## From: Higgins, Cortney [mailto:Cortney_Higgins@omb.eop.gov] Sent: Friday, May 30, 2014 2:27 PM To: Culligan, Kevin Cc: Wayland, Robertj Subject: RE: State Plan TSDs

No, thank you.

From: Culligan, Kevin [mailto:Culligan.Kevin@epa.gov] Sent: Friday, May 30, 2014 2:26 PM To: Higgins, Cortney Cc: Wayland, Robertj Subject: FW: State Plan TSDs

Did you get these yesterday?

<< State Plan Considerations TSD_04-10-14_InteragencyCommentsUnderEO12866_EPA Responses_V2_5.29.14.docx >> << Projecting Emission Performance TSD_04-10-14_InteragencyCommentsUnderEO12866_EPA Responses_V2_5.29.14.docx >>

### Technical Support Document (TSD) for Carbon Pollution Guidelines for Existing Power Plants: Emission Guidelines for Greenhouse Gas Emissi ons from Existing Stationary Sources: Electric Utility Generating Units

Docket ID No. EPA-HQ-OAR-2013-0602



# State Plan Considerations

U.S. Environmental Protection Agency Office of Air and Radiation

June 2014

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2 Table of Contents

I. Introduction .................................................................................................................. ......3 II. Description of State Plan Pathways .................................................................................4 A. Direct Emission Limits .............................................................................................6 B. Portfolio Approach ....................................................................................................8 III. Enforceability Considerations under Different State Plan Scenarios .........................12 A. Parties Regulated by the State other than Affected EGUs ......................................13 B. Private or Public Third-Party Entity not Regulated by the State ............................15 C. State Agency, Authority, or Entity ..........................................................................16 D. Multi-State Approaches

............................... ........................ ........................ ...........17 IV. Incorporating End-Use Energy Efficiency and Renewable Energy Programs and Measures under a Rate-Based Approach ......................................................................19 A. Concept of Adjusting EGU CO 2 

### Emission Rates based on the Effects of End-Use Energy Efficiency and Renewable Energy ..................................................................19 B. Approaches for Adjusting EGU CO 2 

### Emission Rates ............................................20 C. Methods and Tools for Quantifying Avoided CO 2 

### Emissions from End-Use Energy Efficiency and Renewable Energy .........................................................................23 V. Quantification, Monitoring, and Verifica tion of End-Use Energy Efficiency and Renewable Energy Programs and Measures .................................................................32 A. Quantification, Monitoring, and Verification for End-Use Energy Efficiency .....35 B. Quantification, Monitoring, and Verification for Renewable Energy Measures ...45 VI. Reporting and Recordkeeping for End-Use Energy Efficiency and Renewable Energy Programs and Measures ....................................................................................71 A. Reporting for End-Use Energy Efficiency Programs and Measures .....................72 B. Reporting for Renewable Energy Programs and Measures ...................................74 VII. Treatment of Interstate Emission Effects ......................................................................79 A. Background ............................................................................................................81 B. Summary of Possible Approaches for Treat ment of Interstate Emission Effects..83 VIII. Appendix ...................................................................................................................... .....92

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3 I. Introduction
As discussed in the preamble, in section VIII.F, the EPA is proposing to give states broad discretion to develop state plans that best su it their circumstances and policy objectives. In developing its plan, a state will need to make a number of decisions th at will require careful consideration, in order to ensure that its plan both meets a state’s policy objectives and is approvable by EPA. The preamble, in section VIII. F, identified several key decision points and factors that states should consider when developi ng their plans. In this section of the preamble, the EPA also raised a number of considerations for how it will apply the proposed general plan approvability criteria to different types of state plan approaches. This includes a number of considerations related to appropriate approaches, methods, and materials that are submitted for state plan components in an approvable plan, under different types of state plans. This technical support document (TSD) explains and discusses these considerations in depth, and elaborates options proposed in the preamble where relevant. Topics addressed in this TSD include:

 Description of state plan pathways

o Provided as context for the discussion of applied considerations that follows

 Enforceability considerations un der different plan scenarios

o Summary of potential enforceable mechanisms under different state plan
scenarios

 Incorporating energy efficiency and re newable energy (EE/RE) requirements and programs in state plans, including:

o Options for adjusting EGU CO 2 

### emission rates based on the effect of EE/RE requirements and programs

o Methods for estimating avoided CO 2 

### emissions that result from EE/RE requirements and programs , for use in projecting emission performance under a state plan and in ex post adjustment of CO 2 

### emission rates during plan implementation

 Quantification, monitoring, and verification of EE/RE requirements and programs

o Survey of quantification, monitoring, and verification under existing state and utility EE/RE requirements and programs Comment [A1]: 1. This TSD should echo the emphasis in the preamble on the role of the ISO/RTO or other planning authority with respect to understanding the system/reliability implications of a state plan design on the grid and about including “guidance” to states about utilizing flexibility to address events (including retirements) that may occur during the compliance period while ensuring grid reliability.

EPA response: A companion TSD, Projecting EGU CO 2 Emission Performance in State Plans, addresses the potential role of ISO/RTO in facilitating state plan development in a respective grid region, including the role that an ISOs/RTOs could play in providing analytical support to states during plan development.

Deleted:

Comment [A2]: The discussion of avoided CO 2 calculations conflates two separate issues: their use as part of an ex ante determination of whether a state plan (such as a portfolio approach) will achieve a given level of emissions (or emissions rate) as part of an equivalency determination and their use ex post to ‘adjust’ emissions. It would help clarify things if this distinction were discussed. With regards to the ex post use, all emissions are already measured at the stack, so an avoided emissions calculation is unnecessary and would constitute double counting of emissions reductions.

EPA response: We have added text here in response to this comment. The referenced TSD section addresses both considerations.

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4 o Discussion of possible approaches for minimum requirements or guidance for quantification, monitoring, and verification for EE/RE requirements and programs included in state plans, building off exis ting state processes and infrastructure

o Discussion of areas where supplement al information would be useful for estimating avoided CO 2 

### emissions from EE/RE requirements and programs

 Reporting and recordkeeping for responsible parties subject to EE/RE requirements or implementing EE/RE programs included in state plans

o Survey of reporting and recordkeeping under existing state and utility EE/RE requirements and programs

o Discussion of possible approaches for EE/RE reporting requirements for state plans, building off existing state processes and infrastructure

o Discussion of areas where supplement al information would be useful for estimating avoided CO 2 

### emissions from EE/RE requirements and programs

 Treatment of interstate emission effects

o Further elaboration of proposed approaches and alternatives discussed in the preamble

It should be noted that the preamble discusses, and solicits comment on, legal issues concerning whether CAA section 111(d) authorizes some of the types of state plans described in this TSD and whether it authorizes state plans to include some of these types of measures. This TSD does not further discuss those legal issues, but solely for the purpose of describing all of the available types of state plans and measures, assu mes that all of them are authorized under CAA section 111(d).

II. Description of State Plan Pathways
As discussed in the preamble, the EPA is proposing a state plan approach that could accommodate a diverse set of state requirements, programs, and measures, through two basic approaches – direct emission limits and a po rtfolio approach. These two basic approaches provide four distinct state plan “pathways” under CAA section 111(d). These pathways include:

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5  Rate-based CO 2 

### emission limits applied to affected EGUs;

 Mass-based CO 2 

### emission limits applied to affected EGUs;

 A state-driven portfolio approach

 A utility-driven por tfolio approach

Under this flexible approach, a state plan coul d include a combination of measures that reduce
CO 2 

### emissions at affected EGUs through the appli cation of emission limits as well as measures
that involve actions within the interconnected electri city system that reduce utilization at affected EGUs and thereby avoid EGU CO 2 

### emissions. Examples of these latter measures include, among others, end-use energy efficiency resource standa rds and renewable energy portfolio standards, as well as certain components of utility integrated resource plans. A state could either rely solely
on CO 2 

### emission limits that are enforceable against affected EGUs or, alternatively, rely on a portfolio approach, which would include those limits as well as other enforceable measures. Table 1 provides practical examples of possibl e state plan approaches under each of these pathways, which are discussed in more detail below.

This section elaborates the different plan appr oaches that are discussed in section VIII.B of the preamble, to provide context for the applied considerations that are discussed throughout the remainder of the TSD. In particular, some of these considerations apply to different types of state plan approaches. For example, section III of this TSD addresses enforceable legal mechanisms that might apply under different types of state plans, such as utility- and state-driven portfolio approaches, which would apply enforceable obligations to different entities. Section IV of this TSD applies to state pl ans that implement rate-based CO 2 

### emission limits for affected EGUs that also provide for the adjustment of CO 2 

### emission rates based on the effect of enforceable end-use energy efficiency and renewable energy requirements and programs that are incorporated in a plan. Section V of this TSD addresses quantification, monitoring, and verification of end-use energy efficiency an d renewable energy programs and measures.
Considerations addressed in this section woul d apply to states implementing a rate-based emission limit approach that provides for adjustment of CO 2 

### emission rates based on the effect of end-use energy efficiency and renewable energy, as well as states implementing utility- or statedriven portfolio approaches that incorporate en d-use energy efficiency and renewable energy

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6 requirements and programs. Likewise, section VI of this TSD addresses considerations for reporting and recordkeeping for end-use energy efficiency and renewable energy requirements and programs, which would apply for these types of state plans.

Table 1. Different Illustrative Plan Approaches

A. Direct Emission Limits
The first basic state plan approach is CO 2 

### emission limits that apply directly to affected EGUs, and includes two pathways: 1.) rate-based CO 2 

### emission limits applied to affected EGUs; and 2.) mass-based CO 2 

### emission limits applied to affected EGUs. For both types of emission limits, end-use energy efficiency and rene wable energy measures that avoid EGU CO 2 

### emissions could be a major component of a state’s overall strategy for cost-effectively reducing EGU CO 2 

### emissions.

1. Rate-Based CO 2 

### Emission Limits Applied to Affected EGUs Comment [A3]: It would be helpful to have the equivalent formula for rate

‐ based equivalency. In particular, all of the above considerations apply to the numerator of this formula. In addition, the contributions to the denominator should be specified. Specific questions include:

 Does generation from new NGCC units count? New nuclear or CCS?

 What amount of generation from existing clean units (including non

‐ hydro RE, hydro, nuclear, etc.) is included in the denominator? How are uprates dealt with?

 Is the EE generation included in the denominator gross savings or net savings?

EPA response: This topic is addressed in a companion TSD, Projecting EGU CO 2 Emission Performance in State Plans. We have made revisions in that TSD in response to similar comments in that document. The referenced section in this TSD describes different types of possible state plans.

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7 Rate-based emission limits would apply a lb CO 2 

### /MWh emission limit to affected EGUs. Depending on a state’s approach, compliance flex ibility could be provided through different mechanisms, such as averaging among affected sour ces, or the use of tradable credits for avoided
CO 2 

### emissions resulting from end-use energy effi ciency and renewable energy measures as discussed below. In the case of the latter approach, such credits could be used by an affected EGU to adjust its CO 2 

### emission rate when demonstrating compliance with a rate-based emission
limit. 1 

### Rate-based emission limits could be implemen ted on a state-by-state basis, or through multi-state averaging or trading. Rate-based em ission limits might also be a component of a portfolio approach (described below), where the emission rate limit would not assure full achievement of the required leve l of emission performance specified for affected EGUs in the state plan, in which case the emission limit would be supplemented with other enforceable

measures.

Rate-based emissions limits could incorporat e end-use energy efficiency and renewable energy measures that avoid EGU CO 2 

### emissions, through an administrative adjustment by the
state or tradable crediting system. 2 

### These adjustment credits could be used by an affected EGU to comply with the rate-based emission li mit, by adjusting the unit’s reported CO 2 

### emission rate. 3 

### Under this approach, end-use energy efficiency and renewable energy measures that avoid EGU
CO 2 

### emissions would be enforceable components of a state plan. These actions would need to be enforceable components of a state plan to pr ovide assurance that a sufficient amount of adjustment credits will be available to facilita te EGU compliance with the emission rate limit,

1 Section IV of this TSD discusses possi ble approaches for such adjustments. 2 Under a tradable credit system, a state would issue adjustment credits based on avoided CO 2 emissions achieved through end-use energy efficiency and renewable ener gy measures. EGUs could then apply these tradable adjustment credits when demonstrat ing compliance with a rate-based CO 2 emission limit. These tradable credits might be issued to affected EGUs for free or through pur chase. Alternatively, end-use energy efficiency and renewable energy actions undertaken by private parties (i ncluding EGU owners and operato rs) might be eligible for the issuance of adjustment credits. Under an administra tive adjustment approach, a state program administrator might administratively adjust an affected EGU’s CO 2 emission rate based on avoided CO 2 emissions achieved through state end-use energy efficiency and renewabl e energy deployment programs or utility compliance with energy efficiency resource standards or renewable energy portfolio standards. These adjustments might be apportioned to affected EGUs based on a predetermined me tric. Affected EGUs would then begin with an adjusted CO 2 emission rate when considering additional actions necessary for compliance with the rate-based CO 2 emission limit. 3 Section IV of this TSD discusses po ssible approaches for such adjustments.

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8 and that end-use energy efficiency and renewable energy measures that generate adjustment credits are properly quantified, monitored, and verified. 4



### 2. Mass-Based CO 2 

### Emission Limits Applied to Affected EGUs
Mass-based emission limits would apply either an individual limit on CO 2 

### tons emitted
from an affected EGU or establish a finite CO 2 

### emissions budget for a group of affected EGUs. The latter approach is typically implemented through a tradable allowance system.

With mass-based emission limits, end-use en ergy efficiency measures that avoid EGU
CO 2 

### emissions could be a major component of a state’s overall strategy for cost-effectively reducing EGU CO 2 

### emissions, but would be complementary to the enforceable state plan ( i.e. , not included as enforceable measures in a state pl an). These actions could be used to help a state cost-effectively achieve the CO 2 

### emissions limits, or to achieve other policy goals, but CO 2 

### emissions performance would be assured through the enforceable limit on mass emissions from
affected EGUs.

B. Portfolio Approach
The second basic state plan approach uses a portfolio of actions, in which a state plan includes multiple programs and measures that are designed to achieve either a rate-based or mass-based emissions performance goal for affected EGUs. This approach includes two pathways: 1.) a state-driven portfolio approach; and 2.) a utility-driven portfolio approach. A portfolio approach would include emission limits for affected EGUs along with other enforceable end-use energy efficiency and renewable energy measures that avoid EGU CO 2 

### emissions. A portfolio approach could be state-driven or utility-driven, dependi ng on the utility regulatory
structure in a state.

In general, a portfolio approach is distinguished from an emission limit approach by the fact that achievement of the full level of required emission performance for affected EGUs

4 Section V of this TSD addresses considerations for quant ification, monitoring, and verification of end-use energy efficiency and renewable energy measures. Comment [A4]: It would be very helpful to have the explicit formula that is the basis for determining

mass

‐ based equivalence. In particular, the precise list of sources whose emissions count needs to be specified. Specific questions include:

 Do emissions from new NGCC units count?

 Do emissions from new CCS units count?

 Do emissions from units with a capacity factor of less than 1/3 or other uncovered

sources count?

 How will biomass emissions be incorporated when the final guidance on this is available?

EPA response: This topic is addressed in a companion TSD, Projecting EGU CO 2 Emission Performance in State Plans. We have made revisions in that TSD in response to similar comments in that document. The referenced section in this TSD describes different types of possible state plans.

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9 specified in the plan is not ensured through the ap plication of direct emissi on limits that apply to
affected EGUs.

A portfolio approach would include both dir ect emission limits that apply to affected
EGUs and other indirect measures that avoid EGU CO 2 

### emissions. Under a portfolio approach, end-use energy efficiency and renewable energy measures that avoid EGU CO 2 

### emissions would be enforceable components of a state plan. This would be necessary because the emission limit applied directly to affected EGUs would not as sure full achievement of the required level of emission performance specified in the state plan. 5



### As discussed below, due to differences in st ate utility regulatory st ructure, a portfolio approach implemented in a restructured stat e with retail competition will likely look quite different from one implemented in a state with ve rtically integrated, regulated electric utilities. This includes the process for developing the portfolio approach, the mechanisms for implementing it, the responsible parties, and the regulatory and legal relationships among parties and state regulators.

1. State-Driven Portfolio Approach
A state-driven portfolio approach – rather than a utility-driven approach – is more likely to be adopted in a state with a restructured el ectricity sector. In these states, rate-regulated electric utilities have typically divested electric generation assets and there is often also retail competition where non-utility entities can s upply retail customers with electricity. 6 

### Electric distribution utilities in these states typically purchase electricity from competitive wholesale markets. As a result, utilities in these states ty pically do not engage in a utility integrated resource planning (IRP) process. IRP processes, which are a natural fit for implementing a

5 Under a portfolio approach, either a rate-based or mass- based emission limit might be applied. Such plans might also include application of a direct emission limit to a subset of affected EGUs. Both scenarios would necessitate inclusion of supplemental measures, such as end-use energy efficiency and renewable energy, or other measures that directly apply to affected EGUs (e.g., repowering or retirement of one or more high-emitting EGUs), in order to achieve the required level of emission performance for affected EGUs specified in the state plan. 6 In some restructured states, the holding company that ow ns the distribution utility may also own generating assets which are operated on a competitive basis. In these inst ances, there typically are legal provisions in place that mandate the independent management and opera tion of generation and distribution assets.

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10 portfolio approach, are mu ch more common in states with regu lated vertically integrated utilities that own and operate electric generating assets.

In restructured states, policies for increasing end-use energy efficiency and renewable energy are often established throu gh regulations that apply to electric distribution utilities, such as end-use energy efficiency resource standard s and renewable portfolio standards. Many of these states have also established independent n on-profit entities to administer end-use energy efficiency and renewable energy deployment programs funded through regulated electricity

rates.

Under a state-driven portfolio approach a mix of entities might have enforceable obligations under a state plan. This includes owne rs and operators of affected EGUs subject to direct emission limits, as well as electric distri bution utilities, private or public third-party entities, and state agencies or authorities th at administer end-use energy efficiency and renewable energy deployment programs or are subject to portfolio requirements.

2. Utility-Driven Portfolio Approach
A state with vertically integrated, state-regulate d electric utilities is more likely to adopt a utility-driven portfolio approach. In such stat es, private utilities own and operate electric generation, transmission, and distribution system s necessary to supply retail customers with electricity. 7 

### These utilities are overseen by state public utility commissions that approve utility capital investments and oversee utility opera tions, and allow utilities to recover approved investments and operating costs, along with a specifi ed financial rate of return, through regulated retail electricity rates. State utility commissions often require regulated utilities to engage in an integrated resource planning (IRP) process, which seeks to identify the least-cost set of resources available to provide electricity to retail customers over a multi-year period, and often includes evaluation of measures such as end-use energy efficiency, demand-side management, and

7 In some instances these regulated utilities may supplem ent electric generation with purchases through wholesale electricity markets and may also sell surplus generati on in these wholesale markets on a competitive basis.

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11 renewable energy. 8 

### Once an IRP is approved by a state public utility commission, a utility’s cost recovery and rate of return is often linked to identified measures and metrics in the IRP. 9



### Under a utility-driven portfolio approach, a vertically integrated utility would develop and implement a portfolio of measures designed to meet the rate-based or mass-based emission performance level for its affected EGUs specified in the state plan. This plan would likely be developed and approved through an IRP-like process overseen by the state public utility commission. If there is more than one rate-regulat ed electric utility in the state, the state might apportion the state emission performance le vel for affected EGUs among utilities.

A utility plan under this approach might rely heavily on end-use energy efficiency and renewable energy actions, but also might focus on direct actions at af fected EGUs, such as repowering to fire a lower-carbon fuel or retirement of high-emitting units. Such plans might
also include direct emission limits on affected EGUs, or implementation of an environmental dispatch approach that incorporates CO 2 

### emission rate into the dispatch protocol used by the utility to schedule electric generation. 10



### Under a utility-driven portfolio approach, the entire suite of obligations under the plan would be enforceable against the utility company, which would also be an owner and operator of
affected EGUs. If there are other affected EGUs in the state that are not owned and operated by a vertically integrated utility, a state plan might need to include other measures that address CO 2 

### emission performance by these affected EGUs.

A similar approach could be taken by munici pally owned utilities or utility cooperatives, which often also engage in an IRP process. However, state public utility commissions (PUCs)

8 Depending on the state, an IRP process may also a ssess factors such as fuel diversity and environmental performance, among others, when identifying th e least-cost mix of resources for a utility. 9 In some cases, an IRP prescribes or authorizes specific actions. In others, an IRP serves as a guide for the utility and the public utility commission when evaluating acquisiti on or implementation of specific utility resources or programs. In such cases, the specific resource or progra m is approved through a PUC order that authorizes or requires actions and identifies performance obligations. Thes e orders may or may not be fully consistent with provisions in an IRP. 10 Vertically integrated utilities, even if they operate within the footprint of a competitive wholesale electricity market, may self-schedule generation assets.

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12 often do not regulate th ese utilities. As a result, implementati on of a portfolio approach by these entities would introduce practical enforceab ility considerations under a state plan. III. Enforceability Considerations under Different State Plan Scenarios
As discussed in the preamble of the propos al, in section VIII.F.1, a state plan must include enforceable measures. To ensure that its plan is enforceable, a state will need to:

 Identify in its plan the entity or entities responsible for meeting compliance and other enforceable obligations under the plan

 Include mechanisms for demonstrating compliance with plan requirements or demonstrating that other binding obligations are met

 Provide a mechanism(s) for legal action if aff ected EGUs are not in compliance with plan requirements or if other entities fail to meet enforceable plan obligations

As discussed in the preamble, responsible entities in an approvable state plan may include an owner or operator of an affected EGU, other entities with responsibilities assigned by a state, or the state itself. Other entities might include an en tity that is regulated by the state, such as an electric distribution utility, or a private or pub lic third-party entity. State responsibility might include obligations that are assumed directly by a state agency, authority, or other state entity to carry out aspects of a state plan.

While this approach provides states with broad discretion to develop plans that best suit their circumstances and policy objectives, assigni ng responsibility to other parties regulated by the state, private or public third-party enti ties, or state entities raises enforceability
considerations. This section discusses how the general enforceability approach discussed in the preamble, and described above, might apply in practice under different state plan approaches.

This section describes possible scenarios of responsible entities and legal mechanisms and approaches that might be used to address en forceability considerations under different types of state plans. These s cenarios were developed to capture th e range of entities that are currently implementing end-use energy efficiency and renewa ble energy deployment programs in states, or are subject to states requirements such as end- use energy efficiency resource standards (EERS)

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13 or renewable portfolio standards (RPS). For each of these examples, this section describes current legal relationships between these entities and the state, and discusses possible legal instruments that might provide the state with the authority to ensure that obligations in a state plan are met and to address failure to meet those obligations. The mechanisms discussed take different forms, but would specify the three el ements described above: obligations, compliance demonstration, and enforcement mechanisms. This section also discusses enforceability
considerations in cases where states act jointly through a multi-state plan.

A. Parties Regulated by the State other than Affected EGUs
One likely state plan scenario involves incl usion of enforceable obligations for stateregulated entities other than affected EGUs. An exam ple of a state-regulated entity that is not an owner or operator of affected EGUs may be an electric distribution utility. 11 

### These entities are typically regulated by a state public utility commi ssion. An example of an enforceable state plan measure that might apply to an electric distribution utility is a compliance obligation under a state end-use energy efficiency resource standard (EERS) or renewable portfolio standard (RPS), or implementation of incentive programs for the deployment of end-use energy efficiency and renewable energy technologies.

Another example is where a vertically integr ated, state-regulated utility implements a portfolio of enforceable actions under a state plan , which may include actions that apply directly to affected EGUs as well other actions such as end-use energy efficiency and renewable energy deployment programs. While vertically integrat ed utilities may own and operate affected EGUs, some of the measures implemented may require different enforceability mechanisms than an emission limit applied to an affected EGU.

11 Electric distribution utilities are also often referred to as local distribution companies (LDCs). Here we refer to an electric distribution utility as an entity that owns and oper ates an electric distribution network but is not the owner and operator of EGUs. As discussed further, vertically integrated utilities own and operate electric distribution networks as well as EGUs.

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14 1. Electric Distribution Utility with Obligat ions to Meet an EERS or RPS Pursuant to State Regulations

EERS and RPS requirements are typically implemented through state regulations, but may also be implemented through a public u tility commission order. State EERS and RPS regulations provide legal instruments generally comparable in enforceability to regulatory emission limits applied to EGUs. These regula tions typically specify compliance obligations, reporting, and enforcement. However, many state RPS regulations and some EERS regulations include alternative compliance paym ent (ACP) provisions that prov ide the utility with the option of making a payment in lieu of full compliance with the portfolio requirement. Thus, state EERS and RPS mandates may not guarantee achievement of a given level of end-use energy efficiency or renewable energy deployment during a plan performance period. 12



### 2. Vertically Integrated Electric Utility with Obligations under a State-Approved Integrated Resource Plan

A utility integrated resource plan (IRP) may include a number of direct and indirect
actions that affect EGU CO 2 

### emissions, and may also include compliance with EERS and RPS regulations. Broadly, IRPs may prescribe or au thorize actions for which utilities can recover capital investments and operating costs through regulated retail electricity rates. 13 

### This creates strong financial incentives for implementing an action, but may not mandate an action.

For a state plan under this scenario, an enforceability consideration is whether an IRP, and related public utility commission orders, must include additional requirements to implement

12 We note that some direct emission limits for CO 2 emissions include somewhat similar provisions. For example, both the RGGI state CO 2 emission budget trading programs and the California GHG emission budget trading program include cost containment prov isions where more emission allowances are made available to affected sources at certain allowance price thresholds. In both thes e instances, such relevant characteristics of the state regulations would need to be taken into account when projecting the CO 2 emission performance that will be achieved by affected EGUs under the state plan. 13 In some cases, an IRP prescribes or authorizes specific actions. In others, an IRP serves as a guide for the utility and the public utility commission when evaluating acquisiti on or implementation of specific utility resources or programs. In such cases, the specific resource or program is approved through a PUC order that authorizes or requires actions and identifies performance obligations. Thes e orders may or may not be fully consistent with provisions in an IRP.

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15 certain actions, beyond denial of rate recovery or a change to utility tariffs if a utility fails to meet specified obligations in the IRP. If so, this may require state legislation to provide additional authority to state public utility commis sions in some states, or confer additional authority to other agencies (e.g., a state environmental agency).

B. Private or Public Third-Party Entity not Regulated by the State
Another state plan scenario involves public or private third-party entities with enforceable obligations under a state plan. A private or public third-party entity could be a utility entity that is not regulated by a state public u tility commission, such as a municipal utility or a utility cooperative. 14 

### It could also be a private non-profit en tity established to administer end-use energy efficiency and renewable energy deployment programs. 15 

### In most cases, since they often expend electricity ratepayer funds, such non-profit entities are created by state legislation and overseen by state public utility commission s or state-regulated private utilities.

An appropriate legal instrument or agreement applicable to such entities included in a state plan might include legal arrangements similar to those currently used to establish independent entities that expend el ectricity ratepayer dollars in multiple states. For entities not subject to state oversight, such a mechanism might also include mechanisms where an entity voluntarily submits to the authority of a state, pursuant to state statutory or regulatory authority specified in a state plan. Such agreements might be attached to a funding source. For example, the entity would voluntarily submit to such authority as a condition of receiving certain funds, such as state appropriated funds or funds coll ected through state-regulated electricity rates. Alternatively, a municipal utility or utility cooper ative might voluntarily su bmit to state authority as a condition of the state agreeing to let the enti ty implement a portfolio approach, in lieu of the application of certain direct CO 2 

### emission limits for affected EGUs owned and operated by such entities through a state regulation. In some cases , new state statutory authority might be enacted

14 Here, “not regulated” refers to regulation of electricity rates by a state public utility commission. To the extent that such entities are owners and oper ators of affected EGUs, these EGUs may be subject to state environmental and other regulations. In some cases these utility entities are al so subject to state EERS and RPS regulations, as specified under state law. 15 Examples include the Energy Trust of Oregon, the Delawa re Sustainable Energy Utility, and Efficiency Vermont.

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16 to support a state plan, specifying enforceable obligations for these private or public third-party entities under the plan.

An additional consideration is whether such le gal instruments or agreements, if related to a renewable energy or end-use energy efficiency deployment program, should specify a stable budget authority and funding source through each plan performance period. Such authority and funding might be necessary to ensure that suitable funds are made available to achieve the level of energy savings or renewable energy deployme nt projected in the state plan, which may be necessary to achieve the level of emission performance by affected EGUs that is projected will be achieved through implementation of the plan.

C. State Agency, Authority, or Entity
This state plan scenario involves a state entity with an enforceable obligation in a state plan. For example, state authorities in some states implement renewable energy and end-use energy efficiency deployment programs. 16 

### In this scenario, the requirement for the state entity would be an enforceable component of the state plan.

One type of legal arrangement that might be applied under this scenario is legislation directing state executive branch agencies or i ndependent state authorities to follow through on obligations under a state plan.

Such legislation might provide independent legal authority under state law to compel executive branch actions, or actions by independent state authorities under the plan, if obligations are not met. Depending on the form of legislation, this could also provide citizens with the ability to compel state action under stat e law, if obligations are not met under a state plan. 17

16 A prominent example is the New Yo rk State Energy Research and Development Authority (NYSERDA), which administers energy efficiency and renewable energy deployment programs. 17 We note that under the CAA, measures included in an a pproved 111(d) state plan woul d be federally enforceable by EPA, and that citizens would also have the ability to file citizen suits to compel enforcement of state plan obligations, under CAA Section 304 (42 U.S. Code Section 7604).

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17 An additional consideration is whether such legal arrangements, if related to a renewable energy or end-use energy efficiency deployment program, should also specify a stable budget authority and funding source through the plan performance period, or other provisions, to ensure that programs are implemented as projected under the state plan.

D. Multi-State Approaches
As discussed in the preamble, in section V III.F.1, multi-state appr oaches introduce crosscutting enforceability considerations.

For these multi-state approaches, states would demonstrate emission performance from affected EGUs in aggregate jointly with partner states. For states participating in a multi-state approach, the individual state performance goals in the emission guidelines would be replaced with an equivalent multi-state performance goal. For example, states taking a rate-based approach would demonstrate that all affected E GUs subject to the multi-state plan achieve a weighted average CO 2 

### emission rate that is consistent, in aggregate, with an aggregation of the state-specific rate-based CO 2 

### emission performance goals establis hed in the emission guidelines that apply to each of the participating states. If states were taking a mass-based approach, participating states would demonstr ate that all affected EGUs subject to the multi-state plan emit a total tonnage of CO 2 

### emissions consistent with a translat ed multi-state mass-based goal. This multi-state mass-based goal would be based on tr anslation of an aggregation of the state-specific
rate-based CO 2 

### emission performance goals established in the emission guidelines that apply to each of the participating states.

1. Multi-State Emission Budget or Rate-Based Emission Trading Programs
The Regional Greenhouse Gas In itiative (RGGI) is an example of a multi-state approach to regulation of CO 2 

### emissions. Through this initiative, nine states are currently implementing
coordinated CO 2 

### emission budget trading programs. The program works as a coordinated regional whole through a shared emission and allowance tracking system and allowance auction process, but is implemented in accordance with materially consistent stand-alone state regulations and individual statutory au thority. These regulations recognize CO 2 

### allowances issued by other participating states for use by affected EGUs when comp lying with each state’s

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18 emission limitation, but contain all the nece ssary components to administer the program requirements on an individual state basis. 18 

### As a result, while the initiative is implemented regionally, each CO 2 

### emission budget trading program regula tion is enforceable against affected EGUs at the state level and functions as a discrete program.

As a result, a multi-state emission budget trad ing program approach, such as RGGI, is enforceable in practice at the state level. A multi-state rate-based emission trading program could also be established in much the same manner as a multi-state emission budget trading program,
and could therefore be enforceable at the state level. 19



### 2. Multi-State Portfolio Approaches
A multi-state portfolio approach could intr oduce novel enforceability considerations. If it were based on interdependent emission reduction strategies among states that are not tied to emission limits that directly apply to affected EGUs, the emission performance of affected EGUs in one participating state may be dependent, in pa rt, on actions taken in other participating states. If a state (or states) failed to implement commitmen ts under the multi-state plan, this raises the question of whether the EPA should address non-performance of one or more participating states in the context of failure to achieve the required level of multi-state emission performance under the plan, or instead enforce actions at the individua l state level for those states that are failing to meet commitments under the multi-state plan.

18 The emission limitation consists of a requirement to submit CO 2 allowances equal to reported CO 2 emissions during a compliance period. While states have individu al emission budgets, representing the total number of allowances issued for a given year th at are available for allocation, there are no individual state emission limits. The CO 2 emission constraint is regional, based on the sum of state CO 2 emission budgets. 19 Enforceability would be contingent, in part, on states having comparable enforcement mechanisms.

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19 IV. Incorporating End-Use Energy Efficiency and Renewable Energy Programs and Measures under a Rate-Based Approach

A. Concept of Adjusting EGU CO 2 

### Emission Rates based on the Effects of End-Use Energy Efficiency and Renewable Energy

As discussed in the preamble, in section VIII.F.3, the EPA is proposing that RE and demand-side EE requirements, programs, and measures may be incorporated into a rate-based plan approach. 20 

### Measures that avoid CO 2 

### emissions from affected EGUs, such as quantified and verified end-use energy savings and renewable energy generation, could be used to adjust the
CO 2 

### emission rate of an affected EGU when demonstrating compliance with a rate-based CO 2 

### emission limit. Alternatively, a state could use the effect of such measures as a basis for administratively adjusting the average CO 2 

### emission rate of affected EGUs when demonstrating achievement of the required emission rate performance level in a state plan.

Under this approach, affected EGUs could comply with a rate-based CO 2 

### emission limit through actions at the EGU, 21 

### as well as through the use of credits 22 

### for actions that occur elsewhere in the interconnected electricity system that avoid CO 2 

### emissions from affected EGUs. If a state is implementing a portfolio approach, then the state could administratively adjust the average CO 2 

### emission rate of affected EGUs through a similar process when demonstrating achievement of the required emission rate performance level in the state plan.

This section explores in depth the mechanic s and implications of the different possible approaches for adjusting CO 2 

### emission rates that are summarized in the preamble. Aspects of this discussion may apply to both retrospective demonstration of CO 2 

### emission performance

20 The EPA is also proposing that RE and demand-side EE measures could be used under a mass-based portfolio approach in an approvable state plan. However, the focus of this section is limited to application of such measures under a rate-based approach. 21 This could include an individual affected EGU or group of affected EGUs if a rate-based averaging or trading approach is used. 22 These credits could be tradable, or represent non-tradable credits administratively apportioned to affected EGUs. This latter approach effectively represents an ad ministrative adjustment applied by the state.

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20 achieved by affected EGUs under an approved state plan and projections of CO 2 

### emission performance by affected EGUs included in a submitted state plan.

B. Approaches for Adjusting EGU CO 2 

### Emission Rates
As discussed in the preamble, cred its or adjustment to an EGU CO 2 

### emission rate, based on the effect of RE and demand-side EE programs and measures, might represent avoided MWh of electric generation or avoided tons of CO 2 

### emissions. 23 

### If adjustment or credits represent avoided MWh, they would be added to the denominator of the lb CO 2 

### /MWh emission rate when determining an adjusted lb CO 2 

### /MWh emission rate. If adjustment or credits represent avoided
CO 2 

### emissions, they would be subtracted from the numerator when determining an adjusted lb
CO 2 

### /MWh emission rate. The approach chosen could affect the amount of credit or adjustment provided for RE and demand-side EE programs and measures. These implications are discussed
below.

1. Adjustment of CO 2 

### Emission Rate based on Avoided MWh
One approach is to adjust an EGU’s CO 2 

### emission rate based on avoided MWh of generation from an EGU, or cohort of EGUs, re sulting from RE and demand-side EE programs
and measures. 24 

### A MWh crediting or adjustment approach implicitly assumes that the avoided
CO 2 

### emissions come directly from the particular affected EGU (or group of EGUs) to which the adjustment or credits are applied. It assumes, in effect, that an additional emission-free MWh is being generated by that respective EGU, and that the RE or demand-side EE measure reduces
CO 2 

### emissions from that individual EGU or group of EGUs. 25 

### In practice, the average or marginal CO 2 

### emission rate in the power pool or identified region – representing the avoided
CO 2 

### emissions from the generating sources being displaced by a MWh of energy savings or a

23 The preamble solicits comment on the appropriateness of these different approaches, which are further elaborated in this section. 24 It should be noted that this was the process used by EPA for incorporating end-use energy efficiency, renewable energy, and nuclear energy when calculating state CO 2 emission performance goals for affected EGUs. As discussed in the preamble, states may have flexibility to use a di fferent approach when demonstrating the effect of these measures in a rate-based state plan. 25 As a result, the assumed avoided CO 2 emissions from an individual MWh of energy savings or generation from renewable energy will differ based on the reported CO 2 emission rate of the individual EGU to which the MWh is applied as an adjustment to its MWh output.

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21 MWh of renewable energy generation – could differ significantly from the calculated avoided
CO 2 

### emissions derived by adjusting the MWh output of an affected EGU. The following examples highlight these concepts.

Example 1 : Assume an EGU with a stack emission rate of 1,500 lb CO 2 

### /MWh generates 1,000 MWh. Also assume that 1,000 emission-free MWh credits for the effect of demand-side EE measures are added to the denominator when calculating the EGU’s adjusted CO 2 

### emission rate. The adjusted CO 2 

### emission rate is 1,500,000 lb CO 2 

### divided by 2,000 MWh, which equals a
CO 2 

### emission rate of 750 lb CO 2 

### /MWh. In this example, each MWh credit represents 750 lb of
avoided CO 2 

### emissions.

Example 2 : The same calculation applied to an affected EGU with a 2,000 lb CO 2 

### /MWh rate would yield a different result. In this instance the adjusted emission rate is 2,000,000 lb CO 2 

### divided by 2,000 MWh, which equals a CO 2 

### emission rate of 1,000 lb CO 2 

### /MWh. In this example, each MWh credit represents 1,000 lb of avoided CO 2 

### emissions.

2. Adjustment of CO 2 

### Emission Rate based on Avoided CO 2 

### Emissions
An alternative approach is to provide an adjustment to the CO 2 

### emission rate of an EGU, or cohort of EGUs, based on the estimated CO 2 

### emissions that are avoided in the power pool or identified region as a result of RE and demand-side EE programs and measures. This approach acknowledges that the avoided CO 2 

### emissions may come from the electric power pool or other identified region as a whole, rather than an individual EGU. The avoided CO 2 

### emissions are determined based on the MWh saved or generated, multiplied by a CO 2 

### emission rate for the power pool or region.

This CO 2 

### emission rate could be based on the average or marginal emission rate in the power pool, region, or state. A marginal avoided emission rate represents the generation that is displaced at the margin for every MWh saved or generated through an RE or demand-side EE program or measure. An average avoided emision ra te is based on either all fossil generation in a region or total generation. This approach assumes that every MWh saved or generated equally displaces generation from every generator in a power pool or region.

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22 Another approach that has been suggested by some stakeholders is crediting or adjustment based on the level of the rate-based emission limit for affected EGUs (or the overall rate-based level of emission performance for affected EGUs specified in a state plan). For example, under this approach, if the emission rate limit were 1,500 lb CO 2 

### /MWh, one MWh of energy savings or renewable energy generation would result in a credit or adjustment representing 1,500 lb of CO 2 

### that could be subtracted from the numerator of an EGU’s CO 2 

### emission rate. This approach assumes that affected EGUs jointly emit CO 2 

### from the stack on an average basis at this required compliance level (i.e., consistent with a “closed” averaging system), and that a MWh saved or generated avoids CO 2 

### emissions from affected EGUs at this average compliance level. 26



### 3. Other Considerations

Some of the CO 2 

### emissions avoided through RE and demand-side EE measures may be from non-affected EGUs. This may result because affected EGUs are only a subset of the fossil fuel-fired EGU fleet, which also includes (or will in clude) existing non-affected fossil fuel-fired EGUs, such as simple-cycle combustion turbines used to meet peak demand, as well as new fossil fuel-fired EGUs subject to emission standards under CAA section 111(b). Furthermore, as the fleet capital stock slowly turns over, affect ed EGUs under section 111(d) will comprise a slowly shrinking subset of the total fossil fuel-f ired EGU fleet. These dynamics may need to be addressed in a state plan when crediting or adjusting CO 2 

### emission rates of affected EGUs based on the effects of RE and demand-side EE measures. The approaches described in more detail later in this section may be able make these di stinctions between affected and non-affected fossil
fuel-fired EGUs.

26 This outcome might be expected in a closed averaging system, without the use of crediting or adjustment for the avoided emission effects of RE and demand-side EE meas ures. In this instance an EGU that emitted above the compliance rate would need to averag e its performance with (or submit tradable credits obtained from) an EGU that performed below the required rate. On balance, all EGUs subject to the emission rate limit would perform at or below the compliance rate.

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23 C. Methods and Tools for Quantifying Avoided CO 2 

### Emissions from End-Use Energy Efficiency and Renewable Energy

1. Introduction
There are a number of approaches for quantifying the avoided CO 2 

### emissions resulting from end-use energy efficiency and renewable energy (EE/RE) programs, requirements and

measures 27 

### in the electric sector. These approaches ra nge from the application of basic avoided emission rates to using sophis ticated electric sector models. 28 

### Annual average avoided emission rates have often been used for rough approximations of CO 2 

### emissions avoided from reduced electric energy use. 29 

### An annual average avoided emission rate assumes that EE/RE programs and measures reduce electric generation from all generating types on a proportional basis consistent with the generation mix in a region. A marginal emission rate represents the emission rate of an electric generating unit (EGU) or cohort of EGUs likely to be displaced by EE/RE measures (i.e., a marginal avoided emissions rate), based on the last unit(s) to come online to meet electricity load and the first unit(s) to be brought offline when electricity load is reduced.

The primary question underlying estimating CO 2 

### emissions reductions from EE/RE measures is the determination of which electric generators will be displaced (i.e. , cease generation or reduce generation output) in the presence of incremental EE/RE. This section briefly describes a range of avoided emission rates approaches, their underlying assumptions, and considerations associated with the use of different avoided emission rate approaches.

2. Average Emission Rate Approach
An average emission rate (typically expressed in tons of CO 2 

### /MWh) is usually understood to mean the average of all generators’ emissions rates, weighted by annual generation. The rate (r avg 

### ) is calculated as:

27 As used here, the term “EE/RE measures” refers to any program actions or regulatory requirements that result in the increased use of energy-efficient equipment or practices, or renewable energy generating resources. 28 Electric sector models include simulation dispatch m odels (i.e. production-cost models) and capacity expansion planning models. 29 See, for example, EPA “Household Carbon Footprint Calculator,” available at http://www.epa.gov/climatechange/ghgemissions/ind-calculator.html

.

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24 ݎ ௔௩௚ 

### ൌ ∑ ݁ ௜ ௜ 

### ∑ ݃ ௜

௜ 

### Where:

e = annual emissions (tCO 2 

### ) from all sources i and g = annual generation (MWh) from all sources i

. Because the average emission rate puts the sum of all generation in the denominator (as MWh), including nuclear, hydroelectric, and renewable generating resources, the rate fundamentally assumes that EE/RE reduces all generating types by an equal proportion, regardless of their type or contribution to the margin. 30 

### EGUs are generally dispatched on an economic merit order, where the least-cost EGUs (on a variable cost basis) are dispatched first, and higher cost resources are dispatched later. Since nuclear, hydr o, wind, and solar resources operate at a very low cost, 31 

### they are generally dispatched before most fossil units. 32 

### Under current and historical operating conditions, there are few circumstances in which non-fossil resources reduce output in the presence of lower demand. As a result, in states with a moderate contribution of non-emitting resources to total generation, the average emission rate may be lower than could reasonably be expected for reductions from EE/RE programs and measures. 33 

### Conversely, in states that have significant baseload fossil generation and few no n-emitting resources, a state-average emission rate may reflect an emission rate that is too high. This may occur by incorporating emissions from coal-fired EGUs that are less likely to reduce generation with a reduction in electricity load, compared with other lower-emitt ing fossil fuel-fired EGUs.

30 In other words, a two-percent reduction in energy use would cause all EGUs in the system to reduce generation output by two percent, including coal, gas, nucl ear, hydro, and renewable generating resources. 31 For representative variable costs for new EGU, see supporting documentation for the Electricity Market Module of the Annual Energy Outlook (AEO) 2013, table 8.2., “Cos t and performance characteristics of new central station electricity generating technologies”. Geothermal, wind, and solar generating resources are assumed to have a variable operating cost of $0/MWh. Hydroelectric generati ng resources have an assumed variable operating cost of $2.60/MWh and incur no fuel cost, while nuclear generating resources have an assumed variable operating cost of $2.10/MWh (exclusive of fuel costs). In contrast, gas a nd coal units are assumed to have variable operating costs from $3-$7/MWh (exclusive of fuel costs. 32 The exception is rare curtailment events for renewable resources when more energy is produced than required, and due to operational constraints, where wind turbines are stal led to maintain system energy balance. Renewable energy generators, such as wind and solar, are sometimes referred to as “non-dispatchable” resources, since the renewable energy resource is intermittent and these generators cannot be called upon to run when the renewable energy resource is unavailable. However, here we refer to ec onomic dispatch of these resources at times when the renewable energy resource is available. In these instances, th ese generators are often one of the first resources to be called upon, due to their low variable operating costs. 33 Counting hydroelectric, nuclear, and renewable resources in the denominator would re nder the emissions rate too low, and thus the avoided emissions smaller than actually realized.

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25 3. Marginal Emission Rate Approach
A marginal emission rate represents the emi ssion rate of the EGU or cohort of EGUs likely to be displaced by EE/RE ( i.e., an avoided emission rate). A marginal unit is the highestcost unit dispatched at any point in time. 34 

### Under most circumstances, and at any given time, the marginal unit is the last unit to be brought online to meet electricity demand and the first unit to be brought offline when electricity load is reduced. Due to constraints on generating unit ramp

rates 35 

### and transmission availability, it is not unc ommon for multiple units to be dispatched incrementally simultaneously, thus creating a cohort of marginal units. Marginal unit(s) change on a moment-to-moment basis, determined by load requirements and the variable cost of each unit available to generate another unit of power. A marginal unit can either be a unit brought online to meet load or may be an EGU that is alr eady operating, but that is dispatched at a greater level of output to meet load.

The marginal emission rate ( r marginal 

### ) can be expressed for any given hour ( t ) as a function of the difference between two distinct cases – the reference case ( i.e., in the absence of incremental EE/RE programs and measures) and the change case, where the EE/RE programs and measures have been implemented. A formula describing this rate is written as follows:

ݎ ௟௔௡௜௚௥௔௠,௧ 

### ൌ ∑ ݁ ௥௘௙,௜,௧ ௜ 

### െ ∑ ݁ ாாோா,௜,௧ ௜ 

### ∑ ݃ ௥௘௙,௜,௧

௜ 

### െ ∑ ݃ ாாோா,௜,௧ ௜



### Where:

e ref 

### and e EERE 

### = emissions (tCO 2 

### ) from EGUs i in hour t in the reference case ( ref ) and the change case ( EERE ), respectively; and g ref 

### and g EERE 

### = generation (MWh) from EGUs i in hour t in the reference case ( ref ) and the change case ( EERE ), respectively.

34 See EPA’s Roadmap for Incorporating EE/RE Policies and Programs in State Implementation Plans: Appendix B, available at http://www.epa.gov/statelocalclimate/doc uments/pdf/overview_paper_4-28-2011.pdf 35 Ramp rate refers to the ability of an EGU to respond to increasing load, based on its ability to increase output. Ramp rates are typically determined by technology type, wi th some technologies, such as combustion turbines, able to more quickly increase output in response to increasing load.

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26 The magnitude of the EE/RE program and the EE/RE load impact shape 36 

### is a key element in determining marginal emissions reductions . In order to obtain a valid estimate of the emission reduction effect of an EE/RE program, an annual marginal avoided emission rate should be calculated that reflects the EE/RE program’s load impact shape and magnitude. This annual marginal avoided emission rate may then be applied to other EE/RE programs with similar load impact shapes and magnitudes. The ma rginal emission rate is highly time sensitive, as are the impacts of EE/RE programs and measur es. For example, the EGU that is on the margin and is most likely to be displaced from EE/RE in each hour of the year. In addition, different EE/RE programs may have very different load impact shapes, reducing energy requirements in different hours of the year. The interaction between the pattern of EGUs on the margin and the load impact shape of EE/RE programs and measures results in a specific marginal avoided emission rate. Applying an annual marginal avoided emission rate calculated based on the impact of one specific set of EE/RE programs and measures to another set of EE/RE programs and measures that is substantively different in timi ng or magnitude of energy savings or generation (i.e ., with a different load impact shape and magnitude) may result in erroneous results ( i.e. the assumption that the wrong EGUs are displaced). 37



### Several mechanisms have been proposed to estimate the marginal emission rate without the use of a formal electric dispatch simulation model. These mechanisms rely on historic hourly generation and emissions data, collected by EP A’s Clean Air Markets Division, to estimate hourly marginal emissions rates for a past historical year. The benefit of these mechanisms is that they are simple to apply, but (a) are difficult to verify or validate without the benefit of a formal model and (b) rely on historical data and patterns of dispatch, which may not represent future patterns of dispatch.

36 The load impact shape of an EE/RE program or measure is the hourly (or, if necessary, daily or seasonal) pattern of either energy savings from an EE program or measure, or generation from an RE generator that is supplied to the grid. 37 For example, an EE program focused on measures that reduce peak electricity demand, such as more efficient air conditioning, or a solar RE program, may result in significan t reductions in electricity use from the grid during peak demand hours, and little electricity use reduction during ov ernight “trough” hours. In contrast, an industrial EE program may result in a relatively constant electricity load reduction over most hours. An EE program focused on peak reduction measures may reduce generating output from primarily peaking units, while an EE program targeting EE measures with a more constant load impact shape ma y significantly reduce baseload generation during overnight trough hours.

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27 4. Methods and Tools for Estimating Avoided CO 2 

### Emission Rates and Avoided CO 2 

### Emissions

4.1. Calculation Tool Method
The EPA has developed a user-friendly tool to estimate the emission reduction impacts of EE/RE requirements, programs and measures. The “ AVoided Emissions and geneRation Tool ” (AVERT) 38 

### was developed to help air quality planners quantify NOx and SO 2 

### emission impacts, as specified in EPA’s Roadmap for Incorporating EE/RE Programs in NAAQS SIPs. 39 

### AVERT can also be used to quantify the displaced CO 2 

### emissions of EE/RE measures within the
continental United States.

The AVERT method uses historical hourly emissions rates based on recent the EPA data on fossil fuel-fired EGUs’ hourly generation and emissions reported through EPA’s Acid Rain Program. 40 

### This method couples historical hourly generation and emissions with the hourly load reduction profiles of EE/RE programs and measures to determine hourly emissions reductions on the margin. AVERT can be used to estimate EE/RE-related emissions reductions in a current or near-future year. However, AVERT estimates for current or future years are based on historical behavior rather than projected economic behavi or. As a result, AVERT does not use projections of future fuel or electricity market prices that affected EGU dispatch, and is therefore not an appropriate tool for longer-term projections.

Users of AVERT can analyze how the different load profiles of a variety of EE programs and measures, as well as wind and solar technologies, affect the magnitude and location of CO 2 

### emissions at the county, state, and regional level. AVERT has a flexible framework with a simple user interface designed specifically to meet the needs of state air quality planners and
other interested stakeholders.

38 More information about AVERT, including documentation and a user’s manual, is available at (http://www.epa.gov/avert). 39 See Appendix I of the Roadmap for Incorporating Energy Efficiency/Renewable Energy Policies and Programs
,

available at http://epa.gov/airquality/eere/pdfs/appendixI.pdf ), for details about how this approach can be used in the different NAAQS SIP pathways. 40 http://ampd.epa.gov/ampd/. Deleted:

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28 AVERT may be used to derive marginal emission reductions from historical generation and emissions data, which can be used to derive a marginal avoided CO 2 

### emission rate. However, AVERT does not quantify average emissions rates. AVERT approximates historical dispatch behavior using a statisti cal algorithm. It does not repres ent transmission constraints, or significant changes in grid structures or futu re economic conditions. To estimate a recent historical marginal CO 2 

### emissions reduction from existing EE/RE programs or measures, a user would input the MWh related to results from EE/RE programs or measures (representing either MWh of electricity savings or MWh of generation) in a representative historical baseline year as a positive increment to electricity load, and record the emissions incrementally added in the
tool. 41 

### The calculated marginal CO 2 

### emission rate is the incremental CO 2 

### emissions added by AVERT, based on historical EGU dispatch pattern s, divided by the incremental MWh of EE/RE savings or generation input to AVERT as an increase in electricity load. This approach reflects the marginal impact of EE/RE measures based on historical recorded patterns of emissions and generation. 42



### 4.2. Electricity Sector Modeling Method

Quantification of avoided CO 2 

### emissions from EE/RE requirements, programs, and measures can be achieved through retrospective modeling approaches. Models can be used to
calculate avoided CO 2 

### emissions by comparing actual realized EGU CO 2 

### emissions to projected
EGU CO 2 

### emissions that would have occurred in a historical reference case that does not include implementation of the EE/RE that is being evaluated. The appropriate choice of model depends on the look-back period. For short look-back periods of one to three years, an electricity system simulation dispatch model can de termine the marginal generation contribution to emissions in a

41 Because AVERT represents a historical baseline year, EE and RE programs that occurred in a past year are already recorded by the statistics of AVERT. To estimate the emissions impacts of historic EE/RE programs, a user would increase the load by the EE/RE in crement to estimate what generation and emissions would have been in the reference case look-back year. 42 AVERT reflects fuel and emission control technologies to the extent they have influenced dispatch during the base year chosen. However, AVERT cannot change dispat ch based on future economic or regulatory conditions, such as expected fuel prices, emission allowance prices, or specific emissions limits. AVERT should not be used for this type of analysis. When used to review historical da ta, AVERT will capture the impact of historical fuel prices and other impacts on the variable cost of produc tion, but cannot capture specific emission limits.

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29 historical reference case ( i.e. absent incremental EE/RE programs). 43 

### Over the short term, simulation dispatch models properly account for EGU economic dispatch considerations, such as fuel and emission allowance prices, and operational constraints, such as ramp rates, outages, and heat rate curves. Look-back periods beyond three to five years would benefit from use of a utility-scale capacity expansion and dispatch plan ning model to understand the change in build out of new generating capacity, as well as transm ission and distribution infrastructure, and its impact on generation between the historical reference case and actual realized historical

outcome.

Electricity System Simulation Dispatch Models Quantifying the CO 2 

### emissions reductions achieved by EE/RE measures through
modeling of a near-term look-back period require s a counterfactual historical reference case
model run, which examines how the electric system would have operated in the absence of the

EE/RE emission reduction measures under considera tion. The emissions projected in this model
run may be compared against actual realized emissions during the historical period. The lookback model should be calibrated by running the same model with the EE/RE measures in place
and comparing the outcome of that model against realized generation and emissions at an
appropriate spatial scale. 44



### Simulation dispatch models can be readily run for historical years provided they are loaded with the accurate input assumptions, incl uding actual historic fuel costs, emission allowance prices, and transmission constraints. Wh ile these models will not choose economically optimal EGU retrofit or retirement decisions, they will provide a change in EGU dispatch and the associated change in emissions across a large region in a more detailed manner than capacity expansion planning models.

43 “Reference case” here refers to the case in which addi tional incremental carbon emi ssions reduction mechanisms are not employed, in this case resulting from EE/RE programs and measures. 44 Generally, simulation models will not capture exact output of individual EGUs relative to reality due to a variety of factors, including outages and other non-economic considerations not reflected in the model. Therefore, a comparison at an individual EGU scale may not be meani ngful, but aggregate emissions at a state or regional scale should be expected to be comparable.

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30 Simulation dispatch models may be most relevant as part of ex-post plan reporting, for estimating the avoided CO 2 

### emissions from affected EGUs that occurred as a result of EE/RE measures included in a plan, during a specified plan reporting period.

Utility-Scale Capacity Expansion and Dispatch Planning Models Quantifying the CO 2 

### emissions reductions achieved by EE/RE measures through modeling over a longer-term look-back period requires a counterfactual historical reference case model run, which examines how the electric syst em would have operated and have been built out, in the absence of the EE/RE measures under consideration. The critical difference between this type modeling approach and the use of a simulation dispatch model is the assessment of changes made at the “build margin” – i.e. , new additions to generating capacity that may have been avoided or compelled, or retirements of existing units that may not have occurred in the reference case. The emissions projected in this model run may be compared against actual realized emissions during the historical period . The look-back model should be calibrated by running the same model with the EE/RE measures in place and comparing the outcome of that model run against actual realized generation and emissions at an appropriate spatial scale.

Capacity expansion and dispatch planni ng models could be run for a longer-term historical period to better reflect what the el ectricity system would have looked like in the
absence of the EE/RE measures. When EE or RE resources have been added over the course of three to five years, these models will reflect ho w these resources have avoided new power plants, retrofits, or fuel switch decisions. Some models may also be able to reflect avoided transmission
investments.

Capacity expansion and dispatch planning models may be more relevant than simulation dispatch models for projecting the emission perform ance that will be achieved by affected EGUs under a plan. As discussed below, these models are able to assess both the “operating” and “build” margins that impact EGU CO 2 

### emissions as the result of EE/RE measures.

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31 5. Considerations Associated with use of an Avoided Emissions Rate
Operational versus Build Margin Avoided emission rates approaches that do not include a capacity expansion model all assume that EE/RE measures only impact the operational margin – i.e., they impact moment-tomoment operations of EGUs in the existing grid. While this is true, deployment of EE/RE over a period of years may have impacts beyond the operational margin. Deployment of significant EE/RE measures over time often impacts decision s to build new fossil ge nerating capacity, retire existing aging generating capacity, and make diff erent decisions about transmission expansion.
These different decisions about what infrastructu re to build or retire are known as the “build margin,” and may ultimately have a greater impact on long-term emissions outcomes than the operational margin.

While a new wind farm brought online next year has an impact on patterns of generation from existing fossil EGUs, decadal-scale planning associated with a policy meant to encourage EE/RE has an impact on the choice of whether or not to pursue the construction of new fossil generating capacity. A utility pursuing aggressive EE/RE programs may avoid the construction of new fossil generating capacity and expansion of transmission and distribution capability, and may even allow the utility to retire non-economic generating units no longer required for generation or reliability purposes.

The use of an avoided emissions rate calculated based on the operational margin alone may fail to represent the impact of EE/RE measures that occur at the build margin. This differentiation is particularly important in re gions where the pursuit of EE/RE measures may result in the retirement of high-emitting, non-economic generating assets. The use of a capacity expansion and dispatch planning model would he lp accurately assess avoided emissions due to changes at both the build and operational margins.

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32 Quantifying In-State versus Out- of-State Emissions Reductions The electric system is not confined by stat e boundaries, and emissions displaced by EE/RE measures may occur over a wide geographic area, 45 

### including outside of the state that implemented the EE/RE measures. Without the use of a simulation dispatch model (or, under some circumstances, use of a tool such as AVERT) 46 

### it can be challenging to attribute emissions
reductions that occur within th e implementing state versus emissions reductions that occur across state boundaries. If a state sought to recognize the effect of EE/RE measures and quantified emissions reductions using an approach that did not account for avoided emissions at an appropriate spatial scale, it may inappropriately account for emissions reductions that occur in other states, or conclude that all emissions reductions occur within the state’s boundaries. 47 

### In interconnected areas in which some states pursue mass-based emissions reductions approaches through their state plans while other states pursue rate-based approaches that include adjustment or crediting for avoided CO 2 

### emissions from implementation of EE/RE measures, avoiding double-counting of emission eff ects among states will be an important consideration when quantifying the avoided emissions resulting from EE/RE measures. These considerations are
discussed below in section VII of this TSD.

V. Quantification, Monitoring, and Verifi cation of End-Use Energy Efficiency and Renewable Energy Programs and Measures

As discussed in the preamble, in section VII.F.4, a key consideration for state plans is the process and requirements for quantifying, monito ring, and verifying the effect of renewable

45 See California Energy Commission, Emissions Reductions from Renewable Energy and Energy Efficiency in California Air Quality Management Districts (2011), available at ( http://ucciee.org/downloads/CAEmissionsReductions.pdf ). 46 AVERT captures the magnitude of in-state versus out-of -state emissions reductions, but may not be an accurate assessment tool for edge-cases – i.e. states that fall near the boundaries of the AVERT regions – because AVERT does not capture inter-regional transmission. 47 In the simplest case, a state without any fossil genera ting capacity that implements EE/RE measures would cause emissions reductions in neighboring states, and none with in its own borders. Similarly, a state with significant, predominantly baseload fossil generation may also cause littl e in-state emissions reductions from implementation of EE/RE measures because those emissions reductions may occur at marginal generators located outside of the state. Conversely, a state with significant marginal fossil gene rating capacity might realize reductions in emissions from EE/RE measures implemented in other states. These complications may arise regardless of if a state is a net importer or net exporter of energy. The key differentiation is if th e state’s EGUs are generally on the margin relative to interconnected EGUs in neighboring states. Comment [A5]: 2. Can renewable energy that is physically located in a state with a mass

‐ based policy be used for out

‐ of

‐ state compliance in a state with a rate

‐ based policy?

EPA response: This question is related to treatment of interstate emission effects, which is addressed later in section VII of the TSD.

Comment [A6]: 3. Commenters suggest separating the RE and EE EM&V discussion completely into separate sections. They are different issues. For EE, the Uniform Methods Project was developed to provide a national approach to EM&V. Commenters suggest citing UMP as an optional but preferred approach to EM&V and are willing to provide assistance.

EPA response: This section is divided into two subsections that address EE and RE separately. We have maintained both within a single major section of the TSD because state plans containing either enforceable RE or EE measures would be subject to a similar requirement to include an EM&V plan for those

measures in the state plan.

We have highlighted the role of the Uniform Methods Project (UMP) in subsequent edits later in this section.

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33 energy and demand-side energy efficiency measures that result in electricity generation or savings. 48 

### In the preamble, the EPA proposes that a state plan that includes enforceable RE and demand-side EE measures must include an evaluation, measurement, and verification (EM&V) plan that explains how the effect of these measures will be determined in the course of plan implementation. An EM&V plan will specify the analytic methods, assumptions, and data sources that the state will employ during the st ate plan performance periods to determine the energy generation and energy savings related to RE and demand-side EE measures. As discussed in the preamble, an EM&V plan would be subj ect to EPA approval as part of a state plan. In the preamble, the EPA also discusses its intent to develop guidance for acceptable EM&V methods that could be incorporated in an approvable EM&V plan included as part of an approvable state plan. The EPA seeks comment in the preamble on the critical features of such guidance, including scope, applicability, and minimum requirements, as well as the appropriate basis for
and technical resources used to establish such guidance, including existing state and utility protocols and existing international, national, and regional consensus standards or protocols. This section further elaborates these considerations discussed in the preamble , with individual subsections addressing RE and demand-side EE programs and measures

.

The appropriate type of EM&V for RE and demand-side EE programs and m easures will depend on the state plan approach. For states im plementing a mass-based portfolio approach, the effect of renewable energy and demand-side energy efficiency requirements, programs, and measures in helping to achieve the required level of CO 2 

### emission performance under a state plan will be directly evident in reductions in the monitored CO 2 

### emissions from affected EGUs. 49 

### In effect, the overall impact of these measures could be tracked through CO 2 

### emission monitoring, reporting, and record-keeping requirements applied to affected EGUs. However, for states implementing a rate-based plan approach, an approvable plan will need to include

48 In particular, this consideration applies to states impl ementing a rate-based emission limit approach that provides for adjustment of CO 2 emission rates based on the effect of end-use en ergy efficiency and renewable energy, as well as states implementing utility- or state-driven portfolio ap proaches that incorporate e nd-use energy efficiency and renewable energy requirements and programs. 49 There could be exceptions, for example where a st ate plan includes acknowledgement of avoided CO 2 emissions that occur outside state borders as a result of state plan measures. See section VII of this TSD for further discussion of the treatment of interstate effects. Comment [A7]: EPA: Note, this revised text conforms with revisions made to the preamble, at section VIII.F.4, in response to interagency comments. We have also made additional changes throughout this section to conform with the revised preamble text at section VIII.F.4.

Deleted:

Deleted: .seeks comment on the suitability of current state and utility quantification, monitoring, and verification approaches for end-use energy efficiency and renewable energy in the context of an approvable state plan, and on whether harmonization of state approaches, or supplemental actions and procedures, should be required in an approvable state plan. The preamble also discusses generally whether the EPA should establish good practice guidance for quantification, monitoring, and verification of renewable energy and demand-side energy efficiency measures included in an approvable state plan, and solicits comment on the content of such guidance.
Deleted: quantification, monitoring, and verification

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34 quantification, monitoring, and reporting requi rements related to RE and demand-side EE requirements, programs, and measures incorporated in a state plan.

Utilities and states have conducted ongoing EM&V of end-use energy efficiency and renewable energy measures and programs for several decades. These evaluations, which include quantification, monitoring and verification of results, generally rely upon a well-defined set of industry -standard practices and procedures. However, measurement approaches vary by state based on multiple factors, including the measure and program type being evaluated, the level and nature of regulatory oversight, the degree of stat e and utility experience with these measures and programs, and the overall magnitude of program impacts.

This section of the TSD discusses current st ate and utility evaluation, monitoring, and verification approaches for end-use energy efficiency and renewable energy programs and mandates. This section also discusses the potential suitability of these approaches in the context of an approvable state plan, and whether harmon ization of state approaches, or supplemental actions and procedures, might be warranted in an approvable state plan. In particular, this section
discusses considerations related to the establishment of requirements and guidance for quantification, monitoring, and verification of en d-use energy efficiency and renewable energy measures for an approvable state plan. It also discusses the possible appropriate basis for and
resources used to establish such requirements and guidance. This discussion includes consideration of existing state and utility protocol s, as well as any international, national, and regional consensus standards or protocols.

This section also discusses the types of end- use energy efficiency and renewable energy measures and programs for which EM&V of results is relatively straightforward. Such approaches might be subject to streamlined review of EM&V protocols included in an approvable plan, provided that such protocols are applied in accordance with EPA requirements and guidance . For example, many utilities have implemented a similar core set of end-use energy efficiency and renewable energy measures and prog rams for utility customers. For these types of measures and programs, a substantial base of experience has been established nationally for quantification, monitoring, and verification of measure and program outcomes. Deleted: evaluation

Deleted: good practice guidance or

Deleted: , if the EPA were to take this approach

Deleted: quantification, monitoring, and verification

Deleted: quantification, monitoring, and verification
Deleted: industry best practices

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35 In the preamble, at section VIII.F.4, the EPA notes that it is not proposing to limit the types of RE and demand-side EE programs and measures that may be included in a state plan. However, less established types of measures and programs, such as new and innovative demandside EE programs that seek to alter consumer and building occupant behavior may pose quantification and verification challenges. Still ot her types of measures, such as state energyefficient appliance standards and building codes, have not typically been subject to similar evaluation of energy savings results. These types of approaches may have substantial impacts, but may require additional documentation of EM&V methods in accordance with EPA guidance, including development of appropriate quantification, monitoring, and verification protocols if they do not currently exist

. Deleted: Oother

Deleted: those

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36 A. Quantification, Monitoring, and Veri fication for End-Use Energy Efficiency

1. Introduction
For rate-based state plans, a key element of the plan is a demonstration of how the state, and related entities with enforceable obligations under the plan, will measure and verify energy savings to be achieved the through the implementation of end-use energy efficiency measures incorporated in the plan. 50 

### In the context of demand-side energy efficiency programs currently overseen by state PUCs, this function is typically addressed through an evaluation, measurement, and verification plan (EM&V plan). This sec tion discusses current state and utility EM&V practice for end-use energy efficiency programs and discusses considerations related to acceptable EM&V plan s and evaluation approaches for a state plan under CAA section 111(d).

2. Background on Evaluation, Monitoring, and Verification (EM&V) of Energy Efficiency Measures

From the time that demand-side energy efficiency (EE) emerged as an important energy strategy in the 1970s, 51 

### efforts to evaluate the impacts of EE actions have been critical to their success, credibility, and expansion. Starting with measurement and verification (M&V) of individual projects, these efforts have evolved to the point where there is now a mature and rigorous evaluation, measurement, and verifica tion (EM&V) industry. This industry includes many professional firms, protocols and guidelines, training and certification programs, regulatory oversight, and established conferences with a rich library of published reports and publically available data and analyses.

State agencies responsible for planning, implementing, and evaluating demand-side energy efficiency programs and polici es utilize EE savings values, as follows: 52

50 In this section we use the term “end-use energy efficien cy measure” or “energy efficien cy measure” to refer to an end-use energy efficiency requirement (such as an EERS), and energy efficiency program, or individual installed energy efficiency measure, such as installation of an energy-efficient air conditioner through an energy efficiency program. 51 National Energy Program Fact Sheet on the President's Program, April 20, 1977. 52 State and Local Energy Efficiency Action Network. 2012. Energy Efficiency Program Impact Evaluation Guide

. Prepared by Steven R. Schiller, Sch iller Consulting, Inc., available at http://www.seeaction.energy.gov

. Deleted: possible

Deleted: protocol

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37  Projected savings: values reported by a program implementer or administrator before the efficiency activities are completed

 Claimed savings: values reported by a program implementer or administrator after the efficiency activities have been completed, prior to independent evaluation of savings

 Evaluated savings: values reported by an in dependent third-party evaluator after the efficiency activities and an impact evaluation have been completed.

Both claimed and evaluated energy savings involve real-time and/or retrospective assessments of the performance and implementation of an energy efficiency program or a portfolio of programs. Important impacts for evaluation include energy and demand savings and non-energy benefits (e.g., avoided emissions, health benefits, job creation and local economic development, energy security, transmission and distribution benefits, and water savings). Impact evaluations also support cost-effectiveness analys es aimed at determining the value of energy efficiency programs to utility cu stomers and identifying relative program costs an d benefits of energy efficiency compared to other energy resources, including both demand- and supply-side options.

Regardless of how the energy savings of an energy efficiency measure are determined, all energy savings values are estimates of savings and not directly measured. Savings are determined by comparing energy use after an ener gy efficiency project or measure is installed (the reporting period) with what is assumed to be the energy use in the absence of the project or measure (the “counterfactual” scenario, or baseline). Savings therefore depend critically on baseline assumptions, which are necessarily estimated with varying degrees of accuracy. Figure 1-1 illustrates this concept.

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38 Figure 1. Energy Use Before, During, and After an Energy Efficiency Project is Installed 53



### 3. Current EM&V Practices in States
3.1 EM&V for Demand-Side Energy Efficiency Programs Overseen by State PUCs
Current practice with EM&V for demand-side energy efficiency programs in the U.S. is primarily defined by state utility commission (PUC) 54 

### requirements for customer-funded efficiency programs. The level of PUC oversight varies from state to state, but this oversight process has generated the majority of the industry guidance and protocols for documenting energy savings from energy efficiency programs. Typically, impact evaluation reports are prepared based on the requirements established by PUCs and submitted (usually annually) for PUC review, approval, and use in resource planning and performance assessment. According to a recent survey, most states (79 percent) rely on independent consultants and contractors to conduct evaluations, while some states (21 percent) use utility and/or government agency staff. 55

53 Ibid. 54 In some states these government entities are referred to as a public service commission (PSCs) or board of public utilities (BPU), as well as other names. 55 Kushler, M.; Nowak, S.; Witte, P. , A National Survey of State Policies and Practices for the Evaluation of Ratepayer-Funded Energy Efficiency Programs, American Council for an Energy-Efficient Economy (ACEEE) (February 2012), Report Number U122 Available at http://www.aceee.org/ research-report/u122.

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39 The range of EM&V budgets varies signifi cantly between states, typically from two percent to six percent of total energy efficiency program expenditures. 56 

### The average EM&V budget in 2011 was about 3.6 percent of program expenditures. Reasons for this disparity may include the fact that as states expand energy efficiency programs, they may implement more complex programs, which require additional EM&V. 57 

### EM&V effort in states also typically increases as the magnitude of program expenditures and energy savings impacts increase, and as states and utilities gain experience in im plementing energy efficiency programs.

States at the low end of this EM&V expenditure range typically rely heavily on deemed savings approaches, which are a common and relatively low-cost strategy for documenting energy savings. Deemed savings are measure-sp ecific stipulated values based on historical and verified data (in some cases using the results of prior EM&V studies). Unlike other EM&V approaches, with deemed savings there are no – or very limited – measurement activities. Instead, only the quantity of energy efficiency measures implemented is verified (e.g., number of motors installed correctly, number of energy-efficient air conditioners that were purchased using a program rebate). The verified installed energy efficiency measures are then multiplied by the estimated (or deemed) energy savings per measure to derive energy savings for each measure and energy savings for the total number of measures installed through an energy efficiency program. The use of deemed energy savings is only considered appropriate for efficiency actions with well-known characteristics. A variant of this approach is the deemed savings calculation
, which involves the use of one or more agreed-upon (stipulated) engineering algorithms used to generate energy and/or demand savings associated with energy efficiency measures. These calculations may include predetermined assumptions for one or more parameters in the algorithm, but typically require users to input data associated with the actual installed measure into the algorithm. 58

56 Wallace, P.; Forster, H.J. (2012). State of the Effici ency Program Industry Budgets , Expenditures, and Impacts 2011. Consortium for Energy Efficiency. www.cee1.org/files/2011 CEE An nual Industry Report.pdf

. 57 Expansion of energy efficiency programs may also lead to a reduction in EM&V costs per unit of energy savings, as programs achieve economies of scale and experience in conducting EM&V activities. 58 Examples of equipment types that are commonly evaluate d using deemed savings values and calculations include energy-efficient washing machines, computer equipment, and refrigerators, and lighting retrofit projects with wellunderstood operating hours. For deemed savings calculati ons, evaluators collect information about the actual Comment [A8]: The opposite effect can also be

seen: additional programs mean more experience with EM&V and hence reduced costs.

EPA response: We have added a footnote in response to this comment.

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40 The deemed savings values, themselves, are typically centrally located in a “Technical Reference Manual” (TRM). The content and format of these TRMs vary, but in most cases consists of a database of standardized, state- or region-specific algorithms (deemed calculations) and associated energy savings estimates (deemed savings values) for energy efficiency measures. TRMs also include various data assumptions, sample calculations, and other inputs that the state uses to develop energy savings values for the range of energy efficiency programs in place. The benefits to energy efficiency program administrators of using a TRM include reduced EM&V costs and greater certainty regarding projected, claimed, and evaluated energy savings values (see definitions above). There are about 20 states currently using TRM databases. 59



### It should be noted that TRM values for individual energy efficiency measures are not always formally vetted in a regulatory process, although this is a good practice. 60 

### A recent survey of TRMs found that deemed energy savings values for comparable energy efficiency measures vary across states and regions. 61 

### The reasons for these variations include the use of different calculation methodologies, technical a ssumptions, and input variables. Some of these differences are expected based on relevant differences in weather and baseline assumptions (e.g., existing building stock and common practices vary from one state to another). However, other differences are related to out-of-date input assu mptions and calculation errors. In the context of state plans, this variation, and in particular data quality issues with some TRMs, raises consideration of whether complete reliance on ex isting TRM resources for state plans is prudent and appropriate, including how such reliance could or should be circumscribed.

In addition to the use of deemed savings, states on the higher end of the EM&V expenditure range rely to a greater extent on a variety of direct measurement approaches for documenting energy savings. Rather than mandating which EM&V methods must be used in a

installed measures -- such as hours of usage, wattage, and/or equipment capacity -- and combine this with predetermined assumptions in the algorithm. 59 State and Local Energy Efficiency Action Network, Scoping Study to Evaluate Feasibility of National Databases for EM&V Documents and Measure Savings , 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. (June 2011), available at http://www.eere.energy. gov/seeaction/pdfs/ emvscoping__databasefeasibility.pdf. 60 State and Local Energy Efficiency Action Network, Energy Efficiency Program Impact Evaluation Guide
, prepared by Steven R. Schiller, Schiller Consulting, Inc. (2012), available at http://www.seeaction.energy.gov

. 61 Ibid.

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41 particular situation, PUCs typically allow uti lities and other program administrators to select from a range of appropriate EM&V approaches that are consistent with standard practice in the energy efficiency industry. EM&V analyses and cal culations are then carried out, in most cases by an independent, third-party evaluator, throu gh a process that is unbiased, uses technically rigorous methods, effective peer review, and is subject to public review and comment. In addition, energy savings are frequently certified by the PUC as compliant with requirements defined in a pre-approved EM&V plan.

EM&V requirements in states with the most experience implementing and overseeing energy efficiency programs are typically based upon the following industry best practices:

 Use of one or more of the industry-standard EM&V protocols or guidelines (listed below), as well as the use of deemed sa vings values for well-understood energy efficiency programs and measures

 Consideration of local factors, such as climate, building type, and occupancy.

 Involvement of stakeholders and solicitation of expert advice regarding EM&V processes and resulting energy savings impacts.

 Conduct of EM&V activities (e.g., direct equipment measurements, application of deemed savings, and reporting of impacts) on a regular basis.

 Provision of interim and annual reporting of achieved energy savings.

Despite this well-defined and generally accepted set of industry best practices, many states with energy efficiency programs use different input values and assumptions (e.g., net versus gross savings, run-time of equipment, measure lifetime) in applying these practices. This can result in significant differences in claimed energy savings values for similar energy efficiency measures between states, even when the same measure type is installed under otherwise identical circumstances. In response to a growing awareness of this lack of cross-state comparability, policy makers, regulatory agencies, and other stakeholders are increasingly advocating for the use of common evaluation approaches across jurisdictions. Several national and regional EM&V efforts have emerged to promote collaboration and information sharing across states. These initiatives include the Northeast Energy Efficiency Partnership’s (NEEP)

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42 EM&V Forum, which is active in New England, New York, and the Mid-Atlantic, and the Pacific Northwest’s Regional Technical Forum (R TF). Both efforts aim to promote multi-state coordination in EM&V practices, make EM&V results more transparent and publicly available, and support the adoption of similar definitions, methods, and input assumptions. 62



### In addition to stakeholder efforts to promote EM&V collaboration and information sharing, a growing number of EM&V protocols and guidelines, some of which have recently been developed, are being used in the U.S. to promote greater consistency of measurement techniques and methodologies:

a. b. U.S. DOE Uniform Methods Project (UMP) Protocols 64



### c. International Performance Measurement and Verification Protocol (IPMVP) 65



### d. Federal Energy Management Program (FEMP) M&V Guidelines 66



### e. American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Guideline 14, Measurement of Energy and Demand Savings 67



### f. California Evaluation Protocols 68



### g. ISO New England (ISO-NE) Manual for Measurement & Verification of Demand

Resources 69

62 For a list of EM&V resources, including more informa tion about these regional EM&V collaboratives, see http://www1.eere.energy.gov/seeaction/evaluation.html

. 64 U.S. Department of Energy (DOE), Uniform Methods Project (April 2013) , available at: http://energy.gov/eere/about-us/initiatives-and-projects/uniform-methods-project-determining-energy-efficiencyprogram-savings

. 65 Efficiency Valuation Organization (EVO), International Performance Measurement and Verification Protocol (2012), available at: http://www.evo-world.org/. 66 FEMP, M&V Guidelines: Measurement and Verification for Federal Energy Projects, Version 3.0 (April 2008), available at: https://www1.eere.energy.gov/femp/pdfs/mv_guidelines.pdf

. 67 American Society of Heating, Refrigerati ng and Air-Conditioning Engineers (ASHRAE), Guideline 14: Measurement of Energy and Demand Savings (June 2002) , available at: https://gaia.lbl.gov/people/ryin/public/Ashrae_guideline14- 2002_Measurement%20of%20Energy%20and%20Demand%20Saving%20.pdf

. 68 California Public Utilities Commissions (CPUC), California Energy Efficiency Evaluation Protocols: Technical, Methodological, and Reporting Requirements for Evaluation Professionals (2006), available at: http://www.calmac.org/events/EvaluatorsProtoco ls_Final_AdoptedviaR uling_06-19-2006.pdf. Moved down [1]: International Performance Measurement and Verification Protocol (IPMVP) 63 ¶

Moved (insertion) [1]

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43 h. PJM Energy Efficiency Measurement and Verification Manual 70



### i. State and Local Energy Efficiency Action Ne twork, Energy Efficiency Program Impact
Evaluation Guide 71 

### j. U.S. DOE Superior Energy Performance M easurement and Verification Protocol for Industry 72



### While many states are currently relying upon these protocols and guidelines, other states and regional organizations (e.g., ISOs and RTOs) take the additional step of specify ing accuracy and uncertainty requirements for energy savings estimates. For example, ISO-NE requires that energy efficiency bids into its Forward Capacity Market (FCM) ensure that impact evaluations achieve ±10 percent statistical precision at the 80% confidence interval (see below for more on FCMs).

Regardless of the evaluation approach followed, the majority of state PUCs and energy efficiency program administrators aim to strike a balance between the transaction costs of EM&V activities (i.e., expense, time, staff effo rt) and the resulting reliability, validity, and usefulness of the estimated energy savings re sults. The appropriate balance between EM&V costs and the rigor of EM&V – and the related cer tainty of energy savings estimates – is often determined based on the type of program (including program purpose and goals), level of program expenditures, and magnitude of anticipated energy savings.

3.2 EM&V for Energy Efficiency Measures used in ISO Forward Capacity Markets
Two Independent System Operators (ISOs) re sponsible for operating regional electricity grids and overseeing wholesale electricity markets in certain regions of the country have

69 ISO-New England (ISO-NE), Measurement and Verification of Demand Reduction Value from Demand Resources (2013), available at http://www.iso-ne.com/rules_proced s/isone_mnls/MMVDR/index.html. 70 PJM, Manual 18B: Energy Efficiency Measurement & Verification (2010) , available at http://www.pjm.com/~/media/documents/manuals/m18b.ashx

. 71 U.S. DOE State and Local Energy Efficiency Action Network (SEE Action), Energy Efficiency Program Impact Evaluation Guide (December 2012), available at: http://www1.eere.energy.gov/seeaction/pdfs/emv_ee_program_impact_guide.pdf. 72 U.S. DOE, Superior Energy Performance Measurement and Verification Protocol for Industry (2012), available at: http://superiorenergyperformance.en ergy.gov/pdfs/sep_mv_protocol.pdf. Comment [A9]: EPA: Added based on interagency comment.

Comment [A10]: This approach is not separate from or inconsistent with the listed guides. Please clarify the language.

EPA response: We have made edits in response to this comment to clarify this point.

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44 established forward capacity markets (FCMs) that pay suppliers to ensure sufficient electric generating capacity is available to meet future peak electricity demand. In operating these markets, ISO New England (ISO-NE) and PJM both allow demand-side energy efficiency programs and other demand-side resources to compete directly with electric generators to meet the regional capacity needs. One requirement for utilities and other energy efficiency program administrators seeking to bid into the market is to submit an evaluation plan. ISO acceptance of this evaluation plan “qualifies” energy efficiency programs and projects as prospective market resources. The evaluation plan specifies the amount of energy and demand savings to be delivered over the contract period (typically three years into the future), and documents how the requirements of the ISO’s M&V standards manual will be satisfied.

Based on experience to-date, states bidding their energy efficiency programs into both the ISO-NE and PJM forward capacity markets are typically subjected to EM&V requirements that go beyond the evaluation already conducted for the purpose of meeting PUC requirements. This is because, while PUCs typically require evaluation protocols and procedures for documenting the cost-effectiveness of annual energy (MWh ) savings, FCMs require the measurement and verification of capacity (MW) savings during specific peak demand hours. In addition to the evaluation of energy savings, a separate set of measurement techniques and data collection protocols are required to document peak demand reduction impacts. Furthermore, attaining the level of statistical precision and confidence de scribed above typically requires additional sampling 73 

### than is required by PUCs. One considerat ion is whether EM&V requirements in ISO capacity markets include components that woul d facilitate better estimation of avoided CO 2 

### emissions related to energy efficiency programs include in state plans.

For the states located in ISO-NE and PJM, the common evaluation requirements for FCM participation have created an impetus for regional collaboration on EM&V practices. New England and Mid-Atlantic states continue to wo rk together to establish consistent evaluation protocols through the creation of an “EM&V Forum,” which is convened by the Northeast

73 With additional sampling requirements, energy efficiency program evaluators are typically required to measure a larger percentage of the energy efficiency measures instal led within the total population of all measures installed through an energy e fficiency program.

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45 Energy Efficiency Partnerships (NEEP) and supports common evaluation methods, reporting metrics, and cost sharing on research studies. 74 

### The Forum also serves as a venue for information exchange to address common EM&V challeng es encountered with FCM participation.

74 More information about the EM&V Forum is available through Northeast Energy Efficiency Partnerships, at https://neep.org/emv-forum/index

.

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46 3.3 EM&V for Programs and Policies Not Typically Overseen by PUCs
In contrast to energy efficiency programs overseen by PUCs, EM&V is less common for other types of energy efficiency requirements or programs, especially for minimum energy efficiency requirements that do not involve the expenditure of electricity ratepayer dollars. Examples include building energy codes, appliance efficiency standards, various energy efficiency financing programs, behavioral change programs, and market transformation programs that target both the suppliers of energy-efficient products and increasing consumer demand for those products. While these approaches often have substantial impacts in reducing

energy use, they may also face EM&V challenges. In some cases, appropriate evaluation protocols and approaches have not been developed for some programs and measures. In cases where appropriate EM&V methods do exist, there may also be less experience applying them. 75



### 4. Considerations for EM&V of End-Use Ener gy Efficiency Programs and Measures in
State Plans

A key consideration for state plans is the process and requirements for EM&V of RE and
demand-side EE measures that result in electrici ty generation or savings. As described in the preamble, at section VII.F.4, the EPA in tends to develop guidance on acceptable methods that can be incorporated in an EM&V plan included as part of an approvable state plan. Critical features of such EM&V guidance, including sc ope, applicability, and minimum criteria, are
discussed in this section.

4.1 Accuracy of Energy Savings Estimates
To document and verify that avoided CO 2 

### emissions from energy efficiency programs and measures are real and persistent, impact eval uation must be rigorous and transparent. Impact assessment should also consider the appropriate balance between certainty of results and the EM&V costs to achieve a specified level of certainty. Because energy savings data are estimates , their use as part of the basis for determining the avoided CO 2 

### emissions resulting from energy

75 Examples of such EM&V methods are described in the PNNL report, “Building Energy Codes Program: National Benefits Assessment: 1992-2040.”; and in Meyers et al, “Energy and Economic Impacts of U.S. Federal Energy and Water Conservation Standards Adopted From 1987 through 2012” LBNL-6217E. Deleted: may

Deleted: many currently Comment [A11]: This text may overemphasize EM&V challenges for this subset of measures. For example, extensive analysis goes into appliance standards, both ex ante to set the standard and ex post when standards are reviewed for possible update.

EPA response: We have made edits to this text in response to this comment.

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47 efficiency programs and measures in a state plan will depend upon the level of accuracy of this information. Therefore, evaluation results should be reported as “expected values”—that is, energy savings values are expected to be correct within an associated range of certainty. Key considerations for EM&V of energy efficiency programs and measures in state plans are similar to those faced in the design of any program evaluation approach: (1) the level of certainty that is required given a program’s objectives and requirements, and (2) how achievement of that

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48 necessary level of certainty is balanced with the amount of effort (e.g., resources, time, money) used to obtain that level of certainty.

4.2 EM&V Technical Considerations for State Plans
Using energy efficiency requirements, program s, and measures as an emission reduction approach in state plans requires considerat ion of several evaluation-related technical considerations. The following sections describe these considerations.

4.2.1 Qualifying Demand-Side Energy Efficiency Actions

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49 States are currently implementing a wide range of demand-side energy efficiency requirements, programs, and measures. However, EM&V of some of these programs and measures are associated with greater levels of measurement precision and certainty than others, based in part on the EM&V procedures currently in place. For example, energy efficiency programs subject to PUC oversight and review are frequently evaluated using rigorous evaluation procedures that are based upon several decades of research and experience. These energy efficiency programs are subject to a quasi-judicial, public, and transparent review process, which can lead to adoption of EM&V protocols that convey a relatively high level of certainty for EM&V results.

In contrast, other energy efficiency requirements and measures, some of which may result in very significant and cost-effective energy savings (e.g., building energy codes, local tax credits, EE loan programs, etc.), are not subject to PUC oversight and typically have comparably fewer EM&V requirements. There are also some newer EE program designs (e.g., certain behavior-based programs and some market transformation programs 76 

### ) for which rigorous EM&V methodologies or a track record of energy savings persistence do not yet exist. 77

76 Behavior-based energy efficiency programs aim to affect consumer energy-use behaviors in order to achieve energy and/or peak demand savings. Techniques to measure the impacts of these program designs are emerging and currently under development. Market transformation programs are characterized by strategic intervention in a market to address market barriers and market failures to accelerate market adoption of energy-efficient technologies and practices, and create lasting market change. While market transformation approaches can have very high energy savings impacts, by creating sustained deployment of energy-efficient technologies and practices, evalua tion of these strategies is challenging due to the involvement of numerous market players and the multi-year timeframe for achieving energy savings. 77 We note that EM&V approaches and protocols for behavior-based end-use energy efficiency programs do exist, but they have not been widely applied. For examples, see State and Local Energy Efficiency Action Network (SEE Action), Evaluation, Measurement, and Verification (EM&V) of Re sidential Behavior-Based Energy Efficiency Programs: Issues and Recommendations (2012), Prepared by A. Todd, E. Stuart, S. Schiller, and C. Goldman, Lawrence Berkeley National Laboratory. Available at http://www1.eere.energy.gov/seeaction/pdfs /emv_behaviorbased_eeprograms.pdf.

77 We note that EM&V approaches and protocols for behavior-based end-use energy efficiency programs do exist, but they have not been widely applied. For examples, see State and Local Energy Efficiency Action Network (SEE Action), Evaluation, Measurement, and Verification (EM&V) of Residential Behavior-Based Energy Efficiency Programs: Issues and Recommendations (2012), Prepared by A. Todd, E. Stuart, S. Schiller, and C. Goldman, Deleted: various

Comment [A12]: One commenter suggests behavior based programs have been used for decades. Evaluation approaches exist for them, for example, http://www1.eere.energy.gov/seeaction/pdfs/emv_ behaviorbased_eeprograms.pdf.

EPA response: We have made edits to this text in response to this comment and have added a footnote referencing the existence of EM&V protocols for behavior

‐ based programs.

Deleted: ¶

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50 As discussed in the preamble, while the EPA does not intend to limit the types of RE and demand-side EE measures and programs that can be included in a state plan – provided that supporting EM&V is rigorous, complete, and consistent with EPA requirements and guidance – the level and type of documentation required by EPA in an approvable state plan may depend on whether EM&V practices for that type of program or measure are well established. One option for organizing these variations in EM&V practices is with a qualitative hierarchy, as follows:

 EM&V procedures and protocols well established – for example, rebate and direct install programs for appliances , HVAC, and lighting equipment

 EM&V procedures and protocols moderately well established – for example, building codes and standards

 EM&V procedures and protocols less well established – for example, building disclosure and labeling programs

Table 2 provides an illustrative characterizatio n of the relative level of EM&V uncertainty for different types of energy efficiency programs and measures under this approach. This information is illustrative and generalized . In particular, there are numerous exceptions to the categorization of the relative uncertainty of EM&V results for different types of programs
and measures listed in Table 2

.

Table 2. Illustrative Characterization of EM&V Procedures and Protocols for Common Energy Efficiency Programs and Polic i es 78



### EM&V Procedures and EM&V Procedures and EM&V Procedures and

Lawrence Berkeley National Laboratory. Available at http://www1.eere.energy.gov/seeaction/pdfs /emv_behaviorbased_eeprograms.pdf.

78 This table is intended as a generalized description, ba sed upon numerous conversations with professional energy efficiency program evaluators. It should be noted that there are states with building energy codes, behavior programs, and market transformation programs that are well documented and subject to rigorous EM&V. In addition, such characterizations will change over time, as EM&V approaches for new and innovative programs and measures become standard practice. 79 This includes energy efficiency progr ams and measures for which there is significant experience with EM&V, a robust set of existing EM&V studies and reports, and relatively straightforward EM&V approaches. Deleted: W

Deleted: 4.1

Comment [A13]: The three tier approach for relative establishment of EM&V approaches could be problematic. Some of the approaches in the middle column on page 47, such as building commissioning and CHP, have well established procedures. The discussion seems to omit EM&V currently used by the ESCO industry. If a tiered approach were used, it would need to be updated

over time as new approaches become standard practice. Has EPA considered that and how it will be done?

EPA response: We have made edits to this subsection and table 2 in response to this comment. We have also added text acknowledging the need to update such categorization over time as EM&V becomes standard practice for different types of EE programs and measures. Finally, we note that the text states that Table 2 is intended to be illustrative only, not a definitive indication of the degree to which EM&V protocols are established for different types of EE programs and measures. Deleted: 4.1

Deleted: ¶

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51 Protocols Well Established Protocols Moderately Well Established Protocols Less Well Established

 Direct install incentive programs for building equipment (retrofits and new construction), including:

o lighting

o heating, ventilation, and air conditioning (HVAC)

o refrigeration

o motors

 Consumer-direct and mid-stream rebates forENERGY STARcertified lighting, appliances (including residential refrigerator recycling), and HVAC equipment

 Building commissioning and retro-commissioning

 Incentives for certified energy-efficient residential new construction, such as ENERGY STAR Homes

 Combined heat and power (CHP) installations/retrofits

 Electrical distribution system and transmission system upgrades  Building energy codes (requirements and incentive programs for new construction, remodels)

 State government building/operations programs (procurement, design standards, etc.)

 Product-specific upstream market transformation programs directed at manufacturers

 Industrial energy efficiency new construction or retrofits  General education programs for consumers, contractors, distributers, suppliers

 Targeted training programs

 Building labeling and disclosure programs

 Targeted consumer behavior programs

As discussed in the preamble, at section VIII.F.4, EPA is proposing to allow a wide (or unlimited) set of energy efficiency program and measure types in state plans, as long as the energy savings are adequately documented according to rigorous EM&V methods and appropriate state regulatory oversight. Recognizing these variations in EM&V procedures and protocols, one option for EM&V requirements and guidance for state plans is to streamline Deleted: mid-stream and

Deleted: 

### <#> Building commissioning and retro-commissioning ¶

Deleted: 

### <#> Combined heat and power (CHP) installations/retrofits¶ Deleted: Point-of-sale product sales

Deleted: or Deleted: limit the eligible types of energy efficiency programs and measures that could be included in a state plan to

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52 review of EM&V plans for a pre-defined list of well-understood program types for which evaluation is straightforward and energy savings results are subject to a relatively low level of uncertainty. 79 

### Other programs and measures with less well developed EM&V approaches would require greater documentation in state plans of EM&V methods that will be applied. This proposed approach is intended to maximize state flexibility and accommodate the full range of state energy efficiency programs, while simultaneously maintaining EM&V rigor and transparency. As discussed in the preamble, at section VIII.F.4, EPA is also taking comment on the option of limiting the eligible types of energy efficiency programs and measures that could be included in a state plan to a pre-defined list of well-understood program types for which evaluation is straightforward and energy savings results are subject to a relatively low level of uncertainty.

4.2.2 Avoided Transmission and Distribution (T&D) Losses from End-Use Energy Efficiency Measures

In general, the difference between the amount of electricity input to the transmission system by an EGU and the amount ultimately de livered to an end-user constitutes transmission and distribution (T&D) line losses. 80 

### According to EIA data, nationally, annual electricity
transmission and distribution losses are equivalent to about seven percent of the electricity that is input to the transmission sy stem in the United States. For every unit of energy use avoided at the end-use site, energy efficiency also avoids the lo sses that would otherwise occur as electricity is delivered to consumers through the T&D system. 81 

### Many state PUCs are aware of this
additional benefit of demand-side energy efficiency programs, and actively credit program energy savings results to account for program contributions to avoided line losses, albeit using a range of measurement approaches and calculations. A consideration for EM&V requirements

79 This includes energy efficiency pr ograms and measures for which there is significant experience with EM&V, a robust set of existing EM&V studies and reports, and relatively straightforward EM&V approaches. 80 The T&D system includes all the power lines and related equipment used to deliver electricity from an electric generating plant to an end-use site. Along the way, some of the supplied by the generator is lost due to the resistance of the wires and equipment that the electricity passes throu gh, as well as reactive power losses in alternating current systems due to inductance and capacitance. Most of this lost energy is converted to heat. The magnitude of losses in the T&D system depends on the physical ch aracteristics of the system in question, as well as how it is operated. 81 U.S. EPA, Assessing the Multiple Benefits of Clean Energy: A Resource for States (February 2010), available at: http://epa.gov/statelocalclimate/documen ts/pdf/epa_assessing_benefits_ch3.pdf Deleted: An alternative approach is

Deleted: EPA is proposing to allow a wide (or unlimited) set of energy efficiency program and measure types in state plans, as long as the energy savings are adequately documented according to rigorous EM&V methods and appropriate regulatory oversight. The former option potentially reduces measurement uncertainty, while the latter approach may provide more flexibility.

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53 and guidance for state plans is whether to account for avoided T&D losses, and how to do so in a
consistent manner across states. 4.2.3 Reported Energy Savings Values
Energy savings results for energy efficiency programs are often expressed in terms of annual MWh of savings per year. However, for an assessment of the associated avoided CO 2 

### emissions impacts, it may be useful to utilize time-differentiated (i.e., hourly, seasonal) energy savings data. 82 

### Information about the timing of energy savings has direct implications for estimating the avoided CO 2 

### emissions that result from an efficiency program or portfolio ofprograms. The temporal energy savings profile that results from the application of energyefficient technologies and practices to different end-uses can vary significantly. For example, air conditioner programs save energy primarily on hot summer days, whereas a refrigerator program saves energy every hour of the year. Time-differentiated information related to electricity generation is useful in estimating avoided CO 2 

### emissions. In particular time-differentiated data is necessary to estimate the marginal avoided CO 2 

### emissions related to electric generation, as
discussed above in section IV.C.3.

In practice, state PUCs around the country have substantially different requirements and recommendations for evaluating and reporting time-differentiated energy savings. Some energy efficiency program administrators report annual energy savings impacts, where savings are typically based on either tracking data (i.e., data used to estimate savings for planning purposes) or evaluated (i.e., ex-post) savings data. Other programs supplement reporting of annual energy savings with data on the timing of energy savi ngs, which can be used to identify the marginal EGU or cohort of marginal EGUs that would ha ve provided generation in the absence of the energy savings. This supplemental data can be used to more accurately estimate avoided CO 2 

### emissions that result from program energy savings. Due to improved evaluation software and data availability, it is increasingly common for energy efficiency program EM&V plans to include calculation of estimated seasonal or even hourly energy savings as part of the program evaluation process. A consideration for EM&V requirements and guidance for state plans is the
extent to which time-differentia ted data on energy savings from energy efficiency programs is

82 This is often referred to as the “load shape” of energy savings achieved through an energy efficiency measure. Deleted: in

Deleted: or

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54 available, and whether states can readily acquire such data and information for use in implementing their state plans.

A related consideration is metr ics reported for electricity savings. The primary metric required to understand the avoided CO 2 

### emissions impacts of energy efficiency programs and measures is annual MWh of energy saved. In addition, a secondary metric is MW demand reduction impacts, which may be desirable because it is helpful in identifying the marginal EGU or cohort of EGUs, in particular units on the build margin. This information is necessary to estimate the marginal avoided CO 2 

### emissions related to electric generation, when reporting on
avoided CO 2 

### emissions achieved through energy efficiency programs and measures during a plan reporting period, as discussed above in section IV.C.3. Identifying EGUs on the build margin, based on estimates of MW demand savings that will be achieved through the implementation of energy efficiency programs and measures included in a state plan, may also be useful in projecting emission performance by affected EGUs that will be achieved under the state plan.

4.2.4 Savings Definitions: Net and Gross Savings
As described above, state PUCs typically specify whether energy efficiency program administrators are required to report either gross or net energy savings, or both. Gross savingsare the change in energy use (MWh) and demand (MW) that results directly from programrelated actions taken by program participants, rega rdless of why they part icipated in a program. Net savings refer to the change in energy use and demand that is directly attributable to a particular energy efficiency program. 83 

### Reporting of net savings helps a PUC ensure that energy efficiency program budgets are being used to pr omote technologies and practices that are not

83 Calculations of net energy savings involve excluding energy efficiency measures undertaken by "free riders" (i.e., EE program participants who receive a program rebate ev en though they would have taken the efficiency action anyway), or adjusting energy savings estimates to account for these effects. Free riders increase program costs without producing additional energy savings impacts beyond what would have occurred in the absence of the EE program. Free ridership may also be addressed in the setting of baselines that are used to calculate energy savings. Estimates of net energy savings may also involve an assessment of "free drivers" (sometimes referred to as "spillover effects"). These are individuals who do not di rectly participate in an EE program, but who undertakeefficiency actions in response to program activity (e.g., marketing/advertising, greater availability of energyefficient equipment in a marketplace as the result of EE programs). Accurate estimation of free ridership and spillover effects is complex, especially in areas of the country with robust energy efficiency markets with multiple non-program influences competing for customers’ attention.

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55 otherwise being adopted in the marketplace. A consideration for EM&V requirements and guidance for energy efficiency requirements and programs included in state plans is whether required reporting of energy savings should be specifi ed on either a gross or net basis, or both, to promote national consistency in measuring the imp act of energy efficiency measures across state plans. 84



### 4.2.5 “Measure Life” and Persistence of Savings
Measure life and persistence of energy savings describe the ongoing effects of an installed energy efficiency measure, including the retention of the measure ( i.e. , is it still in place) and the performance degradation of that measure, which reduces a measure’s achieved energy savings over time. Typically, program administrators estimate the impact of energy efficiency programs in terms of first-year savings (in MWh), plus the cumulative MWh savings realized from that program (or measure) over an assumed “measure lifetime”. Depending on the mix of energy efficiency measures and thei r assumed measure lives, these energy-savings benefits may extend from 10 to 15 years, or more into the future from the point of measure installation. In practice, evaluators determin e measure lifetimes on the basis of engineering judgment, manufacturer specifications, and some empirical field studies. These values are frequently entered into PUC-managed state technical databases for ongoing and repeated use in
evaluation studies. For state plans, a key consideration for EM&V is whether measure life and persistence values for energy efficiency measures documented by states are accurate, up-to-date,
and consistent with those utilized in other stat es (after accounting for appropriate non-energy factors, such as weather and building occupancy type).

5. Options for EM&V Requirements and Guidance for State Plans
As EPA develops guidance on acceptable evaluation methods that can be incorporated in an EM&V plan included as part of an approvable state plan, the agency (as discussed in the preamble at section VIII.F.4 ) is seeking comment on the appropriate basis for and technical

84 If both gross and net savings were requi red to be reported, this would increase the transparency of reported energy savings estimates, but only one savings value would be used to evaluate the effect of energy efficiency programs and measures on CO 2 emissions from affected EGUs. Deleted: of

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56 resources used to establish such guidance, incl uding consideration of existing state and utility protocols, as well as existing international, national, and regional consensus standards or protocols, as described in this section.

As summarized in the preamble, and discussed in more de pth in this section, utilities and states have conducted ongoing evaluation of en d-use energy efficiency and renewable energy measures and programs for several decades. These evaluations, which include quantification, monitoring and verification of results, gene rally rely upon a well-defined set of industry -standard practices and procedures. As a result, existi ng state and utility EM&V requirements and processes generally provide a solid foundation for minimum EM&V requirements that can be
utilized by the EPA in the development of EM&V requirements and guidance for state plans. However, measurement approaches vary by state based on multiple factors, including the measure and program type being evaluated, the level and nature of regulatory oversight, the degree of state and utility experience with th ese measures and progr ams, and the overall magnitude of program impacts. Due to this variation in state EM&V approaches, as well as the specific objectives of a state plan under CAA section 111(d), harmonization of state EM&V approaches, or inclusion of supplemental EM&V actions and procedures, may be warranted in an approvable state plan.

As discussed previously, current state EM&V practices involve aligning the level of EM&V effort (i.e., rigor, reliability, validity, and uncertainty of energy savings estimates) with
the appropriate level of certainty of evaluation results , while taking into consideration the magnitude of energy efficiency program impacts. This approach is consistent with the objective of achieving environmental results, ensur ing minimum levels of cross-state consistency, and supporting and encourag ing the use of energy efficiency re quirements, programs, and measures in state plans. To advance these objectives, the EPA could take several possible approaches for documenting energy efficiency savings from measures in state plans.

Options for EM&V requirements and guidance for state plans that incorporate energy efficiency requirements, programs, and measures include: Deleted: might

Deleted: established

Deleted: best
Deleted: require the
Deleted: to be aligned
Deleted: required
Deleted: and
Deleted: These best practices are
Deleted: credible
Deleted: e Deleted: e Deleted: state
Deleted: support
Deleted: the following process considerations are relevant for documenting
Deleted: or Comment [A14]: Options listed omit a “middle of the road” approach such as the Uniform Methods Project.

EPA response: We have included a “middle

‐ of

‐ the

‐ road” option in response to this comment and have included the Uniform Methods Project (UMP) as an example of such an option.

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57  Establishing specific EM&V requirements with a level of defined rigor – such as a required minimum level of precision and accuracy (see discussion of ISO forward capacity markets above) – for all energy efficiency programs and measures

 Establishing specific EM&V requirements for certain types of widely used energy efficiency programs and measures – such as those addressed by DOE’s Uniform Methods Project (UMP) – while establishing a generalized EM&V approach that states can apply to programs that are relatively new, innovative, or untested

 Establishing a set of generalized, process-oriented EM&V requirements that apply to all energy efficiency programs and measures, while providing flexibility to customize EM&V approaches, as appropriate for different types of programs and measures, provided that EM&V meets these minimum requirements

At one end of this spectrum, establishing program- specific EM&V requirements and an associated level of rigor for EM&V provides certainty to states in terms of required energy savings documentation, and do es so in a manner that ensures a consistent level of EM&V rigor across all state plans. However, this approach may require significant effort by the EPA to establish such requirements, and could potentiall y duplicate state efforts currently under way to harmonize EM&V practices. This approach may also limit the variety of valid EM&V approaches applied at the state level, and by extension the types of energy efficiency programs and measures that could be included in a state plan . It could also inhibit the development of innovative EM&V approaches that improve the accuracy of energy savings estimates. At the other end of the spectrum, if only generalized, process-oriented EM&V requirements and guidance are established, then a state has maximum flexibility, but also faces somewhat greater uncertainty about whether the EM&V approach incl uded in a state plan will be approved by the
EPA. This could increase the transaction costs incu rred by states during the development of their plans, and could possibly delay the full implementation of energy efficiency programs incorporated in state plans.

Alternatively, a middle-ground approach involves a combination of specific EM&V
criteria for common energy efficiency program and measure types, along with generalized Deleted: ;

Deleted: Establishing no EM&V requirements at all, beyond basic requirements to quantify and verify energy savings, and allowing states to establish their own EM&V protocols;

Formatted: Indent: Before: 0.5", No bullets or numbering Comment [A15]: Under a rate

‐ based approach, this is risky and should not be allowed (states with lax EM&V could potentially generate false efficiency credits that lower their compliance costs). For rate

‐ based approaches, EPA should consider requiring strong national EM&V standards for efficiency (and indicating its preference for this approach here), drawing from DOE’s uniform methods project and other state of the art approaches. On the other hand, for mass

‐ based approaches, EPA should consider allowing states to use their own EM&V for efficiency.

EPA response: We have deleted discussion of this option in response to this comment.

Deleted: minimum specified

Deleted: , and

Deleted: no specific

Deleted: increased

Deleted: proposed

Comment [A16]: Though this comment bookends the options, a lack of EM&V requirements would be extremely problematic.

EPA response: We have deleted discussion of this option in response to this comment and the previous comment.
Deleted: In the middle of the spectrum,
Deleted: some minimum

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58 guidance for emerging program designs and measures

. Such an approach would provide some level of certainty regarding acceptable EM&V approaches in state plans, while maintaining a certain degree of flexibility for states to determine an appropriate mix of EM&V approaches
, given the types of energy efficiency programs and measures included in their plan.

In addition, one option for supplementing either approach described above is to prescribe who can conduct EM&V activities and prepare energy savings documentation, and to specify their needed qualifications. This approach is analogous to professional certification requirements in the accounting and engineering fields, in which a minimum level of credibility, rigor, and accountability is imparted to the services provided by qualified individuals and firms. Criteria for eligible evaluators might include a demonstration of independence from those implementing or administering the energy efficiency programs and measures ( i.e. , identification and mitigation of potential conflicts of interest) and required minimum levels of training, experience, or certification. This approach recognizes that th e qualifications, integrity, and independence of those conducting EM&V of energy efficiency programs and measures, and preparing energy savings estimates, is critical to assuring best-p ractice EM&V. However, such requirements alone may not ensure sufficient evaluation rigor.

5.1 Use of EM&V Protocols
Establishing requirements and guidance for EM&V of energy efficiency programs and measures included in state plans may involve:

 Relying on existing EM&V infrastructure and protocols, most of which have been established for utility-customer funded energy efficiency programs overseen by state
PUCs

 Establishing new protocols and procedures

Relying on existing approaches has the benefit of utilizing existing resources that can be relatively quickly ramped up for use in state plans. However, existing state and utility EM&V infrastructure and protocols may not be applicable to the full range of energy efficiency programs and measures that a state may want to in clude in its plan. In addition, because existing Deleted: could be specified for all energy efficiency programs and measures, using general guidance, and/or establishing EM&V criteria for specific widely used energy efficiency programs and

measures Deleted: States would have
Deleted: about
Deleted: as well as
Deleted: some Deleted: in establishing appropriate
Deleted: for
Deleted: A supplemental approach, in addition to those
Deleted:

,

Deleted: or

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59 state and utility EM&V infrastructure and protocol s were established to support the goals of state energy efficiency programs, in current form they may not adequately support the level of EM&V required for state plans under CAA section 111(d). In particular, this may include the form and precision of energy savings data and reporting necessary to evaluate avoided CO 2 

### emissions that result from energy efficiency programs and measure included in state plans.

5.2 EPA Review of EM&V Plans as Part of the State Plan Review Process
As discussed in the preamble, at section VIII.F.4, the EPA is proposing that a state plan must include an EM&V plan, which is subject to approval by EPA, as part of plan review and approval. Under this approach, the EPA would review these EM&V plans as part of its review of submitted state plans. One option is that an approvable EM&V plan could rely primarily on state- or utility-level EM&V plan review and approval processes, consistent with established EPA requirements and guidance for EM&V, with open public involvement and state lead-agency approval

. Using existing state EM&V plan review processes may better ensure that energy savings estimates are transparent, peer reviewed, and address stakeholder input. Using state processes also minimizes duplication of state an d the EPA requirements, and balances the need for EM&V credibility and rigor with an interest in encouraging the deployment of cost-effective energy efficiency programs and measures through incorporation in state plans.

5.3 General Quality Standards for EM&V Rigor and Accuracy
Since existing state EM&V process vary, EM&V guidance established by EPA may need to identify and establish minimum criteria for EM&V rigor, accuracy and reliability, and quality control. Requirements could be (a) a single set of requirements that apply to all energy efficiency programs and measures in all states or (b) a variable or flexible set of requirements with increasing levels of EM&V effort and rigor depending on the relative degree of uncertainty of energy savings from the energy efficiency programs and measures in a state plan. For example, well understood energy efficiency meas ures with a higher degree of energy savings Deleted:

Deleted: Development of EM&V plans that are included in a state plan

Deleted: of energy savings reported. Under this approach, states would develop EM&V plans as part of the state plan development process. The EPA would then review these EM&V plans as part of its review of a submitted state plan.

Deleted: However, this approach could create uncertainty for states about the approvability of a proposed EM&V approach in a state plan, and could also reduce the consistency and comparability of EM&V approaches used in state plans. At the same time, existing state EM&V processes currently vary in the level of regulatory oversight, which could necessitate establishment of minimum criteria for EM&V plans.
Deleted: the EPA
Deleted: requirements

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60 certainty might require a lower level of EM&V effort, while measures with greater complexity or uncertainty of energy savings effect s would require greater EM&V effort. 85



### For s imple, well-understood and straightforw ard energy efficiency programs and measures, such as lighting retrofits , EPA guidance might specify only verification that measures were installed and the use of deemed energy savings values ( i.e., lower EM&V effort level)

. In contrast, EPA guidance might specify more detailed EM&V (i.e., a higher level of EM&V effort)
for less well-understood or more complex energy efficiency programs and measures, such as behavior programs and market transformation programs

.
A prescri ptive EM&V approach in EPA guidance for different types of energy efficiency programs and measures would provide states with certainty while supporting a consistent level of EM&V rigor across all states. A flexible EM&V approach, based on an individual assessment of the measurement uncertainty related to the energy efficiency programs and measures included in a state plan could provide states with greater flexibility when selecting energy efficiency programs and measures. However, the lack of a prescribed EM&V approach in EPA guidance could increase uncertainty about the approvability of different plan approaches.

6. EM&V Documentation in a 111(d) State Implementation Plan
EM&V documentation will be an important component of state plans that incorporate energy efficiency programs and measures, because transparency and reproducibility increase overall confidence in reported energy savings results. A crucial component of EPA’s proposed approach for evaluating energy efficiency progra ms and measures included in a state plan is a requirement that state plans that include enfor ceable energy efficiency and renewable energy measures must include an EM&V plan for these measures. These EM&V plan s would specif y how achieved energy savings will be retrospectively evaluated at appropriate increments during the plan period. Decisions about the level of EM &V documentation that is necessary in a state

85 For the purposes of this discussion, lower, medium, and high levels of “EM&V effort” are intentionally indeterminate. One possibility is that “lower EM&V effo rt” could refer to greater reliance on deemed savings values, smaller sample sizes for measured savings, fewer direct measurements, and pro portionately greater reliance on ex-ante estimates. “Medium” and “high” levels of EM&V effort could require incrementally more effort in each of these areas. Other interpretations of this concept are possible. Deleted: S

Deleted: require

Deleted: , while

Deleted: , would require more detailed EM&V (high level of EM&V effort).

Deleted: bed
Deleted: all

Deleted: this EM&V documentation is an
Deleted: , which
Deleted: ies a priori

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61 plan must consider tradeoffs between provision of more information and greater transparency, and the level of EM&V effort required. Excessive documentation requirements may not add value in terms of transparency, but may discourage the inclusion of cost-effective energy efficiency options in state plans. However, two basic criteria for EM&V documentation should be applied in state plans:

 Energy savings documentation should be provided at a level of detail that allows for recalculation of program energy savings totals; and

 EM&V information in state plans should be provided in a consistent manner across states to allow for comparison, benchmarking, and more efficient review of plans by the public
and EPA

6.1 Illustrative Example of an EM&V Plan for End-Use Energy Efficiency Programs
Measures in a State Plan

The following is an example of a possible outline of the type s of information that might be included in an EM&V plan for energy effici ency programs and measures included in a state plan. An EM&V plan would speci fy how EM&V activities will be conducted and reported for relevant energy efficiency programs and measur es during a state plan performance period. An EM&V plan could apply to utility energy efficiency programs that are incorporated into a state plan on a stand-alone basis, and might also apply to such programs when used to meet mandatory energy efficiency requirements, such as an EERS, that are incorporated into a state plan.

Who Will Document Savings and When

 Name of the organization that will prep are evaluated energy savings reports

 Relationship of the organization to the subject energy efficiency program(s) and program administrator(s)

 Schedule of when the reports will be prepared and what period of time they will cover

 Name of the state or regional government en tity, or non-governmental entity, which will review and certify the evaluated savings Deleted: and their Comment [A17]: Incomplete sentence

– please clarify.

EPA response: This was a typo, as this bullet was originally combined with the second bullet. Thank you for spotting.

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62  How evaluated energy savings reports will be made publicly available and what the primary use of the reports will be

Documentation Procedures

 List of energy savings metrics to be report ed (e.g., annual MWh, monthly MWh, hourly MWh, average MW), and whether gross or net savings, or both, will be reported

 Name of impact evaluation protocols, guid ance documents, and other methods that will be followed in preparing evaluated energy savings reports

 Description of the range of uncertainty for energy savings estimates indicated in evaluated energy savings reports, including sources of uncertainty

 Description of assumptions concerning availability of data and data collection methods

 Indicate how the following issues, if applicable, will be addressed in the claimed and evaluated savings estimates:

o Inclusion of estimates of avoided electrici ty transmissions and distribution losses

o Adjustment of gross savings estimates to net savings estimates (if applicable

o Sources of uncertainty

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63 B. Quantification, Monitoring, and Verifi cation for Renewable Energy Measures
For rate-based state plans, a key element of the plan is a demonstration of how the state, and related entities with enforceable obligations under the plan, will measure and verify electric generation that is achieved through the implementation of renewable energy measures incorporated in the plan. 86 

### This section discusses current state and utility quantification, monitoring, and verification practices for renewable energy measures, and discusses considerations related to possible acceptable quantification, monitoring and verification approaches for a state plan under CAA section 111(d).

States and utilities use a variety of policy instruments to increase the production and use of renewable energy. The principal mechanisms include: renewable portfolio standards (RPSs), feed-in tariffs (FITs), tax incentives (e.g., property tax exemptions; production-based tax incentives; etc.), financial assistance programs (e.g., grants, loans, and other direct financial assistance based on generating capacity or investme nt level), and other policies (R&D support; manufacturing incentives; workforce training; net me tering; etc.). Experience to date indicates that RPSs have led to the vast majority of the increase in renewable energy generating capacity and generation resulting from state policies. However, FITs and production-based tax incentives have been among the most important incentives used by states and utilities to help achieve RPS requirements, as well as to spur additional production and use of renewable energy. Further, these types of programs rely on measurable electric generation as the basis for compliance or incentive payments. As a result, the following discussion focuses on quantification, monitoring,
and verification mechanisms related to these stat e policies. Other types of programs (e.g., certain grant and rebate programs) may not currently qu antify electric generation output from funded renewable energy projects. However, if such programs were modified to require the collection of such data, many of the quantification, monitoring, and verification considerations discussed in this section would also generally apply.

86 In this section we use the term “renewable energy meas ure” to refer to a renewable energy requirement (such as an RPS), a renewable energy deployment program, or individual installed renewable energy measures, such as installation of a solar photovoltaic system through a renewable energy deployment program.

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64 1. Renewable Portfolio Standards
A RPS is designed to increas e the amount of renewable energy a distribution utility or load-serving entity provides to retail electricity customers. 87 

### . This increased customer demand in turn increases the production of renewable energy to meet demand. To achieve compliance with a RPS, an increasing share of a distribution utility’s electricity retail sales is required to be produced or acquired from renewable energy resources and delivered to customers. To verify compliance, RPSs have been complemented by tracking systems for renewable energy generation and use. These tracking systems account for the growing amount of renewable energy that is produced for obligated retail sellers as well as large and small retail energy consumers that purchase renewable energy on a voluntary basis. 88



### The point of regulation for state RPSs is typically investor-owned electric distribution utilities, because most RPS apply to entities under the jurisdiction of state PUCs. In a number of states, municipally-owned utilit ies and electric cooperatives are exempt from state RPS, have lower RPS requirements, or are required to develop their own renewable energy procurement targets. Additionally, some states have created separate renewable energy requirements for each
of their affected distribution utilities.

The absolute amount of renewable energy that each distribution utility is obligated to deliver will vary, with requirements in the form of a fixed amount of renewable energy (either MWh or MW of capacity) or percentage of retail sales.

There are several pathways that affected distri buted utilities typically have to meet state RPS requirements, including building and operating renewable energy generating capacity, purchasing electricity from renewable energy ge nerators, and purchasing the attributes from renewable energy generation. Many state RPSs take this latter approach. Rather than requiring

87 In states that have restructured their electricity sect ors and introduced retail competition, entities other than a utility may supply electricity to a retail customer. These en tities use a regulated distribution utility’s network to deliver electricity to a retail consumer. These entities either generate their own electricity or contract for supply from wholesale electricity market participants. In this section, we use the term “distribution utility” to refer broadly to both local distribution companies (LDCs) and other load-serving entities that supply electricity to retail customers. 88 “Voluntary” renewable energy purchases, as used here, refers to renewable energy purchases in addition to the renewable energy required by RPSs.

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65 each distribution utility to gene rate electricity from its own renewable energy facilities or purchase electricity from a renewable facility ow ned by others, many states require distribution utilities to acquire renewable energy certificates (REC s) that represent the attributes of the unit of renewable electricity produced. 89



### By allowing REC trading, many states have created markets for RECs based on specific state RPS requirements. Renewable energy generato rs can sell RECs as another product bundled with the underlying power they produce or sell RECs separately to different customers. Once the RECs are separated from the power generated, the power has no attributes associated with it and is considered generic or “null” power. 90



### There are a number of key aspects of RPS design and implementation that affect the quantification, monitoring, and verification of re newable energy generation used to meet a RPS:

 Eligible renewable energy resources . While most RPS-eligible resources in most states
will result in avoided CO 2 

### emissions from fossil fuel-fired EGUs, some RPS-eligible resources in some states are responsible for greenhouse gas (GHG) emissions or do not meet common definitions of renewable energy (e.g., waste coal, coal-bed methane, and fuel cell operation using fossil-fuel feedstocks).

 Existing and new resources. RPS-eligible re sources can include facilities that began operation prior to the enactment of the RPS and, more importantly, prior to the proposal of the emission guidelines by EPA. 91

89 RECs are contractual instruments that convey ownership of th e attributes of a unit of energy generated, but do not represent the energy itself. The attri butes conveyed with RECs include info rmation about the generator, such as: type of resource (e.g., wind), plant-level air emissions (if any), geographic location, nameplate capacity (MW), commercial operation date, ownership, and the eligibility for RPS compliance or voluntary market certification. 90 These distinctions are typically made as part of utility disclosure to customers about the energy resource mix and emissions of the electricity used by a customer that was su pplied from by the distribution utility. “Generic power” or “null power” refers to energy th at has no generation attributes or descriptive information ( i.e. , the remaining system mix of power, after assignment of specified power to diffe rent utility customers, through power purchase contracts or purchase of generation attributes through RECs). For electric ity labeling, disclosure to customers, or other market claims, generic or null power is typically assigned the attr ibutes of the remaining system mix of power, after the assignment of attributes as described above. 91 In the preamble, the EPA is proposing that, for an ex isting state requirement, program or measure, a state may apply toward its required emission performance level th e emission reductions that existing state programs and

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66  Scope of coverage . In some states a RPS applies to all retail sales in a state, but in others only a subset of retail sales (e.g., only invest or-owned utility retail sales) are subject to a
RPS.

 Credit multipliers . Some states provide additional incentives for specific eligible resources in the form of bonus credit toward compliance in their RPS accounting framework. For example, these states may favor certain resources (e.g., distributed solar PV), or locally-important resources or t echnologies. The MWh produced or renewable energy certificates (RECs) related to MW h production from such facilities may be counted twice or three times toward compliance with a RPS in such states. However, these credit multipliers and bonuses are not an accurate representation of the amount of renewable energy generation that is attributable to a RPS. For the purpose of quantifying the amount of renewable energy produced as a result of a RPS included as a measure in a state plan, only the actual renewable energy generation used to comply with an RPS is
relevant.

 Banking . Some states permit the carryover of renewable energy produced in one year to satisfy RPS requirements in a subsequent year. Accounting for year-to-year carryover should be addressed in a state plan, in order to determine the renewable energy generation that occurred in a respective reporting year or compliance period.

 Alternative compliance payments (ACP) . Many states allow a compliance alternative which requires obligated entities to pay a pred etermined fee to the state for each MWh of RPS shortfall. Although these ACP payments may be directed to programs to promote the deployment of renewable energy technologies, these payments are not equivalent to renewable energy generation and should not be accounted as such.

 Interstate issues . While treatment of interstate emission effects is discussed in detail in section VII, for quantification, monitoring, and verification of renewable energy

measures achieve during the plan period due to actions taken after the date on which the emission guidelines are proposed (i.e., from June 2014 onward).

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67 generation under a RPS it is important to note that most states allow use of eligible renewable energy resources located in other st ates to satisfy the state RPS requirements. 92



### Considerations related to the quantif ication, monitoring, and verification of renewable energy generation used to meet a RPSs depends on the design and implementation of the RPS. Distribution utilities subject to a RPS may meet their RPS oblig ations by building and operating their own renewable energy generating facilities , entering into bilateral contracts with other parties to purchase renewable energy, and participating in the REC market. Each compliance method has specific implications for the quantification, monitoring, and verification of renewable energy generation used to meet RPS obligations. Implications under these different pathways are discussed below.

Build renewable generating facilities In many states, utilities with RPS obligatio ns may build, own, and operate their own renewable energy generating facilities. This pathway is often used by vertically integrated utilities subject to a RPS. For large renewabl e energy generating facilities, production is measured through a revenue-grade utility meter as it enters the grid at the point of interconnection. This meter is subject to the same verification standards as for any other generator participating in the wholesale market.

Some utilities with RPS obligations also bu ild, own, and operate smaller distributed renewable energy generating facilities. Smaller generators, such as residential rooftop solar PV systems of less than 10 kW capacity, often don’t have discrete metering of their total generation. 93 

### State RPS requirements may permit these distributed generators to qualify for use in meeting utility RPS obligations based on an engineering estimate of their renewable energy generation output , provided the distributed genera tors are registered with a REC tracking system and the generation output is verified according to tracking system and RPS rules.

92 This may also include international renewable energy resources, such as Canadian hydroelectric and wind energy resources, which may be used to comply with some state RPSs. 93 Metered data for these PV systems may only track net el ectricity supply to or from the grid, representing either surplus generation that is not used to serve on-site electricity load or additional net electri city supplied from the grid if the system does not meet a building’s total electricity load. Comment [A18]: Suggest including this clarification in the preamble.

EPA response: This is discussed in the preamble, in the section discussing treatment of interstate emission effects (section VIII.F.6).

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68 Bilateral contract model
Under the bilateral contract mo del, distribution utilities with RPS obligations contract with renewable energy generators for supply. These contracts typically specify a delivery amount in MWh over a specified contract period. Thes e supply contracts may be short- or long-term, may specify generation from certain renewable energy EGUs, and may be solicited through an RFP or entered into through negotiation. Quantification of renewable energy generation (in MWh) is accomplished through the use of a revenue-grade meter that measures the flow of electricity from the generator into the transmi ssion grid. A contract may also stipulate an adjustment to the metered MWh generation data to account for transmission losses that occur between the point of injection of electricity to th e transmission grid and the point of receipt at a utility transmission or distribution system. A rene wable energy supply contract also generally addresses the ownership of the RECs related to the renewable energy generation. Under such a contract, purchase of the RECs should accompany the purchase of the electricity, in order for the utility to satisfy its RPS obligations through the contract. 94



### State RPS compliance processes may provide for PUC review of supply contracts, including inspection of meters and verification of electricity delivery from the generator to the utility distribution network through a specified contract path (e.g., through evidence of transmission rights held or scheduled). The purch asing utility also reports their purchase and delivery of RPS-compliant renewable energy pursuant to the contract to the state agency responsible for RPS enforcement, typically the st ate PUC or state energy office. Verification is accomplished by audit of electricity supply cont racts along with REC tracking system reports of RECs held by the utility and submitted for retireme nt by the tracking system administrator. Some state RPS require that electricity from qualifying renewable energy sources be produced within the state or a specified grid region, or if outside the state or specified grid region, that electricity be delivered to the state or grid region. In such cases, the verification of electricity delivery is typically done by the REC tracking system admi nistrator before issuing RECs for the imported energy. Verification can be provided, for example, by demonstration of scheduled delivery

94 This ensures that multiple parties are not using the sa me MWh of renewable energy generation to comply with their RPS obligations.

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69 through the ISO or RTO serving the state or region, through demonstration that the seller holds transmission rights for delivery or poss ession of NERC tags for the energy. 95 

### Bilateral contracts also typically require certification by the seller that attributes related to the sold electricity have not been and will not be otherwise sold, retired, claimed, represented as part of energy sold elsewhere, or used to satisfy obligations in another jurisdiction.

REC model Under the REC model, renewable energy genera tors register their EGU with a renewable energy tracking system, which have been established by several regional groupings of states, as
well as a few individual states. 96 

### The registration process collects data about the generator’s attributes: type of resource (e.g., wind), plant- level emissions, geograph ic location, nameplate capacity (MW), commercial operation date, ownership, and the eligibility for RPS compliance or voluntary market certification. After the generator is registered, revenue-meter data is transmitted to the tracking system. Meter accuracy is verified for renewable energy generators in the same manner as for any other generator pa rticipating in wholesale electricity markets.

Each MWh of renewable energy generation reported to the tracking system by a registered generator results in the issuance of a REC, with its own unique serial number and information about the generator, location, resource type, and the month in which the MWh was generated, and the month or quarter in which the certificate was issued. The renewable energy

95 A NERC Tag, sometimes referred to as an E Tag, is an electronic tag that is used to track wholesale electricity transactions that involve the transfer of electricity across or through control areas. NERC Tags allow transmission system operators to track electricity transactions in real time in order to assess any potential reliability implications of scheduled power transactions. NERC Tags define the physi cal path of an electricity transaction from the point of generation to the point of receipt, and also define the fi nancial path, including all parties to a transaction. All wholesale electricity transactions that will result in the transf er of electricity from one control area to another, or that involve transfers through a control area, must be accompanie d by a NERC Tag. Based on a real-time assessment of NERC Tags, system operators can curtail transfers if reliabili ty issues would arise as a result of the transfer. NERC tags are issued through an electronic system in accordance with specifications established by the North American Electric Reliability Corporation (NERC). 96 Currently, nine regional renewable energy certificate (REC) tracking systems operate in different regions of North America, including: Texas Renewable Energy Credit Program, run by the Electric Reliability Council of Texas (ERCOT), NEPOOL Generation Information System (GIS), PJM Generation Attribute Tracking System (PJM-GATS), Western Renewable Energy Generation Info rmation System (WREGIS), Midwest Renewable Energy Tracking System (M-RETS), North American Renewables Registry (NARR), Michigan Renewable Energy Certification System (MIRECS), Nevada Tracks Rene wable Energy Credits (NVTREC), and North Carolina Renewable Energy Tracking System (NC-RETS). For more information see http://apps3.eere.energy.gov/greenpower /markets/certificates.shtml?page=3

.

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70 generator can then sell the renewable electricity as a bundle (both the commodity electricity and the associated REC) or unbundle the RECs fro m the electricity and sell the two products separately. Other market participants, such as brokers, REC marketers, and load-serving entities also maintain accounts with the tracking system so that REC electronic transactions can be recorded within the tracking system platfo rm. The system tracks each REC through these transactions and ultimately “retires” the RE C when the final purchaser designates it for
retirement. Retirement could result from the REC bein g used to satisfy a state RPS, or as a result of a voluntary buyer retiring the REC to demonstrate that they had purchased and used renewable energy to meet their electricity demand.

Because the tracking system follows the REC from the point of issuance to retirement, including all interim transactions, it minimizes the opportunity for renewable energy to be double-counted across, for example, two diff erent state RPSs, or between two voluntary purchasers. In recent years, the various tracking systems have developed interchange standards so that RECs generated within one tracking system can be transferred to and used within another tracking system. 97 

### Note that not every potential interchange possibility is currently supported, and that many states have additional eligibility restrictions within their RPS that may limit the use of RECs related to electric generation from distant locations. These include requirements in some state RPSs for the seller to hold firm transmission rights for delivery of the accompanying electricity from the renewable energy generator into the respective ISO/RTO system or grid system in which a state is located.

Small distributed generators Smaller distributed generators, such as reside ntial rooftop solar PV systems of less than 10 kW capacity, often don’t have discrete metering of their total generation. State RPS requirements may permit these distributed genera tors to qualify for use in meeting utility RPS obligations based on an engineering estimate of their renewable energy generation output , provided the distributed generators are registered with a REC tracking system and the generation output is verified according to tracking system and RPS rules. Where such projects are third-

97 Additional linkages between tracking systems are bei ng established. More information can be found at http://www.narecs.com/resources/registries/

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71 party owned and operated, the pr oject developer will own the RE Cs and factor their revenue value into their pricing offered to the site host for electricity suppl y. Note also that many utilitysponsored renewable energy incentive programs sti pulate that all RECs resulting from the project must be transferred from the generation owner to the utility as a condition of participation in the incentive program. These RECs can then be used by the utility to meet its RPS obligations, or can be sold to other parties.

State agency role In many states, the PUC or its equivalent is responsible for establishing the detailed rules and procedures that obligated parties must foll ow to comply with a RPS. The PUC is usually responsible for receipt and review of obligated parties’ periodic compliance reports, imposing compliance penalties as needed, and for evaluating the impacts of the program on energy costs, generation diversity, and market operations. The list of eligible resources and MWh requirements are often set through state legislation, but these decisions may also be delegated to the PUC for study and promulgation through regulations of commission orders.

In some states the energy office may be responsible for certifying the eligibility of specific generators to participate in the RPS a nd for making siting determinations. In New York, for example, the New York State Energy Research and Development Authority (NYSERDA) is responsible for the centralized procurement of the renewable energy needed to meet the RPS for
all of the state’s investor-owned utilities.

2. Feed-in Tariffs
Feed-in tariffs (FITs) are offered by some individual electric dist ribution utilities and some states for renewable energy systems that meet eligibility criteria. 98 

### Under a FIT, the utility offers to purchase specific kinds of electricity (e.g., solar) from sellers at posted prices or under a published pricing formula for a specified period of time. FITs typically have caps on the amount

98 There are several states that offer FITs, including Ca lifornia, Hawaii, Maine, Oregon, Rhode Island, South Carolina, Vermont and Washington, as well as numerous electric utilities. Deleted: Public Utilities Commission (
Deleted: )

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72 of renewable energy that will be purchased by a utility (in MWh of energy or MW of capacity). FITs may also include customer impact caps for the tariff as a whole (in total dollars spent or in specified retail rate impacts allowable), and may also have limits on the size of any participating renewable energy generator from which the utility will purchase electricity through the FIT. FITs may also have pricing formula s that are differentiated by resource or that change through time as specified benchmarks are achieved (e.g., MW of renewable energy generating capacity subject to the FIT, amount of electricity purchased through a FIT as a percentage of utility sales, or retail rate impact level reached). Typically, the tariff treats all similarly-situated generators in a
consistent manner.

Quantification of renewable energy generation output under a FIT is accomplished through the use of a revenue-grade meter to measur e the generator’s injection of electricity into the grid. The utility’s tariff will typically specify the minimum performance characteristics
and/or certifications that a meter must meet in orde r to be used on its system. Utilities retain the right to inspect and test the calibration of meters connected to their systems. As the utility will be paying the generator each month based on the meter reading, it is in the utility’s interest to ensure that the meter is reading precisely and accurately through time.

Both the utility and the state will need to consider the ownership of the environmental attributes arising from the renewable energy ge neration purchased by a utility through a FIT, and whether the renewable energy can be counted toward RPS compliance. If renewable energy generation purchased by a utility through a FIT may be counted toward RPS compliance, then it should not be counted separately as another renewable energy program in a state plan.

State agency role FITs are usually authorized by state statutes that specify which utilities must offer a FIT, eligibility criteria (e.g., renewable energy resource type, location, project MW generating capacity limits), and sometimes overall program ta rgets (e.g., total installed MW of generating capacity subject to the FIT). State statutes may al so specify whether the utilities offering a FIT will receive the RECs related to purchased electricity generation output for use in complying with a state RPS, and whether customers recei ving FIT payments may also receive incentives under other utility and state programs. Typically st ate statutes leave implementation details to the Deleted: e

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73 PUC (or other utility governing body, if applicable, for municipal and cooperative utilities), but may provide guidance on what to consider in se tting FIT payment levels. Based on this statutory authority, PUCs develop detailed rules governing implementation, which can include payment levels and contract length. PUCs may direct the affected utilities to develop standard contracts with all the terms and conditions spelled out, and these standard contracts must be approved by the PUC. As with state RPS, the PUC is respons ible for receipt and review of the utility’s periodic status reports, approving changes to a tariff if needed, and evaluating the impacts of the tariff on retail prices, generation diversity, and electricity system operations.

Several FITs are offered by distribution utili ties not overseen by PUCs, such as municipal utilities and rural electric cooperatives. These ut ilities have a variety of governance structures ( e.g. , municipal government, cooper ative board of directors). The utility governing bodies in these situations will be responsible for receipt an d review of the utility’s status reports, taking corrective action if needed, and evaluating the impacts of the tariff.

3. State Tax Incentives
Several states offer a variety of tax incentives to promote the production and use of renewable energy. These currently include sales tax exemptions for certain kinds of equipment (e.g., PV panels), property tax abatement for impr ovements to a building or facility related to the asset value of the renewable energy generating system, and income tax credits for the installation of renewable energy systems based on capacity or investment level. Several states provide a renewable energy production tax credit based on the amount of renewable energy generated. This approach is useful because it results in a measureable quantity of renewable energy electricity generation.

With a production-based tax incentive, the renewable energy generator might claim a tax credit for each MWh of qualifying renewable energy generation within the state. One design consideration for a production-based tax incentive th at affects quantification of renewable energy generation output is whether the electricity must be sold to a third party as opposed to being used by the site host. In the former case, a revenue-gra de utility meter would be present at the point of interconnection to the electricity grid, which pr ovides measurement of MWh generation output

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74 for tax compliance purposes. Site-host use might necessitate the installation of an additional meter within the project site to permit reliable measurement of the renewable energy generator’s output.

State agency role Currently, existing state tax policies are primarily under the authority of the state revenue agency. The state revenue agency might have the primary responsibility for establishing the rules for production-based tax incentives, although it may seek advice from state energy agencies regarding the technical aspects of renewable energy generator operation and the behavior of energy markets. The renewable energy generator might claim the tax incentive through the state tax collection process and report MWh generation to claim the tax credit. The revenue agency could receive tax filings from the owner and operators of renewable energy generators and be responsible for determining whether the taxpayer’s claim for tax incentives is supported by the MWh generation evidence. Assuming the state revenue authority retains its ability to audit the taxpayer’s return, it could verify claimed MWh generation.

As with FITs, the renewable energy gene ration resulting from production-based tax incentives might be used for RPS compliance. If that were to become the case, then it should not be counted separately in a state plan from MWh generation used to comply with a state RPS.

4. Options for Quantification, Monitoring , and Verification of Renewable Energy
Measures in State Plans

As summarized in the preamble, and discussed in more de pth in this section, utilities and states have conducted ongoing evaluation of renewable energy measures and programs for several decades. These evaluations, which include quantification, monitoring and verification of results, generally rely upon a set of standard practices and procedures. In addition, states have designed and implemented REC tracking systems to facilitate compliance with state RPS. This resource provides the ability to track the location and attributes of renewable energy generators, and the electric generation from these generators , as well as the parties that use RECs for compliance with state RPS. As a result, existing state and utility requirements and processes for quantification, monitoring, and verification of renewable energy programs and measures

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75 generally provide a solid foundation for minimum requirements and guidance for EM&V for RE measures in state plans that are established by the EPA.

The programs discussed above (RPS, FIT, and performance-based tax incentives) all require quantification, monitoring, and verification of electricity generation from renewable energy generators, as well as provisions of ot her key information, to determine eligibility and track program activity or complian ce with regulatory requirements (if applicable). Quantification of electricity generation is typically through the use of revenue-quality meters, 99 

### or engineering estimates for small distributed generators. Thes e data are essential to program management, verification of compliance or payments, budget control, and tracking progress toward goals. For example, PUCs overseeing compliance with state RPS receive compliance information from each obligated utility, including retail sales, compliance status based on MWh of electricity generated by eligible utility-owned renewable en ergy sources, or electricity or RECs purchased from eligible renewable energy generators, which may also consider application of multipliers or alternative compliance payments. 100 

### PUCs overseeing utility FIT and state agencies overseeing performance-based tax incentives managers receive reports containing MWh of electric generation from qualified electric generators that received payments under either a FIT or tax incentive. These data are essential for normal program management and accountability.

Current state data requirements under RPS, FIT, and production-based tax incentives are tailored to the objectives of these programs a nd facilitating effective regulatory oversight. Typically, avoiding CO 2 

### emissions, while considered a relevant co-benefit, is not a primary objective of these regulations and programs. As a result, additional information and reporting may be necessary to accurately quantify the avoided CO 2 

### emissions associated with the renewable energy generated through an RPS, FIT, or production-based tax incentive that is included in a state plan. The following types of information will incr ease the accuracy and verifiability of avoided
CO 2 

### emission estimates related to renewable energy requirements, programs, and measures

99 “Revenue-quality meter” refers to a meter used for b illing purposes in wholesale electricity markets, which typically need to meet ISO or RTO precision requirements or other specifications. 100 Compliance status will also consider the application of credit multipliers or alternat ive compliance payments, if relevant under an RPS. Deleted: or

Deleted: might be
Deleted: for state plans

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76 included in a state plan. For example, information on the location of the renewable energy generation (e.g., in-by state or within a specified grid region) of the renewable energy generation used for compliance with state requirements and programs would be helpful in determining
avoided CO 2 

### emissions. Information about the locati on of electric generators that supplied electricity generation that was imported to a stat e or grid region, will also be important. Timedifferentiated information related to electricity generation is also useful in estimating avoided
CO 2 

### emissions. In particular time-differentiated data is necessary to estimate the marginal
avoided CO 2 

### emissions related to electric generation. Such time-differentiated data could be based on metering or engineering estimates for a technology type that indicate the typical generation profile for the renewable energy resource. This could include time differentiation on an hourly, daily, or seasonal basis. If RECs can be banked and used or RPS compliance at a later time than the year in which the electricity ge neration related to the REC occurred, information about the quantity and vintage of RECs from prior year(s) generation that is used for RPS compliance will also be useful.

VI. Reporting and Recordkeeping for End-Use Energy Efficiency and Renewable Energy Programs and Measures

As discussed in the preamble, in section VIII.F.5, reporting and recordkeeping for enduse energy efficiency and renewable energy requ irements and programs will be an important component of certain types of sate plans. If a state plan incorporates renewable energy and demand-side energy efficiency requirements and programs under a rate-based approach or implements a mass-based portfolio approach with such measures, reporting and recordkeeping requirements for an approvable plan would differ from those applicable to an affected EGU. For example, these requirements may include complian ce reporting by an electric distribution utility subject to an end-use energy efficiency res ource standard (EERS) or renewable portfolio standard (RPS). They may also include reporting by a vertically integrated utility implementing an approved integrated resource plan. In the latte r instance, the utility may also be the owner and operator of affected EGUs, but additional reporting of quantified effects of renewable energy and demand-side energy efficiency measures under the utility plan would be necessary to demonstrate emissions performance under the state plan. In other instances, a state agency or

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77 entity or a private or public third-party entity may be implementing programs and measures that support the deployment of clean energy technologies that are incorporated in a state plan. In each of these instances, reporting of program compliance or program outcomes is a necessary part of an approvable plan to demonstrate performance under the plan.

In the preamble, the EPA seeks comment on appropriate reporting and recordkeeping requirements for entities implementing end-us e energy efficiency and renewable energy programs included as enforceable measures in a stat e plan, or for entities subject to requirements, such as an EERS or RPS, that are included as an enforceable state plan measure. This section provides examples of current reporting and r ecordkeeping under state energy efficiency requirements and programs, such as EERS, RPS, and utility and state deployment programs for energy efficiency and renewable energy. The section then examines the suitability of these reporting and recordkeeping practices as potent ial approaches in an approvable state plan.

A. Reporting for End-Use Energy Efficiency Programs and Measures
Reporting requirements and time frames (i.e. how often reports are required) for entities implementing energy efficiency programs and measur es are key considerations for state plans. In a state-regulatory context with PUC oversight, impact reports are the mechanism by which utilities and other program administrators doc ument energy (MWh) and demand (MW) savings. These reports serve as basis for PUC review of total achieved energy savings relative to program goals or regulatory requirements, as well as for determining financial perf ormance incentives for utilities, where they exist.

In most states, impact reporting is initially conducted at the level of efficiency “programs” (each consisting of numerous “project” installations or efficiency measures occurring at individual homes, commercial buildings , or industrial facilities). Program level data are then aggregated to the “portfolio” level to capture the full impact of energy efficiency investments occurring under a PUC’s jurisd iction for the timeframe of interest.

Impacts reports are typically submitted annually, but in some cases program administrators also provide interim (e.g., quarterly) reports. This added step can help inform

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78 progress towards goals, as well as provide for corrections in cases where evaluated (ex-post) energy savings are not achieving projected or claimed (ex-ante) savings levels.

The information provided below presents a range of common reporting elements and common practices implemented by state PUCs. Th ese reporting elements and practices – which raise important considerations for the reporting of energy-efficiency impacts in state plans –
include:

 State EM&V guidelines, protocols, and/ or framework utilized, where applicable

 Energy efficiency policy or program information reported to PUCs in annual reports:

o Short description of the polic ies or programs implemented

o Implementation schedules and timeframes

 Energy-savings impacts reported to PUCs in annual reports:

o Incremental annual and lifetime MWh savings for reporting (in the case of an energy efficiency program) or compliance years ( in the case of utility compliance with a multi-year Energy Efficiency Resource Standard)

o Peak demand (MW) impacts (reported in many, but not all states)

 Verification documentation, which shows that installation of energy efficiency measures occurred, and the installed measures are capable of generating energy savings

 EM&V process followed:

o Date and location of on-site facility visits and field observations

o Description of public process for review of overall EM&V approach, EM&V plan, and EM&V results

o Information about evaluators:

 Name of firms and individuals performing EM&V activities, and qualifications

 Certification that evaluators were selected through a public bid process, and are third-parties unaffiliated with efficiency program administrators or the state government

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79  EM&V methods used:

o Deemed savings values - name, date, and public location of technical reference manual (TRM) 101 

### used for deemed savings values

o Direct measurement approaches - description of the measurement approaches and reference to the EM&V protocols, standards, and guidance documents used

 Other documentation:

o Data about the quantity of measures/projects on which the full program-level energy savings impacts are based (i.e., information describing the sample size and sampling procedures used)

o Whether net or gross energy savings 102 

### are estimated, definitions used for gross and net savings, and the basis for gross to net calculations, if applicable

o Avoided transmission and di stribution (T&D) impacts assumptions, if applied

The energy savings EM&V reporting elements listed above vary from state to state in terms of type and level of documentation, and reports are provided in different formats from state to state. This significant variation among states in reporting contents and format raises several considerations for states utilizing demand-side en ergy efficiency programs in state plans. One is whether the reporting processes, timeframes, and documentation required by state PUCs, described above, are sufficient and appropriat e in the context of state plans. Another consideration is whether lead state agencies that oversee energy efficiency programs should be required to certify reported energy efficiency sa vings impacts on behalf of the state, potentially including certification that the values are approp riate and conservative, and meet their approval. A final consideration is whether and how energy savings impact reports are made available for public input and comment prior to finalization, recognizing that impact reports in many states

101 A technical reference manual (TRM) is a document cons isting of predetermined savings values, assumptions, methods, and calculation approaches for conducting EM&V of state demand-side energy efficiency programs. Most states with robust efficiency programs rely on a TRM. 102 Gross savings are the change in energy use and/or energy demand that results directly from program-related actions taken by program participants, regardless of why th ey participated in the program. Net savings refer to the change in energy use and/or energy demand that is directly attributable to a particular energy efficiency program.

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80 exist but are not easily located or widely accessible by the public, nor are they provided in
consistent formats from state to state.

B. Reporting for Renewable Energy Programs and Measures

1. Typical Reporting and Compliance Requirements under State RPS
Each state has different reporting and compliance requirements for its RPS, but all states with mandatory RPS require obligated entities to provide compliance reports to the state PUC or equivalent state oversight agency. Compliance oblig ations are typically specified in authorizing legislation, regulations, or PUC orders. Compliance is typically on an annual basis, and includes a list of required reporting elemen ts. Some states also require distribution utilities to provide an implementation plan describing how they will comp ly with the state RPS rules in the future.

Data requirements for reporting may vary based on the design and implementation of a RPS. However, for nearly all state RPS requirements, annual compliance report data is based on measurable electric generation results and verified through tracking system data. 103 

### In some states, compliance reports may also include st ate-level projections of renewable energy generation resulting from current or proposed state RPS policies.

The most common form of tracking system for RPS compliance is a regional or state REC tracking system or registry. These systems track RECs for both the compliance and voluntary markets. RECs are typically provided with a unique identification number and may be certified by a third-party verifier. Annual comp liance reports containing REC data typically include the number of RECs the utility or load -serving entity procured and retired, what renewable energy generators supplied the RECs, and how much the utility spent on procuring the
RECs.

2. Typical Reporting for Renewable Energy Deployment Programs 104

103 Some state RPS require electric utilities to procure a specified amount of renewable energy generating capacity, rather than supply a specified number of MWh or percentage of electricity supply from renewable energy generation to retail customers. 104 In this section, “deployment programs” refers to incentive programs and market transformation programs designed to accelerate the market deployment of renewable energy technologies.

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81 Renewable energy deployment programs involve the provision of a payment or credit for a renewable energy project, or for a quantified amount of electricity generation, in the case of performance-based incentives. Qualification of eligible projects and payment for qualifying electric generation (or related attributes) require reporting of electric generation and other project for each specific program. Program administrators use this information to track program progress and report to PUCs or other oversight entities. The summary below addresses typical reporting required for utility-administered programs, as well as programs administered by non-profit entities and state agencies and authorities.

Reporting for utility administered renewable energy incentive programs Some utilities offer incentives to electricity consumers to acc elerate the deployment of renewable energy technologies, such as rebates, feed-in tariffs, and net metering programs. As mentioned previously, it is easier to quantify th e renewable electricity generation resulting from some programs than it is for others. Utilities administering FITs, for example, will track the number of customer contracts, resource type , capacity of each contracted project, MWh generated, and utility expenditures for that ge neration under the tariff. In contrast, utilities administering a rebate or loan program are more likely to track the number of customer participants, the type and size of the projects, the cost of the projects, and the amount of rebates paid or loans provided. Measuring the electric generation output of these projects may not necessary to evaluate program status.

Net-metering is a renewable energy incentive program that is based on performance, but where the total output of the net-metered devi ce is often unknown. Utilities reporting on netmetering programs track the number of participating customers, the type and size of net-metered systems, and overall net-metered capacity. However, the gross amount of electricity generated may not be known if a single bi-directional meter is used. Such meters only record net electricity withdrawn from the grid or net electricity productio n supplied to the grid during an identified time period. Utilities and the customers where the renewable energy generating system is located may not necessarily know the total electric generation from the renewable energy system, unless
two meters are installed – one to measure to tal output from the customer-sited system, and another to measure the total electricity purchased from the utility.

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82 Many of these renewable energy deployment programs are developed as part of requirements by PUCs, and therefore utilities mu st provide reporting on a routine basis to the PUC about program expenditures and outcomes (typically quarterly or annually). These records should be readily accessible to states for estimating the impacts of their renewable energy deployment programs included in a state plan. However, some utility incentive programs are administered by distribution util ities that are not regulated by a state PUC (e.g., municipal and cooperative electric utilities). In these instan ces program reporting data may not be readily available to a state, unless separately required by a state if such programs are included in a state plan.

Renewable energy deployment programs may be designed and implemented under the auspices of a utility integrated resource plan (IRP). 105 

### IRPs document how a utility will meet forecasted annual peak and energy demand over a defined period of time through a combination of supply-side and demand-side resources. IRPs are typically mandated through state legislation or PUC orders and may include renewable energy generation planning, particularly as it relates to compliance with in-state requirements. IRPs are typically submitted on an annual basis to a state utility commission and/or other state entity, and address a multi-year period (e.g., 10 years is a typical period for an IRP). IRPs are a good resource for tracking and forecasting utility renewable energy developments within a state. Though they may not include renewable energy production data, data included in IRPs may help states project renewable energy generation trends in subsequent years, and are a good resource for the development of state plans.

Reporting for renewable energy incentive programs administered by non-profit or state
entities State renewable energy financial incentives are typically administered by a PUC, state revenue agency, other state agency (e.g., state energy office), or a private non-profit or for-profit entity contracted by a state agency. These programs may include an administrative process for

105 IRPs are typically required in states with vertically inte grated electric utilities, but are less common in states that have deregulated their electricity sectors and introduced co mpetition for the supply of electricity to retail customers.

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83 pre-qualification, which in some instances may be competitive (e.g., performance-based contracts) or available on a first-come, first-serve basis (e.g., capped production tax incentive). Applications to incentive programs are good sources of data, and program administrators usually compile data from approved applications to track program status. Additional reporting data is also typically required to receive the incentive. For example, a production-based tax incentive is calculated based on the amount of electricity gene rated by a renewable energy installation, which may be tracked and verified through utility or third-party metering protocols. These reports, which are currently used for internal reporting for budgetary control and performance evaluation, and to track other performance metrics for regular public program reporting, could form much of the basis for reporting under state plans for such measures.

3. Considerations for Reporting Requirements for Renewable Energy Measures
in State Plans

State renewable energy requirements, such as RPS and FITs, and incentive programs typically include robust reporting requirements. For nearly all state RPS requirements, annual compliance report data is based on measureable electric generation, using revenue

- quality meters, and verified through tracking system data. 106 

### Other requirements and programs that provide performance-based payments and incentives, such as FITs, net metering, and performance-based tax incentives, also require reporting of metered generation output. 107 

### State and utility incentive programs where payment of incentives is not based on electric generation may not currently be sufficient for repor ting under a state plan. Additional reporting requirements may be necessary if these programs are included as enforceable measures in a state plan.

In addition to the reporting states currently require for renewable energy requirements and programs, supplemental reporting information or adjustments may be necessary for state

106 Small distributed renewable energy systems, such as those below 10 kW in capacity, are often allowed to use engineering estimates to determine annual output. 107 Some of these programs, such as net metering, may also require supplemental reporting in order to track total generation that avoids CO 2 emissions. In many instances, net meteri ng programs only track the net electricity supplied to a customer or supplied to the grid by the re newable energy system, rather than total generation output. Deleted:

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84 plans to demonstrate the avoided CO 2 

### emissions associated with these requirements, programs, and measures. States may need to require additi onal reporting detail, such as the location of renewable energy generating units that supplie d output used to comply with a state RPS. Additional reporting detail about when renewable en ergy was generated may also be valuable for estimating the avoided CO 2 

### emissions from renewable energy generation, especially if a marginal avoided emission rate approach is used. This includes reporting of the typical generating profile of a renewable energy generating unit, group of units, or renewable energy resource type. 108 

### For distributed renewable energy resources, reporting of the MW capacity of generating systems that are installed as a re sult of state requirements or programs during a reporting period would also be useful for estimating avoided CO 2 

### emissions. These distributed resources, since they are located “behind” the utility meter at a customer location, have a similar effect in reducing the demand for electricity supplied from the grid as end-use energy efficiency

measures.

Example reporting requirements that provide sufficient data for estimating the avoided
CO 2 

### emissions from renewable energy requirements and programs might include the following:

 Metered MWh generation, using a revenue quality meter, or estimates of annual output for small systems below 10 kW in capacity

 MW capacity of “behind-the-meter” distributed renewable energy generating systems added during a reporting period as the result of a state program

 For renewable energy resources reported, including through REC data, the typical generating profile of a renewable energy generating unit, group of units, or renewable energy resource type

 For REC data, information including the follow ing generator attributes: type of resource (e.g., wind), plant-level emissions, geographic location, nameplate capacity (MW), commercial operation date, ownership, and the eligibility for RPS compliance or voluntary market certification

108 This might include information about the seasonal or da ily generating profile of the generating unit or renewable energy resource type.

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85 VII. Treatment of Interstate Emission Effects
Programs and measures in a state plan, such as RE and demand-side EE measures, may affect the emission performance of the interconnect ed electricity system beyond a state border. In addition, many state measures allow for actions in neighboring states to meet the in-state requirement, or explicitly address CO 2 

### emissions in neighboring states. For example, many state renewable portfolio standards allow for generation by qualifying renewable energy sources in other states to count toward meeting the state po rtfolio requirement. Some states also apply CO 2 

### emission requirements related to the generation of power purchased by regulated utilities, including power imported from out of state.

As discussed in the preamble to the proposal, in section VIII.F.6, the EPA recognizes the complexity of accounting for interstate effects as sociated with measures in a state plan in a consistent manner, to minimize the likelihood of double counting. The EPA also realizes that
interstate effects on CO 2 

### emissions from affected EGUs could be attributed in different ways in the context of an approvable state plan. This section discusses in more detail the options and
alternatives for treatment of interstate CO 2 

### emission effects presented in the preamble. These options and alternatives could be applied to both projections of plan performance and demonstration of achieved emission performance under a plan. These options and alternatives may not be mutually exclusive – in some instances states could apply different approaches, without introducing the potential for double coun ting of emission effects. One option presented could lead to double counting of em ission effects, and we highlight these aspects of this option in
the discussion below.

In general, the options and alternatives address different possible state plan scenarios, and consider the range of interstate approaches that states are currently using to implement electricity sector policies, such as multi-state emission bu dget trading programs and regional renewable energy certificate markets for state RPSs. The options and alternatives reflect possible accounting approaches for interstate emission effects under CAA section 111(d) that could potentially align with these current state program s and measures that we anticipate states may want to include in a state plan.

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86 A. Background
Electricity flows across state lines. Often el ectricity load centers (i.e., areas of high electricity demand) in one state are supplied in pa rt by generating units in another state. As a result, some states are net exporters or import ers of electricity on an annual basis. Reducing electricity load through improved end-use energy efficiency (e.g., through state energy efficiency programs) or deploying new renewable energy el ectric generating capacity (e.g., through a state RPS) therefore can result in CO 2 

### emission effects that are realized outside the state that implements the regulation or program that produ ces the effects. Reducing electricity demand or increasing available electric generating capacity also often impacts the economic dispatch curve and locational economics that are used to dispatch EGUs on a regional basis. As a result, state end-use energy efficiency and renewable energy regulations and programs often have regional effects on electricity generation and avoided CO 2 

### emissions. In addition, many state regulations explicitly address CO 2 

### emissions in neighboring states, or a llow for actions in neighboring states to meet an in-state regulatory requirement. For example, many state RPS allow for generation in
other states to count toward meeti ng a utility portfolio requirement.

End-use energy efficiency actions reduce elect ricity load, and ultimately impact electric generation. In some instances improving en d-use energy efficiency will reduce electric generation nearby a load center (e.g., in the case of a load pocket with limited access to electricity transmission capacity). In such cases, it may be feasible to directly link in-state enduse energy efficiency programs and measures to avoided CO 2 

### emissions from specific in-state EGUs. More often, reduction of electricity load will impact EG U dispatch across a regional generation control area, based on factors such as power plant economics and electricity transmission capability, and could also impact flows between control areas. 109 

### In these cases, state end-use energy efficiency programs and meas ures will affect electricity generation in the state that reduces load, as well as in neighboring states.

109 Often these dispatch economics differ by location, based on electricity demand, transmission constraints, and generation economics of individual power plants necessa ry for meeting demand (e.g., in competitive wholesale markets, these factors are represente d through locational marginal prices (LMPs), which determine dispatch).

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87 State RPS regulations also impact electricity generation at a regional level. Over time, state RPSs result in the introduction of new, incremental renewable energy generating capacity to regional generation control areas, which affects EG U dispatch at the regional level. State RPSs are typically applied to electric distribution utiliti es as a percentage of sales (e.g., a specified percentage of delivered electricity must come from qualifying renewable energy sources). Many state RPSs do not require the qualifying renewa ble energy electric generation to take place within the state, or even be delivered into the state, but instead require that the renewable energy be supplied within (or delivered into) the ISO/RTO in which the state resides. Often, utility compliance with state RPS is through the submis sion of renewable energy credits (RECs), which represent the attributes of renewable energy generation but not the actual electricity generated. As a result, in many cases the intent of the state policy is often to affect the characteristics of the regional electric generation mix, rather than the state generation mix.

The approach to implementing an RPS may differ in vertically integrated, cost-of-service states where the distribution utility also owns electric generating capacity and dispatches generation resources within its se rvice territory. In such cases, the RPS may require a utility to increase its renewable energy generating capacity, rather than supplying a percentage of the electricity it delivers to retail customers from renewable energy sources to meet load. A number
of state RPS also include “carve-outs” or “set-a sides” where a portion of the renewable energy supplied to retail customers must come from renewable energy generating capacity located inside the state. Most of these carve-outs are for distributed solar photovoltaic generating capacity, which are located at the point of customer end-use (e.g., rooftop mounted solar PV on residential homes and commercial buildings). 110 

### Distributed solar PV capacity of ten provides benefits to the electric distribution system by im proving distribution system reliability and avoiding the need for distribution system capacity upgrades. This type of distributed renewable energy generation has effects similar to end-use energy efficiency, as it reduces the customer electricity load that must

110 A number of RPS also have carve-outs for other renewable energy resources, typically those where there is a significant renewable energy resource located in the state. An example is carve-outs for offshore wind energy in coastal states.

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88 be met through large EGUs connected to the grid. 111 

### Regardless of the approach taken, state RPS regulations typically have impacts on EGU dispatch, and related avoided CO 2 

### emissions, beyond
the state border.

B. Summary of Possible Approaches for Treatment of Interstate Emission Effects
As discussed in the preamble, the EPA is proposing a set of approaches for addressing
interstate emission effects that result from the implementation of state plans that incorporate enduse energy efficiency and renewable energy programs. The preamble also solicits comment on additional alternatives. The proposed approaches in the preamble include:

 For EE programs and measures:

o A state may take into account in its plan only those CO 2 

### emission reductions occurring in the state that result from demand-side energy efficiency programs and measures implemented in the state.

o States participating in multi-state plans w ould have the flexibility to distribute the
CO 2 

### emission reductions among states in the multi-state area.

o States could jointly demonstrate CO 2 

### emission performance by affected EGUs through a multi-state plan in a contiguous electric grid region, in which case attribution among states of emission reductions from demand-side energy efficiency measures would not be necessary.

 For RE programs and measures:

o Consistent with existing state RPS policies, a state could take into account all of
the CO 2 

### emision reductions from renewable energy programs and measures implemented by the state, whether they occur in the state and/or in other states.

o States participating in multi-state plans w ould have the flexibility to distribute the
CO 2 

### emission reductions among states in the multi-state area.

o States could jointly demonstrate CO 2 

### emission performance by affected EGUs through a multi-state plan in a contiguous electric grid region, in which case

111 Distributed solar PV is also typically peak coincident , meaning it provides its greatest electric generation output at times of peak system electricity demand. At many times of the day and year, solar PV systems supply electricity back to the grid, when PV system out put exceeds building electricity demand.

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89 attribution among states of emission reduc tions from renewable energy measures would not be necessary

This section surveys the range of potential approaches that could be applied for individual state plans, as well as approaches that could be applied on a regional basis. The surveyed approaches include those proposed, as well as alternatives. These basic approaches, including variants of some approaches, include:

 State may only claim the impact of a measure in reducing in-state EGU CO 2 

### emissions For plan measures such as end-use energy efficiency and renewable energy regulations and programs, estimating the avoided CO 2 

### emissions from in-state versus out-of-state EGUs could be addressed through modeling, other analytical tools, or proxy metrics (e.g., net import factor).

 State that implements the measure cl aims the emissions reduction benefit Under this approach, the state that impl ements the measure (e.g., end-use energy efficiency and renewable energy regulations or programs, or an emission limit that addresses out-of-state generation) claims the avoided CO 2 

### emissions, regardless of where they occur.

 Cooperative multi-state accounting Multiple states are allowed to mutually ag ree to how they will distribute avoided CO 2 

### emissions from state plan measures (e.g., end-use energy efficiency and renewable energy regulations or programs, or an emission limit that addresses out-of-state generation) across their respective EGU fleets. Avoided CO 2 

### emissions are distributed among states by agreed formula they derive – an accounting “credit” in one state for
out-of-state avoided CO 2 

### emissions is complemented by an accounting “debit” in
the other state where the avoided CO 2 

### emissions occurred (i.e., through an increase in reported CO 2 

### emissions or CO 2 

### emission rate).

 Tradable regional EE/RE credit market This is a variant of the multi-state accounting approach, which could be applicable where multiple states in a region are implementing rate-based state plans. Under this approach, state end-use energy efficiency and renewable energy regulations and programs that meet

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90 EM&V guidelines or requirements are allowed to generate credits, based on MWh of energy savings or renewable energy generation. These credits, which are denoted in
avoided tons of CO 2 

### or avoided MWh, could be used by affected EGUs toward demonstration of compliance with state rate-based CO 2 

### emission limits within a designated region. EE/RE credit issuance could be on a project and/or program basis. State accounting for interstate emission effects would be addressed through the credit market and determined based on credits held by affected EGUs.

 Regional demonstration by states of EGU emission performance States are allowed to regionally demonstrat e emission performance by affected EGUs. Stets jointly demonstrate emission performan ce for affected EGUs, in terms of total CO 2 

### emissions (under a mass-based multi-state plan) or weighted average CO 2 

### emission rate (under a rate-based multi-state plan).

 The EPA jointly assesses regional performance achieved in aggregate by all individual state plans in a grid region The EPA assesses interstate effects on a region al basis during the plan review process. The EPA requires states to agree to an interstate attribution process only if necessary (i.e., if regional performance falls short of the aggregated identified performance levels for
affected EGUs in individual st ate plans). Alternatively, the EPA requires plan revisions if regional performance falls short of the aggregated regional performance level (i.e., the aggregated identified performance levels for affected EGUs in individual state plans).

Table 3 includes illustrative examples of the application of some of the different approaches for addressing interstate emission eff ects summarized above. The table explains how these approaches might be applied in different state plan contexts. The illustrative examples consider the range of approaches states are currently using to implement electricity sector policies, all of which interstate effects, such as multi-state emission budget trading programs, regional renewable energy certificate markets used for state RPS compliance, and end-use energy efficiency programs.

Table 3. Applied Examples of Intersate Emission Effects Attribution Approaches

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91 1. State May Claim the Impact of a Measure on CO 2 

### Emissions from Affected EGUs
Within its Borders

Under this approach, the effect of a state measure could be applied to help demonstrate emission performance by affected EGUs in th e state if it has the effect of avoiding CO 2 

### emissions from those in-state EGUs. This could be done regardless of whether the action taken to implement the state measure occurs within or ou tside the state. For example, renewable energy generation that occurs outside the state as a result of a state renewable portfolio standard obligation would still be a valid state plan action, provided the out-of-state renewable energy generation has the effect of avoiding CO 2 

### emissions from affected EGUs inside the state. As another example, for a state that is a net importer of electricity, improvements in demand-side EE and related reductions in electricity demand may reduce the need for generation from both
affected in-state and out-of-state EGUs. These electricity demand reductions could be applied to help demonstrate emission performance by affected EGUs in the state if the reduction in electricity demand has the effect of avoiding CO 2 

### emissions from those in-state EGUs.

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92 Estimating the effect of RE and demand-side EE measures on in-state versus out-of-state
EGU CO 2 

### emissions could be addressed through modeling, other analytical tools, or proxy metrics such as a net import factor.

Modeling could be used to assess the interstate effects of state measures on EGU CO 2 

### emissions, both for projections of emission performance under the plan and ex post demonstration of performance achieved. Under th is approach, both projected plan performance and performance achieved is assessed on a state-by-state basis.

Ex ante projections of plan performance To project the effect of EE/RE measures un der a state plan, a dispatch model would be applied to a grid region to estimate the marginal or average avoided CO 2 

### emissions impact of the plan measures on a state-by-state basis within the region. To the extent that a state’s EE/RE measures were projected to avoid CO 2 

### emissions from its own in-state EGUs, these effects could be applied to meet the required level of CO 2 

### emission performance for affected EGUs in the state plan. (See section IV.C of this TSD for a full discussion of using a dispatch modeling approach to projected avoided CO 2 

### emissions that will be achieved through a plan.)

Ex post demonstration of plan performance To assess the state-by-state avoided CO 2 

### emissions that result from the implementation of a plan, a dispatch model would also be applied to a grid region, on a retrospective “look-back” basis. This modeling would assess the avoided CO 2 

### emissions resulting from reported MWh of energy savings and MWh of reported renewable energy generation, as a result of implementation of EE/RE measures in the plan. Under a rate-based plan approach, modeled estimates of avoided
CO 2 

### emissions, based on reported EE savings and RE generation, could be applied through an administrative adjustment by the state program ad ministrator or through the issuance of tradable EE/RE credits within the state. For ex post demonstration under a mass-based plan approach, performance would be determined based on reported stack CO 2 

### emissions from affected EGUs— no further analysis would be necessary. (See section IV.C of this TSD for a full discussion of using a modeling look-back appr oach to estimate avoided CO 2 

### emissions.)

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93 Use of simplified proxy metrics to apportion effects among states Simplified metrics, such as a net electricity import or export factor, might also be applied to assess the impact of state actions in avoiding CO 2 

### emissions from in-state affected EGUs. For example, in a state that imports 30% of electricit y on average during a year, energy savings from EE measures might be multiplied by a factor of 0.70. 112 

### Avoided CO 2 

### emissions might then be calculated by multiplying this adjusted energy savings number by the average or marginal CO 2 

### emission rate for affected EGUs in the state. This type of approach could be employed in both projections of plan performance and ex post de monstrations of performance. However, this method would be subject to uncertainty, as electri city net imports may vary significantly on an annual basis, due to changes in system dispatch. (See section IV.C of this TSD for a discussion of dispatch dynamics that affect avoided CO 2 

### emissions.)

This approach would avoid double counting of emission effects of state measures amongstates. However, it could reduce incentives for states to employ measures that have a systemwide, regional effect in reducing EGU CO 2 

### emissions. In effect, because an adjustment factor would be applied to energy savings under this approach, a net importer state would need to achieve greater energy savings through end-use energy efficiency requirements and programs to
achieve a ton of avoided CO 2 

### emissions under its plan than a state that is not a net importer.

112 In this instance, it would be assumed that 30% of th e reduction in electricity load resulted in avoided CO 2 emissions from out-of-state EGUs that serve electricity load in the importing state.

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94 2. State that Implements the Meas ure Claims the Emission Effects
Under this approach, the state that implements the measure (e.g., an EERS or RPS, or an
emission limit that addresses the attributes of purchased electricity from out-of-state generation)
claims the avoided CO 2 

### emissions, regardless of where they occur.

If the avoided CO 2 

### emissions from state plan measures at the regional level are greater
than avoided emissions from affected EGUs within the state, these interstate effects would need to be accounted for and applied to affected EGUs within the state. This could be achieved through an administrative adjustment by the state, or through a tradable credit system that is
limited to affected EGUs in the state.

Under an administrative adjustment approach , out-of-state avoided emissions would be applied to the in-state EGU fleet by the state program administrator when determining average
fleet CO 2 

### emission rate or tonnage CO 2 

### emissions. Under a tradable credit approach, credits
would be issued for all avoided CO 2 

### emissions resulting from appl icable state plan measures, without regard to where the avoided emissions occurred. Since the tradable credit system would be limited to affected EGUs in the state, use of the credits by affected EGUs when demonstrating compliance with a rate-based emission limi ts would functionally apply the avoided CO 2 

### emissions to the state that was responsible for the measure.

This approach provides a clear policy signal an d incentives that reward state actions that
reduce EGU CO 2 

### emissions on a system-wide, regional basis. However, this approach, absent cooperative accounting among states in a grid region, as described below, will likely lead to double counting of emission impacts among states, which could reduce the overall emissions reductions achieved through state plans on a national basis under CAA section 111(d). We also note below that other approaches could also provide incentives for a regional, system-based approach to achieving CO 2 

### emissions reductions from affected EGUs, without raising the prospect of double counting of emission effects among state.

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95 3. Cooperative Multi-State Accounting of Interstate Emission Effects
Under this approach, multiple states would be allowed to mutually agree on how they
will distribute avoided CO 2 

### emissions from RE and demand-side EE measures across their respective EGU fleets. Avoided CO 2 

### emissions would be distribute d among states according to a formula that they specify. Based on this agreed formula, each state would adjust its demonstrated emission performance by affected EGUs accordin gly. In effect, a “credit” for out-of-state emission effects in one state would be complemented by a “debit” for such effects in another

state.

This approach provides states with discretion about how to attribute interstate effects, based on their situations and policy preferences in a grid region. Importantly, this approach also avoids the potential for double counting of interstate emission effects among states. However, this approach is premised on regional collaboration among all states in a grid region. Not all states in a grid region may be willing to cooperate in implementing such an accounting approach.

4. Tradable Regional EE/RE Credit Market
Under this approach, RE and demand-side EE ac tions that meet applicable quantification, monitoring, and verification requirements would be issued tradable credits that could be applied by affected EGUs to their reported CO 2 

### emission rates when demonstrating compliance with an emission limitation in a state plan. 113 

### A credit issued in one state could be used by an affected EGU in another state toward meeting its respective rate limit. 114



### A regional credit market would be premised on agreement among states that credits issued throughout a region could be used in multiple states. The distribution among different states of usage of the credits would be determined by economic factors such as credit prices and

113 These credits might be denoted in avoided CO 2 emissions or MWh of electricity savings or electricity generation, as described above in Section VI.E.3., incorporating RE and demand-side EE measures under a rate-based approach. Depending on a state’s circumstances and its plan approach, these tradable credits might represent a new instrument created for use under a state plan, or a state might use an existing instrument, such as RECs. 114 Credits could be issued on a program or project basis. The types of measures for which credits could be issued and the basis for issuing credits would be an enforceable element of a state plan.

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96 EGU marginal emissions abatement costs. In eff ect, accounting of interstate effects would be allocated among states based on prices in the credit market.

This approach is applicable if multiple states are implementing rate-based state plans. Where states were implementing a mix of rate-based and mass-based state plans in a shared grid region, this approach would lead to double count ing of emission effects among plans, unless this market-based EE/RE credit approach was also coupled with a cooperative accounting agreement among states. In this latter instance, for st ates implementing a mass-based approach, where
credits for avoided CO 2 

### emissions are transferred to affected EGUs located in another state for compliance purposes, the state from which credits were transferred would adjust its reported CO 2 

### mass emission from affected EGUs when demonstrating achievement of the required CO 2 

### emission performance level by affected EGUs identified in the state plan. 115



### 5. Regional Demonstration by States of Emission Performance
Under this approach, multiple states would demonstrate CO 2 

### emission performance by affected EGUs on a regional basis. 116 

### This could allow states in a contiguous grid region to implement a portfolio of RE and demand-side EE measures without the need for state-by-state
attribution of avoided CO 2 

### emissions. Instead, states would asse ss the impact of state measures in avoiding CO 2 

### emissions from the fleet of affected EGUs in the multi-state region.

This approach creates incentives for the implementation of system-based approaches that collaboratively reduce EGU CO 2 

### emissions on a regional basis, while also avoiding the need to attribute interstate emission effects among states . However, regional collaboration will require more time for the development of multi-state pl ans. This approach is also premised on the

115 Note that in this example, state reporting of overall achieved CO 2 emission performance by affected EGUs under a state plan is distinct from demonstration of compliance by affected EGUs subject to a mass-based CO 2 emission limit. For EGU compliance, no adjustment would be made to CO 2 emissions reported by affected EGUs subject to the mass-based emission limit, even though emis sions from these affected EGUs may have been reduced as a result of EE/RE regulations and programs implemented in a neighboring state. In this case, the state would adjust the overall CO 2 emissions from the affected fleet to account for the “export” of avoided CO 2 emission credits, in order to demonstrate the overall level of CO 2 emission performance that is assumed to have been achieved by the affected EGU fleet under the plan. 116 This approach could be applied for CO 2 emission performance on either a rate or mass basis.

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97 willingness of all states in a gr id region to participate in the development and implementation of a multi-state plan. Some states in a grid re gion may be unwilling to collaborate regionally.

6. Assessment of Interstate Effects by the EPA in the Course of State Plan Review
Under this approach, the EPA would evaluate interstate effects on a regional basis during the plan review process. 117 

### The EPA would assess the emissions performance of affected EGUs on a regional basis, considering the measures contained in the group of state plans for a respective grid region. Under this approach, the EPA might conduct an analysis that considers all of the state program measures together on a combined basis and evaluates projected emissions performance achieved by affected EGUs in the region.

To the extent that all affected EGUs in a regi on are projected to achieve the required level of performance represented in individual state pl ans, or are projected to achieve an aggregate regional level of performance consistent with the level of required performance included in all state plans in the region, instances of double count ing of interstate effects among states are less important. The EPA could indicate as part of pl an approval that it will review actual emission performance achieved by affected EGUs during the plan period on a regional basis.

VIII. Appendix

Survey of Existing State Policies and Programs that Reduce Power Sector CO 2 

### Emissions
[This appendix will include the content in the document, Survey of Existing State Policies and Programs that Reduce Power Sector CO 2 

### Emissions. This draft document was submitted to OMB on April 3, 2014.]

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1 

### Technical Support Document (TSD) for Carbon Pollution Guidelines for Existing Power Plants: Emission Guidelines for Greenhouse Gas Emissi ons from Existing Stationary Sources: Electric Utility Generating Units

Docket ID No. EPA-HQ-OAR-2013-0602

Projecting EGU CO 2 

### Emission Performance in State Plans

U.S. Environmental Protection Agency Office of Air and Radiation

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2 

### Table of Contents

I. Introduction .................................................................................................................. ......3 II. Analytic Approaches for Projecting CO 2 

### Emissions from Affected EGUs ..................5 A. Electricity System Modeling Approaches for Projecting EGU CO 2 

### Emissions .......5 B. Growth Tools for Projecting Future EGU Utilization and CO 2 

### Emissions...............9 III. Translating from a Rate-Based Emission Performance Goal to a Mass-Based Emission Performance Goal ............................................................................................11 A. Concept ...................................................................................................................1 1 B. Projection Scenarios ................................................................................................13 IV. Projecting CO 2 

### Emission Performance under a State Plan – Overview .....................17 V. Applied Considerations for Different Types of State Plans .........................................18 A. End-Use Energy Efficiency and Renewable Energy .............................................18 B. Emission Budget Trading Programs ......................................................................32 VI. Process Considerations ....................................................................................................38 A. Provision of the EPA Guidance .............................................................................38 B. Party that Translates the Rate-Based Goal to a Mass-Based Goal ........................40I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### I. Introduction
As discussed in the preamble, in section VIII. F.7, all state plans will need to include a projection of the CO 2 

### emission performance by affected EGUs that will be achieved under a state plan (inclusive of plan measures that avoid CO 2 

### emissions from affected EGUs, such as end-use energy efficiency and renewable energy). Depending on the type of plan approach, this will include either a projection of the average CO 2 

### emission rate achieved by affected EGUs or total
CO 2 

### emissions from affected EGUs.

The EPA is also proposing that a stat e may translate the state rate-based CO 2 

### emission performance goal for affected EGUs to an equivalent mass-based CO 2 

### emission performance goal. If this translation option is used, a state pl an must also include a projection used to derive
the mass-based CO 2 

### emission performance goal. This transl ation will involve a projection of CO 2 

### emissions from affected EGUs during the initial 2020-2029 plan performance period and in
2030 , under a scenario that assumes the rate-bas ed goal in the emission guidelines is met.

As discussed in the preamble, the EPA is striving to find a balance between providing state implementation flexibility and ensuring th at the emission performance required by CAA section 111(d) is properly defined in state plan s and that plan performance projections have technical integrity. The credibility of state plans under section 111(d) will depend in large part on ensuring credible and consistent emission performa nce projections in state plans. Therefore, the use of appropriate methods, tools, and assu mptions for such projections is critical.

The preamble, at section VIII.F.7, seeks comment on options presented for how CO 2 

### emission projections might be conducted in an a pprovable state plan, and how different types of state plan approaches are represented in thes e projections. These options include the use of historical data and parameters for estimating th e future impact of individual state programs and measures. Alternatively, a projection could be based on modeling, such as use of a capacity expansion and dispatch planning model, or a dispatch simulation model. 1 

### This latter approach would be able to capture dynamic interactions within the electricity sector, based on system

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### operation and market forces, including interactions among state programs and measures and the dynamics of market-based measures.

In the preamble, the EPA further seeks comment on whether the EPA should develop guidance that describes acceptable projection approaches, tools, and methods for use in an approvable plan, as well as whether the EPA sh ould provide technical resources for conducting projections.

This technical support document (TSD) elabor ates these options and considerations. The TSD discusses possible analytic approaches for translating from a rate-based CO 2 

### emission performance goal to a mass-based goal, and projecting the CO 2 

### emission performance that will be achieved through a state plan. It discusses both modeling and non-modeling approaches, such as electricity sector capacity expansion and di spatch planning models, dispatch simulation models, and growth tools that base projections on historical data and algorithms. The TSD also discusses possible approaches for developing inpu ts that are used for emission projections and applied considerations for different types of state plans. Topics addressed include:

 Section II discusses analytic approaches for projecting CO 2 

### emissions from affected
EGUs

 Section III discusses the concept and practice of translating from a rate-based CO 2 

### emission performance goal to a mass-based CO 2 

### emission performance goal

 Section IV discusses the concept and practice of projecting EGU CO 2 

### emission performance under a state plan

 Section V discusses applied considerations for projecting EGU CO 2 

### emission performance under different types of state plans, including:

o Considerations that should be addressed in conducting projections of emission performance for different types of plans

o Data needs and methods for developing inputs to EGU CO 2 

### emission projections, for different types of state plans

 Section VI discusses process considerations for conducting EGU CO 2 

### emission projections for state plans, including:

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### o Whether the EPA should provide guidance and other analytic support for conducting projections in state plans and translation of rate-based CO 2 

### emission performance goals to mass-based goals

II. Analytic Approaches for Projecting CO 2 

### Emissions from Affected EGUs
This section surveys different types of methods and tools for projecting CO 2 

### emissions from affected EGUs, including modeling tools and other tools that base projections on historical data and use algorithms to extrapolate future CO 2 

### emissions performance based on past performance.

A. Electricity System Modeling Approaches for Projecting EGU CO 2 

### Emissions

1. National-scale capacity expansion and dispatch planning models
National-scale electricity capacity expansion and dispatch planning models are typically used for fundamentals-based projections of the po wer sector (i.e., projections of the expected response of the sector to factors such as electri city demand, fuel prices, and emission constraints) that may extend over a period of several decades. These models are built to evaluate the impacts of market, technical, and regulatory factors on the electric power sector and related markets. Typical outputs of such models include EGU disp atch, fuel consumption, fuel prices, wholesale electricity prices, emissi ons, EGU retirements, and infrastructu re expenditures (e.g., addition of new EGU capacity and installation of retrofit pollution control technologies).

National-scale electricity capacity expansion and dispatch planning models have moderate spatial detail with broad scope, generally encompassing the entire country or transmission system interconnects (i.e. Eastern, Western, and ERCOT), which are subdivided into smaller areas, such as balancing authorities or control areas. 2 

### For computational efficiency, these models generally model several representative hours of the year, or aggregate hours into representative bundles with similar electricity de mand profiles (i.e. peak, shoulder, off-peak). In these models, to reduce model size, existing EGUs may be aggregated into “model plants” to the extent that such EGUs share key unit characteristic s, such as location, size, efficiency, operating

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### costs, pollution retrofit control status, age, and fu el type use/availability. These types of models are well suited to project dynamic entry and exit (capacity expansion and unit retirement) to meet energy and capacity requirements while minimizing system costs, maintainin g reliability criteria, and following other constraints, such as mi nimum build times, transmission constraints, renewable energy availability, or emission limitations.

2. Utility-Scale Capacity Expansion and Dispatch Planning Models
Utility-scale capacity expansion and dispatch pl anning models are similar in concept to related national-scale models. However, utility-scale capacity expansion and dispatch planning models are typically used for evaluating narrower utility planning and investment decisions, such as procurement of a specific new electric generati ng facility and retirement or retrofit decisions for existing capacity within a specific utility’s te rritory. Utility planning m odels typically project outcomes for periods of up to two decades. Utility-scale capacity expansion and dispatch planning models are an industry standard, used regularly in state electricity regulatory proceedings. Within the electricity sector there is broad familiarity with these models at state PUCs. Multiple vertically integrated utilities use capacity expansion and dispatch planning models to conduct forward planning and re view the economics of specific EGU retrofit decisions. Utilities that submit integrated resource plans (IRP) typically use a utility-scale capacity expansion and dispatch planning model to examine long-term strategies and develop short-term action plans. 3 

### Utilities have experience using these models to examine CO 2 

### emission reduction strategies or CO 2 

### emission constraints, as IRP scenarios may include greater penetration of end-use energy efficiency or renewable energy, proxy CO 2 

### emission prices, emission trading, and limits on CO 2 

### mass emissions.

3 See, for example: The Duke Energy Caroli nas IRP (Annual Report), September 2012, available at http://www.energy.sc.gov/file s/view/Duke_IRP 2012.pdf ; PacifiCorp 2013 IRP (Vol 1), April 2013, available at http://www.pacificorp.com/es/irp.html ; TVA IRP, March 2011, available at http://www.tva.gov/environment/reports/irp/archive/index.htm ; Georgia Power Company 2013 IRP, January 31, 2013, available at http://facts.psc.state.ga.us/Pu blic/GetDocument.aspx?ID=145981 ; 2011 Joint IRP of Louisville Gas and Electric and Kentucky Utilities Company, April 2011, available at http://psc.ky.gov/PSCSCF/2011% 20cases/2011-00140/20110421_L G%26E-KU_IRP_Volume%20I.pdf ; Great River Energy IRP, November 2012, available at http://www.greatriverenergy.com/makinge lectricity/resourceplan/pdoc295631.pdf ; Public Service Company of Oklahoma IRP, October 2012, available at http://occeweb.com/pu/PSO%202012%20IRP.pdf

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### Utility-scale capacity expansion and dispatch planning models tend to have relatively high spatial detail with limited geographic scope, generally encompassing a utility service territory or a sub-regional scale. These models generally have better temporal resolution than the national-scale capacity expansion and dispatch planning models, with each model year typically dispatched based on an annual hourly load duration curve. 4 

### Utility-scale capacity expansion and dispatch planning models typically represen t individual EGUs, where each EGU has specific operational characteristics.

Due to the additional spatial and temporal re solution of these models as compared to the national-scale models, the number of technology options for capacity expansion is generally
limited to reduce the runtime of the model. This can be done through an outside-the-model screening analysis to pre-select the resources most likely to be economic in a planner’s area of interest, or by running the model iteratively to eliminate rarely chosen technology alternatives.

3. Electricity System Dispatch Simulation Models
Dispatch simulation models are regularly used by utilities, grid operators, and independent power producers (IPP) for short-term planning, ratemaking, dispatch decisions, and market intelligence. Dispatch si mulation models are typically driven by near-term economics, system restrictions and market constraints, incl uding a typically more detailed representation of an EGU’s operational constraints ( e.g. , ramp rates, heat input curves, and unit downtime for maintenance). These models typically do not add or retire generating capacity on an economic basis, although EGU additions and retirements may be exogenously input to these models. As a result, projections from these models tend to be considered more robust in the shorter term. 5 

### Grid operators, including utilities, and independent sy stem operators (ISO) use dispatch simulation models in near real-time to match demand with electric generation from available generating units and dispatch EGUs on a least-cost basi s. EGU owners and operators run dispatch

4 Load duration curves typically represent electricity load during a typical week for each month. 5 Some planners use dispatch simulation models in conjun ction with national or utility-scale capacity expansion and dispatch planning models, where the capacity expansion and dispatch planning model indicates the disposition of new and existing generating resources, and the dispatch simula tion model is used to simulate operation of individual EGUs. In this case, these models can be used in the same time horizon as a capacity expansion and dispatch planning model ( i.e ., decades).I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### simulation models to assist in fuel procurement, forecast revenues and costs, and calculate the avoided generation supply costs related to procurement of end-use energy efficiency and renewable energy resources. 6 

### Other utilities use dispatch simulation models to forecast retail rates for ratemaking proceedings and other planning purposes.

Electricity system dispatch simulation mode ls (also called production cost models) utilize security constrained economic dispatch (SCED) algorithms to determine which EGUs operate on an hourly (or shorter) basis to meet electricity demand. 7 

### These models typically have a very broad spatial scope, generally covering multiple Regional Transmission Organization (RTO) regions, and often modeling entire interconnects (i.e. Western, Eastern, and ERCOT). While individual EGUs are modeled in detail, including fuel and variable costs and operational constraints, transmission is simplified to char acterize thermal constraints between zones, which typically represent control areas or balancing au thorities. Zones contain both load (electricity demand) and EGUs; EGU dispatch and electricity demand are balanced to maintain transmission system reliability while providing least-cost service on a variable cost basis. Some versions of these models operate at a “nodal” level, wher e transmission constraints between individual
EGUs and load are modeled as well. 8 

### Dispatch simulation m odels typically operate chronologically, modeling either all 8760 hours of the year, or typical weeks of the year. These models contain substantially more detail about individual EGUs than regional or national capacity expansion and dispatch planning models , including EGU ramp rates, minimum outages, maintenance schedules, emission rates, fuel use constraints, and heat rate curves depicting expected efficiency changes at various levels of output.

6 For example, see Hornby, R., P. Chernick, D. White, et al., 2013. Avoided Energy Supply Costs in New England: 2013 Report. http://www.rieermc.ri.gov/documents/2013%20Evaluation%20Studies/AESC%20Report%20- %20With%20Appendices%20Attached.pdf 7 The Federal Energy Regulatory Commission (FERC) define s security constrained economic dispatch as “the level at which each available resource should be operated, given act ual load and grid conditions, such that reliability is maintained and overall production costs are minimized”. SCED optimizes dispatch based not only on the marginal costs of all available generating resources, but also constr aints on transmission availability and ancillary services. See FERC, “Security Constrained Economic Dispatch: Defi nition, Practices, Issues, and Recommendations” (2006), available at http://www.ferc.gov/industries/electric/indus-act/joint-boards/final-cong-rpt.pdf

. 8 “A “nodal” model represents the entire transmission network in a given area, without making the simplifying assumptions that load is served on a more aggregate “zona l” level.” A caveat is that while a nodal model has more “links” and places where supply must meet demand, it is still an approximation in terms of the electrical operation of the transmission network (the network is represented as a DC flow network, not an AC flow network). Deleted:

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### 4. Multi-Sector Models
Multi-sector energy models are typically used to examine the effect of energy and environmental policies that affect multiple eco nomic sectors, such as multi-sector emission trading systems. Multi-sector models are used to review trends in emissions, expected broadscale resource use, and energy sector impacts under changing regulatory and economic conditions, and often review chan ges over a period of decades.

Multi-sector models cover a broad range of energy sectors beyond the electricity sector, and can better reflect energy demand and technology choices by energy end-users. Such models typically have relatively limited spatial detail with broad scope, generally encompassing the entire country subdivided into from one to 30 regions. Such models tend to have much more limited temporal resolution and treatment of EGU dispatch. EGUs are typically aggregated to a few broad technology types. A ke y strength of multi-sector energy models is the ability to provide multi-sectoral feedback between energy resource use and price ( i.e. , tracking national fuel supplies and adjusting price to account for demand).

The range of national- and utility scale capaci ty expansion and dispatch planning models, and dispatch simulation models identified above all tend to focus on properly characterizing the electricity sector in order to answer secto r-specific questions. Multi-sector energy models attempt to include many other energy-using sectors of the economy in order to better capture interactions between these sectors. The more aggregate d representation of the electricity sector in multi-sector models may limit their use to providi ng input data for more specific analysis in an electricity sector model, and to better understand ing variations in electricity load that may result from changes outside the electricity sector.

B. Growth Tools for Projecting EGU Utilization and CO 2 

### Emissions
Organizations use growth tools for a variety of reasons
, including to estimate future emissions inventories for state and regional air quality modeling
, 9 

### and to estimate the impact of load-reduction measures such as end-use energy efficiency and distributed renewable energy on

9 See, for example, the ERTAC Load Growth Model, available at http://www.ertac.us/index_egu.html

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### individual EGU emissions, and county, state, 10 

### and regional emissions rates. 11 

### Because these algorithms are generally based on publicly available data 12 

### and do not rely on economic data or proprietary information regarding individual EGUs, they provide a low-cost, simple, and often transparent framework for estimating how EGUs wi ll respond to changing system conditions.

Non-modeling approaches, such as growth tools, approximate future emissions and generation from existing and new fossil fuel-f ired EGUs under differ ent assumed growth, retrofit, and load-reduction scenarios. These forecast tools do not simulate economic EGU dispatch, but could use demand growth rates and el ectricity production trends from other energy modeling forecasts as an input assumption. 13 

### The algorithms in these forecast tools assume that EGU dispatch behavior generally follows simple rules based on past operation. In the absence of significant shifts in fuel prices and electrici ty demand, EGUs may be expected to behave similarly in the future as they did in the past. Several common features of these forecast tools are that they (a) generally build on historical gene ration and emissions output from individual EGUs, (b) are insensitive to fuel and emission price forecasts, (c) do not solve for optimal economic EGU dispatch or EGU capacity expansion, and (d ) do not capture transmission constraints or limits. The algorithms in these forecast tools generally divide the contiguous US 14 

### into regional power markets, following ISO boundaries, eGRID boundaries, NERC regional boundaries, or similar designations. These algorithms generally seek to examine how operation and emissions from individual EGUs could be expected to cha nge with changes in environmental regulations or installed pollution control retrofits and additio nal or reduced hourly electricity demand. Some algorithms use the observed historical behavior of individual EGUs to approximate future behavior, while others add additional steps of differentiating EGUs into fuel groups and unit

10 See EPA’s AVERT (Avoided Emissions and Generation Tool), available at http://epa.gov/statelocalclimate/resources/avert/index.html

. 11 See Flexibility Weighted Ho urly Average Emissions Rate (FW-HAER) tool, available at http://nepis.epa.gov/Adobe/PDF/P1002UQO.pdf ; Time Matched Marginal (TMM) emissions tool, a proprietary algorithm used to estimate avoided emissions; D. Jacobson and C. High, “U.S. Policy Action Necessary to Ensure Accurate Assessment of the Air Emission Reduction Benefits of Increased Use of Energy Efficiency and Renewable Energy Technologies,” Journal of Energy & Environmental Law (2010)

. 12 Hourly emissions and generation data for all fossil fuel -fired EGUs greater than 25 MW are available from EPA’s Clean Air Markets Division (CAMD) through its Air Markets Program Data (AMPD). 13 For example, EIA’s AEO 2013 electricity load growth rates and EGU production trends are available at http://www.eia.gov/forecasts/aeo/assumptions/pdf/0554(2013).pdf. 14 Hawaii and Alaska do not report hourly generation and emission data from individual EGUs to EPA, and are therefore generally excluded from these forecast tools.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### types, with implicit differentiation of economic outcomes for these different groups. Some of these algorithms may contain subroutines to a dd new generating capacity automatically to meet load requirements.

III. Translating from a Rate-Based Emission P erformance Goal to a Mass-Based Emission
Performance Goal

As discussed in the preamble, in section VIII. C.2, the EPA is proposing that the projected
CO 2 

### emission performance by affected EGUs (taking into account the qualifying impacts of plan
measures that avoid CO 2 

### emissions from affected EGUs) must be equivalent to, or better than, the required CO 2 

### emission performance level in the stat e plan. This required level of emission performance in the state plan is the rate-based goal for the state in the emission guidelines, or a translated mass-based goal if the state chooses to use this approach. State plans that are projected to achieve an average CO 2 

### emission rate (CO 2 

### lb/MWh) or tonnage CO 2 

### emission outcome by all affected EGUs equal to, or lower than, the required level of CO 2 

### emission performance in the state plan would be considered to meet this pl an approvability criterion. States may demonstrate such emission performance by affected EGUs either by state or jointly on a multi-state basis.

This section of the TSD discusses the concept of a mass-based CO 2 

### emission performance goal, considerations for constructing projection scenarios for such a translation, methods for conducting such a translation, and key input assumptions for such a translation.

A. Concept

A mass-based CO 2 

### emission performance goal translates the application of a rate-based emission performance goal to an expected CO 2 

### emissions outcome in tons during a plan performance period. A mass-based CO 2 

### emission performance goal is calculated by projecting
the tons of CO 2 

### that would be emitted during a state plan performance period (e.g., 2020-2029,2030-2032) by affected EGUs in the state if they hypothetically were meeting the state ratebased CO 2 

### emission performance goal for affected EGUs established in the emission guidelines. The translation of a rate-based goal (expressed in lb CO 2 

### /MWh of useful energy output from affected EGUs) to tons (expressed as total tons of CO 2 

### emissions from affected EGUs over a specified time period) is based on a projection of affected EGU utilization and dispatch mix. Comment [A1]: Is it possible to provide an example or equation as to how this is done? Would be helpful in clarifying the approach.

EPA response: Translating a rate-based goal to a mass-based goal is based on an analytical process, as explained in this section, rather than a specific equation. We have, however, added a practical example later in this section in response to this comment.

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### Importantly, this projection is conducted assuming the absence of qualifying state programs and measures contained in a state plan, and applying th e rate-based goal in the emission guidelines as a proxy emission limit for affected EGUs. State pr ograms and measures in the state plan are not included in this projection, because the purpose of this analysis is to determine the tonnage CO 2 

### emissions that corresponds to the state-specific rate-based CO 2 

### emission performance goal for affected EGUs in the emission guidelines, without the eligible state programs and measures that are included in the state plan.

Translation of a rate goal to a mass goal seeks to answer the question, “What would happen to EGU CO 2 

### emissions if one applied the rate goals in the emissions guidelines instead of the measures in the state plan?” Because the emission guidelines do not specify the emissions reduction measures that a state must use in its plan, only the level of emission performance that must be achieved through a plan, there is no specified “policy” or set of emission reduction measures in the emission guidelines to apply when conducting this projection. However, a proxy policy can be applied to project the emission performance in tons that would be achieved if the state plan were to include suitable measures to achieve the required level of emission performance established through the state rate-based CO 2 

### emission performance goals in the emission guidelines. This proxy involves applying the rate-based emission goal for a state as a rate-based average CO 2 

### emission limit for affected EGUs in a state and then projecting the CO 2 

### emissions that would occur if such a limit were applied.

When demonstrating projected emission performance under a mass-based plan, a state would project the CO 2 

### emissions outcome that would be achieved under the suite of requirements, programs, and measures in its plan. The state plan requirements, programs, and measures substitute for EPA’s application of the best system, which is represented by the ratebased goal in the emission guidelines. If the CO 2 

### emissions outcome, in total tons of CO 2 

### emissions over each plan performance period, is equal to or less than what would be emitted by affected EGUs through the application of the rate-based goal in the emission guidelines ( i.e. , equal to or less than the translated mass-based goal), the plan would be deemed to achieve the required emission performance criterion.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### B. Projection Scenarios
As described above, the projection scenar io for translating from a rate-based CO 2 

### emission performance goal to a mass-based CO 2 

### emission performance goal does not include requirements, programs, and measures included in a state plan. Construction of this scenario must therefore carefully consider treatment of eligible “on-the-books” state requirements, programs and measures included in the state plan. 15



### Projection scenarios for translating from a rate-based CO 2 

### emission performance goal to a
mass-based CO 2 

### emission performance goal, and comparing projected emission performance under a state plan to this goal, include the following:

1. A Reference Case Scenario . This scenario projects the average CO 2 

### emission rate and
CO 2 

### emissions from affected EGUs in the ab sence of the EPA emission guidelines or any enforceable requirements, programs, and measures included in a state plan. This scenario does, however, include all current on-the-books state requirements, programs, and

measures that are not included as enforceable measures in a state plan. These measures are complementary to the state plan. Becau se these measures will influence EGU CO 2 

### emissions, they should, however, be included in the reference case projection scenario.
2. A Mass-Based CO 2 

### Emission Goal Policy Scenario . This projection scenario is used to translate a rate-based goal to a mass-based goal. The scenario applies a rate-based CO 2 

### emission limit to affected EGUs that is equi valent to the state-specific rate-based lb
CO 2 

### /MWh emission goal in the EPA emission guidelines. 16 

### The CO 2 

### emissions from affected EGUs projected during the specified plan performance period in this scenario represents the translated mass-based CO 2 

### emission performance goal for the state plan.

15 An “existing measure” refers to a state or utility re quirement, program, or measure that is currently “on the books.” For the purposes of this discussion, this may incl ude a legal requirement that includes current and future obligations or current programs and measur es that are in place and are anticipated to be continued or expanded in the future in accordance with established plans. Existing m easures may have past, current, and future impacts on EGU CO 2 emissions. 16 The proxy emission limit applied includes crediting for end- use energy efficiency, rene wable energy, and nuclear generation included in building blocks three and four, which were used by EPA when calculating the state-specific CO 2 emission performance goals for affected EGUs in the proposed emission guidelines. In essence, these measures can be used by affected EGUs as “compliance” flexibility mechanisms when “complying” with the proxy emission rate limit in this projection scenario. As a result, the proxy rate-based emission limit is able to capture all four building blocks included by EPA when calculating the rate-based CO 2 emission performance goals. Comment [A2]: Would this be an average emission rate based on total MWh (entire generation) or only fossil fleet generation? Would be helpful to clarify.

EPA response: As stated here, this is the average CO 2 emission rate and CO 2 mass emissions for affected EGUs. As used in the preamble and TSDs, “affected EGUs” refers to fossil fuel-fired EGUs subject to a state plan under CAA section 111(d).

Comment [A3]: This seems to imply that the state-specific rate would be multiplied by the state’s generation (including existing fossil fleet, 8% existing nuclear + under construction nuclear, existing renewables, and MWh energy savings) to reach a mass-based target above the reference scenario? Would be helpful to clarify the approach using an example/equation.

EPA response: As stated here, this projection scenario applies a proxy rate-based emission limit to affected EGUs in a state that equals the state-specific CO 2 goal for affected EGUs in that state. The scenario then projects the CO 2 mass emissions from those affected EGUs. The proxy emission rate limit that is applied includes the ability to credit for end-use energy efficiency, renewable energy, and nuclear generation as a compliance flexibility mechanism. In this way, the scenario includes end-use energy efficiency, renewable energy, and nuclear energy generation consistent with measures in the proposed BSER building blocks three and four.

We have added clarifying text to the footnote in

res p onse to this comment.
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### To construct this scenario, this emission limit is added to the underlying reference case
scenario described above.
3. A State Plan Policy Scenario . This projection scenario includes the enforceable requirements, programs, and measures included in the state plan, and is used to project
CO 2 

### emission performance by affected EGUs under the state plan. To construct this scenario, the enforceable requirements, programs, and measures included in the state plan are added to the underlying reference case scenario described above.

An applied example is provided below in Box 1.
Box 1. Example Mass-Based Goal Translation and Projection of Plan Performance

Example State Rate-Based CO 2 Emission Performance Goal Assumptions :

 State interim rate-based CO 2 emission performance goal for affected EGUs: 1,100 lb CO 2 /MWh

 State final rate-based CO 2 emission performance goal for affected EGUs: 1,000 lb CO 2 /MWh
Reference Case Scenario :

 Under this scenario, the projected average CO 2 emission rate for affected EGUs is 1,500 lb CO 2 /MWh during the 2020-2029 interim performance period and 1,500 lb CO 2 /MWh in 2030.

Mass-Based CO 2 Emission Goal Policy Scenario :

 A proxy emission rate limit is applied to affected EGUs (1,100 lb CO 2 /MWh on average during 2020-2029; 1,000 lb CO 2 /MWh in 2030 and subsequent years during the projection period).

 Under this scenario, the projected CO 2 mass emissions from affected EGUs during the 2020-2029 interim performance period are 100,000,000 tons of CO 2 (an average of 10,000,000 tons per year during this period) and 9,000,000 tons of CO 2 in 2030.

 The mass-based interim emission performance goal for affected EGUs is 100,000,000 tons of cumulative CO 2 emissions during the 2020-2029 interim plan performance period.

 The mass-based final emission performance goal for affected EGUs is 9,000,000 tons of CO 2 per year, in 2030 and subsequent years. During plan implementation, this final goal can be met on a three-year rolling average basis, beginning with the period 2030-2032, as discussed in the preamble at section VIII.B.2.c.
State Plan Policy Scenario:

 This scenario includes the suite of requirements, programs, and measures included in the state plan.

 Under this scenario, the projected CO 2 mass emissions from affected EGUs during the 2020-2029 interim plan performance period are 98,000,000 tons of CO 2 and 8,800,000 tons of CO 2 in 2030.

 Based on this analysis, the state plan is projected to achieve both the translated interim and final massbased CO 2 emission performance goals for affected EGUs.



### 1. Constructing the Reference Case
A key consideration for translating from a rate-based CO 2 

### emission performance goal to a
mass-based CO 2 

### emission performance goal is proper construction of a reference case scenario.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### This includes assumptions for key variables that may drive EGU CO 2 

### emission projections, 17



### such as:

 Electricity load growth projections (energy and peak demand)

 Fuel supply, delivery, and pricing assumptions

 Cost and performance of electric generating technologies

 EGU firm builds and retirements ( e.g., those scheduled with a regional transmission organization or independent system operator (RTO/ISO) ) 18



###  Transmission capability and ISO/RTO transmission expansion plans

 Applicable federal regulations (other than the EPA emission guidelines)

 Applicable state regulations and programs (other than those that are included in the state plan)

It may be necessary in many instances to include assumptions about other state programs implemented by neighboring states in the same region. This would be especially relevant for
states that are located within the same electri c power pool (or adjoining power pools) that are administered by a common RTO/ISO.

17 Process considerations related to constructing reference case scenarios are addressed in section VI of this TSD. 18 ISOs and RTOs are independent organizations that administer a regional electric power pool (EGU dispatch and electricity transmission systems), and often also administer related wholesale electricity markets for electric energy and capacity

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### 2. Treatment of Existing State Regulations and Programs in the Reference Case
A key aspect of the reference case is proper treatment of existing state regulations, programs, and measures. As discussed previously, existing state regulations, programs, and
measures that are not enforceable measures in a state plan are complementary to the state plan – as a result, they should be included in the reference case scenario rather than the state plan scenario. These state regulations, programs, an d measures should not, however, be ignored altogether, as they influence EGU CO 2 

### emissions. Instead, these stat e actions are occurring in the background – either when a proxy rate-based CO 2 

### emission limit is applied in the Mass-Based
CO 2 

### Emission Goal Policy Scenario ; or when the state plan requirements, programs, and measures are applied in the State Plan Policy Scenario . As a result, these state actions are properly addressed in the reference case scenario.

In effect, when evaluating whether a state plan will meet the mass-based CO 2 

### emission performance goal, the two policy scenarios described above, each of which involve adding a
different CO 2 

### emission reduction policy on top of the reference case scenario, are compared to
one another. If the State Plan Policy Scenario achieves projected tonnage CO 2 

### emissions equal to or lower than the projected CO 2 

### emissions in the Mass-Based CO 2 

### Emission Goal Policy
Scenario , then the state plan can be deemed to meet the translated mass-based CO 2 

### emission performance goal.

As discussed in the preamble, the EPA is proposing that a state may apply toward its required emission performance level the emission reductions that are achieved by existing state requirements, programs, and measures during a plan performance period, due to actions 19 

### taken after the date of the proposal of the emission guidelines. 20 , 21 

### In practice, this means that emission

19 An “action” as used here refers to an action taken pursuant to a state requirement, program, or measure. For example, the installation of an end-use energy efficiency measure, such as an energy-efficient refrigerator installed through a utility energy efficiency progr am to meet the utility’s obligations under a state energy efficiency resource standard (EERS), would constitute an “action” taken pursuant to an existing state requirement. 20 The preamble also takes comment on alternative dates for eligible actions, including: the start date of the plan period, the date of promulgation of emission guidelines, th e end date of the base period for the EPA’s BSER-based goals analysis (e.g., beginning of 2013 for blocks 1-3 and be ginning of 2017 for block 4, end-use energy efficiency), the end of 2005, or another date. 21 As discussed in the preamble, at section VIII.F.2.b, the EPA is also proposing that this proposed limitation would not apply to existing renewable energy requirements, pr ograms, and measures because existing renewable energy Comment [A4]: EPA: Edits in this section are conforming edits given changes made to the preamble at section VIII.F.2.b.

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### reductions that occur in 2020 and later due to actions taken pursuant to an existing state requirement, program, or measure could be applied toward meeting the required level of emission performance in a state plan if thes e actions occur after proposal of the emission guidelines (e.g., as of June 2014 and in subseq uent years). For example, emission reductions during the initial plan performance period that result from end-use energy efficiency technologies and measures installed beginning in June 2014 could be applied toward meeting the required level of emission performance during the plan performance period. These investments might be made to meet requirements under an existing end-use energy efficiency resource standard (EERS).

Under a rate-based plan, the approach described above would address the eligibility date for demand-side energy efficiency measures that, through MWh savings, avoid CO 2 

### emissions
from affected EGUs. Measures installed after th e eligibility date could generate MWh savings during the plan period, and related avoided CO 2 

### emissions, that could be applied toward meeting a required rate-based emission performance level. Under the proposed option, the eligibility date would be the date of proposal of the emission guidelines. 22



### Under a mass-based plan, the approach described above would be applied when establishing a reference case scenario projection that is used to translate a rate-based goal to a mass-based goal. For example, the assumed amount of energy savings from demand-side energy efficiency measures installed subsequent to the eligibility da te that are used to meet an existing

generation prior to the date of proposal of the em ission guidelines was factored into the state-specific CO 2 goals as part of BSER building block three. 22 Although such a limitation is not propo sed for RE measures, we also describe here how such a limitation could be applied to RE measures under such an approach. For example, under this approach in the context of a rate-based plan , new renewable energy generating capacity installed in Ju ne 2014 or later to meet an existing, on-the-books RPS would be a qualifying measure in a state plan. Howeve r, only MWh generation beginning in 2020 and related avoided CO 2 emissions could be applied toward meeti ng a required emission rate performance level in a state plan

. Similarly, under this approach in th e context of a mass-based plan, the re ference case might include the required MWh of renewable energy generation neces sary to meet a state RPS as of the date of proposal of the emission guidelines (e.g., as of June 2014). Renewable energy gene ration that is used to meet a state RPS, but that is incremental to the amount of generation used to meet the existing RPS obligation included in the reference case as of June 2014, could be used toward demonstration of CO 2 emission performance under a state plan. This renewable energy generation would be incremental to the renewable energy generation already assumed in the reference case scenario. Deleted: or renewable energy

Deleted: or renewable portfolio standard (RPS)

Deleted: qualifying renewable energy and
Deleted: MWh generation or

Deleted: MWh generation or

Moved [1]: For example, under this approach, new renewable energy generating capacity installedin June 2014 or later to meet an existing, on-thebooks RPS would be a qualifying measure in a state plan. However, only MWh generation beginning in 2020 and related avoided CO 2 emissions could be applied toward meeting a required emission rate performance level.
Deleted: qualifying renewable energy and

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### EERS would not be included in the electricity load forecast used in the reference case scenario. Energy efficiency measures installed prior to the eligibility date to meet an existing EERS would be factored into the electricity load forecast used in the reference case scenario. This treatment would represent in the reference case past actions taken under existing state programs and measures that are not eligible for inclusion in a state plan.

IV. Projecting CO 2 

### Emission Performance under a State Plan – Overview
As discussed in the preamble, in section V III.D.4, one of the required components of a state plan is a projection that a plan will achieve the required level of CO 2 

### emission performance by affected EGUs that is specified in the plan . (This identified level of performance must be consistent with either the state-specific rate-based CO 2 

### emission performance goals for affected EGUs identified in the emission guidelines, or an equivalent translated mass-based CO 2 

### emission performance goal.)

This emission projection is based on a scenar io that includes the suite of requirements, programs, and measures in the state plan – the State Plan Policy Scenario described above. Depending on the plan approach, construction of th is state plan scenario may be straightforward. For example, if the state plan consists solely of an emission limit, the state plan scenario would apply this emission limit to the underlying reference case scenario. Other types of state plan approaches are more involved, in particular wh en the use of end-use energy efficiency and renewable energy regulations, programs, or measures are included in a state plan. This could include a state plan that applies a rate-based CO 2 

### emission limit that provides credit for end-use energy efficiency and renewable energy measures that avoided CO 2 

### emissions, or the inclusion of such measures through a portfolio approach. These types of plans will require input assumptions for the amount of end-use energy efficiency and renewable energy resource (in MWh over the plan period) that will be reali zed through implementati on of the plan. Utilitydriven portfolio approaches may also include a di verse set of actions taken directly at affected EGUs that will need to be properly represented in the state plan scenario.

Considerations for developing estimates of energy savings and energy generation that will be achieved through end-use energy efficiency and renewable energy regulations, programs, and measures included in a state plan are discussed below in section VI. Deleted: after a respective eligibility date

Deleted: This could be achieved by not including an EERS or RPS requirement in a reference case projection, beginning at a specified date. The reference case would, however, include the level of such requirements up to the date at which such measures would become eligible for inclusion in a state plan.
Deleted: ¶ For example, the reference case might include the required MWh of renewable energy generation necessary to meet a state RPS as of the date of proposal of the emission guidelines (e.g., as of June 2014). Renewable energy generation that is used to meet a state RPS, but that is incremental to the amount of generation used to meet the existing RPS obligation included in the reference case as of June 2014, could be used toward demonstration of CO 2 emission performance under a state plan. This renewable energy generation would be incremental to the renewable energy generation already assumed in the reference case scenario.¶I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### V. Applied Considerations for Different Types of State Plans 23



### There are a number of considerations for properly representing different state plan approaches in CO 2 

### emission projection scenarios. This includes both accurate representation of the attributes of state regulations, programs, and m easures in the scenario, as well as the methods and data sources used to derive certain input assumptions that are used in CO 2 

### emission projections. This includes:

 Estimating the future effects of end-use energy efficiency and renewable energy requirements, programs, and measures

 Properly characterizing flexibilities included in emission limits, such as emission budget trading programs

 Properly addressing characteristics of multi-state regulations and programs

A. End-Use Energy Efficiency and Renewable Energy
Evaluating the impact of a state end-use energy efficiency requirement or program included in a state plan, as part of a projection of CO 2 

### emissions from affected EGUs under a state plan
, involves projections of the impact of the requirement or program on energy and capacity savings, and the impact of this reducti on in electricity load and peak demand on EGU dispatch and CO 2 

### emissions from affected EGUs. 24 

### This involves projections of the level of current and future energy and capacity savings achieved through program investment or activities in each year, the distribution of those savings on a daily and seasonal basis (e.g., the load shape of the energy and capacity savings), a nd the effective useful life of those energy and capacity savings (e.g., the life of installed m easures representing the persistence of energy savings). Such projections may also need to address net program energy savings after accounting for potential “free-ridership,” which involves energy savings that were likely to have occurred in the absence of program incentives, and “spillover,” which involves broader market

23 Different potential state plan approaches are described in detail in the accompanying State Plan Considerations TSD. 24 The evaluation discussed in this section is rele vant for state plans that implement a rate-based CO 2 emission limit applicable to affected EGUs that provi des for adjustment or crediting of the CO 2 emission rate of an affected EGU based on the effects of end-use energy efficiency and renewabl e energy. It is also relevant for state plans that take either a rate-based or mass-based po rtfolio approach. Descriptions of these plan approaches are provided in the accompanying State Plan Considerations TSD.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### transformation impacts that result from the program. These energy efficiency program projections would then be used to adjust elect ricity load forecasts, as necessary, for modeling runs using an electricity sector dispatch and capacity expansion planning model. This modeling would evaluate the impact of the energy and capacity savings on the dispatch of EGUs, construction and retirement of EGUs, and related CO 2 

### emissions from affected EGUs.

Similar considerations apply for projecting the impact of renewable energy requirements and programs included in a state plan on CO 2 

### emissions from affected EGUs. The renewable energy generation and generating capacity in a state or region that results from renewable energy requirements, programs, and measures in a st ate plan will affect EGU dispatch and CO 2 

### emissions from affected EGUs. This section disc usses these considerations in more depth, including approaches and data sources for estimating the impact of end-use energy efficiency and renewable energy requirements and programs as part of state plan projections of CO 2 

### emission performance by affected EGUs.

1. Potential Approaches for Estimating the Future Effects of State Energy Efficiency Requirements, Programs, and Measures

There are two basic approaches for developing a ten-year or longer forecast of end-use energy efficiency resources that will result from state energy efficiency requirements and programs: a bottom-up or a top-down approach. Th ese forecasts would contain data that could be used to develop inputs to EGU CO 2 

### emission projections in a state plan, using modeling or an EGU growth tool, both of which are summarized above.

A bottom-up approach is based on annual evaluated and reported data from state and utility energy efficien cy programs, and program-level util ity compliance reports under state energy efficiency requirements, such as an end- use energy efficiency resource standard (EERS). One example of a bottom-up approach is the state- by-state end-use energy efficiency projection developed by ISO New England for use in its system planning process. 25 

### In simple terms, ISO

25 Each year, ISO New England produces a Regional System Plan (RSP) that provides a comprehensive assessment of the New England bulk power system that is used as input data for evaluating the future reliability of the grid. One component of the annual RSP is a future estimate of peak loads and annual energy use that is modified (reduced) byI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### New England develops production cost curves for en ergy efficiency measures based on historical performance of energy efficiency as documented in evaluation, measurement, and verification (EM&V) studies. ISO New England then applies those production cost curves (with adjustments for inflation and other factors) to future state or utili ty energy efficiency program budgets for each of the six New England states over a ten-year horizon. The ISO New England energy efficiency forecast includes both reductions in annual energy use (MWh) and peak demand (MW). ISO New England has produced an energy ef ficiency forecast for the last three Regional System Plans (2011, 2012, and 2013), and the near-term estimates in these forecasts have been validated by the actual quantity of end-use energy efficiency that has qualified for the annual capacity auctions conducted by ISO New England as part of its forward capacity market. Other approaches to projecting energy efficiency impacts, such as those used by New York ISO (NYISO), PJM Interconnection, and the Ca lifornia Public Utilities Commission (CPUC), estimate the effects of energy efficiency requirements and programs over a shorter time frame. In these cases, energy efficiency projections are ty pically consistent with the periods for which energy efficiency programs or program budgets have been approved by state PUCs, or consistent with the period for which energy and demand savings are acquired in ISO and RTO forward capacity markets.

Top-down projection methods analyze aggreg ate energy use changes resulting from enduse energy efficiency requirements or programs, often for a geographic region, entire industry, or
economic sector. A top-down approach is determined on the basis of state energy efficiency policy requirements, and assumes that utilities an d other parties implement efficiency programs necessary to achieve required energy and demand savings. In this way, a top-down approach is typically based on an estimated annual percentage reduction in energy use that results from state energy efficiency requirements and programs. One example of a top-down approach is the EPA’s state-level projection of the impacts of “on-the-books” 26 

### energy requirements and programs.

the energy efficiency forecast. Information about the ISO New England energy efficiency forecasting method and assumptions is included in, ISO-New England (IS O-NE) Energy-Efficiency Forecast Working Group, Draft Final Energy-Efficiency Forecast 2018-2023 (March 2014), availa ble at: http://www.isone.com/committees/comm_wkgrps/othr/enrgy_effncy_frcst/ 26 As used here, “on the books” refers to state energy-efficiency requirement s and programs currently in place and specified in state legislation or administrative order. These requirements include energy efficiency resource standards (EERS) and dedicated sources of energy efficiency program funding.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### EPA’s approach uses these state requirements and program commitments as the basis for adjusting national electricity load forecasts for use in electricity system modeling. 27 

### In this case, EIA Annual Energy Outlook (AEO) projections of future electricity use (MWh) and peak loads (MW) are modified to account for the reduction in energy sales due to state and utility programs and associated energy savings requirements. 28 

### These energy savings requirements are examined on a state-by-state basis and adjusted, as necessa ry, to reflect known increases or decreases in energy efficiency program budgets and other factors likely to affect whether state energy efficiency requirements are achieved. In addition to EPA’s projections, a top-down approach is used to develop EE forecasts by LBNL 29 

### , NREL 30 

### , and some state energy offices and
commissions.

The LBNL and the EPA forecast models are useful for comparison with the bottom-up ISO/RTO approaches. Where discrepancies between the national top-down analyses of end-use energy efficiency savings and the more granular bottom-up energy efficiency forecasts conducted by ISOs and RTOs exist, review of key assumptions regarding state policies for the different approaches may be warranted. Ideally, using the two approaches as complementary analyses may provide for helpful comparison and reconciliation of energy savings estimates used in state plan projections of EGU CO 2 

### emission performance.

The electricity load forecasts developed by ISOs and RTOs are important because they are often the base case from which adjusted load forecasts that incorporate projected energy efficiency program savings are developed. Fo r reasons described above, ISOs and RTOs are beginning to include some adjustments to their base case load forecasts to account for energy efficiency program impacts. In most cases, thes e efforts are focused on including the future

27 While EPA’s approach utilizes AEO forecasts of electri city use and peak loads, other credible and long-term forecasts could be used in a similar manner. U.S. EPA, Background and Draft Methodology for Estimating Energy Impacts of EE/RE Policies (March 2014), available at: http://epa.gov/statelocalclimate/state/statepolicies.html

. 28 For example, annual incremental and cumulative ener gy savings requirements for utilities included in a state EERS. 29 Lawrence Berkeley National Laboratory (LBNL), The Future of Utility Custom er-Funded Energy Efficiency Programs in the United States: Projected Spending and Savings to 2015 (January 2013), available at:http://emp.lbl.gov/publications/future-utility-customer-funded-energy-efficiency-programs-united-states-projectedspend. 30 National Renewable Energy Laboratory, State Energy Efficiency Resource Standards: Policy Design, Status, and Impacts (May 2014), available at: http://www.nrel.gov/publications/. Deleted: 31

Deleted: [Forthcoming April 2014 – Citation TBD]
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### anticipated impacts of existing “on the books” energy efficiency requirements and programs and adjusting load forecasts accordingly. However, in so me cases there is also an effort to anticipate new incremental energy efficiency investments in th e future that are not tied to existing energy efficiency requirements and programs. 32 

### When conducting a projection of EGU CO 2 

### emission performance as part of a state plan that include s energy efficiency requirements and programs, it will be important to know how the base electricity load forecast for the state or region was developed, whether it al ready includes the effect of state and utility energy efficiency requirements and programs, and whether and how it should be adjusted to account for the future effects of existing on-the-books and incremental (i.e., new) energy efficiency requirements and programs that are included in the state plan.

1.1 Potential Uses of Energy Efficien cy Projections for State Plan Emission Projections

Whether developed through a bottom-up or top-down approach, projections of annual energy and peak load reductions that result from state energy efficiency requirements and programs included in a state plan are nece ssary inputs to projections of EGU CO 2 

### emission performance under the state plan. Energy and peak demand savings estimates included in energy efficiency projections are used as a decrement to fu ture electricity load forecasts that are used in conducting EGU CO 2 

### emission performance projections. The energy efficiency projection is used as an input, or modifier, to various models or other tools used to project the impact of energy efficiency resources on state or regional CO 2 

### emissions. For example
, capacity expansion and dispatch planning models are capable of incorporating energy efficiency program impact data, such as annual energy and peak load reductions, when projecting EGU dispatch and capacity additions, and the avoided CO 2 

### emissions that are projected to result from these requirements and programs.

1.2 Data Issues and Considerations for Using and Developing Energy Efficiency

32 In New England states that have policies to pursue “all cost-effective energy effici ency,” the ISO-NE energy efficiency forecast assumes that energy efficiency program investments will continue beyond the approved program funding period (typically documented three-year plans), either at a constant level or some discounted level based on assumptions about an increase in the cost of saved energy over time.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### Projections Depending on what data sources and approaches are used to project the future energy and demand savings from energy efficiency requirements and programs, there are certain strengths and limitations regarding the a pproach and methodology used. Generally, these strengths and limitations relate to data availability and en ergy efficiency forecast assumptions, such as:

 Energy efficiency requirements and programs included

 Jurisdictions covered

 Planning timeframe

 Embedded energy and demand savings from energy efficiency requirements and programs in base electricity load forecasts

 Cost of saved energy for different energy efficiency measures

 Energy efficiency measure life and measure energy performance decay

 Time of energy and demand savings for energy efficiency measures (availability of hourly data necessary to derive a load reduction profile for an energy efficiency measure)

Bottom-up versus top-down forecasting approaches have different strengths and limitations related to the data and assumptions described above. In the case of bottom-up approaches, state energy efficiency requirements and programs can be fully addressed in the analysis. In top-down approaches, such as EIA AEO analysis, greater focus is placed on federal policies (e.g., codes and standards) but less data is incorporated to reflect state energy efficiency requirements and programs. Bottom-up approaches typically include state-specific data that are rolled up to a regional level, while top-down national electricity load forecasts do not have a comparable level of granular state data detail. ISO New England provides energy and demand savings forecasts for state energy efficiency programs (average annual and peak demand coincident with the ISO defined peak load peri ods). The ISO NE energy efficiency forecast is informed by data collected at the energy ef ficiency measure, individual program, program portfolio, sector, and state levels.

An important consideration with both top-down and bottom-up energy efficiency forecasts is the extent to which energy efficiency program effects have become embedded intoI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### the long-range economic forecasts used as an input in developing electricity load forecasts. In
some cases the economic forecast includes the eff ect of historical energy efficiency policies, either implicitly or explicitly, while in othe r cases the economic forecast may also anticipate some limited quantity of futu re energy efficiency investment that is incremental to the anticipated effect of existing energy efficiency requirements and programs. An additional consideration is whether and how building energy codes and appliance standards (both current and future) are accounted for in the base electricity load forecast.

Another consideration, for all energy efficiency projections, is energy efficiency program spending. While “on the books” energy efficiency requirements and programs may include multi-year approved energy efficiency program budgets, actual program expenditures may differ. This has been the case in some of the New England states, for example, where ISO New England has made adjustments to “discount” the spending levels to reflect actual spending trends, and not used the state approved budgets identified th rough stakeholder discussions. Additionally, assumptions are made about how the overall cost of saved energy for a portfolio of energy efficiency programs will change ov er time. It is generally assume d in most energy efficiency projections that the cost of installing energy efficiency measures will become more expensive into the future as state programs move beyond “low-hanging fruit” and increasingly focus on achieving deeper and broader energy savings through whole-building, multi-fuel programs addressing new buildings and building retrofits). 33



### While many existing sources of energy efficiency projection data do not account for hourly savings, it is becoming increasingly possible for states to examine and incorporate
information about the time dimension of energy efficiency impacts. Smart meters combined with data-sharing and analysis technologies are making it easier for utilities and other energy efficiency program administrators to more accurately determine how the total energy savings achieved in a calendar year are spread out across the hours of that year. These data can be

33 Evidence to date is mixed as to a relationship of larg er scale energy efficiency programs and broader energy efficiency measure portfolios, and the asso ciated deeper levels of energy saving s, to increasing cost of saved energy. Economies of scale, and expertise gained by program ad ministrators from managing larger programs for multipleyears, can lead to cost reductions. However, at some point, as program administrators move away from initial lowcost strategies and end-use en ergy efficiency measures, it is assumed that the cost of saved energy will increase. Deleted: policies

Deleted:

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### applied to energy efficiency projections to provide a better estimate of the timing of energy and demand savings. Such time-diffe rentiated data is valuable for identifying the marginal EGU or cohort of marginal EGUs that are affected by energy efficiency requirements and programs, which can be used to provide more refined estimates of avoided CO 2 

### emissions due to changes in EGU dispatch and the addition of new generating capacity.

2. Potential Approaches for Estimating the Future Effects of State Renewable Energy Requirements, Programs, and Measures

This section describes data and analytic considerations for the representation of renewable energy requirements and programs included in state plans, when conducting projections of EGU CO 2 

### emission performance that will be achieved under a plan. A range of data and analytic considerations are examined that may be relevant when using different modeling approaches, including use of capacity expansion and dispatch planning models, and less sophisticated statistical or top-down projection approaches. Examples of specific considerations are described for three renewable energy policies that may be used as enforceable measures in a state plan— renewable portfolio standards (RPS), feed-in tariffs (FIT), and performance-based tax incentives.

2.1 Renewable Portfolio Standards
RPS requirements are typically set at the state level with an increasing percentage of total retail sales over a set schedule. The RPS requirement defines the eligible resource types (e.g., wind, solar, etc.) and in some cases, may specify resource-specific requirements, such as a percentage of the overall RPS target that is set-aside for a specific resource. It also defines the allowable geographic boundary for obtaining renewa ble energy or RECs. With this context, the following issues may be important to consider when projecting the impact of state RPS on EGU
CO 2 

### emissions.

2.1.1 RPS as an Input to Electricity Sector Modeling
Electricity sector modeling includes the use of dispatch simulation models and capacity expansion and dispatch planning models that simulate the operation of individual EGUs (or aggregations of EGUs) in the electric system over time based on a detailed characterization of Deleted: onI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### those EGUs, engineering and market operating constr aints, other market factors (e.g., fuel prices, transmission constraints), emission constraints, and the requirement to meet a certain level energy and peak demand. These models may be based on a small control area, but more likely are regional or national in scope. Some, such as capacity expansion and dispatch planning models, simulate EGU dispatch and also consider the impact of long-term generating capacity investment decisions when optimizing system operation and buildout over a long-term planning horizon. These are typically optimization framew orks that have as their objective meeting electricity demand subject to a broad range of operating, environmental and market constraints, including meeting RPS requirements.

When using these types of analytic tools to project EGU CO 2 

### emissions, a number of analytic and data considerations are relevant for analysis of RPS impacts on EGU CO 2 

### emissions. These analytic and data considerations are summarized below.

Translation of RPS Requirements to Re newable Energy Generation Requirements Most RPS are retail sales-based requirements, while most electricity sector analytic tools are generation-based models. When projecting CO 2 

### emission performance by affected EGUs using a generation-based analysis tool, it is necessary to translate the RPS sales-based requirement to a generation requirement using a transmission and distribution loss rate to “ gross up” the sales estimate. For example, if an RPS requires 100 MWh of sales be met with eligible renewable energy resources, then the required renewable energy generation necessary to meet the RPS is 100 MWh / (1 + T&D l oss rate). 34



### RPS-Eligible Resources vs. St ate Plan-Eligible Resources Some RPS rules define a broad range of eligible renewable energy generating resources. These could include renewable energy EGUs that emit CO 2 

### , and EGUs that were constructed and began operation recently or many years ago. Some of these specific EGUs may not be eligible for use in a plan, in particular units that began operation prior to eligibility dates for actions that may be included in a state plan (if such limitations were applied to renewable energy measures in

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### state plans)

. 35 

### Thus, the RPS requirement would need to be adjusted to reflect the use of only those resources eligible for use in state plans. This would be addressed through the treatment of existing RPS in the analysis base case, as described above in section III.B.2.

RPS Vintage Rules Some RPS requirements provide that only renewable energy EGUs that began operation after a certain date are eligible. To the extent these renewable energy EGUs are eligible under a state RPS but not under the state plan, the analys is should explicitly address these resources. This could be done either through an adjustment of the MWh needed to meet the RPS, to account for renewable energy resources that are not eligible for use in a state plan, or through the use of two modeled RPS requirements for each class of renewable energy resource, with the RPS that addresses resources not eligible in a state plan addressed in the modeling reference case.

In/Out-of-State Contribution Some RPS allow some of the requirement to be met by out-of-state resources. Some modeling frameworks may allow the user to exp licitly specify the source region of eligible renewables. From a modeling perspective, this means a state would allow a broader supply area and model a broader area generally. If the renewable energy resources have different characteristics across the relevant geographic area , then data is needed on the characteristics of these resources by region (e.g., resource availability, performance, and capital and production costs). EIA (for NEMS), EPA (for IPM), and NREL (ReEDS) provide information on the characteristics and performance of renewable energy resources by region. 36



### Characteristics of Renewable Resources

35 As discussed in the preamble, and explained in section III.B.2 of this TSD, EPA is proposing that emission reductions that occur in 2020 and later due to actions ta ken pursuant to an existing state requirement, program, or measure could be applied toward meeting the required level of emission performance in a state plan if these actions occur after proposal of the emission guidelines (e.g., as of June 2014 and in subsequent years). As discussed in the preamble, at section VIII.F.2.b, the EPA is also proposing that this proposed limitation would not apply to existing renewable energy requirements, programs and measures b ecause existing renewable energy generation prior to the date of proposal of the emission guidelines was factored into the state-specific CO 2 goals as part of BSER building block three. 36 EPA’s Integrated Planning Model generation profiles for wind and solar in the EPA IPM v.5.13 base case are available at http://www.epa.gov/powersectormodeling/BaseCasev513.html

. Comment [A5]: EPA: Edits in this section are conforming edits given changes made to the preamble at section VIII.F.2.b.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### In a dispatch modeling framework, better emission projections will result when the source of renewable energy is known and the energy profile is modeled. Renewable energy resources, such as wind or solar PV, may differ s ubstantially in generation profile, as the supply of electricity to the grid from the EGU is based on availability of the renewable energy resource. The time during which electricity generation is s upplied will influence the marginal fossil fuelfired EGU (or cohort of EGUs) that is displaced by renewable energy generation. Understanding the renewable energy resource base, including the energy profile of the relevant renewable energy resource types will improve the modeling of EGU dispatch and projections of avoided
CO 2 

### emissions that result from renewable energy generation. Data may include a detailed 8760

- hour energy output profile for renewable energy re sources, or at a minimum, a seasonal diurnal profile for such resources. If no state-specific data is available, generic output profiles for different renewable energy resources are available from NREL. 37



### Renewable Energy Resource Availability and Economics Emission projections will be enhanced by a representation of the new renewable energy EGUs that are likely to be brought online as a result of a state RPS, based on an analysis of available renewable energy resources and econo mics. This requires understanding the relative economics (e.g., capital costs, fixed operation and maintenance (FOM) costs, variable operation and maintenance (VO&M) costs, and fuel costs) and operating conditions for different types of renewable energy generators, as well as rene wable energy resource availability (e.g., MW capacity available at different wind classes, sola r insolation levels, and the characteristics of biomass). Having this information allows for be tter projections of the level and quality of renewable resources likely to be brought forward as the result of a state RPS. This will result in better emissions projections.

37 NREL’s datasets are intended for use by energy professionals, such as transmission planners, utility planners, project developers, and university rese archers who perform wind and solar inte gration studies and need to estimate power production from hypothetical wind a nd solar plants. The Eastern Wind Dataset ( http://www.nrel.gov/electricity/transmission/eastern_wind_methodology.html ) contains modeled wind farm data points for the eastern United States for 2004, 2005, and 2006. The Western Wind Dataset ( http://www.nrel.gov/electricity/transmission/western_wind_methodology.html ) includes information about the methodology used to develop the datase t, the accuracy of the data, site selection, and power output. The Solar Integration Datasets (http://www.nrel.gov/electricity/transmissi on/solar_integration_methodology.html ) are solar photovoltaic (PV) power plant five-minute and hourly day- ahead forecasts of generation output for approximately 6,000 simulated PV plants in the Un ited States for the year 2006. Deleted: isI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### NREL has a suite of tools that can be used to estimate the potential costs of renewable energy under various assumptions. 38 

### For example, the CREST model is a cost-of-energy analysis tool intended to assist policy makers evaluating the appropriate payment rate for a cost-based renewable energy incentive policy. The model aims to determine the cost-of-energy, or minimum revenue per unit of production, needed for a sample (modeled) renewable energy project to meet its investors' assumed minimum requ ired after-tax ra te of return. 39



### Retail Rate Impacts Many state RPSs have cost containment mechanisms or effective caps on the allowable impact on retail rates or on customer bills that can result from implementation of an RPS. If these caps are triggered, it will delay further incr eases in the RPS targets, depending on RPS implementation rules. This would lower estimates of renewable energy generation needed to satisfy the RPS requirements. Likewise, to limit rate impacts, many state RPS include an alternative compliance payment (ACP) provision, which requires obligated entities to pay a predetermined fee to the state for each MWh of RPS shortfall. Although these ACP payments may be directed to programs to promote the deployment of renewable energy tech nologies, these payments are not equivalent to renewable energy generation and should not be accounted as such.



### Market Impacts – Multiple State Players One important issue is to account for actions of others. Modeling results that consider the
RPS-related actions of other states could differ substantially from those that consider a state’s actions in isolation. This requires having at l east a regional, if not national, modeling framework.

38 NREL's Energy Analysis web site ( http://www.nrel.gov/analysis/models_tools.html ) has links to tools such as the Cost of Renewable Energy Spreadsheet Tool (CREST) and the System Advisor Model (SAM). CREST (https://financere.nrel.gov/finance/content/crest-cost-ener gy-models) makes performance predictions and cost of energy estimates for grid-connected power projects based on system design parameters that the user specifies. The SAM cash flow model (http://sam.nrel.gov/) helps assess so lar, wind, or geothermal projects, design cost-based incentives, and evaluate the impact of tax incentives or other support structures on renewable energy projects. 39 The CREST model is a product of a 2009-2010 partners hip between the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE) Solar Energy Technologies Program (SETP), and the National Association of Regulatory Utility Commissioners (NARUC ). The model was developed by Sustainable Energy Advantage (SEA) under the direction of NREL. The report, user manual, and CREST models are free and available for download at: https://financere.nrel.gov/finance/content/crest-cost-energy-models.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### A broader framework captures co mpetition for renewables (and incr eased prices, gr eater reliance on poorer resources), as well as market-wide im pacts on EGU dispatch and capacity expansion.

2.1.2 Data Needs for Estimating Generation Resulting from State RPS
Projections of renewable energy generation will require assembling the following data:

 Resource availability, resource performance, and resource costs will be necessary for the more sophisticated modeling approaches described above.

 Projections of retail sales, by year, adjusted to account for any exclusions from the RPS obligation (e.g. small utilities, cooperatives , municipalities, or perhaps certain large industrial loads). These covered sales must be calculated and projected using forecasts of
annual retail demand.

 RPS requirements by year, so the annual forecas t of covered retail sales can be multiplied by these percentages.

 The extent to which credit multipliers are used for compliance. Credit multipliers reduce the number of MWh needed for RPS compliance, and a downward adjustment should be made based on the percentage of comp liance achieved by credit multipliers.

 Representation of alternative compliance payment (ACP) provisions, if applicable, and other relevant compliance flexibility provisions provided through the RPS.

 Estimates of transmission and distribution (T &D) losses, so that retail sales can be “grossed up” as described above. T&D losses estimates are available at the national level and can also be obtained for various grid regions from the appropriate regional grid operator.

 If an electricity sector capacity expansio n and dispatch planning model is not used, estimates of the geographic origin, by state and grid-region, of generation used to satisfy the RPS will be necessary. If generation to satisfy the RPS is expected to come from out of state, the basis for these assumptions should be documented.

 CO 2 

### emission rate associated with renewable energy generation, by resource type (if applicable).

 Generation profile, by renewable energy resource type

2.2 Feed-in Tariff and Othe r Performance-Based Incentives Deleted: (FIT)I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### A feed-in-tariff (FIT) is a performance-based incentive (similar to production tax credits) that typically guarantees utility customers who own a eligible renewable electricity generation system (e.g., roof-top solar PV system) will be paid a specific amount by their utility for the electricity the system generates and provides to the grid over a fixed period of time. Such tariffs usually offer a fixed payment amount per kWh, but variations may require competitive bids. In some cases, FIT payments may be in addition to other incentives (such as a production tax credit). With a FIT, the amount of renewable energy that will be generated is not specified in the tariff schedule. A similar uncertainty about the amount of renewable energy generation that will occur exists for production-based tax credits. In the case of an RPS, the amount of renewable energy generation necessary to meet the RPS is known given the required RPS level and a utility sales projection. 40 

### In the case of FITs the response to the program may be more uncertain. The remainder of the discussion focuses on estimating these impacts.

The key information required to estimate the generation that will occur as a result of a
FIT include s :

 An estimate of the rene wable energy generation that will be provided by year for the FIT, along with estimates of payments to be made. These should capture the impacts of interactions with other policies, including RPS requirements, net metering, and federal investment and production tax credits. If generators receiving FIT payments are also eligible to satisfy an RPS, states should en sure their estimates of renewable electricity generation are not double-counted. For analysis using a detailed capacity expansion and dispatch planning model, market penetration of renewable energy generation to meet an RPS may be an output of the model. In this case, information is required on the capital costs, FOM costs, and VOM costs of the renewable energy generating technology. This is the same information required for modeling an RPS; however, the modeling or analysis mechanism may differ. For example, these costs may be reduced directly in a modeling

40 Most state RPS schedules are established as a percentage of utility sales in a given year, although some include specified MWh amounts or are based on MW of generating capacity.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### framework to reflect the FIT payment (e.g., reducing VOM to reflect the FIT in the years it is available).

 Information on the types of renewable energy resources, including their location, output levels, energy output profiles ( across all 8 , 760 hours of the year or seasonally), and operating life of the EGU (by technology, so that they can be included in an electric dispatch model or mapped to an appropriate load shape or marginal avoided emission rate if using simpler analytical methods.

 An estimate of whether the projected retail pr ice impacts of the FIT will lead to lowering the amount paid to eligible renewable energy generators, if a FIT includes caps on generation subject to the tariff based on rate impacts. If retail electricity rate impacts or budgetary impacts become unsustainable, the projected generation resulting from the FIT
will be overstated.

2.2.1 Data Needs for Estimating Genera tion Resulting from Feed-In Tariff and Performance-Based Tax Incentives

Projections of renewable gene ration that will occur as the result of FITs and other performance-based incentives will require asse mbling the following data about the specific incentive programs that will suppor t renewable energy generation:

 Caps on generating capacity, if any, by year, because such caps will limit the amount of renewable energy generation resulting from the tariff or tax incentive.

 Capacity amounts by renewable energy resour ce type that will be subject to a FIT or other performance-based incentives, and the capacity factors for these resource types, so that total generation in MWh can be calculated.

 Payment levels per kWh or MWh for each year of the FIT or other production-based
incentive.

 Budget amounts, if known, by year, which may be expended to support renewable generation. When divided by the incentive payment levels, on a per-kWh or per-MWh basis, these budget amounts will yield an estim ate of the total electric generation that will be supported by the FIT or other production-based incentive.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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###  State experience and trends with FITs a nd other production-based incentives. Lacking budget or capacity limits, prior experience in the state, or the experience of other states and utilities, normalized for state or util ity size, could be the basis for estimated renewable energy generation at a given incentive level.

 Because performance is metered at the busbar (i.e., the point of interconnection to the electricity transmission or dist ribution system), no adjustments would be needed for T&D
losses.

 Estimates of the geographic origin, by state, of generation that receives support from these programs. In most cases, eligible generation will be in-state, but if generation is expected to come from out of state, the basis for these assumptions should be
documented.

 CO 2 

### emission of renewable energy generation, by resource type (if applicable).

B. Emission Budget Trading Programs
Emission budget trading programs establish an emission limit for a group of emission sources and establish a budget of tradable emission allowances equal to the emission constraint for the group of sources. An emission allowance typically represents a limited authorization to emit one ton of a regulated pollutant. These programs also typically include a number ofadditional flexibility mechanisms beyond the ability to trade allowances. These include multiyear compliance periods, the ability to bank allowances issued in a previous compliance period for use in a subsequent compliance period, the use of out-of-sector project-based emission offsets, and cost-containment allowance reserves that make additional allowances available to the market if pre-established allowance price thresholds are achieved. 41 

### As a result, annual emissions from affected sources subject to an emission budget trading program often differ from the established annual emission budget for affected sources. In addition, these programs may be multi-sector in nature, regulating emissions fo r source categories in addition to EGUs. As a result, state plan emission projections will need to accurately account for and represent these compliance flexibilities, as well as the scope of affected sources if they are broader than EGUs

41 Depending on the program, these cost containment allowa nce reserves make additional allowances available from within the base emission budget (i.e., from “within the emission cap”), or add to the base emission budget (i.e., increase the emission cap). Comment [A6]: Here and throughout this TSD, has EPA considered using “system” instead of “program(s)”?

EPA response: “Program” has typically been used to refer to various emission budget trading programs, including RGGI, the Acid Rain Program, and the NO X Budget Trading Program.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### affected under CAA section 111(d). 42 

### In general, most electricity sector capacity expansion and dispatch planning models can be configured to evaluate these program flexibilities and project
CO 2 

### emissions from affected sources, considering these compliance flexibilities.

1. Addressing the Sectoral Scope of Emission Budget Trading Programs
Some existing state emission budget trad ing programs addressing GHG emissions regulate emission sources in addition to EGUs, such as industrial sources. 43 

### We refer to these here as multi-sector emission budget trading progr ams. All existing state emission budget trading programs addressing GHG emissions include out-of-sector project

- based emission offsets, which may be used to cover a portion of the compliance obligation of affected sources.

For multi-sector emissions budg et trading programs, state plan emission projections would need to evaluate projected CO 2 

### emissions across all source categories covered by the state or multi-state program. This would be necessary to project the CO 2 

### emissions performance of affected EGUs under the multi-sector emissions budget trading program.

For emissions budget trading programs that re gulate EGUs and include offsets, which we define here as emissions reductions from sources not regulated by the trading program, emissions reductions from offsets would not be counted when evaluating CO 2 

### emission performance of affected EGUs, because those reductions would not come from those affected EGUs. However, state plan emissions projections would need to ev aluate the use and impact of offsets, because the availability of offsets would affect the amount of CO 2 

### emissions from affected EGUs.

Addressing Multi-Sector Emission Trading A state or regional emissions budget trading program could potentially regulate sources from multiple emissions sectors beyond the electric generating sector that is the focus of the EPA emission guidelines. For example, the California GHG emissions budget trading program is a multi-sector emissions trading program that address emission sources outside the scope of the EPA emission guidelines for EGUs. If a multi- sector emissions budget trading program is

42 For example, the Regional Greenhouse Gas Initiative (RGGI), which is an emission budget trading program limited to EGUs, includes EGUs that are not subject to CAA section 111(d). 43 The California GHG emission trading program also includ es large industrial sources and as of 2015 will include distributors of transportation, natural gas, and other fuels. Deleted:

Comment [A7]: This language should match what is in the preamble (see interagency comments).

EPA response: We believe that this language is consistent with the revised language in the p reamble addressin g offsets. Comment [A8]: We believe that a proposal of this importance should be clearly stated in the Preamble and that the EPA should specifically request comments on alternatives, including allowing the use of state plan components incorporating out-of-sector offsets financed by affected EGUs to comply with CO2 emission performance goals established by this rule.

EPA response: We have not accepted this suggestion, as it is inconsistent with CAA section 111(d). As discussed throughout the preamble, EPA’s determination of BSER is based on measures that reduce CO 2 emissions from affected EGUs. Further, as stated at section VIII of the preamble, while we are proposing to provide states with broad flexibility in developing state plans, under CAA section 111(d), those plans must assure that the required level of emission performance for affected EGUs is achieved through emission reductions at those affected EGUs.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### included in a state plan, CO 2 

### emission projections provided as part of the state plan will need to evaluate projected CO 2 

### emissions across all covered emissions sectors under the program. This would be necessary to project the CO 2 

### emissions or weighted average CO 2 

### emission rate of
affected EGUs that will be achieved under th e multi-sector emissions budget trading program included in the state plan.

Evaluating the projected impact of a multi-sector emissions budget trading program on
the CO 2 

### emissions performance of affected EGUs introduces an additional level of analytical complexity to emissions projections. For example, additional modeling capabilities may be necessary to adequately evaluate CO 2 

### emissions performance across sectors in a multi-sector emissions budget trading program.

Adequately projecting the CO 2 

### emissions of affected EGUs subject to a multi-sector emissions budget trading program may require modeling using a multi-sector energy model. 44 

### The use of an electricity sector dispatch and cap acity expansion planning model, might also be required, as a complement to a multi-sector model. Some multi-sector models, include an electricity sector dispatch and capacity expans ion planning module. However, use of a standalone electricity sector model, might also be n ecessary as a supplement to a multi-sector energy model, in order to project CO 2 

### emissions or the weighted average CO 2 

### emission rate from
affected EGUs at a sufficient level of resoluti on for state plan emission projections. Under this approach, a multi-sector energy model might be used to project the level of CO 2 

### emissions abatement achieved across the multiple emission s ectors covered by the program. This multisector projection could be used to develop a CO 2 

### marginal abatement cost curve representing cost-effective, non-electricity sector emission re duction opportunities at increasing cost levels. The marginal abatement cost curve would then serve as an input assumption for the electricity sector capacity expansion and dispatch planning model, which would be used to project the CO 2 

### emission performance of affected EGUs (e.g., the CO 2 

### emissions or CO 2 

### emission rate of

44 For example, the Energy 2020 model was used by Cali fornia to evaluate the impacts of its multi-sector GHG emissions budget trading program. Other multi-sector models are available with similar capabilities, such as the National Energy Modeling System (NEMS) developed and implemented by the U.S. Energy Information Administration (EIA).I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### individual affected EGUs, or the total CO 2 

### emissions or weighted average CO 2 

### emission rate across multiple affected EGUs). 45



### Multi-sector emission budget trading programs also often address GHGs beyond CO 2 

### . If this is the case, emission projections in a state plan would need to account for emissions abatement opportunities for each of the GHGs regulated under the program, and project emissions reductions for each of the regulated GHGs. This would be necessary to project the
extent to which affected emission sources in di fferent industrial sectors reduce emissions of nonCO 2 

### GHGs, which could impact projected CO 2 

### emissions from affected EGUs.

Addressing Emission Offsets
Emission offsets in CO 2 

### or GHG emissions budget trading programs represent projectbased GHG emissions reductions outside the sector or sectors regulated by the program. 46 

### Emissions reductions achieved through eligible offset projects are awarded allowances or “credits” that may be used by an affected source to meet a portion of its allowance compliance obligation. For example, under the RGGI program “CO 2 

### offset allowances” awarded for GHG emissions reductions achieved through approved offset projects may be used by affected sources to meet up to 3.3 percent of their CO 2 

### allowance compliance obligation. 47



### .
The ability to use GHG emission offsets for compliance means that CO 2 

### emissions from EGUs regulated under the emissions budget trading program may exceed the base CO 2 

### emissions budget established for the program. Offset allowances or credits are awarded in addition to the existing CO 2 

### emissions budget, in exchange for CO 2 

### -equivalent emissions reductions achieved

45 This marginal abatement co st curve would be applied in a similar manne r as marginal abatem ent cost curves are applied for GHG emission offsets in modeling analyses of emission budget trading programs. Form a modeling perspective, emission reductions from other sectors could be used by affected EGUs to demonstrate compliance with the emission limit. When economic to do so, emission re ductions from affected EGUs would be foregone and replaced by emission reductions from emission sources in othe r sectors that are also subject to the multi-sector emission budget trading program. 46 “Offsets” as used in the context of CO 2 or GHG emissions budget trading programs are distinct from offsets in the NSR permitting context under the CAA, where in certain in stances emissions of a criteria pollutant from a proposed new facility must be offset with creditable emissions reduc tions at an existing facility, if the state or jurisdiction where the proposed facility would be located is in non-attainment status for the pollutant. 47 This percentage increases to five and ten percent of a CO 2 allowance compliance obligation at specified $7 and $10 price triggers, respectively. Comment [A9]: There are several places in the various files where offsets are discussed. However, EPA has directly addressed this issue in the TSD entitled, “Projecting Emission Performance TSD_04- 10- 14”. Therein EPA makes several statements that are not consistent with federal agency initiatives nor many state initiatives that do encourage offsets as a cost-effective means to achieve reductions in greenhouse gases. • Under this approach, state plans would ignore the CO2-equivalent emissions reductions projected to be achieved through offsets, when projecting the CO2 emissions performance that will be achieved by the affected EGU source category through implementation of the state plan. • Rather, when demonstrating emission performance by affected EGUs, the projected CO2 emissions or weighted average CO2 emission rate for affected EGUs under the state plan would not incorporate a credit for the CO2-equivalent emissions reductions represented by offset allowances or credits used by affected EGUs for compliance with the emission budget trading program.

EPA analysis of carbon cap

‐ and

‐ trade legislation along with a large literature document the cost savings afforded by including offsets in a national

‐ level program aimed at achieving significant reductions in GHG emissions. The memorandum from the President also makes it clear that EPA should to the greatest extent possible tailor the 111(d) regulation to reduce costs, allow market

‐ based instruments, employ regulatory flexibility, and be implemented in a manner that ensures continued provision of reliable and affordable electric power for consumers and businesses. Given the severability approach taken by EPA with respect ... [1]

Deleted: initially Comment [A10]: EPA: We have not accepted this change because it is incorrect. See next comment.

Deleted: This percentage increases to five and ten percent of a CO2 allowance compliance obligation at specified $7 and $10 price triggers, respectively Comment [A11]: Suggest adding this and a footnote that states: This percentage increases to five and ten percent of

a CO2 allowance compliance obligation at specified $7 and $10 price triggers, respectively.

EPA response: We have not accepted these changes, because they

are incorrect. The RGGI participating states removed these offset “triggers” as part of program ... [2]

Comment [A12]: Can EPA take comment on how to incorporate offsets when gross emissions may exceed the base cO2 emissions budget.

EPA response: The approach to offsets explained in this section of the TSD would not preclude offsets from being included in a state plan. However, credit or adjustment of affected EGU emission p erformance would not be p rovided for GHG ... [3]I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### outside the capped emissions sector. 48 

### Consequently, the use of offsets by affected sources to meet a portion of their compliance obligation under an emissions budget trading program could result in higher projected gross CO 2 

### emissions from affected EGUs in a state plan, because the use of offsets functionally expands the CO 2 

### emissions budget for affected EGUs. This allows
affected EGUs to emit more CO 2 

### while meeting their compliance obligation under the emissions budget trading program, in exchange for CO 2 

### -eq uivalent emissions reductions achieved outside of the affected source category. As a result, to properly project the CO 2 

### emissions from affected EGUs in a state plan that includes an emissions budget trading program that allows for the use of offsets, it is necessary for modeling to also project the extent to which offsets are used by affected EGUs for compliance. 49



### Under this approach, state plans could demonstrate how the CO 2 

### -equivalent emissions reductions projected to be achieved through offsets, when projecting the CO 2 

### emissions performance that will be achieved by the affected EGU source category meets the state goals

. Effectively, such a system, when demonstrating emission performance by affected EGUs, the projected CO 2 

### emissions or weighted average CO 2 

### emission rate for affected EGUs under the state plan
, would incorporate a credit for the CO 2 

### -equivalent emissions reductions represented by offset allowances or credits used by affected EGUs for compliance with the emission budget trading program. 50 

### In the preamble, the EPA seeks comment on 

### alternatives including allowing the use of state plan components incorporating offs ets financed by affected EGUs to comply with CO2 emission performance goals established by this rule.

2. Multi-State Emission Trading Programs
Emission budget trading programs may be multi-state in nature. For such programs,

48 A key criterion that must be met for the award of offset allowances or credits is a demonstration that the offset project is “additional” (i.e., that it would not have occurr ed absent the incentive provid ed through the award of the offset allowance or credit). 49 Existing capacity expansion and dispatch planning models can project the use of offsets for compliance based on specified offset marginal abatement supply curves, which represent the amount of offset credits/allowances assumed to be available from different categories of offset projects at different GHG emissions abatement costs. 50 In other words, the projected CO 2 emissions or weighted average CO 2 emission rate for affected EGUs would be based on the direct emissions from these EGUs alone, with no calculation of “net” EGU CO 2 emissions that factor in the CO 2 -eq uivalent emissions reductions represented by offset credits or allowances used by an EGU to meet a portion of its compliance obligation. Comment [A13]: EPA: We have not accepted this change – see next comment.

Deleted:

.

Deleted: would ignore
Deleted: through implementation of the
Deleted: plan

Deleted: This does not mean that an emission budget trading program included in a state plan could not include an offset component.
Deleted: Rather, Comment [A14]: Suggest deleting this, or making the suggested edits, and adding to the end of the paragraph: EPA requests comment and data to support this approach under a state implementation plan.

EPA response: We have not accepted these edits as they are inconsistent with the proposed treatment of offsets discussed in the preamble.

The approach to offsets explained in this section of the TSD would not preclude offsets from being included in a state plan. However, credit or adjustment of affected EGU emission performance would not be provided for GHGemission reductions achieved through out-ofsector offsets.

We have added text in the preamble (VIII.C.2) in response to interagency comments clarifying the treatment of offsets and how they could be included in state plans, as well explaining the p otential p olic y value of offsets.

Deleted: not Comment [A15]: Addition (5 25)

EPA response: We have not accepted this revision, as it is inconsistent with CAA section 111(d). As discussed throughout the preamble, EPA’s determination of BSER is based on measures that reduce CO 2 emissions from affected EGUs. Further, as stated at section VIII of the preamble, while we are proposing to provide states with broad flexibility in developing state plans, under CAA section 111(d), those plans must assure that the required level of emission performance for affected EGUs is achieved through emission reductions at those affected EGUs.
Deleted:

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### emissions reductions are achieved on a regional, rather than a state-by-state basis.

For example, in the multi-state Regional Greenhouse Gas Initiative (RGGI) emissions budget trading program, individual participating states have established CO 2 

### emissions budgets in state regulations. However, there is no requirement limiting total CO 2 

### emissions from affected
sources in an individual state. State regulations include reciproc ity provisions allowing emission
sources to use CO 2 

### allowances issued by another participating state for compliance with the state program. This provides for state-to-state CO 2 

### allowance flows (and the potential for differences in state-by-state CO 2 

### emissions relative to state em issions budgets) based on where emission

sources determine it is most economical to achieve CO 2 

### emissions reductions. However, in aggregate, the CO 2 

### emissions budgets in each of the participating state regulations establish a regional cap on CO 2 

### emissions from affected EGUs. As a result, while a multi-state emission budget trading program may be projected to result in CO 2 

### emissions from affected EGUs
consistent with a multi-state mass-based CO 2 

### emission performance goal, the CO 2 

### emissions outcomes may vary by state. This necessitates evaluating a multi-state emission budget trading program as a whole, because the individual regula tions of participating states function together as single integrated program.

To address these issues, states participati ng in a multi-state emission budget trading program would jointly demonstrate that the multi- state program is achieving the required level of
CO 2 

### emission performance on a multi-state basis, based on the CO 2 

### emission performance of all affected EGUs in the multi-state group implementing the program.

Some state emission budget trading prog rams also include international partner jurisdictions. 51 

### In such instances, the program could be treated in a similar fashion as a multistate program that involves only U.S. states. In this instance, emission projections evaluating an international program would include all jurisdictions participating in the program, but emission performance for state plans would be assessed based only on the CO 2 

### emission performance of affected EGUs in the subset of the program represented by U.S. states. Although the CO 2 

### emission performance of EGUs (or other emission sources) in a foreign country would not be

51 Currently, the EPA is only aware of one such instance, which is the linkage of the California GHG emission budget trading program with a similar program in Quebec. Deleted: the allowance market

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### addressed in the state plan, the entire international program would be evaluated as part of the emission projection included in the state plan. This would be necessary in order to project
international allowance flows and CO 2 

### emissions across all participating jurisdictions, as these cross-jurisdictional flows would impact projected CO 2 

### emissions from affected EGUs in U.S.

states. VI. Process Considerations
As discussed in the preamble, in section VIII.F.7, the credibility of state plans under section 111(d) will depend in large part on ensuring credible and consistent emission performance projections in state plans. Therefore, the use of appropriate methods, tools, and assumptions for such projections is critical. Fu rthermore, considerations for projecting emission performance under a state plan will differ depe nding on the type of plan. This includes differences in how inputs to projections are derived; how projections are conducted, including tools and methods; and how aspects of a plan are represented in these projections.

In the preamble, the EPA seeks comment on whether the EPA should develop guidance that describes acceptable projection approaches, tools, and methods for use in an approvable plan, as well as provide technical resources for conducting projections. This section of the TSD
elaborates on these considerations.

A. Provision of the EPA Guidance
One approach to address these considerations is for the EPA to provide guidance for
EGU CO 2 

### emission projections included in state plans. Such guidance could include default modeling assumptions, or data sources for key as sumptions. State modeling projections included in a state plan could include assumptions th at deviate from the EPA’s recommended default assumptions, but a state plan would justify th e reason for using alternative assumptions. The EPA technical guidance could specify recommended reference case assumptions for use with modeling or EGU utilization growth tools, for example:

 Electricity load growth projections (energy and peak demand)

 Fuel supply, delivery, and pricing assumptions

 Cost and performance of electric generating technologies Deleted: recommended

Comment [A16]: Suggest EPA consider developing guidance on best practices and other ways to encourage standardization.

EPA response: We acknowledge the comment and note that we are seeking comment on this in the preamble at section VIII.F.7.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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###  Cost and performance of pollution control equipment

 EGU firm builds and retirements (those scheduled with a regional transmission organization or independent system operator (RTO/ISO) 52



###  Transmission capability and ISO/RTO transmission expansion plans

 Applicable federal regulations (other than the EPA emission guidelines)

 Applicable state regulations and programs (oth er than the alternative standards that are included in the state plan)

It would be necessary in many instances to include assumptions about other state programs implemented by neighboring states in the same region. This would be especially
relevant for states that are located within the same electric power pool (or adjoining power pools) that are administered by a common RTO/ISO. To address this need, the EPA technical guidance could provide documentation of state programs and policies included in a reference case, as well as those that are eligible for inclusion in a state plan as alternative standards. The guidance could compile information about state programs and provide model input assumptions related to these programs (e.g., MWh of electric generation needed to meet a state renewable portfolio standard). 53 

### The EPA might also play a role in facilitating coordination among states as they develop their plans, to harmonize regional assumptions.

ISOs and RTOs, in discussions with the EPA have also offered to support states in evaluating the emission performance of state pl ans on a regional basis. The ISO/RTO Council, an organization of electric grid operators, ha s suggested that ISOs and RTOs could provide analytic support to help states develop and impl ement their plans. The ISOs and RTOs have the capability to model the system-wide effects of indi vidual state plans. Providing assistance in this way, they felt, would allow states with borders th at fall within an RTO or ISO footprint to assess

52 ISOs and RTOs are independent organizations that administer a regional electric power pool (EGU dispatch and electricity transmission systems), and often also administer related wholesale electricity markets for electric energy and capacity. 53 EPA’s manual, Roadmap for Incorporating Energy Efficiency/Ren ewable Energy Policies and Programs into State Implementation Plans/Tribal Implementation Plans (July 2012), could potentiall y support and be expanded upon to develop this component of EPA technical modelin g guidance. In particular, see Appendix I: EPA’s Draft Methodology for Estimating Energy Impacts of EE/RE Policies. The draft manual is available at http://www.epa.gov/airquality/eere.html . State environmental regulations addressing EGUs are itemized in the modeling documentation for the EPA IPM Base Case v.5.13.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW
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### the system-wide impacts of potent ial state plan approaches. In a ddition, as the state implements its plan, ISO/RTO analytic support would allow the state to monitor the effects of its plan on the regional electricity system. ISO/RTO analytic capability could help states assure that their plans are consistent with region-wide system reliabilit y. The ISO/RTO Council suggested that the EPA ask states to consult with the applicable IS O/RTO in developing their state plans.

B. Party that Translates the Rate-Based Goal to a Mass-Based Goal
In the preamble, in section VIII.F.7, The EPA seeks comment on whether it should develop guidance that describes acceptable projection approaches, tools, and methods for use in an approvable plan, as well as provide technical resources for conducting projections.

One consideration for state plans that use a mass-based CO 2 

### emission performance goal is the party that conducts the translation of the rate-based CO 2 

### emission performance goal in the emission guidelines to a mass-based goal—either the EPA or the state. In the preamble, in section VIII.D.3, t he EPA seeks comment on whether to assist states that seek to translate the rate-based goal into a mass-based goal.

One approach is for the EPA to provide a pr esumptive translation of the state-specific
rate-based CO 2 

### emission performance goal to an equivalent mass-based goal for all states, for those states that request it, and/or for multi- state regions. This could include default modeling assumptions and results of modeling runs for a Reference Case Scenario and an EPA MassBased CO 2 

### Emission Goal Policy Scenario , as described above in section III.B. A state could utilize the presumptive mass-based CO 2 

### emission performance goal for the state or multi-state region identified through these EPA modeling runs. If a state proposed modifications to EPA default modeling assumptions, it would need to ju stify these modifications as part of the CO2 emission projection included in its state plan, and present an emission projection that supports a proposed modified mass-based CO 2 

### emission performance goal.

Another approach is for the EPA to provide guidance for states to use in translating a rate-based goal to a mass-based goal. This could include information about acceptable analytical methods and tools, as well as default input assu mptions for key parameters that will likely influence projections, such as electricity load forecasts and projected fossil fuel prices. Under Deleted: T

Comment [A17]: Suggest that EPA have more guidance/clarity on how compliance with state targets would be evaluated under a mass-based approach.

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### this approach, the EPA might also provide a coor dinating function in addressing the assumptions applied by multiple states within a grid re gion, acknowledging that assumptions about state programs across a broader grid region that are included in an analysis scenario will influence projections of CO 2 

### emissions by affected EGUs in any particular state.

Under this approach, states could deviate from these default methods and assumptions with justification. Following the guidance could provide a streamlined path for the EPA approval of emissions projections, but states would still ha ve flexibility to use other approaches, which the
EPA would review.Page 37: [1] Comment [A9] Author 

### There are several places in the various files where offsets are discussed. Howe ver, EPA has directly addressed this issue in the TSD entitled, “Projecting Emission Performance TSD_04-10- 14”. Therein EPA makes several statements that are not cons istent with federal agency initiatives nor many state initiatives that do encourage offsets as a cost-effective means to achieve reductions in greenhouse gases. • Under this approach, state plans would ignore the CO2-equivalent emissions reductions projected to be achieved through offsets, when projecting the CO2 emissions perform ance that will be achieve d by the affected EGU source category through implementation of the state plan. • Rather, when demonstrating emission performance by affected EGUs, the projected CO2 emissions or weighted average CO2 emission rate for affected EGUs under the state plan would no t incorporate a cr edit for the CO2- equivalent emissions reductions represented by offset allo wances or credits used by affected EGUs for compliance with the emission budget trading program.



## EPA analysis of carbon cap

‐ and

‐ trade legislation along with a large literature document the cost savings afforded by including offsets in a national

‐ level program aimed at achieving significant reductions in GHG emissions. The memorandum from the President also makes it clear that EPA should to the greatest extent possible tailor the 111(d) regulation to reduce costs, allow market

‐ based instruments, employ regulatory flexibility, and be implemented in a manner that ensures continued provision of reliable and affordable electric power for consumers and businesses. Given the severability approach taken by EPA with respect to the building blocks, USDA thinks that the inclusion of offsets is desirable, consistent with the memorandum, and should be included as an option for public comment. See edits.

EPA response: The approach to offsets explained in this section would not preclude offsets from being included in a state plan. However, credit or adjustment of affected EG U emission performance would not be provided for GHG emission reductions achieved through out-of-sector offsets.
We have added text in the preamble (VIII.C.2) clarifying th e treatment of offsets and how they could be included in state plans, as well explaini ng the potential policy value of offsets. Page 37: [2] Comment [A11] Author 

### Suggest adding this and a footnote that states: 

## This percentage increases to five and ten percent of a CO2 allowance compliance obligation at specified $7 and $10 price triggers, respectively.

EPA response: We have not accepted these changes, because they are incorrect. The RGGI participating states removed these offset “triggers” as part of program revisions made in 2013. See http://www.rggi.org/docs/Progra mReview/_FinalProgramReviewM aterials/Model_Rule_Summary.p df

.

Page 37: [3] Comment [A12] Author 

### Can EPA take comment on how to incorporate offsets wh en gross emissions may exceed the base cO2 emissions budget.

EPA response: The approach to offsets explained in this section of the TSD would not p reclude offsets from being included in a state plan. However, credit or adju stment of affected EGU emission p erformance would not be provided for GHG emission reductions achieved through out-of-sector offsets.
We have added text in the preamble (VIII.C.2) clarifying th e treatment of offsets and how they could be included in state plans, as well explaini ng the potential policy value of offsets.