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, 2011Global 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 ne cessarily 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 94111Global 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 (P NM), 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 Compan y), John Fernald (NM Gas Company), Keven

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

Sims (Farmington Municipal Electric), Thom Moor e (Farmers’ Electric C oop), Christine Chavez

(Los Alamos Dept. of Public Utilities), Julie Willia ms-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 va luable comments throughout the

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

(SWEEP), Keith Freischlag (SWEEP), Tom Singer (N RDC), 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), Er ik 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), Vict oria Sandoval (Graybar), James McLane (WH

Pacific), Phyllis Kaplan (C ASA) and Robb Thomson.

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

• Global Energy Partners: Ceci lia 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 PartnersGlobal Energy Partners vii

An EnerNOC Company 

## 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 Organi zation ......................................................................................... 1-4

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

2.1 Analysis Appr oach ........................................................................................... 2-1

2.1.1 LoadMAP Mod el ................................................................................... 2-2

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

2.1.3 Baseline Fore cast ................................................................................. 2-8

2.1.4 Energy Efficiency Meas ure Analys is ....................................................... 2-9

2.1.5 Energy-Efficiency Potentia l.................................................................. 2-13

2.1.6 Strategy Recomme ndations ................................................................ 2-14

2.2 Data Develo pment ......................................................................................... 2-14

2.2.1 Data Sour ces ..................................................................................... 2-14

2.2.2 Data Applic ation ................................................................................ 2-18

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

3.1 Residential Se ctor ............................................................................................ 3-3

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

3.3 Industrial Se ctor .............................................................................................. 3-9

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

4.1 Residential Se ctor ............................................................................................ 4-1

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

4.3 Industrial Se ctor .............................................................................................. 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 Econ omic Scr een ...................................................................... 5-13

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

6.1 Overall Electric Energy Efficiency Pote ntial ......................................................... 6-1

6.2 Electricity Resident ial Sector ........................................................................... 6-10

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

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

6.2.3 Residential Potentia l by Enti ty ............................................................. 6-18

6.3 Commercial Sector Potentia l ........................................................................... 6-21

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

6.3.2 Commercial Potential by Market Segm ent ............................................ 6-28viii www.gepllc.com 6.3.3 Commercial Potential by Entity

............................................................. 6-35

6.4 Industrial Sect or Pote ntial ............................................................................... 6-38

6.4.1 Industrial Potent ial by En d Use ............................................................ 6-40

6.4.2 Industrial Potent ial by En tity ................................................................ 6-42

6.5 Annual Savings and Co sts ............................................................................... 6-44

6.6 Scenario Analysis

............................................................................................ 6-47Global Energy Partners ix

An EnerNOC Company 

## LIST OF FIGURES

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

Figure 2-2 LoadMAP Analysis Framewor k ............................................................................. 2-3

Figure 2-3 Approach for Measure Assessment ....................................................................... 2-9

Figure 3-1 Sector-Level Electric ity Use, 2009 ........................................................................ 3-1

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

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

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

Figure 3-5 Commercial Electricity Consumpt ion by End Us e, 2009 .......................................... 3-8

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

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

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

Figure 4-1 Residential Baseline Fore cast by En d Use ............................................................. 4-2

Figure 4-2 Residential Baseline Electricity Us e 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 Pote ntial Energy Savings .................................................. 6-3

Figure 6-2 Energy Efficiency Potential En ergy Forecast s (GWh) .............................................. 6-3

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

Figure 6-4 Residential Energy Efficie ncy Potential Savings .................................................... 6-12

Figure 6-5 Residential Energy Efficienc y Potential Fo recast .................................................. 6-12

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

Figure 6-7 Commercial Energy Efficienc y Potential Sa vings .................................................. 6-22

Figure 6-8 Commercial Energy Efficiency Potential Fore cast ................................................. 6-23

Figure 6-9 Commercial Achievable Potential Savin gs 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 Efficienc y Potential Sa vings ..................................................... 6-39

Figure 6-12 Industrial Energy Efficienc y Potential Fo recast .................................................... 6-39

Figure 6-13 Industrial Achievable Potential Sa vings 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 .. 6-48Global Energy Partners xi

An EnerNOC Company 

## LIST OF TABLES

Table 1-1 Explanation of Abbreviati ons and Acro nyms .......................................................... 1-3

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

Table 2-2 Residential End Uses an d Technologi es ................................................................ 2-5

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

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

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

Table 2-7 Utility Saturation Survey s .................................................................................. 2-15

Table 2-8 Data Applied for the Market Pro files ................................................................... 2-19

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

Table 2-10 Residential Electric Eq uipment Stan dards ........................................................... 2-21

Table 2-11 Commercial Electric Equi pment Standa rds .......................................................... 2-22

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

Table 2-13 Avoided Cost Forecasts — State-Level Av erage ................................................... 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 Re sidential Se ctor ............................................................... 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 Segm ent, 2009 .......................... 3-11

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

Table 4-2 Commercial Electricity Consumpt ion by End Us e (GWh) ......................................... 4-5

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

Table 4-4 Industrial Electricity Consum ption by End Us e (GWh) ............................................ 4-7

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

Table 5-1 Summary of Residential Eq uipment Meas ures ....................................................... 5-2

Table 5-2 Summary of Residential Non- equipment Meas ures ................................................ 5-4

Table 5-3 Summary of Commercial Eq uipment Meas ures ...................................................... 5-5

Table 5-4 Summary of Commercial Equipmen t Measures (Con tinued) .................................... 5-6

Table 5-5 Summary of Commercial Non- equipment Meas ures ............................................... 5-7

Table 5-6 Summary of Commercial Non-equipm ent Measures (C ontinued) ............................. 5-8

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

Table 5-8 Summary of Industrial Me asures (Conti nued) ..................................................... 5-10

Table 5-9 Summary of Industrial Me asures (Conti nued) ..................................................... 5-11

Table 5-10 Summary of Industrial Me asures (Conti nued) ..................................................... 5-12

Table 5-11 Number of Measures Evaluate d ......................................................................... 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 Enti ty (Peak Demand Savings MW) .......................... 6-8

Table 6-5 Electricity Energy Efficiency Potentia l for the Resident ial Sector ............................ 6-11xii www.gepllc.com Table 6-6 Residential Potential by Market Segm ent, 2025 .................................................... 6-13

Table 6-7 Residential Achievable Potential by End Use and Mark et Segmen t, 2025 ................ 6-13

Table 6-8 Residential Savings by End Us e 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 Pote ntial by Enti ty (MWh) ................................................... 6-19

Table 6-12 Energy Efficiency Potential fo r the Commerci al Sector .......................................... 6-22

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

Table 6-14 Commercial Achievable - Low Savings for Equipment Me asures (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 Us e and Potential Type (GWh) .................................... 6-40

Table 6-21 Industrial Efficiency Pote ntial by Enti ty (MWh) ..................................................... 6-42

Table 6-22 Summary of Costs for Ac hievable Po tential .......................................................... 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 ... 6-48Global Energy Partners 1-1

An EnerNOC Company 

### 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 th rough 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 ener gy efficiency strategies and measures in New

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

(SWEEP 1 ) broadly addresses policy options for New Mexico’s energy efficiency strategy, but does

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

for each measure. The Tri-State Energy Efficiency Potential Study conducted in 2009 2 provides

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

reports, including a 2005 potential study prepared for PNM 3 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 pote ntial 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 an d 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/progra ms/buildings/codes/beyondcod e/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 , 2006Introduction 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 savings 4 and we developed three types of potential: technical potential, economic

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

to efficiency savings. Achievable potential em bodies a set of assumpti ons about the decisions

consumers make regarding the efficiency of th e 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 measur es regardless of their cost. At the time of

equipment failure, customers replac e 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 al l 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) te st, 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 opti on at the time of equi pment failure and also

adopt every other cost-effecti ve and applicab le 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 es tablishes 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 co mbined 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 (ins tead 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 seve ral 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 2.1.2.2Introduction 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 EstimatesGlobal Energy Partners 2-1

An EnerNOC Company 

### 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 fo r 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-efficienc y 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 Developmen t 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 (LoadMAP TM

) to develop the baseline

forecast, as well as the estimates of energy-eff iciency 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 ha s 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 tr eat older, less efficient appliance/equipment

stock separately from newer, more efficient eq uipment. 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 saturation s, 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 eq uipment 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 equipmen t 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 toState of New Mexico EE and DR Study An alysis Approach and Data Development

Global Energy Partners 2-3

An EnerNOC Company 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 fa cilitates sensitivity analysis.

• Includes appliance and equipment models custom ized 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 al so 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 electricit y 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 Developmen t 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 ma rket segments (building types, end uses and

other dimensions) that are relevant in New Mexi co. 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 sing le-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 represen ts 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.State of New Mexico EE and DR Study An alysis Approach and Data Development

Global Energy Partners 2-5

An EnerNOC Company 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 officesAnalysis Approach and Data Developmen t State of New Mexico EE and DR Study

2-6 www.gepllc.com • 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 an d 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 list s 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 indust ries 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 Manuf acturing, accounting for 44% an d 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 th at are appropriate for New Mexico. Because these vary by industry, they

are shown in Chapter 5.

With the segmentation scheme defined, the ne xt 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 (custo mer counts and energy use totals) for calibrating

the LoadMAP model to known data for the base-year.State of New Mexico EE and DR Study An alysis Approach and Data Development

Global Energy Partners 2-7

An EnerNOC Company 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 MiscellaneousAnalysis Approach and Data Developmen t State of New Mexico EE and DR Study

2-8 www.gepllc.com

2.1.2.2 Market Profiles

The next step was to develop market profiles fo r 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 co mmercial 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 us e UECs expressed in kWh/household and for

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

• Intensity for the residential sector represents th e 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 commerc ial sector, intensity, computed as the

product of the saturation and the EUI, repr esents 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 intens ity 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 absenc e 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 nation al 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 standards 6

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

6 At the time of the analysis, the 2009 Ne w Mexico Building Code was in effect.State of New Mexico EE and DR Study An alysis Approach and Data Development

Global Energy Partners 2-9

An EnerNOC Company • 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 asse ss the savings, costs, and other attributes of

energy-efficiency measures. These characterist ics 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 pe rformance, 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. Potent ial 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 envelo pe, the application of controls to optimize

energy use, and other actions result ing in improved energy efficiency.

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

a variety of secondary sources. This universal lis t 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 th e 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:Analysis Approach and Data Developmen t State of New Mexico EE and DR Study

2-10 www.gepllc.com • Equipment measures, or efficient energy-consuming equi pment, save ener gy by providing

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

standard efficiency refrigerator with an ENER GY STAR model. For eq uipment 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 ai r 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 progra mmable 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 on e 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, th e project team assessed their energy-saving

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

performance factors. Following the measure ch aracterization, we pe rformed an economic

screening of each measure, whic h 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, Ta ble 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 measur es, 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 standard s or the entry of new products to the market.State of New Mexico EE and DR Study An alysis Approach and Data Development

Global Energy Partners 2-11

An EnerNOC Company 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 measur es 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 feasibility 7 of

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

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

End Use Measure Satura

‐

tion in

2009 8 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 an d whether

it is feasible to install the measure. For instance, attic fans are not applicable to homes without attics, and in some homes w ith attics, it

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

8 Note that saturation levels r eflected for 2009 change over time as more measures are adopted.Analysis Approach and Data Developmen t State of New Mexico EE and DR Study

2-12 www.gepllc.com

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 meas ure 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 annua l energy and demand savings for each measure

by all appropriate avoided costs for each year, an d discounting the dollar savings to the present

value equivalent. The analysis us es 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 includ ed 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 dynami cally, 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 foll owing about the economic screen:

• The economic evaluation of every measure in th e 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 measur e applied must be compared to the kWh

consumption of a baseline condition.

• The economic screening was conducted only fo r 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 SE ER 15. However, in 2015, due to federal energy

efficiency standards, the SEER 13 unit goes of f 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 ta ble also shows how the

economic choice for two of the li ghting 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. Ot herwise, 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 fo r evaluating measure-level cost-effectiveness, but other test pers pectives

may sometimes be considered in energy efficiency potential studie s. 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 administerin g the

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

broader context of energy efficiency programs and initiative s put into place to deliver the energy efficiency measures.State of New Mexico EE and DR Study An alysis Approach and Data Development

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### 2.1.5 Energy-Efficiency Potential

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

National Action Plan for Ener gy-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, determ ining the technical potential is relatively

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

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

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

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

measures shown in Table 2-5 are then applie d 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 sa vings. 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 applie d, 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 no n-equipment measure as determined in the

cost-effectiveness screening process describe d 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 ra tes (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 wi th 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 fo r Energy Efficiency (2007). National Action Plan for Energy Efficien cy Vision for 2025: Developing a Framework

for Change

. www.epa.gov/eeactionplan

.Analysis Approach and Data Developmen t State of New Mexico EE and DR Study

2-14 www.gepllc.com • The range of savings in 10 years from the survey of experts was used to define the

range of achievable potential in 2021. MARs an d 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 po tential 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 es timates by measure, cust omer segment and sector

and developed a set of recommendations for strate gies 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 da ta 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)State of New Mexico EE and DR Study An alysis Approach and Data Development

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An EnerNOC Company • 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 en ergy 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 responsesAnalysis Approach and Data Developmen t State of New Mexico EE and DR Study

2-16 www.gepllc.com 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 us ed, 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 stra tified 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 esti mate 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 indust rial segments across

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

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

• EnergyShape TM

Database . This database contains end-us e 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 pe ak 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 agai nst 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 estima tes of energy and peak demand savings

values, measure costs, and effective useful lif e (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 sourcesState of New Mexico EE and DR Study An alysis Approach and Data Development

Global Energy Partners 2-17

An EnerNOC Company 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 an d 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 characterist ics. http://www.census.gov/acs/www/

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

details on business characteristic s. 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) maintain s 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 stud y, 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.Analysis Approach and Data Developmen t State of New Mexico EE and DR Study

2-18 www.gepllc.com 

### 2.2.2 Data Application

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

2.2.2.1 Data Application for Market Characterization

To construct the high-level market characterizati on of electricity use an d households/floor space

for the residential, commercial, and industrial sect ors, 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 cust omers 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 fo ur segments, we determined the housing type

breakdown based on the American Community Survey and applied it to th e 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. Ba sed on the market research conducted for this

study, we determined that the home type of lo w-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 fr om 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 segmen t, 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 equipm ent characteristics,

building characteristics, customer behavi or, operating characte ristics, and energyefficiency actions already taken. These were compared with and supplemented by the

utility saturation surveys, an d then adjusted, if needed.

3. Incorporated secondary data sources to supp lement 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 Prof iles, 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 pr oject team to vet the data against their

knowledge and experience.

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

shown in Table 2-8.State of New Mexico EE and DR Study An alysis Approach and Data Development

Global Energy Partners 2-19

An EnerNOC Company 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 requ ired for the baseline forecast. These inputs are

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

dwellings/buildings.Analysis Approach and Data Developmen t State of New Mexico EE and DR Study

2-20 www.gepllc.com Table 2-9 Data Needs for the Baseline Foreca st 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 assumptions 11

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 equi pment standards, as shown in Table 2-10 and

Table 2-11.

11 We developed baseline purchase decision s using the Energy Information Agency’s Annual Energy Outlook report (2011), which

utilizes the National Energy Modeling Syst em (NEMS) to produce a self-consistent suppl y and demand economic model. We calibrate d

equipment purchase options to match manufacturer shipme nt data for recent years and then trended forward.State of New Mexico EE and DR StudyAnalysis Approach and Data DevelopmentGlobal Energy Partners2-21An EnerNOC Company Table 2-10 Residential Electric Equipment StandardsToday'sEfficiencyorStandardAssumption 1stStandard(relativetotoday'sstandard)2ndStandard(relativetotoday'sstandard)EndUse Technology 201120122013201420152016201720182019202020212022202320242025CentralACRoomACEvaporativeCentralACEvaporativeRoomACCooling/Heating HeatPumpSpaceHeating ElectricResistanceWaterHeater(<=55gallons)WaterHeater(>55gallons)Screw‐in/PinLampsLinearFluorescentRefrigerator/2ndRefrigeratorFreezerDishwasherClothesWasherClothesDryerRange/OvenMicrowavePersonalComputerMonitorLaptopComputerTVCopier/Printer/FaxDVD/VCR/AudioDevicesandGadgetsPoolPumpWellPumpFurnaceFanConventionalConventional5%moreefficient(EF3.17)ConventionalConventionalConventional/EnergyStarConventionalConventionalConventionalConventionalConventionalSEER14EER11.0ConventionalConventionalSEER14.0/HSPF8.0SEER13EER9.8SEER13.0/HSPF7.7Conventional(MEF1.26fortoploader)Conventional(EF3.01)ElectricResistanceEF0.95HeatPumpWaterHeaterAdvancedIncandescent‐tier2T8EF0.90EF0.90Incandescent AdvancedIncandescent‐tier1MiscellaneousMEF1.72fortoploaderCoolingWaterHeatingLightingAppliancesElectronics25%moreefficient25%moreefficient14%moreefficient(307kWh/yr)MEF2.0fortoploaderConventional/EnergyStarConventional/EnergyStarNAECAStandardNAECAStandardConventional(355kWh/yr)Analysis Approach and Data DevelopmentState of New Mexico EE and DR Study2-22www.gepllc.com

Table 2-11 Commercial Electric Equipment StandardsToday'sEfficiencyorStandardAssumption 1stStandard(relativetotoday'sstandard)2ndStandard(relativetotoday'sstandard)EndUse Technology 201120122013201420152016201720182019202020212022202320242025ChillersRoofTopUnitsPackagedTerminalAC/HP EER9.8Cooling/Heating HeatPumpElectricResistanceElectricFurnaceVentilation VentilationScrew‐in/PinLampsLinearFluorescent T12HighIntensityDischargeWaterHeating WaterHeaterWalk‐inRefrigerator/FreezerReach‐inRefrigeratorGlassDoorDisplayEPACT2005StandardOpenDisplayCaseEPACT2005StandardVendingMachinesEPACT2005StandardIcemakerDesktopComputerLaptopComputerNon‐HVACMotorsCommercialLaundryMiscellaneousAdvancedIncandescent‐tier1IncandescentT8EISA2007StandardMEF1.6MEF1.2670%Efficiency62.3%EfficiencyEF0.97OfficeEquipmentRefrigerationEPACT2005Standard42%moreefficient18%moreefficient33%moreefficient2010StandardConventional/EnergyStarConventional/EnergyStarCoolingSpaceHeatingLighting2007ASHRAE90.1EER11.0/11.2EER11.0EER11.0/COP3.3AdvancedIncandescent‐tier2ElectricResistanceElectricFurnaceConstantAirVolume/VariableAirVolumeMetalHalideState of New Mexico EE and DR Study An alysis Approach and Data Development

Global Energy Partners 2-23

An EnerNOC Company

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%.Analysis Approach and Data Developmen t State of New Mexico EE and DR Study

2-24 www.gepllc.com 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 (i nstantaneous 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 th e market could absorb these measures.

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

existing buildings, receive longer adoption cu rves 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 Powe r and Conservation Council ramp rates, and

previous potential studies. They were adjust ed 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 po tential. 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

An EnerNOC Company 

### 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 Me xico 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. stat es. 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 cu rrently 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 la rgest 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.Market Assessment and Market Profiles State of New Mexico EE and DR Study

3-2 www.gepllc.com 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 20,901,581State of New Mexico EE and DR Study Ma rket Assessment and Market Profiles

Global Energy Partners 3-3

An EnerNOC Company



### 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 wa s 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 fr om 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 sect or 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% Low Income

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

3-4 www.gepllc.com 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

7,680 6,474 Total End Use Technology Saturation 

## Average Market Profiles

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

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

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

household electricity usage. The miscellaneous en d 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 coo ling, space heating, miscellaneous and water

heating.State of New Mexico EE and DR Study Ma rket Assessment and Market Profiles

Global Energy Partners 3-5

An EnerNOC Company Figure 3-3 Residential Electricity Use by End Use, 2009

Cooling

13%

Space Heating

7% Heating/

Cooling

0%

Water Heating

7%

Appliances

33% Interior

Lighting

12%

Exterior

Lighting

3% Electronics

15% Miscellaneous

8%

Figure 3-4 presents the end-use shares of tota l 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 segmen ts 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

Water Heating

Appliances

Interior Lighting

Exterior Lighting

Electronics

MiscellaneousMarket Assessment and Market Profiles State of New Mexico EE and DR Study

3-6 www.gepllc.com



### 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 co mmercial 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.State of New Mexico EE and DR Study Ma rket Assessment and Market Profiles

Global Energy Partners 3-7

An EnerNOC Company 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

14.3 7,898 Total End Use Technology Saturation 

## Average Market Profiles

Figure 3-5 shows the breakdown of annual electric ity usage by end use. Li ghting 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 en d-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 gasState of New Mexico EE and DR Study Ma rket Assessment and Market Profiles

Global Energy Partners 3-9

An EnerNOC Company 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 sa les 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 sector s, the industrial marke t 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 5 HP 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%

6,530 100% Total 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 ga s 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 Ma rket Assessment and Market Profiles

Global Energy Partners 3-11

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 indust rial 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 6,530Market 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%ofTotalAnnualElectricityUse Cooling

Space Heating

Comb Heat/Cool

Ventilation

Interior Lighting

Exterior Lighting

Machine Drive

Process

OtherGlobal Energy Partners 4-1

An EnerNOC Company 

### CHAPTER 4



## BASELINE FORECAST

Prior to developing estimates of energy-efficie ncy 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 me tric against which energy-efficiency potentials

— technical, economic, and achievable — are measured.



### 4.1 RESIDENTIAL SECTOR

In general, the baseline forecast incorporates assumptions about econom ic growth, electricity

prices, appliance/equipment standards and buil ding 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 grou p. 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 th e end-use level for the residential sector as a

whole. Overall, residential use increases mode stly, 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 base line forecast beginning in 2012 is the federal

lighting standards. The st andard 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 comb ined heating and cooling that reflects higher

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

particularly in rural areas.

4. Water heating grows modestly as a result of hi gher electric saturation s in new construction.

5. Appliances increase slightly, reflecting the sm all increases in satura tions of dishwashers,

clothes washers and clothes dryers which offs ets 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 substantia l. 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 inco rporate 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 2025AnnualUse(GWh) 

### Cooling

Space Heating

Heat/Cool

Water Heating

Appliances

Interior Lighting

Exterior Lighting

Electronics

MiscellaneousState of New Mexico EE and DR Study Baseline Forecast

Global Energy Partners 4-3

An EnerNOC Company 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 ho usehold. 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 stan dards. 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 2025UseperHousehold(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 re latively flat during the forecast horizon. It

starts at 7,898 GWh in 2009, decreases from 20 10 to 2015 and increases to 7,871 GWh in 2025.

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

sector as a whole. Most end uses show modest gr owth 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 2025AnnualUse(GWh) Cooling

Space Heating

Comb. Heat/Cool

Ventilation

Water Heating

Food Preparation

Refrigeration

Interior Lighting

Exterior Lighting

Office Equipment

MiscellaneousState 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 peri od 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 fore cast at the end-use level for the industrial

sector as a whole. Overall, industrial annual en ergy 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 2025AnnualUse(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 2025GWh 

### Industrial

Commmercial

ResidentialGlobal Energy Partners 5-1

An EnerNOC Company 

### CHAPTER 5



## ENERGY-EFFICIENCY MEASURES

5.1 LIST OF ENERGY EF FICIENCY MEASURES

The first step of the energy efficiency measure analysis is to identify the list of all relevant

energy efficiency measures that should be consid ered for the New Mexico potential assessment.

For this study, Global prepared a preliminary list of measures fo r 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 presen t a summary of the commercial

equipment and non-equipment measures, re spectively. 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 wa ter 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 indu strial measures considered for this study

are described in Volume 6.Energy-Efficiency Measures Stat e 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 S i n g l e F a m i l y

( e x i s t i n g &

n

e w )

Mu l f i F a m i l y

( e x i s t i n g &

n

e w )

Mo

b i l e H o m e

( e x i s t i n g &

n

e w )

L

o w I n c o m e

( e x i s t i n g &

n

e w )

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+) XXXXState of New Mexico EE and DR Stud y 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 S i n g l e F a m i l y

( e x i s t i n g &

n

e w )

M u l f i F a m i l y

( e x i s t i n g &

n

e w )

M o b i l e H o m e

( e x i s t i n g &

n

e w )

L

o w I n c o m e

( e x i s t i n g &

n

e w )

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 XXXXEnergy-Efficiency Measures Stat e of New Mexico EE and DR Study

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

Measure S i n g l e F a m i l y E x i s t i n g

S i n g l e F a m i l y N e w

C o n s t r u c t i o n

Mu

l f i F a mi l y E x i s t i n g

Mu l t i F a m i l y N e w

C o n s t r u c ti o n

Mo

b i l e H o me E x i s t i n g

Mu l t i F a m i l y N e w

C o n s t ru c ti o n

L

o w I n c o me E x i s t i n g

L o w I n c o me N e w

C o n s t r u c t i o n

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 XState of New Mexico EE and DR Stud y 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/yrEnergy-Efficiency Measures Stat e 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 Stud y Energy-Efficiency Measures

Global Energy Partners 5-7

An EnerNOC Company Table 5-5 Summary of Commercial Non-equipment Measures



### Measure E x i s t i n g

N e w



### 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 XEnergy-Efficiency Measures Stat e of New Mexico EE and DR Study

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



### Measure E x i st i n g

N e w



### 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 ControlsState of New Mexico EE and DR Stud y Energy-Efficiency Measures

Global Energy Partners 5-9

An EnerNOC Company Table 5-7 Summary of Industrial Measures

Measure O t h e r I n d u s t r i a l

E x i s t i n g

O t h e r I n d u s t r i a l Ne w

S

e m i c o n d u c t o r E x i s t i n g

S e m i c o n d u c t o r Ne

w

O i l a n d P e t r o l e u m

E x i s t i n g

O i l a n d P e t r o l e u m

Ne w

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 

### XXXXEnergy-Efficiency Measures Stat e of New Mexico EE and DR Study

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

Measure O t h e r I n d u s t r i a l

E x i s t i n g

O t h e r I n d u s t r i a l N e w

S

e m i c o n d u c t o r E x i s t i n g

S e m i c o n d u c t o r N e w

O i l a n d P e t r o l e u m

E x i s t i n g

O i l a n d P e t r o l e u m

N e w

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 

### XXXXState of New Mexico EE and DR Stud y Energy-Efficiency Measures

Global Energy Partners 5-11

An EnerNOC Company Table 5-9 Summary of Industrial Measures (Continued)

Measure Ot h e r I n d u s t r i a l

E x i s t i n g

Ot h e r I n d u s t r i a l Ne w

S

e m i c o n d u c t o r E x i s t i n g

S e m i c o n d u c t o r Ne

w

Oi l a n d P e t r o l e u m

E x i s t i n g

Oi l a n d P e t r o l e u m

Ne w

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 XEnergy-Efficiency Measures Stat e of New Mexico EE and DR Study

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

Measure O t h e r I n d u s t r i a l

E x i s t i n g

O

t h e r I n d u s t r i a l N e w

S

e m i c o n d u c t o r E x i s t i n g

S e m i c o n d u c t o r N e w

O i l a n d P e t r o l e u m

E x i s t i n g

O i l a n d P e t r o l e u m

N e w

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 for surface motors X X

Smart Well X XState of New Mexico EE and DR Stud y Energy-Efficiency Measures

Global Energy Partners 5-13

An EnerNOC Company



### 5.2 RESULTS OF THE ECONOMIC SCREEN

Table 5-11 summarizes the numb er of equipment and non-equi pment 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 analys is. 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 en ergy 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 fo recast 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 foreca st 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 ener gy 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 forecasts 12

.

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 Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-3

An EnerNOC Company Figure 6-1 Summary of Achievab le Potential Energy Savings



### Achievable

‐ Low Achievable

‐ High Economic

Technical

0% 5% 10% 15% 20% 25%

2012 2015 2020 2025Savingsas%ofBaselineForecast

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 2025GWh



### 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 IndustrialSavingsin2025(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 Electr ic 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 56,255Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study

6-6 www.gepllc.com 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 52,084State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-7

An EnerNOC Company 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 3,509,632Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study

6-8 www.gepllc.com Table 6-4 presents the peak demand savings from energy-efficiency meas ures for each entity.

Table 6-4 Energy Efficiency Potentia l 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 4.81State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-9

An EnerNOC Company 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 5.67Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study

6-10 www.gepllc.com 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 al l 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 base line 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 foreca st. By 2025, technical potential reaches 1,752State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-11

An EnerNOC Company GWh, 23.6% of the baseline energy forecast. Peak demand savings are 41 MW in 2012,

which represents 3.1% of the baseline foreca st 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 seve ral 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%Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study

6-12 www.gepllc.com Figure 6-4 Residential Energy Efficiency Potential Savings



### Achievable

‐ Low Achievable

‐ High Economic

Technical

0% 5% 10% 15% 20% 25%

2012 2015 2020 2025Savingsas%ofBaselineForecast

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 2024GWh



### Baseline Forecast

Achievable

‐ Low

Achievable

‐ High

Economic

TechnicalState of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-13

An EnerNOC Company 

### 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, sing le-family homes account for the largest share of

potential savings by segment, displayed in Table 6-6.

Table 6-7 shows the savings by en d use and market segment. The segments are similar in terms

of the savings opportunities by end use, but th ere are a few notable differences. Single-family

homes have more exterior lighting and so have mo re savings potential for this end use. Similarly,

single-family homes have swimming pools and ther efore 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 conditioni ng compared to single-f amily homes, reflecting

an older appliance stock. Low income has a relati vely 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 Poten tial 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

‐ 620Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study

6-14 www.gepllc.com 

### 6.2.2 Residential Potential by End Use, Technology and Measure Type

Table 6-8 provides estimates of sa vings for each end use and type of potential. Focusing first on

technical and economic potential, there are si gnificant savings that are both possible and

economic in numerous end uses:

• Water Heating offers the highest technical potentia l, which reflects the across the boardinstallation of solar water heating. However, solar water heating does not become costeffective, using the study’s a ssumptions of equipment cost and avoided cost, during the

forecast period.

• Cooling offers the second-highest technical pote ntial, 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 maintenanc e. 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 th e 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 opportun ities. 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 th e forecast horizon, so economic potential

reflects the purchase of ENERGY STAR units across all technologies in this end use.State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-15

An EnerNOC Company 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 1,752Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study

6-16 www.gepllc.com 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 saving s since heat pump water heaters are cost

effective starting in 2012.

• Electronics, appliances, and cool ing 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 mino r contributions from this end

use.

Figure 6-6 Residential Achievab le Potential by End Use in 2025



### 0 50 100 150 200 250 300 350Savingsin2025(GWh) 

### Achievable

‐ High

Achievable

‐ Low

As described in Chapter 4, using our LoadMAP mode l, we develop separate estimates of potential

for equipment and non-equipment measures. Tabl e 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.State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-17

An EnerNOC Company 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 36.25 136.90 427.91 684.21Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study

6-18 www.gepllc.com 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 accordin g to its share of total

residential electricity use. Then, these estimate s were adjusted to reflect weather differences

between the entity’s area and the state as a whole.State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-19

An EnerNOC Company Table 6-11 Residential Efficien cy 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 28,114Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study

6-20 www.gepllc.com 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 4,107State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-21

An EnerNOC Company 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 foreca st. 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 foreca st 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.Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study

6-22 www.gepllc.com 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 2025Savingsas%ofBaselineForecastState of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-23

An EnerNOC Company 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 2025GWh



### 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 saving s 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 tec hnical potential at 548 GWh in 2025. However,

linear LED lighting is not cost effective, so econ omic 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 te chnical potential at 297 GWh in 2025. These

savings result from installation of high-efficiency equipment and numerous thermal shell

measures, HVAC control strategies, and retroc ommissioning. 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 comme rcially available. Most of these measures are

cost effective, resulting in economic potentia l 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 an d 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 surp risingly, 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.Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study

6-24 www.gepllc.com 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 1,425.0State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-25

An EnerNOC Company Figure 6-9 Commercial Achievable Poten tial Savings by End Use in 2025 (GWh)



### 0 50 100 150 200 250 300Savingsin2025(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.Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study

6-26 www.gepllc.com 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 85.7 252.6 361.2State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-27

An EnerNOC Company 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 85.7 252.6 361.2Electric Energy Efficiency Potential Results State of New Mexico EE and DR Study

6-28 www.gepllc.com 

### 6.3.2 Commercial Potential by Market Segment

Table 6-16 shows potential estimates by segmen t. 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 Reta il 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.State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-29

An EnerNOC Company Figure 6-10 Achievable Potential Savings in 2025 by Commercial Building Type (GWh)

0 10 20 30 40 50 60 70 80 90 100RealisticAchievableSavingsin2025 Achievable

‐ Low

Achievable

‐ High

The Table 6-17 and Table 6-18 pr esents 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 wa lk-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 motorsElectric Energy Efficiency Potential ResultsState of New Mexico EE and DR Study6-30www.gepllc.com

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 Health Lodging MiscellaneousLow High Low High Low High Low High Low High Low High Low HighLow High Low HighLow High Low HighCooling2.3 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 5.2 1.0 2.2 3.5 7.8Air-Cooled Chiller 1.0 2.3 - - 0.0 0.0 0.3 0.6 0.0 0.1- - 0.2 0.4 0.2 0.41.7 4.5 - - 0.1 0.2Evaporative AC - - - - - - - - - -0.1 0.3 - - - - 0.0 0.0 0.0 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 0.0 0.1 0.3 0.1 0.3RTU 1.0 2.2 2.0 4.4 2.4 6.0 3.1 6.5 - - 0.6 1.4 - - - - 0.3 0.7 0.4 0.8 1.8 3.9Water-CooledChiller0.2 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 0.0 0.5 1.1 1.6 3.5CombinedHeating/Cooling0.4 0.8 0.1 0.1 0.0 0.1 0.3 0.7 0.7 1.4 0.1 0.2 - - - - 0.1 0.2 2.2 5.0 0.4 1.0Heat 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 0.2 1.7 4.0 0.4 1.0PTHP 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - - 0.0 0.0 - - - - 0.0 0.0 0.4 1.0 0.0 0.0Ventilation0.2 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 0.1 0.0 0.1 0.5 1.2Water Heating1.4 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 0.7 1.2 2.8 2.0 4.5Food Preparation0.2 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 0.9 0.5 1.5 0.6 1.4Dishwasher 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 0.1 0.1 0.3 0.0 0.0Fryer 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 0.2 0.1 0.2 0.1 0.1Hot FoodContainer0.0 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 0.3 0.2 0.6 0.3 0.6Oven 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 0.3 0.2 0.5 0.3 0.6Refrigeration0.3 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 0.9 0.2 0.6 0.8 1.6Glass DoorDisplay- - - - - - - - - - 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 0.1 0.1 0.2 0.1 0.1Open DisplayCase0.1 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 0.2 0.0 0.1 0.2 0.4Reach-inRefrigerator0.0 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 0.1 0.0 0.1 0.1 0.2Walk-inRefrigerator0.2 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 0.5 0.1 0.3 0.4 1.0Interior Lighting9.1 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 13.4 20.4 27.3 16.0 23.1High-Bay Fixtures 0.2 0.4 0.1 0.1 - - 0.6 1.0 - - - - 0.4 0.6 0.1 0.2 0.1 0.1 - - 3.8 6.4Linear 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 2.6 0.2 0.3 0.7 1.3Screw-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 10.6 20.2 27.0 11.5 15.4Exterior Lighting3.0 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 6.4 3.3 5.2 11.3 18.7HID 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 6.1 1.6 2.8 8.3 14.5Linear 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 0.0 0.0 0.0 0.5 0.8Screw-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 0.3 1.8 2.4 2.6 3.4Office Equipment1.2 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 2.1 0.1 0.2 0.9 1.7DesktopComputer0.6 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 0.4 0.0 0.0 0.4 0.7Laptop 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 0.0 0.0 0.0 0.0 0.0State of New Mexico EE and DR StudyElectric Energy Efficiency Potential ResultsGlobal Energy Partners6-31An EnerNOC CompanySmall Office Large Office Restaurant Retail Grocery Warehouse School College Health Lodging MiscellaneousLow High Low High Low High Low High Low High Low High Low HighLow High Low HighLow High Low HighMonitor 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 0.0 0.0 0.0 0.0 0.0POS 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 0.0 0.0 0.0 0.0 0.1Printer/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 0.0 0.0 0.0 0.0 0.0Server 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 1.6 0.0 0.1 0.4 0.9Miscellaneous0.7 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 0.3 2.5 5.8 0.8 1.6Non-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 0.1 0.0 0.0 0.1 0.1Pool Heater 0.3 0.7 0.1 0.2 - - - - - - - - - - 0.1 0.2 0.0 0.1 0.8 2.2 0.4 0.8Pool Pump 0.3 0.7 0.1 0.2 - - - - - - - - - - 0.2 0.2 0.0 0.1 1.7 3.6 0.4 0.8Total forEquipment15.6 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 23.8 28.1 45.5 25.6 44.1Electric Energy Efficiency Potential ResultsState of New Mexico EE and DR Study6-32www.gepllc.com

Table 6-18 Commercial Achievable Savings from No n-Equipment Measures in 2025 by Building Type (GWh)Small Office Large Office Restaurant Retail Grocery Warehouse School College Health Lodging MiscellaneousLow High Low High Low HighLow High Low High Low High Low High Low High Low High Low High Low HighCooling2.6 7.6 5.2 15.13.110.05.316.42.68.71.13.0 0.20.72.26.012.333.00.92.62.98.5Advanced NewConstruction Designs- - - - 0.4 1.3 - - 0.2 0.6- - - - - - 0.6 2.1 - - - -Air Cooled Chiller -Condenser AirTemperature Reset- - - - - - - - - - - - - - 0.1 0.2 1.1 2.7 - - - -Air Cooled Chiller -Economizer0.6 1.5 - - 0.0 0.0 0.3 0.8 0.1 0.1 - - - - - - 2.0 4.6 - - 0.1 0.1Air Cooled Chiller - VSD- - - --------- 0.10.40.20.54.210.9--0.00.1ComprehensiveRetrocommissioning- - - - - - - - - - - - - - - - 0.0 0.0 - - - -Custom Measures- - - --------- ----0.20.5----Energy ManagementSystem0.9 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 10.4 0.8 2.3 0.5 1.6Insulation - Ceiling (Best)- - - ---0.00.1---- ----------Insulation - Ceiling(Better)0.0 0.1 - - 0.0 0.0 - - - -- - - - - - - - 0.0 0.0 - -Insulation - Ceiling (Good)- - - -0.00.10.10.20.00.1-- ----0.00.0--0.00.0Insulation - Wall Cavity(Best)0.0 0.0 - - - - - - 0.4 1.7- - - - - - 0.1 0.5 - - - -Insulation - Wall Cavity(Better)- - - - - - 0.1 0.5 0.2 0.9- - - - - - 0.1 0.4 - - - -Insulation - Wall Cavity(Good)- - - - - - 0.0 0.0 - - - - - - - - - - - - - -Roofs - High Reflectivity0.0 0.0 - -0.10.50.41.40.10.40.00.2 --------0.10.2RTU - Maintenance0.6 1.9 1.2 4.00.51.81.75.80.82.60.20.8 0.10.20.20.70.20.50.10.31.13.7Thermostat -Clock/Programmable0.1 0.2 0.0 0.1 - - 0.1 0.3 0.2 0.5 - - - - 0.0 0.1 0.1 0.2 - - - -Water Cooled Chiller -Condenser WaterTemperature Reset- - - - - - - - - - 0.1 0.3- - 0.3 0.7 0.0 0.0 - - - -Water Cooled Chiller -Economizer0.2 0.5 0.8 2.0 0.0 0.0 0.1 0.2 0.0 0.0 0.3 0.8 - - - - 0.0 0.0 - - 0.9 2.4Water Cooled Chiller - VSD- - 0.4 1.0------0.41.0 --0.82.10.00.0--0.10.3Windows - High Efficiency0.3 0.9 - -0.83.0--0.00.0-- ----------Space Heating0.4 1.2 0.4 1.20.00.12.37.60.30.90.00.0 0.00.00.62.00.72.10.20.60.10.2Advanced NewConstruction Designs- - - - 0.0 0.0 - - 0.0 0.2- - - - - - 0.0 0.1 - - - -ComprehensiveRetrocommissioning- - - - - - - - - - - - - - - - 0.0 0.0 - - - -Custom Measures- - - --------- ----0.00.0----Energy ManagementSystem0.3 0.9 0.4 1.2 0.0 0.1 0.9 2.8 0.2 0.5 - - - - 0.5 1.4 0.4 1.1 0.2 0.6 0.1 0.2Insulation - Ceiling (Best)- - - ---0.00.0---- ----------Insulation - Ceiling(Better)0.0 0.0 - - 0.0 0.0 - - - -- - - - - - - - 0.0 0.0 - -Insulation - Ceiling (Good)- - - -0.00.00.00.10.00.0-- ----0.00.00.00.00.00.0Insulation - Wall Cavity(Best)0.0 0.0 - - - - - - 0.0 0.0 -- - - 0.0 0.2 0.1 0.4 - - - -Insulation - Wall Cavity(Better)- - - - - - 0.3 1.0 0.0 0.0 -- - - 0.0 0.1 0.1 0.2 - - - -Insulation - Wall Cavity(Good)- - - - - - 0.9 3.2 - - - - - - - - - - - - - -State of New Mexico EE and DR StudyElectric Energy Efficiency Potential ResultsGlobal Energy Partners6-33An EnerNOC CompanySmall Office Large Office Restaurant Retail Grocery Warehouse School College Health Lodging MiscellaneousLow High Low High Low HighLow High Low High Low High Low High Low High Low High Low High Low HighSpace Heating - HeatRecovery Ventilator0.0 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 0.0 0.0 0.0 0.0 0.0Thermostat -Clock/Programmable0.1 0.2 0.0 0.1 - - 0.2 0.5 0.0 0.1 - - - - 0.1 0.3 0.0 0.1 - - - -Combined Heating/Cooling0.6 2.2 1.1 3.90.82.60.51.70.51.70.10.3 1.24.00.10.30.10.40.51.70.72.5Heat Pump - Maintenance0.6 2.1 1.1 3.90.82.60.31.00.51.60.10.3 1.24.00.10.30.10.30.51.60.72.4Insulation - Ceiling (Best)- - - ---0.00.0---- ----------Insulation - Ceiling(Better)0.0 0.0 - - 0.0 0.0 - - - -- - - - - - - - 0.0 0.0 - -Insulation - Ceiling (Good)- - - -0.00.00.00.00.00.0-- ----0.00.00.00.10.00.0Insulation - Wall Cavity(Best)0.0 0.0 - - - - - - 0.0 0.1 -- - - 0.0 0.0 0.0 0.1 - - - -Insulation - Wall Cavity(Better)- - - - - - 0.1 0.2 0.0 0.0 -- - - 0.0 0.0 0.0 0.1 - - - -Insulation - Wall Cavity(Good)- - - - - - 0.1 0.5 - - - - - - - - - - - - - -Ventilation0.0 0.1 0.0 0.10.10.30.00.10.00.10.00.0 0.00.00.00.00.00.00.00.00.20.6Ventilation - CO2Controlled0.0 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 0.0 0.0 0.0 0.1 0.3Ventilation - Exhaust HoodSensor Control- - - - 0.1 0.2 - - 0.0 0.0 - - - - - - - - - - - -Ventilation - VariableSpeed Control- - - - - - - - - - - - - - - - - - - - 0.1 0.3Water Heating0.1 0.1 - -0.10.20.10.30.30.60.10.1 ------0.00.0--Water Heating -Drainwater Heat Recovery0.0 0.0 - - 0.0 0.0 - - 0.0 0.00.0 0.0 - - - - - - 0.0 0.0 - -Water Heating - FaucetAerators0.1 0.1 - - 0.1 0.1 0.1 0.3 0.2 0.3 0.1 0.1 - - - - - - 0.0 0.0 - -Water Heating - Hot WaterSaver- - - - 0.0 0.1 - - 0.1 0.2 - - - - - - - - - - - -Water Heating - PipeInsulation- - - - - - - - 0.0 0.0 - - - - - - - - - - - -Water Heating - TankBlanket0.0 0.0 - - 0.0 0.0 - - 0.00.0 - - - - - - - - - - - -Refrigeration- - - -----0.20.9-- ----------Open Display Case - NightCovers- - - - - - - - 0.2 0.9 - - - - - - - - - - - -Exterior Lighting0.1 0.2 0.1 0.30.10.40.30.80.10.40.00.0 0.00.00.00.10.30.80.10.30.10.4Advanced NewConstruction Designs- - - - 0.0 0.1 - - 0.0 0.1- - - - - - 0.0 0.2 - - - -ComprehensiveRetrocommissioning- - - - - - - - - - - - - - - - 0.0 0.0 - - - -Custom Measures- - - --------- ----0.00.1----Energy ManagementSystem0.1 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 0.5 0.1 0.3 0.1 0.4Lighting Commissioning0.0 0.0 0.0 0.00.00.00.00.00.00.00.00.0 0.00.00.00.00.00.00.00.00.00.0LightingRetrocommissioning- - 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 0.0 - -Interior Lighting0.8 2.1 1.5 4.10.61.42.87.21.54.10.30.5 0.30.50.51.41.75.01.02.10.51.3Advanced NewConstruction Designs- - - - 0.1 0.3 - - 0.3 1.0- - - - - - 0.3 1.0 - - - -ComprehensiveRetrocommissioning- - - - - - - - - - - - - - - - 0.0 0.0 - - - -Custom Measures- - - --------- ----0.10.4----Energy ManagementSystem0.4 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 3.1 0.5 1.4 0.3 0.9Electric Energy Efficiency Potential ResultsState of New Mexico EE and DR Study6-34www.gepllc.comSmall Office Large Office Restaurant Retail Grocery Warehouse School College Health Lodging MiscellaneousLow High Low High Low HighLow High Low High Low High Low High Low High Low High Low High Low HighIndoor Lighting -Daylighting Controls0.1 0.4 0.0 0.1 0.1 0.2 0.3 0.9 0.1 0.3 - - - - 0.0 0.0 0.0 0.1 0.0 0.0 - -Interior Fluorescent -Photocell-ControlledDiming Ballasts- - - - - - - - 0.3 0.6 - - - - - - 0.0 0.0 - - - -Interior Lighting - GuestRoom Controls- - - - - - - - - - - - - - - - - - - - - -Interior Lighting - LED ExitLighting0.1 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 0.2 0.4 0.5 0.2 0.3Lighting Commissioning0.1 0.2 0.1 0.20.00.10.20.70.10.30.00.1 0.00.00.00.10.00.10.00.10.00.1LightingRetrocommissioning- - 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 0.1 0.0 0.0 - -Office Equipment0.1 0.3 0.2 0.70.00.00.00.10.00.00.00.1 0.00.10.00.10.10.30.00.00.10.2Office Equipment - EnergyStar Power Supplies0.1 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 0.3 0.0 0.0 0.1 0.2Miscellaneous0.0 0.1 - --------- ----0.00.00.00.10.00.1Pool Pump - Timer0.0 0.1 - --------- ----0.00.00.00.10.00.1Total of Other Measures4.7 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 41.6 2.7 7.4 4.6 13.7State of New Mexico EE and DR Study Electr ic 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 potentia l for each entity in the state. These estimates

were developed by taking the total end-use estima tes for the state and allocating them to each

entity according to its share of total commercia l 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 mi x of commercial sector activity in each entity’s

area is consistent with the mix for the state as a whole. While th is is a reasonable assumption,

each entity should take care in applying thes e estimates. For example, if the entity has no

colleges, then the savings attributed to this se ctor at the state level should be removed or

reallocated among the remaining sectors 13

.

Table 6-19 Commercial Efficien cy 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 1,359State of New Mexico EE and DR Study Electr ic 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 130,207 423,795 803,665 949,820Electric 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 ex traction 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 ar e 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 efficien cy 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 fr om these customized ap proaches should be

characterized individually. To further understand these opportunities, it would be appropriate to

carry out site-specific engineerin g 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 Pote ntial 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 Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-39

An EnerNOC Company Figure 6-11 Industrial Energy Efficiency Potential Savings



### Achievable

‐ Low Achievable

‐ High Economic

Technical

0% 5% 10% 15% 20%

2012 2015 2020 2025Savingsas%ofBaselineForecast

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 2025GWh



### Baseline Forecast

Achievable

‐ Low

Achievable

‐ High

Economic

TechnicalElectric 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 fo r energy savings across the range of potential.

Cooling and lighting have the next highest saving s 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 1,594State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-41

An EnerNOC Company 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 fo r 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 Pote ntial Savings by End Use in 2025 (GWh)

0 100 200 300 400 500 600 700 800 900 1,000Savingsin2025(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 IndustrialAchievable‐LowSavingsin2025(GWh)

Cooling

Space Heating

Heat/Cool

Ventilation

Interior Lighting

Exterior Lighting

Machine Drive

Process

OtherElectric 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 potentia l for each entity in the state. These estimates

were developed by taking the total end-use estima tes for the state and allocating them to each

entity according to its share of total industri al 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 mi x of industrial activity in each entity’s area is

consistent with the mix for the state as a whole. Th erefore, 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 remove d or reallocated among the remaining sectors 14

.

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.State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-43

An EnerNOC Company 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 0Electric 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 esti mated 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 progra m 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.State of New Mexico EE and DR Study Electr ic Energy Efficiency Potential Results

Global Energy Partners 6-45

An EnerNOC Company 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

‐ AverageState of New Mexico EE and DR StudyElectric Energy Efficiency Potential ResultsGlobal Energy Partners6-46An EnerNOC Company Table 6-23 Summary of Costs for Achievable Potential20122013201420152016201720182019202020212022202320242025AverageAnnualSavings(GWh)Achievable‐Low66.681.052.346.5103.8100.8116.2145.996.873.973.9155.9170.6188.8105.2Achievable‐High187.0199.4107.779.0201.1168.7183.8223.4138.0120.2129.8270.2307.0340.1189.7IncrementalMeasureCost(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$60.5$68.6$51.4Achievable‐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$96.2$102.8$87.7ProgramAdministrationCosts(Million$)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$9.1$10.3$7.7Achievable‐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$14.4$15.4$13.2TotalProgramCostwithIncentivesat50%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$39.4$44.6$33.4Achievable‐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$62.5$66.8$57.0Global Energy Partners 6-47

An EnerNOC Company



### 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 av oided 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 3,883Electric Energy Efficiency Potential Results

6-48 www.gepllc.com Table 6-25 Scenario Analysis Results – En ergy 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 – En ergy 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 2025Global Energy Partners,

500 Ygnacio Valley Road, Suite 450

Walnut Creek, CA 94596 P: 925.482.2000

F: 925.284.3147

E: globalhq@gepllc.com ABOUT GLOBAL

Global Energy Partners is a pr emier provider of energy and

environmental engineering and tech nical services to utilities,

energy companies, research organizations,

government/regulatory agencies and private industry.

Global’s offerings range from strategic planning to turn-key

program design and implementation and technology

applications.

Global is a wholly-owned subsidiary of EnerNOC, Inc committed

to helping its clients achieve strategic business objectives with a

staff of world-class experts, state of the art tools, and proven

methodologies.