202 -306 -258 -353 -439 -638

Natural Gas WH (out) -5 -7 -8 -108 -12 -15 -18 -226

Fuel Oil WH (out) -30 -44 -59 -85 -71 -101 -129 -176

Incoming

Electric WH (in) 5 7 8 108 12 15 18 226

Natural Gas WH (in) 138 200 261 391 329 454 568 814

Fuel Oil WH (in) 0 0 0 0 0 0 0 0

EnerNOC Utility Solutions Consulting 10-1

CHAPTER 10

CONCLUSIONS AND RECOMMENDATIONS

The results of this study reveal that significant energy efficiency opportunities exist in New 

Jersey, despite appliance and efficiency standards and a challenging macroeconomic 

environment. Our analysis has shown that New Jersey can realize an achievable range of 

reductions from 3.1% to 5.9% of the forecasted 2016 electric load, as well as 1.0% to 1.9% of 

the forecasted 2016 natural gas load, by implementing the measures presented in this report.

New Jersey’s energy-efficiency programs have a strong legacy, ample market momentum, and a 

good platform to deliver joint electric and natural gas programs on a uniform, statewide basis. 

The suite of programs is being evaluated for the next four-year planning cycle, and based on this 

study, EnerNOC provides the following recommendations for the programs.

General Recommendations 

 Capitalize on joint electric and natural gas programs: Since the New Jersey Office of 

Clean Energy manages the statewide energy efficiency portfolio in all New Jersey electric and 

natural gas utility territories, there is a good opportunity to create cross-cutting programs 

with uniform marketing messages for combined electric and natural gas savings opportunities 

for customers. This should allow for cost savings and administrative savings.

 Increase focus on business programs: Our study shows that the majority of energy 

efficiency potential exists in the commercial and industrial sectors. Historically, 60-70% of 

the New Jersey EE budgets have been allocated to residential programs. The NJOCE should 

consider increasing program efforts in the C&I sectors, not only to harvest larger EE savings, 

but to increase business competitiveness and decrease operating costs. Additionally, these 

sectors offer larger projects, which can be bundled more easily with creative financing and 

incentives.

 Collaboration among stakeholders: The discourse and information sharing between 

NJOCE, CEEEPS, stakeholders, implementers, and EnerNOC on this study has been efficient

and transparent. Continuing this trend to cultivate a mutual understanding of continuous 

improvement and development is of paramount importance to the future success of 

programs. We recommend a continued interaction among these parties with regular touch 

points and workshops. Possible workshop topics are: technical resource manual with deemed 

measure databases; evaluation, measurement, and verification protocols; emerging 

technologies; innovative program strategies; periodic reviews of program results; and 

sharing success stories from individual programs or customers.

Residential Recommendations 

 Focus on lighting: The largest share of achievable energy efficiency potential in the 

residential sector continues to come from CFLs. This is in spite of the forthcoming EISA 

standards that will reduce their per-unit savings compared to the new baseline. Also, New 

Jersey should focus strong attention on specialty lamps, as they are not addressed in the 

EISA standard.

 Appliance recycling programs show considerable promise: Recycling programs for 

appliances such as second refrigerators and room air conditioners show a considerable 

amount of potential, and should be considered for the New Jersey market. Consider ways to 

combine this offering with trade allies or market partners who are delivering other appliance 

related programs. 
Conclusions and Recommendations

10-2 www.enernoc.com

 Develop whole-house opportunities: Measures such as duct sealing, insulation, energy 

management systems, and programmable thermostats offer opportunities for a jointly 

delivered electric and natural gas program for whole-house savings. 

 Investigate behavioral feedback programs: Behavioral change programs have 

traditionally not been formal components of energy efficiency portfolios, largely due to 

difficulties in measuring and attributing savings. However, there is mounting evidence that 

these programs do produce measurable savings and program administrators around the 

country are beginning to aim personalized messaging, energy reports, and other media at 

customers in an effort to reduce their energy usage. This study includes fairly conservative 

assumptions regarding savings, penetration rates, and program rollouts for a “behavioral 

feedback tools” measure for the residential sector. The measure passed the cost 

effectiveness screen and contributed meaningful savings to the portfolio. While the impacts 

are relatively small compared to other measures (< 1% of total energy savings), this is a 

new and emerging opportunity that may undergo meaningful change in the coming years. 

For New Jersey, this would be an interesting opportunity to keep in mind, as it is a program 

that lends itself well to the combined statewide electric and natural gas delivery framework. 

 Consider social media avenues for targeted program delivery: As internet social 

media paradigms become the norm in today’s wired society, companies like Groupon, 

Amazon Local Deals, and Living Social have assembled a nationwide network of businesses 

into a well-oiled, rebate-issuing machine. NJOCE should consider if there are opportunities to 

link their energy efficiency trade ally network to one of these companies to facilitate the 

target marketing, processing, and delivery of rebates. These vendors have sophisticated 

tracking systems and databases that may facilitate EM&V reporting on the back end as well.

Commercial and Industrial Recommendations 

 Aggressively pursue lighting savings: The commercial sector in particular has significant 

savings potential in lighting, both interior, exterior, screw-in, and high bay. Savings are also 

available through occupancy sensors, timers, and energy management systems. NJOCE 

should strongly pursue lighting savings to accelerate the phase out of T12 fluorescent 

lighting. In particular, program efforts can help intercept building operators before they 

make purchase and stocking decisions that could lead to the hoarding of T12 lamps. 

 Create customized, multi-year plans for large, complex customers: For large 

customers, strategic energy management (SEM) 22 initiatives can deliver savings over longer 

time horizons. This means a larger tracking and time commitment, but many jurisdictions are 

finding this to be a more effective method than a “one and done” installation and rebate 

approach. These relationships involve personalized plans, identification of metrics, goalsetting, technical assistance, and attention from dedicated account executives or energy 

coaches. This is similar to the current “Energy Savings Improvement Plan” program, and 

administrators should consider expanding or refining it to cater to New Jersey’s largest C&I 

customers. 

 Focus industrial program efforts on motor controls and system optimizations: The 

savings for the industrial sector are all about control and optimization of motors and 

processes. Low-cost retrofits can often have significant energy impacts with minimal 

disruption of (and often times improvement of) business processes. 

 Target niches with segment specific programs: There are specific segments that offer 

considerable savings potential, but will not typically be reached by standard rebate programs 

and generic business programs. Consider whether it makes sense to initiate a specifically 

targeted program such as one for food preparation equipment in restaurants or refrigeration 

equipment in grocery stores. 

 

22 Sometimes called Continuous Energy Improvement (CEI).
EnerNOC Utility Solutions Consulting 11-1

CHAPTER 11

COMPARISON TO RECENT REGIONAL POTENTIAL STUDIES

We compared the average annual potential savings for all sectors from our study with two recent 

regional studies to see how they aligned. In general, the results that we produced are on a 

reasonable par with these studies. The two studies compared were: 

 Delaware’s Energy Efficiency Potential and Program Scenarios to Meet Its Energy 

Efficiency Resource Standard. A study by Center for Energy and Environmental Policy, 

University of Delaware, available at:

http://www.ceep.udel.edu/energy/publications/2011_DNREC_EERS_CEEP_Report_May_2011.

pdf

Our Achievable High case most closely corresponds to the case in this study that assumes 

the most aggressive participation rates in the country (i.e. Vermont), and so is compared to 

it. We compare our Achievable Low case with their case that assumes the average 

participation rates from the “14 leading states” that have the highest participation rates in 

the nation. This study covers electricity and natural gas.

 Electric Energy Efficiency Potential for Pennsylvania. A study by GDS Associates and 

Nexant, May 10, 2012, available at: http://www.puc.state.pa.us/electric/pdf/Act129/Act129-

PA_Market_Potential_Study051012.pdf

Our Achievable High Case corresponds to their high case, in which they assume high 

adoption rates and an incentive amount that is 100% of the incremental cost of measures. 

We compare our Achievable Low Case to their case with incentives of 30% to 60% of 

incremental cost. This study only covers electricity.

The three studies show an annual Achievable High potential for electric savings in the range of 

1.1% to 1.9%, while the Achievable Low is in the range of 0.7% to 0.8% per year. 

For natural gas, the two studies have an annual Achievable High potential between 0.5% and 

0.9%, whereas the Achievable Low is in the range of 0.3% to 0.5% per year. Please see the 

Table 11-1 and Figure 11-1 for the data.

Table 11-1 Comparison to other studies (average annual savings vs. baseline forecast)

Achievable High Achievable Low

Electricity 

New Jersey – ENOC (2013-2016) 1.5% 0.8%

Delaware – U of DL (2011-2015) 1.9% 0.8%

Pennsylvania – GDS (2013-2016) 1.1% 0.7%

Natural Gas

New Jersey – ENOC (2013-2016) 0.5% 0.3%

Delaware – U of DL (2011-2015) 0.9% 0.5%

Pennsylvania – GDS (2013-2016) N/A N/A
Comparison to Recent Regional Potential Studies

11-2 www.enernoc.com

Figure 11-1 Comparison with recent regional potential studies

1.5%

0.8%

1.9%

0.8%

1.1%

0.7%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

2.0%

Achievable High Achievable Low

Electric EE Potential 

Average Annual Savings vs. Baseline Forecast

NJ - ENOC (2013-2016)

DL - UofDL (2011-2015)

PA - GDS (2013-2016)

0.5%

0.3%

0.9%

0.5%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

2.0%

Achievable High Achievable Low

Natural Gas EE Potential 

Average Annual Savings vs. Baseline Forecast
EnerNOC Utility Solutions Consulting 12-1

CHAPTER 12

ENERGY EFFICIENCY POTENTIAL BEYOND 2016 

New Jersey’s next program planning cycle for the years 2013 to 2016 was the primary focus of 

this study and report. However, because there is a small incremental effort to include additional 

years in our modeling framework, we have extended the methodologies described above to 

produce estimates of energy efficiency potential through the year 2024. This will provide insight 

into longer term planning for the next two planning cycles: 2017 to 2020 and 2021 to 2024.

We present overall and sector-level results of the energy-efficiency analysis for the State of New 

Jersey. Key findings related to potentials are summarized below.

 Achievable Low potential forms a lower point on the range of achievable potential. Across 

all sectors, this metric is 29,925 BTU in 2016 and increases to 160,552 BTU by 2024. This 

represents 2.3% of the baseline forecast in 2016 and 11.4% in 2024. 

 Achievable High potential forms the upper bound on the range of achievable potential. It 

is 57,144 BTU in 2016, which represents 4.4% of the baseline forecast. By 2024, the 

cumulative savings are 225,579 BTU, 16.0% of the baseline forecast. 

 Economic potential, which reflects the savings when all cost-effective measures are taken, 

is 127,588 BTU in 2016. This represents 9.9% of the baseline energy forecast. By 2024, 

economic potential reaches 326,006 BTU, 23.1% of the baseline energy forecast. 

 Technical potential, which reflects the adoption of all energy efficiency measures 

regardless of cost-effectiveness, is a theoretical upper bound on savings. In 2016, energy 

savings are 177,390 BTU, or 13.7% of the baseline energy forecast. By 2024, technical 

potential reaches 471,288 BTU, % of the baseline energy forecast. 

Table 12-1 and Figure 12-1 summarize the energy-efficiency savings for the different levels of 

potential relative to the baseline forecast. Figure 12-2 displays the energy-efficiency forecasts.

To combine the electric and natural gas energy efficiency potentials, kWhs and therms are both 

converted to a common unit, BTUs, in order to facilitate comparison. Table 9-1 in the fuel 

switching analysis chapter shows the conversion factors.
Energy Efficiency Potential BEYOND 2016

12-2 www.enernoc.com

Table 12-1 Summary of Combined Electric and Natural Gas Energy Efficiency Potential

2013 2016 2020 2024

Baseline Forecast (million BTU) 1,308,205 1,291,174 1,344,903 1,412,982

Cumulative Savings (million BTU)

Achievable Potential Low 5,678 29,925 87,381 160,552

Achievable Potential High 11,799 57,144 140,787 225,579

Economic Potential 45,966 127,588 224,560 326,006

Technical Potential 62,433 177,390 324,214 471,288

Energy Savings (% of Baseline)

Achievable Potential Low 0.4% 2.3% 6.5% 11.4%

Achievable Potential High 0.9% 4.4% 10.5% 16.0%

Economic Potential 3.5% 9.9% 16.7% 23.1%

Technical Potential 4.8% 13.7% 24.1% 33.4%

Figure 12-1 Summary of Combined Electric and Natural Gas Energy Savings

0%

5%

10%

15%

20%

25%

30%

35%

40%

2013 2016 2020 2024

Energy Savings (% of Baseline Forecast)

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential
EnerNOC Utility Solutions Consulting 12-3

Figure 12-2 Combined Electric and Natural Gas Potential Forecasts (million BTU)

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

Energy Consumption (million BTU)

Baseline Forecast

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential

Electric Energy Efficiency – Overall Results 

Table 12-2 and Figure 12-3 summarize the electric energy-efficiency savings for the different 

levels of potential relative to the baseline forecast. Figure 12-4 displays the electric energyefficiency forecasts.

Table 12-2 Summary of Electric Energy Efficiency Potential

2013 2016 2020 2024

Baseline Forecast (GWh) 74,776 73,031 76,603 81,041

Cumulative Savings (GWh)

Achievable Potential Low 446 2,255 6,200 10,945

Achievable Potential High 918 4,277 9,891 15,219

Economic Potential 3,418 9,369 15,536 21,932

Technical Potential 3,708 9,868 16,276 23,126

Energy Savings (% of Baseline)

Achievable Potential Low 0.6% 3.1% 8.1% 13.5%

Achievable Potential High 1.2% 5.9% 12.9% 18.8%

Economic Potential 4.6% 12.8% 20.3% 27.1%

Technical Potential 5.0% 13.5% 21.2% 28.5%
Energy Efficiency Potential BEYOND 2016

12-4 www.enernoc.com

Figure 12-3 Summary of Electric Energy Savings

0%

5%

10%

15%

20%

25%

30%

35%

2013 2016 2020 2024

Energy Savings (% of Baseline Forecast)

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential

Figure 12-4 Electric Potentials Forecasts (GWh)

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

Energy Consumption (1,000 MWh)

Baseline Forecast

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential
EnerNOC Utility Solutions Consulting 12-5

Natural Gas Energy Efficiency – Overall Results 

Table 12-3 and Figure 12-5 summarize the natural gas energy-efficiency savings for the different 

levels of potential relative to the baseline forecast. Figure 12-6 displays the natural gas energyefficiency forecasts.

Table 12-3 Summary of Natural Gas Energy Efficiency Potential

2013 2016 2020 2024

Baseline Forecast (1,000 therms) 4,560,186 4,588,711 4,718,937 4,893,965

Cumulative Savings (1,000 therms)

Achievable Potential Low 5,906 42,208 167,194 358,224

Achievable Potential High 13,420 83,980 280,684 521,336

Economic Potential 70,161 208,193 475,061 760,595

Technical Potential 201,774 649,293 1,387,187 2,077,276

Energy Savings (% of Baseline)

Achievable Potential Low 0.1% 0.9% 3.5% 7.3%

Achievable Potential High 0.3% 1.8% 5.9% 10.7%

Economic Potential 1.5% 4.5% 10.1% 15.5%

Technical Potential 4.4% 14.1% 29.4% 42.4%

Figure 12-5 Summary of Natural Gas Energy Savings

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

2013 2016 2020 2024

Energy Savings (% of Baseline Forecast)

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential
Energy Efficiency Potential BEYOND 2016

12-6 www.enernoc.com

Figure 12-6 Natural Gas Potential Forecasts (1000 therms)

0

1,000

2,000

3,000

4,000

5,000

6,000

Energy Consumption (1,000 therms)

Baseline Forecast

Achievable Potential Low

Achievable Potential High

Economic Potential

Technical Potential

Overview of Energy Efficiency Potential by Sector and Fuel

Table 12-4, Figure 12-7, and Figure 12-8 summarize the range of electric achievable potential by

sector. The commercial sector accounts for the largest portion of the savings, followed by 

residential. The industrial sector contributes a relatively small amount of potential.

Table 12-4 Electric Achievable Potential by Sector (GWh)

2013 2016 2020 2024

Achievable Low Savings (GWh)

Residential 173 926 2,159 2,919

Commercial 251 1,217 3,676 7,309

Industrial 22 113 365 716

Total 446 2,255 6,200 10,945

Achievable High Savings (GWh)

Residential 352 1,769 3,497 4,174

Commercial 519 2,296 5,802 10,034

Industrial 46 212 592 1,011

Total 918 4,277 9,891 15,219
EnerNOC Utility Solutions Consulting 12-7

Figure 12-7 Achievable Low Electric Potential by Sector (GWh)

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

2013 2016 2020 2024

Achievable Low Savings (1,000 MWh)

Residential

Commercial

Industrial

Figure 12-8 Achievable High Electric Potential by Sector (GWh)

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

2013 2016 2020 2024

Achievable High Savings (1,000 MWh)

Residential

Commercial

Industrial
Energy Efficiency Potential BEYOND 2016

12-8 www.enernoc.com

Table 12-5, Figure 12-9, and Figure 12-10 present the range of natural gas achievable potential 

by sector. Again, like the electric analysis, the commercial sector accounts for the largest portion 

of the savings, followed by the residential and then the industrial sectors. 

Table 12-5 Natural Gas Achievable Potential by Sector (million therms)

2013 2016 2020 2024

Achievable Low Savings (million therms)

Residential 0.6 6.9 32.0 83.2

Commercial 5.2 34.3 131.2 266.8

Industrial 0.1 1.0 4.0 8.2

Total 5.9 42.2 167.2 358.2

Achievable High Savings (million therms)

Residential 1.1 12.8 50.6 115.9

Commercial 12.0 69.2 223.3 392.9

Industrial 0.3 2.0 6.8 12.5

Total 13.4 84.0 280.7 521.3
EnerNOC Utility Solutions Consulting 12-9

Figure 12-9 Achievable Low Natural Gas Potential by Sector (million Therms)

0

100

200

300

400

500

600

2013 2016 2020 2024

Achievable Low Savings (million therms)

Residential

Commercial

Industrial

Figure 12-10 Achievable High Natural Gas Potential by Sector (million Therms)

0

100

200

300

400

500

600

2013 2016 2020 2024

Achievable High Savings (million therms)

Residential

Commercial

Industrial
Energy Efficiency Potential BEYOND 2016

12-10 www.enernoc.com

EnerNOC Utility Solutions Consulting

500 Ygnacio Valley Road, Suite 450

Walnut Creek, CA 94596

P: 925.482.2000

F: 925.284.3147

About EnerNOC Utility Solutions Consulting

EnerNOC Utility Solutions Consulting is part of EnerNOC Utility Solutions group, which 

provides a comprehensive suite of demand-side management (DSM) services to 

utilities and grid operators worldwide. Hundreds of utilities have leveraged our 

technology, our people, and our proven processes to make their energy efficiency 

(EE) and demand response (DR) initiatives a success. Utilities trust EnerNOC to work 

with them at every stage of the DSM program lifecycle – assessing market potential, 

designing effective programs, implementing those programs, and measuring program 

results. 

EnerNOC Utility Solutions delivers value to our utility clients through two separate 

practice areas – Program Implementation and EnerNOC Utility Solutions Consulting.

• Our Program Implementation team leverages EnerNOC’s deep “behind-the-meter 

expertise” and world-class technology platform to help utilities create and 

manage DR and EE programs that deliver reliable and cost-effective energy 

savings. We focus exclusively on the commercial and industrial (C&I) customer 

segments, with a track record of successful partnerships that spans more than a 

decade. Through a focus on high quality, measurable savings, EnerNOC has 

successfully delivered hundreds of thousands of MWh of energy efficiency for 

our utility clients, and we have thousands of MW of demand response capacity 

under management.

• The EnerNOC Utility Solutions Consulting team provides expertise and analysis 

to support a broad range of utility DSM activities, including: potential 

assessments; end-use forecasts; integrated resource planning; EE, DR, and 

smart grid pilot and program design and administration; load research; 

technology assessments and demonstrations; evaluation, measurement and 

verification; and regulatory support. 

The EnerNOC Utility Solutions Consulting team has decades of combined experience 

in the utility DSM industry. The staff is comprised of professional electrical, 

mechanical, chemical, civil, industrial, and environmental engineers as well as 

economists, business planners, project managers, market researchers, load research 

professionals, and statisticians. Utilities view our experts as trusted advisors, and we 

work together collaboratively to make any DSM initiative a success.