*** Draft for Public Input *** 

Evaluation Measurement and Verification (EM&V) Guidance

for Demand-Side Energy Efficiency (EE)

U.S. Environmental Protection Agency

DRAFT FOR PUBLIC INPUT

August 3, 2015
*** Draft for Public Input *** 

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iii

Contents

Public Comment Opportunity.............................................................................................................v

Acronyms and Abbreviations............................................................................................................vii

1. Introduction...................................................................................................................................1

1.1 Experience with EM&V for Demand-Side EE ..............................................................................1

1.2 Determining Baselines..............................................................................................................2

1.3 Approach to EM&V in the Emission Guidelines..........................................................................3

1.4 Applicability and Scope of this Guidance Document...................................................................4

1.5 How to Use this Document........................................................................................................5

1.6 Intended Audience....................................................................................................................6

1.7 Evolving EM&V Practices and Guidance Updates .......................................................................6

2. EM&V Guidance Applicable to All Demand-Side EE .........................................................................7

2.1 EM&V Methods........................................................................................................................8

2.1.1. Discussion ...................................................................................................................................8

2.1.2. Applicable Guidance ...................................................................................................................9

2.2 Electricity Savings Metrics and Baselines.................................................................................11

2.2.1. Discussion .................................................................................................................................11

2.2.2. Applicable Guidance .................................................................................................................12

2.3 Reporting Timeframes and Considerations..............................................................................14

2.3.1. Discussion .................................................................................................................................14

2.3.2. Applicable Guidance .................................................................................................................15

2.4 Deemed Savings .....................................................................................................................15

2.4.1. Discussion .................................................................................................................................15

2.4.2. Applicable Guidance .................................................................................................................16

2.5 Independent Factors Affecting Energy Consumption and Savings.............................................17

2.5.1. Discussion .................................................................................................................................17

2.5.2. Applicable Guidance .................................................................................................................17

2.6 Accuracy and Reliability of Quantified Savings.........................................................................18

2.6.1. Discussion .................................................................................................................................18

2.6.2. Applicable Guidance .................................................................................................................19

2.7 Avoiding Double Counting.......................................................................................................20

2.7.1. Discussion .................................................................................................................................20

2.7.2. Applicable Guidance .................................................................................................................21

2.8 Effective Useful Life and Persistence of Savings .......................................................................22

2.8.1. Discussion .................................................................................................................................22

2.8.2. Applicable Guidance .................................................................................................................22

2.9 Savings Quantification and Verification Cycles.........................................................................23

2.9.1. Discussion .................................................................................................................................23

2.9.2. Applicable Guidance .................................................................................................................24

2.10 Transmission and Distribution (T&D) Savings Adders .............................................................24

2.10.1. Discussion ...............................................................................................................................24

2.10.2. Applicable Guidance ...............................................................................................................25

2.11 Interactive Effects.................................................................................................................25

2.11.1. Discussion ...............................................................................................................................25
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2.11.2. Applicable Guidance ...............................................................................................................25

2.12 Use of EE EM&V Protocols and Guidelines.............................................................................26

2.12.1. Discussion ...............................................................................................................................26

2.12.2. Applicable Guidance ...............................................................................................................28

3. Supplemental Guidance for Specific Categories of EE.....................................................................29

3.1 Demand-Side EE Programs......................................................................................................29

3.1.1. Program Description.................................................................................................................29

3.1.2. Applicable Guidance – Direct Action EE Programs...................................................................31

3.1.3. Applicable Guidance – Indirect Action EE Programs ................................................................31

3.2 Project-Based Energy Efficiency...............................................................................................32

3.2.1. Description................................................................................................................................32

3.2.2. Applicable Guidance – Project-Based Energy Efficiency...........................................................33

3.3 Building Energy Codes.............................................................................................................36

3.3.1. Description................................................................................................................................36

3.3.2. Applicable Guidance – State and Local Government Building Energy Code and 

Compliance Programs...............................................................................................................37

3.4 Incremental Product Energy Standards....................................................................................40

3.4.1. Description................................................................................................................................40

3.4.2. Applicable Guidance – State and Local Government Incremental Product Energy 

Standards..................................................................................................................................40

Appendix A. Glossary of Terms....................................................................................................... A-1

Appendix B. Optional EM&V Plan Template for Demand-Side EE..................................................... B-1

Appendix C. EM&V Methods for Common EE Programs, Projects, and Measures: Best 

Practices and Resources................................................................................................................. C-1
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Public Comment Opportunity

The EPA invites the public to comment on the draft EM&V guidance and make recommendations for 

how it can be improved for the purpose of implementing the applicable EM&V provisions of the CPP. 

Comments pertaining to aspects of the proposed model trading rule must be submitted in the 

regulatory docket for that action. Such comments should not be submitted to the email address below.

Important information about the comment process includes: 

• The draft guidance can be accessed at: http://www2.epa.gov/cleanpowerplantoolbox

• The public will have 90 days following the publication of the proposed model trading rule in the 

Federal Register to comment

• Comments pertaining to this EM&V guidance should be submitted to: emvinput@epa.gov

• All comments received by the EPA will be considered as the EPA works to finalize the EM&V 

guidance

• The EPA invites the public and all interested stakeholders to comment on any aspect of the draft 

EM&V guidance; however, as the EPA works to finalize this document, the agency has particular 

interest in feedback on the following questions: 

- Does the guidance provide enough information to help EE providers determine what EM&V 

methods (i.e., project-based measurement and verification, comparison group methods, and 

deemed savings) to use for purposes of quantifying savings from specific EE programs, projects, 

and measures? 

- Does the guidance include sufficient information about the appropriate circumstances and 

safeguards for the use of deemed savings values? For project-based measurement and 

verification and comparison group methods? 

- Should the guidance specifically encourage greater use of comparison group approaches? Under 

what circumstances is the application of such empirical methods practical and cost-effective? 

Would additional guidance be useful on “top-down” econometric EM&V methods, and the ways 

in which such methods can be used to verify savings at a high level of aggregation?

- Is the guidance in Section 3 on particular EE program types (consumer-funded EE programs, 

project-based EE, building energy codes, and appliance standards) helpful, clearly presented, 

and sufficient/complete? Can this guidance be reasonably implemented, considering data 

availability, cost effectiveness, accuracy of results, and other factors?

- Is the guidance on important technical topics (e.g., common practice baselines, accuracy and 

reliability, verification) helpful, clearly presented, and sufficient/complete? Can this guidance be 

reasonably implemented, considering data availability, cost effectiveness, accuracy of results, 

and other factors? 

- How useful and usable is the guidance, overall? Does the relationship between the component 

parts (i.e., Sections 1-3 and Appendices A-C) clear and relatively easy to follow? Is each of these 

sections and appendices helpful, clearly presented, and sufficient/complete? What specific 

examples, graphics, or other visual elements would help illustrate concepts described in the 
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vi

guidance?

- Does the guidance not cover any important EM&V topics relevant to fulfilling the EM&V related 

requirements of the emission guidelines? Is additional guidance needed to support the 

implementation of other eligible zero- and low-emitting measures that are directly metered? 

What topics, if any, are unnecessarily included? 

- How can the guidance most effectively anticipate the expected changes and evolution in 

quantification and verification approaches over time (given the time horizon for the emission 

guidelines)? 
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Acronyms and Abbreviations

ANSI – American National Standards Institute

ASHRAE – American Society of Heating, Refrigerating, and Air-Conditioning Engineers 

ASME – American Society of Mechanical Engineers

CHP – combined heat and power (electricity generation systems)

C&S – Building Energy Code and Product Energy Standard 

CPP – Clean Power Plan 

CPB – common practice baseline

CSF – control savings factor (for lighting controls)

EGU – electricity generation units

EE – energy efficiency

EERS – Energy Efficiency Resource Standard

ESCO – Energy services company

EFLH – equivalent full load hours

EM&V – evaluation, measurement, and verification

EPA – (United States) Environmental Protection Agency

EUL – effective useful life

FEMP – (U.S. Department of Energy) Federal Energy Management Program 

HVAC – heating, ventilating, and air-conditioning

HHV – high heating value

IE – independent third-party evaluator

IPMVP – International Performance Measurement and Verification Protocol 

LED – light emitting diode

LHV – low heating value

MMBtu – million British thermal units

MFG – multi-fuel generator

MWh – megawatt-hour

PB-MV – project-based measurement and verification

RCT – randomized control trial

RTF – (Northwest Power and Conservation Council Northwest) Regional Technical Forum

RE – renewable energy

REC – Renewable Energy Certificate

RGU – renewable generating unit

RUL – remaining useful life

SEE ACTION – State and Local Energy Efficiency Action Network

T&D – transmission and distribution (system)

UMP – (United States Department of Energy) Uniform Methods Project

WHP – waste heat to power (electricity generation systems)
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1. Introduction 

The Clean Power Plan (CPP) supports the use of demand-side energy efficiency (EE) as a proven, costeffective, and widely available emission reduction measure1

for the power sector. States, private 

organizations and firms, and other entities around the country have already made substantial 

investments in EE programs and projects, resulting in lower electricity costs, reduced air emissions, and 

cleaner air. The EPA expects such investments to continue, and has established provisions in the CPP for 

crediting the resulting EE savings in certain state plans that demonstrate compliance in terms of an 

emission rate. 

To ensure that EE measures are quantifiable and verifiable, the EPA’s final emission guidelines require 

that all EE providers demonstrate that they will apply best-practice EM&V approaches (as discussed in 

Section VIII.K.3 of the preamble). One way to make this demonstration is to use the presumptively 

approvable EM&V approaches specified in the proposed model trading rule in Section IV.D.8. States may 

also submit other means of meeting the EM&V requirements so long as the state satisfactorily 

demonstrates in the state plan submittal that such alternative means of addressing requirements are as 

stringent as the presumptively approvable approach.

The EPA is providing this draft evaluation, measurement, and verification (EM&V) guidance as 

supplemental information to help states and EE providers successfully implement the EM&V provisions 

in the emission guidelines and proposed model trading rule. Contents of this document include 

background information, baseline definitions and applicable EM&V methods, the appropriate use of 

industry-standard protocols and guidelines, and other topics for successfully quantifying and verifying 

savings for purposes of generating emission rate credits (ERCs) and adjusting an emission rate.

The scope of the guidance is limited to EM&V for demand-side EE. For renewable energy and other zeroand low-emitting measures that generate electricity, all applicable requirements for quantification and 

verification are provided in the emission guidelines and proposed model trading rule, and no further 

guidance is offered at this time. The EM&V guidance similarly does not apply to states submitting mass 

(or tonnage) based plans. In these cases, compliance is determined solely by CO2 emissions 

measurements at the affected source.

1.1 Experience with EM&V for Demand-Side EE

From the time that demand-side EE emerged as an important energy strategy in the 1970s,2efforts to 

quantify and verify the MWh savings of these actions have been critical to their success, credibility, and 

expansion. The earliest such efforts involved project-based measurement and verification (PB-MV) of 

individual projects; this was followed by an evolution and improvement in practices for a broad range of 

 

1

The emission guidelines use the term “measure” to refer to an eligible action that results in MWh that can be 

used to adjust an emission rate for compliance purposes. In the context of demand-side EE, “measure” refers to

an installation or modification of equipment or systems at an end-use energy consumer facility – or strategy 

intended to affect consumer energy use behaviors – that reduces the amount of energy that would otherwise have 

been used to deliver an equivalent or improved level of end-use service.

2

National Energy Program Fact Sheet on the President’s Program, April 20, 1977. Available at 

http://www.presidency.ucsb.edu/ws/?pid=7373.
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EE program strategies and delivery mechanisms across sectors.

3

Today, these EM&V practices are 

applied by utilities, energy service companies (ESCOs), and other EE providers. They are also backed up 

by several well-established protocols and guidelines, and overseen by Public Utility Commissions (PUCs)

and other implementing agencies and authorities. The EM&V industry is now comprises many large 

firms and hundreds of individual practitioners, and is supported by training and certification programs, 

as well as a rich library of published reports and publicly available data and technical resources.

The EM&V approaches in wide use today – including budget levels, oversight procedures, and preferred 

methods – are derived from PUC4requirements for consumer-funded EE programs, as well as the 

Federal Energy Management Program’s (FEMP) requirements for ESCO projects. While the level of 

review varies somewhat by state and program, these oversight mechanisms have generated the 

majority of the protocols and best practices for quantifying savings in the industry. The specific EM&V 

approach that is applied to a given program or project depends on the type of EE, overall policy 

objectives, available budgets, and other factors. For consumer-funded EE programs and ESCO projects, 

savings are typically quantified on an annual basis. 

With this evolution in the accuracy and reliability of EM&V, many states and utilities now routinely rely 

on EE to achieve energy (MWh) and capacity (MW) goals. In addition, two Independent System 

Operators (ISOs) – ISO New England (ISO-NE) and PJM – have established forward capacity markets 

(FCMs)5that pay suppliers of EE programs and other demand-side resources to compete directly with 

electric generators to meet regional capacity needs. The oversight and quality control of EE resources 

that are bid into the market is governed by EM&V rules and requirements defined in evaluation manuals 

established by ISO-NE and PJM. 

Despite improvements in EM&V over time, quantification knowledge is more robust for some EE 

program and policy types than for others. Additionally, there is limited experience applying EM&V 

procedures and protocols to emissions trading programs, where each MWh of replaced generation 

becomes a commodity that can be bought and sold by a regulated source. Environmental regulators, 

including the U.S. EPA and most state environmental agencies, have limited experience quantifying and 

verifying EE in this regulatory context. As a result, the EPA’s final emission guidelines include a number 

of safeguards and quality-control features that are intended to ensure the accuracy and reliability of the 

claimed EE savings.

1.2 Determining Baselines

The key challenge with quantifying EE savings is the identification of an accurate baseline from which to 

measure MWh results. Regardless of the protocols and procedures applied, all savings values are 

determined by comparing energy use with an EE program or project in place with the best estimate of 

the likely energy use in the absence of the project or measure (the “counterfactual” scenario, or 

baseline). In general, the entity overseeing or managing EE activities determines the applicable baseline 

 

3

EM&V is defined to mean the set of procedures, methods, and analytic approaches used to quantify the MWh 

from demand-side EE and other eligible resources, and thereby ensure that the resulting savings and generation 

are quantifiable and verifiable.

4

These government entities are also referred to as a public service commission or a board of public utilities.

5

Forward capacity markets are intended to ensure sufficient electric generating capacity is available to meet 

future peak electricity demand.
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prior to EE implementation on the basis of policy objectives and various programmatic considerations.

MWh savings are then quantified relative to this baseline using EM&V methods determined by program 

type, available budgets, the magnitude of expected impact, and other factors. 

Figure 1 illustrates observed energy use with an EE project installed, and a baseline of estimated EE use 

without that project. In this illustration, the baseline is determined using information on energy use 

patterns prior to installation. Other methods of determining baseline energy use apply, depending on 

the EE type and the EM&V method used, as described further in this document. 

Figure 1-1. Energy Use Before, During, and After an EE Project is Installed6

1.3 Approach to EM&V in the Emission Guidelines

In June 2014, the EPA proposed carbon pollution emission guidelines for certain existing EGUs, as well as 

a “State Plans Considerations” technical support document (TSD) 7that outlined a general approach to 

establishing EM&V requirements and guidance. The TSD proposed that the EPA’s EM&V provisions could 

leverage the industry-standard practices, protocols, and methods currently utilized by the majority of 

states implementing demand-side EE and RE programs. The EPA further noted that many state PUCs, 

and other regulatory bodies and program management authorities, already have significant EM&V 

infrastructure in place, and some have been applying, refining, and enhancing their approaches for over 

30 years. 

Most public comments on this topic affirmed that the protocols and procedures already in place and 

 

6

Ibid.

7

See discussion beginning on p. 34 of the State Plan Considerations TSD for the Clean Power Plan Proposed Rule: 

http://www2.epa.gov/carbon-pollution-standards/clean-power-plan-proposed-rule-state-plan-considerations.
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widely used should indeed be leveraged in the EPA’s final emission guidelines. Commenters also 

provided numerous examples of well-regarded oversight approaches, quality-control practices, and 

quantification and verification methodologies that are currently applied (in addition to pointing out 

needed improvements to EM&V practices, especially relating to cross-jurisdictional inconsistencies in 

the way EM&V is applied). Additional perspectives shared in comments include the importance of 

striking a reasonable balance between EM&V rigor and accuracy on the one hand, and evaluation costs 

and effort on the other, and the need for the EPA to avoid excessive interference with EM&V practices 

that are already robust, transparent,

8

and working well. Finally, commenters indicated that it is critical 

for the agency to support the continued evolution of credible EM&V practices into the future.

1.4 Applicability and Scope of this Guidance Document

This document establishes 

guidance to help states, affected 

EGUs, and EE providers (including 

the firms they hire) implement 

the requirements in the EPA’s 

emission guidelines, as well as 

the presumptively approvable 

EM&V approaches for 

quantifying and verifying MWh 

savings. As specified above, the 

guidance applies only in the 

context of rate-based state 

plans—including “emission 

standards” and “state measures”

plan types—that explicitly credit 

MWh savings in the form of ERCs 

or other denominator rate 

adjustments.

In terms of programmatic 

applicability, this document 

applies to all EE activities 

initiated by EE providers such as 

investor-owned utilities (IOUs), 

public utilities, private 

organizations (such as energy services companies, or ESCOs), and the owners and operators of large 

commercial and industrial end-users. It is also applicable to programs implemented in all customer 

sectors, including low-income.9

 

8

E.g., providing an opportunity for public involvement in planning activities, internet access to EM&V plans and 

reports, and disclosure of relevant inputs, methods, and assumptions.

9

It is important to note that low-income programs are generally implemented for reasons other than maximizing 

energy savings. A primary goal of these programs is to lower the burden of energy costs for a disadvantaged 

population. Alleviating energy burden as broadly as possible is related to energy savings but has other dimensions. 

What is Not Covered

This document provides guidance on the best practices, technical 

assumptions, and industry-standard protocols and procedures 

that can be used to quantify and verify MWh savings from 

demand-side EE. 

This document does not:

• Apply to zero- or low-emitting measures other than EE. 

• Prescribe which demand-side EE measures are eligible.

• Provide criteria for projecting the impacts of such measures. 

• Offer information or resources about calculating displaced CO2

emissions from EE. 

• Address the accounting procedures for how a quantified and 

verified MWh can be used to adjust a rate, or for how crossjurisdictional issues are addressed.

• Provide information on other state plan requirements, such as 

the operation of ERC tracking or emission trading systems. 

Information about these aspects of state plan submissions is 

provided in Section VIII of the draft model trading rule.
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This EM&V guidance does not apply to states electing to submit mass-based plans in which compliance 

is based on monitored emissions at the affected source10. Therefore, mass-based plans do not require 

explicit adjustments to emission rates based on demand-side EE.

1.5 How to Use this Document

This guidance is organized and intended to be used, as follows:

• Section 2 provides a high-level discussion of 12 key EM&V topics and establishes guidance to help EE 

providers develop EM&V plans that document how the applicable regulatory requirements will be 

addressed. The guidance in this section applies to all demand-side EE used to generate ERCs and 

otherwise adjust an emission rate.

• Section 3 establishes additional EM&V guidance—beyond the general guidance provided in 

Section 2—for several common EE program and project types. The specific program and project 

types addressed comprise: 

- Programs implemented using utility customer funds (“utility EE programs”)

- Individual or aggregated EE projects, such as those implemented by ESCOs or at industrial 

facilities (e.g., water treatment plants)

- Building energy codes

- Appliance energy standards

• Appendix A provides a brief glossary of key terms used in this document. This glossary is intended to 

be consistent with industry-standard protocols and reference documents, and can be supplemented 

with the more complete glossary provided in the SEE Action Energy Efficiency Impact Evaluation 

Guide.

11

• Appendix B provides templates for program and project EM&V plans. These templates can be used 

(but are not required) to indicate how the relevant approaches, methods, and parameters required 

by the emission guidelines will be applied over the course of program and project implementation. 

As described below, EM&V plans are a required component of a qualification package used to 

generate ERCs from eligible resources.

 

Such programs also serve other public policy objectives and produce co-benefits beyond electricity savings, 

including but not limited to health, safety and family stability. In addition, these programs typically are designed 

with the intent to efficiently deliver bundled services. For all these reasons, energy savings is only one metric by 

which such programs are measured. The U.S. Department of Energy (DOE) Weatherization Assistance Program 

(WAP) that offers funding to states for weatherizing low-income homes, uses the number of homes weatherized as 

the primary metric to evaluate performance. While these additional considerations affect the decision criteria for 

determining cost-effectiveness of these programs, the methods for verifying their electricity savings are the same 

as those used for evaluating EE for non-low income consumers.

10 It should be noted that states with mass-based plans may have PUC-led EM&V requirements to ensure that 

consumer-funded EE programs are cost-effective and achieve incremental savings.

11 State and Local Energy Efficiency Action Network. 2012. Energy Efficiency Program Impact Evaluation Guide. 

Prepared by Steven R. Schiller, Schiller Consulting, Inc., www.seeaction.energy.gov.
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• Appendix C discusses considerations involved in selecting and implementing the EM&V methods in 

Section 2.1. It also provides, for several common EE measures, illustrative examples of how PB-MV

can be applied, with information about the applicable analytic steps and best practices.

While this draft EM&V guidance is not an EM&V primer, it provides discussion and references to several 

industry-standard protocols, guidelines, and other resources such as the State and Local Energy 

Efficiency Action Network (SEE Action) EM&V Web portal12 and the EPA’s emission guidelines page.

13

1.6 Intended Audience

This guidance is intended for state officials, providers of demand-side EE, and private firms (e.g., 

evaluators and verifiers) hired to help execute the EPA’s provisions for quantification and verification of 

EE savings. For state air regulators, lay readers, and the public, the high-level descriptions of the 12 

topics addressed in Section 2 may be helpful. These descriptions are followed by a discussion of 

applicable guidance that EE providers, evaluators, and verifiers can use as they develop and implement 

EM&V plans. The guidance can also be used by private organizations and firms, the public, and other

parties interested in better understanding the EPA’s EM&V requirements for purposes of participating in 

state plan development and similar processes.

1.7 Evolving EM&V Practices and Guidance Updates

The EPA recognizes that the best-practice EM&V approaches, protocols, and procedures that are now 

used by states, EE providers, and others – and upon which this guidance is largely based – will evolve 

and improve over time as new technologies emerge and the EE marketplace changes. To ensure that 

this guidance continues to be relevant and helpful over time, the EPA intends to periodically provide 

updates that reflect changes to what is considered best practice. 

The agency may also release complementary guidance on how to manage EE policies, programs, and 

projects as a portfolio and strategically invest in EM&V to reduce uncertainty and better deliver on an 

aggregate level of energy savings. Such guidance would define a verification approach involving 

econometric analysis of aggregate consumption data for geographic areas over multiple years. The 

intent of such an approach would be to provide flexibility to states with established EE activity, to make 

strategic trade-offs across in their EE and EM&V investments across their EE portfolios, while ensuring 

that all EM&V-related regulatory requirements in the emission guidelines are satisfied.14 This approach 

can be a useful check and balance in assessing the aggregate impact of multiple policies, programs and 

measures.

 

12 See: https://www4.eere.energy.gov/seeaction/evaluation-measurement-and-verification-resource-portal

13 http://www2.epa.gov/cleanpowerplan

14 This guidance would apply to states that elect to incorporate demand-side EE outside of an ERC trading program, 

and that manage their EE policies, programs and projects as a portfolio. EPA anticipates that a combination of 

elements will be required to demonstrate adequate stringency of verification at the portfolio level and will be 

issuing further guidance
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2. EM&V Guidance Applicable to All Demand-Side EE

This section includes EM&V guidance for 12 key topics 

that is applicable to all demand-side EE that is used to 

generate ERCs or otherwise adjust an emission rate. It 

includes high-level background information, guidance,

and terms to help EE providers develop EM&V plans. As 

previously described, the guidance provided here

leverages and is consistent with current EM&V best 

practices, protocols, and procedures that are already 

used by the majority of states across the country. This 

guidance therefore balances the need for rigor and

accuracy with the effort and cost associated with 

quantification and verification.

For each of the 12 topics, the guidance provided is 

generally consistent with EM&V best practices. This 

means that the guidance either (1) is consistent with 

established protocols or guidelines that have been 

developed with expert and stakeholder input; or (2) 

uses alternative methods that are well documented 

and have been subjected to and endorsed by peer 

review, but are not documented in established 

protocols or guidelines. The best practices 

recommended here generally falls into the first 

category.

This section of the guidance is supplemented with additional best practices and technical assumptions 

applicable to common EE program categories (Section 3) and illustration of how these approaches 

should be applied to certain EE project and measure types (Appendix C). For the 12 EM&V topics

addressed below, the following information is provided:

• Discussion: This section includes a high-level overview, relevant background information, and 

applicability to the EPA’s emissions guidelines.

• Applicable Guidance: This information is intended to help states, EE providers, and private firms 

hired to quantify and verify EE savings implement the regulatory requirements defined in the 

emission guidelines, as reiterated here. These approaches and assumptions expand upon, illustrate, 

and provide practical clarification of the preamble and emission guidelines and are based on 

industry best practices. 

• Key Terms: Text boxes provide terminology for key EM&V concepts, consistent with industrystandard usage.

The EM&V topics covered in this section include:

1. EM&V methods 

2. Electricity savings metrics and baselines

Key Terms 

 EE measure: a single technology, energyuse practice or behavior that, once 

implemented or adopted, reduces 

electricity use of a particular end-use, 

facility, or premises; EE measures may be 

implemented as part of an EE program or 

as an independent privately-funded 

action.

 EE project: a combination of multiple 

technologies, energy-use practices or 

behaviors implemented at a single facility 

or premises for the purpose of reducing 

electricity use; EE projects may be 

implemented as part of an EE program or 

as an independent privately-funded 

action.

 EE program: Organized activities 

sponsored and funded by a particular 

entity to promote the adoption of one or 

more EE project or EE measure with 

similar characteristics for the purpose of 

reducing electricity use. 
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8

3. Reporting timeframes and considerations

4. Deemed savings

5. Independent factors affecting energy consumption and savings 

6. Accuracy and reliability of quantified savings

7. Avoiding double counting

8. Effective useful life and persistence of savings

9. Savings quantification and verification cycles

10. Transmission and distribution (T&D) savings adders

11. Interactive effects

12. Use of EE EM&V Protocols and Guidelines

The presumptively approvable approaches for each of these topics are described in Section IV.D.8 of the 

proposed model trading rule.

2.1 EM&V Methods 

2.1.1. Discussion

Three general categories of EM&V methods for quantifying the MWh savings include 1) deemed savings

2) project-based measurement and verification, and 3) comparison group methods. Each of these 

methods is defined in industry-standard protocols and commonly applied by EE providers, oversight 

entities, and the firms they hire to quantify 

and verify savings. The decision of which 

method or methods to apply for which EE 

activities or components involves 

consideration of factors such as objectives 

of the EE activity being evaluated, the scale 

of the activity, and evaluation budget and 

resources. PB-MV and deemed savings are 

commonly used for determining savings 

from individual EE measures and projects. 

By contrast, comparison-group methods 

are usually only used to estimate savings 

from EE programs, but the use of such 

methods could be expanded further. 

Key Terms 

 Deemed savings values are estimates of electricity 

savings for a single unit of an installed EE measure that 

(1) has been developed from data sources (such as prior 

metering studies) and analytical methods that are widely 

considered acceptable for the measure and purpose, and 

(2) is applicable to the situation under which the 

measure is being implemented. Common sources of 

deemed savings values are previous evaluations and 

studies that involved actual measurements and analyses. 

With deemed savings, the per-unit MWh values are 

determined and agreed to by parties prior to EE 

implementation. When deemed savings are used to 

quantify MWh savings, a separate verification process is 

needed to confirm the quantity of units installed.
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9

Related to comparison group methods is 

the approach of using macroeconomic 

models, sometimes known as “top-down”

EM&V. Top-down EM&V methods to 

evaluate portfolios of EE programs 

involves using (1) aggregate (e.g., utility 

service area, county, census block, etc.) 

energy use or per-unit energy 

consumption indices (e.g., energy 

consumption per-unit of output or per 

capita) and (2) energy-use driver data 

(e.g., income, prices, population) to 

determine savings from portfolios of 

programs. Some states have adopted this 

approach as a complement to the abovelisted methods in order to confirm 

aggregate savings results obtained using 

other approaches. It could also be a useful 

approach for mass-based plans to ensure 

the overall effectiveness of EE efforts. 

2.1.2. Applicable Guidance

 Determine which of the above 

allowable EM&V methods to apply for 

quantifying savings for each program 

or type of project. Refer to Appendix C

and Table C-1 for examples of how 

different methods can apply to 

different types of EE. In general, less 

expensive methods (such as deemed 

savings) are acceptable for EE 

components that contribute relatively 

little savings, or where there is little 

uncertainty as to average unit savings.

More rigorous methods (such as PBMV) are recommended for larger, 

more variable, and more complex components of savings. Comparison group methods are ordinarily 

applicable only if:

o A valid comparison group can be defined.

o The program participants are relatively large in number, and relatively homogeneous, such 

as residential or small commercial customers.

o The magnitude of expected savings is large compared to the expected random differences 

between the participant and comparison group averages.

- Provide a rationale in EM&V plans for this determination, and describe how it is consistent with 

industry best practice. 

Key Terms

(continued) 

 Project-based measurement and verification is the 

process of determining savings from an individual EE 

measure or project (versus an EE program). The IPMVP, 

described in Section 3.12, defines two retrofit isolation

and two whole-facility PB-MV options used in the EE 

industry:

- Retrofit isolation – assessing savings from each EE 

measure individually (IPMVP Options A & B). 

- Whole facility – analyzing savings from each EE 

measure in a project/facility collectively (IPMVP 

Option C, review of energy bills or Option D, 

calibrated simulation).

- Some combination of the above.

Because the measurement process ordinarily involves 

direct observation of installed equipment, or of its effects 

on whole-facility consumption, the process is referred to 

as measurement and verification, and a separate 

verification step is not needed for the EE measures 

subject to this process.

 Comparison group EM&V methods determine program 

savings based on the differences in electricity 

consumption patterns between a comparison group the 

program participants. Comparison group approaches 

include randomized control trials (RCTs) and quasiexperimental methods using nonparticipants, and may 

involve simple differences or regression methods.

Because the effects of implemented measures is 

reflected in the observed participant-comparison 

differences, separate verification is not required. These 

methods are generally used to estimate program-level 

savings, not facility- or project-level savings, and are 

therefore considered an evaluation method, as well as a 

PB-MV method.
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10

- When determining the frequency of conducting EM&V for consumer-funded EE programs (every 

one, two, or three years per the proposed model-rule regulations), consider the following: the 

complexity of the program or project, the variability of the savings, the EM&V method being 

applied, and the relative scale and magnitude of savings. In general, less frequent verification is 

appropriate for EE components that contribute relatively little savings, or where there is little 

variability from year to year, and little uncertainty as to measures’ continued operation until the 

next verification period. More frequent verification is recommended for larger, more variable, 

more uncertain, and more complex components of savings. 

• For comparison group approaches, apply best-practice protocols and guidelines such as those 

published by the SEE Action Network and the U.S. DOE’s Uniform Methods Project.

• For deemed savings approaches, follow the guidance provided in Section 2.4 on Deemed Savings, 

which provides terms, suggested approaches, and technical assumptions to ensure that appropriate 

safeguards for the use of deemed savings are implemented. When applying PB-MV methods, use 

one or more best-practice protocols and guidelines. Examples include:

- International Performance Measurement and Verification Protocol (IPMVP, an international PBMV guidance document),15

- Federal Energy Management Program (FEMP) protocols and guidelines,16

- American Society of Heating, Refrigeration, and Air-Conditioning Engineers (ASHRAE) protocols 

and guidelines17, and 

- U.S. DOE, The Uniform Methods Project (UMP): Methods for Determining Energy Efficiency18

• Apply the guidance in Section 2.12 below on Use of EE EM&V Protocols and Guidelines, which 

provides guidance on determining what best-practice protocols and guidelines should be applied.

 Refer to Appendix C of this document for illustrative examples of how these methods can be applied 

in practice. 

 Refer to Table 2-1 for which of the three general categories of EM&V methods can be appropriate 

for different situations or conditions of EE activities.

Table 2-1. Situations where each General Category of EM&V Methods Are or Are Not 

Applicable

Situation or Conditions for 

Applying EM&V

General Category of EM&V Method

Comparison Group PB-MV Deemed

Individual project Method not applicable OK OK

Large numbers of relatively 

homogeneous participants (e.g., 

residential, small commercial)

Method requires this 

condition

OK OK

 

15 http://www.evo-world.org

16 http://www1.eere.energy.gov/femp/pdfs/mv_guidelines.pdf

17 https://www.ashrae.org/home

18 http://www.energy.gov/eere/about-us/ump-protocols (version as of August 2015)
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11

Key Term

 Gross savings: savings calculated with respect to a 

defined baseline. 

 Net savings: the difference between energy 

consumption with the program in place and that which 

would have occurred absent the program.

 Baseline: conditions (including electricity consumption) 

that would have existed without implementation of the 

subject EE activity. Baseline is used to estimate 

measure-, project- and program-related savings.

 Common practice baseline (CPB): default technology 

or condition that would have been in place at the time 

of project implementation absent the EE installation. 

Section 2.2.2 defines the CPB for different types of EE 

activity.

Well-defined, simple, consistent 

EE measures and conditions

OK OK Method requires this 

condition

Large savings per participant, or 

very large number of 

participants

Method requires this 

condition

OK OK

Inconsistent measures and 

conditions across units

OK OK Method not applicable

Complex, unique measures Method not applicable Method is required for 

this condition

Method not applicable

Valid comparison group can be 

defined

Method requires this 

condition

OK OK

EE program contributes 

relatively little savings to total 

EE provider EE portfolio

Method cost may not be 

justified

Method cost may not be 

justified

Method may be 

preferred

EE program contributes 

relatively large savings to total 

EE provider EE portfolio

Method is recommended 

if method requirements 

are also satisfied

Method is typically 

recommended

Method is not typically 

recommended

Note: “OK” indicates method may be applied in this situation.

2.2 Electricity Savings Metrics and Baselines

2.2.1. Discussion

Electricity savings from an EE activity is 

the difference between observed usage 

with EE in place and the usage that would 

have occurred in the absence of EE during 

the same time period. Defining what 

would have happened without the EE 

program or project (i.e., the 

“counterfactual baseline conditions”)

represents the fundamental challenge to 

quantifying savings, and therefore 

warrants a comparatively detailed 

discussion. Baselines are typically defined 

by the installed equipment at the time of 

retrofit, or some other standard 

alternative to the installed EE technology. 

The EPA, for purposes of the emission 

guidelines, defines EE savings as the 

difference between observed electricity 

usage and an appropriate “common practice baseline” (CPB). Such CPBs are specified below with 

respect to different EM&V methods and EE activities.

One benefit of using a CPB is that it inherently adjusts the baseline over time to reflect market 

conditions and naturally occurring improvements in efficiency over time. Establishing a well-defined and 

consistently applied CPB avoids crediting activity. 
*** Draft for Public Input *** 

12

In the context of EE programs, the term gross savings refers to savings calculated with respect to a 

defined baseline, while net savings is due to the difference between energy consumption with the 

program in place and that which would have occurred absent the program. 19 The CPB as defined in 

Section 2.2.2 is consistent with baseline definitions used for gross savings by many existing EE programs. 

Thus, for much of the EE activity within existing programs, the “gross savings” that would be determined 

using current methods and practices for those programs will be consistent with the savings relative to 

the CPB as defined here, and can be reported as MWh savings for purposes of the CPP.

2.2.2. Applicable Guidance

• When a well-designed comparison group method is used, use the control group (with randomized 

control trials) or the comparison group of non-participants (with quasi-experimental approaches) to 

quantify the CPB electricity consumption. 

- In these cases, separately determining the CPB efficiency of individual pieces of equipment is 

unnecessary.20

- Design the comparison group and analysis approach in a way that represents what the 

participants would have done absent the program or absent the EE intervention. 

- With comparison group specifications, describe how the comparison group was selected and 

what it is intended to represent.

• For the three EM&V methods addressed in Section 2.1, use the following CPB guidance:

- For equipment that is replaced on failure, define the CPB as:

 The federal standard or the market average industry/consumer practice at the time of 

implementation, whichever results in a lower savings value. This approach recognizes the 

dynamic nature of baselines in the context of changing market conditions.

 For states (or EE providers operating in those states) that have product standards that are 

more stringent than the federal standard or market average, and where the state is 

counting the savings increment due to the more stringent product standard as a state 

measure, use the state product standard as the CPB for EE at higher efficiency than the state 

product standard. (See double counting Section 2.7) 

- For early replacement activities, with strong evidence that replacement of functioning 

equipment is due to program influence, a dual baseline is applicable: 

 Use existing conditions for defining the CPB for the remaining useful lifetime21 (RUL) of the 

replaced equipment or system. Use the CPB that would apply to new construction or 

replacement on failure for the remainder of the new equipment EUL.

- For building shell improvements of existing buildings, define the CPB as:

 

19 For discussion and guidance on determination of net and gross savings, see the Uniform Methods Project 

Estimating Net Energy Saving: Methods and Practices. Net savings attempts to account for free ridership, spillover, 

and market effects (see Key Definitions text box).

20 The comparison and control groups, in most cases, intrinsically account for free ridership and participant 

spillover, but do not account for nonparticipant spillover and long-term market effects.

21 Remaining useful life cannot exceed the effective useful life of the replacement measure.
*** Draft for Public Input *** 

13

 The existing condition of the building shell unless renovations are extensive enough to 

trigger new construction code compliance, in which case the following new construction 

guidance applies

- For new construction, the CPB is defined as follows: 

 For commercial buildings, the generally most stringent of:

o the applicable state or local building code in effect as of January 1, 2013, 

o the market industry average practice in the state, or 

o ASHRAE 90.1-2007/2009 IECC. 

“Generally most stringent” means that buildings built to this standard generally use the least 

energy, all else being equal. This baseline recognizes the dynamic nature of baselines in the 

context of changing market conditions.22

 For residential buildings, the generally most stringent of:

o the applicable state or local building code in effect as of January 1, 2013, 

o the market industry average practice in the state, or 

o ECC 2009. 

“Generally most stringent” means that buildings built to this standard generally use the least 

energy, all else being equal. This baseline recognizes the dynamic nature of baselines in the 

context of changing market conditions.

 For states (or EE providers in those states) that are increasing the stringency of their state

building codes, use the updated state code as a baseline if the state has included and is 

already counting those savings separately. (See double counting discussion in Section 2.7)

Table 7.1 of the 2012 SEE Action Impact Guide can be referred to for defining general approaches to 

determining baselines for specific EE activities.

23

The CPB as defined here applies to EE activities in the context of consumer-funded programs, ESCOsupported projects, and privately funded projects outside of consumer-funded programs and ESCOs. 

Where there is the possibility of the same EE activity being counted as part of two or more categories of 

EE activity --consumer-funded program, ESCO activity, or private activity—care must be taken to avoid 

counting the same savings more than once. See Section 2.7 on avoiding double counting. 

The definitions of CPB in terms of standard efficiency equipment for new or replacement-on-failure 

situations, and as dual baseline for early replacement are consistent with common approaches to 

defining gross savings for utility programs. Whether a particular utility’s gross savings determination is 

fully consistent with the guidance in this document depends on details of the standards used as 

 

22 Implementation of the EE project itself should not be a determinant for code or standard applicability. For 

example, if the project is a lighting retrofit and the lighting retrofit itself triggers a code requirement for upgraded 

lighting, the code would not necessarily be an applicable basis for a CPB. In this situation, the code would only be 

applicable as a CPB, if other, substantial, actions to the subject building (e.g., a major remodel) triggered the 

subject code.

23 State and Local Energy Efficiency Action Network. 2012. Energy Efficiency Program Impact Evaluation Guide. 

Prepared by Steven R. Schiller, Schiller Consulting, Inc., www.seeaction.energy.gov. (Or current version.)
*** Draft for Public Input *** 

14

baselines, and other particulars described here such as verification methods, EUL determination, and 

frequency of updates of deemed values or other key parameters.

Use of market average baselines where standards do not exist is not currently common practice for 

consumer-funded programs. This definition is intended to ensure that, in the absence of a clear 

standard, savings reflect movement of efficiency beyond what is already occurring in the market. Where 

standards do not exist, utility program evaluated net savings may under some circumstances be used in 

place of savings calculated relative to a market average baseline. To use utility net savings in this 

context, the state must provide an explanation of how net savings are calculated, and why this 

calculation is expected to be at least as stringent as savings relative to a market average baseline. Other 

aspects of the savings determination should also be consistent with the guidance in this document. For 

guidance on determination of net savings, see the Uniform Methods Project Estimating Net Energy 

Saving: Methods and Practices.

2.3 Reporting Timeframes and Considerations

2.3.1. Discussion

Current industry practices for reporting annual 

electricity savings varies across states and EE 

providers with regard to specific content 

requirements, definitions, and timing. Local 

policy objectives, the breadth of EE activities, 

and other factors typically drive decisions about

such reporting attributes.

The reporting process for consumer-funded EE 

programs typically involves projecting and 

reporting savings as part of the planning phase, 

as well as ongoing annual reporting as savings 

accrue over time. This “ex-post” reporting is 

typically based on savings derived by applying 

one of the EM&V methods described above in 

section 2.1. In almost all cases, ongoing annual savings values are reported on an incremental and 

cumulative basis (see text-box terms). 

The regulatory requirements for EE reporting, as defined in the EPA’s emissions guidelines, are intended 

to support greater consistency across jurisdictions and EE providers in how savings data are quantified 

and collected. In addition, the requirement to report both incremental and cumulative savings, and the 

associated timing provisions, are consistent with the Energy Information Agency’s (EIA) approach to 

collecting EE program data via Form 86124.

 

24 See: http://www.eia.gov/electricity/data/eia861/

Key Terms

 Reporting-year incremental savings: the 

electricity savings quantified and verified as a 

result of EE activities operating for the first time 

in the reporting year; reported in annual 

megawatt hours (MWh). 

 Reporting-year cumulative savings: the 

electricity savings quantified and verified as a 

result of EE activities in the reporting year from 

both (a) EE activities operating for the first time in 

the reporting year and (b) EE activities initiated in 

prior years and still in effect; reported in 

megawatt hours (MWh).
*** Draft for Public Input *** 

15

2.3.2. Applicable Guidance

• When using stipulated effective useful life (EUL) values (see Section 2.8 on Effective Useful Life and 

Persistence of Savings) for reporting savings, report savings pro rata based on the day the EE activity 

began saving energy during the reporting year.

- For emission standard plans in which EE generates ERCs, annual savings can be quantified for 

any consecutive 12-month period.

- For state measures plans, report savings as if they started accruing on January 1 of the reporting 

year and continued in the program for a full year (irrespective of which day the EE activity began 

saving energy)

25

.

• Report current year incremental and cumulative savings values on the basis of the best available 

information at the time of reporting. Incorporate new information gained from routine and ongoing 

EM&V activities on a going-forward basis. 

- The text box that illustrates how forward adjustments can be applied.

2.4 Deemed Savings 

2.4.1. Discussion

As described in Section 2.1 above, one of the three categories of EM&V methods for quantifying savings 

is the application of deemed savings. Deemed values are appropriately applied only to relatively simple, 

well-defined efficiency measures such as light bulbs or specific pieces of equipment for which the 

performance characteristics and location-specific conditions are well known. In these instances, a 

deemed savings approach can provide reasonable reliable and accurate savings values, on average. 

Because these stipulated values are agreed upon in advance, deemed savings can help alleviate some of 

the guesswork in program planning and design. Deemed savings can also result in a form of risk, in 

 

25 EE activities generate a stream of savings over a pre-determined number of years, or EUL. Regardless of the 

specific day that the EE activity was installed and began savings energy, it is assumed that savings begin on January 

1 and that this counts as the first full year of the project or measure EUL. 

Example of Forward Adjustments to EE Savings 

If a program is determined to save 10,000 MWh per year for 10 years starting in Year X, 10,000 MWh may be used as 

the amount of incremental savings in Year X and 10,000 MWh may be used for reporting cumulative savings in Years 

X + 1 through X + 9. If during Year X + 3 a better annual savings value for that program is determined to be 9,500 

MWh, 9,500 MWh should be used for reporting cumulative savings starting in Years X + 3 through X + 9. Examples of 

significant new information that could cause an update in savings values include:

 Savings are adjusted because of verification activities; for example, savings might be zeroed for EE actions in 

facilities that have been shut down or savings are reduced if high level of savings degradation/performance is 

determined. 

 Savings are adjusted because of new cycles of savings determination (see Section 2.9 on verification and 

evaluation cycles); for example, savings are updated when an applicable deemed savings value is 

modified/updated in an approved database.

 Savings values are updated when errors are found in prior-year savings calculations.
*** Draft for Public Input *** 

16

which overestimates or underestimates of savings 

can occur when EE projects or measures do not 

perform as expected, or if deemed values are applied 

in the wrong circumstances. The verification 

activities commonly required by state PUCs and 

other oversight and management bodies can 

alleviate this risk26.

For more complex efficiency projects or for projects 

with significant savings variability, measurementbased methods (i.e., PB-MV and comparison group 

methods) are more appropriate than deemed 

savings. However, deemed values can in some cases 

be properly applied to these projects if one or more 

key parameters is directly monitored over time at 

the project site. For example, in a high-efficiency 

motor program, actual operating hours could be 

monitored over a full work cycle27. 

Deemed savings values are usually documented in 

resources such as a document or database in formats that can vary from a spreadsheet to an online 

searchable database. The term of art for such resources is technical reference manuals (TRMs)28. As of 

this document’s publication, approximately 20 TRMs are in use across the United States at the state and 

regional level.29 TRMs can be valuable, but methodologies for estimating savings and the actual values

vary widely. Some TRMs include information based on prior-year evaluations including, in some cases, 

rigorous metering, and analysis. Many others have values based on computer simulations or engineering 

algorithms). Ongoing and new state, regional, and federal efforts to improve the quality and 

documentation of TRMs are encouraged and can support higher-quality savings values for compliance 

with the EPA’s emissions guidelines and reduced EM&V costs.

2.4.2. Applicable Guidance

• Apply deemed savings to relatively simple EE projects and measures (e.g., light bulbs or specific 

pieces of equipment) for which the performance characteristics and location-specific conditions 

have been evaluated and are well known.

- Do not apply them to complex EE projects or measures with significant savings variability

 

26 The emission guidelines include regulatory requirements for verification, as described in section 2.9 of this 

document.

27 This approach is consistent with the definition of IPMVP Option A. However using deemed savings alone is not 

considered a measurement and verification method, per se.

28 TRMs generally include information about the technology or measure itself, the savings value, measure life, peak 

load impacts, engineering algorithms to calculate savings, source documentation, specific assumptions, and other 

relevant material to support the calculation of savings in particular applications. 

29 Many of these TRMs are listed in the following document: Scoping Study to Evaluate Feasibility of National 

Databases for EM&V Documents and Measure Savings. SEE Action Network. Prepared by Jayaweera, T.; Haeri, H.; 

Lee, A.; Bergen, S.; Kan, C.; Velonis, A.; Gurin, C.; Visser, M.; Grant, A.; Buckman, A.; The Cadmus Group Inc. 

www.eere.energy. gov/seeaction/pdfs/emvscoping__databasefeasibility.pdf. June 2011.

Key Terms

 Deemed savings values: estimates of 

average annual electricity savings for a single 

unit of an installed EE measure that (a) has 

been developed from data sources and 

analytical methods widely considered 

acceptable for the measure and (b) is 

applicable to the situation and conditions in 

which the measure is implemented. 

Individual parameters or calculation methods 

also can be deemed, including EUL values. 

Deemed savings values are applicable for 

specific EE measures. A single deemed 

savings value may not be used for a program 

as a whole, nor for a multi-measure project, 

because of the degree of variation in how 

systems are used in different building types

or market segments. Deemed savings are 

also called stipulated savings.
*** Draft for Public Input *** 

17

• Each deemed savings value must indicate the conditions for which the value is applicable (e.g., 

climate, building type, end use, and measure implementation mechanism). 

• Ensure that deemed savings values:

- Are based on EE measure definition, applicability conditions, assumptions, calculations, and 

references that are well documented in work papers that are publicly available;

- Are quantified as the most likely averages of electricity savings and other factors that determine 

such values over the lifetime of the EE measure, such as average occupancy, typical weather, 

typical operating hours and EUL; 

- Are developed by independent, third parties and, whenever possible, are based on empirical 

techniques such as RCTs and quasi-experimental design. 

• Apply deemed savings values only for the specific EE measures, program or project delivery 

mechanism (e.g., direct install versus point-of-sale rebates), end-uses (e.g., single-family versus 

multifamily residential), operating conditions (e.g., climate, operating hours), and other assumptions 

for which the values were developed.

• Update deemed savings values on a going-forward basis; see section 2.3 on Reporting Incremental 

and Cumulative Savings.

2.5 Independent Factors Affecting Energy Consumption and Savings

2.5.1. Discussion

Observed changes in electricity consumption are 

the result of a variety of independent factors 

and influences. These range from the outdoor 

temperature to occupancy levels in a building to 

production levels. To isolate the electricity 

savings that result from the EE activity in 

question, each of these independent factors 

must be taken into account.

Determining the influence of these factors is critical to the credibility of savings estimates, and 

distinguishes properly determined savings from a simple and unreliable comparison of electricity use

before and after implementation of a program, project, or measure. Each of the three EM&V methods 

described in Section 2.1 has a mechanism for accounting for independent factors. For deemed savings 

values, independent factors are implicitly quantified through the associated applicability conditions (see 

Section 2.4); for PB-MV, these factors are considered via the use of regression analyses, computer 

simulation modeling, or engineering calculation adjustments; and for comparison group methods, 

through random assignment, matched comparison groups, or through large-scale consumption data 

regression analyses. 

2.5.2. Applicable Guidance

• Within a single EE program, quantify savings for the constituent EE projects or measures using 

consistent assumptions for independent factors. 

• Quantify EE savings using values of independent factors that are expected to apply over the life of 

the EE measure, as follows:

Key Term 

 Independent factors: the variables (e.g., weather, 

occupancy, production levels) that affect 

electricity consumption and savings, and vary 

independently of the EE measure under study.
*** Draft for Public Input *** 

18

- Actual, normalized conditions that exist over the period when EE savings occur, if these 

conditions are measured throughout the measure life, for example as part of ongoing PB-MV.

 With this approach, adjust baseline electricity-consumption data to reflect actual 

independent factors observed after the measure is in place.

 Examples of adjusted independent factors are:

o Observed weather conditions for a residential heating efficiency project,

o Observed occupancy rates for a commercial building lighting efficiency project, or

o Observed product production rates for an industrial efficiency project.

- Normalized or standardized (typical) conditions that can be reasonably expected to occur 

throughout the EUL.

 With this approach, both baseline and performance period data on electricity consumption 

must be normalized to data on the independent factors, where reasonable and appropriate. 

Examples of normalized independent factors are:

o Typical weather conditions for a residential heating efficiency project,

o Typical occupancy rates for a commercial building lighting efficiency project, or

o Typical product production rates for an industrial efficiency project.

• Where first-year savings values – derived by applying first-year independent factors – are used to 

represent annual savings for the EUL of the project or measure, provide a justification for why this is 

a reasonable assumption (i.e., justify why first-year independent factors can be shown to represent 

standard/typical conditions over the life of the measure).

2.6 Accuracy and Reliability of 

Quantified Savings

2.6.1. Discussion

It is a best practice in the EE industry for 

EM&V plans to include information on how

the accuracy and reliability of EE savings will 

be determined based on the selected EM&V 

methods. The level of accuracy and reliability 

of quantified and verified MWh savings 

values is determined by the rigor of the 

EM&V methods applied, where rigor is 

typically quantified using statistical 

indicators such as confidence intervals and 

or the relative precision at a given 

confidence level (for annual MWh savings, or 

for a representative sample of an EE 

program population). The accuracy and 

reliability of quantified savings reflects the 

magnitude of the following two types of 

Key Terms

 Accuracy: A concept that refers to how close and 

estimate or measured value is likely to be to the true 

value. The term can also be used in reference to a 

model or a set of measured data, or to describe a 

measuring instrument's capability. 

 Reliability: The quality of a measurement process that 

would produce similar results on (1) repeated 

observations of the same condition or event, or (2) 

multiple observations of the same condition or event 

by different observers. Reliability refers to the 

likelihood that the observations can be replicated. 

 Rigor: the level of effort expended to minimize 

uncertainty in savings estimates such as sampling 

error and bias. The higher the level of rigor, the more 

confident one is that the results of the EM&V 

activities are both accurate and precise. Rigor may be 

quantified or described with metrics for reliability and 

certainty, such as statistical confidence and precision.
*** Draft for Public Input *** 

19

error: 

• Systematic error: inaccuracies in the same direction, causing savings values to be consistently either 

overstated or understated. Systematic errors (also referred to as bias) may result from incorrect 

assumptions, a methodological issue, or a flawed reporting system.

 Random error: error occurring by “chance” that may cause the savings estimates to be 

inconsistently overstated or understated. Random errors include an observed change in energy use 

due to unaccounted-for factors that affect energy use. 

The magnitude of random error can be quantified based on the variations observed across different 

units. By contrast, systematic error or bias is not quantifiable based on the observations. For this reason, 

it is important to report the quantifiable random error, and to describe the steps that have been taken 

to minimize the potential for systematic error, and provide a subjective assessment of the potential 

effects of such error. 

2.6.2. Applicable Guidance

• Assumptions required for savings quantification should be designed neither to provide optimistic 

savings estimates (aiming to err on the high side) nor to provide conservative estimates (aiming to 

err on the low side).

• If sampling is used for quantifying savings values, ensure that actual observed confidence/precision 

values are applied (versus ex-ante estimates of confidence/precision). If sampling is used to quantify 

savings, report the statistical precision of the associated estimates. Examples of use of sampling for 

savings quantification include:

- PB-MV of the program savings, based on PB-MB for a sample of projects and installed measures.

- A program-level estimate of savings or of key parameters used to calculated savings (e.g. 

lighting operating hours) derived from a random sample of units.

- For savings determined by comparison group methods, the statistical confidence intervals or 

confidence/relative precision levels of the program effect measured by the comparison group 

analysis should be reported. Applicable guidance documents include: 

 SEE Action Guide on evaluating behavior programs,30

 Uniform Methods Project Sample Design Cross-Cutting Protocol (Section 11)31, and 

 Uniform Methods Project Whole-Building Retrofit Evaluation Protocol (Section 8)32

• Apply and cite applicable industry-standard protocols and guidance documents for sampling. Best 

practices for statistical sampling are described in:

- ISO New England Manual for Measurement and Verification of Demand Reduction Value from 

Demand Resources.

33

 

30 State and Local Energy Efficiency Action Network. (May2012). Evaluation, Measurement, and Verification 

(EM&V) of Residential Behavior-Based Energy Efficiency Programs: Issues and Recommendations. Prepared by 

Todd, A.; Stuart, E.; Schiller, S.; Goldman, C.; Lawrence Berkeley National Laboratory. www1.eere energy.gov/see

action/pdfs/emv_behaviorbased_eeprograms.pdf 

31 See: http://www.energy.gov/sites/prod/files/2013/11/f5/53827-11.pdf

32 See: http://www.energy.gov/sites/prod/files/2013/11/f5/53827-11.pdf
*** Draft for Public Input *** 

20

- The California Evaluation Protocols. 

- Uniform Methods Project Sample Design Cross-Cutting Protocol (Chapter 11).

• For deemed savings: 

- Quantify random errors if applicable

- Include the statistical precision (margin of error) of any EM&V parameters determined using 

sampling

• For all EM&V methods, discuss potential risks and biases (and associated quality-control measures) 

in EM&V plans and monitoring and verification reports.

• For states trading ERCs across borders, coordinate in an effort to apply the same or consistent 

EM&V approaches to ensure the savings values are determined with comparable levels of accuracy 

and reliability. 

2.7 Avoiding Double Counting

2.7.1. Discussion

Double counting occurs when the MWh savings from a single EE program, project, or measure are 

counted more than once under the same regulation or program. This type of error must be prevented to 

maintain programmatic integrity and credibility, and to ensure that EE results in real and permanent 

reductions in CO2 emissions. Tracking, accounting, and quality checks are steps that are routinely 

undertaken in states and regions across the country to avoid double counting. The purpose of these 

steps is to avoid the following circumstances:

• Savings from a single EE program or project being claimed by more than one EGU or state. For 

example:

- Two EGUs claiming the savings from the same lighting retrofit program, or an EGU claiming the 

same savings that a state is claiming.

• Two or more EE programs or projects operating at the same time claiming savings from the same 

MWh savings. For example:

- Some or all savings from the same retrofit being claimed by a residential behavior-based 

program and a retailer point-of-sale incentive program.

34

Savings from a single retrofit project being claimed by a utility incentive program and the ESCO 

that implemented the retrofit.

• Two or more programs operating during different years claiming savings from the same projects or 

measures, for example:

- A 2020 program incenting an LED lamp operating for 10 years, with the lamp failing after 2 years 

and being replaced by a new LED lamp that receives an incentive from another program.

 

33 Current version is manual M-MVDR, revision 6, dated June 1, 2014

34 This potential for double counting is particularly important in the context of randomized encouragement 

programs, where part of the savings seen in treatment/control differences is due to increased participation in 

general offering programs.
*** Draft for Public Input *** 

21

• Inconsistent baselines across a portfolio of programs, for example:

- A state claiming (1) in one program savings from enacting a C&S with 100-percent compliance 

that results in savings above a prior C&S or common practice, and (2) in another program 

claiming savings with a baseline defined below the new C&S (e.g., a baseline defined by a prior 

C&S) for the same types of EE projects or measures.

- A state claiming credit for federal actions such as building code determinations or appliance 

standards

2.7.2. Applicable Guidance

• Implement systematic tracking and accounting procedures, including the use of well-structured and 

well-maintained tracking and reporting systems such as those already being used by many states 

and EE providers.

• Implement the following procedures to avoid or correct for double counting:

- For programs and projects with identified consumers, track EE actions (type and number of 

measures implemented) at the utility-customer level using customer name, address, account 

number, and date of actions for each program. 

- For programs without identified consumers, such as point-of-sale rebates and retailer or 

manufacturer incentive programs, track applicable vendor, retailer, and manufacturer data.

Include the appropriate specifications and quantities of program-incented units sold or shipped, 

with as much granularity as possible.

- Use the consumer-level data to identify and correct for duplicate EE activity records across 

programs with “trackable” consumers and across non-program projects such as private-sector 

transactions for projects sponsored by an ESCO.

- Identify and correct for duplicate EE activity records across programs and non-program projects 

such as private-sector transactions for projects sponsored by an ESCO.

- Identify instances where tracked consumer activity is likely to be double counted with upstream 

activity, and subtract the estimated overlap from one or the other’s savings claims.

• For programs with identified consumers but without identified EE actions (e.g., an information or 

behavioral program) that apply comparison-group EM&V, use the comparison group’s tracked 

activity to determine the baseline activity in the other programs; the balance of the participant 

group’s tracked activity is incremental other-program activity.

- The savings for this incremental activity is reflected both in the total tracked savings for the 

other programs and in the comparison-group-based savings for the informational program, and 

should be subtracted from one or the other total.

- Use the SEE Action Guide or the UMP protocol for evaluating behavior programs for further 

guidance on applying this method35.

 

35 See: https://www4.eere.energy.gov/seeaction/publication/evaluation-measurement-and-verification-emvresidential-behavior-based-energy-efficiency
*** Draft for Public Input *** 

22

2.8 Effective Useful Life and Persistence of Savings

2.8.1. Discussion

While the full cost of an EE project or 

measure is typically borne at the time of 

purchase and installation, the resulting MWh 

savings accrue for the full duration of time for 

which the EE is in place. The typical practice 

of state PUCs (for consumer-funded EE 

programs) and ESCOs is to apply one or more 

EM&V methods to measure and report EE

savings during the first year, and then to 

assume a constant (or in some cases, 

systematically declining) level of savings in 

each year for the full lifetime of the project or measure (or, alternatively, for a specified time horizon 

such as 10 years). This period of time is referred to as the effective useful life (EUL).36

EUL is a function of the expected life of the equipment and the number of years that the measure 

actually persists, as determined using field measurements of on-the-ground conditions. The methods for 

determining EUL of a given measure vary somewhat across the country and by EE provider based on 

observable conditions (such as weather and climate), input assumptions (such as rates of measure 

failure), and other factors.

37 For commonly implemented measure types, it is typical for state, regional, 

or national entities to collaborate on mutually beneficial research to refine and improve EUL 

measurements, especially in light of ongoing industry trends and technology evolution over time.

2.8.2. Applicable Guidance

 Use Section 2.9 (Savings Quantification and Verification Cycles) of this document to inform first-year 

verification activities undertaken to determine whether measures were properly installed, 

functioning, and capable of generating savings. 

• Determine deemed EUL values using either or both:

- Documented best practices that are determined by independent entities and publically 

documented per the requirements indicated below in the subsection on Deemed Savings. 

- Persistence studies conducted by independent entities at least once every 5 years to determine 

values. 

 If deemed EUL values are used: 

 

36 See: Energy Savings Lifetimes and Persistence: Practices, Issues and Data, Ian M. Hoffman, Steven R. Schiller, 

Annika Todd, Megan A. Billingsley, Charles A. Goldman, Lisa C. Schwartz, Lawrence Berkeley National Laboratory, 

February 2015.

37 For example, technical measure life or equipment life usually is defined as the median number of years that a 

measure is installed or initiated and is operational. Less commonly, it is defined as the mean number of years to 

failure. Median value means the time at which half of the measures are removed from service or are otherwise no 

longer operating as assumed, and half remain operating as assumed. 

Key Term 

 Effective useful life (EUL): an estimate of the 

duration of savings from individual EE measures, 

reported in years. Values are typically specific to 

individual EE measures or projects but also may be 

specified by program. EUL is defined through various 

means, including median number of years that the 

measures/projects installed under a program are still 

in place and operable.
*** Draft for Public Input *** 

23

- Report incremental and cumulative savings with the assumption that savings revert to zero at 

the end of the applied EUL (after a period of time equal to the EUL has elapsed). This implies 

that project or program participants do not continue the EE practice beyond “measure life,” and 

that if a new measure is implemented at the end of the prior measure’s EUL, a reassessment of 

the appropriate CPB is needed. 

- Consider using ongoing field verifications to determine the actual (versus deemed) EUL values 

for measure lifetime and persistence of savings. If ongoing field verification is used, EE savings 

can be counted for as long as verification indicates that the project or measure persists.

- Apply persistence and/or degradation studies to establish and adjust deemed values (i.e., in lieu 

of conducting regular interval inspections to determine if measures are functioning and 

generating savings).

• If project or program persistence studies are conducted to determine the duration of savings, then 

savings can be counted as long as the verification activities indicate continued measure operation 

and performance.

- Such studies should be conducted at least every five years

• Participate in collaborative and joint research to improve the breath and quality of EUL values

(several such research activities are ongoing in states around the country). 

2.9 Savings Quantification and Verification Cycles

2.9.1. Discussion

Determining MWh savings from an EE 

activity is typically a two-step process: (1) 

verifying that a measure or project has been 

installed and (2) quantifying savings. 

To illustrate the difference between the two

activities, consider a project involving 

replacement of 100-watt incandescent 

lamps with 13-watt LED lamps.

Verification involves confirming that the 

replaced lamps are 100 watts, that the new 

ones are 13 watts, and that the lamps are installed and working. Verification confirms that the measure 

has the potential to save electricity, with the savings depending on how many hours the lamps operate. 

The number of hours the lamps operate might be determined by using a (1) deemed savings value for 

13-watt lamps that replace 100-watt lamps or (2) verified based on metering at a sample of projects, 

using the IPMVP Option A or B.

38

 

38 See: http://www.evo-world.org/index.php?option=com_content&view=article&id=272&Itemid=379&lang=en

Key Term 

 Verification (project or measure): an assessment by an 

independent entity to ensure that the EE measures 

have been installed correctly and could generate the 

predicted savings. Verification may include assessing 

baseline conditions and confirming that the EE 

measures are operating according to their design 

intent. Site inspections, phone and mail surveys, and 

desk review of program documentation are typical 

verification activities. 
*** Draft for Public Input *** 

24

2.9.2. Applicable Guidance

• Verify a sample of projects to represent the full program population in cases where many projects 

are implemented in a program (in cases where verifying every project is not feasible or practical).

Determine sample sizes as defined in Section 2.6 on Accuracy and Reliability of Quantified Savings.

• Use verification findings to adjust annual electricity savings on a going forward basis.

• Apply the following verification strategies for these common EE activities:

- For EE retrofits, verification can include confirming (1) installation rates of the indicated EE 

measures, (2) that these installations are above and beyond CPB and meet reasonable quality 

standards, and (3) that the measures are operating correctly per design intent and can generate 

the predicted savings. 

- For EE new construction projects, verification can include reviewing and confirming 

commissioning documentation.

- For EE point-of-sale rebate or distributor incentive programs, verification can include 

confirming the sales data used for determining electricity savings and verification with a sample 

of end users. 

• Use EM&V and the derived savings realization rates to adjust claimed annual electricity savings.

- If savings quantification is conducted separately from savings verification (e.g., deemed savings 

and PB-MV methods), the savings quantification may determine savings per verified unit. This 

value can then be applied to the verified units.

- When comparison-group methods are used, the analysis may be considered to provide a 

combination of savings quantification and verification. That is, the analysis yields both what was 

actually installed and operating, as well as the operational practices that affect savings. Separate 

verification activities are therefore not necessary.

 To continue to count savings after the first year with comparison group methods, establish 

an EUL as described in Section 2.8.2 or continue the comparison group analysis in each year 

for which savings continue to be counted.

 If the comparison group analysis is continued in successive years, include a discussion of the 

basis on which the comparison group remains appropriate and valid. 

2.10 Transmission and Distribution (T&D) Savings Adders

2.10.1. Discussion

The difference between the electricity generated (busbar value) and consumed (meter value) is due to

losses in the transmission and distribution (T&D) system. U.S. Energy Information Agency (EIA) data

indicates that national, annual T&D electricity losses average about 6 percent of the electricity that is 

transmitted in the U.S.39 Every unit of electricity consumption avoided at an end-use site also avoids

losses that would have occurred as that electricity was delivered through the T&D system. Requirements 

and guidance on how T&D savings can be added to end-use electricty savings values follow.

 

39 The national average loss from 1990 to 2012 is six percent. See: 

http://www.eia.gov/tools/faqs/faq.cfm?id=105&t=3
*** Draft for Public Input *** 

25

2.10.2. Applicable Guidance

 Adjust MWh savings results from EE programs, projects, and measures by using a T&D line-loss 

adjustment factor (adder) based on the lesser of 6 percent of the site-level savings or the calculated 

statewide annual average T&D loss rate total electric supply minus direct electricity use divided by 

direct electricity use)40 expressed as a percentage and based on values in the most recent year and 

published in the U.S. EIA State Electricity Profile.

 For Voltage/VAR optimization and conservation voltage regulation (CVR) - that lower both line 

losses and facility-level MWh consumption – identify and document the procedures that will be 

used to quantify the portion of overall savings that occur on the customer-side of the utility. 

2.11 Interactive Effects

2.11.1. Discussion

EE measures often have indirect impacts on 

electricity and fossil-fuel use in systems not 

directly affected by the subject measures. 

For example: 

 Installing efficient lighting in a building’s 

cooled and heated space can decrease 

the electricity use of cooling systems 

and/or increase natural gas 

consumption in heating systems.

This section provides guidance on how 

indirect electricity impacts, called 

interactive effects, should be addressed.

2.11.2. Applicable Guidance

• Address quantification of interactive effects of electricity consumption in EM&V plans and 

referenced in monitoring and verification reports.

• Use the U.S. DOE’s Uniform Methods Project (UMP)41 or other applicable protocols and methods to 

estimate interactive electricity effects.

• It is not necessary to quantify the interactive effects of end-use fossil fuel use (i.e., non-electricity 

fuels such as natural gas) for the purpose of the EPA’s emissions guidelines for affected electric 

utility generating units.

- However, it should be noted that that these cross-fuel effects have implications for overall 

greenhouse gas (GHG) emissions. Evaluating such effects is a best practice in many states. 

 

40 Estimated losses in MWh, total electric supply, and direct electricity use values are available in the U.S. EIA’s 

State Electricity Profiles. See table on Supply and Disposition of Electricity (currently Table 10). Direct electricity 

use refers to the electricity generated at facilities that is not put onto the electricity grid, and therefore does not 

contribute to T&D losses.

41 See chapter 2: http://energy.gov/sites/prod/files/2013/07/f2/53827_complete.pdf (Version as of August 2015)

Key Term

 Interactive effects: increases or decreases in the use of 

electricity or fossil fuels that occur outside of the end 

uses targeted by a specific EE measure, project, or 

program. For example, reduction in lighting loads 

through an energy-efficient lighting retrofit can reduce 

buildings’ air conditioning and increase heating 

requirements because less heat is generated by 

energy-efficient lighting systems compared with less 

efficient lighting systems. 
*** Draft for Public Input *** 

26

2.12 Use of EE EM&V Protocols and Guidelines

2.12.1. Discussion

A key aspect of industry best-practices with EE savings quantification is the use of one or more EM&V 

protocols and guidelines. Several such documents define, provide instructions for use, and generally 

govern the application of the three EM&V methods outlined in Section 2.1 above. Examples of these 

protocols and guidelines are provided in Table 2-2. EPA supports the use of these resources in state 

plans, and encourages their further development for demand-side EE savings as they relate to the 

requirements of the CPP.

As noted in Section 1 above, the development of these national, regional, and state-by-state protocols 

and guidelines is primarily an outgrowth of the utility-administered EE programs, as well as public- and 

private-sector ESCO projects, in place in most states throughout the country.

Table 2-2: Examples of Industry-Standard EE EM&V Protocols and Guidelines42

Protocol/Guideline

Sponsor

Website Summary

Uniform Methods Project (UMP) 

U.S. Department of Energy (DOE)

http://www.energy.gov/eere/aboutus/ump-protocolsProvides protocols for PB-MV for 

many common EE measures and 

technologies based on accepted 

methods for a core set of widely 

deployed EE measures (version as of 

August 2015). 

Energy Efficiency Program Impact 

Evaluation Guide

SEE Action - U.S.DOE and U.S. 

Environmental Protection Agency 

(EPA)

http://www.epa.gov/eeactionplan Describes common terminology, 

structures, and approaches used for 

determining energy savings and 

avoided emissions and other nonenergy benefits resulting from 

facility (non-transportation) EE 

programs. It provides context, 

planning guidance, and discussion of 

issues that determine the most 

appropriate evaluation objectives 

and best practices approaches for 

different efficiency portfolios.

Roadmap for Incorporating Energy 

Efficiency/Renewable Energy Policies 

and Programs into State and Tribal 

Implementation Plans 

U.S. EPA

http://www.epa.gov/airquality/eere

/pdfs/EEREmanual.pdf

Provides guidance for incorporating 

EE and renewable energy policies 

and programs into State and tribal 

implementation plans.

 

42 Table 2-2 lists of some of the protocols and guidelines that can be considered “established” and which are 

publically available and have been promulgated and/or adopted by a State, regional, national, or international 

organization. Stakeholders may request that EPA to recognize additional protocols and guidelines as they emerge 

over time. 
*** Draft for Public Input *** 

27

Protocol/Guideline

Sponsor

Website Summary

NEEP Regional-Common EM&V 

Methods and Savings Assumptions 

Guidelines 

Northeast Energy Efficiency 

Partnership

http://www.neep.org/regional-emvmethods-and-savings-assumptionsguidelines-2010Provides methods for determining 

gross energy and demand savings 

and savings assumptions for a 

priority set of EE program/project 

types or measures.

California Energy Efficiency 

Evaluation Protocols: Technical, 

Methodological, and Reporting 

Requirements for Evaluation 

Professionals

California Public Utility Commission

http://www.calmac.org/publications

/EvaluatorsProtocols%5FFinal%5FAd

optedviaRuling%5F06%2D19%2D200

6%2Epdf

Guides the efforts associated with 

evaluating California’s EE programs 

and program portfolios.

California Evaluation Framework 

(2004)

California Public Utility Commission

http://www.calmac.org/publications

/California%5FEvaluation%5FFrame

work%5FJune%5F2004%2Epdf

Provides a consistent, systematized, 

cyclic approach for planning and 

conducting evaluations of 

California’s EE programs.

International Performance 

Measurement and Verification 

Protocol (IPMVP) 

Efficiency Evaluation Organization

http://www.evo-world.org Provides an overview of current best 

practices for determining savings 

from EE projects and measures; 

provides a framework and 

definitions that can help 

practitioners develop PB-MV plans 

for their projects.

FEMP PB-MV Guidelines 

U.S. DOE Federal Energy 

Management Program

http://www.mnv.lbl.gov/keyMnVDo

cs

Provides guidelines and methods for 

documenting and verifying the 

savings associated with federal 

agency performance contracts; 

contains procedures and guidelines 

for quantifying the savings resulting 

from energy efficiency.

ASHRAE Guideline 14, Measurement 

of Energy and Demand Savings

American Society of Heating, 

Refrigerating, and Air-Conditioning 

Engineers 

http://www.ashrae.org ASHRAE is the professional 

engineering society that has been 

most involved in writing guidelines 

and standards associated with EE; 

compared with the FEMP PB-MV

Guidelines and the IPMVP, Guideline 

14 is technically more detailed and 

addresses the analyses, statistics, 

and physical measurement of energy 

use for determining energy savings. 

Regional Technical Forum (RTF) 

Northwest Power and Conservation 

Council

http://www.rtf.nwcouncil.org An advisory committee established 

to develop standards to verify and 

evaluate the savings from a wide 

range of EE and conservation 

measures; maintains an extensive 

and well documented database of 

deemed savings values.
*** Draft for Public Input *** 

28

Protocol/Guideline

Sponsor

Website Summary

ISO-NE Measurement and 

Verification of Demand Reduction 

Value from Demand Resources –

Manual M-MVDR

Independent System Operator – New 

England 

http://www.isone.com/participate/rulesprocedures/manualsProvides guidance and required 

criteria for measuring and verifying 

performance of demand resources 

participating in the wholesale 

electric markets administered by 

ISO.

PJM Manual 18B: Energy Efficiency 

Measurement & Verification 

PJM Interconnection

https://www.google.com/url?sa=t&r

ct=j&q=&esrc=s&source=web&cd=1

&ved=0CB8QFjAA&url=https%3A%2

F%2Fwww.pjm.com%2F~%2Fmedia

%2Fdocuments%2Fmanuals%2Fm18

b.ashx&ei=m9xHVceiEMvJtQXviYDo

Dw&usg=AFQjCNEQb0Z65Y_2ESjjdA

P10sPjZb94Mw&sig2=Ydqecugs2PPn

uJTwxmtPIw&bvm=bv.92291466,d.b

2w

Provides guidance on measuring and 

verifying the demand reduction 

value of EE resources.

EE EM&V activities related to EPA’s emissions guidelines can benefit from applying established 

guidelines and protocols. It should be noted, that while EPA encourages the use of well-established 

EM&V guidelines and protocols, the agency recognizes that these resources do not provide a step-bystep “recipe” for quantifying savings. This is largely because:

• Approaches vary from state to state due to a variety of factors. These factors include the program, 

project, or measure being evaluated, whether savings values have been established in the past for 

the subject EE activity, and the overall magnitude of program impacts. 

• Guidelines and protocols per se provide flexibility with respect to key EM&V issues, such as selection 

of methodologies and key parameters, the timeframe addressed by EM&V (short-term, first-year, or 

lifetime data collection and analyses of savings), and the desired accuracy of savings. 

In this way, EPA recognizes that the application of EM&V guidelines and protocols requires professional 

judgment and assessment of the EE activities to determine the appropriate EM&V method, 

assumptions, other factors to apply, and applicability within the context of EPA emissions guidelines, 

calculations and other elements.

2.12.2. Applicable Guidance

• If EM&V plans and monitoring and verification specify the use of protocols or guidelines, provide a 

list of applicable minimum requirements and description of applicable sections, methods, and 

portions of the protocol or guideline.43

 

43 For example, simply referencing the IMPVP is not sufficient since it allows the use of four different options with 

flexibility with regards to a number of savings calculation assumptions
*** Draft for Public Input *** 

29

3. Supplemental Guidance for Specific Categories of EE 

Section 3 provides EM&V guidance that is specific to several common categories of demand-side EE 

programs, projects, and measures. The EPA is providing guidance on these particular EE activities 

because they are commonly implemented (at scale) in all regions of the country, represent the 

significant majority of all EE savings currently being achieved, and because such guidance was requested 

by stakeholders. Each of these EE activities can also be characterized as having some form of state

agency oversight or dedicated EM&V protocols and procedures.

The guidance in this section is intended to supplement Section 2, which applies to all demand-side EE 

savings (MWh). The best-practice approaches and technical assumptions provided below are not 

intended to provide a “recipe” for how EM&V for should be implemented. Rather, this guidance is 

intended to inform decisions regarding certain EM&V parameters that are fundamental to the programs 

described. EE providers can apply the approaches and assumptions in Section 3 as they prepare EM&V 

plans for the specific program and project categories addressed.44 As above, this section leverages and is 

consistent with prevailing industry best practices and assumptions currently being applied by state PUCs 

and other oversight and sponsoring entities. It applies only to rate-based state plans that allow the use 

of EE to generate ERCs or adjust an emission rate to comply with the emission guidelines.

The specific categories of demand-side EE covered in this section include:

• Utility and publicly administered EE programs

• Project-based EE (evaluated site-by-site) 

• State and local government building energy code and compliance programs

• State and local government incremental product energy standards

By providing this additional guidance on these categories, the EPA is in not intending to limit the EE 

activities that states may implement. Rather, the EPA is proposing that any demand-side EE program, 

project, or measure that results in MWh savings may be potentially eligible under the proposed model 

trading rule, provided that it meets the presumptively approvable provisions for eligibility described in 

section IV.C.3 of the model trading rule preamble, and that supporting EM&V is rigorous, transparent, 

credible, complete and fulfills the requirements provided in the emission guidelines and the state plan.

3.1 Demand-Side EE Programs

3.1.1. Program Description

Demand-side EE programs refer to a wide range of activities to support the efficient usage of electricity.

These activities may be funded from different sources through different mechanisms and be 

 

44 Should conflicts arise between the guidance in this section and the guidance in Section 2, this guidance has 

precedence (since it is tailored to the specific programs and projects listed here). When preparing EM&V plans and 

monitoring and verification reports, the applicable industry protocols and guidelines listed in this document should 

be referenced. 
*** Draft for Public Input *** 

30

administered by various entities, including investor-owned utilities (IOU), public utilities, state energy 

offices (SEO), and non-profit entities sanctioned by state legislators and public utility commissions. 

Examples of demand-side EE programs range from marketing, education, and outreach to the direct 

installation of efficient appliances in low-income households and complex industrial upgrades. In 2013, 

utility EE programs alone were reported to have gross incremental45 electricity savings of approximately 

24,000 GWh46 with an estimated 16 million metric tons of avoided CO2.

Demand-side EE programs can include direct and indirect action programs:

• Direct action programs are those that result in the direct, explicit implementation at end-use energy 

consumer facilities, of installed pieces of equipment or systems, as well as modifications of 

equipment, systems, or operations that reduce the amount of electricity that would otherwise have 

been used to deliver an equivalent or improved level of end-use service. Examples include: 

- Consumer product rebates, 

- Prescriptive and custom HVAC and lighting retrofit incentives, 

- Incentives or technical assistance for construction of new energy efficient buildings, 

- Whole-house retrofits, 

- Street lighting retrofits, 

- Commissioning and retrocommissioning, and 

• Indirect action programs are those intended to facilitate or indirectly result in implementation, at 

end-use energy consumer facilities, of installed pieces of equipment or systems, as well as 

modifications of equipment, systems, or operations that reduce the amount of electricity that would 

otherwise have been used to deliver an equivalent or improved level of end-use service. Examples

include: 

- Consumer behavior programs, 

- Marketing education and outreach programs, 

- Workforce education and training programs, 

- Financing programs,

47 and 

- Energy audit programs. 

Note that both direct and indirect programs can be specifically directed toward low-income households 

and disadvantaged communities. Specific EM&V guidance is organized by whether the subject program 

relies on direct or indirect actions, as described above.

 

45 Incremental savings include all energy savings that accumulated in 2013 from new 2013 participation in existing 

energy efficiency programs and all participants in new 2013 programs. 

46 CEE Annual Industry Report, 2014 State of the Efficiency Program Industry, May 2015, 

http://www.library.cee1.org/sites/default/files/library/12193/CEE_2014_Annual_Industry_Report.pdf

47 Some direct action programs have financing components and the savings of those programs can be assessed as 

described for direct action programs. However, for programs that only offer financing, their ability to generate 

incremental savings can be assessed using the indirect program suggested approaches and assumptions provided 

herein.
*** Draft for Public Input *** 

31

3.1.2. Applicable Guidance – Direct Action EE Programs

The following EM&V guidance reflects industry best practices and technical assumptions, and is 

intended to assist EE providers as they implement direct action EE programs.

• EM&V methods – The savings from direct action EE programs can be determined using the full suite 

of EM&V methods defined in Section 2.1: PB-MV, comparison group approaches, and deemed 

savings. 

• Baselines – CPBs are applicable for direct action EE programs and should be defined consistently 

within a given action, as described in Section 2.2. 

• Independent factors – To ensure that electricity savings are calculated consistently, each project in 

a single program should apply the same approach to independent factor conditions, as described in 

Section 2.5.

• Accuracy and reliability of reported savings values – As indicated in Section 2.6, reported accuracy 

and reliability should address both random error, quantified in terms of statistical precision, and 

systematic bias, addressed via discussion of potential sources of bias and their likely effects. 

• Avoiding of double counting – Procedures to avoid double counting are described in Section 2.7.

• Evaluation cycles – Section 2.9 describes the requirements, including frequency, for verification to 

confirm measures were installed and are operating to produce savings, and for quantification of 

savings, and for their combination via comparison group methods..

3.1.3. Applicable Guidance – Indirect Action EE Programs

• EM&V methods – The EM&V methods that can be used for indirect action EE programs depend on 

the program structure and delivery, as follows.

- Comparison group methods using RCT approaches are widely considered reliable and rigorous, 

and are encouraged by the EPA. However, use of these methods require that the program can 

be delivered to certain customers while excluding others from its influence, with random 

assignment of who receives the program incentive and who does not.

- When including comparison group methods in a quasi-experimental design, the EE provider 

should justify the validity of the quasi-experimental comparison group as a representation of the 

participants in the absence of the EE intervention. The approach to ensuring validity should also 

be described.

• Baselines 

- When direct comparison is used to quantify savings using comparison group methods, the MWh 

usage of the comparison group of non-participants defines the equivalent of a CPB. When 

regression methods are used, the regression estimate that corresponds to the participant 

condition absent the EE intervention represents the CPB. Direct comparison is commonly used 

with RCT, while regression is more commonly used with quasi-experimental design, but either 

analysis method may be used with either design. The rationale for the design and analysis 

method used should be specified in the EM&V plan. In particular, the plan should describe how 

the specified comparison group represents the participants absent the intervention.

- When deemed or PB-MV methods are used, baselines for indirect action programs should be 

defined consistently with baselines for similar EE actions in direct programs.
*** Draft for Public Input *** 

32

• Independent factors – Comparison group methods can be applied to produce savings for the 

particular conditions of the consumption data included in the analysis, or on a weather-normalized 

basis.

• Accuracy and reliability of reported savings values – As indicated in Section 2.6, reported accuracy 

and reliability should address both random error, quantified in terms of statistical precision, and 

systematic bias, addressed via discussion of potential sources of bias and their likely effects.

• Avoiding double counting – Applicable procedures for avoiding double counting are described in 

Section 2.7. In addition, if an indirect action program is operated on the same participants for 

successive years, savings may be counted as a persistent effect of a prior year or as the current 

program effect, but not both simultaneously in the same year.

• Effective useful life and persistence of savings – With indirect action programs using comparison 

group methods, the persistence of savings should be determined each year (or as discussed above

possibly every other or third year). Savings are simply quantified until they are shown to fall to a 

zero or near-zero. For deemed or PB-MV methods, a value for the EUL of program savings should be 

quantified for that period.

• Evaluation cycles – Section 2.9 describes the requirements, including frequency, for verification to 

confirm measures were installed and are operating to produce savings, and for quantification of 

savings, and for their combination via comparison group methods.

• Verification – When comparison groups are the basis for PB-MV, verification for indirect action EE 

programs is the same as for direct action EE programs. That is, the savings determined by the 

comparison group analysis implicitly reflects both what actions were taken and quantification of 

associated savings.

- The following alternate verification approaches, however, are suggested for comparison and 

control group approaches:

 With quasi-experimental approaches, verification activities should be undertaken to ensure 

the actual installation of measures. Examples include confirming the number of students 

that took a training class and the curriculum of the class for a workforce education and 

training program, or confirming that marketing or educational program materials were 

actually distributed for a marketing program. The recommended frequency of verification 

depends on program specific considerations, but should be between once per year and no 

less than every 3 years.

 With RCT control groups, verification should confirm the proper (random) selection of 

treatment and control group members.

3.2 Project-Based Energy Efficiency

3.2.1. Description

Project-based EE involves implementation of one or more EE projects, retrofit or new construction, by 

private firms (including ESCOs, contractors, or site owners/developers) at public or privately owned 

facilities in any market sector (e.g., residential, multifamily, commercial). Project examples include 

retrofits at a school or university campus, retrofits of individual office or apartment buildings, and 

retrofits at industrial facilities; many projects are completed for the municipal, schools and hospitals 
*** Draft for Public Input *** 

33

(MUSH) market, including water treatment plants. This category can also include projects such as direct 

load control and EE projects at water treatment plants.

A distinguishing characteristic of project-based EE is that it applies PB-MV, or measure-based deemed 

savings values, instead of program-based EM&V methods. That is, savings are quantified for each 

project. By contrast, program-level savings quantify and verify savings only for a sample of projects (to 

represent all projects in the full program), or by conducting participant or market studies to determine 

factors that apply to the program as a whole.

48

During 2012, ESCO projects were estimated to have achieved gross incremental electricity savings of 

about 2,500 GWh and 34,000 GWh of ongoing project savings. It should be noted that some of these 

savings could overlap with demand-side EE program savings, and care should be taken to avoid double 

counting between these two categories.49

3.2.2. Applicable Guidance – Project-Based Energy Efficiency

• EM&V methods – This EM&V guidance provides for the use of any of the EM&V methods defined in 

Section 2.1 (i.e., PB-MV, comparison group methods, and deemed savings). In practice, however, 

comparison group methods are typically not practical for individual projects. This is due to the 

difficulty in finding a proper comparison, or control, group for a single project or a small group of 

projects.50

- Therefore, the recommended methods are PB-MV and deemed savings, as described Section 

2.4. In practice, PB-MV is often used in combination with deemed savings approaches.51 In 

practice, the suggested and more common PB-MV methods for retrofit projects are IPMVP 

Options A, B and C and, for new construction or replace on failure, IPMVP Option D.

• Baselines – As indicated in Section 2.2, CPBs are the regulatory requirement for quantifying savings. 

These baselines should be defined consistently across a portfolio of individual projects. Although the 

individual projects might apply differing baselines (e.g., because of the applicability of a code or 

standard, or the condition of replaced equipment), the requirements for defining baselines should 

be consistent. 

 

48 This is because the savings from individual projects are assigned to the responsible entity, whether a contractor 

or consumer, and not to a program administrator as in the case with EE programs.

49 Estimating Customer Electricity Savings From Projects Installed by the U.S. ESCO Industry, Juan Pablo Carvallo, 

Peter H. Larsen, Charles A. Goldman, Lawrence Berkeley National Laboratory , LBNL-6877E, May 2015.

50 For example, finding the right comparison facility, occupants, and owner for retrofits at a college campus, office 

building, or factory. With PB-MV, one could say that the “comparison group” is the affected facility before the 

efficiency retrofit. This approach is known as pre-post analysis. However, because of how the comparison group is 

defined, it does not have the benefits of more rigorously implemented quasi-experimental methods.

51 For example with IPMVP Option A, some information used to determine savings is gathered through metering 

and other information is based on deemed savings values. In contrast to the application of deemed savings alone, 

IPMVP Option A involves the application of facility-specific data and parameters in the quantification of savings. 

Advances in metering and analyses technologies and practices (such as advances in the use of data available from 

smart meters) are lowering the cost and increasing the reliability of PB-MV savings quantification.
*** Draft for Public Input *** 

34

For private EE contracts with consumers such 

as ESCO contracts, the baselines for savings 

calculation may be set according to the needs 

and preference of the customer. However, for 

states reporting savings to EPA, savings from 

these projects must be calculated using CPBs as 

defined in Section 2.2. Thus, for state reporting 

of privately implemented project savings, a 

second set of calculations may be required in 

addition to those used to establish and 

administer the contract between the provider 

and its customer.

Commonly, the baseline for calculating savings 

for such contracts is the existing equipment. As 

indicated in Section 2.2, the CPB for calculating 

savings corresponds to existing equipment only 

in the case of retrofit, and then only for the 

remaining useful life (RUL) of the equipment.

For replace-on-failure or new construction, and 

for early replacement after the RUL, the CPB is 

standard efficiency or market common practice 

equipment. Since it will not ordinarily be 

possible to take measurements under standard 

efficiency or market practice conditions, an 

adjusted calculation should be used to 

determine savings relative to the CPB as 

required.

If deemed methods are used to calculate

savings for purposes of the private contract, an 

alternative deemed calculation using the CPB as 

defined in Section 2.2 should be used to 

calculate savings for purposes of reporting 

savings to the EPA.

If PB-MV is the basis for the savings determined for the private contract, the measured values

should be used also in an alternative calculation of determine savings relative to the CPB. This 

means that the CPB efficiency level should be substituted for the existing equipment efficiency in 

the savings calculations or simulations developed from the measured data. If the PB-MV method is 

based on measured differences between the prior existing and new equipment, the savings relative 

to the CPB can be calculated from the savings relative to prior equipment as follows:

Savings|CPB 

= Savings|Existing x (1/EFFCPB - 1/EFFNEW)/ (1/EFFEX - 1/EFFNEW)

where

Savings|CPB = Savings relative to the CPB

Savings|Existing = Savings relative to the existing equipment

Industry-Standard Protocols

and Guidelines

The following are industry best practices PB-MV

guidelines and protocols for project-based EE

 IPMVP – International Performance 

Measurement and Verification Protocol: 

Concepts and Options for Determining Energy 

and Water Savings Volume I, EVO-10000 -

1.2007, Efficiency Valuation Organization. 

www.evo-world.com

 FEMP – M&V Guidelines: Measurement and 

Verification for Federal Energy Projects, 

Version 4.0, Prepared for the U.S. Department 

of Energy Federal Energy Management 

Program.

 ASHRAE – Guideline 14-2002: Measurement of 

Energy and Demand Savings, American Society 

of Heating, Refrigerating, and Air-Conditioning 

Engineers

 U.S. DOE UMP – Uniform Method Project: 

http://www.energy.gov/eere/downloads/unif

orm-methods-project-methods-determiningenergy-efficiency-savings-specific

 For deemed savings practices, the operating 

procedures of well-established deemed 

savings databases, such as the one operated 

by the Northwest Regional Technical Forum. 

http://www.rtf.nwcouncil.org ve contains a list 

of protocols that can be applied, with 

appropriate explanation in EM&V plans and 

reports.
*** Draft for Public Input *** 

35

EFFCPB = efficiency of the CPB equipment

EFFNEW = efficiency of the new equipment

EFFEX = = efficiency of the existing equipment.

Alternative methods to calculate savings relative to the CPB may also be used.

• Independent factors. As indicated in Section 2.5.2, the same values of the independent factors 

should be assumed for the baseline or baseline period as for the with- EE conditions. These values 

may be either actual values of the independent factors observed during the period when savings 

occur, or may be estimated typical values. With PB-MV methods, the savings typically are based on 

actual conditions. In contrast, normalized or typical conditions are recommended as the basis for 

calculating deemed savings values. Caution should be used when combining PB-MV methods with 

deemed savings methods within a single project to ensure that independent factors are considered 

consistently in savings quantification. 

• Accuracy and reliability of reported savings values. As discussed in Section 2.6, the certainty of 

reported savings values should be described in monitoring and verification reports via a written 

discussion of the PB-MV or deemed savings method(s) used, potential risks and biases, and related 

quality-control measures utilized. It is particularly important to indicate the sources of any deemed 

savings values, and to specify how the metering (what is metered, for how long, etc.) provides 

representative data. If sampling is used to determine savings, the confidence and precision of the 

sample’s metric (e.g., lighting operating hours) must be reported. If the savings relative to the CPB 

are calculated as an adjustment to savings relative to a different baseline used for the private 

contract, the method and rationale for the determination of savings relative to the CPB should be 

described.

• Avoiding double counting. Procedures to avoid double counting are described in Section 2.7.3.

Particular caution should be used to avoid double counting if the project was also part of a direct 

action EE program or might be influenced by an indirect action EE program that induces a consumer 

to save energy (e.g., a behavior program). This could otherwise result in an outcome where some of 

the same savings are claimed twice. If a project also participates in a direct action program, the 

appropriate steps include coordinating across initiatives and adequately documenting savings

claims.

• Effective useful life and persistence of savings. On a project-by-project basis, the persistence of 

savings (i.e., the number of years after initial installation that savings are counted) can be 

determined with deemed EUL values. Persistence of savings, however, is typically based on periodic 

verification of all projects or a sample of representative projects. Verification, involving site 

inspections to ensure that EE measures are still operating correctly, can occur each year for a subset 

of projects on a rotating cycle, which should occur every 2 or 3 years. These verification results 

should be used to adjust annual savings. 

• Evaluation cycles. Section 2.9.2 describes the requirements, including frequency, for verification to 

confirm measures were installed and are operating to produce savings, and for quantification of 

savings.
*** Draft for Public Input *** 

36

3.3 Building Energy Codes

3.3.1. Description

Local building energy codes are enforceable

EE requirements that apply to the design 

and construction of buildings in many 

jurisdictions.

52According to the U.S. DOE, 

“model building energy codes and 

standards have the potential to save U.S. 

consumers an estimated $330 billion by 

2040. This equates to nearly 80 quads of 

cumulative full-fuel-cycle energy savings 

and over 6.2 billion metric tons of avoided 

carbon dioxide emissions.”

53

Specific building energy code actions that 

states and local governments may take

include:

• Adoption of new energy codes with 

greater EE requirements than codes

that have already been determined by 

the federal government to be cost 

effective, and 

Ex-ante estimates of building code impacts 

are completed regularly as codes are 

developed and adopted. In contrast, ex-post quantification of energy savings from building energy code 

adoption and compliance activities is not as common or well established. The primary code adoption 

and compliance impact evaluation work to-date has been completed in six states (Arizona, California, 

New York, Oregon, Rhode Island, and Washington) and at Pacific Northwest National Laboratory 

 

52 Energy codes are adopted by State and local governments and govern the design and construction of new 

residential and commercial structures in their jurisdictions, as well as in some cases the retrofitting of existing 

structures. Energy codes reference areas of construction such as wall and ceiling insulation, window and door 

specifications, HVAC equipment efficiency, and lighting fixtures. Usually, there are two methods for compliance. 

The most common that codes take is the prescriptive approach, in which the code stipulates the stringency of the 

materials and equipment the builder must use. The other method is the performance approach, the code allocates 

a total allowable energy use for a building, and the builder can choose the materials and equipment that will meet 

this target. State-level policies on building energy codes vary widely across the 50 States, the District of Columbia, 

and the five U.S. territories, and sometimes even within States, e.g. home rule States. Two foundational model 

building energy codes may be adopted by States and local jurisdictions to regulate the design and construction of 

new buildings: the International Energy Conservation Code® (IECC) and the ANSI/ASHRAE/IESNA Standard 90.1 

Energy Standard for Buildings except Low-Rise Residential Buildings.

52 The IECC addresses all residential and 

commercial buildings. ASHRAE 90.1 covers commercial buildings, defined as buildings other than single-family 

dwellings and multi-family buildings three stories or less above grade.

53 https://www.energycodes.gov/status-state-energy-code-adoption - accessed June 12, 2015

Key Building Energy Code Definitions

 Code: Specifically, legal EE requirements that apply to 

the design and construction of buildings, usually for 

new buildings and for renovations and additions 

applying to existing buildings.

 Adoption: The process and actions required to put a 

code in place formally, such as a rulemaking process.

 Compliance: The process of meeting the code 

requirements and demonstrating that these 

requirements have been satisfied. Compliance is the 

responsibility of the builder or contractor.

 Enforcement: The process of verifying that a building 

meets the code. This process is typically conducted by a 

building code official.

 Naturally Occurring Market Adoption (NOMAD): The 

proportion of savings or application of measures

equivalent to the code that would have taken place in 

the market even if the code had not been adopted.

Source: Attributing Building Energy Code Savings to Energy 

Efficiency Programs, IEE/IMT/NEEP Report, February 2013, The 

Cadmus Group, Inc., Energy Futures Group NMR Group, Inc. 

Optimal Energy
*** Draft for Public Input *** 

37

(PNNL)54 for U.S. DOE. These states have regulatory structures that define acceptable procedures for 

quantifying savings from code programs and attribute code program savings to EE program 

administrators.55

3.3.2. Applicable Guidance – State and Local Government Building Energy Code and Compliance 

Programs

• EM&V methods – Achieved electricity savings from energy codes may be determined using a 

bottom-up approach that uses this equation, or a structurally similar analysis:

Annual electricity savings = (affected construction and retrofit area per year) × (electricity savings per 

unit of area) × (compliance rate) = square footage per year × (MWH savings/square foot) x 

(percentage)

For determining electricity savings per unit of area (for code adoption programs) or compliance 

rates and energy savings (for compliance rate programs), acceptable options are direct empirical and 

indirect estimation:

- Direct Empirical: These approaches are based on data collection for a representative sample of 

existing buildings that have been built or renovated subject to the subject code.

• With the modeling version of this approach, an empirically tested building energy simulation model 

is used with typical weather data and actual characteristics for the sample buildings. With the 

billing/energy data analysis approach, energy bills from buildings built or renovated under the new 

code are compared with energy bills of buildings constructed prior to the new code., The models or 

billing analyses are used for:

- Electricity savings (net of compliance) – estimated by comparing the modeled energy use of an 

as-built building to modeled use of the same configuration building if it were built to meet the 

prior code exactly, or comparing buildings built under the new code to similar buildings built 

prior to the new code. 

- Compliance rates – estimated by comparing the modeled energy use of an as-built building to 

modeled use of the same building if it were built to meet the current code exactly.56

• Indirect Estimation: This approach is associated primarily with assessing code compliance rates using 

secondary information, such as documents filed with building departments, building audits, or 

surveys of code officials. The DOE/PNNL checklist, developed under the American Reinvestment and 

Recovery Act (ARRA), is an example of a method that provides such an approach for assessing code 

compliance.57

The recommended approach for determining electricity savings involves accounting for naturally 

occurring market adoption (NOMAD) of measures that are required by the code. NOMAD may be 

 

54 http://www.energycodes.gov/resource-center

55 Attributing Building Energy Code Savings to Energy Efficiency Programs, IEE/IMT/NEEP Report, February 2013, 

Prepared by: The Cadmus Group, Inc., Energy Futures Group NMR Group, Inc. Optimal Energy

56 The preferred way to determine compliance rates is with modeling or billing analyses of actual buildings that 

were built or renovated and which were subject to the code. However, such analyses can be enhanced by, or 

possibly replaced with interviews with key trade allies and/or experts in the building standard development 

process.

57 http://www.energycodes.gov/compliance/evaluation
*** Draft for Public Input *** 

38

estimated through collection of market data or through expert judgment techniques. Acceptable 

approaches include conducting literature searches on the penetration rates of similar technologies 

with similar product characteristics, the use of expert opinions (e.g., via a Delphi process) on the 

expected penetration rates in the absence of a code requirement, and reviewing relevant market 

data. Use of multiple approaches is encouraged.

Data on the amount of construction and retrofits that would be affected by the new code each year 

(i.e., how many square feet of each building type will be built or renovated in a given year) are 

available from various resources such as:

- Industry statistics published by construction trade organizations 

- Publicly available building and renovation permit reports 

- Data purchased from market research firms

- U.S. Census data (used to scale national numbers to state-specific values)

• Electricity Savings Metrics and Baselines – Electricity savings from building energy codes and 

compliance enhancement programs should be determined with respect to a common practice 

baseline (CPB). With building energy codes, the CPB should be determined with consideration of 

naturally occurring market adoption (NOMAD) of efficiency building practices in the absence of an 

energy code or a prior energy code. (See text box for definition of NOMAD and related terms). 

The baseline needs to be estimated with consideration of building practices assumed to have 

occurred in the absence of the code. Baseline building efficiency levels may be below, at, or even 

above the efficiency of the code-mandated efficiency 

• Accuracy and reliability of reported savings values – As discussed in Section 2.6, the certainty of 

reported savings values should be described in monitoring and verification reports with a discussion 

of the EM&V method(s) used, potential risks and biases, and related quality-control measures 

utilized. It is particularly important to specify the source(s) of construction and renovation data, perunit savings estimates, compliance rates, and NOMAD. If sampling is used to determine savings, the 

confidence and precision of the sample metric (e.g., compliance rates) should be reported.

• Avoiding double counting – Procedures to avoid double counting particularly between code 

initiatives and programs or projects are described in Section 2.7. To avoid double counting among 

multiple code efforts, a simple way may be to assume the baseline for the new code is the prior 

code, assuming NOMAD has not moved building efficiency practices beyond the prior code.

• Effective useful life and persistence of savings – At a minimum, code savings can be assumed to 

continue until at least the time at which a new state or local code is put into place. More 

realistically, however, savings from structural measures in a building built under a new code may be 

assumed to continue up to the time of the next natural major renovation of the building.

• Evaluation cycles – Construction/renovation square-footage data should be updated at least 

biennially and per-unit electricity savings values updated at least once every 4 years or whenever 

new building energy codes are put in place for the building type(s), whichever is more often. The 

principle metrics that should be updated at least every 4 years are baselines with respect to:

- Any new state or local building energy codes that have come into force, and
*** Draft for Public Input *** 

39

- NOMAD – as construction practices, with respect to efficiency, would be expected to change 

over time, in the absence of codes, so that the CPB in, for example, 2029 might be much more 

”efficient” than in 2025.

Select EM&V Resources for Quantifying Savings from Building Codes

The following studies reflect the state-of-the-art regarding ex-post impact evaluation for building codes:

• Building Energy Codes Program: National Benefits Assessment, 1992–2040. 2014. Pacific Northwest 

National Laboratory 

• Measuring State Energy Code Compliance. 2010. Pacific Northwest National Laboratory 

• Residential Energy Code Compliance Evaluation: Guidance for Project Teams, Draft. November 2014. 

Pacific Northwest National Laboratory. PNNL-23538

• California Energy Efficiency Evaluation Protocols: Technical, Methodological, and Reporting 

Requirements for Evaluation Professionals, Codes And Standards And Compliance Enhancement 

Evaluation Protocol, April 2006, Prepared for the California Public Utilities Commission by The 

TecMarket Works Team

• Attributing Building Energy Code Savings to Energy Efficiency Programs, Prepared by The Cadmus 

Group, Inc., Energy Futures Group, NMR, and Optimal Energy for the Northeast Energy Efficiency 

Partnerships (NEEP) and its funding partners, the Institute for Market Transformation (IMT) and IEE. 

February 2013

• Statewide Codes and Standards Program Impact Evaluation Report for Program Years 2010-2012. 

August 2014. Prepared for: California Public Utilities Commission Prepared by Cadmus, Energy Services 

Division and DNV GL

• Resource Guide for Policy Makers. June 2011. U.S. DOE Building Energy Codes Program

The following are reports that use or discuss “top down” (econometric) evaluation of codes:

• The Impact of State Level Building Codes on Residential Electricity Consumption, Anin 

Aroonruengsawat, Maximilian Auffhammer, and Alan H. Sanstad, Energy Journal 2012, Volume 33, 

Number 1

• Are Building Codes Effective at Saving Energy? Evidence From Residential Billing Data In Florida, Grant 

D. Jacobsen and Matthew J. Kotchen*, The Review of Economics and Statistics, March 2013, 95(1): 34–

49

• Analysis of Energy Saving Impacts of New Residential Energy Codes for the Gulf Coast. Lucas, R., ‘’’ The 

Pacific Northwest National Laboratory contract DE-AC05-76RL01830 (2007)
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40

3.4 Incremental Product Energy Standards

3.4.1. Description

Appliance and equipment (product) energy standards are EE requirements that specify the minimum 

efficiency levels of specific products. Federal standards58 currently apply to about 55 categories of 

appliances and equipment sold in the United States.

59 For products not subject to existing national 

standards (and thus not subject to federal pre-emption60), states may adopt their own product 

standards for sales within their borders. Within the past decade, states have set standards for products 

ranging from DVD players to swimming pool pumps to water dispensers. Since 2001, Arizona, California, 

Connecticut, Maryland, Massachusetts, New York, Oregon, Rhode Island, and Washington have each 

passed several rounds of state product standards.61,62

In setting the actual product standards, the U.S. DOE and state energy offices adhere to an extensive 

and robust analytical process. This typically involves conducting detailed energy savings (and economic 

impact) potential studies of the anticipated future effects of these standards. In contrast, only a limited 

number of ex-post energy saving studies have been completed. California has conducted three cycles of 

energy code and appliance standard evaluations for the statewide Codes and Standards Program

(implemented by four utility program administrators). The evaluation approach used in California is 

based on bottom-up analyses and is the primary basis for the following suggested EM&V approaches.

3.4.2. Applicable Guidance – State and Local Government Incremental Product Energy Standards

• EM&V methods – Achieved electricity savings from product standards should be determined on a 

product-by-product basis using a bottom-up approach and this equation:

Annual electricity savings = 

(products sales volume per year) × (per unit electricity savings of sold products subject to standard) 

There are two approaches that can be applied, each with a different metric for sales volume:

 

58 Electricity savings associated with federal product standards or adopting codes that the federal government has 

already determined to be cost-effective cannot be used for compliance with EPA’s emissions guidelines.

59 Standards usually include the test procedures needed to measure the efficiency of these products and some 

guidance on how equipment that meets these standards needs to be labeled or included in directories. A recent 

study indicated that existing Federal standards alone will produce annual electricity savings in 2035 of about 720 

TWh, saving about 14 percent of what the projected annual electricity consumption in that year would have been 

without standards, along with annual emissions reductions in 2035 of around 470 million metric tons of CO2. From: 

The Efficiency Boom: Cashing In on the Savings from Appliance Standards, Updated from and supersedes report 

ASAP-7/ACEEE-A091, Amanda Lowenberger, Joanna Mauer, Andrew deLaski, Marianne DiMascio, Jennifer Amann, 

and Steven Nadel, March 2012. Report Number ASAP-8/ACEEE-A123. For a list of States that have adopted

national standards, see: http://www.appliance-standards.org/federal and 

http://www.energy.gov/eere/buildings/appliance-and-equipment-standards-program

60 Federal regulation becomes the law and supersedes any State regulation. Once the Federal government 

establishes an energy-efficiency standard, no State may have a regulation different from the Federal standard. This 

is referred to as Federal pre-emption.

61 Quoted directly from http://www.appliance-standards.org/standard-basics-DOE-state-legislature-productrequirements accessed 12/30/14. 

62 For list of State standards see http://www.appliance-standards.org/states
*** Draft for Public Input *** 

41

- The first approach is based on the view that a standard moves the entire market, with:

 Product sales volume = total applicable market sales

 Per unit electricity savings = the difference in sales-weighted average energy use of products 

sold under NOMAD vs after the new standard.

- The second approach is based on the view that the standard eliminates only the least efficient 

units, with: 

 Product sales volume = applicable market sales currently below the new standard

 Per unit electricity savings = difference between the new standard and sales-weighted 

average energy use of products that would not meet the new standard under NOMAD.

Sources of product sales data are:

- Industry statistics published by product-manufacturing trade organizations 

- Publicly available market characterization reports 

- Data purchased from market research firms, such a point-of-sale data and surveys of vendors, 

retailers, and contractors

- U.S. DOE Technical Support Documents for appliance and equipment standards 

- U.S. Census data (used to scale national numbers to state-specific values)

Caution should be used when applying these data as they can be based on limited market surveys or 

might be missing certain products or models subject to the standard, but not necessarily tracked.

Per-unit electricity savings should be based on:

- Established laboratory-based test methods to determine average unit energy savings. A source 

of laboratory-testing requirements could be those established by industry groups, DOE, and the 

California Energy Commission.63 The baseline should include assumptions about NOMAD to 

calculate a conservative correction factor for the unit-energy savings.

- Use of field measurements with NOMAD adjustments.

 

63 Singh, Harinder, Ken Rider, Betty Chrisman, and Jared Babula. 2014. 2014 Appliance Efficiency Regulations. 

California Energy Commission. Publication Number: CEC-400-2014-009-CMF 
*** Draft for Public Input *** 

42

At this time, NOMAD estimates are typically 

determined by using a Delphi technique. 

These NOMAD estimates should include 

consideration of effects of prior-year 

standards and standards support programs.

• Electricity Savings Metrics and Baselines –

Determine savings from product energy 

standards with respect to a CPB. For product 

standards, determine CPB with consideration 

of NOMAD of higher efficiency products in the 

absence of a standard.

- NOMAD is a projection of what the annual 

sales,

64 over time, of products meeting 

the standards would have been if the 

standards had not been adopted.

- Once the standard is in effect, the natural 

market no longer exists or can exist in 

reality. Methods for determining NOMAD 

are discussed in the next item on EM&V 

methods.

• Accuracy and reliability of reported savings 

values – As discussed in Section 2.6, the 

certainty of reported savings values should be 

described in monitoring and verification 

reports with a discussion of the EM&V 

method(s) used, potential risks and biases, 

and related quality-control measures that 

were used. Particularly important to indicate 

are the source(s) of product sales data, perunit savings estimates, and NOMAD. If 

sampling is used in the process of determining 

savings, however, the confidence and 

precision of the sample’s metric (e.g., field 

measured electricity consumption) can and 

should be reported.

• Avoiding double counting – Procedures to avoid double counting particularly between code 

initiatives and programs or projects are described in Section 2.7. Updated product standards should 

be considered so that prior and new state or local standards for the same product(s) do not double 

count the same increments of savings.

• Effective useful life and persistence of savings – At a minimum, savings should be assumed to 

continue until at least a new federal, state or local standard is put into place.

 

64 Not only sales, but also installation of the sold equipment should be assessed, but for the purposes of this 

guidance document, only sales data are described as involved in determining electricity savings.

Relevant EM&V protocols

 Following are a protocol and a guidebook that 

can be consulted for guidance on product 

standard EM&V:

- California Energy Efficiency Evaluation 

Protocols: Technical, Methodological, and 

Reporting Requirements for Evaluation 

Professionals, Codes And Standards And 

Compliance Enhancement Evaluation 

Protocol, April 2006, Prepared for the 

California Public Utilities Commission by The 

TecMarket Works Team

- Section 9 of this document: Energy-Efficiency 

Labels and Standards: A Guidebook For 

Appliances, Equipment, And Lighting 2nd 

Edition, Stephen Wiel and James E. McMahon, 

Collaborative Labeling And Appliance 

Standards Program (CLASP) Washington, 

D.C. USA, February 2005. LBNL Report 

Number: LBNL-45387(A)

- Related EM&V reports that can provide 

valuable information are:

- Statewide Codes and Standards Program 

Impact Evaluation Report for Program Years 

2010–2012. August 2014. California Public 

Utilities Commission Prepared by Cadmus, 

Energy Services Division, and DNV GL.

- Realized and Prospective Impacts of U.S. 

Energy Efficiency Standards for Residential 

Appliances, Stephen Meyers, James 

McMahon, Michael McNeil, Xiaomin Liu, 

Environmental Energy Technologies Division 

Lawrence Berkeley National Laboratory, LBNL49504, June 2002.
*** Draft for Public Input *** 

43

• Evaluation cycles – Electricity savings values, which are reported for each year, are based on perunit electricity savings values and sales volume data. Sales volume data should be updated at least 

biennially and per-unit electricity savings values updated at least once every 4 years or whenever 

new standards are put in place for the same product(s), whichever is more often. The principal 

metrics that likely would be updated at least every 4 years are baselines with respect to:

- Any new state or federal product standards that have come into force.

- NOMAD – it is expected that product efficiencies will change over time, in the absence of the 

standard, so that the CPB in, for example, 2029 might be much more “efficient” than in 2025.
*** Draft for Public Input *** 

A-1

Appendix A. Glossary of Terms

This glossary includes only terms that are used in this draft EM&V guidance.65

Accuracy: concept that refers to the relationship between the true value of a variable and an estimate of 

the value. The term can also be used in reference to a model or a set of measured data, or to describe a 

measuring instrument's capability.

Adoption: process and actions required to put a code in place formally, such as a rulemaking process.

Baseline: conditions (including electricity consumption) that would have existed without 

implementation of the subject EE activity. Baseline conditions are used to estimate measure-, project-,

and program-related savings.

Code: legal EE requirements that apply to the design and construction of buildings, usually for new 

buildings and for renovations and additions applying to existing buildings.

Common practice baseline (CPB): default technology or condition that would have been in place at the 

time of project implementation without a decision to install a more efficient system or measure, for 

example, the system(s) or measure(s) a typical consumer/building owner would have continued with or 

installed at the time of project implementation.

Comparison group EM&V methods: approaches to determine program savings by taking the difference 

between a comparison group’s electricity consumption and the consumption of program participants. 

Comparison group approaches include RCTs and quasi-experimental methods using nonparticipants.66

These methods are generally used to estimate program-level savings versus facility- or project-level 

savings

Compliance: process of meeting the code requirements and demonstrating that these requirements 

have been satisfied. Compliance is the responsibility of the builder or contractor.

 

65 Certain states, EE providers, and other stakeholders may currently apply variations of these terms. For additional 

information, readers can consult the glossary of the SEE Action EM&V Guide. State and Local Energy Efficiency 

Action Network. 2012. Energy Efficiency Program Impact Evaluation Guide. Prepared by Steven R. Schiller, Schiller 

Consulting, Inc., www.seeaction.energy.gov.

66 With PB-MV, one could say that the “comparison group” is the affected facility before the efficiency retrofit. This 

approach is known as pre-post analysis and some people categorize it as a quasi-experimental method. However, 

because of how the comparison group is defined, it does not have the benefits of more rigorously implemented 

quasi-experimental methods and is not considered a comparison group method for the purposes of this guidance.
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A-2

Deemed savings values: Also called stipulated savings, deemed savings values are estimates of 

electricity savings for a single unit of an installed EE measure that (1) has been developed from data 

sources (such as prior metering studies) and analytical methods that are widely considered acceptable 

for the measure and purpose, and (2) is applicable to the situation under which the measure is being 

implemented. 

Individual parameters or calculation methods can also be deemed; for example, effective useful life of a 

measure or the annual operating hours of light fixtures in an elementary school classroom. Common 

sources of deemed savings values are previous evaluations and studies that involved actual 

measurements and analyses. With deemed savings, the per-unit MWh values are determined and 

agreed to by parties prior to EE implementation.

EE measure: at an end-use energy consumer facility, an installed piece of equipment or system; a 

strategy intended to affect consumer energy use behaviors; or modification of equipment, systems, or 

operations that reduces the amount of energy that would otherwise have been used to deliver an 

equivalent or improved level of end-use service.

EE program: activity, strategy, or course of action undertaken by an implementer or administrator. Each 

program is defined by a unique combination of the program strategy, market segment, marketing 

approach, and energy efficiency measure(s) included. Programs consist of a group of projects with 

similar characteristics and installed in similar applications.

EE project: activity or course of action involving one or multiple energy efficiency measures at a single 

facility or site.

Effective useful life (EUL): an estimate of the duration of savings from individual EE measures, reported 

in years. Values are typically specific to individual EE measures or projects but also may be specified by 

program. EUL is defined through various means, including median number of years that the 

measures/projects installed under a program are still in place and operable.

Electricity savings: change in electricity use resulting from the implementation of EE measures and 

practices, reported in units of megawatt-hours (MWh). 

Enforcement: process of verifying that a building meets the code. This process is typically conducted by 

a building code official.

Free ridership: portion of a program’s supported savings that would have occurred in the absence of the 

program. 

Gross savings: change in energy consumption and/or demand that results directly from program-related 

actions taken by participants in an energy efficiency program, regardless of why they participated.

Independent factors: variables (e.g., weather, occupancy, production levels) that affect electricity 

consumption and savings, and vary independently of the variable under study.

Independent factors: the explanatory factors (e.g., weather or occupancy) that affect the variable under 

study (e.g., electricity consumption) and can vary independently of the variable under study.
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A-3

Inspections: site visits to facilities at which an EE project or measure was implemented. Inspections 

document the existence, characteristics, and operation of baseline or EE project equipment and 

systems, and the factors that affect energy use. Inspections can or might not include review of 

commissioning or retro-commissioning documentation.

Interactive effects: increases or decreases in the use of electricity or fossil fuels that occur outside of the 

end uses targeted by a specific EE measure, project, or program. For example, reduction in lighting loads 

through an energy-efficient lighting retrofit can reduce buildings’ air conditioning and increase heating 

requirements because less heat is generated by energy-efficient lighting systems compared with less 

efficient lighting systems. 

Market effects: changes in the supply chain for energy efficient equipment or the behavior of 

participants and market actors resulting from market intervention(s).

Project-based measurement and verification: PB-MV is the process of using measurements to 

determine electricity savings associated with individual projects or measures reliably. PB-MV can be 

applied to a census or sample of projects (measures) in a program (project) to determine average 

savings for the program (project). With PB-MV, baseline electricity consumption is compared with postproject (or post-measure) electricity consumption measurements, along with analyses and documented 

assumptions to quantify savings. The IPMVP defines two retrofit isolation and two whole-facility PBMV options used in the efficiency industry: 

Retrofit isolation – assessing savings from each EE measure individually (IPMVP Options A & B). 

Although Option A allows some stipulation of factors, Option A differs from the use of deemed 

saving values in that all PB-MV options require some project site measurements.

Whole facility – analyzing savings from each EE measure in a project/facility collectively – (IPMVP 

Option C, review of energy bills or Option D, calibrated simulation).

Some combination of the above. 

See Chapter 5 for more information on the IPMVP options.

Naturally occurring market adoption (NOMAD): proportion of savings or application of measures 

equivalent to the code that would have taken place in the market even if the code had not been 

adopted.

Net savings: change in energy consumption and/or demand that is attributable to a particular energy 

efficiency program. This change in energy use and/or demand may include, implicitly or explicitly, 

consideration of factors such as free ridership, participant and non-participant spillover, and induced 

market effects. These factors may be considered in how a baseline is defined (e.g., common practice) 

and/or in adjustments to gross savings values.

Random error: error occurring by “chance” that may cause the savings estimates to be inconsistently 

overstated or understated. Random errors include an observed change in energy use due to 

unaccounted-for factors that affect energy use.
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A-4

Realization rate: the ratio of electricity savings an independent third party determines divided by the 

savings claimed by the measure, project, or program provider(s). The ratio’s deviation from 1.0 can be 

due to (1) adjustments for data errors, (2) differences in implemented measure counts or other claimed 

information because of verification activities, or (3) other performance differences revealed through the

PB-MV activities.

Reliability: quality of a measurement process that would produce similar results on (1) repeated 

observations of the same condition or event, or (2) multiple observations of the same condition or event 

by different observers. Reliability refers to the likelihood that the observations can be replicated.

Reporting year cumulative savings: the amount of electricity savings quantified and verified as a result 

of EE activities in the reporting year from both (a) EE activities operating for the first time in the 

reporting year and (b) EE activities initiated in prior years and still in effect; reported in annual megawatt 

hours, MWh. 

Reporting year incremental savings: the amount of electricity savings quantified and verified as a result

of EE activities operating for the first time in the reporting year; reported in annual megawatt hours, 

MWh. 

Spillover: additional reductions in energy consumption that are due to an EE program’s influences 

beyond those directly associated with the installed EE measures—these include participant and 

nonparticipant spillover.

Systematic error: inaccuracies in the same direction, causing savings values to be consistently either 

overstated or understated. Systematic errors (also referred to as bias) may result from incorrect 

assumptions, a methodological issue, or a flawed reporting system.

Technical reference manual (TRM): resource document that includes information used in program 

planning and reporting of energy efficiency programs. It can include savings values for measures, 

engineering algorithms to calculate savings, impact factors to be applied to calculated savings (e.g., netto-gross ratio values), source documentation, specified assumptions, and other relevant material to 

support the calculation of measure and program savings—and the application of such values and 

algorithms in appropriate applications.

Verification: an assessment by an independent entity to ensure that the EE measures have been 

installed correctly and could generate the predicted savings. Verification may include assessing baseline 

conditions and confirming that the EE measures are operating according to their design intent. Site 

inspections, phone and mail surveys, and desk review of program documentation are typical verification 

activities.
*** Draft for Public Input *** 

B-1

Appendix B. Optional EM&V Plan Template for Demand-Side EE

The following guidance, in the form of an optional EE EM&V Plan template is provided to help EE 

providers develop EM&V plans that document how the applicable requirements in the final emission 

guidelines will be implemented. Such plans should be completed for each individual EE program or 

project to be used to generate ERCs or otherwise adjust an emission rate. For program-level EM&V 

plans, any one or more of the EM&V methods addressed in Section 2.1 above may be applied. Plans for

EE projects must apply PB-MV, which is also defined and described in 2.1. Completion of the following 

template results in a stand-alone EM&V plan that contains complete information regarding the EM&V to 

be undertaken, why, when, and how. 

B.1. EM&V Plan Template

Part A. Document Information

1. Program/project name and jurisdiction (e.g., state where the program will be implemented)

2. EE provider and EM&V plan author

3. Contact person for information about the EM&V plan

4. Date and version of the EM&V plan

Part B. Program/Project Background

1. Short description of the program or project being evaluated

a. EE measures offered or strategies implemented 

2. Entities

a. EE provider, including associated implementation contractors (if any)

b. State agency or other entity with oversight or implementing responsibility

c. Target market sector and delivery mechanism (for EE programs only)

3. Implementation schedule

4. Projections for annual electricity savings over the effective useful life (EUL) of the EE 

program/project67

5. Program/project budget

Part C. EM&V Overview

1. Savings quantification

a. Metric definition – i.e., annual MWh of adjusted gross savings based on a CPB

b. EM&V method – describe the value of the metric(s); include summary description of 

data collection approach, sample design, analyses methods, and significant 

assumptions; indicate the industry best-practices, protocols (e.g. IPMVP and the specific 

option) being applied.

c. Persistence of savings – if stipulated EULs are utilized, indicate source of such values and 

why they are applicable to the subject program; describe any other approaches utilized.

d. Independent factors – list and describe to be considered and supporting data that will 

be used to determine these variables’ value; include how these factors are analyzed to 

quantify savings.

 

67 Program life may be estimated as the average life of the measures being offered under the program. 
*** Draft for Public Input *** 

B-2

e. Description of whether savings will be based on conditions during performance period 

or normalized to standard/typical conditions (or other conditions); define standard 

conditions if applicable.

f. Deemed savings – if used, describe the version of the deemed savings database to be 

applied and/or the source of deemed savings; and how correct application of deemed 

savings values is ensured.

g. Sampling – if used, describe the sampling design and targeted confidence and precision 

for resulting savings.

h. T&D losses – if applied to savings values, specify the value of the loss factor, its source, 

and the applicable methodology.

i. Interactive effects – describe how interactive effects are calculated, their values, data 

sources and how the values are factored into measure saving values; if interactive 

effects are not included, explain why. 

2. Verification activities – indicate intended verification activities, including:

a. When they will occur and who will conduct

b. How they will be used to adjust savings values as needed

3. Avoiding double counting – indicate sources of potential double counting of savings and how it 

will be avoided including the tracking and accounting procedures that will be applied.

4. Accuracy and reliability of reported savings values – indicate expectations for overall certainty of 

savings estimates, how the certainty of quantified MWh savings values will be assessed, and the 

methods to be used to control the types of error inherent to the applied EM&V methods, 

including:

a. Statistical indicators of certainty such as confidence and precision 

b. Discussion of the threats to validity and potential risks, bias or error inherent to the 

applied EM&V methods

c. Methods for minimizing bias and other threats to validity

d. Quality-control procedures 
*** Draft for Public Input *** 

C-1

Appendix C. EM&V Methods for Common EE Programs, Projects, and Measures: 

Best Practices and Resources

This appendix discusses existing best practices for quantify and verify savings, with relevance 

for the processes of EM&V planning, implementation, and ex-post documentation. The purpose 

of Appendix C is to provide illustrative examples of how EE savings can be quantified and 

verified at the program, project, and measure level, and to offer associated information 

resources and lessons gained from experience over the last several decades. Much of this 

information can similarly be applied to EE programs, projects, and measures that are not 

explicitly covered. 

C.1. EM&V Methods for Select EE Program Types

Table C-1, Common EM&V Methods and Activities for Typical Consumer-Funded EE Programs, identifies

the actual evaluation activities that are typically undertaken when a particular EM&V method is selected 

and applied. This table is offered as an information resource, as applied to most of the common EE 

programs in use today. It does not cover all program types and circumstances, does not prescribe one 

way to conduct EM&V (i.e., there are valid and appropriate reasons why a certain situation may call for a 

different method or set of EM&V activities).

Table C-1. Common EM&V Methods and Activities for Typical Consumer-Funded EE Programs

Type of Energy 

Efficiency Program

EM&V 

Method

Typical Evaluation Activities Example Guidance and 

References Links

C

o

mparison

M

&

V

Deemed

Residential Audit 

Programs

X X X • Residential building 

simulation

• Savings algorithms

• Billing analysis

• Surveys to determine 

actions taken, together 

with deemed savings per 

unit or measure

Uniform Methods Project, 

Chapter 8: Whole-Building Retrofit 

with Consumption Data Analysis 

Evaluation Protocol

See also SEE Action’s Evaluation 

Measurement and Verification 

Portal for more references on 

evaluation methods and Technical 

Resource Manuals for deemed 

savings estimates by state or 

region

http://www.energy.gov/site

s/prod/files/2013/11/f5/538

27-8.pdf

https://www4.eere.energy.g

ov/seeaction/evaluationmeasurement-andverification-resource-portal
*** Draft for Public Input *** 

C-2

Type of Energy 

Efficiency Program

EM&V 

Method

Typical Evaluation Activities Example Guidance and 

References Links

C

o

mparison

M

&

V

Deemed

Residential Whole 

House Retrofit 

Programs

X X X • Billing/regression analysis

• Limited onsite data 

collection

• Building Simulation 

analysis

• Surveys to determine 

actions taken, together 

with deemed savings

Uniform Methods Project,

Chapter 8: Whole-Building Retrofit 

with Consumption Data Analysis 

Evaluation Protocol 

http://www.energy.gov/site

s/prod/files/2013/11/f5/538

27-8.pdf

Residential Lighting 

Retrofit Programs

X X • Onsite lighting loggers & 

lighting inventory

• Deemed hours of use 

(HOU) and coincidence 

factor (CF)

• Baseline matching of 

equivalent light output 

(lumens) for technologies 

not covered by federal 

standards

Uniform Methods Project; 

Chapter 21: Residential Lighting 

Protocol (December 2014) 

http://energy.gov/sites/pro

d/files/2015/02/f19/UMPCh

apter21-residential-lightingevaluation-protocol.pdf

Residential HVAC 

Retrofit Programs

X X • Onsite metering to 

determine full load hours 

(EFLH), capacity and CF

• Deemed EFLH and CF

• Gather data on system 

efficiency levels and 

charge

Uniform Methods Project, 

Chapter 4: Small Commercial and 

Residential Unitary and Split 

Cooling Systems protocol (April 

2014)

http://energy.gov/sites/pro

d/files/2013/11/f5/53827-

4.pdf

Residential Water 

Heating Retrofit 

Programs

X X • Onsite Data collection on 

water usage and 

temperatures

• Deemed system 

efficiencies and water 

usage profiles 

• Deemed savings values 

per unit capacity

Most recent study on stimulating 

adoption of high efficiency water 

heating is useful Residential 

Water Heating Program 

Facilitating the Market 

Transformation to Higher 

Efficiency Gas-Fired Water 

Heating, Prepared for the CEC by 

Gas Technology Institute, 

December 2012

http://www.energy.ca.gov/

2013publications/CEC-500-

2013-060/CEC-500-2013-

060.pdf
*** Draft for Public Input *** 

C-3

Type of Energy 

Efficiency Program

EM&V 

Method

Typical Evaluation Activities Example Guidance and 

References Links

C

o

mparison

M

&

V

Deemed

Residential 

Refrigerator 

Recycling Programs

X X • Gather equipment model 

numbers to estimate 

removed units’ 

consumption and partyear usage 

• Regression analysis to 

estimate usage reduction

• Deemed savings values 

per unit capacity

Uniform Methods Project; 

Chapter 7: Residential Recycling 

Protocol (April 2013)

http://energy.gov/sites/pro

d/files/2013/11/f5/53827-

7.pdf

Residential 

Consumer 

Electronics 

Replacement 

Programs

X X • Gather data on 

equipment energy hourly 

and energy usage, and 

load profiles

• Deemed baseline usage 

and savings algorithms

• Deemed savings values 

per unit capacity

No protocols but useful 

references include: 

(1) Set-Top-Box Pilot and Market 

Assessment (Research into Action, 

April 2015)

(2) Literature Review of 

Miscellaneous Energy Loads 

(MELs) in Residential Building, 

Prepared by Energy Solutions, 

2014

http://www.calmac.org/pub

lications/SCE_STB_Report_0

4_30_2015_FINAL.pdf

Low income Energy 

Efficiency 

Weatherization 

Programs

X X X • Onsite data collection to 

verify measure 

installation

• Billing analysis

• Building simulation 

models 

• Surveys to determine 

actions taken, together 

with deemed savings

Uniform Methods Project, 

Chapter 8: Whole-Building Retrofit 

with Consumption Data Analysis 

Evaluation Protocol

“Evaluation of a Low-Income 

Energy Efficiency Program,” by 

Jacqueline Berger, APPRISE, Paper 

published in ACEEE 2014 Summer 

Conference Proceeding 

http://www.energy.gov/site

s/prod/files/2013/11/f5/538

27-8.pdf

Residential Behavior 

Programs

X • Billing Analysis using 

randomized control trials

• Website usage statistics 

to inform billing analysis

Uniform Methods Project; 

Chapter 17: Residential Behavior 

Protocol (January 2015)

http://eetd.lbl.gov/sites/all/files/

publications/behavior-basedemv.pdf

http://energy.gov/sites/pro

d/files/2015/02/f19/UMPCh

apter17-residentialbehavior.pdf
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C-4

Type of Energy 

Efficiency Program

EM&V 

Method

Typical Evaluation Activities Example Guidance and 

References Links

C

o

mparison

M

&

V

Deemed

Residential New 

Construction 

Programs

X X • Building Simulation 

Analysis

• HERS ratings and onsite 

data collection to verify 

system installed

• Surveys to estimate 

baseline & naturally 

occurring market 

adoption (NOMAD)

• Surveys to determine 

actions taken, together 

with deemed savings

California Energy Efficiency 

Evaluation Protocols: Codes And 

Standards and Compliance 

Enhancement Evaluation Protocol, 

April 2006, California Public 

Utilities Commission 

Attributing Building Energy Code 

Savings to Energy Efficiency 

Programs, IEE/IMT/NEEP Report, 

February 2013, Prepared by: The 

Cadmus Group, Inc., Energy 

Futures Group NMR Group, Inc. 

Optimal Energy

http://www.calmac.org/pub

lications/EvaluatorsProtocol

s_Final_AdoptedviaRuling_0

6-19-2006.pdf

Non Residential 

Lighting Programs

X X • Onsite lighting loggers & 

lighting inventory

• Deemed HOU and CF

• Baseline matching of 

equivalent light output 

(lumens) for technologies 

not covered by standards

• Surveys to determine 

actions taken, together 

with deemed savings

Uniform Methods Project, 

Chapter 2 Commercial and 

Industrial Lighting Evaluation 

Protocol (April 2013) 

http://energy.gov/sites/pro

d/files/2013/11/f5/53827-

2.pdf

Non Residential 

Lighting Controls 

Programs

X X • Onsite metering of 

lighting EFLH to estimate 

control savings factor 

(CSF)

• Deemed CSF

• Whole building analysis if 

control savings expected 

to exceed 10% of building 

usage

• Surveys to determine 

actions taken, together 

with deemed savings

Uniform Methods Project, 

Chapter 3: Commercial and 

Industrial Lighting Controls 

Evaluation Protocol (April 2013)

http://energy.gov/sites/pro

d/files/2013/11/f5/53827-

3.pdf
*** Draft for Public Input *** 

C-5

Type of Energy 

Efficiency Program

EM&V 

Method

Typical Evaluation Activities Example Guidance and 

References Links

C

o

mparison

M

&

V

Deemed

Compressed Air 

Programs

X X • Engineering estimates 

(with or without 

simulation models) based 

on (a) spot 

measurements to 

determine airflow, line 

pressure, compressor 

specific power, part-load 

performance, and 

operating hours and/or 

(b) metering to estimate

compressor power, 

operating load and 

energy consumption

• In some cases onsite 

leakage measurement for 

programs that seek to 

seal leaks

• Surveys to determine 

actions taken, together 

with deemed savings

Uniform Methods Project, 

Chapter 22: Compressed Air 

Evaluation Protocol (November 

2014)

http://energy.gov/sites/pro

d/files/2015/01/f19/UMPCh

apter22-compressed-airevaluation.pdf

Commercial New 

Construction 

Programs

X X • Onsite visits to gather or 

confirm data on building 

operation and 

characteristics

• Building simulation 

models

• Data collection to 

estimate baselines and 

NOMAD

• Surveys to determine 

actions taken, together 

with deemed savings

Uniform Methods Project, 

Chapter 13: Commercial New 

Construction Evaluation Protocol 

(September 2013)

http://energy.gov/sites/pro

d/files/2014/10/f18/Chapte

r%2015--

Commercial%20New%20Co

nstruction%20Protocol.pdf
*** Draft for Public Input *** 

C-6

Type of Energy 

Efficiency Program

EM&V 

Method

Typical Evaluation Activities Example Guidance and 

References Links

C

o

mparison

M

&

V

Deemed

Large Commercial 

and Industrial 

Custom Measure 

Programs

X • Spot or short term 

metering of end uses and 

processes affected by 

retrofit to gather energy 

use and performance 

data

• Gather data on 

independent variables 

driving consumption, 

including production

• Develop and validate 

engineering savings 

equations using 

regression analysis and 

above indicated data

IPMVP – International 

Performance Measurement and 

Verification Protocol: Concepts 

and Options for Determining 

Energy and Water Savings Volume 

I, EVO-10000-1.2007, Efficiency 

Valuation Organization. 

http://www.evoworld.org/index.php?view=

download&alias=1543-

2012-ipmvp-volume-i-inenglish-27-

20&option=com_docman&It

emid=1585&lang=en

Non Residential 

Retrocommissioning 

Programs

X • Gather data on 

independent variable 

driving usage pre and 

post installation of BAS 

and meter data for 

relevant systems within 

boundary for engineering 

or computer simulation 

analyses

• Regression analysis to 

adjust savings based on 

changes in independent 

variables

Uniform Methods Project,

Chapter 16: Retrocommissioning 

Protocol (September 2014)

http://energy.gov/sites/pro

d/files/2014/10/f18/Chapte

r%2016--

Retrocommissioning%20Eva

luation%20Protocol.pdf

Key for Evaluation Methods

C = Comparison of usage, billing analysis to estimate net savings

M&V = Measurement and verification of key parameters used to estimate savings

D = Deemed values for key parameters used to estimate savings
*** Draft for Public Input *** 

C-7

C.2. Project-Based Measurement and Verification for Common EE Technologies 

As discussed in Section 3.1, PB-MV is a set of procedures for quantifying savings from an individual EE 

measure or project, versus an EE program. The information provided in this section illustrates how many 

of the EM&V topics introduced in Section 2 above are typically applied in practice to quantify and verify 

savings. It describes the PB-MV approaches frequently applied to quantify savings for specific 

technologies at the project and measure level, but does not provide guidance on whether PB-MV or 

deemed savings is the preferred approach (this section assumes that the decision to used PB-MV has 

already been made). As discussed in Section 2.1, selecting an EM&V methods involves tradeoffs

between cost, accuracy, and value of the resulting information in light of available budgets and desired 

levels of accuracy and reliability. 

C.3. Residential Lighting

C.3.1. Definition 

These projects involve installing efficient lighting products in residential dwelling, such as Light Emitting 

Diode (LED) lamps, and dimmable lights and. In all cases, the measure installed is designed to promote 

lamps with higher efficacy (lumens/Watt) and the same or better color resolution index. This guidance is 

applicable to at least the following four common program design approaches, for both new construction 

and retrofit applications of residential lighting measures:

• Direct installation of lighting products, including Energy Service Company (ESCO) projects

• Consumer incentives (e.g., rebates, coupons)

• Giveaways (installed for free during audits or mailed to homeowners)

• Upstream/Mid-stream/Downstream buy downs of retail lamp/fixture prices (e.g., point of sale 

rebates)

C.3.2. Key Challenges in Estimating Energy Savings

The primary measurement challenges for estimating lighting technology savings evaluation are:

1. Operating hours – Determining the operating hours for the lighting systems (baseline and project 

operating hours) where in many cases the exact location, building type, and fixture type are not 

known or cannot be easily found.

2. Baseline wattage – Determining the baseline wattage of lamps being replaced by more efficient 

lamps (baseline wattage) when in many cases the lumen output of the baseline bulb is not known 

and it is not known if the more efficient lamps provides lower, higher or equivalent lumens output. 

In addition, for upstream programs it is not known if the more efficient bulb simply replaced a bulb 

of similar efficiency or efficacy. 

3. Indirect savings or additional electricity use resulting from interaction with HVAC systems –

Estimating the indirect effects of installing more efficient lamps on the energy use of existing 

heating, ventilation and cooling systems. 

4. Free Riders and Technical Progress– Estimating underlying market adoption rates is challenging.

Particularly in lighting where product innovation is occurring a rapid pace. Consequently, programs 

that incent switching to current long-lived technology (e.g. a CFLs installed in 2010 persist through 

2020 in a light use application) may yield short term energy savings but also reduce longer-term 
*** Draft for Public Input *** 

C-8

savings that would have occurred if the consumer had later voluntarily switched to more efficient 

options (e.g. shifting directly from incandescent to a higher efficiency LED in 2015). 

The most common evaluation methods for dealing with each challenge are discussed below:

A. Estimating Hours of Operation (HOU)68

M&V Approach69 Typical Application

Self-reports from homeowner Sites where trained auditors/contractors have 

installed more efficient bulbs as part of residential 

audit or direct install program

Deemed hours from previous evaluations or 

TRM

Evaluation of savings from upstream programs where 

retailers or distributors have received rebates to buy 

down incremental cost of bulbs, exact location of 

bulb installation is not known and the evaluation 

budget is not sufficient to cover cost of metering.

Install lighting loggers for short-term (from 

weeks to months) measurement and to 

extrapolate result to annual usage

Most common application in states where lighting 

programs have been operated for many years, 

lighting represents a significant portion of portfolio 

savings and results can be used by multiple program 

administrators

B. Estimating Baseline wattage

M&V Approach Typical Application

In-home Inspection of a sample of baseline 

bulbs

Direct-install programs, Residential Audit Programs 

where CFL or LED’s are installed for low cost or free

Use multiplier factors taken from TRM or 

previous evaluations to directly convert 

tracking data on energy efficient bulb wattage 

to estimated delta watts70

Upstream lighting programs where location of bulb 

installation is not known, tracking systems are not 

completely developed and program is in first few 

years of operation 

Use Energy Star Lumen Equivalence Method 

with adjustment for EISA standards to estimate 

delta watts.

71

Upstream lighting programs where tracking systems 

have matured and shelf data exists to adjust baseline

usage to account for EISA standard impact and 

possible sell through of existing product

 

68 Note the range of recently evaluated residential lamp operating hours range from 1.7 to 3.0 hours per day. 

69 Note all of these approaches assume that hours of use for the new efficient bulbs is equivalent to the hours of 

use for the baseline bulbs. This assumption may need to be tested as saturation of LED’s increase.

70 Savings=multiplier * efficient bulb wattage. This multiplier is usually based on a bin match of the lumens 

produced by specific baseline and more efficient bulbs

71 Examples of equivalent wattage tables can be found in Massachusetts Technical Reference Manual 2011

(http://www.ma-eeac.org/index.htm), the New York Standard Approach for Estimating Energy Savings from Energy 

Efficiency Programs 2010 (http://www.dps.ny.gov/TechManualNYRevised10-15-10.pdf ), and the Database for 

Energy Efficiency Resources (http://www.deeresources.com )
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C. Estimating Interactive effects from efficient lighting on HVAC system usage

M&V Approach Typical Application

Estimate indirect savings impacts using Waste Heat 

factors taken from previous evaluation studies or 

TRMs from adjacent states or regions.

Lighting Programs or Direct Project installations 

where efficiency of existing HVAC systems is 

not known

Use simulation modeling Lighting Programs have been in effect for many 

years and the evaluation budget is sufficient to 

gather data on the system efficiency of HVAC 

systems where lamps have been installed

D. Other important evaluation issues

Finally, it is important to note that as lighting efficiency programs mature and the saturation of CFLs and 

LED increase, there will be a higher possibility that efficient lighting products will be used to replace in 

situ or existing efficient lighting products previously purchased. This possibility can be assessed using 

survey of homeowner purchase patterns or limited on site visits to a sample of participants.

C.3.3. Relevant protocols or evaluation studies for more information

1. Uniform Methods Project; Chapter 21: Residential Lighting Protocol (December 2014) 

http://www.energy.gov/sites/prod/files/2015/02/f19/UMPChapter21-residential-lightingevaluation-protocol.pdf

2. KEMA, Inc.; Cadmus Group, Inc. (February 8, 2010). Final Evaluation Report: Upstream Lighting 

Program. Prepared for California Public Utilities Commission, Energy Division.

http://www.calmac.org/publications/FinalUpstreamLightingEvaluationReport_Vol2_C ALMAC.pdf.

3. Navigant Consulting; Itron; Opinion Dynamics; Michaels Energy (October 23, 2013). Residential 

Energy Star Lighting PY5 Evaluation Report. Presented to Commonwealth Edison Company. 

http://www.ilsag.info/comed_eval_reports.html. 

4. Nexus Market Research, Inc.; RLW Analytics, Inc. GDS Associates (January 20, 2009). Residential 

Lighting Markdown Impact Evaluation. Prepared for Markdown and Buydown Program Sponsors in 

Connecticut, Massachusetts, Rhode Island, and Vermont. 

http://www.env.state.ma.us/dpu/docs/electric/09-64/12409nstrd2ae.pdf

C.4. Small Commercial and Residential Unitary and Split Cooling Systems

C.4.1. Definition

These projects involve installing efficient cooling systems in residential and small commercial 

applications. Typical projects involve packaged systems with capacities between three and 20 tons and 

split systems with capacities <=65,000 BTU/hour (5.4 tons). This guidance is applicable to at least the 

following common program design approaches, for both new construction and retrofit applications of 

small commercial and residential unitary and split systems measures:

• Direct installation of cooling systems, including ESCO projects

• Consumer incentives (e.g., rebates, coupons)

• Upstream/Mid-stream/Downstream buy downs of retail cooling system prices (e.g., point of sale 

rebates)
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C.4.2. Key Challenges in Estimating Energy Savings

The two most difficult or primary measurement challenges for this technology are:

1. Determining baseline efficiency conditions and 

2. Determining Equivalent Full Load Hours (EFLH) for cooling system use. 

The most common evaluation methods for dealing with each challenge are discussed below:

A. Determining Baseline Efficiency Conditions or System Ratings

M&V Approach Typical Application

Gather baseline efficiency ratings from HVAC 

system equipment nameplates from a sample of 

participating homeowners or survey HVAC 

contractors to determine the CPB

For situations where contractor or homeowner 

reports cooling system is being replaced early or 

before the end of its useful life. 

Use minimum efficiency level required by building 

or appliance code to estimate savings

For situations where the cooling system is being 

installed because equipment is failing or burned

out or as part of a new construction project

B. Determining Equivalent Full Load Hours for Cooling System Use

M&V Approach Typical Application

Simulate hours of HVAC system use using building 

simulation models based on prototypes of typical 

homes and climate conditions

Situations where size, climate conditions and 

layout of homes is known with reasonably 

accuracy based on current or previous data 

collection

Conduct short-term metering of system use during 

cooling season for a short period of time, at least one 

month, during typical occupancy conditions), 

Situations where accurate estimates of impacts 

on peak use are needed and there is sufficient 

evaluation budget to support the metering. 

Use deemed hours of cooling use from neighboring 

state, or regional TRMs 

Situations where programs are just starting out 

and or it is not practical to measure or meter 

system hours of use

C.4.3. Relevant Protocols and Sources for readers interested in more detailed information

1. Uniform Methods Project, Chapter 4:Small Commercial and Residential Unitary and Split Cooling 

Systems protocol (April 2014)

2. ASHRAE. (2010). Performance Measurement Protocols for Commercial Buildings. 

3. Consortium for Energy Efficiency (CEE). (2009). Commercial Unitary AC and HP Specifications, 

Unitary Air Conditioning Specification. Effective January 16, 2009. 

www.cee1.org/com/hecac/hecactiers.pdf. ISO-New England, Inc. (June 2010). 

4. ISO New England Manual for Measurement and Verification of Demand Reduction Value from 

Demand Resources Manual (M-MVDR).

5. KEMA. (February 10, 2010). Evaluation Measurement and Verification of the California Public 

Utilities Commission HVAC High Impact Measures and Specialized Commercial Contract Group 
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Programs 2006-2008 Program Year. 

www.calmac.org/publications/Vol_1_HVAC_Spec_Comm_Report_02-10-10.pdf.

C.5. Residential Whole Building Retrofits

C.5.1. Definition 

These projects involve installing multiple EE measures, such as insulation, weather stripping, set-back 

thermostats, efficient lighting and/or efficient heating and cooling systems in residential dwellings. The 

savings from individual measures usually interact with each other, so it is not appropriate to estimate 

the savings from individual measures and sum them.

This guidance is applicable to common program-design approaches such as Home Performance with 

Energy Star (HPwES), residential audit programs, and any other program that seeks to reduce overall 

energy use in residential dwellings using measures that address both building shell and building system 

improvements.

C.5.2. Key Measurement Challenges

The key challenge in estimating energy savings from this program type is to isolate the electricity savings 

from the installation of multiple measures in the participating houses from market, weather, economic 

and other factors that affect household electricity consumption. Three different evaluation methods to 

deal with this challenge and their typical applications are described in the tables below. 

M&V Approach Typical Application

Randomized Control Trials applied to a sample of 

participants and non-participants in the program72

Programs or projects where customers can be 

randomly assigned the opportunity to 

participate in the program and do not have to 

be recruited.

Quasi Experimental Design to Select Participant and 

Comparison Groups and control for self-selection bias 

using regression and pooled techniques.73 Two 

approaches include:

1. Two-stage74 regression approach using past and 

future participants as the comparison or control 

group

2. Pooled fixed effects regression approach if 

there is insufficient data on past or future 

participants to create the comparison group

Most common program situation where 

customers must be recruited to join programs 

and install measures, billing data is available 

and evaluation budget is sufficient to gather 

detailed data on home characteristics. 

 

72 State and Local Energy Efficiency Action Network. 2012. Evaluation, Measurement, and Verification (EM&V) of 

Residential Behavior-Based Energy Efficiency Programs: Issues and Recommendations. Prepared by A. Todd, E. 

Stuart, S. Schiller, and C. Goldman, Lawrence Berkeley National Laboratory. http://www.behavioranalytics.lbl.gov. 

73 Uniform Methods Project, Chapter 8: Whole-Building Retrofit with Consumption ( Data Analysis Evaluation 

Protocol (Prepared by Mimi Rosenberg and Ken Agnew for the National Renewable Energy Laboratory NREL, April 

2013) http://www.energy.gov/sites/prod/files/2013/11/f5/53827-8.pdf

74 Two stages in this regression approach refers to the first stage of the regression analysis where changes in usage 
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M&V Approach Typical Application

Building simulation models to estimate savings using 

Building Characteristic Data Gathered by Program 

contractors or implementers 

Situations where it is difficult to access 

sufficient billing data and or administrator has 

confidence in implementer’s building 

simulation models because it has been 

calibrated to billing energy usage. 

C.5.3. Relevant Protocols for More Information

See Uniform Methods Project, Chapter 8: Whole-Building Retrofit with Consumption Data Analysis 

Evaluation Protocol reference. http://www.energy.gov/sites/prod/files/2013/11/f5/53827-8.pdf

C.6. Commercial Lighting

C.6.1. Definition 

These projects involve installing efficient lighting products (ballasts, lamps, and fixtures) in 

nonresidential buildings such as offices, grocery stores, restaurants, warehouses, retail, and multifamily 

housing units. Example projects include installing T5/T8 fluorescent lighting systems for general area 

lighting and more focused LEDs for task lighting. There are three common program delivery approaches:

• Direct installation of lighting products, including ESCO projects

• Consumer incentives (e.g., rebates)

• Upstream/Mid-stream/Downstream buy downs of lamp and fixture prices (e.g., distributor 

incentives).

C.6.2. Key Measurement Challenges

Key measurement challenges include: 1) Ensuring lighting logger readings are carefully reviewed and 

screened to ensure accurate estimates of hours of use in rooms where daylighting and occupancy 

fluctuations can cause flicker problems. 2) Accurately weighting these use area specific HOU results into 

an average hours of use for the entire building 3) Determining baseline wattage of lighting systems 

where the precise physical location is unknown and inventories of lighting systems that do not meet 

current code are still available for sale.

The most common evaluation methods for dealing with each challenge are discussed below:

A. Determining Average HOU by Room Type and Whole Building

M&V Approach Typical Application

Collect average hours of usage by area use type75

from a representative sample of buildings using selfProject or program evaluations of new lighting projects or measures where there is insufficient 

 

or savings are estimated using past or previous participating customers and then in a second stage of analysis 

where changes in usage are estimated for the current participant sample. Savings are estimated using a difference 

of differences approach across the entire group. Use of past or future participants as a comparison group helps 

avoid biases in savings estimates introduced by customer self-selection into the program. 

75Examples of area use types include conference room, offices, halls, bathrooms, storage rooms, or retail display.
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reports from building managers and or HOU 

estimates from forecasting models.

time or resources to install lighting loggers and 

collect usage data over a 6 to 12 week period. 

Retrieve hours of lighting system or fixture usage by 

room type from building energy management 

systems or time clocks

Evaluations at sites where sophisticated energy 

management systems log lighting usage and 

schedules. 

Install lighting loggers in a representative sample of 

area use types within a sample of participating 

buildings. 

Evaluations where savings from lighting 

projects constitute the majority of portfolio 

savings and no recent studies of lighting HOU 

have been conducted in available TRMS or 

recent evaluations

B. Determining Baseline Lighting System Wattage

M&V Approach Typical Application

Collect detailed fixture wattage inventory by area 

usage type before the lighting retrofits are installed.

For accelerated or early retirement of existing 

lighting systems before the projected or 

anticipated end of their useful lives from 

building manager’s perspective. 

Determine the CPB conditions using most recent 

state or federal product standards for equivalent 

lumens or trade ally input if market baseline is more 

efficient than standards. Potentially make 

adjustments for non-qualifying equipment that is still 

available in distributor warehouses.

For new construction, normal replacement, or 

replace on burnout projects where the baseline 

replacement system is most likely to be a 

lighting system that just meets minimum 

efficiency requirements

Install lighting loggers in a representative sample of 

room usage types within a sample of participating 

buildings. Develop a lighting logger quality-control 

protocol to ensure HOU estimates are accurate.

Evaluations where savings from lighting 

projects constitute the majority of portfolio 

savings and no recent studies of lighting HOU 

have been conducted in available TRMS or 

recent evaluations

C.6.3. Relevant Protocols for readers interested in more detailed information

1. Uniform Methods Project, Chapter 2: Commercial and Industrial Lighting Evaluation Protocol (April 

2013) 

2. California Public Utilities Commission (CPUC). (2008). http://www.deeresources.com. 

3. Federal Energy Management Program (FEMP). (2008). M&V Guidelines: Measurement and 

Verification for Federal Energy Projects Version 3.0. 

http://www1.eere.energy.gov/femp/pdfs/mv_guidelines.pdf

4. Massachusetts Program Administrators. (October 2011). Massachusetts Technical Reference Manual 

for Estimating Savings from Energy Efficiency Measures 2012 Program Year–Plan Version. 

www.masssave.com.
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C.7. Commercial Chiller Systems

C.7.1. Definition

These projects involve installing or retrofitting electricity consuming chillers and/or associated auxiliary 

equipment. Chillers provide mechanical cooling for commercial, institutional, multiunit residential, and 

industrial facilities. Cooling may be required for facility heating, ventilation, and air conditioning (HVAC) 

systems or for process cooling loads (e.g., data centers, manufacturing process cooling). 

C.7.2. Key Challenges in Quantifying Energy Savings

Key measurement challenges include: (1) Determining annual electricity consumption of the existing 

chiller system, (2) Determining the length of the appropriate monitoring periods for collection of system 

data, and (3) Normalizing savings to performance period independent variables such as weather and 

changes in occupancy.

Baseline Energy Consumption

Methods for determining baseline electricity consumption of Chiller Systems are outlined in the table 

below.

M&V Approach Typical Application

IPMVP Option A – Retrofit Isolation

Key parameter measurements include cooling load, 

outside air temperature and part-load efficiency 

factors from manufacturer testing

Project level evaluation where expected 

variation in occupancy and chiller loads is likely 

to be relatively low over a typical year

IPMVP Option C – Whole Building Billing Analysis 

Pre and post installation over at least a year period

For early replacement projects where 

estimated costs of metering are high and the 

estimated savings are large compared to 

normal variations in total building energy usage

IPMVP Option D – Calibrated Building Simulation

Modeling with potential adjustments for impact of 

new product standards and or changes in occupancy

For replace on burnout or new construction 

projects where baseline condition is likely to be 

chiller system that meets the minimum 

efficiency standards

All of the methods above require the evaluator to collect data on the condition of the existing 

equipment (with the exception of new construction) and make an estimate of the remaining useful life 

of the equipment for use in developing savings estimates using the dual baseline approach. To support 

use of existing usage conditions for early replacement projects evaluators must present evidence that 

the program has likely induced an early replacement of the existing chiller equipment. Data sources for 

condition and remaining useful life of in-situ equipment/systems include interviews with facility 

managers, equipment logs, inspection of equipment, and manufacturer’s data. 

Determining the Length of the Monitoring Period 

The frequency and length of the monitoring period (for electricity consumption, cooling loads, etc.) 

associated with chiller equipment depends on the type of load and frequency of equipment operation. 

Continuous monitoring for large systems with variable loads (such as chillers service process loads) is 
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recommended for at least three months, while spot measurements of electricity consumption can be 

sufficient for systems with constant loads and known hours of operation. 

Normalizing Savings to Account for Independent Variables 

In many cases, it will be necessary to run regression equations to separate out the impacts of chiller 

measures from independent variables such as operating temperatures or process throughput. The 

model’s predictive power should be tested using R2values or T statistics on the estimated coefficient for 

the independent variable of interest to ensure accuracy. The Commercial Chiller protocol76 from the 

Uniform Methods Project recommends a model fit thresholds of >0.75 for R2 and T statistics of greater 

than 2.0 to determine if savings estimates are statistically significant.

C.7.3. Relevant Protocols and Evaluation Sources for More Information

1. Uniform Methods Project, Chapter 14: Chiller Evaluation Protocol, Chapter reference (Prepared by 

Alex Tiessen, Posterity Group for the National Renewable Energy Laboratory, September 2014). 

Reference http://www.energy.gov/sites/prod/files/2014/10/f18/Chapter%2014--

Chiller%20Evaluation%20Protocol.pdf

2. EVO. (January 2012). International Performance Measurement and Verification Protocol –Concepts 

and Options for Determining Energy and Water Savings Volume 1. Efficiency Valuation Organization.

3. Fagan, F., Bradley, K., Lutz, A. (2011). Strategies for Improving the Accuracy of Industrial Program 

Savings Estimates and Increasing Overall Program Influence. Prepared for the International Energy 

Program Evaluation Conference.

4. Ridge, R., Jacobs, P., Tress, H., Hall, N., Evans, B. (2011). One Solution to Capturing the Benefits of 

Early Replacement: When Approximately Correct is Good Enough. Prepared for the International 

Energy Program Evaluation Conference.

5. US DOE FEMP. (April 2008). M&V Guidelines: Measurement and Verification for Federal Energy 

Projects—Version 3.0. U.S. Department of Energy Federal Energy Management

 

76 Table 6 page 13 in the Chiller Evaluation protocol at: 

http://energy.gov/sites/prod/files/2014/10/f18/Chapter%2014--Chiller%20Evaluation%20Protocol.pdf