Global Energy Partners 

500 Ygnacio Valley Road, Suite 450 

Walnut Creek, CA 94596 

P: 925.482.2000 

F: 925.284.3147 

E: gephq@gepllc.com 

ENERGY EFFICIENCY POTENTIAL 

STUDY FOR THE STATE OF 

NEW MEXICO 

Volume 2: Electric Energy Efficiency 

Analysis 

June 30, 2011 

Global Energy Partners iii 

An EnerNOC Company 

Disclaimer 

This report was prepared as an account of work sponsored by an agency of the United States 

Government. Neither the United States Government nor any agency thereof, nor any of their 

employees, makes any warranty, express or implied, or assumes any legal liability or 

responsibility for the accuracy, completeness, or usefulness of any information, apparatus, 

product, or process disclosed, or represents that its use would not infringe privately owned 

rights. Reference herein to any specific commercial product, process, or service by trade name, 

trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, 

recommendation, or favoring by the United States Government or any agency thereof. The views 

and opinions of authors expressed herein do not necessarily state or reflect those of the United 

States Government or any agency thereof. 

This report was prepared by 

Global Energy Partners 

An EnerNOC Company 

500 Ygnacio Valley Blvd., Suite 450 

Walnut Creek, CA 94596 

Project Director: Ingrid Rohmund 

Project Manager: Bridget Kester 

Subcontractor: 

The Brattle Group

353 Sacramento Street, Suite 1140 

San Francisco, CA 94111 

Global Energy Partners v 

An EnerNOC Company 

Acknowledgements 

This material is based upon work supported by the Department of Energy under Award 

Number(s) DE-EE0000108. It was managed by the State of New Mexico’s Energy, Minerals and 

Natural Resources Department’s (EMNRD) Energy, Conservation and Management Division. 

For supporting this work, we thank EMNRD Secretary John Bemis and EMNRD staff Ken Hughes, 

Fernando Martinez, Craig O’Hare (formerly of EMNRD), Brian Johnson, Randy Sweat, Susie 

Marbury and Harold Trujillo. 

For providing utility-specific data that were central to the analysis, we thank Erick Seelinger 

(PNM), Steve Bean (PNM), Dean Brunton (PNM), Sharon James (PNM), Alena Gilchrist 

(KEMA/PNM), Jan Nelson (SPS/Xcel), Suzanne Doyle (SPS/Xcel), Heather Hemphill (SPS/Xcel), 

Mandy McLean (SPS/Xcel), Jeremy Peterson (SPS/Xcel), Ruth Sakya (SPS/Xcel), Paul Royalty (El 

Paso Electric), Susanne Stone (El Paso Electric), Derek Pearson (El Paso Electric) Steve Casey 

(NM Gas Company), Dru Jones (NM Gas Company), John Fernald (NM Gas Company), Keven 

Groenewold (NMRECA), Richard Marquez (NMRECA), Lance Adkins (Farmers’ Electric Coop), Mike 

Sims (Farmington Municipal Electric), Thom Moore (Farmers’ Electric Coop), Christine Chavez 

(Los Alamos Dept. of Public Utilities), Julie Williams-Hill (Los Alamos Dept. of Public Utilities), and 

Deenise Becenti (Navajo Tribal Utility Authority), all of whom were highly supportive and 

responsive throughout the data acquisition process. 

We would also like to thank the stakeholders that provided valuable comments throughout the 

study and participated in the various stakeholder meetings, particularly Tammy Fiebelkorn 

(SWEEP), Keith Freischlag (SWEEP), Tom Singer (NRDC), Jeff Primm (PRC), Leslie Padilla (PRC), 

Marc Martinez (PRC), Roy Stephenson (PRC), Theresa Becenti-Aquilar (PRC), Brendan Miller 

(NMEDD), Tom Schuster (City of Las Cruces), Erik Aaboe (Santa Fe County), Luis Duran (NM 

Workforce), Chris Wentz (Galvin Electric Initiative), Calvin Steckler (PSFA), Birk Jones (Yearout), 

Robin Harder (ENERGY STAR Homes Program), Victoria Sandoval (Graybar), James McLane (WH 

Pacific), Phyllis Kaplan (CASA) and Robb Thomson. 

Finally, we acknowledge the analysis teams from Global and Brattle: 

• Global Energy Partners: Cecilia Arzbaecher, Jan Borstein, Gaynoll Cook, Anthony Duer, 

Vish Ganti, Debyani Ghosh, Patricia Hurtado, Kelly Marrin, Joe Prijyanonda, King Lee, 

Barb Ryan, Abigail Sanchez, Greg Wikler, Craig Williamson, Sharon Yoshida 

• The Brattle Group: Ahmad Faruqui and Doug Mitarotonda 

Sincerely, 

Bridget Kester and Ingrid Rohmund 

Global Energy Partners 

Global Energy Partners vii 

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CONTENTS 

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

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

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

1.3 Defnitions of Potential ...................................................................................... 1-2

1.4 Abbreviations and Acronyms ............................................................................. 1-3

1.5 Report Organization ......................................................................................... 1-4

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

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

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

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

2.1.3 Baseline Forecast ................................................................................. 2-8

2.1.4 Energy Efficiency Measure Analysis ....................................................... 2-9

2.1.5 Energy-Efficiency Potential.................................................................. 2-13

2.1.6 Strategy Recommendations ................................................................ 2-14

2.2 Data Development ......................................................................................... 2-14

2.2.1 Data Sources ..................................................................................... 2-14

2.2.2 Data Application ................................................................................ 2-18

3 MARKET ASSESSMENT AND MARKET PROFILES .................................................. 3-1

3.1 Residential Sector ............................................................................................ 3-3

3.2 Commercial Sector ........................................................................................... 3-6

3.3 Industrial Sector .............................................................................................. 3-9

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

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

4.2 Commercial Sector ........................................................................................... 4-4

4.3 Industrial Sector .............................................................................................. 4-7

4.4 Baseline Forecast Summary .............................................................................. 4-8

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

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

5.2 Results of the Economic Screen ...................................................................... 5-13

6 ELECTRIC ENERGY EFFICIENCY POTENTIAL RESULTS......................................... 6-1

6.1 Overall Electric Energy Efficiency Potential ......................................................... 6-1

6.2 Electricity Residential Sector ........................................................................... 6-10

6.2.1 Residential Potential by Market Segment .............................................. 6-13

6.2.2 Residential Potential by End Use, Technology and Measure Type ........... 6-14

6.2.3 Residential Potential by Entity ............................................................. 6-18

6.3 Commercial Sector Potential ........................................................................... 6-21

6.3.1 Commercial Potential by End Use, Technology, and Measure Type ......... 6-23

6.3.2 Commercial Potential by Market Segment ............................................ 6-28
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6.3.3 Commercial Potential by Entity ............................................................. 6-35

6.4 Industrial Sector Potential ............................................................................... 6-38

6.4.1 Industrial Potential by End Use ............................................................ 6-40

6.4.2 Industrial Potential by Entity ................................................................ 6-42

6.5 Annual Savings and Costs ............................................................................... 6-44

6.6 Scenario Analysis ............................................................................................ 6-47
Global Energy Partners ix 

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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 ....................................................................... 2-9

Figure 3-1 Sector-Level Electricity Use, 2009 ........................................................................ 3-1

Figure 3-2 Residential Electricity Use by Customer Segment, 2009 ......................................... 3-3

Figure 3-3 Residential Electricity Use by End Use, 2009 ......................................................... 3-5

Figure 3-4 End-Use Shares of Total Electricity Use by Housing Type, 2009 .............................. 3-5

Figure 3-5 Commercial Electricity Consumption by End Use, 2009 .......................................... 3-8

Figure 3-6 Commercial End Use Intensities by Building Type, 2009 ......................................... 3-9

Figure 3-7 Industrial Electricity Use by End Use, 2009 ......................................................... 3-11

Figure 3-8 Industrial Electricity Use by End Use, 2009 ......................................................... 3-12

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

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

Figure 4-3 Commercial Baseline Electricity Forecast by End Use ............................................. 4-4

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

Figure 4-5 Baseline Forecast Summary ................................................................................. 4-8

Figure 6-1 Summary of Achievable Potential Energy Savings .................................................. 6-3

Figure 6-2 Energy Efficiency Potential Energy Forecasts (GWh) .............................................. 6-3

Figure 6-3 Achievable Potential by Sector, 2025 .................................................................... 6-4

Figure 6-4 Residential Energy Efficiency Potential Savings.................................................... 6-12

Figure 6-5 Residential Energy Efficiency Potential Forecast .................................................. 6-12

Figure 6-6 Residential Achievable Potential by End Use in 2025 ............................................ 6-16

Figure 6-7 Commercial Energy Efficiency Potential Savings .................................................. 6-22

Figure 6-8 Commercial Energy Efficiency Potential Forecast ................................................. 6-23

Figure 6-9 Commercial Achievable Potential Savings by End Use in 2025 (GWh) .................... 6-25

Figure 6-10 Achievable Potential Savings in 2025 by Commercial Building Type (GWh) ............ 6-29

Figure 6-11 Industrial Energy Efficiency Potential Savings ..................................................... 6-39

Figure 6-12 Industrial Energy Efficiency Potential Forecast .................................................... 6-39

Figure 6-13 Industrial Achievable Potential Savings by End Use in 2025 (GWh) ....................... 6-41

Figure 6-14 Industrial Achievable – Low Potential Savings by End Use in 2025 (GWh) .............. 6-41

Figure 6-15 Annual Program Costs ...................................................................................... 6-45

Figure 6-16 Scenario Analysis Results – Energy Savings as a Percent of the Baseline Forecast .. 6-48

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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 End Uses and Technologies ................................................................ 2-5

Table 2-4 Sample Equipment Measures for Central Air Conditioning – Single Family Home .... 2-11

Table 2-5 Sample Non-Equipment Measures – Single Family Home, Existing ........................ 2-11

Table 2-6 Economic Screen Results for Selected Residential Equipment Measures ................. 2-12

Table 2-7 Utility Saturation Surveys .................................................................................. 2-15

Table 2-8 Data Applied for the Market Profiles ................................................................... 2-19

Table 2-9 Data Needs for the Baseline Forecast and Potentials Estimation in LoadMAP .......... 2-20

Table 2-10 Residential Electric Equipment Standards ........................................................... 2-21

Table 2-11 Commercial Electric Equipment Standards .......................................................... 2-22

Table 2-12 Data Needs for the Measure Characteristics in LoadMAP ...................................... 2-23

Table 2-13 Avoided Cost Forecasts — State-Level Average ................................................... 2-24

Table 3-1 Electricity Use by Entity, 2009 ............................................................................. 3-2

Table 3-2 Residential Sector Electricity Usage and Intensity by Segment Type ........................ 3-3

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

Table 3-4 Commercial Sector Market Characterization Results, 2009 ...................................... 3-6

Table 3-5 Commercial Sector Composite Market Profile, 2009 ............................................... 3-7

Table 3-6 Industrial Market Profile, 2009 ........................................................................... 3-10

Table 3-7 Industrial Electricity Use (GWh) by End Use and Segment, 2009 .......................... 3-11

Table 4-1 Residential Baseline Electricity Forecast by End Use and Technology (GWh) ............ 4-3

Table 4-2 Commercial Electricity Consumption by End Use (GWh) ......................................... 4-5

Table 4-3 Commercial Baseline Electricity Forecast by End Use and Technology (GWh) ........... 4-6

Table 4-4 Industrial Electricity Consumption by End Use (GWh) ............................................ 4-7

Table 4-5 Baseline Forecast Summary ................................................................................. 4-8

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

Table 5-2 Summary of Residential Non-equipment Measures ................................................ 5-4

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

Table 5-4 Summary of Commercial Equipment Measures (Continued) .................................... 5-6

Table 5-5 Summary of Commercial Non-equipment Measures ............................................... 5-7

Table 5-6 Summary of Commercial Non-equipment Measures (Continued) ............................. 5-8

Table 5-7 Summary of Industrial Measures .......................................................................... 5-9

Table 5-8 Summary of Industrial Measures (Continued) ..................................................... 5-10

Table 5-9 Summary of Industrial Measures (Continued) ..................................................... 5-11

Table 5-10 Summary of Industrial Measures (Continued) ..................................................... 5-12

Table 5-11 Number of Measures Evaluated ......................................................................... 5-13

Table 6-1 Summary of Energy Efficiency Potential ................................................................ 6-2

Table 6-2 Achievable Energy-efficiency Potential by Sector (GWh) ......................................... 6-4

Table 6-4 Energy Efficiency Potential by Entity (Peak Demand Savings MW) .......................... 6-8

Table 6-5 Electricity Energy Efficiency Potential for the Residential Sector ............................ 6-11
xii www.gepllc.com 

Table 6-6 Residential Potential by Market Segment, 2025 .................................................... 6-13

Table 6-7 Residential Achievable Potential by End Use and Market Segment, 2025 ................ 6-13

Table 6-8 Residential Savings by End Use and Potential Type (GWh) .................................... 6-15

Table 6-9 Residential Achievable - Low Potential by Technology – Selected years (GWh) ....... 6-17

Table 6-10 Residential Achievable - Low Savings for Non-equipment Measures (GWh) ............. 6-18

Table 6-11 Residential Efficiency Potential by Entity (MWh) ................................................... 6-19

Table 6-12 Energy Efficiency Potential for the Commercial Sector .......................................... 6-22

Table 6-13 Commercial Potential by End Use and Potential Type (GWh) ................................. 6-24

Table 6-14 Commercial Achievable - Low Savings for Equipment Measures (GWh) .................. 6-26

Table 6-15 Commercial Achievable - Low Savings for Non-equipment Measures (GWh) ........... 6-27

Table 6-16 Commercial Potential by Market Segment, 2025 ................................................... 6-28

Table 6-17 Commercial Achievable Savings in 2025 by Building Type (GWh) ........................... 6-30

Table 6-18 Commercial Efficiency Potential by Entity (MWh) .................................................. 6-35

Table 6-19 Energy Efficiency Potential for the Industrial Sector .............................................. 6-38

Table 6-20 Industrial Potential by End Use and Potential Type (GWh) .................................... 6-40

Table 6-21 Industrial Efficiency Potential by Entity (MWh) ..................................................... 6-42

Table 6-22 Summary of Costs for Achievable Potential .......................................................... 6-46

Table 6-23 Scenario Analysis Results – Energy Savings (GWh) ............................................... 6-47

Table 6-24 Scenario Analysis Results – Energy Savings as a Percent of the Baseline Forecast ... 6-48
Global Energy Partners 1-1 

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CHAPTER 1 

INTRODUCTION 

1.1 BACKGROUND 

The State of New Mexico’s Energy, Minerals and Natural Resources Department’s (EMNRD) 

Energy, Conservation and Management Division contracted with Global Energy Partners to 

conduct a state-wide energy efficiency (EE) and demand response (DR) market potential study to 

address utility-level programs in the state. The U.S. Department of Energy (DOE) awarded 

EMNRD funding for this project through the American Recovery and Reinvestment Act (ARRA) to 

enhance the State Energy Program. 

The 2005 adoption of New Mexico’s Efficient Use of Energy Act (EUEA) directs New Mexico to 

support public utility development of all cost-effective energy efficiency and load management 

measures. These measures include removing regulatory disincentives and allowing rate recovery 

of energy efficiency and load management program costs. Under rules set forth by the New 

Mexico Public Regulation Commission (PRC), investor-owned gas and electric public utilities must 

obtain PRC approval of energy efficiency programs, implement those programs, and report their 

results and costs. 

No comprehensive study of the potential for energy efficiency strategies and measures in New 

Mexico has ever been conducted. A 2008 report prepared by Southwest Energy Efficiency Project 

(SWEEP1

) broadly addresses policy options for New Mexico’s energy efficiency strategy, but does 

not analyze potential energy efficiency measures individually, or assess existing saturation levels 

for each measure. The Tri-State Energy Efficiency Potential Study conducted in 20092

 provides 

some estimates for New Mexico for the rural electric co-ops that are a part of Tri-State. Other 

reports, including a 2005 potential study prepared for PNM3

 and a survey of 2006 gas utility 

demand-side management programs are limited in scope and are based on 2004 data. The New 

Mexico and federal public policies encouraging energy efficiency and the recent increase in 

federal funding for such projects make evident the need for a detailed, comprehensive, current 

potential study that assesses individual energy efficiency measures and considers regional 

differences within the state. 

1.2 OBJECTIVES 

Key objectives for the study include: 

• Conduct a state-wide energy efficiency potential study to determine the potential for 

development of specific energy efficiency measures to reduce the consumption of natural 

gas and electricity by regions in New Mexico 

• Conduct a state-wide demand response potential study to determine the potential for 

reduction in peak demand through demand response programs 

• Identify energy-efficiency measures that meet the total resource cost (TRC) test 

o Specify measures relating to housing and building structures and appliances 

o Address climate zones and other geographic considerations, as well as utility 

service areas 

 

1

 Southwest Energy Efficiency Project, Beyond Code: A Guide to Creating Energy Efficient and Sustainable Buildings in the Southwest, 

2008. http://www.swenergy.org/programs/buildings/codes/beyondcode/SWEEP_Beyond_Code_Guide_2008.pdf 2

 Nexant, Cadmus Group, System Wide Electric Energy Efficiency Potential Study, 2010. 3

 Itron, Public Service New Mexico Electric Energy Efficiency Potential Study, 2006 
Introduction State of New Mexico EE and DR Study 

1-2 www.gepllc.com 

• Analyze various market penetration rates associated with technical, economic, and 

achievable potential estimates 

• Describe and quantify the strategies for implementing those measures in a manner that 

produces the maximum achievable energy savings 

• Run scenarios based on three levels of avoided costs 

• Provide information to the public 

1.3 DEFNITIONS OF POTENTIAL 

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

represent net savings4

 and we developed 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. For this reason, we developed a range of achievable potential. 

All four levels are described below. 

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 

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 in the residential sector include: 

• Ductless mini-split air conditioners with variable refrigerant flow 

• Ground source (or geothermal) heat pumps 

• LED lighting for general service and linear applications 

Technical potential also assumes the adoption of every available other 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. The retrofit measures are phased in over a number of years, which is longer for 

higher-cost measures. 

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

In this analysis, the total resource cost (TRC) test, which compares lifetime energy and capacity 

benefits to the incremental cost of the measure, is applied. Economic potential assumes that 

customers purchase the most cost effective option at the time of equipment failure and also 

adopt every other cost-effective and applicable measure. 

Achievable - High potential takes into account expected program participation resulting from 

ideal implementation conditions and customer preferences for energy-efficient technologies and 

demand response programs. Achievable - High establishes a maximum target for the EE savings 

that a utility 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 represents a lower bound on Achievable potential. It reflects 

limited DSM budgets and significant barriers to customer acceptance. 

 

4

 The baseline forecast includes naturally occurring conservation, so the potential estimates represent net program savings (instead of 

gross savings). 
State of New Mexico EE and DR Study Introduction 

Global Energy Partners 1-3 

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1.4 ABBREVIATIONS AND ACRONYMS 

Throughout the report we make reference to several abbreviations and acronyms. Below shows the 

abbreviation or acronym, along with what it stands for and a reference to the section in the report 

that defines the abbreviation or acronym. 

Table 1-1 Explanation of Abbreviations and Acronyms 

Acronym Explanation First referred to in

ACS American Community Survey Chapter 2.2.1.5

AEO Annual Energy Outlook Chapter 2.2.1.5

B/C Ratio Benefit to Cost Ratio Chapter 2.1.5

BEST Building Energy Simulation Tool Chapter 2.2.1.3

C&I Commercial and Industrial Chapter 2.1

D&B Dun and Bradstreet Chapter 2.2.1.5

DEEM Database of Energy Efficiency Measures Chapter 2.2.1.3

DEER Database for Energy Efficient Resources Chapter 2.2.1.4

DR Demand Response Chapter 1.1

EE Energy Efficiency Chapter 1.1

EIA Energy Information Administration Chapter 2.1

EPRI Electric Power Research Institute Chapter 2.1.1

EUEA Efficient Use of Energy Act Chapter 1.1

EUI Energy‐use Index Chapter 2.1.2.2

HH Household Chapter 2.2.2.2

IOU Investor Owned Utility Chapter 2.2.2.2

LoadMAP Load Management Analysis and Planning Chapter 2.1.1

MARs Market Acceptance Rate Chapter 2.1.2

MMTherm Million therms Chapter 2.2.2.5

NTUA Navajo Tribal Utility Authority Chapter 3

NWPPC Northwest Power and Conservation Council Chapter 2.2.1.4

PIFs Program Implementation Factors Chapter 2.1.2

Sq. ft. Square feet Chapter 2.2.2.2

SWEEP Southwest Energy Efficiency Project Chapter 1.1

TRC Total Resource Cost Chapter 1.2

UEC Unit Energy Consumption Chapter 2.1.2.2
Introduction State of New Mexico EE and DR Study 

1-4 www.gepllc.com 

1.5 REPORT ORGANIZATION 

This report is presented in seven volumes: 

Volume 1, Executive Summary 

Volume 2, Electric Energy Efficiency Analysis 

Volume 3, Natural Gas Energy Efficiency Analysis 

Volume 4, Demand Response Analysis 

Volume 5, Summary of Potential Estimates and Study References 

Volume 6, Appendices to Electric Energy Efficiency Analysis 

Volume 7, Appendices to Natural Gas Energy Efficiency Analysis 

This volume contains the following chapters: 

1. Introduction 

2. Analysis Approach and Data Development 

3. Market Assessment and Market Profiles 

4. Baseline Forecast 

5. Energy-Efficiency Measures 

6. Energy-Efficiency Potential Estimates 
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CHAPTER 2 

ANALYSIS APPROACH AND DATA DEVELOPMENT 

2.1 ANALYSIS APPROACH 

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

in Figure 2-1 and summarized below. 

1. Held a meeting with the project team and various stakeholders in the state to refine the 

objectives that were identified in the RFP. This resulted in a work plan for the study. 

2. Performed a market characterization to describe sector-level electricity use for the residential 

and C&I sectors for the base year (2009). This included using utility data and secondary data 

from sources such as EIA. 

3. Utilized primary market research and secondary sources to understand how customers in 

New Mexico currently use electricity. Combining this information with the market 

characterization, we developed energy market profiles that describe energy use by sector, 

segment, and end use for the base year, 2009. 

4. Developed a baseline electricity forecast by sector, segment, and end use for 2010 through 

2025. 

5. Identified and analyzed energy-efficiency measures appropriate for New Mexico. 

6. Estimated four levels of energy-efficiency potential, Technical, Economic, Achievable - High, 

and Achievable - Low. 

7. Reviewed the current programs offered in the state and researched program best practices 

to recommend strategies for achieving savings. 

The steps are described in further detail throughout the remainder of this chapter. 
Analysis Approach and Data Development State of New Mexico EE and DR Study 

2-2 www.gepllc.com 

Figure 2-1 Overview of Analysis Approach 

Baseline forecasting

Customer surveys

Secondary data

Forecast data

Prototypes and 

energy analysis

Market characterization Utility data

EIA data

EE measure list 

Measure description Measure screening

Customer acceptance 

at measure level

Program results

Survey of experts

Establish objectives

Base-year 

energy use by 

fuel, segment 

End-use 

forecast by 

fuel, segment

Technical and 

economic 

potential

Achievable 

potential

Synthesis Program results

Best-practices research

Strategy

Recommendations

2.1.1 LoadMAP Model 

We used the Load Management Analysis and Planning tool (LoadMAPTM) to develop the baseline 

forecast, as well as the estimates of energy-efficiency potential. Global developed LoadMAP in 

2007 and has used 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 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, replacement upon failure, early replacement, and non-owner 

acquisition separately. 

• 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 
State of New Mexico EE and DR Study Analysis Approach and Data Development 

Global Energy Partners 2-3 

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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 equipment 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.5

 

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

2.1.2 Market Characterization 

Before assessing the potential savings from EE, it is critical to develop a good understanding of 

where New Mexico is today in terms of electricity use and customer behavior. The purpose of the 

market assessment is to develop market profiles that describe current electricity use in terms of 

sector, customer segment, and end use. The base year for this study is 2009 since that was the 

most recent year for which utility data were available. 

The market was also characterized by the entity that serves the end-use electric customers. In 

addition to providing a snapshot of electricity use in the base year, it was used to develop factors 

for allocating the potential estimates for each sector to each entity, a key objective of the study. 

 

5

 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., technical potential). 
Analysis Approach and Data Development State of New Mexico EE and DR Study 

2-4 www.gepllc.com 

2.1.2.1 Segmentation for Modeling Purposes 

The market assessment began by defining the market segments (building types, end uses and 

other dimensions) that are relevant in New Mexico. The segmentation scheme employed 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

Dimension 1 Sector Residential, commercial, industrial

Dimension 2 Geographic region

Residential: 3 electric IOUs, 1 Non‐IOU group

(includes munis, co‐ops, and NTUA)

Commercial: Statewide

Industrial: Statewide  

Dimension 3 Building type

Residential (Single family, Multi family, Mobile

home, and Low income)

Commercial (Offices, Restaurant, Retail, etc.)

Industrial (Oil & gas extraction, Electronics

manufacturing, Other industrial)

Dimension 4 Vintage Existing and new construction (for residential and

commercial sectors)

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

appropriate by sector)

Dimension 6 Appliances/end uses and

technologies

Technologies such as lamp type, air conditioning

equipment, motors by size, etc.  

Dimension 7 Equipment efficiency levels for

new purchases

Baseline and higher‐efficiency options as

appropriate for each technology

For the residential sector, there was ample market and survey data. For this reason, the 

residential sector was divided into four groups. Three of the groups represent the service areas 

of each of the investor-owned utilities (IOUs): Public Service New Mexico (PNM), Southwest 

Public Service (SPS) and El Paso Electric (El Paso). The remaining entities were combined into a 

single non-IOU group. Energy use in each group was further divided into customer segments and 

then end use and technology within each customer segment. The customer segments were 

defined as: 

• Single-family homes. This segment includes single-family detached homes, 

townhouses, duplexes or row houses, and manufactured homes. 

• Multi-family homes. The multi-family segment includes apartments or condos in 

buildings with more than two units. 

• Mobile homes: This segment includes mobile homes. Note that manufactured homes 

are considered in the single-family segment. 

• Low-income homes. The low-income category represents those customers that have 

an annual household income of $30,000 or less. This segment includes a mixture of 

home types. 

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

that are appropriate for New Mexico. These are shown in Table 2-2. 
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Table 2-2 Residential End Uses and Technologies 

End Use Technology

Cooling Central Air Conditioning (CAC)

Cooling Room Air Conditioning (RAC)

Cooling Evaporative Central AC

Cooling Evaporative Room AC

Combined Heating/Cooling Central Heat Pump

Combined Heating/Cooling Electric Resistance

Water Heating Water Heater

Interior Lighting Screw‐in Lamps

Interior Lighting Linear Fluorescent Lamps

Exterior Lighting Screw‐in Lamps

Appliances Refrigerator

Appliances Freezer

Appliances Second Refrigerator

Appliances Clothes Washer

Appliances Clothes Dryer

Appliances Stove

Appliances Microwaves

Electronics Personal Computers

Electronics Monitor

Electronics Laptops

Electronics TVs

Electronics Copier/Printer/Fax

Electronics DVD/VCR/Audio

Electronics Devices and Gadgets

Miscellaneous Pool Pump

Miscellaneous Well Pump

Miscellaneous Furnace Fan

Miscellaneous Miscellaneous

For the commercial sector it is useful to think of the segments based on the unique 

characteristics of the type of building. For this study we are using the following eleven building 

types: 

• Small office (less than 50,000 square feet) —all types of offices, including 

medical/dental offices 
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• Large office (greater than or equal to 50,000 square feet) — all types of offices 

including large government facilities 

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

• Retail — retail establishments from small boutiques to large box retailers 

• Grocery — supermarkets, convenience stores and markets 

• Warehouse — refrigerated and non refrigerated storage 

• School — primary and secondary schools 

• College — colleges, universities and technical colleges 

• Health — hospitals and nursing homes 

• Lodging — motels, hotels, resorts and small inns 

• Miscellaneous — all remaining building types such as public assembly, police stations, 

amusement parks, and parking garages 

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

that are appropriate for New Mexico. Table 2-3 lists the end uses and technologies used in this 

study. 

The industrial sector is typically segmented by industry type. Because the industrial sector is 

complex, the study isolated the largest industries for analysis and combined the remaining 

industries into a single category. The two major industries in New Mexico are Oil and Gas 

Extraction and Electronics Manufacturing, accounting for 44% and 13% respectively of total 

electricity sales in the industrial sector in 2009. The remaining industries were combined into the 

“Other Industrial” category. In addition to segmentation by industry, we identified the set of end 

uses and technologies that are appropriate for New Mexico. Because these vary by industry, they 

are shown in Chapter 5. 

With the segmentation scheme defined, the next step was to perform a high-level market 

characterization of electricity sales in the base year for each customer segment. We used various 

data sources to identify the annual sales and number of customers in each customer segment. 

This information provided control totals (customer counts and energy use totals) for calibrating 

the LoadMAP model to known data for the base-year. 
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Table 2-3 Commercial End Uses and Technologies 

End Use Technology

Cooling Air‐Cooled Chiller

Cooling Water‐Cooled Chiller

Cooling Evaporative AC

Cooling RTU

Cooling PTAC

Combined Heating/Cooling Heat Pump

Combined Heating/Cooling PTHP

Space Heating Electric Resistance

Space 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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2.1.2.2 Market Profiles 

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

technology. For residential, we also developed residential market profiles for each utility. A 

market profile includes the following elements: 

• Market size represents 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. 

• Saturations define the fraction of buildings with the electric technologies. (e.g., homes 

with electric space heating, commercial floor space with space cooling). 

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

of electricity consumed in 2009 by a specific technology in buildings that have the 

technology. For the residential sector, we use UECs expressed in kWh/household and for 

the commercial sector, EUIs expressed in kWh/square foot. 

• Intensity for the residential sector represents the average use for the technology across 

all homes in 2009. It is computed as the product of the saturation and the UEC and is 

defined as kWh/household. For the commercial sector, intensity, computed as the 

product of the saturation and the EUI, represents the average use for the technology 

across all floor space in 2009. 

• Usage is the annual electricity use by a technology/end use in the segment. It is the 

product of the market size and intensity and is quantified in GWh. 

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

2.1.3 Baseline Forecast 

The next step was to develop the baseline forecast of annual electricity use and peak demand by 

customer segment and end use under a “business as usual” (without new utility programs) 

scenario for the fourteen-year planning horizon starting in 2012. This process is crucial as it 

allows projections to be determined in the absence of future EE programs. The baseline forecast 

incorporates changes in market conditions and naturally-occurring conservation. The end-use 

forecast also includes the unfolding impacts of codes and standards. Given the recent extensive 

attention to energy efficiency at the national level through Smart Grid and American 

Reinvestment and Recovery Act (ARRA) stimulus efforts and promulgated through the 

implementation of more stringent codes and standards both nationally and in New Mexico, we 

have taken steps in our modeling framework to capture the effects of market influences in our 

baseline forecast assessments. This is an important issue for this study, as the adoption of future 

codes and standards will have a direct bearing on how much utility program EE potential there 

can be over and above the effects of those efforts. 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., new construction forecasts) 

• Electricity price forecasts 

• Trends in fuel shares and equipment saturations 

• Existing and approved changes to building codes and standards6

 

• The (future) effects of utility programs offered prior to 2012 

 

6

 At the time of the analysis, the 2009 New Mexico Building Code was in effect. 
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• Utilities’ internally developed forecasts for electricity sales 

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

2.1.4 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, Global 

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

lifetimes. We used this information, along with the avoided costs, in the economic screen to 

determine economically feasible measures. Figure 2-3 outlines the framework for measure 

analysis. 

Figure 2-3 Approach for Measure Assessment 

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, determining 

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

performing cost-effectiveness screening. Potential measures include the replacement of a unit 

that has failed or is at the end of its useful life with an efficient unit, retrofit/early replacement of 

equipment, improvements to the building envelope, the application of controls to optimize 

energy use, and other actions resulting in improved energy efficiency. 

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

a variety of secondary sources. This universal list of EE measures covers all major types of enduse 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 can be categorized into types, equipment measures and non-equipment 

measures according to the LoadMAP taxonomy: 
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• Equipment measures, or efficient energy-consuming equipment, save energy by providing 

the same service with a lower energy requirement. An example is the replacement of a 

standard efficiency refrigerator with an ENERGY STAR model. For equipment measures, many 

efficiency levels are available for a specific technology that range 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 federal 

standard SEER 13 unit and spans a broad spectrum of efficiency, with the highest efficiency 

level represented by a ductless mini-split system with variable refrigerant flow (at SEER 

levels of 18 or greater). 

• 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 the 

air conditioner only when people are home. Non-equipment measures fall into one of the 

following categories: 

• Building shell (windows, insulation, roofing material) 

• Equipment controls (thermostat, occupancy sensors) 

• Equipment maintenance (cleaning filters, changing setpoints) 

• Whole-building design (natural ventilation, 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 

Non-equipment measures can apply to more than one end use. For example, insulation levels will 

affect the energy use of cooling and space heating. 

We developed a preliminary list of EE measures and circulated it among the stakeholders. The 

final list included in the study, which reflects feedback from the stakeholders, is presented in 

Chapter 5. 

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

characteristics. For each measure we 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 potential. 

2.1.4.1 Representative Measure Data Inputs 

To provide an example of the measure data, Table 2-4 and Table 2-5 present samples of the 

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

of residential central air conditioning (CAC) in single-family homes. Table 2-4 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. 
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Table 2-4 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 $ 3,794 1,490 2009 2014

SEER 14 (ENERGY STAR) 15 $4,072 1,367 2009 2020

SEER 15 (CEE Tier 2) 15 $4,350 1,317 2009 2020

SEER 16 (CEE Tier 3) 15 $4,628 1,275 2009 2020

Ductless Mini‐split System 15 $8,193 1,118 2009 2020

Table 2-5 lists some of the non-equipment measures affecting an existing single-family home 

with CAC. These measures are also evaluated for cost effectiveness based on the lifetime 

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

model and depend on the base year saturation of the measure, the applicability and feasibility7

 of 

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

Table 2-5 Sample Non-Equipment Measures – Single Family Home, Existing 

End Use Measure

Satura‐

tion in

20098

Applicability

/Feasibility

Lifetime

(years)

Measure

Installed

Cost

Energy

Savings

(%)

Demand

Savings

(%)

Cooling Central AC — Early

Replacement 0% 8% 15 $2,895 10.0% 10.0%

Cooling

Central AC —

Maintenance and

Tune‐Up

41% 100% 4 $125 10.0% 10.0%

Cooling Ceiling Fan   52% 75% 15 $160 11.0% 2.8%

Cooling Whole‐House Fan 7% 19% 18 $200 9.0% 2.3%

Cooling Insulation —  Ducting 15% 75% 18 $500 3.0% 3.0%

Cooling Repair and Sealing —

Ducting 12% 50% 18 $5,003 10.0% 10.0%

Cooling Insulation — Ceiling 46% 90% 12 $2,663 3.0% 3.0%

Cooling Windows —

Reflective Film 5% 10% 15 $1,550 6.1% 1.5%

Cooling

Windows — High

Efficiency/ENERGY

STAR

5% 45% 10 $267 7.0% 5.3%

Cooling Thermostat —

Clock/Programmable 47% 90% 25 $7,500 12.0% 9.0%

Cooling Home Energy

Management System 20% 38% 20 $300 10.0% 5.0%

 

7

 The applicability and feasibility 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 without attics, and in some homes with attics, it 

may not be feasible to install an attic fan because of lack of space. 

8

 Note that saturation levels reflected for 2009 change over time as more measures are adopted. 
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2.1.4.2 Screening Measures for Cost-Effectiveness 

Only measures that are “cost-effective” are included in economic and achievable potential, 

Therefore, for each individual measure an economic screen is performed. This study uses the 

total resource cost (TRC) test that compares the lifetime benefits (both energy and peak 

demand) of each applicable measure with its installed cost that includes material, labor, and 

administration of a delivery mechanism, such as an energy efficiency program.9

 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. For economic 

screening of measures, incentives are not included because they represent a simple transfer 

from one party to another, but have no effect on the overall measure cost. 

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. 

Table 2-6 shows the results of the economic screen for CAC for selected years, as well as results 

for two interior lighting technologies. In 2010, the most cost-effective option is SEER 14, while in 

2012, due to rising energy costs, it changes to SEER 15. However, in 2015, due to federal energy 

efficiency standards, the SEER 13 unit goes off the market and SEER 14 becomes the standard 

efficiency unit. In 2015 and beyond, the economic screen selects the SEER 14 option because the 

marginal savings between the standard efficiency SEER 14 unit and the higher-efficiency options 

are not sufficient to make the higher-efficiency units economical. The table also shows how the 

economic choice for two of the lighting technology options varies over the study period. If the 

measure passes the screen (has a benefit-to-cost (B/C) ratio greater than or equal to 1.0), the 

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

Table 2-6 Economic Screen Results for Selected Residential Equipment Measures 

Technology 2010 2012 2015 2018 2020

Central AC SEER 13 SEER 13 SEER 14

(Energy Star)

SEER 14

(Energy Star)

SEER 14

(Energy Star)

Interior Lighting

Screw‐in

CFL

(45 lm/watt)

CFL

(45 lm/watt)

CFL

(45 lm/watt)

LED

(197 lm/watt)

LED

(197 lm/watt)

Interior Lighting  

Linear Fluorescent T8 T8 T8 T8 Super T8

 

9

 Note that the TRC test is typically the industry standard for evaluating measure-level cost-effectiveness, but other test perspectives 

may sometimes be considered in energy efficiency potential studies. The Participant test measures the benefits and costs from the 

perspective of program participants as a whole. The Ratepayer Impact Measure (RIM) test measures the difference between the 

change in total revenues paid to a utility and the change in total costs to a utility resulting from the energy efficiency and demand 

response programs. The Utility Cost (UC) test measures the costs and benefits from the perspective of the utility administering the 

program. Neither the RIM nor UC tests are typically applied in the context of measure-level economic screens, but rather in the 

broader context of energy efficiency programs and initiatives put into place to deliver the energy efficiency measures. 
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2.1.5 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).10 The NAPEE Guide represents the most credible and comprehensive industry 

practice for specifying energy-efficiency potential. Specifically, four types of potentials were 

developed as part of this study: 

• Technical potential is a theoretical construct that assumes the highest efficiency 

measures that are technically feasible to install are adopted by customers, regardless of 

cost or customer preferences. Thus, determining the technical potential is relatively 

straightforward. LoadMAP “chooses” the most efficient equipment options for each 

technology at the time of equipment replacement. In addition, it installs all relevant nonequipment measures for each technology to calculate savings. 

For example, for residential central air conditioning (CAC), as shown in Table 2-4, the 

most efficient option is a ductless mini-split system. The multiple non-equipment 

measures shown in Table 2-5 are then applied to the energy used by the ductless minisplit system to further reduce CAC energy use. LoadMAP applies the savings due to the 

non-equipment measures one-by-one to avoid double counting of savings. The measures 

are evaluated in order of their B/C ratio, with the measure with the highest B/C ratio 

applied first. Each time a measure is applied, the baseline energy use for the end use is 

reduced and the percentage savings for the next measure is applied to the revised 

(lower) usage. 

• Economic potential results from the purchase of the most efficient cost-effective

option available for a given equipment or non-equipment measure as determined in the 

cost-effectiveness screening process described above. As with technical potential, 

economic potential is a phased-in approach. Economic potential is still a hypothetical 

upper-boundary of savings potential as it represents only measures that are economic 

but does not yet consider customer acceptance and other factors. 

• Achievable potential defines the range of savings that is very likely to occur.

o Achievable – High reflects high awareness of efficiency options, minimal 

barriers to customer adoption, best-practices program design, and incentives 

that represent a substantial portion of the incremental cost combined with 

high administrative and marketing costs. 

o Achievable - Low reflects lower awareness of energy efficiency options, 

lower incentive levels and lower administrative and market costs. 

The calculation of technical and economic potential is straightforward as described above. To 

develop estimates for achievable potential, we specify adoption rates for each measure that 

reflect the combination of market acceptance rates (MARs) and program implementation factors 

(PIFs). We base the expected adoption rates on the recent experience at New Mexican utilities 

and the range of achievable potential from the survey experts as follows: 

• The savings estimates for 2012 were aligned with reported utility savings for measures 

from the study that corresponded to utility programs. 

• The range of first-year savings from the survey of experts was used to define the range 

of achievable potential in 2012. The MARs were defined such that the high end of the 

range of achievable was reached. The PIFs were defined such that the low end of the 

range of achievable was reached. 

 

10 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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• The range of savings in 10 years from the survey of experts was used to define the 

range of achievable potential in 2021. MARs and PIFs in ten years were defined so as to 

achieve the range from the survey. In some cases, the “high” estimate approached or 

exceeded the percent of savings represented by economic potential. In these cases, the 

Achievable – High savings were capped at a maximum of 75% of economic potential. 

2.1.5.1 Scenario Analysis 

In addition to developing a reference set of potential estimates, two alternative scenarios were 

also developed: 

• 75% avoided costs – the avoided costs from the reference case were scaled down by 

25% to create this scenario 

• 150% avoided costs – the avoided costs from the reference case were scaled up by 50% 

to create this scenario 

Using these alternate avoided cost forecasts, the economic and achievable potentials were re 

estimated. 

Results of all the potentials analysis are presented in Chapter 6. 

2.1.6 Strategy Recommendations 

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

and developed a set of recommendations for strategies for achieving the highest level of energy 

efficiency. The results of this review are presented in Chapter 7. 

2.2 DATA DEVELOPMENT 

This section begins with a description of the data sources used in this study, followed by a 

discussion of how these sources were applied. 

2.2.1 Data Sources 

The data sources are organized into the following categories: 

• Utility-provided data 

• Statewide customer surveys 

• Global Energy Partners’ databases and analysis tools 

• Energy-efficiency measure data 

• Other secondary data and reports 

2.2.1.1 Utility-provided Data 

In order to appropriately characterize the market in New Mexico, we asked each utility to provide 

the following: 

• Utility 2009 billing data — customers, usage, revenue 

• Peak demand by rate class 

• Number of customers and electricity sales by segment (housing type, building type, 

SIC/NAICS) 

• Energy and peak demand forecasts, at the sector level 

• Customer growth forecast 

• Price history and forecast 

• Recent saturation surveys for residential and/or business customers (see Table 2-7) 
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• Surveys on customer attitudes towards energy efficiency or demand response programs 

• System load shapes (at the class- or end-use level if available) 

• Recent load research studies 

• Avoided costs (peak capacity and energy) 

• Discount rate 

• Escalation rate 

• Line loss factors 

• Status of Automated Metering Infrastructure (AMI) 

• Program data 

o Description of existing energy efficiency programs 

o Description of existing demand-response programs 

o Recent program evaluation reports 

o Recent energy efficiency potential studies 

• Recent potential studies — PNM and Tri-State Rural Electric Cooperative 

Table 2-7 Utility Saturation Surveys 

Sector Utility Description

Residential PNM 2,903 responses; conducted Spring 2006

Residential SPS 419 responses; conducted May 2010

Residential El Paso   2,930 responses; conducted 2010–2011 (LivingWise Program Summary

Report)  

Residential Tri‐

State Conducted 2007  

Commercial PNM Small commercial: 2,321 responses; conducted Spring 2006

Large commercial: 601 responses; conducted Spring 2006

Commercial SPS 460 responses; conducted in 2008 (covers entire SPS service territory,

including Texas)

2.2.1.2 Statewide Customer Surveys 

The recently-completed utility surveys were supplemented with two statewide surveys of 

residential and C&I customers. The statewide surveys focused on the key data elements 

necessary for estimating potential and developing strategy. These include: 

• Appliance and end-use saturation and inventories by fuel 

• Saturation of energy-efficiency measures and demand response technologies 

• Customer behavior and likely participation in EE and DR programs 

• Barriers to engaging in EE and DR programs and activities 

For the residential sector, 1,102 households from throughout the state responded to the survey. 

Global used a simple random sample for the residential sector, but quotas by housing type and 

utility service area (the three IOUs and the rest of the state as a group) were monitored. The 

results were weighted to be representative of the state based on the utility service territory and 

housing type. The survey was conducted online through e-Rewards, as well as through telephone 

surveys through Resolution Research and Marketing. The online survey yielded 806 responses 
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and 296 surveys were conducted by telephone. Telephone surveys were included to reduce bias 

associated with lack of access to a computer, an issue for low-income and elderly customers. 

For the C&I sector, a simple random sample was used, but quotas based on the type and size of 

businesses from ZapData, as well as utility service area, were monitored. The survey was 

conducted online through e-Rewards, as well as through telephone surveys through Resolution 

Research and Marketing. The online survey yielded 420 responses and 319 surveys were 

conducted by telephone. Originally our goal was to reach 1,000 businesses, but the response 

rates in New Mexico through online and telephone surveys were lower than average. To develop 

population estimates, the sample was post stratified by building type and size to develop 

appropriate expansion weights. 

2.2.1.3 Global Energy Partners Databases, Analysis Tools, and Reports 

Global maintains several databases and modeling tools that we use for forecasting and potential 

studies. 

• Energy Market Profiles Database. Since the late 1990s, Global staff has maintained a 

database of end-use profiles by sector, customer segment and region for electricity and 

natural gas. The database contains market size, fuel shares/saturations, UECs/EUIs, 

intensities, and total sales. 

• Building Energy Simulation Tool (BEST). 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. 

• Database of Energy Efficiency Measures (DEEM). Global maintains a database of 

energy efficiency measures for residential, commercial, and industrial segments across 

the U.S. This is analogous to the DEER database developed for California. Global updates 

the database on a regular basis as it conducts new energy efficiency potential studies. 

• EnergyShapeTM Database. This database contains end-use load shapes for residential 

and commercial segments for nine regions in the U.S. For the non-HVAC end uses, we 

used the EnergyShape data to develop the peak factors that represent the fraction of 

annual energy use that occurs during the peak hour. The peak factors were calibrated to 

available utility data for the system peak. The final peak factors were applied to annual 

energy savings to calculate the peak-demand savings from EE measures. 

• Recent Studies. Global 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, and Avista Utilities. In addition, we used the 

information about impacts of building codes and appliance standards from a recent 

report for the Institute for Energy Efficiency. 

2.2.1.4 Energy Efficiency Measure Data 

In addition to BEST and DEEM (described above), several other sources of data were used to 

characterize the energy-efficiency measures. 

• 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. 

• Cost data sources
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o RS Means Facilities Maintenance and Repair Cost Data 

o RS Means Mechanical Construction Costs 

o RS Means Building Construction Cost Data 

o Sixth Northwest Conservation and Electric Power Plan (2010) 

o USGBC — LEED New Construction & Major Renovation (2008) 

o RS Means Green Buildings Project Planning & Cost Estimating Second Edition 

(2008) 

o Grainger Catalog Volume 398, (2007-2008) 

o Navigant Study 

2.2.1.5 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. 

• U.S. Census Data: 

o The American Community Survey (ACS) is an ongoing survey that provides data 

every year on household characteristics. http://www.census.gov/acs/www/ 

o Census Bureau’s Economic Census, which is conducted every five years, collects 

details on business characteristics. We used the 2007 version. 

http://www.census.gov/econ/census07/ 

o The Census Bureau also provides a mapping of SIC to NAICS codes. 

http://www.census.gov/eos/www/naics/ 

• Dun and Bradstreet. Dun and Bradstreet (D&B) maintains a large database of business 

characteristics that is continually updated. For our analysis we used D&B’s ZapData 

program to gather information on the types, size, and numbers of commercial and 

industrial customers within New Mexico. http://www.dnb.com/

• 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. 

• 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, Global conducted an assessment of the 

national potential for energy efficiency, with estimates derived for the four DOE regions 

(including the West region that includes New Mexico). 

• 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. 
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2-18 www.gepllc.com 

2.2.2 Data Application 

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

2.2.2.1 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 data from each of the utilities, 

the Annual Energy Outlook, American Community Survey, and Dun and Bradstreet: 

• Historical customer billing data by sector (e.g., residential, commercial, industrial) 

• Summary of residential customers by housing type 

• Summary of non-residential customers by rate class and size 

• Listing of all non-residential customers including annual energy, SIC/NAICS (where 

available), and customer type 

To segment the residential customers into the four segments, we determined the housing type 

breakdown based on the American Community Survey and applied it to the number of customers 

reported by the billing data for 2009. The 2009 ACS shows that 35% of households in New 

Mexico earned less than $30,000 in 2009. We must reduce the number of households in the 

other segments that are based on home type. Based on the market research conducted for this 

study, we determined that the home type of low-income households in New Mexico breaks down 

into the following: 

• 64% single family homes 

• 19% multi-family homes 

• 17% mobile homes 

These low-income homes were then subtracted from the other home type segments to give the 

number of customers by segment. 

2.2.2.2 Data Application for Market Profiles 

To develop the market profiles for each segment, we used the following general approach: 

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

annual electricity use, and annual intensity. 

2. Used the primary market research on residential customers to incorporate information on 

existing appliance and equipment saturations, appliance and equipment characteristics, 

building characteristics, customer behavior, operating characteristics, and energyefficiency actions already taken. These were compared with and supplemented by the 

utility saturation surveys, and then adjusted, if needed. 

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, Energy Market Profiles, and other regional sources. 

5. Ensured calibration to control totals for annual electricity sales in each segment. 

6. Worked with the IOU staff and the extended project team to vet the data against their 

knowledge and experience. 

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

shown in Table 2-8. 
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Table 2-8 Data Applied for the Market Profiles 

Model Inputs Description Key Sources

Market size   Base‐year residential dwellings and

C&I floor space

• Utility billing data  

• American Community Survey  

• D&B data  

• Statewide Surveys  

• Energy Market Profiles

Annual intensity

Residential: Annual energy use

(kWh/household)

C&I: Annual energy use (kWh/sq ft)

• Utility data

• Energy Market Profiles  

• Previous studies

Appliance/equipment

saturations

Fraction of dwellings with an

appliance/technology

Percentage of C&I floor space with

equipment/technology

• Statewide survey data  

• Utility saturation surveys  

• 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 for a technology in floor space

that has the technology

• HVAC uses: BEST simulations using

prototypes developed for NM  

• Non HVAC uses: Engineering

analysis

• Energy Market Profiles

• California RASS and CEUS

• Results from previous studies

Appliance/equipment

vintage distribution Age distribution for each technology

• Statewide survey data

• Utility saturation surveys

• Previous 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

• Utility data  

• EnergyShape database

2.2.2.3 Data Application for Baseline Forecast 

Table 2-9 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. 
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Table 2-9 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

• IOU’s customer growth forecast

• AEO 2011 growth forecast,  

• Tri‐State Potential Study

Equipment purchase

shares for baseline

forecast

For each equipment/technology,

purchase shares for each efficiency

level; specified separately for

equipment replacement (replace‐on‐

burnout), non‐owner acquisition, and

new construction

• Shipments data  

• AEO 2011 forecast assumptions11

Appliance/efficiency standards

analysis

Electricity prices Forecast of average electricity prices

• IOU price forecasts

• AEO price forecast  

• Tri‐State Potential Study

Utilization model

parameters

Price elasticities, elasticities for other

variables (income, weather)

• EPRI’s REEPS and COMMEND

models

• IOU forecasting data  

• AEO 2011

In addition, we implemented assumptions for equipment standards, as shown in Table 2-10 and 

Table 2-11. 

 

11 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 trended forward. 
State of New Mexico EE and DR Study Analysis App

Global Energy Partners An EnerNOC Company Table 2-10 Residential Electric Equipment Standards 

Today's Efficiency or Standard Assumption 1st Standard (relative to toda

2nd Standard (relative to tod

End Use Technology 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2

Central ACRoom ACEvaporative Central AC

Evaporative Room AC

Cooling/Heating Heat PumpSpace Heating Electric Resistance

Water Heater (<=55 gallons)

Water Heater (>55 gallons)

Screw‐in/Pin Lamps

Linear Fluorescent

Refrigerator/2nd Refrigerator

FreezerDishwasherClothes WasherClothes DryerRange/OvenMicrowavePersonal ComputerMonitorLaptop Computer

TVCopier/Printer/FaxDVD/VCR/AudioDevices and GadgetsPool PumpWell PumpFurnace Fan

ConventionalConventional

5% more efficient (EF 3.17)

ConventionalConventional

Conventional/Energy Star

ConventionalConventionalConventionalConventionalConventional

SEER 14

EER 11.0

ConventionalConventional

SEER 14.0/HSPF 8.0

SEER 13

EER 9.8

SEER 13.0/HSPF 7.7

Conventional (MEF 1.26 fortop loader)

Conventional (EF 3.01)

Electric Resistance

EF 0.95

Heat Pump Water Heater

Advanced Incande

T8

EF 0.90EF 0.90

Incandescent Advanced Incandescent ‐ tier 1

Miscellaneous

MEF 1.72 for top loader

Cooling

Water Heating

Lighting

Appliances

Electronics

25% more efficient25% more efficient

14% more efficient (307 kWh/yr)

MEF 2.0 fortop loader

Conventional/Energy Star

Conventional/Energy Star

NAECA StandardNAECA Standard

Conventional (355 kWh/yr)
Analysis Approach and Data Development State of 

2-22 Table 2-11 Commercial Electric Equipment Standards 

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

2nd Standard (relative to today'sst

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

ChillersRoof Top UnitsPackaged Terminal AC/HP EER 9.8

Cooling/Heating Heat Pump

Electric ResistanceElectric Furnace

Ventilation Ventilation

Screw‐in/Pin Lamps

Linear Fluorescent T12High 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

IcemakerDesktop ComputerLaptop Computer

Non‐HVAC MotorsCommercial 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 StarConventional/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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2.2.2.4 Energy Efficiency Measure Data Application 

Table 2-12 details the data sources used for measure characterization. 

Table 2-12 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

• EPRI National Study

• DEEM

• DEER

• Other secondary sources

Peak Demand Impacts

Savings during the peak demand periods

are specified for each 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 per‐unit or per‐square‐

foot basis for the residential and C&I

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

• 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

• Other secondary sources

Applicability

Estimate of the percentage of either

dwellings in the residential sector or

square feet in the C&I sectors where the

measures is applicable and where it is

technically feasible to implement

• DEEM

• DEER

• 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

• Appliance, building codes, and

standards analysis

2.2.2.5 Data Application for Cost-effectiveness Screening 

To perform the cost-effectiveness screening, the following information was needed: 

• Avoided cost of energy and avoided cost of capacity. Each IOU provided its own forecasts 

of avoided energy and capacity costs. The statewide average is shown in Table 2-13. 

• Line losses 

• Program administration costs. Program administration costs can typically vary between 

10–20% of total program costs. For this study, we used a value of 15%. 
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Table 2-13 Avoided Cost Forecasts — State-Level Average 

Electricity 2009 2012 2015 2020 2025 % Change

2009‐2025

Avoided Cost of Energy ($/MWh) $39.46 $44.52 $53.27 $61.33 $72.44 84%

Avoided Cost of Capacity ($/kW‐yr) $182.17 $185.14 $188.27 $193.82 $199.80 10%

Natural Gas 2009 2012 2015 2020 2025 % Change

2009‐2025

Avoided Cost of Energy

($/MMTherm) $707.00 $890.00 $880.00 $950.00 $920.00 30%

2.2.2.6 Potentials Estimation 

To estimate potentials, three sets of parameters were required. 

• Adoption rates for non-equipment measures. Rather than installing all nonequipment measures in the first year of the forecast (instantaneous potential), they are 

phased in according to four adoption schedules that vary based on equipment cost and 

measure complexity. The adoption rates that are developed are based on expert opinion 

and engineering review of how quickly the market could 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. These 

adoption rates are used within LoadMAP to generate the technical and economic 

potentials. 

• Market acceptance rates. These factors are applied to Economic potential to estimate 

Achievable – High potential. These rates were developed using information from the EPRI 

National Potential Study, the Northwest Power and Conservation Council ramp rates, and 

previous potential studies. They were adjusted to align with the upper end of the range 

of potential from the survey of experts. 

• Program implementation factors. These factors are applied to Achievable – High 

potential to calculate Achievable – Low potential. These rates were developed using 

information from the EPRI National Potential Study and previous potential studies. They 

were adjusted to align with the lower end of the range of potential from the survey of 

experts. 

MARs and PIFs are presented in Volume 6. 
Global Energy Partners 3-1 

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CHAPTER 3 

MARKET ASSESSMENT AND MARKET PROFILES 

New Mexico is a widely diverse state. It has a population of just over two million people, but 

spread over 121,000 square miles, making New Mexico the sixth-most sparsely populated state. 

The state is heavily influenced by its years under Spanish rule, as well as the large population of 

Native Americans. New Mexico has the highest percentage of Hispanics and third-highest 

percentage of Native Americans among U.S. states. New Mexico shares a border with Texas, 

Arizona, Colorado, Utah, and Oklahoma, as well as the Mexican states of Chihuahua and Sonora. 

New Mexico is known for its arid climate, but the landscape includes deserts, mesas, high plains 

and snow-covered mountains. The largest city in the state is Albuquerque, where almost onethird of the population currently lives. Las Cruces, located in the agriculture center of the state, 

is the second largest city. Santa Fe, at 7,199 ft, is the highest state capital in the United States. 

The top industries in the state are oil and gas production, tourism, and Federal government. New 

Mexico is the third-leading crude oil and natural gas producer in the U.S. 

Total electricity use for the residential, commercial and industrial sectors in New Mexico in 2009 

was 20,902 GWh. As shown in Figure 3-1, the largest sector is commercial, accounting for 38%, 

or almost 8,000 GWh. The remaining use is split equally between the residential and industrial 

sectors. 

Figure 3-1 Sector-Level Electricity Use, 2009 

Residential,  6,474 ,

31%

Commmercial,  7,898 ,

38%

Industrial,  6,530 , 31%

2009 Electricity Use

20,902 GWh

Electricity providers consist of investor-owned utilities (IOUs), municipalities, rural electric coops 

and the Navajo Tribal Utility Authority, as shown in Table 3-1. The IOUs account for 71% of total 

customers and 66% of total electricity use in the state. 
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Table 3-1 Electricity Use by Entity, 2009 

Utility Type Utility Name Total Number of Customers Total 2009 MWh Sales

IOU PNM 500,391 8,513,669

IOU El Paso 86,469 1,116,861

IOU SPS/Xcel 105,536 4,183,546

Municipal Aztec City of 3,278 43,199

Cooperative Central New Mexico El Coop, Inc 17,491 247,848

Cooperative Central Valley Elec Coop, Inc 12,732 706,597

Cooperative Columbus Electric Coop, Inc 4,661 78,384

Cooperative Continental Divide El Coop Inc 23,518 431,307

Cooperative Duncan Valley Elec Coop, Inc 329 3,913

Cooperative Farmers' Electric Coop, Inc 12,627 375,931

Municipal City of Farmington 43,891 1,159,530

Municipal City of Gallup 10,418 226,461

Cooperative Jemez Mountains Elec Coop, Inc 30,983 348,036

Cooperative Kit Carson Electric Coop, Inc 28,123 303,035

Cooperative Lea County Electric Coop, Inc 10,890 749,347

Municipal Los Alamos County 8,794 547,113

Cooperative Mora‐San Miguel Elec Coop, Inc 10,693 68,385

Tribal Navajo Tribal Utility Authority 8,554 127,700

Cooperative Navopache Electric Coop, Inc 1,586 10,674

Cooperative Northern Rio Arriba E Coop Inc 4,289 44,416

Cooperative Otero County Electric Coop Inc 18,072 182,946

Municipal Raton Public Service Company 4,301 50,280

Cooperative Rio Grande Electric Coop, Inc 302 2,298

Cooperative Socorro Electric Coop, Inc 13,196 178,206

Cooperative Southwestern Electric Coop Inc 2,202 458,702

Cooperative Springer Electric Coop, Inc 3,017 267,860

Municipal Springer Town of 577 4,669

Cooperative Tri‐County Electric Coop, Inc 5 18

Municipal City of Truth or Consequences 4,147 43,460

Cooperative Roosevelt County Elec Coop Inc 6,301 189,997

Cooperative Sierra Electric Coop, Inc 4,090 35,243

Federal Western Area Power Administration 29 201,949

State Total 981,492 20,901,581
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3.1 RESIDENTIAL SECTOR 

This section characterizes the residential market at a high level, and then provides a profile of 

how customers in each segment use electricity by end use. 

Total residential electricity use in 2009 was 6,474 GWh. Some of the IOUs provided the 

residential energy intensity (kWh/household) by segment. For the utilities that did not have the 

segment-level intensities, we applied the ratio from the other utilities to develop segment-level 

intensities. Multiplying the segment intensity by the number of customers results in segmentlevel totals for 2009 electricity use. 

Customer information for each segment is shown in Table 3-2 and Figure 3-2.The single-family 

segment used almost half the total residential sector electricity in 2009 as a result of the largest 

number of customers and the highest intensity. The low-income segment is second highest. 

Table 3-2 Residential Sector Electricity Usage and Intensity by Segment Type 

Segment Intensity   

(kWh/Household) Customers GWh(2009)

% of Total

Usage

Single‐ Family 8,502 356,935 3,035 47%

Multi ‐Family 5,405 104,434 564 9%

Mobile home 7,030 82,917 583 9%

Low Income 7,675 298,591 2,292 35%

Total 7,680 842,876 6,474 100%

Figure 3-2 Residential Electricity Use by Customer Segment, 2009 

Single

Family

47%

Multi

Family

9%

Mobile

Home

9%

LowIncome

35%

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 3-3. The residential market profiles for each housing segment are presented 

in Volume 6. 
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Table 3-3 Market Profile for the Residential Sector 

UEC Intensity Usage

(kWh) (kWh/HH) (GWh)

Cooling Central AC 34.4% 2,014                                693                   584

Cooling Room AC 7.9% 1,153                                   91                     77

Cooling Evaporative Central AC 35.0% 664                                    232                   196

Cooling Evaporative Room AC 5.2% 357                                       19                     16

Combined Heating/Cooling Central Heat Pump 3.0% 4,108                                124                   105

Space Heating Electric Resistance 17.9% 2,971                                531                   448

Water Heating Water Heater 19.0% 2,887                                548                   462

Interior Lighting Screw‐in 100.0% 861                                    861                   725

Interior Lighting Linear Fluorescent 100.0% 81                                         81                     68

Exterior Lighting Screw‐in 100.0% 213                                    213                   179

Appliances Clothes Washer 90.2% 103                                       93                     78

Appliances Clothes Dryer 71.7% 762                                    546                   460

Appliances Dishwasher 71.8% 113                                       81                     68

Appliances Refrigerator 100.0% 892                                    892                   752

Appliances Freezer 37.9% 1,071                                405                   342

Appliances Second Refrigerator 19.3% 1,381                                266                   224

Appliances Stove 44.2% 333                                    147                   124

Appliances Microwave 96.7% 122                                    118                   100

Electronics Personal Computers 87.5% 262                                    230                   193

Electronics Monitor 77.2% 52                                         40                     34

Electronics Laptops 104.3% 113                                    118                     99

Electronics TVs 241.9% 157                                    379                   319

Electronics Copier/Printer/Fax 96.9% 40                                         39                     33

Electronics DVD/VCR/Audio 248.5% 107                                    266                   224

Electronics Devices and Gadgets 100.0% 47                                         47                     39

Miscellaneous Pool Pump 2.8% 2,112                                   59                     50

Miscellaneous Well Pump 14.6% 515                                       75                     63

Miscellaneous Furnace Fan 67.9% 368                                    250                   211

Miscellaneous Miscellaneous 100.0% 236                                    236                   199

Total                7,680               6,474

End Use Technology Saturation

Average Market Profiles

Figure 3-3 presents the end-use breakout for the residential sector as a whole. Appliances 

account for one-third of the usage, followed by lighting and electronics. The electronics end use, 

which includes personal computers, TVs, home audio, etc., also contributes significantly to 

household electricity usage. The miscellaneous end use includes such devices as furnace fans, 

pool pumps, and other “plug” loads (hair dryers, power tools, coffee makers, etc.). Additional 

electricity consumption is allocated among cooling, space heating, miscellaneous and water 

heating. 
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Figure 3-3 Residential Electricity Use by End Use, 2009 

Cooling

13%

Space Heating

7% Heating/

Cooling

0%

WaterHeating

7%

Appliances

33%

Interior

Lighting

12%

Exterior

Lighting

3%

Electronics

15%

Miscellaneous

8%

Figure 3-4 presents the end-use shares of total electricity use for each housing type. Most end 

uses have a fairly constant share across segments. However, the relative use for miscellaneous is 

lower for the multi-family and low-income segments than for single family homes, while the 

share for appliances is lower in single family homes relative to other uses. 

Figure 3-4 End-Use Shares of Total Electricity Use by Housing Type, 2009 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Single Family Multi Family Mobile

Home

Low Income

Cooling

Space Heating

Combined

Heating/Cooling

WaterHeating

Appliances

Interior Lighting

Exterior Lighting

Electronics

Miscellaneous
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3.2 COMMERCIAL SECTOR 

Total electricity use in the commercial sector in 2009 was 7,989 GWh. Using statewide survey 

data and secondary sources, total commercial floor space is estimated at 551 million square feet, 

implying an average intensity of 14.3 kWh per square foot per year. 

Table 3-4 presents the annual electricity use, floor space and intensity estimates for each 

building type. The largest segment is large offices, with 142 million square feet and the largest 

amount of electricity usage with over 3,000 GWh. As expected, restaurants and groceries have 

the highest intensity due to the large amount of cooking and refrigeration. Warehouses, schools 

and the miscellaneous segment have the lowest intensities. 

Table 3-4 Commercial Sector Market Characterization Results, 2009 

Segment Annual Use  

(GWh)

Floor Space  

(million sq. ft.)

Intensity

(kWh/sq.ft.)

Small Office 556.9 40.3 13.8

Large Office 1,037.8 59.4 17.5

Restaurant 663.7 14.8 44.9

Retail 1,079.7 77.7 13.9

Grocery 804.2 18.2 44.2

Warehouse 537.0 74.6 7.2

School 478.0 61.5 7.8

College 351.0 28.6 12.3

Health 740.3 32.9 22.5

Lodging 414.0 23.8 17.4

Miscellaneous 1,235.0 119.0 10.4

Total 7,897.6 550.8 14.3

Table 3-5 shows the market profile for the commercial sector as a whole, representing a 

composite of the eleven building types. Overall, about 75% of commercial floor space is cooled. 

There is some evaporative cooling in the commercial sector, but a much smaller share than in 

the residential sector. About 22% of commercial floor space is heated using electric equipment, 

either some form of resistance heating or heat pumps. Linear fluorescent lighting is the largest 

single energy-consuming technology in the commercial sector, followed by screw-in lamps and 

ventilation equipment. 

Market profiles for each building type are presented in Volume 6. 
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Table 3-5 Commercial Sector Composite Market Profile, 2009 

EUI Intensity Usage

(kWh) (kWh/Sqft) (GWh)

Cooling Air‐Cooled Chiller 10.0% 4.38                                  0.44               242

Cooling Water‐Cooled Chiller 17.9% 2.57                                  0.46               253

Cooling Evaporative AC 9.1% 1.06                                  0.10                 53

Cooling RTU 27.3% 3.43                                  0.93               514

Cooling PTAC 2.1% 3.09                                  0.06                 36

Combined Heating/Cooling Heat Pump 8.4% 5.66                                  0.48               262

Combined Heating/Cooling PTHP 1.5% 4.90                                  0.07                 40

Space Heating Electric Resistance 13.0% 2.04                                  0.27               146

Space Heating Electric Furnace 1.3% 3.52                                  0.05                 26

Ventilation Ventilation 75.4% 1.89                                  1.43               786

Water Heating Water Heater 35.2% 0.62                                  0.22               120

Interior Lighting Screw‐in 100.0% 1.72                                  1.72               948

Interior Lighting High‐Bay Fixtures 65.4% 0.59                                  0.39               214

Interior Lighting Linear Fluorescent 100.0% 1.86                                  1.86           1,025

Exterior Lighting Screw‐in 100.0% 0.21                                  0.21               113

Exterior Lighting HID 100.0% 0.55                                  0.55               303

Exterior Lighting Linear Fluorescent 100.0% 0.07                                  0.07                 37

Refrigeration Walk‐in Refrigerator 41.2% 1.61                                  0.66               364

Refrigeration Reach‐in Refrigerator 41.2% 0.24                                  0.10                 55

Refrigeration Glass Door Display 41.2% 1.01                                  0.42               229

Refrigeration Open Display Case 41.2% 0.45                                  0.19               103

Refrigeration Icemaker 41.2% 0.41                                  0.17                 93

Refrigeration Vending Machine 41.2% 0.51                                  0.21               115

Food Preparation Oven 15.5% 1.02                                  0.16                 87

Food Preparation Fryer 15.5% 1.45                                  0.22               123

Food Preparation Dishwasher 15.5% 0.20                                  0.03                 17

Food Preparation Hot Food Container 15.5% 0.82                                  0.13                 70

Office Equipment Desktop Computer 89.4% 0.48                                  0.43               237

Office Equipment Laptop 89.4% 0.05                                  0.04                 24

Office Equipment Server 89.4% 0.39                                  0.35               191

Office Equipment Monitor 89.4% 0.09                                  0.08                 42

Office Equipment Printer/Copier/Fax 100.0% 0.22                                  0.22               120

Office Equipment POS Terminal 36.0% 0.04                                  0.01                   8

Miscellaneous Non‐HVAC Motors 56.2% 0.27                                  0.15                 85

Miscellaneous Pool Pump 4.6% 0.96                                  0.04                 24

Miscellaneous Pool Heater 1.2% 1.09                                  0.01                   7

Miscellaneous Miscellaneous 100.0% 1.42                                  1.42               783

Total                  14.3           7,898

End Use Technology Saturation

Average Market Profiles

Figure 3-5 shows the breakdown of annual electricity usage by end use. Lighting is the largest 

single end use in the commercial sector, accounting for over one-third of total usage. Cooling is 

second, followed by commercial refrigeration, miscellaneous, and ventilation. Each of the other 

end uses accounts for less than 10% of total usage. 
Market Assessment and Market Profiles State of New Mexico EE and DR Study 

3-8 www.gepllc.com 

 Figure 3-5 Commercial Electricity Consumption by End Use, 2009 

Cooling

14%

Space Heating

2%

Combined

Heat/Cool

1%

Ventilation

10%

Water Heating

1%

Food

Preparation

4%

Refrigeration

12%

Interior

Lighting

28%

Exterior

Lighting

6%

Office

Equipment

8%

Miscellaneous

11%

Figure 3-6 illustrates how the end-use composition of electricity use varies by building type. 

Observations include the following: 

• Lighting and cooling are major end uses across all building types 

• Refrigeration has the largest share in grocery stores and restaurants 

• Office equipment has substantial use in large offices, small offices, health, and colleges 

• Miscellaneous is highest in health since this end use includes medical equipment 

• Electric space heating and water heating are small across all segments, reflecting the high 

fuel share for natural gas 
State of New Mexico EE and DR Study Market Assessment and Market Profiles 

Global Energy Partners 3-9 

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Figure 3-6 Commercial End Use Intensities by Building Type, 2009 

‐ 10.0 20.0 30.0 40.0 50.0

Miscellaneous

Lodging

Health

College

School

Warehouse

Grocery

Retail

Restaurant

Large Office

Small Office

Intensity (kWh/sq. ft.)

Miscellaneous

Office Equipment

Exterior Lighting

Interior Lighting

Refrigeration

Food Preparation

Water Heating

Ventilation

Comb Heat/Cool

Space Heating

3.3 INDUSTRIAL SECTOR 

The industrial sector accounts for almost one-third of total electricity sales. Oil and gas 

extraction and electronics manufacturing are the two largest industries throughout the state, 

accounting for 44% and 13% of total industrial sales in 2009. In order to capture the measures 

that are specific to these industries we isolated the two industries as separate segments, while 

combining the remaining industries into the “Other Industrial” category. 

In 2009, total electricity sales to the industrial sector were 6,530 GWh. Because data on floor 

space for the industrial sector is not a meaningful measure we describe and forecast electricity 

use relative to the base-year values. 

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 2009. Table 3-6 shows the 

composite market profiles for the industrial sector. 
Market Assessment and Market Profiles State of New Mexico EE and DR Study 

3-10 www.gepllc.com 

Table 3-6 Industrial Market Profile, 2009 

Usage

(GWh) % of Use

Cooling Central Chiller 96                      1.5%

Cooling RTU 90                      1.4%

Cooling PTAC 5                        0.1%

Combined Heating/Cooling Heat Pump 13                      0.2%

Space Heating Electric Resistance 80                      1.2%

Space Heating Furnace 15                      0.2%

Ventilation Ventilation 320                   4.9%

Process Process Cooling/Refrigeration 364                   5.6%

Process Process Heating 590                   9.0%

Process Electrochemical Process 261                   4.0%

Process Other Process 37                      0.6%

Interior Lighting Indoor Screw‐in 46                      0.7%

Interior Lighting HID 146                   2.2%

Interior Lighting Indoor Fluorescent 154                   2.4%

Exterior Lighting Outdoor Screw‐in 2                        0.0%

Exterior Lighting HID 26                      0.4%

Exterior Lighting Outdoor Fluorescent 1                        0.0%

Machine Drive Less than 5HP 190                   2.9%

Machine Drive 5‐24 HP 411                   6.3%

Machine Drive 25‐99 HP 1,003                15.4%

Machine Drive 100‐249 HP 569                   8.7%

Machine Drive 250‐499 HP 624                   9.6%

Machine Drive 500 or more HP 1,153                17.7%

Other Other Uses 337                   5.2%

Total               6,530 100%

End Use Technology

Average Market Profiles

Figure 3-7 presents the end-use breakout for the industrial sector in 2009. Machine drive is the 

largest overall end use for the industrial sector, accounting for 61% of energy use. This share is 

higher than what we typically observe for the industrial sector but it reflects the large share of 

electricity used for machine drives by oil and gas extraction industry. Process use accounts for 

19% of energy use. Space conditioning, including cooling, heating, and ventilation, accounts for 

20%. 
State of New Mexico EE and DR Study Market Assessment and Market Profiles 

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An EnerNOC Company 

Figure 3-7 Industrial Electricity Use by End Use, 2009 

Cooling

3%

Space Heating

2%

Combined

Heat/Cool

1% Ventilation

5%

Interior

Lighting

5%

Exterior

Lighting

0%

Machine Drive

61%

Process

19%

Other

5%

Table 3-7 and Figure 3-8 show how the major industrial segments in New Mexico used electricity 

in 2009. Machine drives account for about 80% of total electricity use in the oil and gas segment 

and they account for about half of use in other industrial. In the electronics manufacturing 

segment, energy use is distributed more evenly across the end uses. 

Table 3-7 Industrial Electricity Use (GWh) by End Use and Segment, 2009 

Oil and Gas Electronics

Manufacturing Other Industrial Total

Cooling 28 71 91 190

Space Heating 14 36 45 95

Comb Heat/Cool 2 5 6 13

Ventilation 48 120 153 320

Interior Lighting 65 93 188 345

Exterior Lighting 5 8 16 29

Machine Drive 2,290 197 1,460 3,948

Process 322 191 739 1,252

Other 14 107 216 337

Total 2,788 828 2,914 6,530
Market Assessment and Market Profiles State of New Mexico EE and DR Study 

3-12 www.gepllc.com 

Figure 3-8 Industrial Electricity Use by End Use, 2009 

0%

20%

40%

60%

80%

100%

Oil and Gas Electronics

Manufacturing

Other Industrial

%of Total AnnualElectricity Use

Cooling

Space Heating

Comb Heat/Cool

Ventilation

Interior Lighting

Exterior Lighting

Machine Drive

Process

Other
Global Energy Partners 4-1 

An EnerNOC Company 

CHAPTER 4 

BASELINE FORECAST 

Prior to developing estimates of energy-efficiency potential, a baseline end-use forecast was 

developed to quantify how electricity and natural gas is used by end use in the base year and 

what the consumption of each fuel is likely to be in the future in absence of new utility 

programs. The baseline forecast serves as the metric against which energy-efficiency potentials 

— technical, economic, and achievable — are measured. 

4.1 RESIDENTIAL SECTOR 

In general, the baseline forecast incorporates assumptions about economic growth, electricity 

prices, appliance/equipment standards and building codes already mandated, and naturallyoccurring conservation. As mentioned above, the residential analysis was performed separately 

for PNM, SPS, El Paso and the non-IOUs as a group. In this section, we present the results for 

the state as a whole. The separate forecasts are presented in Volume 6. 

Figure 4-1 presents the baseline forecast at the end-use level for the residential sector as a 

whole. Overall, residential use increases modestly, from 6,474 GWh in 2009 to 7,421 GWh in 

2025, a 14.6% increase. By comparison, the 2011 AEO forecast increases by 6.9% over the 

same time horizon. 

Table 4-1 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 standard incandescent lamps out of the market over 

a three-year period. It causes a decline in interior lighting use by 24% and exterior lighting 

use by 33% over the forecast period. The AEO 2010 forecast projects a 26% decline for both 

types of lighting over the same period. 

2. Cooling stays relatively flat reflecting the appliance standards that are offset partially by 

higher saturations of central AC in new construction relative to evaporative cooling, and a 

reduction in room AC over the forecast period. 

3. There is some growth in space heating and combined heating and cooling that reflects higher 

saturations of electric heating in new construction as builders move away from propane, 

particularly in rural areas. 

4. Water heating grows modestly as a result of higher electric saturations in new construction. 

5. Appliances increase slightly, reflecting the small increases in saturations of dishwashers, 

clothes washers and clothes dryers which offsets the efficiency gains, particularly in 

refrigeration appliances, due to standards. 

6. Growth in electricity use in electronics is modest and reflects an increase in the saturation of 

electronics and the trend toward higher-powered computers, but is tempered by the higher 

efficiency of televisions. 

7. 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. 
Baseline Forecast State of New Mexico EE and DR Study 

4-2 www.gepllc.com 

Figure 4-1 Residential Baseline Forecast by End Use 

‐

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

2009 2012 2015 2020 2025

Annual Use (GWh)

Cooling

Space Heating

Heat/Cool

WaterHeating

Appliances

Interior Lighting

Exterior Lighting

Electronics

Miscellaneous
State of New Mexico EE and DR Study Baseline Forecast 

Global Energy Partners 4-3 

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Table 4-1 Residential Baseline Electricity Forecast by End Use and Technology (GWh) 

End Use Technology 2009 2012 2015 2020 2025 %

Change

Cooling

Central AC 584 577 595 632 707 20.9%

Evaporative Central AC 196 174 166 166 175  ‐10.4%

Room AC 77 71 67 61 59  ‐23.9%

Evaporative Room AC 16 14 14 13 13  ‐19.6%

Space Heating Electric Resistance 448 463 494 549 600 34.1%

Comb. Heat/Cool Central Heat Pump 105 120 145 196 260 147.8%

Water Heating Water Heater 462 480 520 582 645 39.8%

Appliances

Refrigerator 752 641 586 539 544  ‐27.7%

Second Refrigerator 224 175 167 162 171  ‐23.9%

Freezer 342 357 371 386 394 15.2%

Clothes Washer 78 73 72 69 67  ‐14.3%

Clothes Dryer 460 485 529 597 670 45.5%

Dishwasher 68 70 74 83 96 40.3%

Stove 124 130 140 159 178 43.6%

Microwave 100 103 111 126 140 40.7%

Interior Lighting Screw‐in 725 891 604 652 487  ‐32.9%

Linear Fluorescent 68 75 84 101 119 74.6%

Exterior Lighting Screw‐in 179 199 146 159 119  ‐33.5%

Electronics

TVs 319 331 345 331 308  ‐3.7%

Personal Computers 193 196 200 212 232 19.8%

Laptops 99 101 103 112 123 24.0%

Monitor 34 35 38 43 48 40.2%

Copier/Printer/Fax 33 31 29 31 35 7.7%

DVD/VCR/Audio 224 251 285 329 399 77.8%

Devices and Gadgets 39 41 44 49 54 36.5%

Miscellaneous

Furnace Fan 211 225 246 282 313 48.7%

Pool Pump 50 54 61 72 84 70.0%

Well Pump 63 68 75 88 101 58.5%

Miscellaneous 199 213 229 255 282 41.8%

Total 6,474 6,646 6,539 7,035 7,421 14.6%

Figure 4-2 presents the forecast of use per household. Most noticeable is that lighting use 

decreases significantly after 2012, as the lighting standard from EISA comes into effect and as 

LED lamps begin to gain traction in the later years of the forecast. Appliance use also decreases 

over the forecast period due to appliance standards. Use in electronics remains flat over the 

forecast period, reflecting the more efficient television standard which offsets the increase in 

saturation of electronic devices in the home. 
Baseline Forecast State of New Mexico EE and DR Study 

4-4 www.gepllc.com 

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

2009 2012 2015 2020 2025

Use per Household (kWh)

Cooling

Space Heating

Heat/Cool

Water Heating

Appliances

Interior Lighting

Exterior Lighting

Electronics

Miscellaneous

4.2 COMMERCIAL SECTOR 

Electricity use in the commercial sector remains relatively flat during the forecast horizon. It 

starts at 7,898 GWh in 2009, decreases from 2010 to 2015 and increases to 7,871 GWh in 2025. 

Figure 4-3 and Table 4-2 present the baseline forecast at the end-use level for the commercial 

sector as a whole. Most end uses show modest growth over the forecast period. The exceptions 

are interior lighting which declines due to the EISA 2007 lighting standards and refrigeration 

which is affected by the EPACT 2005 standards for refrigeration. 

Figure 4-3 Commercial Baseline Electricity Forecast by End Use 

‐

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

2009 2012 2015 2020 2025

Annual Use (GWh)

Cooling

Space Heating

Comb. Heat/Cool

Ventilation

Water Heating

Food Preparation

Refrigeration

Interior Lighting

Exterior Lighting

Office Equipment

Miscellaneous
State of New Mexico EE and DR Study Baseline Forecast 

Global Energy Partners 4-5 

An EnerNOC Company 

Table 4-2 Commercial Electricity Consumption by End Use (GWh) 

End Use 2009 2012 2015 2020 2025 % Change

Avg.

growth

rate

Cooling 1,098 1,115 1,109 1,116 1,115 1.6% 0.10%

Space Heating 172 158 161 170 178 3.0% 0.18%

Comb. Heat/Cool 303 307 309 316 324 7.1% 0.43%

Ventilation 786 768 756 777 806 2.6% 0.16%

Water Heating 120 122 125 133 142 17.6% 1.01%

Food Preparation 298 301 304 319 336 12.8% 0.75%

Refrigeration 959 917 861 810 799  ‐16.7%  ‐1.14%

Interior Lighting 2,186 1,757 1,634 1,747 1,728  ‐20.9%  ‐1.47%

Exterior Lighting 453 335 318 343 346  ‐23.7%  ‐1.69%

Office Equipment 623 666 678 732 804 29.1% 1.59%

Miscellaneous 900 966 1,030 1,160 1,294 43.8% 2.27%

Total 7,898 7,410 7,285 7,623 7,871  ‐0.3%  ‐0.02%

Table 4-3 presents the commercial sector forecast by technology. Interior screw-in lighting 

decreases significantly over the forecast period as a result of the lighting standard. 
Baseline Forecast State of New Mexico EE and DR Study 

4-6 www.gepllc.com 

Table 4-3 Commercial Baseline Electricity Forecast by End Use and Technology (GWh) 

End Use Technology 2009 2012 2015 2020 2025

%

Change

('09‐

'25)

Cooling

RTU 514.3 520.5 514.2 513.9 515.2 0.2%

Air‐Cooled Chiller 242.1 245.2 245.3 248.0 245.5 1.4%

Water‐Cooled Chiller 252.7 256.0 255.9 257.4 253.6 0.4%

PTAC 35.5 37.2 37.3 38.0 38.7 8.9%

Evaporative AC 53.0 55.7 56.7 59.3 61.7 16.3%

Space Heating

Electric Furnace 26.1 23.9 24.5 25.8 27.0 3.5%

Electric Resistance 146.4 133.7 136.8 143.9 150.6 2.9%

Combined

Heating/Cooling

Heat Pump 262.3 265.5 267.0 272.5 278.2 6.1%

PTHP 40.4 41.4 42.0 43.8 45.9 13.7%

Ventilation Ventilation 785.8 767.7 755.8 776.6 806.1 2.6%

Water Heating Water Heater 120.4 121.6 124.6 133.3 141.6 17.6%

Food Preparation

Dishwasher 17.4 17.0 16.7 17.1 18.0 3.6%

Fryer 123.3 127.9 132.0 141.0 149.6 21.3%

Oven 87.0 90.0 92.7 98.9 104.7 20.4%

Hot Food Container 70.2 66.2 62.8 61.8 63.6  ‐9.4%

Refrigeration

Glass Door Display 229.2 222.7 205.9 184.9 170.4  ‐25.7%

Open Display Case 103.0 101.6 98.8 97.2 97.9  ‐5.0%

Walk‐in Refrigerator 364.3 340.1 317.5 299.0 298.0  ‐18.2%

Reach‐in Refrigerator 54.7 53.0 51.3 50.4 50.8  ‐7.1%

Vending Machine 114.6 108.2 96.1 83.5 81.1  ‐29.3%

Icemaker 92.9 91.1 91.4 95.1 100.7 8.3%

Interior Lighting

Linear Fluorescent 1,024.6 944.3 927.6 960.9 1,022.6  ‐0.2%

Screw‐in 948.0 660.6 557.7 625.3 533.7  ‐43.7%

High‐Bay Fixtures 213.9 151.9 149.0 160.7 172.2  ‐19.5%

Exterior Lighting

Linear Fluorescent 36.6 32.2 32.5 34.3 36.5  ‐0.5%

Screw‐in 113.2 82.2 68.4 76.4 61.9  ‐45.3%

HID 303.4 220.8 216.8 232.4 247.5  ‐18.4%

Office Equipment

Desktop Computer 237.4 264.8 269.2 296.0 332.7 40.1%

Laptop 24.2 27.0 27.5 30.4 34.2 41.3%

Monitor 42.2 45.2 48.7 55.9 63.5 50.4%

Server 190.6 198.8 200.5 210.3 225.0 18.0%

Printer/Copier/Fax 120.1 121.8 123.8 130.5 138.8 15.5%

POS Terminal 8.0 8.4 8.4 8.9 9.4 17.1%

Miscellaneous

Pool Pump 24.4 25.2 26.0 27.6 29.2 19.5%

Pool Heater 6.9 7.2 7.5 7.9 8.2 17.8%

Non‐HVAC Motors 84.8 87.8 90.6 96.7 102.7 21.2%

Miscellaneous 783.4 845.2 905.8 1,027.5 1,153.5 47.2%

Total 7,897.6 7,409.5 7,285.2 7,623.1 7,870.5  ‐0.3%
State of New Mexico EE and DR Study Baseline Forecast 

Global Energy Partners 4-7 

An EnerNOC Company 

4.3 INDUSTRIAL SECTOR 

Figure 4-4 and Table 4-4 present the baseline forecast at the end-use level for the industrial 

sector as a whole. Overall, industrial annual energy use increases steadily from 6,530 GWh in 

2009 to 8,538 GWh in 2025, a 30.7% increase. The AEO 2011 forecast increases by 24% over 

this same time period. 

Figure 4-4 Industrial Baseline Electricity Forecast by End Use 

‐

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

2009 2012 2015 2020 2025

Annual Use (GWh)

Cooling

Space Heating

Comb. Heat/Cool

Ventilation

Interior Lighting

Exterior Lighting

Machine Drive

Process

Other

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

End Use 2009 2012 2015 2020 2025 % Change

Avg.

growth

rate

Cooling 190 220 232 241 250 31.5% 1.71%

Space Heating 95 97 105 111 116 22.0% 1.24%

Comb. Heat/Cool 13 14 15 15 16 26.0% 1.44%

Ventilation 320 350 367 386 406 26.9% 1.49%

Interior Lighting 345 356 372 392 414 19.8% 1.13%

Exterior Lighting 29 30 31 33 35 19.8% 1.13%

Machine Drive 3,948 4,504 4,776 4,883 5,082 28.7% 1.58%

Process 1,252 1,437 1,556 1,655 1,747 39.6% 2.08%

Other 337 387 419 446 470 39.6% 2.08%

Grand Total 6,530 7,395 7,873 8,162 8,538 30.7% 1.68%
Baseline Forecast State of New Mexico EE and DR Study 

4-8 www.gepllc.com 

4.4 BASELINE FORECAST SUMMARY 

Table 4-5 and Figure 4-5 provide an overall summary of the baseline forecast by sector and for 

New Mexico as a whole. Overall, the forecast for the next 16 years is steady, reflecting modest 

growth in customers and the industrial economy, which offset appliance and equipment 

standards and naturally occurring conservation. 

Table 4-5 Baseline Forecast Summary 

Sector 2009 2012 2015 2020 2025 % Change

Avg.

growth

rate

Residential 6,474 6,646 6,539 7,035 7,421 14.64% 0.85%

Commercial 7,898 7,410 7,285 7,623 7,871  ‐0.34%  ‐0.02%

Industrial 6,530 7,395 7,873 8,162 8,538 30.74% 1.68%

Total 20,902 21,450 21,697 22,820 23,829 14.01% 0.82%

Figure 4-5 Baseline Forecast Summary 

‐

5,000

10,000

15,000

20,000

25,000

30,000

2009 2011 2013 2015 2017 2019 2021 2023 2025

GWh

Industrial

Commmercial

Residential
Global Energy Partners 5-1 

An EnerNOC Company 

CHAPTER 5 

ENERGY-EFFICIENCY MEASURES 

5.1 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 Mexico potential assessment. 

For this study, Global prepared a preliminary list of measures for all the stakeholders to review. 

We received quite a bit of feedback from the utilities and Southwest Energy Efficiency Project 

(SWEEP). Their suggestions are included in the final measure list. 

• Residential Measures. The residential measures span all end uses and vary 

significantly in the manner in which they impact energy consumption. Table 5-1 shows 

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 Volume 6. 

• 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, heat pump water heaters were only modeled for some of 

the smaller building types. All commercial measures considered for this study are 

described in Volume 6. 

• Industrial Measures. Table 5-7 presents a summary of the industrial equipment and 

non-equipment measures, respectively. All industrial measures considered for this study 

are described in Volume 6. 
Energy-Efficiency Measures State of New Mexico EE and DR Study 

5-2 www.gepllc.com 

Table 5-1 Summary of Residential Equipment Measures 

End Use Technology Efficiency Option Single Family

(existing &

new)

Mulfi Family

(existing &

new)

Mobile Home

(existing &

new)

Low Income

(existing &

new)

Cooling Central AC SEER 13 XXXX

Cooling Central AC SEER 14 (Energy Star) XXXX

Cooling Central AC SEER 15 (CEE Tier 2) XXXX

Cooling Central AC SEER 16 (CEE Tier 3) XXXX

Cooling Central AC Ductless Mini‐Split System XXXX

Cooling Central AC SEER 20 XXXX

Cooling Room AC EER 9.8 XXXX

Cooling Room AC EER 10.8 (Energy Star) XXXX

Cooling Room AC EER 11 XXXX

Cooling Room AC EER 11.5 XXXX

Cooling Evaporative Central AC Direct XXXX

Cooling Evaporative Central AC Indirect XXXX

Cooling Evaporative Central AC Indirect/Direct XXXX

Cooling Evaporative Room AC Standard XXXX

Combined Heating/Cooling Central Heat Pump SEER 13 XXXX

Combined Heating/Cooling Central Heat Pump SEER 14 (Energy Star) XXXX

Combined Heating/Cooling Central Heat Pump SEER 15 (CEE Tier 2) XXXX

Combined Heating/Cooling Central Heat Pump SEER 16 (CEE Tier 3) XXXX

Combined Heating/Cooling Central Heat Pump Ductless Mini‐Split System XXXX

Combined Heating/Cooling Central Heat Pump Geothermal X    

Space Heating Electric Resistance Electric Resistance XXXX

Water Heating Water Heater EF 0.9 XXXX

Water Heating Water Heater EF 0.95 XXXX

Water Heating Water Heater EF 2.3 (HP) XXXX

Water Heating Water Heater Geothermal X    

Water Heating Water Heater Solar XXXX

Interior Lighting Screw‐in Incandescent (14 lm/watt) XXXX

Interior Lighting Screw‐in Infrared Halogen (17 lm/watt) XXXX

Interior Lighting Screw‐in Infrared Halogen (45 lm/watt) XXXX

Interior Lighting Screw‐in CFL (45 lm/watt) XXXX

Interior Lighting Screw‐in LED (97 lm/watt) XXXX

Interior Lighting Screw‐in LED (197 lm/watt) XXXX

Interior Lighting Linear Fluorescent T12 XXXX

Interior Lighting Linear Fluorescent T8 XXXX

Interior Lighting Linear Fluorescent Super T8 XXXX

Interior Lighting Linear Fluorescent T5 XXXX

Interior Lighting Linear Fluorescent LED XXXX

Exterior Lighting Screw‐in Incandescent (15.6 lm/watt) XXXX

Exterior Lighting Screw‐in Infrared Halogen (17 lm/watt) XXXX

Exterior Lighting Screw‐in Infrared Halogen (45 lm/watt) XXXX

Exterior Lighting Screw‐in CFL (45 lm/watt) XXXX

Exterior Lighting Screw‐in LED (97 lm/watt) XXXX

Exterior Lighting Screw‐in LED (197 lm/watt) XXXX

Appliances Clothes Washer Standard (1.26) XXXX

Appliances Clothes Washer Energy Star (1.72) XXXX

Appliances Clothes Washer AHAM(MEF 1.72) XXXX

Appliances Clothes Washer Energy Star (MEF 2.0) XXXX

Appliances Clothes Washer AHAM(MEF 2.0) XXXX

Appliances Clothes Washer Compact (MEF 2.79) XXXX

Appliances Clothes Dryer Baseline XXXX

Appliances Clothes Dryer High Efficiency XXXX

Appliances Clothes Dryer Baseline (AHAM 2015+) XXXX

Appliances Clothes Dryer High Efficiency (AHAM 2015+) XXXX
State of New Mexico EE and DR Study Energy-Efficiency Measures 

Global Energy Partners 5-3 

An EnerNOC Company 

Table 5-1 Summary of Residential Equipment Measures (continued) 

End Use Technology Efficiency Option Single Family

(existing &

new)

Mulfi Family

(existing &

new)

Mobile Home

(existing &

new)

Low Income

(existing &

new)

Appliances Dishwasher Standard (EF 0.46) XXXX

Appliances Dishwasher Standard (EF 0.63) XXXX

Appliances Dishwasher Energy Star (EF 0.69) XXXX

Appliances Dishwasher Energy Star (EF 0.73) XXXX

Appliances Dishwasher AHAM (EF 0.73) XXXX

Appliances Dishwasher Ultra Efficient (EF 1.1) XXXX

Appliances Refrigerator Standard XXXX

Appliances Refrigerator Energy Star XXXX

Appliances Refrigerator High Efficiency XXXX

Appliances Refrigerator AHAM (2014) XXXX

Appliances Refrigerator High Efficiency (2014) XXXX

Appliances Freezer Standard XXXX

Appliances Freezer Energy Star XXXX

Appliances Freezer High Efficiency XXXX

Appliances Freezer AHAM(2014) XXXX

Appliances Freezer High Efficiency (2014) XXXX

Appliances Second Refrigerator Standard XXXX

Appliances Second Refrigerator Energy Star XXXX

Appliances Second Refrigerator High Efficiency XXXX

Appliances Second Refrigerator AHAM(2014) XXXX

Appliances Second Refrigerator High Efficiency (2014) XXXX

Appliances Stove Baseline XXXX

Appliances Stove Convection XXXX

Appliances Stove Halogen Burners XXXX

Appliances Stove Induction XXXX

Appliances Microwave Microwave XXXX

Electronics Personal Computers Baseline XXXX

Electronics Personal Computers Energy Star XXXX

Electronics Monitor Baseline XXXX

Electronics Monitor Energy Star XXXX

Electronics Laptops Baseline XXXX

Electronics Laptops Energy Star XXXX

Electronics TVs Standard XXXX

Electronics TVs Energy Star (3.1) XXXX

Electronics TVs Energy Star (4.1) XXXX

Electronics TVs Energy Star (5.1) XXXX

Electronics Copier/Printer/Fax Standard XXXX

Electronics Copier/Printer/Fax Energy Star XXXX

Electronics DVD/VCR/Audio Baseline XXXX

Electronics DVD/VCR/Audio Energy Star XXXX

Electronics DVD/VCR/Audio Energy Star (2010) XXXX

Electronics DVD/VCR/Audio Energy Star (2012) XXXX

Electronics Devices and Gadgets Devices and Gadgets XXXX

Miscellaneous Pool Pump Baseline Pump XXXX

Miscellaneous Pool Pump High Efficiency Pump XXXX

Miscellaneous Pool Pump Two‐Speed Pump XXXX

Miscellaneous Well Pump Baseline (40% EF) XXXX

Miscellaneous Well Pump High Efficiency (60% EF) XXXX

Miscellaneous Furnace Fan Standard XXXX

Miscellaneous Furnace Fan ECM XXXX

Miscellaneous Miscellaneous Miscellaneous XXXX

Water Heating Water Heater Solar XXXX
Energy-Efficiency Measures State of New Mexico EE and DR Study 

5-4 www.gepllc.com 

Table 5-2 Summary of Residential Non-equipment Measures 

Measure Single Family Existing

Single Family

New

Construction

Mulfi Family Existing

Multi Family

New

Construction

Mobile Home Existing

Multi Family

New

Construction

Low Income Existing

Low Income

New

Construction

Central AC ‐ Maintenance X X X X X X X X

Attic Fan ‐ Installation X X X X X X X X

Ceiling Fan ‐ Installation X X X X X X X X

Whole‐House Fan and Cover ‐ Installation X X X X X X X X

Central Heat Pump ‐ Maintenance X X X X X X X X

Ducting ‐ Repair and Sealing X X X X X X X X

Thermostat ‐ Clock/Programmable X X X X X X X X

Household ‐ Weatherization X    X    X    X

Insulation ‐ Ducting (Good) X X X X X X X X

Insulation ‐ Ducting (Better) X X X X X X X X

Insulation ‐ Ducting (Best) X X X X X X X X

Insulation ‐ Ceiling (Good) X X X X X X X X

Insulation ‐ Ceiling (Better) X X X X X X X X

Insulation ‐ Ceiling (Best) X X X X X X X X

Insulation ‐ Attic Hatch (Good) X X X X X X X X

Insulation ‐ Attic Hatch (Better) X X X X X X X X

Insulation ‐ Attic Hatch (Best) X X X X X X X X

Insulation ‐ Hydronic Pipe Wrap X X X X X X X X

Roofs ‐ High Reflectivity X X X X X X X X

Windows ‐ Reflective Film X X X X X X X X

Windows ‐ Energy Star X X X X X X X X

Interior Lighting ‐ Fluorescent Torchieres X X X X X X X X

Interior Lighting ‐ Occupancy Sensors X X X X X X X X

Outdoor Lighting ‐ Photovoltaic X X X X X X X X

Outdoor Lighting ‐ Photosensor X X X X X X X X

Outdoor Lighting ‐ Timeclock X X X X X X X X

Water Heating ‐ Faucet Aerators X X X X X X X X

Water Heating ‐ Pipe Insulation X X X X X X X X

Water Heating ‐ Low‐Flow Showerheads X X X X X X X X

Water Heating ‐ Tank Blanket X X X X X X X X

Water Heating ‐ Thermostat Setback X X X X X X X X

Water Heating ‐ Timer X X X X X X X X

Water Heating ‐ Hot Water Saver X X X X X X X X

Refrigerator ‐ Maintenance X X X X X X X X

Second Refrigerator ‐ Removal X X X X X X X X

Freezer ‐ Removal X X X X X X X X

Home Energy Management System X X X X X X X X

Pool Pump ‐ Timer X X X X X X X X

Insulation ‐ Wall Cavity (Good)    X    X    X    X

Insulation ‐ Wall Cavity (Better)    X    X    X    X

Insulation ‐ Wall Cavity (Best)    X    X    X    X

Insulation ‐ Foundation (Good)    X    X    X    X

Insulation ‐ Foundation (Better)    X    X    X    X

Insulation ‐ Foundation (Best)    X    X    X    X

Insulation ‐ Wall Sheathing (Good)    X    X    X    X

Insulation ‐ Wall Sheathing (Better)    X    X    X    X

Insulation ‐ Wall Sheathing (Best)    X    X    X    X

Water Heating ‐ Drainwater Heat Recovery    X    X    X    X

Construction ‐ Energy Star Home (Good)    X    X    X    X

Construction ‐ Energy Star Home (Better)    X    X    X    X

Construction ‐ Energy Star Home (Best)    X    X    X    X

Construction ‐ Advanced Design    X    X    X    X
State of New Mexico EE and DR Study Energy-Efficiency Measures 

Global Energy Partners 5-5 

An EnerNOC Company 

Table 5-3 Summary of Commercial Equipment Measures 

End Use Technology Efficiency Option End Use Technology Efficiency Option

Cooling Air‐Cooled Chiller 1.5 kw/ton, COP 2.3 Interior Lighting Screw‐in Incandescent

Cooling Air‐Cooled Chiller 1.3 kw/ton, COP 2.7 Interior Lighting Screw‐in Halogen (20 lumens/watt)

Cooling Air‐Cooled Chiller 1.26 kw/ton, COP 2.8 Interior Lighting Screw‐in Halogen (45 lumens/watt)

Cooling Air‐Cooled Chiller 1.0 kw/ton, COP 3.5 Interior Lighting Screw‐in Cold Cathode

Cooling Air‐Cooled Chiller 0.97 kw/ton, COP 3.6 Interior Lighting Screw‐in CFL

Cooling Water‐Cooled Chiller 0.75 kw/ton, COP 4.7 Interior Lighting Screw‐in LED (2019)

Cooling Water‐Cooled Chiller 0.60 kw/ton, COP 5.9 Interior Lighting Screw‐in LED (2020+)

Cooling Water‐Cooled Chiller 0.58 kw/ton, COP 6.1 Interior Lighting High‐Bay Fixtures Mercury Vapor

Cooling Water‐Cooled Chiller 0.55 kw/Ton, COP 6.4 Interior Lighting High‐Bay Fixtures Metal Halides

Cooling Water‐Cooled Chiller 0.51 kw/ton, COP 6.9 Interior Lighting High‐Bay Fixtures T5 HO

Cooling Water‐Cooled Chiller 0.50 kw/Ton, COP 7.0 Interior Lighting High‐Bay Fixtures High Pressure Sodium

Cooling Water‐Cooled Chiller 0.48 kw/ton, COP 7.3 Interior Lighting Linear Fluorescent T12

Cooling Evaporative AC Direct Interior Lighting Linear Fluorescent T8

Cooling Evaporative AC Indirect Interior Lighting Linear Fluorescent Super T8

Cooling Evaporative AC Direct/Indirect Interior Lighting Linear Fluorescent T5

Cooling RTU EER 9.2 Interior Lighting Linear Fluorescent LED (2019)

Cooling RTU EER 10.1 Interior Lighting Linear Fluorescent LED (2020+)

Cooling RTU EER 11.2 Exterior Lighting Screw‐in Incandescent

Cooling RTU EER 12.0 Exterior Lighting Screw‐in Halogen (20 lumens/watt)

Cooling RTU Ductless Minisplit System Exterior Lighting Screw‐in Halogen (45 lumens/watt)

Cooling PTAC EER 9.8 Exterior Lighting Screw‐in Cold Cathode

Cooling PTAC EER 10.2 Exterior Lighting Screw‐in CFL

Cooling PTAC EER 10.8 Exterior Lighting Screw‐in LED (2019)

Cooling PTAC EER 11 Exterior Lighting Screw‐in LED (2020+)

Cooling PTAC EER 11.5 Exterior Lighting HID Mercury Vapor

Combined Heating/Cooling Heat Pump EER 9.3, COP 3.1 Exterior Lighting HID Metal Halides

Combined Heating/Cooling Heat Pump EER 10.3, COP 3.2 Exterior Lighting HID T5 HO

Combined Heating/Cooling Heat Pump EER 11.0, COP 3.3 Exterior Lighting HID High Pressure Sodium

Combined Heating/Cooling Heat Pump EER 11.7, COP 3.4 Exterior Lighting HID Low Pressure Sodium

Combined Heating/Cooling Heat Pump EER 12, COP 3.4 Exterior Lighting Linear Fluorescent T12

Combined Heating/Cooling Heat Pump Ductless Minisplit System Exterior Lighting Linear Fluorescent T8

Combined Heating/Cooling Heat Pump Geothermal Exterior Lighting Linear Fluorescent Super T8

Combined Heating/Cooling PTHP EER 9.8 Exterior Lighting Linear Fluorescent T5

Combined Heating/Cooling PTHP EER 10.2 Exterior Lighting Linear Fluorescent LED (2019)

Combined Heating/Cooling PTHP EER 10.8 Exterior Lighting Linear Fluorescent LED (2020+)

Combined Heating/Cooling PTHP EER 11 Refrigeration Walk‐in Refrigerator 14600 kWh/yr

Combined Heating/Cooling PTHP EER 11.5 Refrigeration Walk‐in Refrigerator 10800 kWh/yr

Space Heating Electric Resistance Standard Refrigeration Walk‐in Refrigerator 10000 kWh/yr

Space Heating Electric Furnace Standard Refrigeration Walk‐in Refrigerator 9000 kWh/yr

Ventilation Ventilation Constant Volume Refrigeration Reach‐in Refrigerator 3800 kWh/yr

Ventilation Ventilation Variable Air Volume Refrigeration Reach‐in Refrigerator 3100 kWh/yr

Water Heating Water Heater EF .97 Refrigeration Reach‐in Refrigerator 2500 kWh/yr

Water Heating Water Heater EF .98 Refrigeration Reach‐in Refrigerator 2400 kWh/yr

Water Heating Water Heater EF 2.0 Refrigeration Reach‐in Refrigerator 1500 kWh/yr

Water Heating Water Heater EF 2.3 Refrigeration Glass Door Display 14480 kWh/yr

Water Heating Water Heater EF 2.4 Refrigeration Glass Door Display 11700 kWh/yr

Water Heating Water Heater Geothermal Refrigeration Glass Door Display 8400 kWh/yr

Water Heating Water Heater SEF 0.8‐4.8 Refrigeration Glass Door Display 6800 kWh/yr
Energy-Efficiency Measures State of New Mexico EE and DR Study 

5-6 www.gepllc.com 

Table 5-4 Summary of Commercial Equipment Measures (Continued) 

End Use Technology Efficiency Option

Refrigeration Open Display Case 6500 kWh/yr

Refrigeration Open Display Case 5300 kWh/yr

Refrigeration Open Display Case 5350 kWh/yr

Refrigeration Open Display Case 4330 kWh/yr

Refrigeration Icemaker 7.0 kWh/100 lbs

Refrigeration Icemaker 6.3 kWh/100 lbs

Refrigeration Icemaker 6.0 kWh/100 lbs

Refrigeration Icemaker 5.5 kWh/100 lbs

Refrigeration Vending Machine 3400 kWh/yr

Refrigeration Vending Machine 3000 kWh/yr

Refrigeration Vending Machine 2400 kWh/yr

Refrigeration Vending Machine 1700 kWh/yr

Food Preparation Oven Standard

Food Preparation Oven Energy Star

Food Preparation Fryer Standard

Food Preparation Fryer Energy Star

Food Preparation Dishwasher Standard

Food Preparation Dishwasher Energy Star

Food Preparation Hot Food Container Standard

Food Preparation Hot Food Container Energy Star

Office Equipment Desktop Computer Standard

Office Equipment Desktop Computer Energy Star

Office Equipment Laptop Standard

Office Equipment Laptop Energy Star

Office Equipment Server Standard

Office Equipment Server Energy Star

Office Equipment Monitor Standard

Office Equipment Monitor Energy Star

Office Equipment Printer/Copier/Fax Standard

Office Equipment Printer/Copier/Fax Energy Star

Office Equipment POS Terminal Standard

Office Equipment POS Terminal Energy Star

Miscellaneous Non‐HVAC Motors Standard

Miscellaneous Non‐HVAC Motors Standard (2015)

Miscellaneous Non‐HVAC Motors High Efficiency

Miscellaneous Non‐HVAC Motors High Efficiency (2015)

Miscellaneous Non‐HVAC Motors Premium

Miscellaneous Non‐HVAC Motors Premium (2015)

Miscellaneous Pool Pump Baseline Pump

Miscellaneous Pool Pump High Efficiency Pump

Miscellaneous Pool Pump Two‐Speed Pump

Miscellaneous Pool Heater Baseline

Miscellaneous Pool Heater Heat Pump

Miscellaneous Pool Heater Solar

Miscellaneous Miscellaneous Standard

Miscellaneous Miscellaneous Miscellaneous (2013)
State of New Mexico EE and DR Study Energy-Efficiency Measures 

Global Energy Partners 5-7 

An EnerNOC Company 

Table 5-5 Summary of Commercial Non-equipment Measures 

Measure Existing

New

Water Cooled Chiller ‐ VSD X X

Water Cooled Chiller ‐ High Efficiency Tower Fans 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

Air Cooled Chiller ‐ VSD X X

Air Cooled Chiller ‐ High Efficiency Tower Fans X X

Air Cooled Chiller ‐ Condenser Air Temperature Reset X X

Air Cooled Chiller ‐ Economizer X X

Air Cooled Chiller ‐ Thermal Energy Storage X X

Heat Pump ‐ Maintenance X X

RTU ‐ Maintenance X X

Gas Furnace ‐ Maintenance X X

Gas Boiler ‐ Hot Water Reset X X

Gas Boiler ‐ High Efficiency Hot Water Circulation X X

Insulation ‐ Ducting (Good) X X

Insulation ‐ Ducting (Better) X X

Insulation ‐ Ducting (Best) X X

Insulation ‐ Ceiling (Good) X X

Insulation ‐ Ceiling (Better) X X

Insulation ‐ Ceiling (Best) X X

Insulation ‐ Wall Cavity (Good) X X

Insulation ‐ Wall Cavity (Better) X X

Insulation ‐ Wall Cavity (Best) X X

Ducting ‐ Repair and Sealing X X

Energy Management System X X

Ventilation ‐ Exhaust Hood Sensor Control X X

Ventilation ‐ Variable Speed Control X X

Ventilation ‐ CO2 Controlled X X

Non‐HVAC Motors ‐ Variable Speed Control X X

Thermostat ‐ Clock/Programmable X X
Energy-Efficiency Measures State of New Mexico EE and DR Study 

5-8 www.gepllc.com 

Table 5-6 Summary of Commercial Non-equipment Measures (Continued) 

Measure Existing

New

Roofs ‐ High Reflectivity X X

Windows ‐ High Efficiency X X

Interior Lighting ‐ LED Exit Lighting X X

Interior Lighting ‐ Occupancy Sensors X X

Interior Lighting ‐ Task Lighting X X

Interior Lighting ‐ Timers X X

Interior Fluorescent ‐ Delamp and Install Reflectors X X

Interior Fluorescent ‐ Bi‐Level Fixture w/Occupancy Sensor X X

Interior Fluorescent ‐ Photocell‐Controlled Diming Ballasts X X

Indoor Lighting ‐ Daylighting Controls X X

Water Heating ‐ Faucet Aerators X X

Water Heating ‐ Pipe Insulation X X

Water Heating ‐ Tank Blanket X X

Water Heating ‐ Hot Water Saver X X

Glass Door Display ‐ Anti‐Sweat Heater X X

Glass Door Display ‐ Gasket Replacement X X

Reach‐in Refrigerator ‐ Gasket Replacement X X

Open Display Case ‐ Night Covers X X

Office Equipment ‐ Plug Load Occupancy Sensors X X

Office Equipment ‐ Energy Star Power Supplies X X

Vending Machine ‐ Controller X X

Pool Pump ‐ Timer X X

Space Heating ‐ Heat Recovery Ventilator X X

Lighting Retrocommissioning X

Comprehensive Retrocommissioning X

Custom Measures X X

Water Heating ‐ Drainwater Heat Recovery X

Lighting Commissioning X

Comprehensive Commissioning X

Advanced New Construction Designs X

Interior Lighting ‐ Guest Room Controls    
State of New Mexico EE and DR Study Energy-Efficiency Measures 

Global Energy Partners 5-9 

An EnerNOC Company 

Table 5-7 Summary of Industrial Measures 

Measure Other Industrial

Existing

Other Industrial New

Se

miconductor Existing

Se

miconductor New

Oil and

Petrole

u

m

Existing

Oil and

Petrole

u

m

New

Refrigeration System Controls XXXX

Refrigeration System Maintenance XXXX

Refrigeration System Optimization XXXX

Interior Screw‐in ‐ CFL XXXX

Interior Screw‐in ‐ LED XXXX

Exterior Screw‐in ‐ CFL XXXX

Exterior Screw‐in ‐ LED XXXX

Heat Pump ‐ High Efficiency XXXX

Heat Pump ‐ Ductless VRF XXXX

Heat Pump ‐ Geothermal XXXX

RTU ‐ High Efficiency XXXX

RTU ‐ Ductless VRF XXXX

Evaporative Cooler XXXX

Central Chiller ‐ High Efficiency XXXX

Interior Linear Fluorescent ‐ T8 XXXX

Interior Linear Fluorescent ‐ Super T8 XXXX

Interior Linear Fluorescent ‐ T5 XXXX

Exterior Linear Fluorescent ‐ T8 XXXX

Exterior Linear Fluorescent ‐ Super T8 XXXX

Exterior Linear Fluorescent ‐ T5 XXXX

Interior High Bay ‐ T5 HO XXXX

Interior High Bay ‐ High‐Pressure Sodium XXXX

Interior High Bay ‐ Metal Halide XXXX

Interior High Bay ‐ Metal Halide w/Pulse Start XXXX

Exterior HID ‐ T5 HO XXXX

Exterior HID ‐ High‐Pressure Sodium XXXX

Exterior HID ‐ Metal Halide XXXX

Exterior HID ‐ Metal Halide w/Pulse Start XXXX

Exterior HID ‐ Low‐Pressure Sodium XXXX 
Energy-Efficiency Measures State of New Mexico EE and DR Study 

5-10 www.gepllc.com 

Table 5-8 Summary of Industrial Measures (Continued) 

Measure Other Industrial

Existing

Other Industrial New

Semiconductor Existing

Semiconductor New

Oil and

Petroleum

Existing

Oil and

Petroleum

New

Ventilation ‐ C02 Controls XXXX

Process ‐ Compressed Air System Controls XXXX

Process ‐ Compressed Air System Optimization and Improvements XXXX

Process ‐ Compressed Air System Maintenance XXXX

Process ‐ Compressor Replacement XXXX

Process ‐ Fan System Controls XXXX

Process ‐ Fan System Optimization XXXX

Process ‐ Fan System Maintenance XXXX

Machine Drive ‐ Pumping System Controls XXXX

Machine Drive ‐ Pumping System Optimization XXXX

Machine Drive ‐ Pumping System Maintenance XXXX

Machine Drive ‐ Motors ‐ Premium Efficiency Motor X X

Machine Drive ‐ Pumps ‐ High Efficiency Motor < 5 HP XXXX

Machine Drive ‐ Pumps ‐ High Efficiency Motor  5‐24HP XXXX

Machine Drive ‐ Pumps ‐ High Efficiency Motor  25‐99HP XXXX

Machine Drive ‐ Pumps ‐ High Efficiency Motor  100‐249HP XXXX

Machine Drive ‐ Pumps ‐ High Efficiency Motor  250‐499 HP XXXX

Machine Drive ‐ Pumps ‐ High Efficiency Motor  500 or more HP XXXX

RTU ‐ Maintenance XXXX

Central Chiller ‐ Maintenance XXXX

Central Chiller ‐ Chiller Water Reset XXXX

Central Chiller ‐ VSD XXXX

Central Chiller ‐ High Efficiency Fans XXXX

Central Chiller ‐ Temprature Reset XXXX

Central Chiller ‐ Economizer XXXX

Heat Pump ‐ Maintenance XXXX

LED Exit Lighting XXXX

Occupancy Sensors XXXX
State of New Mexico EE and DR Study Energy-Efficiency Measures 

Global Energy Partners 5-11 

An EnerNOC Company 

Table 5-9 Summary of Industrial Measures (Continued) 

Measure Other Industrial

Existing

Other Industrial NewSe

miconductor Existing

Se

miconductor New

Oil and

Petroleu

m

Existing

Oil and

Petroleu

m

New

Task Lighting XXXX

Time Clocks and Timers XXXX

Daylighting Controls ‐ Photocell Controlled Dimming Ballasts XXXX

Delamp and Install Reflectors XXXX

Bi‐Level Fixture w/Occupancy Sensor XXXX

HVAC ‐ Duct Insulation XXXX

HVAC ‐ Duct Repair and Sealing XXXX

Energy Management System XXXX

Clock/Programmable Thermostat XXXX

Insulation ‐ Ceiling XXXX

Insulation ‐ Wall Cavity XXXX

Roofs ‐ High Reflectivity XXXX

Boiler ‐ High Efficiency XXXX

Furnace ‐ High Efficiency XXXX

Furnace ‐ Maintenance XXXX

Boiler ‐ Hot Water Reset XXXX

Ventilation ‐ Variable Air Volume X X

Central Chiller ‐ Thermoelectric X X

Central Chiller ‐ Efficient Mechanical Layout X X

Reduce Lighting & Cooling Loads X X

Interior Lighting ‐ Skylights X X

Process ‐ Reduce Drag out X X

Process ‐ Counter Flow Rinsing X X

Process ‐ Use Flow restrictors X X

Process ‐ Timers and Controls X X

Process ‐ Conductivity Controls X X

Process ‐ Reduce use of compressed air X X
Energy-Efficiency Measures State of New Mexico EE and DR Study 

5-12 www.gepllc.com 

Table 5-10 Summary of Industrial Measures (Continued) 

Measure Other Industrial

Existing

Other Industrial New

Semiconductor Existing

Semiconductor New

Oil and

Petroleum

Existing

Oil and

Petroleum

New

Process ‐ Insulate Hot tanks X X

Refrigeration ‐ Floating Head Pressure X X

Process ‐ Controls on Fume Hoods X X

Process ‐ Sequence air compressors X X

Cooling ‐ Exhaust Injection X X

Cooling ‐ Reduce Gas Pressure X X

Process ‐ Vacuum pump incremental overbuild X X

Central Chiller ‐ Chiller Optimization X X

Cooling ‐ Change Filter Strategy X X

Cooling ‐ Clean Room HVAC X X

Cooling ‐ Eliminate exhaust and recirculate air X X

Cooling ‐ Reduce Pressure & Chilled Water Temperature X X

VSD on Cooling Tower Pumps X X

Central Chiller ‐ Chiller Heat Recovery X X

Process ‐ Install New Air Compressor X X

Variable Speed Drive for ESP Pumping Units X X

Pump Off Controllers for Rod Beam Pumping Unit X X

Well Conversion to Progressing Cavity Pump X X

Premium Efficiency Motors X X

Well Conversion, Gas Lift to Rod Beam with POC X X

Process Optimization of pump retrofit X X

Variable Speed Drive for Steam Generator Feedwater Pump and/or Fan X X

Variable Speed Drive for Positive Displacement Pump X X

Variable Speed Drive for Gas Compressor X X

Decreasing water/oil ratio X X

VSDs forsurface motors X X

Smart Well X X
State of New Mexico EE and DR Study Energy-Efficiency Measures 

Global Energy Partners 5-13 

An EnerNOC Company 

5.2 RESULTS OF THE ECONOMIC SCREEN 

Table 5-11 summarizes the number of equipment and non-equipment measures evaluated for 

each segment within each sector. 

Table 5-11 Number of Measures Evaluated 

Residential Commercial Industrial Total Number

of Measures

Equipment Measures Evaluated 104 142 37 283

Non‐Equipment Measures Evaluated 52 59 70 181

Total Measures Evaluated 156 201 107 464

Volume 6 summarizes the economic screening process by segment, vintage, end use and 

measure for the residential sector. Volume 6 shows the equivalent information for the 

commercial and industrial sectors. 

Global Energy Partners 6-1 

An EnerNOC Company 

CHAPTER 6 

ELECTRIC ENERGY EFFICIENCY POTENTIAL RESULTS 

This chapter presents the results of the electric energy-efficiency analysis. First, the overall 

potential is presented, followed by results for each sector. 

6.1 OVERALL ELECTRIC ENERGY EFFICIENCY POTENTIAL 

Table 6-1 presents the baseline forecasts of energy consumption and peak demand, as well as 

the four levels of electric energy-efficiency potential across sectors. As discussed in detail in 

Chapter 4, the baseline forecast across all sectors increases over the 16-year time period. This is 

due largely to the growth in the industrial and residential sectors which are tempered somewhat 

due to appliance and equipment standards, building codes and a sluggish economy. Key findings 

related to potentials are summarized below. 

• Achievable - Low potential across all sectors is 67 GWh in 2012 and increases to 1,473 by 

2025. This represents 0.3% of the baseline forecast in 2012 and 6.2% in 2025. By 2025, 

Achievable – Low offsets 62% of the growth in the baseline forecast. Peak demand savings 

from energy-efficiency measures are 6 MW in 2012, which represents 0.2% of the baseline 

forecast of peak demand. By 2025, peak demand savings reach 189 MW, 4.5% of the 

baseline peak demand forecast. 

• Achievable - High potential is 187 GWh in 2012, which represents 0.9% of the baseline 

forecast. By 2025, the cumulative savings are 2,656 GWh, 11.1% of the baseline forecast, for 

an annual average of just under 1% per year. By 2025, Achievable – High offsets more than 

100% of the growth in the baseline forecast. Peak demand savings are 18 MW in 2012, 

which represents 0.5% of the baseline forecast of peak demand. By 2025, peak demand 

savings reach 361 MW, 8.7% of the baseline peak demand forecast. 

• Economic potential, which reflects the savings when all cost-effective measures are taken, 

is 576 GWh in 2012. This represents 2.7% of the baseline energy forecast. By 2025, 

economic potential reaches 3,510 GWh, 14.7% of the baseline energy forecast. Peak demand 

savings are 51 MW in 2012, which represents 0.5% of the baseline forecast of peak demand. 

By 2025, peak demand savings reach 491 MW, 11.8% of the baseline peak demand forecast. 

• Technical potential, which reflects the adoption of all energy efficiency measures 

regardless of cost-effectiveness, is a theoretical upper bound on savings. In 2012, energy 

savings are 695 GWh, or 3.2% of the baseline energy forecast. By 2025, technical potential 

reaches 4,770 GWh, 20.0% of the baseline energy forecast. Peak demand savings are 70 MW 

in 2012, which represents 1.8% of the baseline forecast of peak demand. By 2025, peak 

demand savings reach 851 MW or 20.4% of the baseline peak demand forecast. 

Figure 6-1 summarizes the energy-efficiency savings for the four levels of potential relative to 

the baseline forecast. Figure 6-2 displays the energy-efficiency forecasts12. 

 

12 Annual savings are shown in Volume 6. 
Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study 

6-2 www.gepllc.com 

Table 6-1 Summary of Energy Efficiency Potential 

2012 2015 2020 2025

Baseline Forecast 21,450 21,697 22,820 23,829

Energy Savings (GWh)

Achievable ‐ Low 67 246 810 1,473

Achievable ‐ High 187 573 1,488 2,656

Economic 576 1,171 2,170 3,510

Technical 695 1,520 2,998 4,770

Energy Savings (% of Baseline)

Achievable ‐ Low 0.3% 1.1% 3.5% 6.2%

Achievable ‐ High 0.9% 2.6% 6.5% 11.1%

Economic 2.7% 5.4% 9.5% 14.7%

Technical 3.2% 7.0% 13.1% 20.0%

Peak Savings (MW) 2012 2015 2020 2025

Achievable ‐ Low 6 25 95 189

Achievable ‐ High 18 61 184 361

Economic 51 123 273 491

Technical 70 190 461 851

Peak Savings (% of Baseline)

Achievable ‐ Low 0.2% 0.6% 2.4% 4.5%

Achievable ‐ High 0.5% 1.6% 4.6% 8.7%

Economic 1.3% 3.2% 6.8% 11.8%

Technical 1.8% 4.9% 11.6% 20.4%
State of New Mexico EE and DR Study Electric Energy Efficiency Potential Results 

Global Energy Partners 6-3 

An EnerNOC Company 

Figure 6-1 Summary of Achievable Potential Energy Savings 

Achievable‐ Low

Achievable ‐ High

Economic

Technical

0%

5%

10%

15%

20%

25%

2012 2015 2020 2025

Savings as

% of Baseline Forecast

Figure 6-2 Energy Efficiency Potential Energy Forecasts (GWh) 

3,000

8,000

13,000

18,000

23,000

28,000

2009 2011 2013 2015 2017 2019 2021 2023 2025

GWh

Baseline Forecast

Achievable‐ Low

Achievable ‐ High

Economic

Technical

Table 6-2 and Figure 6-3 summarize the range of achievable potential by sector. The residential 

sector accounts for the largest portion of the savings — about half of the Achievable - Low 

potential in 2025 — followed by the industrial sector. 
Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study 

6-4 www.gepllc.com 

Table 6-2 Achievable Energy-efficiency Potential by Sector (GWh) 

2012 2015 2020 2025

Achievable ‐ Low Savings (GWh)

Residential 36 137 428 684

Commercial 23 86 253 361

Industrial 8 24 129 427

Total 67 246 810 1,473

Achievable ‐ High Savings (GWh)

Residential 95 281 651 990

Commercial 63 215 513 681

Industrial 30 77 324 985

Total 187 573 1,488 2,656

Figure 6-3 Achievable Potential by Sector, 2025 

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

Residential Commercial Industrial

Savingsin2025 (GWh)

Achievable‐ High

Achievable‐ Low

Table 6-3 presents estimates of potential for each entity in the state. These estimates represent the 

sum of the sector-level estimates for each entity. 
State of New Mexico EE and DR Study Electric Energy Efficiency Potential Results 

Global Energy Partners 6-5 

An EnerNOC Company 

Table 6-3 Energy Efficiency Potential by Entity (MWh) 

Utility Type 2012 2015 2020 2025

IOUs

PNM

Achievable ‐ Low 32,698 124,688 384,903 608,747

Achievable – High 88,694 278,959 664,103 1,009,478

Economic 292,240 584,198 970,335 1,334,780

SPS

Achievable ‐ Low 9,652 36,022 135,534 292,214

Achievable – High 28,563 88,169 265,485 570,043

Economic 78,439 175,588 385,997 753,475

El Paso

Achievable ‐ Low 4,267 15,196 47,553 82,622

Achievable – High 11,484 34,151 83,458 136,910

Economic 39,778 71,455 121,707 180,057

Non IOU

Aztec City of

Achievable ‐ Low 175 636 1,903 2,953

Achievable – High 467 1,441 3,344 4,764

Economic 1,521 3,052 5,045 6,380

Central New Mexico El Coop, Inc

Achievable – Low 915 3,251 10,630 19,939

Achievable – High 2,543 7,391 19,015 34,652

Economic 8,700 15,499 27,685 45,590

Central Valley Electric Coop, Inc

Achievable – Low 1,324 4,461 18,544 48,073

Achievable – High 4,390 12,230 41,350 103,376

Economic 9,857 21,656 58,139 135,652

Columbus Electric Coop, Inc

Achievable – Low 299 1,095 3,314 5,178

Achievable – High 808 2,553 6,082 8,787

Economic 2,418 5,317 9,261 11,923

Continental Divide El Coop Inc

Achievable – Low 1,378 4,894 16,274 31,337

Achievable – High 3,916 11,543 30,605 57,364

Economic 12,087 23,484 44,711 75,812

Duncan Valley Elec Coop, Inc

Achievable – Low 16 56 186 358

Achievable – High 44 124 323 607

Economic 162 266 465 794

Farmers' Electric Coop, Inc

Achievable – Low 1,027 3,618 12,707 26,562

Achievable – High 3,036 8,911 25,302 51,721

Economic 8,484 17,485 36,707 68,382

City of Farmington

Achievable – Low 3,393 12,049 40,153 77,599

Achievable – High 9,754 29,099 77,886 146,318

Economic 27,827 58,044 114,176 193,744

City of Gallup

Achievable – Low 809 2,965 8,829 13,344

Achievable – High 2,183 6,975 16,362 22,715

Economic 6,187 14,388 25,050 30,930

Jemez Mountains Elec Coop, Inc

Achievable – Low 1,471 5,308 16,187 26,398

Achievable – High 3,940 11,849 27,926 42,438

Economic 13,647 25,351 41,591 56,255
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Utility Type 2012 2015 2020 2025

Kit Carson Electric Coop, Inc

Achievable – Low 1,189 4,258 13,370 23,242

Achievable – High 3,240 9,606 23,536 38,996

Economic 11,076 20,324 34,697 51,461

Lea County Electric Coop, Inc

Achievable – Low 1,911 6,846 23,216 45,468

Achievable – High 5,658 17,486 48,362 91,503

Economic 13,249 33,564 71,784 122,599

Los Alamos County

Achievable – Low 1,052 3,542 14,517 37,247

Achievable – High 3,454 9,577 31,967 79,445

Economic 8,057 17,113 44,877 104,058

Mora‐San Miguel Elec Coop, Inc

Achievable – Low 345 1,234 3,795 6,370

Achievable – High 913 2,642 6,179 9,726

Economic 3,577 5,834 9,049 12,704

Navajo Tribal Utility Authority

Achievable – Low 431 1,539 4,954 9,008

Achievable – High 1,204 3,593 9,165 16,063

Economic 3,756 7,385 13,499 21,260

Navopache Electric Coop, Inc

Achievable – Low 52 186 570 936

Achievable – High 137 404 944 1,438

Economic 515 886 1,397 1,898

Northern Rio Arriba E Coop Inc

Achievable – Low 167 592 1,934 3,648

Achievable – High 464 1,334 3,427 6,307

Economic 1,630 2,812 4,963 8,254

Otero County Electric Coop Inc

Achievable – Low 683 2,422 8,077 15,611

Achievable – High 1,906 5,484 14,399 27,204

Economic 6,665 11,537 20,837 35,722

Raton Public Service Company

Achievable – Low 195 694 2,225 4,038

Achievable – High 536 1,562 3,916 6,863

Economic 1,872 3,304 5,716 9,010

Rio Grande Electric Coop, Inc

Achievable – Low 10 36 115 212

Achievable – High 27 78 196 348

Economic 101 169 285 457

Socorro Electric Coop, Inc

Achievable – Low 649 2,324 7,438 13,352

Achievable – High 1,793 5,335 13,438 23,161

Economic 5,869 11,130 19,802 30,676

Southwestern Electric Coop Inc

Achievable – Low 627 1,991 10,002 30,677

Achievable – High 2,347 6,173 24,438 69,785

Economic 4,140 9,702 33,470 91,127

Springer Electric Coop, Inc

Achievable – Low 427 1,399 6,349 17,961

Achievable – High 1,500 4,057 14,823 39,824

Economic 3,019 6,792 20,543 52,084
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Utility Type 2012 2015 2020 2025

Springer, Town of

Achievable – Low 22 80 243 391

Achievable – High 59 174 403 600

Economic 218 381 598 791

Tri‐County Electric Coop, Inc

Achievable – Low 0 0 1 2

Achievable – High 0 1 2 3

Economic 1 2 3 3

City of Truth or Consequences

Achievable – Low 184 669 2,045 3,283

Achievable – High 493 1,514 3,593 5,342

Economic 1,640 3,223 5,408 7,170

Roosevelt County Elec Coop Inc

Achievable – Low 465 1,596 6,089 14,347

Achievable – High 1,433 3,989 12,342 28,684

Economic 4,101 7,654 17,427 37,549

Sierra Electric Coop, Inc

Achievable – Low 164 595 1,830 3,006

Achievable – High 437 1,310 3,098 4,723

Economic 1,579 2,843 4,613 6,279

Western Area Power

Administration

Achievable – Low 585 2,173 6,311 8,783

Achievable – High 1,601 5,425 12,720 16,330

Economic 3,335 10,699 19,907 22,755

Grand Total

Achievable – Low 66,580 246,415 809,798 1,472,909

Achievable – High 187,026 573,143 1,488,190 2,655,516

Economic 575,746 1,171,136 2,169,742 3,509,632
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Table 6-4 presents the peak demand savings from energy-efficiency measures for each entity. 

Table 6-4 Energy Efficiency Potential by Entity (Peak Demand Savings MW) 

Utility Type 2012 2015 2020 2025

IOUs

PNM

Achievable ‐ Low 3.01 12.06 43.73 79.60

Achievable – High 8.42 28.60 81.59 144.34

Economic 24.44 59.01 121.26 197.49

SPS

Achievable ‐ Low 0.98 3.91 17.66 38.56

Achievable – High 2.96 9.82 34.10 74.67

Economic 7.95 20.14 49.78 99.91

El Paso

Achievable ‐ Low 0.45 1.77 6.67 13.31

Achievable – High 1.29 4.37 13.34 25.47

Economic 3.68 9.03 20.25 35.20

Non IOU

Aztec City of

Achievable ‐ Low 0.02 0.06 0.20 0.33

Achievable – High 0.04 0.15 0.38 0.59

Economic 0.13 0.30 0.58 0.81

Central New Mexico El Coop, Inc

Achievable – Low 0.07 0.28 1.10 2.43

Achievable – High 0.21 0.66 2.07 4.45

Economic 0.66 1.38 3.06 6.05

Central Valley Electric Coop, Inc

Achievable – Low 0.13 0.46 2.09 5.61

Achievable – High 0.45 1.31 4.77 12.27

Economic 0.95 2.33 6.80 16.42

Columbus Electric Coop, Inc

Achievable – Low 0.03 0.12 0.45 0.84

Achievable – High 0.09 0.31 0.91 1.61

Economic 0.24 0.64 1.40 2.25

Continental Divide El Coop Inc

Achievable – Low 0.12 0.46 1.78 3.86

Achievable – High 0.37 1.14 3.54 7.44

Economic 1.01 2.30 5.25 10.13

Duncan Valley Elec Coop, Inc

Achievable – Low 0.00 0.00 0.02 0.05

Achievable – High 0.00 0.01 0.04 0.09

Economic 0.01 0.02 0.05 0.12

Farmers' Electric Coop, Inc

Achievable – Low 0.10 0.37 1.52 3.51

Achievable – High 0.31 0.97 3.18 7.10

Economic 0.77 1.89 4.70 9.66

City of Farmington

Achievable – Low 0.32 1.18 4.19 8.50

Achievable – High 0.96 2.99 8.66 17.04

Economic 2.43 5.87 12.89 23.02

City of Gallup

Achievable – Low 0.09 0.34 1.12 1.94

Achievable – High 0.25 0.84 2.27 3.71

Economic 0.62 1.70 3.52 5.18

Jemez Mountains Elec Coop, Inc Achievable – Low 0.12 0.46 1.54 2.73

Achievable – High 0.34 1.09 2.87 4.81
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Economic 1.05 2.29 4.34 6.54

Utility Type 2012 2015 2020 2025

Kit Carson Electric Coop, Inc

Achievable – Low 0.10 0.36 1.25 2.36

Achievable – High 0.28 0.86 2.36 4.28

Economic 0.85 1.80 3.53 5.79

Lea County Electric Coop, Inc

Achievable – Low 0.23 0.85 3.12 6.42

Achievable – High 0.69 2.27 6.89 13.68

Economic 1.52 4.36 10.43 18.82

Los Alamos County

Achievable – Low 0.10 0.34 1.48 3.91

Achievable – High 0.34 0.96 3.36 8.59

Economic 0.72 1.69 4.76 11.41

Mora‐San Miguel Elec Coop, Inc

Achievable – Low 0.02 0.09 0.31 0.58

Achievable – High 0.06 0.20 0.52 0.94

Economic 0.24 0.44 0.77 1.26

Navajo Tribal Utility Authority

Achievable – Low 0.04 0.14 0.49 0.96

Achievable – High 0.11 0.35 0.98 1.84

Economic 0.31 0.71 1.47 2.49

Navopache Electric Coop, Inc

Achievable – Low 0.00 0.02 0.06 0.12

Achievable – High 0.01 0.03 0.10 0.20

Economic 0.04 0.08 0.16 0.28

Northern Rio Arriba E Coop Inc

Achievable – Low 0.01 0.05 0.17 0.35

Achievable – High 0.04 0.11 0.31 0.64

Economic 0.12 0.23 0.46 0.86

Otero County Electric Coop Inc

Achievable – Low 0.05 0.20 0.89 2.12

Achievable – High 0.16 0.49 1.67 3.85

Economic 0.50 1.03 2.44 5.25

Raton Public Service Company

Achievable – Low 0.02 0.06 0.20 0.40

Achievable – High 0.04 0.13 0.37 0.72

Economic 0.14 0.28 0.55 0.97

Rio Grande Electric Coop, Inc

Achievable – Low 0.00 0.00 0.01 0.03

Achievable – High 0.00 0.01 0.02 0.05

Economic 0.01 0.01 0.03 0.07

Socorro Electric Coop, Inc

Achievable – Low 0.06 0.21 0.81 1.69

Achievable – High 0.16 0.52 1.56 3.13

Economic 0.48 1.07 2.34 4.28

Southwestern Electric Coop Inc

Achievable – Low 0.06 0.20 1.04 3.21

Achievable – High 0.24 0.64 2.55 7.43

Economic 0.41 1.00 3.52 9.81

Springer Electric Coop, Inc

Achievable – Low 0.04 0.14 0.66 1.89

Achievable – High 0.15 0.42 1.56 4.28

Economic 0.29 0.69 2.18 5.67
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Utility Type 2012 2015 2020 2025

Springer, Town of

Achievable – Low 0.00 0.01 0.02 0.04

Achievable – High 0.00 0.01 0.04 0.06

Economic 0.02 0.03 0.06 0.09

Tri‐County Electric Coop, Inc

Achievable – Low 0.00 0.00 0.00 0.00

Achievable – High 0.00 0.00 0.00 0.00

Economic 0.00 0.00 0.00 0.00

City of Truth or Consequences

Achievable – Low 0.02 0.07 0.26 0.51

Achievable – High 0.05 0.16 0.50 0.94

Economic 0.14 0.35 0.76 1.30

Roosevelt County Elec Coop Inc

Achievable – Low 0.04 0.14 0.66 1.74

Achievable – High 0.13 0.37 1.37 3.53

Economic 0.33 0.71 1.96 4.74

Sierra Electric Coop, Inc

Achievable – Low 0.01 0.05 0.22 0.46

Achievable – High 0.04 0.13 0.40 0.80

Economic 0.13 0.28 0.60 1.10

Western Area Power

Administration

Achievable – Low 0.08 0.29 0.90 1.36

Achievable – High 0.22 0.75 1.94 2.78

Economic 0.45 1.48 3.04 3.91

Grand Total

Achievable – Low 6.34 24.72 94.61 189.42

Achievable – High 18.42 60.67 184.23 361.32

Economic 50.64 123.14 272.92 490.86

6.2 ELECTRICITY RESIDENTIAL SECTOR 

Table 6-5 presents estimates for the four types of potential. Figure 6-4 depicts the potential 

energy savings estimates graphically. 

• Achievable - Low potential projects 36 GWh of energy savings in 2012, 0.5% of the 

baseline forecast. This increases to 684 GWh, 9.2% of the baseline forecast, in 2025. Peak 

demand savings under the Achievable - Low potential are projected to be 2 MW, 0.2% of the 

baseline peak demand forecast, in 2012. The savings increase to 83 MW by 2025 or 5.5% of 

the baseline forecast. Peak demand savings are lower than energy savings because the 

majority of savings come from lighting and the lighting peak is not coincident with the 

system peak. 

• Achievable - High potential is 95 GWh in 2012, which represents 1.4% of the baseline 

forecast. By 2025, the cumulative energy savings are 990 GWh, 13.3% of the baseline 

forecast. Peak demand savings are 6 MW, which represents 0.5% of the baseline forecast of 

peak demand. By 2025, peak demand savings reach 127 MW, 8.5% of the baseline peak 

demand forecast. 

• Economic potential, which reflects the savings when all cost-effective measures are taken, 

is 398 GWh in 2012. This represents 6% of the baseline energy forecast. By 2025, economic 

potential reaches 1.275 GWh, 17.2% of the baseline energy forecast. Peak demand savings 

in 2012 are 27 MW, which represents 2.0% of the baseline forecast of peak demand. By 

2025, peak demand savings reach 169 MW, 11.6% of the baseline peak demand forecast. 

• Technical potential, which reflects the adoption of all energy efficiency measures 

regardless of cost is a theoretical upper bound on savings. In 2012, energy savings are 489 

GWh, or 7.4% of the baseline energy forecast. By 2025, technical potential reaches 1,752 
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GWh, 23.6% of the baseline energy forecast. Peak demand savings are 41 MW in 2012, 

which represents 3.1% of the baseline forecast of peak demand. By 2025, peak demand 

savings reach 395 MW or 26.4% of the baseline peak demand forecast. The fact that peak 

demand savings under technical potential are relatively higher than the other types of 

potential reflects the fact that there are several air-conditioning related measures that are 

available but not cost effective. 

Figure 6-5 shows the forecasts under the four types of potential along with the baseline forecast. 

Table 6-5 Electricity Energy Efficiency Potential for the Residential Sector 

2012 2015 2020 2025

Baseline Forecast 6,646 6,539 7,035 7,421

Energy Savings (GWh)

Achievable ‐ Low 36 137 428 684

Achievable ‐ High 95 281 651 990

Economic 398 631 925 1,275

Technical 489 904 1,422 1,752

Energy Savings (% of Baseline)

Achievable ‐ Low 0.5% 2.1% 6.1% 9.2%

Achievable ‐ High 1.4% 4.3% 9.3% 13.3%

Economic 6.0% 9.7% 13.1% 17.2%

Technical 7.4% 13.8% 20.2% 23.6%

Peak Savings (MW)

Achievable ‐ Low 2 10 42 83

Achievable ‐ High 6 21 65 127

Economic 27 48 92 169

Technical 41 101 225 395

Peak Savings (% of Baseline)

Achievable ‐ Low 0.2% 0.7% 3.0% 5.5%

Achievable ‐ High 0.5% 1.5% 4.6% 8.5%

Economic 2.0% 3.6% 6.6% 11.3%

Technical 3.1% 7.5% 16.2% 26.4%
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Figure 6-4 Residential Energy Efficiency Potential Savings 

Achievable ‐ Low

Achievable ‐ High

Economic

Technical

0%

5%

10%

15%

20%

25%

2012 2015 2020 2025

Savings as

% of Baseline Forecast

Figure 6-5 Residential Energy Efficiency Potential Forecast 

3,000

3,500

4,000

4,500

5,000

5,500

6,000

6,500

7,000

7,500

8,000

2012 2014 2016 2018 2020 2022 2024

GWh

Baseline Forecast

Achievable ‐ Low

Achievable ‐ High

Economic

Technical
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6.2.1 Residential Potential by Market Segment 

Single-family homes in New Mexico account for almost half 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, displayed in Table 6-6. 

Table 6-7 shows the savings by end use and market segment. The segments are similar in terms 

of the 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 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. Low income has a relatively larger opportunity in appliances and air 

conditioning compared to the other segments, again reflecting older appliance age. 

Table 6-6 Residential Potential by Market Segment, 2025 

Single

Family

Multi

Family

Mobile

Home

Low

Income Total

Baseline Forecast 2,574 650 689 3,508 7,421

Energy Savings (GWh)

Achievable ‐ Low 254 54 52 325 684

Achievable ‐ High 371 79 76 464 990

Economic 473 103 100 598 1,275

Technical 618 159 158 817 1,752

Energy Savings (% of Baseline)

Achievable ‐ Low 9.9% 8.2% 7.5% 9.3% 9.2%

Achievable ‐ High 14.4% 12.2% 11.0% 13.2% 13.3%

Economic 18.4% 15.9% 14.5% 17.1% 17.2%

Technical 24.0% 24.4% 23.0% 23.3% 23.6%

Table 6-7 Residential Achievable Potential by End Use and Market Segment, 2025 

Range of Achievable Energy

Savings (GWh) Single Family Multi Family Low Income Total

Cooling 17 – 28 2‐3 4‐6 23‐37

Space heating 8‐14 2‐3 3‐5 13‐22

Heat/cool 10‐16 0.1‐0.2 0.4‐0.7 11‐17

Water heating 68‐102 15‐24 19‐29 103‐155

Appliances 48‐57 6‐7 2‐3 57‐68

Interior lighting 101‐139 16‐22 14‐19 131‐179

Exterior lighting 26‐34 3‐4 3‐4 32‐43

Electronics 31‐54 6‐11 5‐9 43‐74

Miscellaneous 15‐21 1‐1 2‐3 18‐24

Total 325‐464 52‐76 54‐79 430‐620
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6.2.2 Residential Potential by End Use, Technology and Measure Type 

Table 6-8 provides estimates of savings for each end use and type of potential. Focusing first on 

technical and economic potential, there are significant savings that are both possible and 

economic in numerous end uses: 

• Water Heating offers the highest technical potential, which reflects the across the boardinstallation of solar water heating. However, solar water heating does not become costeffective, using the study’s assumptions of equipment cost and avoided cost, during the 

forecast period. 

• Cooling offers the second-highest technical potential, which reflects across-the-board 

installation of SEER 20 in homes with central air conditioning, installation of room AC units 

with a SEER of 11.5 in homes with room AC, indirect evaporative coolers, central AC 

maintenance, installation of various insulation measures, installation of high-efficiency 

windows, and AC duct repair and maintenance. However, these most efficient equipment 

options do not pass the economic screen at any point during the forecast, nor do the higher 

levels of insulation. This results in economic potential that is less than half of technical 

potential. 

• Appliances are the third-highest end use in terms of technical potential savings. This 

reflects both the replacement of failed white-goods appliances with the highest-efficiency 

option and early replacement of refrigerators and removal of second refrigerators and 

freezers. 

• Interior lighting offers the fourth-largest potential savings. The lighting standard begins its 

phase-in starting in 2012, which coincides with the availability in the market place of 

advanced incandescent lamps that meet the minimum efficacy standard. The baseline 

forecast assumes that people will install both advanced incandescent and CFLs in screw-in 

lighting applications. For technical potential, LED lamps are the most efficient option, starting 

in 2012. However, LED lamps do not pass the economic screen until 2020, so CFLs dominate 

until 2019 when LED lamps pass the screen. 

• Home electronics also offer substantial savings opportunities. Technical potential reflects 

the purchase of ENERGY STAR units for all technologies, except PCs and laptops for which a 

super-efficient “climate saver” option is available in the marketplace. However, the climate 

saver options are not cost-effective during the forecast horizon, so economic potential 

reflects the purchase of ENERGY STAR units across all technologies in this end use. 
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Table 6-8 Residential Savings by End Use and Potential Type (GWh) 

End Use Case 2012 2015 2020 2025

Cooling

Achievable ‐ Low 0.1 1.0 15.2 42.4

Achievable ‐ High 0.3 2.2 24.2 68.7

Economic 1.6 5.9 33.7 96.1

Technical 10.6 41.8 134.5 291.2

Space Heating

Achievable ‐ Low 0.1 0.6 10.5 31.2

Achievable ‐ High 0.1 1.3 17.6 51.7

Economic 0.9 3.7 25.0 73.0

Technical 1.2 4.9 34.4 107.3

Heat/Cool

Achievable ‐ Low 0.1 0.8 7.0 17.6

Achievable ‐ High 0.3 1.9 11.0 26.7

Economic 1.4 5.0 15.5 32.8

Technical 3.7 15.8 41.9 79.9

Water Heating

Achievable ‐ Low 1.4 11.6 75.0 174.8

Achievable ‐ High 3.5 24.8 122.1 262.1

Economic 15.1 66.7 192.9 351.2

Technical 24.0 97.1 249.1 431.2

Appliances

Achievable ‐ Low 2.9 18.3 63.4 75.3

Achievable ‐ High 6.8 31.7 73.5 90.2

Economic 28.2 72.9 96.7 115.5

Technical 38.4 118.4 214.3 290.0

Interior Lighting

Achievable ‐ Low 24.0 70.8 166.7 212.0

Achievable ‐ High 63.3 144.4 249.8 290.4

Economic 258.0 270.6 294.0 315.9

Technical 301.3 370.1 408.3 228.1

Exterior Lighting

Achievable ‐ Low 5.0 16.7 39.7 50.3

Achievable ‐ High 13.2 34.0 59.3 67.9

Economic 54.0 62.9 69.5 72.5

Technical 65.2 88.0 95.6 50.2

Electronics

Achievable ‐ Low 2.6 16.0 41.8 59.7

Achievable ‐ High 7.2 39.0 80.8 103.6

Economic 37.0 135.0 169.3 165.1

Technical 37.9 135.9 170.2 165.4

Miscellaneous

Achievable ‐ Low 0.1 1.1 8.7 21.0

Achievable ‐ High 0.3 2.2 12.9 28.9

Economic 1.7 8.3 28.5 52.4

Technical 7.0 31.4 74.1 108.5

Total

Achievable ‐ Low 36 137 428 684

Achievable ‐ High 95 281 651 990

Economic 398 631 925 1,275

Technical 489 904 1,422 1,752
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Figure 6-6 focuses on the range of achievable potential between Achievable - High and 

Achievable - Low. 

• Lighting equipment replacement accounts for the highest portion of the savings as a result of 

the gap between advanced incandescent lamps and CFL lamps and LED lamps. The majority 

of lighting savings are captured by the Achievable - Low case. 

• Water heating also accounts for large savings since heat pump water heaters are cost 

effective starting in 2012. 

• Electronics, appliances, and cooling measures also contribute significantly to the savings, 

although there is considerable room for additional savings beyond the Achievable - Low case. 

• Because of the relatively small share of homes with electric space heating and the limited 

opportunity for higher efficiency equipment, there are only minor contributions from this end 

use. 

Figure 6-6 Residential Achievable Potential by End Use in 2025 

0

50

100

150

200

250

300

350

Savingsin2025 (GWh)

Achievable ‐ High

Achievable ‐ Low

As described in Chapter 4, using our LoadMAP model, we develop separate estimates of potential 

for equipment and non-equipment measures. Table 6-9 presents results for equipment at the 

technology level and Table 6-10 presents non-equipment measures for which Achievable - Low 

potential is greater than zero. The majority of the savings come from the equipment measures, 

with lighting and water heating leading the way. Electronics, appliances and pool pumps provide 

significant savings as well. 
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Table 6-9 Residential Achievable - Low Potential by Technology – Selected years 

(GWh) 

End Use Technology 2012 2015 2020 2025

Cooling

Central AC 0.01 0.06 0.06 0.06

Room AC 0.01 0.03 0.03 0.01

Combined

Heating/Cooling Central Heat Pump 0.10 0.60 2.88 8.92

Water Heating Water Heater 1.26 10.56 59.25 139.30

Appliances

Freezer 0.87 2.06 2.05 0.34

Refrigerator 0.26 0.66 0.66 0.47

Second Refrigerator 0.07 0.17 0.17 0.13

Interior Lighting

Linear Fluorescent 0.00 0.30 1.84 4.29

Screw‐in 23.99 70.25 162.50 203.14

Exterior Lighting Screw‐in 5.03 16.70 39.68 50.25

Electronics

Copier/Printer/Fax 0.04 0.13 0.12 0.16

DVD/VCR/Audio 1.12 6.76 21.01 35.50

Laptops 0.22 1.15 2.23 2.37

Monitor 0.01 0.08 0.23 0.30

Personal Computers 0.36 1.87 4.16 4.68

TVs 0.83 6.04 14.07 16.66

Miscellaneous

Pool Pump 0.10 0.91 4.67 10.16

Well Pump 0.01 0.20 3.65 9.73

Subtotal Equipment 34.29 118.54 319.25 486.47

Total Equipment and Non‐

Equipment measures

36.25 136.90 427.91 684.21
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Table 6-10 Residential Achievable - Low Savings for Non-equipment Measures (GWh) 

Measure 2012 2015 2020 2025

Second Refrigerator ‐ Removal 1.63 15.13 57.53 64.33

Insulation ‐ Wall Cavity (Good) 0.01 0.15 3.89 17.69

Ducting ‐ Repair and Sealing 0.04 0.53 8.54 14.54

Water Heating ‐ Low‐Flow Showerheads 0.02 0.24 4.25 10.24

Water Heating ‐ Tank Blanket 0.03 0.34 5.94 10.00

Freezer ‐ Removal 0.04 0.27 2.99 10.00

Insulation ‐ Ceiling (Good) 0.02 0.14 2.28 9.64

Thermostat ‐ Clock/Programmable 0.02 0.21 3.19 8.94

Home Energy Management System 0.02 0.18 2.57 8.84

Central Heat Pump ‐ Maintenance 0.02 0.21 4.16 8.71

Water Heating ‐ Thermostat Setback 0.03 0.22 2.69 7.41

Central AC ‐ Maintenance 0.02 0.25 3.62 6.20

Water Heating ‐ Faucet Aerators 0.01 0.10 1.65 3.96

Construction ‐ Advanced Design 0.00 0.03 0.67 3.24

Insulation ‐ Foundation (Good) 0.00 0.03 0.68 2.95

Interior Lighting ‐ Fluorescent Torchieres 0.03 0.14 1.55 2.64

Water Heating ‐ Timer 0.01 0.06 0.61 1.85

Household ‐ Weatherization 0.01 0.05 0.53 1.67

Water Heating ‐ Hot Water Saver 0.01 0.04 0.44 1.46

Pool Pump ‐ Timer 0.00 0.03 0.33 1.08

Insulation ‐ Hydronic Pipe Wrap 0.00 0.01 0.13 0.56

Water Heating ‐ Pipe Insulation 0.00 0.01 0.14 0.55

Insulation ‐ Wall Sheathing (Good) 0.00 0.01 0.13 0.54

Insulation ‐ Attic Hatch (Good) 0.00 0.01 0.09 0.35

Insulation ‐ Attic Hatch (Better) 0.00 0.00 0.03 0.16

Insulation ‐ Ducting (Better) 0.00 0.00 0.03 0.12

Windows ‐ Energy Star  ‐  ‐  0.00 0.02

Insulation ‐ Ducting (Good)  ‐  ‐  0.00 0.02

Subtotal Non‐Equipment Measures 1.96 18.36 108.66 197.74

Total Achievable ‐ Low 36.25 136.90 427.91 684.21

6.2.3 Residential Potential by Entity 

Table 6-11 presents the residential sector potential for each entity in the state. The estimates for 

the investor owned utilities were developed from the bottom-up using utility-specific data since 

the data were available. For the Non-IOUs, the estimates were developed by taking the total 

end-use estimates for the state and allocating them to each entity according to its share of total 

residential electricity use. Then, these estimates were adjusted to reflect weather differences 

between the entity’s area and the state as a whole. 
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Table 6-11 Residential Efficiency Potential by Entity (MWh) 

Utility Type 2012 2015 2020 2025

IOUs

PNM

Achievable ‐ Low 19,860 77,105 235,864 359,927

Achievable – High 52,053 157,232 353,166 516,647

Economic 218,157 349,611 493,274 660,124

SPS

Achievable ‐ Low 4,130 16,541 58,912 97,906

Achievable – High 10,795 34,073 89,904 142,230

Economic 45,495 79,359 131,643 186,053

El Paso

Achievable ‐ Low 2,924 9,866 30,139 52,616

Achievable – High 7,659 20,493 46,878 76,854

Economic 31,987 44,994 65,351 97,544

Non‐ IOU

Aztec City of

Achievable ‐ Low 100 356 1,092 1,825

Achievable – High 261 743 1,709 2,665

Economic 1,092 1,677 2,486 3,456

Central New Mexico El Coop, Inc

Achievable ‐ Low 652 2,331 7,205 12,192

Achievable – High 1,707 4,863 11,291 17,883

Economic 7,139 10,973 16,427 23,280

Central Valley Elec Coop, Inc

Achievable ‐ Low 361 1,295 4,046 6,929

Achievable – High 947 2,704 6,346 10,194

Economic 3,961 6,105 9,232 13,295

Columbus Electric Coop, Inc

Achievable ‐ Low 134 480 1,498 2,565

Achievable – High 351 1,001 2,349 3,774

Economic 1,467 2,260 3,418 4,922

Continental Divide El Coop Inc

Achievable ‐ Low 782 2,796 8,643 14,625

Achievable – High 2,048 5,834 13,545 21,452

Economic 8,564 13,163 19,706 27,927

Duncan Valley Elec Coop, Inc

Achievable ‐ Low 13 48 150 257

Achievable – High 35 100 235 378

Economic 147 226 342 493

Farmers' Electric Coop, Inc

Achievable ‐ Low 471 1,689 5,275 9,033

Achievable – High 1,234 3,525 8,273 13,290

Economic 5,164 7,960 12,036 17,333

City of Farmington

Achievable ‐ Low 1,555 5,556 17,020 28,450

Achievable – High 4,073 11,592 26,645 41,560

Economic 17,028 26,145 38,767 53,884

City of Gallup

Achievable ‐ Low 298 1,067 3,297 5,580

Achievable – High 781 2,226 5,167 8,184

Economic 3,267 5,022 7,518 10,654

Jemez Mountains Elec Coop, Inc

Achievable ‐ Low 999 3,569 10,934 18,277

Achievable – High 2,617 7,447 17,117 26,699

Economic 10,939 16,796 24,904 34,616

Kit Carson Electric Coop, Inc

Achievable ‐ Low 811 2,899 8,880 14,844

Achievable – High 2,125 6,048 13,902 21,684

Economic 8,884 13,641 20,226 28,114
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Utility Type 2012 2015 2020 2025

Lea County Electric Coop, Inc

Achievable ‐ Low 392 1,407 4,393 7,523

Achievable – High 1,028 2,936 6,890 11,068

Economic 4,301 6,629 10,024 14,436

Los Alamos County

Achievable ‐ Low 335 1,198 3,672 6,137

Achievable – High 879 2,501 5,748 8,965

Economic 3,673 5,640 8,363 11,624

Mora‐San Miguel Elec Coop, Inc

Achievable ‐ Low 307 1,095 3,356 5,610

Achievable – High 803 2,286 5,254 8,194

Economic 3,357 5,155 7,644 10,624

Navajo Tribal Utility Authority

Achievable ‐ Low 242 866 2,654 4,436

Achievable – High 635 1,808 4,155 6,481

Economic 2,655 4,077 6,045 8,402

Navopache Electric Coop, Inc

Achievable ‐ Low 42 149 462 781

Achievable – High 109 312 724 1,146

Economic 458 703 1,053 1,492

Northern Rio Arriba E Coop Inc

Achievable ‐ Low 127 453 1,389 2,322

Achievable – High 332 946 2,174 3,392

Economic 1,390 2,134 3,164 4,397

Otero County Electric Coop Inc

Achievable ‐ Low 517 1,854 5,790 9,916

Achievable – High 1,355 3,869 9,081 14,589

Economic 5,669 8,737 13,212 19,027

Raton Public Service Company

Achievable ‐ Low 143 511 1,566 2,618

Achievable – High 375 1,067 2,452 3,825

Economic 1,567 2,406 3,568 4,959

Rio Grande Electric Coop, Inc

Achievable ‐ Low 8 30 94 161

Achievable – High 22 63 147 237

Economic 92 142 215 309

Socorro Electric Coop, Inc

Achievable ‐ Low 406 1,452 4,490 7,597

Achievable – High 1,064 3,031 7,036 11,144

Economic 4,449 6,838 10,237 14,507

Southwestern Electric Coop Inc

Achievable ‐ Low 49 174 534 892

Achievable – High 128 364 836 1,303

Economic 534 820 1,216 1,690

Springer Electric Coop, Inc

Achievable ‐ Low 79 284 870 1,454

Achievable – High 208 592 1,361 2,124

Economic 870 1,336 1,981 2,753

Springer Town of

Achievable ‐ Low 17 62 191 319

Achievable – High 46 130 299 466

Economic 191 293 435 604

Tri‐County Electric Coop, Inc

Achievable ‐ Low 0 0 1 2

Achievable – High 0 1 2 2

Economic 1 2 2 3

City of Truth or Consequences

Achievable ‐ Low 112 400 1,250 2,140

Achievable – High 292 835 1,960 3,149

Economic 1,224 1,886 2,852 4,107
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Utility Type 2012 2015 2020 2025

Roosevelt County Elec Coop Inc

Achievable ‐ Low 258 924 2,885 4,941

Achievable – High 675 1,928 4,525 7,269

Economic 2,825 4,354 6,583 9,481

Sierra Electric Coop, Inc

Achievable ‐ Low 122 436 1,362 2,333

Achievable – High 319 910 2,137 3,433

Economic 1,334 2,056 3,109 4,477

Total

Achievable ‐ Low 36,247 136,896 427,910 684,209

Achievable – High 94,958 281,458 651,310 990,281

Economic 397,880 631,137 925,030 1,274,585

6.3 COMMERCIAL SECTOR POTENTIAL 

The baseline forecast for the commercial sector essentially remains flat, which reflects the 

sluggish economy, building codes, and relatively efficient energy-use patterns. Nevertheless, the 

opportunity for energy-efficiency savings is still significant for the commercial sector. 

• Achievable - Low potential projects 23 GWh of energy savings in 2012 and 361 GWh in 

2025. This corresponds to 0.3% of the baseline forecast in 2012 and 4.6% in 2025. Peak 

demand savings under Achievable - Low are projected to be 3 MW, 0.2% of the baseline 

peak demand forecast, in 2012. The savings increase to 63 MW or 4.6% of the baseline 

forecast by 2025. 

• Achievable - High potential is 63 GWh in 2012, which represents 0.8% of the baseline 

forecast. By 2025, the cumulative energy savings are 681 GWh, 8.7% of the baseline 

forecast. In 2012, peak demand savings are 9 MW, which represents 0.7% of the baseline 

forecast of peak demand. By 2025, peak demand savings reach 134 MW, 9.8% of the 

baseline peak demand forecast. 

• Economic potential, which reflects the savings when all cost-effective measures are taken, 

is 130 GWh in 2012. This represents 1.8% of the baseline energy forecast. By 2025, 

economic potential reaches 950 GWh, 12.1% of the baseline energy forecast. Peak demand 

savings in 2012 are 19 MW, which represents 1.4% of the baseline forecast of peak demand. 

By 2025, peak demand savings reach 189 MW, 13.8% of the baseline peak demand forecast. 

• Technical potential, which reflects the adoption of all energy efficiency measures 

regardless of cost, is a theoretical upper bound on savings. In 2012, energy savings are 144 

GWh, or 1.9% of the baseline energy forecast. By 2025, technical potential reaches 1,425 

GWh, 18.1% of the baseline energy forecast. Peak demand savings are 21 MW in 2012, 

which represents 1.6% of the baseline forecast of peak demand. By 2025, peak demand 

savings reach 264 MW or 19.3% of the baseline peak demand forecast. 

Table 6-12 and Figure 6-7 present the savings associated with each level of potential. 
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Table 6-12 Energy Efficiency Potential for the Commercial Sector 

Forecasts (GWh) 2012 2015 2020 2025

Baseline Forecast 7,410 7,285 7,623 7,871

Savings (GWh)

Achievable ‐ Low 23 86 253 361

Achievable ‐ High 63 215 513 681

Economic 130 424 804 950

Technical 144 468 1,014 1,425

Savings (% of Baseline)

Achievable ‐ Low 0.3% 1.2% 3.3% 4.6%

Achievable ‐ High 0.8% 3.0% 6.7% 8.7%

Economic 1.8% 5.8% 10.5% 12.1%

Technical 1.9% 6.4% 13.3% 18.1%

Savings (MW)

Achievable ‐ Low 3 12 39 63

Achievable ‐ High 9 32 87 134

Economic 19 64 136 189

Technical 21 72 170 264

Savings (% of Baseline)

Achievable ‐ Low 0.2% 1.0% 2.9% 4.6%

Achievable ‐ High 0.7% 2.5% 6.5% 9.8%

Economic 1.4% 4.9% 10.1% 13.8%

Technical 1.6% 5.5% 12.6% 19.3%

Figure 6-7 Commercial Energy Efficiency Potential Savings 

Achievable‐ Low

Achievable‐High

Economic

Technical

0%

5%

10%

15%

20%

2012 2015 2020 2025

Savings as

% of Baseline Forecast
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Figure 6-8 Commercial Energy Efficiency Potential Forecast 

‐

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

2009 2011 2013 2015 2017 2019 2021 2023 2025

GWh

Baseline Forecast

Achievable‐ Low

Achievable‐High

Economic

Technical

6.3.1 Commercial Potential by End Use, Technology, and Measure Type 

Table 6-13 presents the commercial sector savings by end use and potential type. The end uses 

with the highest technical and economic potential are: 

• Interior lighting, as a result of LED lighting that is now commercially available in screw-in and 

linear lighting applications, has the highest technical potential at 548 GWh in 2025. However, 

linear LED lighting is not cost effective, so economic potential reflects installation of T5 lamps 

throughout most of the commercial sector. Still, this results in economic potential of 277 

GWh, which is 51% of technical potential. 

• Cooling has the second highest savings for technical potential at 297 GWh in 2025. These 

savings result from installation of high-efficiency equipment and numerous thermal shell 

measures, HVAC control strategies, and retrocommissioning. Many of these measures are 

cost-effective, resulting in economic potential savings of 225 GWh in 2025, or 76% of 

technical potential savings. 

• Exterior lighting takes third place for technical potential savings at 142 GWh in 2025. The 

savings result from LED lighting that is commercially available. Most of these measures are 

cost effective, resulting in economic potential of 126 GWh in 2025, which represents 89% of 

technical potential. 

Commercial refrigeration, water heating and combined heating and cooling also have significant 

savings in terms of technical and economic potential. The savings potential from space heating, 

ventilation, food preparation, office equipment, and miscellaneous uses are relatively small. 

Figure 6-9, Table 6-14, and Table 6-15 focus on achievable potential savings. Figure 6-9 

compares the range of potential in 2025. Not surprisingly, lighting delivers the highest achievable 

savings. Cooling and exterior lighting are next highest in terms of Achievable - Low potential, 

followed by water heating and refrigeration. 
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Table 6-13 Commercial Potential by End Use and Potential Type (GWh) 

End Use Case 2012 2015 2020 2025

Cooling

Achievable ‐ Low 1.2 5.4 24.7 60.4

Achievable ‐ High 5.2 18.3 70.5 161.2

Economic 10.1 34.4 108.8 225.3

Technical 13.1 44.2 139.5 296.8

Space Heating

Achievable ‐ Low 0.0 0.2 1.4 5.0

Achievable ‐ High 0.2 0.9 4.8 16.2

Economic 0.4 1.3 6.1 19.8

Technical 0.7 1.8 8.3 27.1

Combined Heating/Cooling

Achievable ‐ Low 0.2 1.1 5.5 10.6

Achievable ‐ High 0.8 3.9 17.4 30.9

Economic 1.7 7.3 25.3 42.0

Technical 2.9 13.6 37.8 60.5

Ventilation

Achievable ‐ Low 0.2 0.7 1.5 1.9

Achievable ‐ High 0.6 2.0 3.7 4.9

Economic 1.3 4.3 7.4 9.0

Technical 2.5 7.2 20.0 51.6

Water Heating

Achievable ‐ Low 0.9 4.3 12.1 23.3

Achievable ‐ High 2.6 11.7 29.0 50.8

Economic 6.0 25.7 58.3 95.9

Technical 6.0 26.0 59.4 97.2

Food Preparation

Achievable ‐ Low 0.6 2.6 6.7 10.5

Achievable ‐ High 1.8 7.2 16.0 22.6

Economic 3.9 14.8 30.7 40.5

Technical 3.9 14.8 30.7 40.5

Refrigeration

Achievable ‐ Low 0.6 2.9 8.2 14.3

Achievable ‐ High 2.1 8.9 21.8 35.1

Economic 4.5 18.4 42.1 63.9

Technical 6.9 27.9 64.9 101.5

Interior Lighting

Achievable ‐ Low 12.1 41.7 137.4 168.9

Achievable ‐ High 31.1 96.8 243.1 246.3

Economic 61.7 178.7 339.2 277.2

Technical 66.3 191.1 455.8 547.5

Exterior Lighting

Achievable ‐ Low 3.9 15.2 42.6 53.1

Achievable ‐ High 9.9 35.4 80.2 85.6

Economic 19.9 67.1 131.4 126.1

Technical 20.2 67.7 138.4 141.5

Office Equipment

Achievable ‐ Low 2.8 11.0 10.1 8.5

Achievable ‐ High 7.8 28.2 21.1 16.9

Economic 19.8 68.0 42.8 30.6

Technical 20.0 68.3 44.3 36.5

Miscellaneous

Achievable ‐ Low 0.1 0.6 2.4 4.8

Achievable ‐ High 0.4 1.7 5.8 10.7

Economic 1.0 3.8 11.6 20.2

Technical 1.4 5.4 14.8 24.3

Total

Achievable ‐ Low 22.7 85.7 252.6 361.2

Achievable ‐ High 62.5 215.0 513.3 680.6

Economic 130.2 423.8 803.7 949.8

Technical 144.0 467.9 1,014.0 1,425.0
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Figure 6-9 Commercial Achievable Potential Savings by End Use in 2025 (GWh) 

0

50

100

150

200

250

300

Savings in 2025 (GWh)

Acheivable‐ High

Achievable‐ Low

Table 6-14 and Table 6-15 present achievable potential savings for equipment measures and 

non-equipment measures, respectively, under the Achievable - Low case. The greatest savings in 

2025 come from: 

• Replacement of interior screw-in lighting systems (138 GWh) 

• Replacement of exterior lighting systems with HID lamps (34 GWh) 

• Installation of an energy management system (24 GWh) 

• Replacement of water heating equipment (23 GWh) 

Together, these four measures account for more than 60% of the Achievable - Low potential 

savings in the commercial sector in 2025. 
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Table 6-14 Commercial Achievable - Low Savings for Equipment Measures (GWh) 

End Use Technology 2012 2015 2020 2025

Cooling

Air‐Cooled Chiller 0.2 0.8 2.2 3.6

Evaporative AC 0.0 0.0 0.1 0.2

PTAC 0.0 0.1 0.3 0.5

RTU 0.4 1.8 5.7 11.4

Water‐Cooled Chiller 0.3 1.1 3.3 6.3

Combined Heating/Cooling

Heat Pump 0.1 0.7 2.2 3.8

PTHP 0.1 0.1 0.3 0.4

Ventilation Ventilation 0.2 0.7 1.4 1.6

Water Heating Water Heater 0.9 4.3 11.9 22.7

Food Preparation

Dishwasher 0.0 0.1 0.3 0.4

Fryer 0.1 0.5 1.2 1.9

Hot Food Container 0.3 1.2 2.9 4.5

Oven 0.2 0.9 2.2 3.6

Refrigeration

Glass Door Display  ‐  ‐  ‐  0.0

Icemaker 0.0 0.2 0.5 0.8

Open Display Case 0.1 0.6 1.8 3.1

Reach‐in Refrigerator 0.1 0.4 1.0 1.7

Walk‐in Refrigerator 0.4 1.7 4.9 8.4

Interior Lighting

High‐Bay Fixtures 0.3 1.4 3.9 5.2

Linear Fluorescent 0.8 3.2 9.7 14.7

Screw‐in 10.8 36.5 119.3 137.5

Exterior Lighting

HID 2.4 9.5 25.3 33.6

Linear Fluorescent 0.0 0.1 0.3 0.5

Screw‐in 1.5 5.5 16.7 17.7

Office Equipment

Desktop Computer 1.1 4.4 3.9 3.8

Laptop 0.1 0.4 0.4 0.4

Monitor 0.0 0.2 0.2 0.2

POS Terminal 0.1 0.3 0.4 0.5

Printer/Copier/Fax 0.1 0.1 0.1 0.1

Server 1.4 5.6 5.0 3.0

Miscellaneous

Non‐HVAC Motors  ‐  ‐  0.0 0.3

Pool Heater 0.1 0.3 0.9 1.8

Pool Pump 0.1 0.4 1.4 2.7

Subtotal Equipment 22.1 83.1 229.8 297.0

Total Equipment and Non‐Equipment measures 22.7 85.7 252.6 361.2
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Table 6-15 Commercial Achievable - Low Savings for Non-equipment Measures (GWh) 

Measure 2012 2015 2020 2025

Energy Management System 0.3 1.0 6.9 24.0

RTU ‐ Maintenance 0.0 0.3 3.5 6.7

Heat Pump ‐ Maintenance 0.0 0.2 3.0 5.9

Air Cooled Chiller ‐ VSD 0.1 0.2 1.3 4.6

Air Cooled Chiller ‐ Economizer 0.0 0.1 1.1 3.0

Interior Lighting ‐ LED Exit Lighting 0.0 0.2 2.0 2.5

Water Cooled Chiller ‐ Economizer 0.0 0.1 0.8 2.4

Advanced New Construction Designs 0.0 0.0 0.4 2.1

Water Cooled Chiller ‐ VSD 0.0 0.1 0.5 1.8

Insulation ‐ Wall Cavity (Good) 0.0 0.0 0.4 1.7

Air Cooled Chiller ‐ Condenser Air Temperature Reset 0.0 0.1 0.4 1.1

Windows ‐ High Efficiency 0.0 0.0 0.3 1.1

Thermostat ‐ Clock/Programmable 0.0 0.1 0.5 0.9

Insulation ‐ Wall Cavity (Better) 0.0 0.0 0.2 0.9

Indoor Lighting ‐ Daylighting Controls 0.0 0.1 0.3 0.7

Roofs ‐ High Reflectivity 0.0 0.0 0.2 0.7

Lighting Commissioning 0.0 0.0 0.1 0.7

Office Equipment ‐ Energy Star Power Supplies 0.0 0.0 0.1 0.5

Water Heating ‐ Faucet Aerators 0.0 0.0 0.2 0.5

Water Cooled Chiller ‐ Condenser Water Temperature Reset 0.0 0.0 0.1 0.4

Insulation ‐ Wall Cavity (Best) 0.0 0.0 0.1 0.3

Interior Fluorescent ‐ Photocell‐Controlled Diming Ballasts 0.0 0.0 0.1 0.3

Custom Measures  ‐  0.0 0.1 0.3

Open Display Case ‐ Night Covers 0.0 0.0 0.1 0.2

Insulation ‐ Ceiling (Good) 0.0 0.0 0.1 0.2

Ventilation ‐ CO2 Controlled 0.0 0.0 0.1 0.2

Lighting Retrocommissioning 0.0 0.0 0.0 0.1

Pool Pump ‐ Timer 0.0 0.0 0.0 0.1

Water Heating ‐ Hot Water Saver 0.0 0.0 0.0 0.1

Ventilation ‐ Variable Speed Control  ‐  ‐  ‐  0.1

Insulation ‐ Ceiling (Better) 0.0 0.0 0.0 0.1

Space Heating ‐ Heat Recovery Ventilator 0.0 0.0 0.0 0.1

Ventilation ‐ Exhaust Hood Sensor Control 0.0 0.0 0.0 0.1

Comprehensive Retrocommissioning  ‐  ‐  ‐  0.0

Water Heating ‐ Tank Blanket 0.0 0.0 0.0 0.0

Insulation ‐ Ceiling (Best) 0.0 0.0 0.0 0.0

Water Heating ‐ Drainwater Heat Recovery 0.0 0.0 0.0 0.0

Water Heating ‐ Pipe Insulation  ‐  ‐  0.0 0.0

Subtotal for Non‐Equipment Measures 0.6 2.7 22.8 64.4

Total Achievable‐ Low 22.7 85.7 252.6 361.2
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6.3.2 Commercial Potential by Market Segment 

Table 6-16 shows potential estimates by segment. Retail has the largest savings potential in 

2025 with 77 GWh-130 GWh. The achievable savings for retail are 21% of the overall C&I 

Achievable - Low potential and 7.9% of the Retail segment baseline forecast. Retail and Lodging 

have the highest Achievable - Low potential as a percent of the baseline forecast with 7.9%, 

followed by Offices (Small and Large combined) with 6.9%. 

Table 6-16 Commercial Potential by Market Segment, 2025 

Forecast Small Office Large Office Restaurant Retail Grocery Warehouse

Baseline Forecast (GWh) 581 1,107 605 974 739 557

Energy Savings (GWh)

Achievable ‐ Low 23 32 30 77 31 28

Achievable ‐ High 46 66 63 130 68 46

Economic Potential 67 95 89 166 96 66

Technical Potential 101 168 107 228 146 112

Energy Savings as % of Baseline

Achievable ‐ Low 4.0% 2.9% 5.0% 7.9% 4.2% 5.0%

Achievable ‐ High 7.9% 5.9% 10.4% 13.4% 9.1% 8.3%

Economic Potential 11.5% 8.5% 14.7% 17.0% 13.0% 11.9%

Technical Potential 17.4% 15.2% 17.7% 23.5% 19.7% 20.1%

School College Health Lodging Miscella‐ 

neous Total

Baseline Forecast (GWh) 441 363 785 432 1,285 7,871

Energy Savings (GWh)

Achievable ‐ Low 16 16 33 34 42 361

Achievable ‐ High 28 28 72 58 77 681

Economic Potential 43 39 97 76 116 950

Technical Potential 91 68 133 87 183 1,425

Energy Savings as % of Baseline

Achievable ‐ Low 3.6% 4.5% 4.2% 7.9% 3.2% 4.6%

Achievable ‐ High 6.4% 7.8% 9.1% 13.4% 6.0% 8.7%

Economic Potential 9.8% 10.7% 12.4% 17.5% 9.0% 12.1%

Technical Potential 20.6% 18.6% 17.0% 20.1% 14.3% 18.1%

Figure 6-10 summarizes the range of achievable potential for each segment. The Retail segment 

has the largest potential, followed by miscellaneous, lodging, health, and large offices. 
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Figure 6-10 Achievable Potential Savings in 2025 by Commercial Building Type (GWh) 

0

10

20

30

40

50

60

70

80

90

100

Realistic Achievable Savings in 2025

Achievable ‐ Low

Achievable ‐High

The Table 6-17 and Table 6-18 presents the achievable potential for 2025 by measure and 

building type. Lighting replacement and upgrade, particularly for screw-in lamps, is a key 

measure across all buildings. In addition to lighting, the key measures for each building type are 

as follows: 

• Offices: Cooling equipment upgrade and energy management systems 

• Restaurants: Rooftop HVAC units, food preparation equipment, walk-in refrigeration 

upgrade 

• Grocery: Refrigeration, particularly walk-in refrigeration, and water heating 

• Warehouse: Refrigeration equipment upgrade 

• Schools: Heat pump maintenance, water heating equipment upgrade 

• Colleges: Energy management systems, variable speed drives on chillers 

• Health: Energy management systems, variable speed drives on chillers, chiller upgrade 

• Lodging: Heat pump equipment upgrade, high-efficiency pool pump motors 
Electric Energy Efficiency Potential Results State of 

6-30 Table 6-17 Commercial Achievable Savings from Equipment Measures in 2025 by Building Type (GWh)  Small Office Large Office Restaurant Retail Grocery Warehouse School College Heal Low High Low High Low High Low High Low High Low High Low High Low High Low Cooling 2.3 5.1 3.5 7.9 2.5 6.3 3.6 7.7 0.1 0.1 1.5 3.3 0.9 1.7 1.0 1.9 2.0 Air-Cooled Chiller 1.0 2.3 - - 0.0 0.0 0.3 0.6 0.0 0.1 - - 0.2 0.4 0.2 0.4 1.7 Evaporative AC - - - - - - - - - - 0.1 0.3 - - - - 0.0 PTAC 0.0 0.0 0.0 0.0 0.1 0.2 0.1 0.1 - - 0.0 0.0 - - - - 0.0 RTU 1.0 2.2 2.0 4.4 2.4 6.0 3.1 6.5 - - 0.6 1.4 - - - - 0.3 Water-Cooled Chiller 0.2 0.6 1.5 3.5 0.0 0.0 0.2 0.4 0.0 0.0 0.7 1.5 0.7 1.3 0.8 1.6 0.0 Combined Heating/Cooling 0.4 0.8 0.1 0.1 0.0 0.1 0.3 0.7 0.7 1.4 0.1 0.2 - - - - 0.1 Heat Pump 0.4 0.8 0.1 0.1 0.0 0.1 0.3 0.7 0.7 1.4 0.1 0.2 - - - - 0.1 PTHP 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - - 0.0 0.0 - - - - 0.0 Ventilation 0.2 0.4 0.1 0.2 0.1 0.3 0.3 0.6 0.1 0.2 0.1 0.2 0.1 0.2 0.1 0.1 0.0 Water Heating 1.4 3.2 2.2 5.0 1.7 4.5 4.6 9.8 3.7 7.7 2.6 5.9 1.8 3.4 1.0 1.8 0.3 Food Preparation 0.2 0.4 0.2 0.4 5.9 11.8 0.4 0.9 1.0 2.7 0.0 0.1 1.0 2.0 0.3 0.5 0.5 Dishwasher 0.0 0.0 0.0 0.0 0.1 0.2 0.1 0.2 0.0 0.1 0.0 0.0 0.0 0.1 0.0 0.0 0.1 Fryer 0.1 0.2 0.1 0.1 1.2 2.4 0.0 0.1 0.2 0.6 0.0 0.0 0.1 0.2 0.0 0.1 0.1 Hot Food Container 0.0 0.1 0.0 0.1 3.1 6.2 0.1 0.2 0.3 0.8 0.0 0.0 0.3 0.5 0.1 0.2 0.1 Oven 0.1 0.1 0.1 0.2 1.5 3.0 0.2 0.4 0.5 1.2 0.0 0.0 0.6 1.2 0.1 0.3 0.2 Refrigeration 0.3 0.6 0.1 0.3 2.6 5.4 0.9 2.0 6.1 17.0 2.0 4.3 0.6 1.3 0.1 0.2 0.4 Glass Door Display - - - - - - - - - - 0.0 0.1 - - - - - Icemaker 0.0 0.0 0.0 0.0 0.1 0.3 0.0 0.1 0.2 0.4 0.2 0.4 0.1 0.2 0.0 0.0 0.0 Open Display Case 0.1 0.1 0.0 0.1 0.6 1.2 0.2 0.5 1.5 4.3 0.3 0.6 0.1 0.3 0.0 0.0 0.1 Reach-in Refrigerator 0.0 0.1 0.0 0.0 0.3 0.7 0.1 0.3 0.9 2.4 0.1 0.3 0.1 0.2 0.0 0.0 0.1 Walk-in Refrigerator 0.2 0.3 0.1 0.1 1.6 3.2 0.5 1.2 3.5 9.9 1.4 3.0 0.3 0.7 0.1 0.1 0.2 Interior Lighting 9.1 12.8 11.3 16.2 9.4 13.1 41.2 53.6 9.7 14.2 17.6 24.5 6.3 9.5 7.1 8.9 9.5 High-Bay Fixtures 0.2 0.4 0.1 0.1 - - 0.6 1.0 - - - - 0.4 0.6 0.1 0.2 0.1 Linear Fluorescent 1.2 2.1 2.4 4.3 0.3 0.5 2.7 4.7 1.5 3.0 1.6 2.8 1.4 2.0 1.3 2.0 1.5 Screw-in 7.6 10.3 8.8 11.8 9.1 12.6 38.0 47.9 8.2 11.2 16.0 21.7 4.5 6.9 5.7 6.8 7.9 Exterior Lighting 3.0 4.9 3.2 5.4 3.1 5.6 13.2 18.4 3.7 6.6 2.0 3.4 2.8 3.9 2.5 3.5 3.7 HID 2.4 4.2 2.6 4.5 2.7 5.0 3.6 6.2 2.5 4.9 1.9 3.4 2.4 3.5 2.0 3.0 3.5 Linear Fluorescent 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Screw-in 0.5 0.7 0.6 0.8 0.4 0.5 9.6 12.1 1.2 1.7 0.0 0.0 0.4 0.5 0.4 0.5 0.2 Office Equipment 1.2 2.3 2.3 4.4 0.2 0.5 0.6 1.3 0.2 0.3 0.2 0.4 0.5 0.9 0.6 1.0 1.1 Desktop Computer 0.6 1.1 1.7 3.2 0.0 0.0 0.2 0.4 0.0 0.0 0.1 0.2 0.3 0.6 0.3 0.5 0.2 Laptop 0.0 0.1 0.2 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 
State of New Mexico EE and DR Study Electric Ener

Global Energy Partners An EnerNOC Company  Small Office Large Office Restaurant Retail Grocery Warehouse School College Heal Low High Low High Low High Low High Low High Low High Low High Low High Low Monitor 0.0 0.1 0.1 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 POS Terminal 0.0 0.1 0.0 0.0 0.1 0.2 0.2 0.4 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Printer/Copier/Fax 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Server 0.5 1.0 0.3 0.6 0.1 0.2 0.2 0.4 0.1 0.2 0.1 0.1 0.1 0.2 0.3 0.4 0.9 Miscellaneous 0.7 1.4 0.2 0.5 0.0 0.0 0.1 0.2 0.0 0.0 0.0 0.1 - - 0.3 0.4 0.1 Non-HVAC Motors 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.2 0.0 0.0 0.0 0.1 - - 0.0 0.0 0.0 Pool Heater 0.3 0.7 0.1 0.2 - - - - - - - - - - 0.1 0.2 0.0 Pool Pump 0.3 0.7 0.1 0.2 - - - - - - - - - - 0.2 0.2 0.0 Total for Equipment 

15.6 27.0 20.0 34.9 22.5 42.0 52.0 76.7 21.5 43.6 24.2 38.9 11.3 19.0 10.5 15.0 14.1 
Electric Energy Efficiency Potential Results State of 

6-32 Table 6-18 Commercial Achievable Savings from Non-Equipment Measures in 2025 by Building Type (GWh) 

Small Office Large Office Restaurant Retail Grocery Warehouse School College Hea

Low High Low High Low High Low High Low High Low High Low High Low High Low 

Cooling 2.6 7.6 5.2 15.1 3.1 10.0 5.3 16.4 2.6 8.7 1.1 3.0 0.2 0.7 2.2 6.0 12.3 Advanced New Construction Designs - - - - 0.4 1.3 - - 0.2 0.6 - - - - - - 0.6 Air Cooled Chiller - Condenser Air Temperature Reset 

- - - - - - - - - - - - - - 0.1 0.2 1.1 

Air Cooled Chiller - Economizer 0.6 1.5 - - 0.0 0.0 0.3 0.8 0.1 0.1 - - - - - - 2.0 Air Cooled Chiller - VSD - - - - - - - - - - - - 0.1 0.4 0.2 0.5 4.2 Comprehensive Retrocommissioning - - - - - - - - - - - - - - - - 0.0 Custom Measures - - - - - - - - - - - - - - - - 0.2 Energy Management System 0.9 2.6 2.8 8.0 1.1 3.2 2.5 7.2 0.6 1.7 - - 0.0 0.1 0.6 1.8 3.7 Insulation - Ceiling (Best) - - - - - - 0.0 0.1 - - - - - - - - - Insulation - Ceiling (Better) 0.0 0.1 - - 0.0 0.0 - - - - - - - - - - - Insulation - Ceiling (Good) - - - - 0.0 0.1 0.1 0.2 0.0 0.1 - - - - - - 0.0 Insulation - Wall Cavity (Best) 0.0 0.0 - - - - - - 0.4 1.7 - - - - - - 0.1 Insulation - Wall Cavity (Better) - - - - - - 0.1 0.5 0.2 0.9 - - - - - - 0.1 Insulation - Wall Cavity (Good) - - - - - - 0.0 0.0 - - - - - - - - - Roofs - High Reflectivity 0.0 0.0 - - 0.1 0.5 0.4 1.4 0.1 0.4 0.0 0.2 - - - - - RTU - Maintenance 0.6 1.9 1.2 4.0 0.5 1.8 1.7 5.8 0.8 2.6 0.2 0.8 0.1 0.2 0.2 0.7 0.2 Thermostat - Clock/Programmable 0.1 0.2 0.0 0.1 - - 0.1 0.3 0.2 0.5 - - - - 0.0 0.1 0.1 Water Cooled Chiller - Condenser Water Temperature Reset 

- - - - - - - - - - 0.1 0.3 - - 0.3 0.7 0.0 

Water Cooled Chiller - Economizer 0.2 0.5 0.8 2.0 0.0 0.0 0.1 0.2 0.0 0.0 0.3 0.8 - - - - 0.0 Water Cooled Chiller - VSD - - 0.4 1.0 - - - - - - 0.4 1.0 - - 0.8 2.1 0.0 Windows - High Efficiency 0.3 0.9 - - 0.8 3.0 - - 0.0 0.0 - - - - - - - Space Heating 0.4 1.2 0.4 1.2 0.0 0.1 2.3 7.6 0.3 0.9 0.0 0.0 0.0 0.0 0.6 2.0 0.7 Advanced New Construction Designs - - - - 0.0 0.0 - - 0.0 0.2 - - - - - - 0.0 Comprehensive Retrocommissioning - - - - - - - - - - - - - - - - 0.0 Custom Measures - - - - - - - - - - - - - - - - 0.0 Energy Management System 0.3 0.9 0.4 1.2 0.0 0.1 0.9 2.8 0.2 0.5 - - - - 0.5 1.4 0.4 Insulation - Ceiling (Best) - - - - - - 0.0 0.0 - - - - - - - - - Insulation - Ceiling (Better) 0.0 0.0 - - 0.0 0.0 - - - - - - - - - - - Insulation - Ceiling (Good) - - - - 0.0 0.0 0.0 0.1 0.0 0.0 - - - - - - 0.0 Insulation - Wall Cavity (Best) 0.0 0.0 - - - - - - 0.0 0.0 - - - - 0.0 0.2 0.1 Insulation - Wall Cavity (Better) - - - - - - 0.3 1.0 0.0 0.0 - - - - 0.0 0.1 0.1 Insulation - Wall Cavity (Good) - - - - - - 0.9 3.2 - - - - - - - - - 
State of New Mexico EE and DR Study Electric Ener

Global Energy Partners An EnerNOC Company 

Small Office Large Office Restaurant Retail Grocery Warehouse School College Hea

Low High Low High Low High Low High Low High Low High Low High Low High Low 

Space Heating - Heat Recovery Ventilator 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 Thermostat - Clock/Programmable 0.1 0.2 0.0 0.1 - - 0.2 0.5 0.0 0.1 - - - - 0.1 0.3 0.0 Combined Heating/Cooling 0.6 2.2 1.1 3.9 0.8 2.6 0.5 1.7 0.5 1.7 0.1 0.3 1.2 4.0 0.1 0.3 0.1 Heat Pump - Maintenance 0.6 2.1 1.1 3.9 0.8 2.6 0.3 1.0 0.5 1.6 0.1 0.3 1.2 4.0 0.1 0.3 0.1 Insulation - Ceiling (Best) - - - - - - 0.0 0.0 - - - - - - - - - Insulation - Ceiling (Better) 0.0 0.0 - - 0.0 0.0 - - - - - - - - - - - Insulation - Ceiling (Good) - - - - 0.0 0.0 0.0 0.0 0.0 0.0 - - - - - - 0.0 Insulation - Wall Cavity (Best) 0.0 0.0 - - - - - - 0.0 0.1 - - - - 0.0 0.0 0.0 Insulation - Wall Cavity (Better) - - - - - - 0.1 0.2 0.0 0.0 - - - - 0.0 0.0 0.0 Insulation - Wall Cavity (Good) - - - - - - 0.1 0.5 - - - - - - - - - Ventilation 0.0 0.1 0.0 0.1 0.1 0.3 0.0 0.1 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Ventilation - CO2 Controlled 0.0 0.1 0.0 0.1 0.0 0.1 0.0 0.1 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Ventilation - Exhaust Hood Sensor Control - - - - 0.1 0.2 - - 0.0 0.0 - - - - - - - Ventilation - Variable Speed Control - - - - - - - - - - - - - - - - - Water Heating 0.1 0.1 - - 0.1 0.2 0.1 0.3 0.3 0.6 0.1 0.1 - - - - - Water Heating - Drainwater Heat Recovery 0.0 0.0 - - 0.0 0.0 - - 0.0 0.0 0.0 0.0 - - - - - Water Heating - Faucet Aerators 0.1 0.1 - - 0.1 0.1 0.1 0.3 0.2 0.3 0.1 0.1 - - - - - Water Heating - Hot Water Saver - - - - 0.0 0.1 - - 0.1 0.2 - - - - - - - Water Heating - Pipe Insulation - - - - - - - - 0.0 0.0 - - - - - - - Water Heating - Tank Blanket 0.0 0.0 - - 0.0 0.0 - - 0.0 0.0 - - - - - - - Refrigeration - - - - - - - - 0.2 0.9 - - - - - - - Open Display Case - Night Covers - - - - - - - - 0.2 0.9 - - - - - - - Exterior Lighting 0.1 0.2 0.1 0.3 0.1 0.4 0.3 0.8 0.1 0.4 0.0 0.0 0.0 0.0 0.0 0.1 0.3 Advanced New Construction Designs - - - - 0.0 0.1 - - 0.0 0.1 - - - - - - 0.0 Comprehensive Retrocommissioning - - - - - - - - - - - - - - - - 0.0 Custom Measures - - - - - - - - - - - - - - - - 0.0 Energy Management System 0.1 0.2 0.1 0.3 0.1 0.2 0.3 0.7 0.1 0.2 - - 0.0 0.0 0.0 0.1 0.2 Lighting Commissioning 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Lighting Retrocommissioning - - 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Interior Lighting 0.8 2.1 1.5 4.1 0.6 1.4 2.8 7.2 1.5 4.1 0.3 0.5 0.3 0.5 0.5 1.4 1.7 Advanced New Construction Designs - - - - 0.1 0.3 - - 0.3 1.0 - - - - - - 0.3 Comprehensive Retrocommissioning - - - - - - - - - - - - - - - - 0.0 Custom Measures - - - - - - - - - - - - - - - - 0.1 Energy Management System 0.4 1.3 1.2 3.5 0.2 0.5 1.7 4.9 0.6 1.6 - - 0.1 0.1 0.4 1.1 1.0 
Electric Energy Efficiency Potential Results State of 

6-34 

Small Office Large Office Restaurant Retail Grocery Warehouse School College Hea

Low High Low High Low High Low High Low High Low High Low High Low High Low 

Indoor Lighting - Daylighting Controls 0.1 0.4 0.0 0.1 0.1 0.2 0.3 0.9 0.1 0.3 - - - - 0.0 0.0 0.0 Interior Fluorescent - Photocell-Controlled Diming Ballasts 

- - - - - - - - 0.3 0.6 - - - - - - 0.0 

Interior Lighting - Guest Room Controls - - - - - - - - - - - - - - - - - Interior Lighting - LED Exit Lighting 0.1 0.2 0.2 0.2 0.2 0.2 0.5 0.7 0.2 0.2 0.3 0.4 0.2 0.3 0.1 0.1 0.2 Lighting Commissioning 0.1 0.2 0.1 0.2 0.0 0.1 0.2 0.7 0.1 0.3 0.0 0.1 0.0 0.0 0.0 0.1 0.0 Lighting Retrocommissioning - - 0.0 0.1 0.0 0.0 0.0 0.1 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Office Equipment 0.1 0.3 0.2 0.7 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.1 0.0 0.1 0.0 0.1 0.1 Office Equipment - Energy Star Power Supplies 0.1 0.3 0.2 0.7 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.1 0.0 0.1 0.0 0.1 0.1 Miscellaneous 0.0 0.1 - - - - - - - - - - - - - - 0.0 Pool Pump - Timer 0.0 0.1 - - - - - - - - - - - - - - 0.0 Total of Other Measures 4.7 13.8 8.5 25.5 4.8 15.1 11.4 34.3 5.6 17.4 1.6 4.0 1.7 5.2 3.5 9.9 15.1 
State of New Mexico EE and DR Study Electric Energy Efficiency Potential Results 

Global Energy Partners 6-35 

An EnerNOC Company 

6.3.3 Commercial Potential by Entity 

Table 6-19 presents the commercial sector potential for each entity in the state. These estimates 

were developed by taking the total end-use estimates for the state and allocating them to each 

entity according to its share of total commercial electricity use. Then, these estimates were 

adjusted to reflect weather differences between the entity’s area and the state as a whole. 

Please note that the allocation assumes that the mix of commercial sector activity in each entity’s 

area is consistent with the mix for the state as a whole. While this is a reasonable assumption, 

each entity should take care in applying these estimates. For example, if the entity has no 

colleges, then the savings attributed to this sector at the state level should be removed or 

reallocated among the remaining sectors13. 

Table 6-19 Commercial Efficiency Potential by Entity (MWh) 

Utility Type 2012 2015 2020 2025

IOUs

PNM

Achievable ‐ Low 11,610 43,882 129,580 185,942

Achievable – High 31,879 109,791 262,227 347,997

Economic 66,394 216,502 410,667 485,599

SPS

Achievable ‐ Low 3,303 12,446 36,178 51,366

Achievable – High 9,166 31,409 74,340 98,556

Economic 19,057 61,853 116,358 137,633

El Paso

Achievable ‐ Low 1,253 5,031 15,636 23,554

Achievable – High 3,478 12,697 32,130 45,193

Economic 7,231 25,004 50,290 63,112

Non IOU

Aztec City of

Achievable ‐ Low 75 279 811 1,129

Achievable – High 206 697 1,635 2,099

Economic 429 1,375 2,558 2,924

Central New Mexico El Coop, Inc

Achievable ‐ Low 164 609 1,775 2,491

Achievable – High 450 1,524 3,591 4,662

Economic 937 3,005 5,624 6,505

Central Valley Elec Coop, Inc

Achievable ‐ Low 261 973 2,875 4,135

Achievable – High 724 2,457 5,908 7,934

Economic 1,506 4,838 9,247 11,080

Columbus Electric Coop, Inc

Achievable ‐ Low 165 615 1,817 2,613

Achievable – High 458 1,552 3,733 5,013

Economic 951 3,057 5,843 7,001

Continental Divide El Coop Inc

Achievable ‐ Low 393 1,462 4,261 5,981

Achievable – High 1,080 3,659 8,623 11,193

Economic 2,249 7,215 13,505 15,619

Duncan Valley Elec Coop, Inc

Achievable ‐ Low 1 3 8 12

Achievable – High 2 7 17 23

Economic 4 14 27 32

 

13 The analysis tools and databases used to develop the state-level estimates are available to the individual entities should any wish to 

perform customized analysis. 
Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study 

6-36 www.gepllc.com 

Utility Type 2012 2015 2020 2025

Farmers' Electric Coop, Inc

Achievable ‐ Low 319 1,190 3,515 5,055

Achievable – High 885 3,003 7,222 9,700

Economic 1,841 5,915 11,305 13,545

City of Farmington

Achievable ‐ Low 1,267 4,709 13,673 19,030

Achievable – High 3,468 11,754 27,562 35,383

Economic 7,227 23,181 43,133 49,303

City of Gallup

Achievable ‐ Low 511 1,898 5,532 7,764

Achievable – High 1,402 4,750 11,195 14,531

Economic 2,920 9,366 17,532 20,276

Jemez Mountains Elec Coop, Inc

Achievable ‐ Low 445 1,653 4,800 6,681

Achievable – High 1,218 4,127 9,676 12,422

Economic 2,537 8,139 15,143 17,309

Kit Carson Electric Coop, Inc

Achievable ‐ Low 305 1,133 3,289 4,578

Achievable – High 834 2,828 6,631 8,512

Economic 1,739 5,577 10,377 11,861

Lea County Electric Coop, Inc

Achievable ‐ Low 1,143 4,265 12,595 18,115

Achievable – High 3,172 10,763 25,881 34,758

Economic 6,596 21,195 40,509 48,539

Los Alamos County

Achievable ‐ Low 177 658 1,910 2,658

Achievable – High 484 1,642 3,849 4,942

Economic 1,009 3,238 6,024 6,886

Mora‐San Miguel Elec Coop, Inc

Achievable ‐ Low 33 122 355 494

Achievable – High 90 305 716 919

Economic 188 602 1,121 1,281

Navajo Tribal Utility Authority

Achievable ‐ Low 142 529 1,536 2,137

Achievable – High 390 1,320 3,096 3,974

Economic 812 2,604 4,844 5,537

Navopache Electric Coop, Inc

Achievable ‐ Low 10 37 107 150

Achievable – High 27 92 217 281

Economic 57 181 340 393

Northern Rio Arriba E Coop Inc

Achievable ‐ Low 21 78 227 317

Achievable – High 58 195 458 589

Economic 120 386 717 820

Otero County Electric Coop Inc

Achievable ‐ Low 83 308 909 1,307

Achievable – High 229 777 1,868 2,508

Economic 476 1,530 2,924 3,503

Raton Public Service Company

Achievable ‐ Low 35 130 377 525

Achievable – High 96 324 760 975

Economic 199 639 1,189 1,359
State of New Mexico EE and DR Study Electric Energy Efficiency Potential Results 

Global Energy Partners 6-37 

An EnerNOC Company 

Utility Type 2012 2015 2020 2025

Rio Grande Electric Coop, Inc

Achievable ‐ Low 1 3 10 14

Achievable – High 2 8 20 27

Economic 5 16 31 37

Socorro Electric Coop, Inc

Achievable ‐ Low 188 700 2,041 2,865

Achievable – High 517 1,752 4,130 5,361

Economic 1,077 3,456 6,469 7,481

Southwestern Electric Coop Inc

Achievable ‐ Low 19 70 202 281

Achievable – High 51 174 407 522

Economic 107 342 637 728

Springer Electric Coop, Inc

Achievable ‐ Low 49 181 524 730

Achievable – High 133 451 1,057 1,357

Economic 277 889 1,654 1,891

Springer Town of

Achievable ‐ Low 5 18 52 72

Achievable – High 13 44 104 134

Economic 27 88 163 186

Tri‐County Electric Coop, Inc

Achievable ‐ Low 0 0 0 0

Achievable – High 0 0 0 0

Economic 0 0 0 0

City of Truth or Consequences

Achievable ‐ Low 72 269 795 1,143

Achievable – High 200 679 1,633 2,193

Economic 416 1,337 2,556 3,063

Roosevelt County Elec Coop Inc

Achievable ‐ Low 41 154 456 656

Achievable – High 115 390 937 1,258

Economic 239 767 1,466 1,757

Sierra Electric Coop, Inc

Achievable ‐ Low 42 158 468 673

Achievable – High 118 400 961 1,291

Economic 245 787 1,504 1,803

Western Area Power Administration

Achievable ‐ Low 585 2,173 6,311 8,783

Achievable – High 1,601 5,425 12,720 16,330

Economic 3,335 10,699 19,907 22,755

Total

Achievable ‐ Low 22,718 85,738 252,625 361,250

Achievable – High 62,545 214,994 513,305 680,636

Economic 130,207 423,795 803,665 949,820
Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study 

6-38 www.gepllc.com 

6.4 INDUSTRIAL SECTOR POTENTIAL 

The industrial sector makes up about one-third of New Mexico’s total electricity usage. Within the 

industrial sector, oil and gas extraction accounts for about 43% of the total electricity use in 

2009. Electronics manufacturing is also a large industry in New Mexico, accounting for 13% of 

industrial electricity use. Because of the size of these industries, we analyzed the segments 

separate from the rest of the industrial use. 

Most of the equipment replacement opportunities are in the machine drive (motors) end use, but 

potential savings 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 only available from upgrading to still more efficient levels. 

Furthermore, due to the site-specific nature of many industrial sector process energy efficiency 

opportunities, savings potential resulting from these customized approaches should be 

characterized individually. To further understand these opportunities, it would be appropriate to 

carry out site-specific engineering assessments for each customer and we would recommend that 

these assessments be limited to only the very largest customers. 

In 2012, Achievable - Low potential is 8 GWh or 0.1% of the baseline industrial forecast. This 

increases to 427 GWh, or 5.0% of the baseline forecast in 2025. Table 6-20, Figure 6-11 and 

Figure 6-12 present the savings for the various types of potential considered in this study. 

Table 6-20 Energy Efficiency Potential for the Industrial Sector 

Forecasts (GWh) 2012 2015 2020 2025

Baseline Forecast 7,395 7,873 8,162 8,538

Savings (GWh)

Achievable ‐ Low 8 24 129 427

Achievable ‐ High 30 77 324 985

Economic 48 116 441 1,285

Technical 62 149 562 1,594

Savings (% of Baseline)

Achievable ‐ Low 0.1% 0.3% 1.6% 5.0%

Achievable ‐ High 0.4% 1.0% 4.0% 11.5%

Economic 0.6% 1.5% 5.4% 15.1%

Technical 0.8% 1.9% 6.9% 18.7%

Savings (MW)

Achievable ‐ Low 1 2 13 43

Achievable ‐ High 3 8 33 101

Economic 5 12 45 134

Technical 7 17 66 192

Savings (% of Baseline)

Achievable ‐ Low 0.1% 0.2% 1.0% 3.3%

Achievable ‐ High 0.3% 0.6% 2.6% 7.8%

Economic 0.4% 1.0% 3.6% 10.2%

Technical 0.6% 1.4% 5.3% 14.7%
State of New Mexico EE and DR Study Electric Energy Efficiency Potential Results 

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Figure 6-11 Industrial Energy Efficiency Potential Savings 

Achievable‐ Low

Achievable‐ High

Economic

Technical

0%

5%

10%

15%

20%

2012 2015 2020 2025

Savings as

% of Baseline Forecast

Figure 6-12 Industrial Energy Efficiency Potential Forecast 

‐

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

2009 2011 2013 2015 2017 2019 2021 2023 2025

GWh

Baseline Forecast

Achievable‐ Low

Achievable‐High

Economic

Technical
Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study 

6-40 www.gepllc.com 

6.4.1 Industrial Potential by End Use 

Table 6-21 presents the industrial savings by end use and type of potential. As mentioned above, 

machine drives offer the greatest opportunity for energy savings across the range of potential. 

Cooling and lighting have the next highest savings potential, but are dwarfed in comparison to 

machine drives. 

Table 6-21 Industrial Potential by End Use and Potential Type (GWh) 

End Use Case 2012 2015 2020 2025

Cooling

Achievable‐ Low 0 0 2 6

Achievable‐ High 0 1 4 13

Economic 1 2 7 21

Technical 2 4 14 43

Space Heating

Achievable‐ Low 0 0 0 1

Achievable‐ High 0 0 1 3

Economic 0 0 1 4

Technical 1 1 5 17

Combined Heating/Cooling

Achievable‐ Low 0 0 0 0

Achievable‐ High 0 0 0 0

Economic 0 0 0 0

Technical 0 0 0 2

Ventilation

Achievable‐ Low 0.1 0.2 1.1 4

Achievable‐ High 0.2 0.6 3 9

Economic 0.4 1.1 4 14

Technical 0 1 4 14

Interior Lighting

Achievable‐ Low 0 0 1 1

Achievable‐ High 0 1 1 2

Economic 0 2 2 3

Technical 3 7 29 90

Process

Achievable‐ Low 0.0 0.1 0.8 2.6

Achievable‐ High 0.1 0.3 1.5 4.4

Economic 0.2 0.6 2.5 7.4

Technical 0 1 4 11

Machine Drive

Achievable‐ Low 0 0 1 3

Achievable‐ High 0 1 3 9

Economic 0 1 4 13

Technical 1 2 6 20

Other

Achievable‐ Low 7 22 121 401

Achievable‐ High 28 71 302 918

Economic 44 107 410 1,193

Technical 55 133 499 1,398

Total

Achievable‐ Low 8 24 129 427

Achievable‐ High 30 77 324 985

Economic 48 116 441 1,285

Technical 62 149 562 1,594
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Figure 6-13 illustrates the range of achievable potential savings by end use in 2025, reinforcing 

the dominance of the machine drive category. Figure 6-14 shows the savings by segment and 

end use. The specific measures that account for the largest savings in the Oil and Gas segment 

are: 

• Well conversion, gas lift to rod beam with POC (159 GWh) 

• Pump off controllers for rod beam pumping units (47 GWh) 

• Decreasing water/oil ratio (50 GWh) 

• Variable speed drives for surface motors, (45 GWh), ESP pumping units (39 GWh) and 

positive displacement pumps (28 GWh) 

Figure 6-13 Industrial Achievable Potential Savings by End Use in 2025 (GWh) 

0

100

200

300

400

500

600

700

800

900

1,000

Savings in 2025 (GWh)

Achievable‐ High

Achievable‐ Low

Figure 6-14 Industrial Achievable – Low Potential Savings by End Use in 2025 (GWh) 

‐

50

100

150

200

250

300

350

400

Oil and Gas Electronics Other Industrial

Achievable  ‐ Low Savings in 2025 (GWh)

Cooling

Space Heating

Heat/Cool

Ventilation

Interior Lighting

Exterior Lighting

Machine Drive

Process

Other
Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study 

6-42 www.gepllc.com 

6.4.2 Industrial Potential by Entity 

Table 6-22 presents the industrial sector potential for each entity in the state. These estimates 

were developed by taking the total end-use estimates for the state and allocating them to each 

entity according to its share of total industrial electricity use. Then, these estimates were 

adjusted to reflect weather differences between the entity’s area and the state as a whole. 

Please note that the allocation assumes that the mix of industrial activity in each entity’s area is 

consistent with the mix for the state as a whole. Therefore, each entity should take care in applying 

these estimates. For example, if the entity has no Oil and Gas Extraction industry, then the savings 

attributed to this segment should be removed or reallocated among the remaining sectors14. 

Table 6-22 Industrial Efficiency Potential by Entity (MWh) 

Utility Type 2012 2015 2020 2025

IOUs

PNM

Achievable ‐ Low 1,228 3,701 19,459 62,878

Achievable – High 4,763 11,936 48,710 144,835

Economic 7,688 18,086 66,394 189,057

SPS

Achievable ‐ Low 2,219 7,035 40,444 142,943

Achievable – High 8,603 22,687 101,240 329,257

Economic 13,887 34,376 137,995 429,789

El Paso

Achievable ‐ Low 90 298 1,778 6,452

Achievable – High 347 962 4,451 14,862

Economic 560 1,457 6,066 19,400

Non IOU

Aztec City of

Achievable ‐ Low 0 0 0 0

Achievable – High 0 0 0 0

Economic 0 0 0 0

Central New Mexico El Coop, Inc

Achievable ‐ Low 100 311 1,651 5,257

Achievable – High 386 1,004 4,133 12,108

Economic 624 1,522 5,633 15,805

Central Valley Elec Coop, Inc

Achievable ‐ Low 701 2,192 11,624 37,009

Achievable – High 2,719 7,070 29,097 85,248

Economic 4,390 10,713 39,660 111,277

Columbus Electric Coop, Inc

Achievable ‐ Low 0 0 0 0

Achievable – High 0 0 0 0

Economic 0 0 0 0

Continental Divide El Coop Inc

Achievable ‐ Low 203 636 3,370 10,731

Achievable – High 789 2,050 8,437 24,718

Economic 1,273 3,106 11,500 32,266

Duncan Valley Elec Coop, Inc

Achievable ‐ Low 2 5 28 89

Achievable – High 7 17 70 206

Economic 11 26 96 269

Farmers' Electric Coop, Inc

Achievable ‐ Low 236 739 3,917 12,473

Achievable – High 916 2,383 9,806 28,731

Economic 1,480 3,610 13,367 37,503

City of Farmington

Achievable ‐ Low 571 1,784 9,459 30,118

Achievable – High 2,213 5,754 23,679 69,375

Economic 3,573 8,718 32,276 90,558

City of Gallup Achievable ‐ Low 0 0 0 0

 

14 The analysis tools and databases used to develop the state-level estimates are available to the individual entities should any wish to 

perform customized analysis. 
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Utility Type 2012 2015 2020 2025

Achievable – High 0 0 0 0

Economic 0 0 0 0

Jemez Mountains Elec Coop, Inc

Achievable ‐ Low 27 85 452 1,440

Achievable – High 106 275 1,132 3,317

Economic 171 417 1,543 4,330

Kit Carson Electric Coop, Inc

Achievable ‐ Low 72 226 1,200 3,820

Achievable – High 281 730 3,003 8,800

Economic 453 1,106 4,094 11,486

Lea County Electric Coop, Inc

Achievable ‐ Low 376 1,175 6,228 19,830

Achievable – High 1,457 3,788 15,591 45,677

Economic 2,352 5,740 21,251 59,624

Los Alamos County

Achievable ‐ Low 539 1,685 8,936 28,452

Achievable – High 2,091 5,435 22,369 65,538

Economic 3,375 8,236 30,490 85,548

Mora‐San Miguel Elec Coop, Inc

Achievable ‐ Low 5 16 83 266

Achievable – High 20 51 209 612

Economic 32 77 285 799

Navajo Tribal Utility Authority

Achievable ‐ Low 46 144 765 2,435

Achievable – High 179 465 1,914 5,608

Economic 289 705 2,609 7,320

Navopache Electric Coop, Inc

Achievable ‐ Low 0 0 1 4

Achievable – High 0 1 4 10

Economic 1 1 5 13

Northern Rio Arriba E Coop Inc

Achievable ‐ Low 19 60 317 1,010

Achievable – High 74 193 794 2,326

Economic 120 292 1,082 3,037

Otero County Electric Coop Inc

Achievable ‐ Low 83 260 1,378 4,388

Achievable – High 322 838 3,450 10,106

Economic 520 1,270 4,702 13,192

Raton Public Service Company

Achievable ‐ Low 17 53 281 895

Achievable – High 66 171 704 2,063

Economic 106 259 960 2,692

Rio Grande Electric Coop, Inc

Achievable ‐ Low 1 2 12 37

Achievable – High 3 7 29 85

Economic 4 11 40 111

Socorro Electric Coop, Inc

Achievable ‐ Low 55 171 907 2,889

Achievable – High 212 552 2,272 6,656

Economic 343 836 3,096 8,688

Southwestern Electric Coop Inc

Achievable ‐ Low 559 1,748 9,266 29,504

Achievable – High 2,168 5,636 23,196 67,959

Economic 3,500 8,540 31,617 88,709

Springer Electric Coop, Inc

Achievable ‐ Low 299 935 4,955 15,778

Achievable – High 1,159 3,014 12,405 36,343

Economic 1,872 4,567 16,908 47,440

Springer Town of

Achievable ‐ Low 0 0 0 0

Achievable – High 0 0 0 0

Economic 0 0 0 0

Tri‐County Electric Coop, Inc

Achievable ‐ Low 0 0 0 0

Achievable – High 0 0 0 0

Economic 0 0 0 0
Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study 

6-44 www.gepllc.com 

Utility Type 2012 2015 2020 2025

City of Truth or Consequences

Achievable ‐ Low 0 0 0 0

Achievable – High 0 0 0 0

Economic 0 0 0 0

Roosevelt County Elec Coop Inc

Achievable ‐ Low 166 518 2,748 8,751

Achievable – High 643 1,672 6,880 20,157

Economic 1,038 2,533 9,378 26,311

Sierra Electric Coop, Inc

Achievable ‐ Low 0 0 0 0

Achievable – High 0 0 0 0

Economic 0 0 0 0

Western Area Power Administration

Achievable ‐ Low 0 0 0 0

Achievable – High 0 0 0 0

Economic 0 0 0 0

Total

Achievable ‐ Low 7,615 23,781 129,262 427,450

Achievable – High 29,523 76,691 323,575 984,599

Economic 47,659 116,204 441,047 1,285,227

6.5 ANNUAL SAVINGS AND COSTS 

In addition to developing estimates of savings, costs for also developed. Table 6-23 presents the 

following information for the Achievable – Low and Achievable – High cases: 

• Annual savings (incremental savings). The average annual savings are in the range of 

105 GWh to 190 GWh per year for Achievable potential. 

• Total incremental cost of the measures. The average cost for measures ranges from $51 

million to $88 million per year for Achievable potential. 

• Program administration costs, which are estimated at 15% of total incremental measure 

cost. The range of average costs is $8 million to $13 million per year. 

• Estimated program cost assuming incentives that are equal to 50% of the incremental 

equipment cost plus program administration costs. 

Figure 6-15 illustrates the annual program costs assuming incentives levels equal to 50% of 

incremental costs: 

• In the Achievable – Low case, the annual program costs range from $12 million to $43 

million per year, with an average of $33 million per year over the forecast horizon. 

• In the Achievable – High case, the annual program costs range from $24 million to $95 

million per year, with an average of $57 million per year over the forecast period. 
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Figure 6-15 Annual Program Costs 

$0

$10

$20

$30

$40

$50

$60

$70

$80

$90

$100

2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

$ Million

Achievable ‐ Low Achievable ‐ High

Achieve ‐ Low ‐ Average Achieve ‐ High ‐ Average
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Global Energy Partners An EnerNOC Company Table 6-23 Summary of Costs for Achievable Potential 

2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2

Annual Savings (GWh)Achievable ‐ Low 66.6 81.0 52.3 46.5 103.8 100.8 116.2 145.9 96.8 73.9 73.9 155.9 1Achievable ‐ High 187.0 199.4 107.7 79.0 201.1 168.7 183.8 223.4 138.0 120.2 129.8 270.2 3Incremental Measure Cost (Million $)Achievable ‐ Low $24.8 $34.9 $19.7 $18.2 $73.2 $55.3 $46.2 $68.2 $57.1 $51.7 $74.6 $66.0 $Achievable ‐ High $65.4 $84.4 $46.2 $37.6 $146.1 $106.8 $73.9 $96.9 $87.2 $82.3 $102.3 $100.1 $Program Administration Costs (Million $)Achievable ‐ Low $3.7 $5.2 $3.0 $2.7 $11.0 $8.3 $6.9 $10.2 $8.6 $7.8 $11.2 $9.9 Achievable ‐ High $9.8 $12.7 $6.9 $5.6 $21.9 $16.0 $11.1 $14.5 $13.1 $12.4 $15.3 $15.0 $Total Program Cost with Incentives at 50%Achievable ‐ Low $16.1 $22.7 $12.8 $11.8 $47.6 $36.0 $30.0 $44.3 $37.1 $33.6 $48.5 $42.9 $Achievable ‐ High $42.5 $54.9 $30.0 $24.4 $94.9 $69.4 $48.1 $63.0 $56.7 $53.5 $66.5 $65.0 $
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6.6 SCENARIO ANALYSIS 

In addition to the reference case, two scenarios reflecting lower and higher avoided cost 

forecasts were developed. The Low case uses avoided costs that are 75% of those used for the 

Reference forecast and the High case uses avoided costs that are 150% of the Reference 

forecast case. The changes in avoided costs affect economic potential directly and the changes 

flow through to achievable potential. 

• As avoided costs increase, the benefits of savings from energy-efficiency increase, 

causing the benefit-cost ratio to increase. If higher avoided costs result in measure B/C 

ratios to increase to a value of 1.0 or above, then the measures are included in economic 

potential. 

• Conversely, lower avoided costs decrease the benefits from energy efficiency savings, 

thus lowering the B/C ratio. Measures that passed the economic screen in the reference 

case (100% of avoided costs), may no longer pass. 

Focusing on economic potential in 2025, the scenario analysis results in the following: 

• In the Low case, economic potential is 206 GWh lower than in the Reference case, which 

is a 6% reduction in absolute savings. As a percent of the Reference baseline forecast, 

the Low case saves 13.9% in 2025, compared to 14.7% in the Reference case. 

• In the High case, economic potential is 373 GWh higher than in the Reference case, 

which is an 11% increase in absolute savings. As a percent of the Reference baseline 

forecast, the High case saves 16.3% in 2025, compared to 14.7 in the Reference case. 

The changes in savings flow through to achievable potential as shown in Table 6-24, Table 6-25, 

and Figure 6-16. 

Table 6-24 Scenario Analysis Results – Energy Savings (GWh) 

Year Type of Potential

Low

75% of Reference

Avoided Costs

Reference

High

150% of Reference

Avoided Costs

2012

Achievable ‐ Low   64 67 69

Achievable ‐ High   180 187 197

Economic    549 576 600

2015

Achievable ‐ Low   233 246 260

Achievable ‐ High   540 573 610

Economic    1,077 1,171 1,243

2020

Achievable ‐ Low   765 810 883

Achievable ‐ High   1,403 1,488 1,634

Economic    2,009 2,170 2,393

2025

Achievable ‐ Low   1,392 1,473 1,632

Achievable ‐ High   2,512 2,656 2,951

Economic    3,304 3,510 3,883
Electric Energy Efficiency Potential Results 

6-48 www.gepllc.com 

Table 6-25 Scenario Analysis Results – Energy Savings as a Percent of the Baseline 

Forecast 

Year Type of Potential

Low

75% of Reference

Avoided Costs

Reference

High

150% of Reference

Avoided Costs

2012

Achievable ‐ Low   0.30% 0.31% 0.32%

Achievable ‐ High   0.84% 0.87% 0.92%

Economic    2.56% 2.68% 2.80%

2015

Achievable ‐ Low   1.07% 1.14% 1.20%

Achievable ‐ High   2.49% 2.64% 2.81%

Economic    4.96% 5.40% 5.73%

2020

Achievable ‐ Low   3.35% 3.55% 3.87%

Achievable ‐ High   6.15% 6.52% 7.16%

Economic    8.80% 9.51% 10.48%

2025

Achievable ‐ Low   5.84% 6.18% 6.85%

Achievable ‐ High   10.54% 11.14% 12.38%

Economic    13.87% 14.73% 16.30%

Figure 6-16 Scenario Analysis Results – Energy Savings as a Percent of the Baseline 

Forecast 

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

75% AC 100% AC 150% AC

Low   High  Economic

Achievable

Low   High  Economic

Achievable

Low   High  Economic

Achievable

Low   High  Economic

Achievable

2012 2015 2020 2025
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P: 925.482.2000 

F: 925.284.3147 

E: globalhq@gepllc.com 

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