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## Evaluation Measurement and Verification (EM&V) Guidance

**f or**  **Demand -** **Side Energy**  **Efficiency (EE)**  **U.S. Environmental Protection Agency**

**DRAFT FOR PUBLIC INPUT**  **August 3** **, 2015***** Draft for Public Input ****** Draft for Public Input ***

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## Contents **P ublic 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**  **................................ ................................**  **................. 10**  2.2.1. Discussion ................................ ................................ ................................ ................................ . 10 2.2.2. Applicable Guidance ................................ ................................ ................................ ................. 11 **2. 3 Reporting Timeframes and Considerations**  **................................ ................................**  **.............. 13**  2.3.1. Discussion ................................ ................................ ................................ ................................ . 13 2.3.2. Applicable Guidance ................................ ................................ ................................ ................. 13 **2.4 Deemed Savings**  **................................ ................................**  **................................ .....................**  **14** 2.4.1. Dis cussion ................................ ................................ ................................ ................................ . 14 2.4.2. Applicable Guidance ................................ ................................ ................................ ................. 15 **2.5 Independent Factors Affecting Energy Consumption and Savings ................................**  **............. 16**  2.5.1. Discussion ................................ ................................ ................................ ................................ . 16 2.5.2. App licable Guidance ................................ ................................ ................................ ................. 16 **2.6 Accuracy and Reliability of Quantified Savings ................................**  **................................ .........**  **17** 2.6.1. Discussion ................................ ................................ ................................ ................................ . 17 2.6.2. App licable Guidance ................................ ................................ ................................ ................. 18 **2.7 Avoiding Double Counting ................................**  **................................ ................................**  **....... 19**  2.7.1. Discussion ................................ ................................ ................................ ................................ . 19 2.7.2. Applicable Guidance ................................ ................................ ................................ ................. 20 **2. 8 Effective Useful Life and Persistence of Savings**  **................................ ................................**  **....... 20**  2.8.1. Discussion ................................ ................................ ................................ ................................ . 20 2.8.2. Applicable Guidance ................................ ................................ ................................ ................. 21 **2.9 Savings Quantification and Verification Cycles ................................**  **................................ .........**  **23** 2.9.1. Discussion ................................ ................................ ................................ ................................ . 23 2.9.2. Applicable Guidance ................................ ................................ ................................ ................. 23 **2.10 Transmission and Distribution (T&D) Savings Adders ................................**  **............................. 24**  2.10.1. Discussion ................................ ................................ ................................ ............................... 24 2.10.2. Applicable Guidance ................................ ................................ ................................ ............... 24 **2.11 Interactive Effects ................................**  **................................ ................................**  **................. 24**  2.11.1. Discussion ................................ ................................ ................................ ............................... 24*** Draft for Public Input ***

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2.11.2. Ap plicable Guidance ................................ ................................ ................................ ............... 25 **2.12 Use of EE EM&V Protocols and Guidelines ................................**  **................................ .............**  **25** 2.12.1. Discussion ................................ ................................ ................................ ............................... 25 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. App licable 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. App licable Guidance – State and Local Government Incremental Product Energy Standards ................................ ................................ ................................ ................................ .. 40 **Appendix A. Optional EM&V Plan Template for Demand**  **- Side EE**  **................................ .....................**  **A -**  **1 Appendix B. Glossary of Terms**  **................................ ................................**  **................................ .......**  **B -**  **1 Appendix C.**  **EM&V Methods for Common EE Technologies: Best Practices and Resources**  **............... C** **- 1** *** Draft for Public Input ***

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## P **ublic 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 m** **ode l**  **r ule must be submitted in the regulatory**  **docket for that action. Such comments should not be submitted to the email address below** . Important information for commenters includes:

• The draft guidance can be accessed at : http://www2.epa.gov/cleanpowerplanto olbox • The public will have 90 days following the publication of the proposed model 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 considere d 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 draft guidance, the agency has particular interest i n 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 q uantify ing savings from specific EE programs, projects, and measures?

- D oes 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, conside ring 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 fol low ? Is each of these sections and appendices helpful , clearly presented, and sufficient/complete ? What specific*** Draft for Public Input ***

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

- Does the guidance not cover any importa nt 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 meas ures that are directly metered? What topics, if any, a re 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)?*** Draft for Public Input ***

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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 - Build ing Energy Code and Product Energy Standard CPP – Clean Power P lan 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 Conservati on 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 distrib ution (system) UMP – (United States Department of Energy) Uniform Method s Project WHP - Waste heat to power (electricity generation systems)*** Draft for Public Input ***

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## 1. **Introduction** The Clean Power Plan (CPP) supports the use of demand - side energy efficiency (EE) as a proven, cost effective, and widely available emission reduction measure 1 for the power sector. States, private organizations and firms, and other entities around the country have already made substantial investments in EE progra ms 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 rule in Section IV.D.8. States may also submit other means of meeting the EM&V requirements so lon g 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 verificati on (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 rule. Contents include background information and EM&V terms, best practices for selecti ng and applying quantification protocols and methods, procedures for determining appropriate baselines, and other key EM&V topics. The guidance is not a regulatory document, and reading this document does not substitute for a thorough review of the applica ble regulatory requirements and provisions. The scope of the guidance is limited to EM&V for demand - side EE. For renewable energy and other zero and low- emitting measures that generate electricity, all applicable requirements for quantification and verifi cation are provided in the emission guidelines and proposed model 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 CO 2 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, 2 efforts to quantify and verify the MWh savings of these actions h ave 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 practice s for a broad range o f

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, “mea sure” refers to an install ation or modification of equipment or system s 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.*** Draft for Public Input ***

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EE program strategies and delivery mechanisms across sectors . 3 Today, the se EM&V practices are applied by utilitie s, 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 m any large firms and hundreds of in dividual practitioners, and is supported by training and certification programs, as we ll as a rich library of published reports and publicly available data and technical resources . The EM&V approaches in wide use today – including budget level s, oversight procedures, and preferred methods – are derived from PUC4 requirements for c onsumer-fu nded 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 , th ese 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 th is evolution in the accuracy and reliability of EM&V, many states and u tilities now routinely rely on EE to achieve energy (MWh) and capacity (MW ) goals. In addition, two Inde pendent System Operators (ISOs) – ISO New England (ISO - NE) and PJM – have established forward capacity markets (FCMs) 5 that 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, t here 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 bough t and sold by a regulated source. Environmental regulators, including the U.S. EPA and most state environmental agencies, have limited experience quantifying and verif ying EE in this regulatory context. As a result, the EPA’s final emission guidelines incl ude 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 Baseline**  **s** 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 a nalytic approaches used to quantify the MWh from demand - side EE and other eligible resources, and t hereby ensure that the resulting savings and generation are quantifiable and verifiable. 4 T hese government entities are also referred to as a public servic e commission or a board of public utilities. 5 F orward capacity markets are intended to ensure sufficient electric generating capacity is available to meet future peak electricity demand.*** Draft for Public Input ***

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prior to EE implementatio n on the basis of policy objectives and various program matic considerations. MWh savings are the n 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**  **- 1**  **. Energy Use Before, During, and After an E**  **E Project is Installed**  **6** 

### 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) 7 that outlined a general approach to establishing EM&V requirements and guidance. The TSD proposed that the EPA’s EM&V provisions c ould 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 s ignificant EM&V infrastructure in place, and some have been applying, refining, and enhancing their approaches for over 30 years. Most public comment s on this topic affirmed that the protocols and procedures already in place and widely use d 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 p ointing out needed improvements to EM&V practices, especially relating to cross -jurisdiction al inconsistencies in the way EM&V is applied). Additional perspectives shared in comments include the importance of

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 .*** Draft for Public Input ***

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striking a reasonable balance between EM&V rigo r 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 cri tical 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 q uantify ing and verify ing 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 deno minator 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, i nternet 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. Such programs also serve other public policy objectives and produce co - ben efits 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 bundle d services. For all these reasons, energy savings is only on e metric by which such programs are measured. T he 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 evaluat e performance. While these additional considerations affect the decision criteria for **What is Not**  **Covered** T his 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. • Prov ide criteria for projecting the impacts of such measures. • Offer information or resources about calculating displaced CO 2 emissions from EE. • Address the accounting procedures for how a quantified and verified MWh can be used to adjust a rate, or for how c ross jurisdictional 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 rule.*** Draft for Public Input ***

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This EM&V guidance does not apply to states electing to submit mass - based plan s in which compliance is based on monitored emissions at the affected source 10 . 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 b e 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 a pplies 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. Th is glossary is intended to be consistent with industry- standard proto cols 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 qual ification package used to generate ERCs from eligible resources. • **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 , w ith information about the applicable analytic steps and best practices .

determining cost - effectiveness of these programs, th e methods for verifying their electricity savings are the same as those used for evaluating EE for non - low income cons umers . 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.*** Draft for Public Input ***

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While this draft EM&V guidance is not an EM&V primer, i t provide s 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 W eb portal 12 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 execut e 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 understand ing t he EPA’s EM&V requirements for purposes of participating in state plan development and similar process es . 

### 1.7 **Evolving EM&V Practices and Guidance Updates**  The EPA recognizes that the best - practice EM&V appro aches, 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 guidan ce continue s to be relevant and helpful over time, the EPA intends to periodically provide update s 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 an aggregate verification approach that demonstrates how states could continue to make strate gic EM&V invest ments 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 ou tside 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 wi ll be issuing further guidance*** Draft for Public Input ***

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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 previousl y described, t he 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 balance s the need for rigor and accu racy 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 practice s. This means that the guidance either (1 ) is consistent with established pro toc ols 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 . Th e best practice s recommended here generally fall s into the first category. This section of the guidance is supplemented with additional best practice s 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 b ackground information, and applicability to the EPA’s emissions guidelines . • **Applicable Guidance :**  This information is intended to help state s, EE providers , and private firms hired to quantify and verify EE savings implement the regulatory requirements defi ned 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 industry standard 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 impleme nted 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 .*** Draft for Public Input ***

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3. Reporting timeframes and considerations 4. Deemed savings 5. Independent factors affecting energy consumption and savings 6. Accuracy and reliability of q uantified s avings 7. Avoiding double counting 8. Effective useful life and persistence of savings 9. Savings quantification and verification cycles 10. Transmission and d istribution (T&D) s a vings a dders 11. I nteractive effects 12. Use of EE EM&V Protocols and Guideline s The presumptively approvable approaches for each of these topics are described in Section IV.D.8 of the proposed model rule . 

### 2.1 **EM&V Methods**  **2.1.1. Discussion**  Three general categories of EM&V methods for q uantifying 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 activ ity, 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 . 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 **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.

**Key Terms (**  **continued )**   **Project -** **based m easurement 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 diffe rence s in electricity consumption patterns between a comparison group the program participants. Comparison group approaches include randomized control trials (RCTs) and quasi experimental 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.*** Draft for Public Input ***

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using ( 1 ) aggregate (e.g., utili ty 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 portfolio s of programs. Some states have adopted this approach as a complement to the above - listed 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 e ffectiveness 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 for examples of how different methods can apply to different type s 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 are recommended for larg er, more variable, and more complex components of savings,

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

- 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 an d magnitude 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 protocol s and guidelines. Examples include:

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

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

- American Society of Heating, Refrigeration , and Air- Conditioning Engineers (ASHRAE) protocols and guidelines 17, and

- U.S. DOE, The Uniform Methods Project (UMP): Methods for Determining Energy Efficiency 18 • 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 example s of how these methods can be applied in practice.

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)*** Draft for Public Input ***

10 **Key Term**  **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 cont inued with or installed at the time of project implementation.  Refer to Table 2 - 1 to determine which m ethods are appropriate for use with broad categories of EE activities. **Table 2**  **- 1**  **. EM&V**  **Methods Applicable to Broad Categories of EE**  **Activities EE**  **Conditions Comparison Group**  **PB -**  **MV Deemed**  Individual p roject Method not applicable OK OK Large n umbers of relatively homogeneous participants (e . g., residential, small commercial) Method requires this condition OK OK 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



### 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 typi cally defined by the installed equipment at the time of retrofit, or some*** Draft for Public Input ***

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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 a nd 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. 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 defi ned 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 ran domized control trials) or the compa ri son 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 represent s what the participants would have done absent the program or absent the EE intervention.

- With comparison group specification s, describe how the comparison group was selected an d what it is intended to represent. • For the three EM&V methods addressed in Section 2 .1, use the following CPB guid ance :

- For equipment that is **replaced on failure**, define the CPB as:  The federa l 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 state s) that have product standard s 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 E E at higher efficiency than the state product standard. (See double counting S ection 2.7 )

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 spil lover and long-term market effects.*** Draft for Public Input ***

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- For **early replacement activities**, with strong evidence that replacement of functioning equipment is due to program influence, a dual baseline is applicable :  Use exi sting conditions for defining the CPB for the remaining useful lifetime 21 (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 im provements of existing buildings** , define the CPB as :  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 :  For commercial buildings, the approach that yields fewer MWh savings of the applicable state or local building code in effect as of January 1, 2013, the market industry average practice in the state, or ASHRAE 90.1 - 200 7/2009 IECC. This baseline recognizes the dynamic nature of baselines in the context of changing market conditions. 22

 For residential buildings, the approach that yields fewer MWh savings of the applicable state or local building code in effect as of January 1, 2013, the market industry average practice in the state , or ECC 2009. This baseline recognizes the dynamic nature of baselines in the context of changing market conditions.  For states (or EE providers in those state s) 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 se parately. (See double counting discussion in S ection 2.7 ) Table 7.1 of the 2012 SEE Action Impact Guide can be refer red 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, ESC O supported projects, and privately funded projects outside of cons umer-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 sam e 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 baselines, and other particulars descri bed here such as verification methods, EUL determination, and

21 Remaining useful life cannot exceed the effective useful life of the replacement measure. 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, subst antial, 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, In c., www.seeaction.energy.gov . (O r current version .)*** Draft for Public Input ***

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frequency of updates of deemed values or other key parameters. Use of market average baselines where standards do n o t exist is not currently common practice for consumer-funded programs . This d efinition 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 circumstance s 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 stri ngent 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 En ergy Saving: Methods and Practices . 

### 2.3 **Reporting Timeframes and Considerations 2.3.1.**  **Discussion** Current industry practice s for reporting a nnual electricity savings var ies across states and EE providers with regard to specific content requirements, definitions, and timing. Local policy objectives, the brea d th 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 requireme nts 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 861 24 . **2.3.2. Applicable Guidance**  • W hen 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.

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 a s 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 ***

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- For emission standard plans in which EE generate s ERCs, annual savings can be quantified for any consecutive 12 - month period.

- For state measures plans, report s avings as if the y 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 c urrent 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 ba sis.

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



### 2.4 **Deemed Savings 2.4.1.**  **Dis cussion**  As described in S ection 2 .1 above, o ne of the three categories of EM&V method s 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 ave rage. Because the se stipulated values are agreed upon in advance , deemed savings can help alleviate some of the guesswork in program planning and design. D eemed savings can also result in a form of r is k, in 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 v erification

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 M Wh 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, sa vings 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 veri fication 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 ***

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activities commonly required by state PUCs and other oversight and management bodies can alleviate this risk 26 . For more complex efficiency projects or for projects with significant savings variability, measurement based 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 cycle 27 . Deemed savings val ues 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 publicatio n, approximately 20 TRMs are in use across the United States at the state and regional level. 29 TRM s 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 encourage d and can support higher - quality savings values for compliance with the EPA’s emissions guidelines and reduced E M&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 b een 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 ***

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• 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 d elivery 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 d eemed 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 c hanges 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 t he influence o f these factors is critical to the credibility of savings estimates, and distinguish es properly determined savings from a simp l e and unreliable comparison of electricity use before and after implementation of a program , project, or measure. Each of the thr ee 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 fa ctors 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 on the basis of independent factors , 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 ***

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- Actual , normalized conditions that exist over the period when EE savings occur.  With this approach , adjust baseline electricity- consumption data to reflect actual independent factors observed via real -time savings quantifi cation.

- 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 fa ctors, 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 l ighting efficiency project, or o Typical prod uct production rates for an industrial efficiency project. • Where fi rst -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 th is 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 r igor 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 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 f rom 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. R andom error s include an observed change in energy use due to un accounted -for factors that affect **Key Terms**   **Accuracy:** A concept that refers to how close and estimate or measured value is like l y 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 th at 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 b oth 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 ***

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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 Gu**  **idance** • 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 s ampling is used for quant ifying savings values, ensure that a ctual observed confidence/precision values are applied ( versus ex- ante estimate s 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 project s and installed measures .

- A program - level estimate of savings or of key parameters used to calculated savings (e.g. lighting operat ing 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 rep orted. Applicable g uidance 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 a pplicable 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 Resource s . 33

- T he California Evaluation Protocols .

- Uniform Methods Project Sample Design Cross- Cutting Protocol (Chapter 11). • For deemed savings :

- Quantify random errors if applicable

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 33 Current version is manual M - MVDR, revision 6, dated June 1, 2014*** Draft for Public Input ***

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- I nclude 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 th e same or consistent EM&V approaches to ensure the savings values are determined with comparable levels of accuracy and reliability. 

### 2.7 **Avoid ing**  **Double Counting 2.7.1.**  **Discussion** Double counting occurs when the MWh savings from a single EE program, project, or meas ure 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 CO 2 emissions . Tracking, account ing, 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:

- S ome or all savings from the same retrofit being claimed by a residential behavior- based program and a retailer point - of- sale incentive program . 34 S avings from a single ret rofit 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 a n LED l amp 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 . • Inconsistent baselines across a portfolio of programs, for example:

- A state claiming (1) in one program sa vings 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 .

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 ***

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- 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 act ions (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 program s, t rack 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 duplica te 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 th e 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 behavior al 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 me thod 35 . 

### 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 35 See: https://www4.eere.energy.gov/seeaction/publication/evaluation - measurement- a nd -verification - emvresidential - behavior- based - energy- efficiency **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 prog ram are still in place and operable.*** Draft for Public Input ***

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which the EE is in place. The typical pract ice 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 common ly 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 publi cally 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 :

- R eport 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 verification s to determine the actual (versus deemed) EUL values for measu re 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 persist s .

- A pply 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 ) .

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, Lawre nce 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.*** Draft for Public Input ***

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• I f 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).*** Draft for Public Input ***

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### 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) verify ing 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 involve s confirming that the replaced lamps are 100 watts, that the new ones are 13 watts, an d that the lamps are installed and working. Verification confirms that the measure has the potential to save electricity, with the sav ings depend ing 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 **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 v erification 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 the se installation s 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 revi ewing and confirming commissioning documentation .

- For **EE point -** **of -** **sale rebate** or **distribut o**  **r incentive programs** , verification can include confirming the sales data used for determining electricity savings and verification with a sample of end users. • Use E M&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 savin gs per verified unit . This value can then be applied to the verified units.

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 ***

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- 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 w as 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 a n 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 gro up remains appropriate and valid . **2.10** 

### T **rans mission 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 E very unit of electricity consumption avoided at an end - use site also avoid s 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. **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 dir ect 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 Volt age/VAR optimization and conservation voltage re gulation (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

39 T he national average loss from 1990 to 2012 is six percent. See: http://www.eia.gov/tools/faqs/faq.cfm?id=105&t=3 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. **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 ***

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directly affected by the subject measures . For example :  I nstall ing 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 t he U.S. DOE’s Uniform Methods Project (UMP) 41 or other applicable protocols and methods to e stimat e 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 t hat these cross -fuel effects have implications for overall greenhouse gas (GHG) emissions. Evaluatin g such effects is a best practice in many state s. 

### 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 Guidelines** **42 Protocol/Guideline**  **Sponsor Website**  **Summary**

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

26 **Protocol/Guideline Sponsor**  **Website Summary**  **Uniform Methods Project (UMP) U.S. Department of Energy**  **(DOE )**  http://www.energy.gov/eere/about us/ump - protocols Provides 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 non energy benefits resulting from fa cility (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/EEREmanua l.pdf Provides guidance for incorporating EE and renewable energy policies and programs into State and tribal implementation plans. **NEEP Regional -** **Common EM&V Methods and Savings Assumptions**  **Guidelines Northeast Energy Efficiency**  **Partnership** http://www.neep.org/regional - emvmethods - and - savings - assumptions guidelines - 2010 Provides 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%5FAdop tedviaRuling%5F06%2D19%2D2006% 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%5FFramewo rk%5FJune%5F2004%2Epdf Provides a consistent, system at ized, 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 M&V plans for their projects.*** Draft for Public Input ***

27 **Protocol/Guideline Sponsor**  **Website Summary**  **FEMP M&V Guidelines U.S. DOE Federal Energy**  **Management Program** http://www.mnv.lbl.gov/keyMnVDocs 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 efficien cy. **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 M&V Guidelines and the IPMVP, Guideline 14 is technically more detailed and addresses the analyses, st atistics, 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. **ISO -**  **NE Measurement and Verification of Demand Reduction**  **Value from Demand Resources –**  **Manual M -**  **MVDR Independent System Operator**  **– New England**  http://www.iso ne.com/participate/rules procedures/manuals Provides 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&rc t=j&q=&esrc=s&source=web&cd=1&v ed=0CB8QFjAA&url=https%3A%2F%2 Fwww.pjm.com%2F~%2Fmedia%2Fdo cuments%2Fmanuals%2Fm18b.ashx& ei=m9xHVceiEMvJtQXviYDoDw&usg= AFQjCNEQb0Z65Y_2ESjjdAP10sPjZb94 Mw&sig2=Ydqec ugs2PPnuJTwxmtPIw &bvm=bv.92291466,d.b2w 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:*** Draft for Public Input ***

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• 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. • G uid elines 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 d esired 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 protocol s or guideline s, 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 wit h flexibility with regards to a number of savings calculation assumptions*** Draft for Public Input ***

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## 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 t h ese 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 as sumptions 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 a nd 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 no t inten ding 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 th e proposed model rule, provided that it meet s the presumptively approvable provisions for eligi bility described in section IV.C.3 of th e model 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 Descr iption**  D emand - 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 ***

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administered by various entities, including investor- owned utilities (IOU) , public utilities, state energy offices (SEO), and non - profit entities sanctioned by state legislators a nd public utility commissions. Examples of demand - side EE programs range from marketing, education, and outreach to the d irect installation of efficient appliances in low - income households and complex industrial upgrades. In 2013, utility EE programs alone were reported to have gross incremental 45 electricity savings of approximately 24,000 GWh 46 with an estimated 16 million m etric tons of avoided CO 2 . 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 light ing 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 amou nt 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,

- Workforc e education and training programs,

- Fin ancing programs, 47 and

- En ergy audit programs. Note that both direct and indirect p rograms can be specifically directed to ward low- income households and disadvantaged communities. S pecific 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 approa ches and assumptions provided herein.*** Draft for Public Input ***

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**3.1.2. Applicable Guidance**  **– Direct Ac** **tion EE Programs**  The following EM&V guidance reflects industry best practices and technical assumptions, and is intended to assist EE providers as they implement d irect a ction 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** – CPB s 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 s avings are calculated consistently, each project in a single program sh ould 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 i n terms of statistical precision, and systematic bias, addressed via discussion of potential sources of bias and their likely effects. • **Evaluation cycles** – Section 2 .9 describes the requirements, including frequency, for verification to confirm measures we re installed and are operating to produce savings, and for quantification of savings, and for their combination via comparison group methods.. • **Avoiding of double counting**  **–** Procedures to avoid double counting are described in Section 2 .7. **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 considere d 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. Th e 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 regress ion 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, b ut 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 M&V 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 ***

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• **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 a ddress both random error, quantified in terms of statistical precision, and systematic bias, addressed via discussion of potential sources of bias and their likely effects. • **Evaluation cycles** – Section 2 .9 describes the requirements, including frequency, fo r 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 foll owing 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 co nfirming 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 contro l group members. • **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 M&V methods, a value for the EUL of program savings should be quantified for that period. • **Avoid ing**  **double counting –**  Applicable p rocedures for avoid ing 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 bot h simultaneously in the same year. 

### 3.2 **Project -**  **B ased Energy Efficiency**  **3.2.1. Description**  Project - based EE involve s implementation of one or more EE projects, retrofit or new construction, by private firms (includ ing 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 individua l office or apartment buildings, and retrofits at industrial facilities; many projects are completed for the municipal, schools and hospitals*** Draft for Public Input ***

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(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 d istinguish in g 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 quantif y 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 hav e 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 countin g 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 recommende d methods are M&V and deemed savings, as described Section 2 .4. In practice, M&V is often used in combination with deemed savings approaches. 51 I n 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, CPB s are the regulatory requirement for quantifying savings. These baselines should be defined consistently across a portfolio of individual projects. Alth ough 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. For private EE contracts with co nsumers such as ESCO contracts, the baselines for savings calculation may be set according to the needs and preference of the customer. However, for state s reporting savings to EPA, savings from these projects must be calculated using CPBs as defined in

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 ap proach 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 applicatio n 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 ***

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Se ction 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 bas eline for calculating savings for such contracts is the existing equipment. As indicated in Section 2 .2, the CPB for calculating savings correspo nds 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 savin gs 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 subs tituted 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 prio r equipment as follows: Sa vings|CPB = Savings|Existing x (1/EFF CPB - 1/EFF NEW )/ (1/EFF EX - 1/EFF NEW ) where Savings|CPB = Savings relative to the CPB Savings|Existing = Savings relative to the existing equipment EFF CPB = efficiency of the CPB equipment EFF NEW = efficiency of the new equipment EFF EX = = efficiency of the existing equipment. **Industry -** **Standard P**  **rotocols 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.  AS HRAE – 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- deter mining energy- 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 l ist of protocols that can be applied, with appropriate explanation in EM&V plans and reports.*** Draft for Public Input ***

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Alternative methods to calculate savings relative to the CPB may also be used. • **Independent factors**  . With PB - MV methods, the savings typically should be based on actual co nditions. In contrast, n ormalized or typical conditions over the measure’s life should be the basis for calculating deemed savings values. C aution 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 reliabi**  **lity 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 p articularly important to indicate the source s 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 determin e savings, the confidence and precision of the sample’s metric (e.g. , lig hting 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. • **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. • **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 ba sed 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 sh ould be used to adjust annual savings . • **Avoid ing**  **double counting .**  Procedures to avoid double counting are described in Section 2 .7.3 . Particular caution should be used to avoid double counting i f 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.*** Draft for Public Input ***

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### 3.3 **Building Energy Codes 3.3.1.**  **Description** Local b uilding energy codes are enforceable EE requirements that apply to the design and construction of buildings in many jurisdictions . 52 According 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 b uilding energy code actions that state s 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 impac ts are completed regularly as codes are developed and adopted. In contrast, e x- 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 ha s been completed in six state s (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 st ructures. 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 ch oose the materials and equipment that will meet this target. State - level policies on building energy codes vary widely across the 50 State s, the District of Columbia, and the five U.S. territories, and sometimes even within State s, e.g. home rule State s. Two foundational model building energy codes may be adopted by State s 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 stori es 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 Futu res Group NMR Group, Inc. Optimal Energy*** Draft for Public Input ***

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(PNNL) 54 for U . S . DOE. The se state s have regulatory structures that define ac ceptable procedures for quantify ing 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**  • **Electricity Savings Metrics and Baselines** – Electricity s avings 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 w ith consideration of naturally occurring market adoption (NOMAD ) of efficiency building practices in the absence of a n energy code or a prior energy code . (See text box for definition of NOMAD and related terms). The baseline needs to be estimated with co nsideration 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 • **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, a n 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 - bu ilt building to modeled use of the same building if it were built to meet the current code exactly. 56

54 htt p://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 T he 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*** Draft for Public Input ***

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• Indirect Estimation: This approach is associated primarily with assessing code compliance rates using secondary information, such as documents filed with b uilding 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 rec ommended approach for determining electricity savings involves accounting for naturally occurring market adoption (NOMAD) of measures that are required by the code. NOMAD may be estimated through collection of market data or through expert judgment techniq ues. 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 absenc e 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) • **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 w ith 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. • **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 mo re often. T he 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

- 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.

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 ***

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• **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.

• **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.

**Select EM&V Resources for Quantifying Savings from Building Codes** The following studies reflect the state- of-the - a rt 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 Effici ency 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 Te cMarket 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, t he 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 Ser vices 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 Residentia l Electricity Consumption, Anin Aroonruengsawat, * Maximilian Auffhammer, ** and Alan H. Sanstad, Energy Journal 2012, Volume 33, Number 1 • Are Building Codes Effective a t 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) • Why Has California’s Residential Electricity Consumption Been So Flat S ince the 1980s? A Micro econometric Approach, Costa, D.L., and M.E. Kahn, NBER working paper 15978 (2010)*** Draft for Public Input ***

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### 3.4 **Incremental Product Energy Standards 3.4.1.**  **Description** Appliance and equipment (p roduct ) en ergy standards are EE requirements that specify the minimum efficiency levels of specific products. Federal standards 58 currently apply to about 55 categories of appliances and equipment sold in the United States . 59 For products not subject to existing nati onal standards (and thus not subject to federal pre - emption 60 ) , state s may adopt their own product standards for sales within their borders. Within the p ast decade, state s 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, t he 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 stu dies 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 Co des 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** • **Electricity Savings Metrics and Baselines**  **–** Determine s avings 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 .

58 Electricity savings associated with federal product standards or ado pting 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 g uidance on how equipment that meets these standards needs to be labeled or includ ed in directories. A recent study indicated that existing Federal standards alone will produce annual electricity savi ngs 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 CO 2 . F rom: 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 . Fo r a list of States that have adopted nati onal standards, see : http://www.appliance - standards.org/federal and http://www.energy.gov/eere/buildin gs/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 standar d. This is referred to as Federal pre - emption. 61 Quoted directly from http://www.appliance - standards.org/standard - basics - DOE - state - legislature - pro duct requirements accessed 12/30/14. 62 For list of State standards see http://www.appliance - standards.org/states*** Draft for Public Input ***

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- NOMAD is a projection of what the annual sales, 63 over time, of products meeting the standards would have been if the standards had not been adopted.

- O nce the standard is in effect, the natural market no longer exists or can exist in reality. Methods for determin ing NOMAD are discussed in the next item on EM&V method s. • **EM&V methods** – Achieved electricity savings from product standards should be determin ed 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 ) T here are two approaches that can be appl ie d , each with a different metric for sales volume :

- Th e 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 curre ntly 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 publis hed 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 Documen ts 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 mode ls 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 establ ished by industry groups, DOE , and the California Energy Commission. 64 The baseline should include assumption s about NOMAD to calculate a conservative correction factor for the unit - energy savings.

63 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. 64 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 ***

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- Use of field measurements with NOMAD adjustments. At this time , NOMAD estimates are typically determined by us ing a Delphi technique. These NOMAD estimates should include consideration of effect s of prior-year standards and standards support programs . • **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 E M&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, per unit savings estimates, and NOMAD. I f 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. • **Evaluation cycles** – Electricity savings values, which are reported for each year, are based on per- unit 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 “efficie nt” than in 2025. • **Effective useful life and persistence of savings** – At a minimum , s avings should be assumed to continue until at least a new federal, state or local standard is put into place. • **Avoiding double cou**  **nting –**  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. **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 Profession als, 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 a nd Standards: A Guidebook For App liances, 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 val uable 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 Impact s 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 ***

A- 1



## Appendix A. **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 d ocument 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 conta ins complete information regarding the EM&V to be undertaken, why, when, and how. 

### A.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 p lan 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 electri city savings over the e ffective useful life (EUL) of the EE program /project 65 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 s ummary description of data collection approach, sample design, analyses methods, and significant assumptions ; indicat e the industry best - practices, protocols (e.g. IPMVP and the specific option) being applied c. P ersistence of savings – if stipulated EULs are utilized, indicate source of such values and why they are ap plicable to the subject program; describe any other approaches utilized. d. Independent factors – l ist and d escri be to be considered and supporting data that will be used to determine these variables’ value ; include how these factors are analyzed to quantify savings .

65 Program life may be estimated as the average life of the measures being offered under the program.*** Draft for Public Input ***

A- 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. Samplin g – if used, d escri be the sampling design and targeted confidence and prec i sion for resulting savings h. T&D losses – if applied to savings values, spe cify the value of the loss factor, its source , and the applicable method ology . 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 d ouble 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 method s, including: a. Statistical indicators of certainty such as confidence and precision b. D iscussion 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 ***

B - 1 

## Appendix B. **Glossary of Terms** This glossary includes only terms that are used in this draft EM&V guidance. 66 **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 a re 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/build ing 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 consumptio n of program participants. Comparison group approaches include RCTs and quasi - experimental methods using nonparticipants. 67 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.

66 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. 67 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 grou p method for the purposes of this guidance.*** Draft for Public Input ***

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**Deemed savings values :**  A lso 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 elementa ry 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 implementatio n. **EE measure:** a t 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 th e 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 p rogram, 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.*** Draft for Public Input ***

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**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. **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 doc umentation. **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- efficie nt lighting retrofit can reduce buildings’ air conditioning and increase heating requirements because less heat is generated by energyefficient lighting systems compared with less efficient lighting systems. **Market effects:** change s in the supply chain for energy efficient equipment or the behavior of participants and market actors resulting from market intervention(s). **Project -** **based m easurement and verification**  **:** PB - MV is the process of using measurements to determine electricity savings associated with individual projects or measures reliably. M&V can be applied to a census or sample of projects (measures) in a program (project) to determine average savings for the pro gram (project). With M&V, baseline electricity consumption is compared with post - project (or post - measure) electricity consumption measurements, along with analyses and documented assumptions to quantify savings. The IPMVP defines **two retrofit isolation** an d **two whole -** **facility M&V 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 M&V options require some project site measurements. Whole facility – analyzing savings from each EE measure in a project/facility c ollectively – (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 appli cation of measures equivalent to the code that would have taken place in the market even if the code had not been adopted. **Net savings:** c hange 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., c ommon practice) and/or in adjustments to gross savings values.*** Draft for Public Input ***

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**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 una ccounted -for factors that affect energy use. **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 M&V 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 observatio ns 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 . **Rigor:** 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 q uantified or described with metrics for reliability and certainty, such as in terms of reported value confidence and precision. **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 re porting 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., net-to -gross ratio values), source documentation, specified assumption s, and other relevant material to support the calculation of measure and program savings — and the application of such values and algorithms in appropriate applications.*** Draft for Public Input ***

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**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. S ite inspections, phone and mail surveys, and de sk review of program documentation are typical verification activities.*** Draft for Public Input ***

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## 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 A ppendix 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 E**  **M&V Methods and Activities for Typical**  **Consumer -**  **Funded EE P rograms**  **Type of Energy Efficiency Program**  **EM&V**

**Method Typical Evaluation Activities**  **Example Guidance and References**  **Links C** **o m** **p a** **r i** **s o** **n M** **& V** **D e** **e m** **e d**  **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 Measu rement 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/evaluation measurement - and verification - resource - portal*** Draft for Public Input ***

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**Type of Energy Efficiency Program**  **EM&V**

**Method Typical Evaluation Activities**  **Example Guidance and References**  **Links C** **o m** **p a** **r i** **s o** **n M** **& V** **D e** **e m** **e d**  **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 ***

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**Type of Energy Efficiency Program**  **EM&V**

**Method Typical Evaluation Activities**  **Example Guidance and References**  **Links C** **o m** **p a** **r i** **s o** **n M** **& V** **D e** **e m** **e d**  **Residential Refrigerator**  **Recycling Programs X**  **X** • Gather equipment model numbers to estimate removed units’ consumption and part year 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 - based emv .pdf http://energy.gov/sites/pro d/files/2015/02/f19/UMPCh apter17 - residential behavior.pdf*** Draft for Public Input ***

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**Type of Energy Efficiency Program**  **EM&V**

**Method Typical Evaluation Activities**  **Example Guidance and References**  **Links C** **o m** **p a** **r i** **s o** **n M** **& V** **D e** **e m** **e d**  **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/pu b 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 ***

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**Type of Energy Efficiency Program**  **EM&V**

**Method Typical Evaluation Activities**  **Example Guidance and References**  **Links C** **o m** **p a** **r i** **s o** **n M** **& V** **D e** **e m** **e d**  **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 cas es 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/2 015/01/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 nstruct ion%20Protocol.pdf*** Draft for Public Input ***

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**Type of Energy Efficiency Program**  **EM&V**

**Method Typical Evaluation Activities**  **Example Guidance and References**  **Links C** **o m** **p a** **r i** **s o** **n M** **& V** **D e** **e m** **e d**  **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.evo world.org/index.php?view= download&alias=1543 - 2012 - ipmvp -volume - i - in english - 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 ***

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### C.2. **P roject**  **- 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. Th e 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 lig ht of available budgets and desired levels of accuracy and reliability. 

### C.3. **Residential Lighting**  **Definition C.3.1.**  These projects involve installing efficient lighting products in residential dwelling, such as Light Emitting Diode (LED) lamps , and dimmable light s 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) **Key Challenges in Estimating Energy Savings**  **C.3.2.** The primary measurement challenges for estimating lighting technology savings evaluat ion 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** – D etermining 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 lu mens 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 i ndirect 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 ligh ting 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 a lso reduce longer -term*** Draft for Public Input ***

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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).*** Draft for Public Input ***

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The most common evaluation methods for deali ng with each challenge are discussed below: **A. Estimating Hours of Operation (HOU)**  68 **M&V Approach**  69 **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 state s 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 watts 70 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 E nergy 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 **C. Estimating**  **Interactive effects from efficient lighting on HVAC system usage**

68 Note the range of recently evaluated residential lamp operating hours range f rom 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 m ultiplier 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 En ergy 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 )*** Draft for Public Input ***

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**M&V Approach**  **Typical Application** Estimate indirect savings impacts using Waste Heat factors taken from previous evaluation studies or TRMs from adjacent state s 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 i mportant**  **e valuation 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 lightin g 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. **Relevant p rotocols**  **or e** **valuation studies for more information C.3.3.**  1. Uniform Methods Project; Chapter 21 : Residential Lighting Protocol (December 2014) http://www.energy.gov/sites/prod/files/2015/02/f19/UMPChapter21 - residential - lighting evaluation - protocol.pdf 2. KEMA, Inc.; Cadmus Group, Inc. (February 8, 2010). Final Evaluation Report: Upstream Lighting Program. Prepared for California Public Utilities Co mmission, Energy Division. http://www.calmac.org/publications/FinalUpstreamLightingEvaluationReport_Vol2_C ALMAC.pdf . 3. Navigant Consulting ; Itron; Op inion 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.htm l . 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 Definition**  **C.4.1.** 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)*** Draft for Public Input ***

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**Key Challenges in Estimating Energy Savings**  **C.4.2.** The two most difficult or primary measurement challenges for this technol ogy 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 Efficienc y 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 mete ring. 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 **Relevant Protocols and Sources for readers interested in more detailed information**  **C.4.3.** 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 Efficie ncy (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 Verifi cation 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*** Draft for Public Input ***

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Pro grams 2006 - 2008 Program Year. www.calmac.org/publications/Vol_1_HVAC_Spec_Comm_Report_02 - 10 - 10.pdf . 

### C.5. **Residential Whole Building Retrofits Definition**  **C.5.1.** 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 inte ract with each other, so it is not appropriate to estimate the savings from individual measures and sum them. This guidance is applicable to c ommon program - design approaches such as Home Performance with Energy Star (HPwES) , residential a udit p rograms, an d any other program that seeks to reduce overall energy use in residential dwellings using measures that address both building shell and building system improvements. **Key Measurement Challenges C.5.2.**  The key challenge in estimating energy savings from this progr am 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 program 72 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 -stage 74 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, b illing data is available and evaluation budget is sufficient to gather d etailed 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 R osenberg 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*** Draft for Public Input ***

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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 administrat or has confidence in implementer’s building simulation models because it has been calibrated to billing energy usage. **Relevant Protocols for More Information C.5.3.**  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 Definition**  **C.6.1.** 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 progra m 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). **Key Measurement Challenges C.6.2.**  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 T** **ype and W**  **hole B**  **uilding M&V**  **Approach Typical Application**  Collect average hours of usage by area use type 75 from a representative sample of buildings using self Project 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 approac h 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. 75 Examples of area use types include conference room, offices, halls, bathrooms, storage rooms, or retail display.*** Draft for Public Input ***

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reports from building managers and or HOU estimates from forecasting models. time or resources to ins tall 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 lightin g 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 repl acement, 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 **Relevant Protocols for readers interested in more detailed information C.6.3.**  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 .*** Draft for Public Input ***

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### C.7. **Commercial Chiller Systems Definition**  **C.7.1.** These projects involve installing or retrofitting electricity consuming chillers and/or associated auxilia ry 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). **Key Challenges in**  **Quantifying Energy Savings**  **C.7.2.** Key measurement challenges includ e: (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 consump tion of Chiller Systems are outlined in the table below. **M&V Approach**  **Typical Application** IPMVP Option A – Retrofit Isolation Key p arameter m easurements 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 B uilding Billing A nalysis P re 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 B uilding Simulation M odel ing 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*** Draft for Public Input ***

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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 R 2 values or T statistics on the estimated coefficient for the independent va riable of interest to ensure accuracy. The Commercial Chiller protocol 76 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. **Relevant Protocols and Evaluation Sources for More**  **Information C.7.3.**  1. Unifo rm Methods Project, Chapter 14: Chiller Evaluatio n Protocol, Chapter reference ( Prepared by Alex Tiessen, Posterity Group for the National Renewable Energy Laboratory, September 2014) . R eference http://www.energy.gov/sites/prod/files/2014/10/f18/Chapter%2014 -- Chiller%20Evaluation%20Protocol.pdf 2. E VO. (January 2012). Interna tional 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 Industria l 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 Replace ment: 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