From: Higgins, Cortney [mailto:Cortney_Higgins@omb.eop.gov] 

Sent: Monday, May 05, 2014 5:53 PM 

To: Wayland, Robertj 

Cc: Elman, Barry 

Subject: RE: Comments on TSDs for RIN 2060-AR33 

Hi Bob, 

Attached are comments on the remaining TSDs, except for the legal memo. Please let me know if you 

have any questions. 

Regards, 

Cortney 

<< State Plan Considerations TSD_04-10-14_InteragencyCommentsUnderEO12866.docx >> 

<< State Plan Considerations TSD-Appendix_04-03-14_InteragencyCommentsUnderEO12866.docx >> 

<< Projecting Emission Performance TSD_04-10-14_InteragencyCommentsUnderEO12866.docx >> 

<< Resource Adequacy and Reliability TSD_04-10-14_InteragencyCommentsunder EO12866.docx >> 
Technical Support Document (TSD) for 

Carbon Pollution Guidelines for Existing Power Plants: 

Emission Guidelines for Greenhouse Gas Emissions 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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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 CO2 Emission Rates based on the Effects of End-Use 

Energy Efficiency and Renewable Energy ..................................................................19 

B. Approaches for Adjusting EGU CO2 Emission Rates ............................................20 

C. Methods and Tools for Quantifying Avoided CO2 Emissions from End-Use Energy 

Efficiency and Renewable Energy .........................................................................23

V. Quantification, Monitoring, and Verification 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 Treatment of Interstate Emission Effects..83 

VIII. Appendix ...........................................................................................................................92 

 
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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 suit their circumstances and policy objectives. In 

developing its plan, a state will need to make a number of decisions that 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 developing 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 under different plan scenarios 

o Summary of potential enforceable mechanisms under different state plan 

scenarios 

 Incorporating energy efficiency and renewable energy (EE/RE) requirements and 

programs in state plans, including: 

o Options for adjusting EGU CO2 emission rates based on the effect of EE/RE 

requirements and programs 

o Methods for estimating avoided CO2 emissions that result from EE/RE 

requirements and programs 

 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.

Comment [A2]: The discussion of avoided CO2

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.
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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 existing state processes and infrastructure 

o Discussion of areas where supplemental information would be useful for 

estimating avoided CO2 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 supplemental information would be useful for 

estimating avoided CO2 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, assumes 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 portfolio approach. These two basic approaches 

provide four distinct state plan “pathways” under CAA section 111(d). These pathways include: 
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 Rate-based CO2 emission limits applied to affected EGUs; 

 Mass-based CO2 emission limits applied to affected EGUs; 

 A state-driven portfolio approach 

 A utility-driven portfolio approach 

Under this flexible approach, a state plan could include a combination of measures that reduce 

CO2 emissions at affected EGUs through the application of emission limits as well as measures 

that involve actions within the interconnected electricity system that reduce utilization at affected 

EGUs and thereby avoid EGU CO2 emissions. Examples of these latter measures include, among 

others, end-use energy efficiency resource standards and renewable energy portfolio standards, 

as well as certain components of utility integrated resource plans. A state could either rely solely 

on CO2 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 possible state plan approaches under each of these 

pathways, which are discussed in more detail below. 

This section elaborates the different plan approaches 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 plans that implement rate-based CO2 emission limits for affected 

EGUs that also provide for the adjustment of CO2 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 and renewable energy programs and measures. 

Considerations addressed in this section would apply to states implementing a rate-based 

emission limit approach that provides for adjustment of CO2 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 end-use energy efficiency and renewable energy 
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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 CO2 emission limits that apply directly to affected 

EGUs, and includes two pathways: 1.) rate-based CO2 emission limits applied to affected EGUs; 

and 2.) mass-based CO2 emission limits applied to affected EGUs. For both types of emission 

limits, end-use energy efficiency and renewable energy measures that avoid EGU CO2 emissions 

could be a major component of a state’s overall strategy for cost-effectively reducing EGU CO2

emissions. 

1. Rate-Based CO2 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?
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Rate-based emission limits would apply a lb CO2/MWh emission limit to affected EGUs. 

Depending on a state’s approach, compliance flexibility could be provided through different 

mechanisms, such as averaging among affected sources, or the use of tradable credits for avoided 

CO2 emissions resulting from end-use energy efficiency 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 CO2 emission rate when demonstrating compliance with a rate-based emission 

limit.1

 Rate-based emission limits could be implemented on a state-by-state basis, or through 

multi-state averaging or trading. Rate-based emission 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 level 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 incorporate end-use energy efficiency and renewable 

energy measures that avoid EGU CO2 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 limit, by adjusting the unit’s reported CO2 emission rate.3

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

CO2 emissions would be enforceable components of a state plan. These actions would need to be 

enforceable components of a state plan to provide assurance that a sufficient amount of 

adjustment credits will be available to facilitate EGU compliance with the emission rate limit, 

                                                            

1

 Section IV of this TSD discusses possible approaches for such adjustments. 2

 Under a tradable credit system, a state would issue adjustment credits based on avoided CO2 emissions achieved 

through end-use energy efficiency and renewable energy measures. EGUs could then apply these tradable 

adjustment credits when demonstrating compliance with a rate-based CO2 emission limit. These tradable credits 

might be issued to affected EGUs for free or through purchase. Alternatively, end-use energy efficiency and 

renewable energy actions undertaken by private parties (including EGU owners and operators) might be eligible for 

the issuance of adjustment credits. Under an administrative adjustment approach, a state program administrator 

might administratively adjust an affected EGU’s CO2 emission rate based on avoided CO2 emissions achieved 

through state end-use energy efficiency and renewable 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 metric. Affected EGUs would then begin with an adjusted 

CO2 emission rate when considering additional actions necessary for compliance with the rate-based CO2 emission 

limit. 

3

 Section IV of this TSD discusses possible approaches for such adjustments. 
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and that end-use energy efficiency and renewable energy measures that generate adjustment 

credits are properly quantified, monitored, and verified.4

2. Mass-Based CO2 Emission Limits Applied to Affected EGUs 

Mass-based emission limits would apply either an individual limit on CO2 tons emitted 

from an affected EGU or establish a finite CO2 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 energy efficiency measures that avoid EGU 

CO2 emissions could be a major component of a state’s overall strategy for cost-effectively 

reducing EGU CO2 emissions, but would be complementary to the enforceable state plan (i.e., 

not included as enforceable measures in a state plan). These actions could be used to help a state 

cost-effectively achieve the CO2 emissions limits, or to achieve other policy goals, but CO2

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 CO2 emissions. A 

portfolio approach could be state-driven or utility-driven, depending 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 quantification, 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?
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specified in the plan is not ensured through the application of direct emission limits that apply to 

affected EGUs. 

A portfolio approach would include both direct emission limits that apply to affected 

EGUs and other indirect measures that avoid EGU CO2 emissions. Under a portfolio approach, 

end-use energy efficiency and renewable energy measures that avoid EGU CO2 emissions would 

be enforceable components of a state plan. This would be necessary because the emission limit 

applied directly to affected EGUs would not assure full achievement of the required level of 

emission performance specified in the state plan.5

As discussed below, due to differences in state utility regulatory structure, a portfolio 

approach implemented in a restructured state with retail competition will likely look quite 

different from one implemented in a state with vertically 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 electricity 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 supply 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 typically 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 owns the distribution utility may also own generating assets 

which are operated on a competitive basis. In these instances, there typically are legal provisions in place that 

mandate the independent management and operation of generation and distribution assets. 
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portfolio approach, are much more common in states with regulated 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 through regulations that apply to electric distribution utilities, such 

as end-use energy efficiency resource standards and renewable portfolio standards. Many of 

these states have also established independent non-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 owners and operators of affected EGUs subject to 

direct emission limits, as well as electric distribution utilities, private or public third-party 

entities, and state agencies or authorities that 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-regulated electric utilities is more likely to adopt a 

utility-driven portfolio approach. In such states, private utilities own and operate electric 

generation, transmission, and distribution systems 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 operations, and allow utilities to recover approved 

investments and operating costs, along with a specified 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 supplement electric generation with purchases through wholesale 

electricity markets and may also sell surplus generation in these wholesale markets on a competitive basis. 
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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-regulated electric utility in the state, the state might 

apportion the state emission performance level 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 affected 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 CO2 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 CO2

emission performance by these affected EGUs. 

A similar approach could be taken by municipally 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 assess factors such as fuel diversity and environmental 

performance, among others, when identifying the 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 acquisition 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. These 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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often do not regulate these utilities. As a result, implementation of a portfolio approach by these 

entities would introduce practical enforceability considerations under a state plan. 

III. Enforceability Considerations under Different State Plan Scenarios 

As discussed in the preamble of the proposal, 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 affected 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 entity that is regulated by the state, such as an 

electric distribution utility, or a private or public 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, assigning responsibility to other parties regulated by 

the state, private or public third-party entities, 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 enforceability considerations under different types 

of state plans. These scenarios were developed to capture the range of entities that are currently 

implementing end-use energy efficiency and renewable energy deployment programs in states, or 

are subject to states requirements such as end-use energy efficiency resource standards (EERS) 
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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 elements 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 inclusion of enforceable obligations for stateregulated entities other than affected EGUs. An example 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 commission. 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 integrated, 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 integrated 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 operates 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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1. Electric Distribution Utility with Obligations 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 utility commission order. State EERS and RPS 

regulations provide legal instruments generally comparable in enforceability to regulatory 

emission limits applied to EGUs. These regulations typically specify compliance obligations, 

reporting, and enforcement. However, many state RPS regulations and some EERS regulations 

include alternative compliance payment (ACP) provisions that provide 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 CO2 emissions, and may also include compliance with EERS and RPS 

regulations. Broadly, IRPs may prescribe or authorize 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 CO2 emissions include somewhat similar provisions. For example, 

both the RGGI state CO2 emission budget trading programs and the California GHG emission budget trading 

program include cost containment provisions where more emission allowances are made available to affected 

sources at certain allowance price thresholds. In both these instances, such relevant characteristics of the state 

regulations would need to be taken into account when projecting the CO2 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 acquisition 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. These orders may or may not be fully consistent with 

provisions in an IRP. 
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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 commissions 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 utility commission, such as a municipal utility or a 

utility cooperative.14 It could also be a private non-profit entity 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 commissions 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 electricity 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 collected through state-regulated electricity rates. 

Alternatively, a municipal utility or utility cooperative might voluntarily submit to state authority 

as a condition of the state agreeing to let the entity implement a portfolio approach, in lieu of the 

application of certain direct CO2 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 operators of affected EGUs, these EGUs may be subject to state environmental and 

other regulations. In some cases these utility entities are also subject to state EERS and RPS regulations, as specified 

under state law. 

15 Examples include the Energy Trust of Oregon, the Delaware Sustainable Energy Utility, and Efficiency Vermont. 
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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 legal 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 deployment 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 independent 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 state law, if obligations are not met under a state 

plan.17

                                                            

16 A prominent example is the New York 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 approved 111(d) state plan would 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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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 VIII.F.1, multi-state approaches 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 EGUs subject to the multi-state plan achieve a 

weighted average CO2 emission rate that is consistent, in aggregate, with an aggregation of the 

state-specific rate-based CO2 emission performance goals established in the emission guidelines 

that apply to each of the participating states. If states were taking a mass-based approach, 

participating states would demonstrate that all affected EGUs subject to the multi-state plan emit 

a total tonnage of CO2 emissions consistent with a translated multi-state mass-based goal. This 

multi-state mass-based goal would be based on translation of an aggregation of the state-specific 

rate-based CO2 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 Initiative (RGGI) is an example of a multi-state approach 

to regulation of CO2 emissions. Through this initiative, nine states are currently implementing 

coordinated CO2 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 authority. These regulations recognize CO2 allowances 

issued by other participating states for use by affected EGUs when complying with each state’s 
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emission limitation, but contain all the necessary components to administer the program 

requirements on an individual state basis.18 As a result, while the initiative is implemented 

regionally, each CO2 emission budget trading program regulation is enforceable against affected 

EGUs at the state level and functions as a discrete program. 

As a result, a multi-state emission budget trading 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 introduce 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 part, on actions taken in other participating states. 

If a state (or states) failed to implement commitments 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 individual 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 CO2 allowances equal to reported CO2 emissions 

during a compliance period. While states have individual emission budgets, representing the total number of 

allowances issued for a given year that are available for allocation, there are no individual state emission limits. The 

CO2 emission constraint is regional, based on the sum of state CO2 emission budgets. 19 Enforceability would be contingent, in part, on states having comparable enforcement mechanisms. 
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IV. Incorporating End-Use Energy Efficiency and Renewable Energy Programs and 

 Measures under a Rate-Based Approach 

A. Concept of Adjusting EGU CO2 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 CO2 emissions from affected EGUs, such as quantified and 

verified end-use energy savings and renewable energy generation, could be used to adjust the 

CO2 emission rate of an affected EGU when demonstrating compliance with a rate-based CO2

emission limit. Alternatively, a state could use the effect of such measures as a basis for 

administratively adjusting the average CO2 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 CO2 emission limit 

through actions at the EGU,21 as well as through the use of credits22 for actions that occur 

elsewhere in the interconnected electricity system that avoid CO2 emissions from affected EGUs. 

If a state is implementing a portfolio approach, then the state could administratively adjust the 

average CO2 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 mechanics and implications of the different possible 

approaches for adjusting CO2 emission rates that are summarized in the preamble. Aspects of 

this discussion may apply to both retrospective demonstration of CO2 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 administrative adjustment applied by the state. 
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achieved by affected EGUs under an approved state plan and projections of CO2 emission 

performance by affected EGUs included in a submitted state plan. 

B. Approaches for Adjusting EGU CO2 Emission Rates 

As discussed in the preamble, credits or adjustment to an EGU CO2 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 CO2 emissions.23 If adjustment or credits represent 

avoided MWh, they would be added to the denominator of the lb CO2/MWh emission rate when 

determining an adjusted lb CO2/MWh emission rate. If adjustment or credits represent avoided 

CO2 emissions, they would be subtracted from the numerator when determining an adjusted lb 

CO2/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 CO2 Emission Rate based on Avoided MWh 

One approach is to adjust an EGU’s CO2 emission rate based on avoided MWh of 

generation from an EGU, or cohort of EGUs, resulting from RE and demand-side EE programs 

and measures.24 A MWh crediting or adjustment approach implicitly assumes that the avoided 

CO2 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 

CO2 emissions from that individual EGU or group of EGUs.25 In practice, the average or 

marginal CO2 emission rate in the power pool or identified region – representing the avoided 

CO2 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 CO2 emission performance goals for affected EGUs. As discussed 

in the preamble, states may have flexibility to use a different approach when demonstrating the effect of these 

measures in a rate-based state plan. 

25 As a result, the assumed avoided CO2 emissions from an individual MWh of energy savings or generation from 

renewable energy will differ based on the reported CO2 emission rate of the individual EGU to which the MWh is 

applied as an adjustment to its MWh output. 
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MWh of renewable energy generation – could differ significantly from the calculated avoided 

CO2 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 CO2/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 CO2 emission 

rate. The adjusted CO2 emission rate is 1,500,000 lb CO2 divided by 2,000 MWh, which equals a 

CO2 emission rate of 750 lb CO2/MWh. In this example, each MWh credit represents 750 lb of 

avoided CO2 emissions. 

Example 2: The same calculation applied to an affected EGU with a 2,000 lb CO2/MWh 

rate would yield a different result. In this instance the adjusted emission rate is 2,000,000 lb CO2

divided by 2,000 MWh, which equals a CO2 emission rate of 1,000 lb CO2/MWh. In this 

example, each MWh credit represents 1,000 lb of avoided CO2 emissions. 

2. Adjustment of CO2 Emission Rate based on Avoided CO2 Emissions 

An alternative approach is to provide an adjustment to the CO2 emission rate of an EGU, 

or cohort of EGUs, based on the estimated CO2 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 CO2 emissions may come from the electric power pool or other 

identified region as a whole, rather than an individual EGU. The avoided CO2 emissions are 

determined based on the MWh saved or generated, multiplied by a CO2 emission rate for the 

power pool or region. 

This CO2 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 rate 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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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 CO2/MWh, one MWh of 

energy savings or renewable energy generation would result in a credit or adjustment 

representing 1,500 lb of CO2 that could be subtracted from the numerator of an EGU’s CO2

emission rate. This approach assumes that affected EGUs jointly emit CO2 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 CO2 emissions from affected EGUs at this 

average compliance level.26

3. Other Considerations 

Some of the CO2 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 include) 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, affected EGUs under section 111(d) will comprise a 

slowly shrinking subset of the total fossil fuel-fired EGU fleet. These dynamics may need to be 

addressed in a state plan when crediting or adjusting CO2 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 distinctions 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 measures. In this instance an EGU that emitted above the 

compliance rate would need to average 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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C. Methods and Tools for Quantifying Avoided CO2 Emissions from End-Use Energy 

 Efficiency and Renewable Energy 

1. Introduction 

There are a number of approaches for quantifying the avoided CO2 emissions resulting 

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

measures27 in the electric sector. These approaches range from the application of basic avoided 

emission rates to using sophisticated electric sector models.28 Annual average avoided emission 

rates have often been used for rough approximations of CO2 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 CO2 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 CO2/MWh) is usually 

understood to mean the average of all generators’ emissions rates, weighted by annual 

generation. The rate (ravg) 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 models (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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ݎ௔௩௚ ൌ ∑௜ ݁௜

∑௜ ݃௜

Where: 

e = annual emissions (tCO2) 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, hydro, 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 non-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-emitting 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, nuclear, 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., “Cost 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 generating 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 and 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 stalled 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 economic dispatch of these resources at times when the 

renewable energy resource is available. In these instances, these 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 render the emissions rate too 

low, and thus the avoided emissions smaller than actually realized. 
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3. Marginal Emission Rate Approach 

A marginal emission rate represents the emission 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 

rates35 and transmission availability, it is not uncommon 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 already operating, but that is dispatched at a greater 

level of output to meet load. 

The marginal emission rate (rmarginal) 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: 

eref and eEERE = emissions (tCO2) from EGUs i in hour t in the reference case (ref) and the change 

case (EERE), respectively; and 

gref and gEERE = 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 athttp://www.epa.gov/statelocalclimate/documents/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, with some technologies, such as combustion turbines, able 

to more quickly increase output in response to increasing load. 
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The magnitude of the EE/RE program and the EE/RE load impact shape36 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 marginal emission rate is highly time sensitive, 

as are the impacts of EE/RE programs and measures. 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 timing 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 EPA’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 significant reductions in electricity use from the grid during peak 

demand hours, and little electricity use reduction during overnight “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 may significantly reduce baseload generation during overnight 

trough hours.
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4. Methods and Tools for Estimating Avoided CO2 Emission Rates and Avoided 

 CO2 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 SO2 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 CO2 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 behavior. 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 CO2

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/.
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AVERT may be used to derive marginal emission reductions from historical generation 

and emissions data, which can be used to derive a marginal avoided CO2 emission rate. 

However, AVERT does not quantify average emissions rates. AVERT approximates historical 

dispatch behavior using a statistical algorithm. It does not represent transmission constraints, or 

significant changes in grid structures or future economic conditions. To estimate a recent 

historical marginal CO2 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 CO2 emission rate is the incremental CO2 emissions added by 

AVERT, based on historical EGU dispatch patterns, 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 CO2 emissions from EE/RE requirements, programs, and 

measures can be achieved through retrospective modeling approaches. Models can be used to 

calculate avoided CO2 emissions by comparing actual realized EGU CO2 emissions to projected 

EGU CO2 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 determine 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 increment 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 dispatch 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 data, AVERT will capture the impact of historical fuel prices 

and other impacts on the variable cost of production, but cannot capture specific emission limits. 
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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 planning model to understand the change in build 

out of new generating capacity, as well as transmission 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 CO2 emissions reductions achieved by EE/RE measures through 

modeling of a near-term look-back period requires 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 consideration. 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, including actual historic fuel costs, emission 

allowance prices, and transmission constraints. While 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 additional incremental carbon emissions 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 meaningful, but aggregate emissions at a state or regional scale 

should be expected to be comparable. 
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Simulation dispatch models may be most relevant as part of ex-post plan reporting, for 

estimating the avoided CO2 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 CO2 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 system 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 planning models could be run for a longer-term 

historical period to better reflect what the electricity 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 how 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 performance 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 CO2 emissions as the result of EE/RE measures. 

 
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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 decisions to build new fossil generating capacity, retire 

existing aging generating capacity, and make different decisions about transmission expansion. 

These different decisions about what infrastructure 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 regions 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 help accurately assess avoided emissions due to 

changes at both the build and operational margins. 

 
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Quantifying In-State versus Out-of-State Emissions Reductions 

The electric system is not confined by state 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 the 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 CO2 emissions from implementation of EE/RE measures, avoiding 

double-counting of emission effects 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 Verification 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, monitoring, 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 generating capacity that implements EE/RE measures would cause 

emissions reductions in neighboring states, and none within its own borders. Similarly, a state with significant, 

predominantly baseload fossil generation may also cause little 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 generating 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 the 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?

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

savings.48 In the preamble, the EPA 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. This section further elaborates these considerations 

discussed in the preamble. 

The type of quantification, monitoring, and verification for RE and demand-side EE 

programs and measures will depend on the state plan approach. For states implementing a massbased portfolio approach, the effect of renewable energy and demand-side energy efficiency 

requirements, programs, and measures in helping to achieve the required level of CO2 emission 

performance under a state plan will be directly evident in reductions in the monitored CO2

emissions from affected EGUs.49 In effect, the overall impact of these measures could be tracked 

through CO2 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 quantification, monitoring, and reporting requirements related to RE 

and demand-side EE requirements, programs, and measures incorporated in a state plan. 

Utilities and states have conducted ongoing evaluation 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 

                                                            

48 In particular, this consideration applies to states implementing a rate-based emission limit approach that provides 

for adjustment of CO2 emission rates based on the effect of end-use energy efficiency and renewable energy, as well 

as states implementing utility- or state-driven portfolio approaches that incorporate end-use energy efficiency and 

renewable energy requirements and programs. 

49 There could be exceptions, for example where a state plan includes acknowledgement of avoided CO2 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. 
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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 these measures and 

programs, and the overall magnitude of program impacts. 

This section of the TSD discusses current state 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 harmonization 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 good practice guidance or requirements 

for quantification, monitoring, and verification of end-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 guidance, if the EPA were to take this approach. This 

discussion includes consideration of existing state and utility protocols, 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 quantification, monitoring, and verification of results is 

relatively straightforward. Such approaches might be subject to streamlined review of 

quantification, monitoring, and verification protocols included in an approvable plan, provided 

that such protocols are applied in accordance with industry best practices. For example, many 

utilities have implemented a similar core set of end-use energy efficiency and renewable energy 

measures and programs 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. Other types of measures and programs, such as 

those that seek to alter consumer and building occupant behavior may pose quantification and 

verification challenges. Still other types of measures, such as state energy-efficient 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 

development of appropriate quantification, monitoring, and verification protocols. 

 
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A. Quantification, Monitoring, and Verification 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 section discusses current state and utility EM&V 

practice for end-use energy efficiency programs and discusses considerations related to possible 

acceptable EM&V plan and protocol 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 verification (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 policies utilize EE savings values, as follows:52 

                                                            

50 In this section we use the term “end-use energy efficiency measure” or “energy efficiency 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, Schiller Consulting, Inc., available at http://www.seeaction.energy.gov. 
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 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 independent 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 analyses aimed at determining the value of energy 

efficiency programs to utility customers and identifying relative program costs and 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 energy 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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Figure 1. Energy Use Before, During, and After an Energy Efficiency Project is Installed53

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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The range of EM&V budgets varies significantly 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. 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 implementing 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-specific 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. 57 

                                                            

56 Wallace, P.; Forster, H.J. (2012). State of the Efficiency Program Industry Budgets, Expenditures, and Impacts 

2011. Consortium for Energy Efficiency. www.cee1.org/files/2011 CEE Annual Industry Report.pdf . 57 Examples of equipment types that are commonly evaluated 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 calculations, evaluators collect information about the actual 

installed measures -- such as hours of usage, wattage, and/or equipment capacity -- and combine this with 

predetermined assumptions in the algorithm. 

Comment [A7]: The opposite effect can also be

seen: additional programs mean more experience

with EM&V and hence reduced costs.
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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.58

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.59 A recent 

survey of TRMs found that deemed energy savings values for comparable energy efficiency 

measures vary across states and regions.60 The reasons for these variations include the use of 

different calculation methodologies, technical assumptions, 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 assumptions 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 existing 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 

particular situation, PUCs typically allow utilities and other program administrators to select 

                                                            

58 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. 

59 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 . 60 Ibid. 
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from a range of appropriate EM&V approaches that are consistent with standard practice in the 

energy efficiency industry. EM&V analyses and calculations are then carried out, in most cases 

by an independent, third-party evaluator, through 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 savings 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) 

EM&V Forum, which is active in New England, New York, and the Mid-Atlantic, and the 
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Pacific Northwest’s Regional Technical Forum (RTF). 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.61 

 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. International Performance Measurement and Verification Protocol (IPMVP)62

b. DOE Uniform Methods Project (UMP) Protocols63

c. Federal Energy Management Program (FEMP) M&V Guidelines64

d. American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 

Guideline 14, Measurement of Energy and Demand Savings65

e. California Evaluation Protocols66

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

Resources67

g. PJM Energy Efficiency Measurement and Verification Manual68

                                                            

61 For a list of EM&V resources, including more information about these regional EM&V collaboratives, see 

http://www1.eere.energy.gov/seeaction/evaluation.html. 62 Efficiency Valuation Organization (EVO), International Performance Measurement and Verification 

Protocol (2012), available at: http://www.evo-world.org/. 63 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. 64 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. 65 American Society of Heating, Refrigerating 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. 66 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/EvaluatorsProtocols_Final_AdoptedviaRuling_06-19-2006.pdf. 67 ISO-New England (ISO-NE), Measurement and Verification of Demand Reduction Value from Demand 

Resources (2013), available at http://www.iso-ne.com/rules_proceds/isone_mnls/MMVDR/index.html. 68 PJM, Manual 18B: Energy Efficiency Measurement & Verification (2010), available at 

http://www.pjm.com/~/media/documents/manuals/m18b.ashx. 
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h. State and Local Energy Efficiency Action Network, Energy Efficiency Program Impact 

Evaluation Guide69

 While many states are currently relying upon these protocols and guidelines, other states 

and regional organizations (e.g., ISOs and RTOs) specify 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 effort) and the resulting reliability, validity, and 

usefulness of the estimated energy savings results. The appropriate balance between EM&V 

costs and the rigor of EM&V – and the related certainty 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) responsible for operating regional electricity 

grids and overseeing wholesale electricity markets in certain regions of the country have 

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 

                                                            

69 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.

Comment [A8]: This approach is not separate

from or inconsistent with the listed guides. Please

clarify the language.
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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 described above typically requires additional 

sampling70 than is required by PUCs. One consideration is whether EM&V requirements in ISO 

capacity markets include components that would facilitate better estimation of avoided CO2

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 work together to establish consistent evaluation 

protocols through the creation of an “EM&V Forum,” which is convened by the Northeast 

Energy Efficiency Partnerships (NEEP) and supports common evaluation methods, reporting 

metrics, and cost sharing on research studies.71 The Forum also serves as a venue for information 

exchange to address common EM&V challenges encountered with FCM participation. 

                                                            

70 With additional sampling requirements, energy efficiency program evaluators are typically required to measure a 

larger percentage of the energy efficiency measures installed within the total population of all measures installed 

through an energy efficiency program. 71 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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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 may have substantial impacts in reducing 

energy use, many currently 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.72

4. Considerations for EM&V of End-Use Energy Efficiency Programs and Measures in 

 State Plans 

4.1 Accuracy of Energy Savings Estimates 

To document and verify that avoided CO2 emissions from energy efficiency programs 

and measures are real and persistent, impact evaluation 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 CO2 emissions resulting from energy 

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 

 

                                                            

72 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. 

Comment [A9]: 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.
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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, programs, and measures as an emission reduction 

approach in state plans requires consideration 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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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., behaviorbased programs and various market transformation programs73) for which rigorous EM&V 

methodologies or a track record of energy savings persistence do not yet exist. 

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 

                                                            

73 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, evaluation of 

these strategies is challenging due to the involvement of numerous market players and the multi-year timeframe for 

achieving energy savings.

Comment [A10]: 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.
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Table 4.1 provides an illustrative characterization 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 4.1. 

Table 2. Illustrative Characterization of EM&V Procedures and Protocols for 

 Common Energy Efficiency Programs and Polices74 

EM&V Procedures and 

Protocols Well Established 

EM&V Procedures and 

Protocols Moderately Well 

Established 

EM&V Procedures and 

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 

 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 mid-stream 

and upstream market 

transformation programs 

 Building commissioning 

and retro-commissioning 

 Industrial energy efficiency 

new construction or retrofits 

 Combined heat and power 

(CHP) installations/retrofits 

 General education 

programs for consumers, 

contractors, distributers, 

suppliers 

 Targeted training 

programs 

 Building labeling and 

disclosure programs 

 Point-of-sale product 

sales 

 Targeted consumer 

behavior programs 

Recognizing these variations in EM&V procedures and protocols, one option for EM&V 

requirements or guidance for state plans is to limit the eligible types of energy efficiency 

programs and measures that could be included in a state plan to a pre-defined list of well-

                                                            

74 This table is intended as a generalized description, based 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. 

Comment [A11]: 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?   
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understood program types for which evaluation is straightforward and energy savings results are 

subject to a relatively low level of uncertainty.75 An alternative approach is to allow a wide (or 

unlimited) set of energy efficiency program and measure types, 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. 

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 delivered to an end-user constitutes transmission 

and distribution (T&D) line losses.76 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 system in the United States. For every unit of energy use avoided at the 

end-use site, energy efficiency also avoids the losses that would otherwise occur as electricity is 

delivered to consumers through the T&D system.77 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 in state plans is 

whether to account for avoided T&D losses, and how to do so in a consistent manner across 

states. 

                                                            

75 This includes energy efficiency programs 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. 76 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 through, 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 characteristics of the system in question, as well as how it is operated. 77 U.S. EPA, Assessing the Multiple Benefits of Clean Energy: A Resource for States (February 2010), available at: 

http://epa.gov/statelocalclimate/documents/pdf/epa_assessing_benefits_ch3.pdf 
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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 CO2

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

savings data.78 Information about the timing of energy savings has direct implications for 

estimating the avoided CO2 emissions that result from an efficiency program or portfolio of 

programs. 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 CO2 emissions. In particular time-differentiated data is 

necessary to estimate the marginal avoided CO2 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 savings, which can be used to identify the marginal 

EGU or cohort of marginal EGUs that would have provided generation in the absence of the 

energy savings. This supplemental data can be used to more accurately estimate avoided CO2

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 or guidance for state plans is the 

extent to which time-differentiated data on energy savings from energy efficiency programs is 

available, and whether states can readily acquire such data and information for use in 

implementing their state plans. 

                                                            

78 This is often referred to as the “load shape” of energy savings achieved through an energy efficiency measure. 
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 A related consideration is metrics reported for electricity savings. The primary metric 

required to understand the avoided CO2 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 CO2 emissions related to electric generation, when reporting on 

avoided CO2 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 savings 

are the change in energy use (MWh) and demand (MW) that results directly from programrelated actions taken by program participants, regardless of why they participated in a program. 

Net savings refer to the change in energy use and demand that is directly attributable to a 

particular energy efficiency program.79 Reporting of net savings helps a PUC ensure that energy 

efficiency program budgets are being used to promote technologies and practices that are not 

otherwise being adopted in the marketplace. A consideration for EM&V of energy efficiency 

requirements and programs included in state plans is whether required reporting of energy 

                                                            

79 Calculations of net energy savings involve excluding energy efficiency measures undertaken by "free riders" (i.e., 

EE program participants who receive a program rebate even 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 directly participate in an EE program, but who undertake 

efficiency 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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savings should be specified on either a gross or net basis, or both, to promote national 

consistency in measuring the impact of energy efficiency measures across state plans.80

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 their 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 determine 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 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 states (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 summarized in the preamble, and discussed in more depth in this section, utilities and 

states have conducted ongoing evaluation 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. As a result, existing state and utility EM&V requirements and 

processes generally provide a solid foundation for minimum EM&V requirements that might be 

                                                            

80 If both gross and net savings were required 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 CO2 emissions from affected EGUs. 
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established by the EPA 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 these measures and 

programs, 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 best practices require the level of EM&V 

effort (i.e., rigor, reliability, validity, and uncertainty of energy savings estimates) to be aligned 

with the required level of certainty of evaluation results and the magnitude of energy efficiency 

program impacts. These best practices are consistent with credible environmental results, ensure 

minimum levels of cross-state consistency, and encourage the use of state energy efficiency 

requirements, programs, and measures in state plans. To support these objectives, the following 

process considerations are relevant for documenting energy efficiency savings from measures in 

state plans. 

Options for EM&V requirements or guidance for state plans that incorporate energy 

efficiency requirements, programs, and measures include: 

 Establishing specific EM&V requirements with a level of defined rigor for all energy 

efficiency programs and measures; 

 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; 

 Establishing specific EM&V requirements for certain types of widely used energy 

efficiency programs and measures 

 Establishing a set of minimum specified 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 

Comment [A12]: Options listed omit a “middle

of the road” approach such as the Uniform Methods

Project.  

Comment [A13]: 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.  
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At one end of this spectrum, establishing specific EM&V requirements provides certainty 

to states in terms of required energy savings documentation, and do 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 potentially 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, and 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 no specific EM&V requirements are 

established, then a state has maximum flexibility, but also faces increased uncertainty about 

whether the EM&V approach included in a proposed state plan will be approved by the EPA. 

This could increase the transaction costs incurred by states during the development of their plans, 

and could possibly delay the full implementation of energy efficiency programs incorporated in 

state plans. 

In the middle of the spectrum, some minimum EM&V criteria 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. States would have 

some level of certainty about acceptable EM&V approaches in state plans, as well as some 

flexibility in establishing appropriate EM&V approaches for the types of energy efficiency 

programs and measures included in their plan. 

A supplemental approach, in addition to those described above, is to prescribe who can 

conduct EM&V activities and prepare energy savings documentation, and 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 the qualifications, integrity, and independence of 

Comment [A14]: Though this comment

bookends the options, a lack of EM&V requirements

would be extremely problematic.
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those conducting EM&V of energy efficiency programs and measures, and preparing energy 

savings estimates, is critical to assuring best-practice EM&V. However, such requirements alone 

may not ensure sufficient evaluation rigor. 

5.1 Use of EM&V Protocols 

Establishing requirements or 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 include in its plan. In addition, because existing 

state and utility EM&V infrastructure and protocols 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 CO2 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 

Development of EM&V plans that are included in a state plan could rely primarily on 

state- or utility-level review and approval processes, with open public involvement and state 

lead-agency approval 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. Using existing state processes may 

better ensure that energy savings estimates are transparent, peer reviewed, and address 

stakeholder input. Using state processes also minimizes duplication of state and the EPA 
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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. 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. 

5.3 General Quality Standards for EM&V Rigor and Accuracy 

 Since existing state EM&V process vary, the EPA may need to identify and establish 

minimum requirements 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 measures with a higher degree of energy savings certainty 

might require a lower level of EM&V effort, while measures with greater complexity or 

uncertainty of energy savings effects would require greater EM&V effort.81

 Simple, well-understood and straightforward energy efficiency programs and measures, 

such as lighting retrofits might require only verification that measures were installed and the use 

of deemed energy savings values (lower EM&V effort level), while less well-understood or more 

complex energy efficiency programs and measures, such as behavior programs and market 

transformation programs, would require more detailed EM&V (high level of EM&V effort). 

 A prescribed EM&V approach for all types of energy efficiency programs and measures 

would provide states with certainty while supporting a consistent level of EM&V rigor across all 

                                                            

81 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 effort” could refer to greater reliance on deemed savings 

values, smaller sample sizes for measured savings, fewer direct measurements, and proportionately 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. 
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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 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 this EM&V 

documentation is an EM&V plan, which specifies a priori 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 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 types of information that might 

be included in an EM&V plan for energy efficiency programs and measures included in a state 

plan. An EM&V plan would specify how EM&V activities will be conducted and reported for 

relevant energy efficiency programs and measures during a state plan performance period. An 
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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 prepare evaluated energy savings reports and their 

 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 entity, or non-governmental entity, which will 

review and certify the evaluated savings 

 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 reported (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, guidance 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 electricity transmissions and distribution losses 

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

o Sources of uncertainty 

 

Comment [A15]: Incomplete sentence – please

clarify.   
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B. Quantification, Monitoring, and Verification 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.82 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 investment level), and other policies (R&D support; 

manufacturing incentives; workforce training; net metering; 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 state policies. Other types of programs (e.g., certain 

grant and rebate programs) may not currently quantify 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. 

                                                            

82 In this section we use the term “renewable energy measure” 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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1. Renewable Portfolio Standards 

A RPS is designed to increase the amount of renewable energy a distribution utility or 

load-serving entity provides to retail electricity customers.83. 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.84

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 utilities 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 distributed utilities typically have to meet state 

RPS requirements, including building and operating renewable energy generating capacity, 

purchasing electricity from renewable energy generators, and purchasing the attributes from 

renewable energy generation. Many state RPSs take this latter approach. Rather than requiring 

                                                            

83 In states that have restructured their electricity sectors and introduced retail competition, entities other than a 

utility may supply electricity to a retail customer. These entities 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. 

84 “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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each distribution utility to generate electricity from its own renewable energy facilities or 

purchase electricity from a renewable facility owned by others, many states require distribution 

utilities to acquire renewable energy certificates (RECs) that represent the attributes of the unit of 

renewable electricity produced.85 

By allowing REC trading, many states have created markets for RECs based on specific 

state RPS requirements. Renewable energy generators 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.86 

There are a number of key aspects of RPS design and implementation that affect the 

quantification, monitoring, and verification of renewable energy generation used to meet a RPS: 

 Eligible renewable energy resources. While most RPS-eligible resources in most states 

will result in avoided CO2 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 resources 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. 87

                                                            

85 RECs are contractual instruments that convey ownership of the attributes of a unit of energy generated, but do not 

represent the energy itself. The attributes conveyed with RECs include information 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. 86 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 supplied from by the distribution utility. “Generic power” or 

“null power” refers to energy that has no generation attributes or descriptive information (i.e., the remaining system 

mix of power, after assignment of specified power to different utility customers, through power purchase contracts 

or purchase of generation attributes through RECs). For electricity labeling, disclosure to customers, or other market 

claims, generic or null power is typically assigned the attributes of the remaining system mix of power, after the 

assignment of attributes as described above. 

87 In the preamble, the EPA is proposing that, for an existing state requirement, program or measure, a state may 

apply toward its required emission performance level the emission reductions that existing state programs and 
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 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 investor-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 technologies. The MWh produced or renewable 

energy certificates (RECs) related to MWh 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 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 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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generation under a RPS it is important to note that most states allow use of eligible 

renewable energy resources located in other states to satisfy the state RPS requirements.88

Considerations related to the quantification, 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 obligations 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 obligations 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 renewable 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 build, 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.89 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 generators are registered with a REC tracking system 

and the generation output is verified according to tracking system and RPS rules. 

                                                            

88 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. 

89 Metered data for these PV systems may only track net electricity supply to or from the grid, representing either 

surplus generation that is not used to serve on-site electricity load or additional net electricity supplied from the grid 

if the system does not meet a building’s total electricity load. 

Comment [A16]: Suggest including this

clarification in the preamble.
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Bilateral contract model 

Under the bilateral contract model, 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. These 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 transmission 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 the transmission grid and the point of receipt at a 

utility transmission or distribution system. A renewable 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.90 

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 purchasing 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 state PUC or state energy office. Verification is 

accomplished by audit of electricity supply contracts along with REC tracking system reports of 

RECs held by the utility and submitted for retirement 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 administrator before issuing RECs for the imported 

energy. Verification can be provided, for example, by demonstration of scheduled delivery 

                                                            

90 This ensures that multiple parties are not using the same MWh of renewable energy generation to comply with 

their RPS obligations. 
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through the ISO or RTO serving the state or region, through demonstration that the seller holds 

transmission rights for delivery or possession of NERC tags for the energy.91 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 generators 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.92 The registration process collects data about the generator’s 

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. 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 participating 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 

                                                            

91 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 physical path of an electricity transaction from the point of 

generation to the point of receipt, and also define the financial path, including all parties to a transaction. All 

wholesale electricity transactions that will result in the transfer of electricity from one control area to another, or that 

involve transfers through a control area, must be accompanied by a NERC Tag. Based on a real-time assessment of 

NERC Tags, system operators can curtail transfers if reliability 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). 

92 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 Information System (WREGIS), Midwest Renewable Energy 

Tracking System (M-RETS), North American Renewables Registry (NARR), Michigan Renewable Energy 

Certification System (MIRECS), Nevada Tracks Renewable 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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generator can then sell the renewable electricity as a bundle (both the commodity electricity and 

the associated REC) or unbundle the RECs from 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 platform. The system tracks each REC through these 

transactions and ultimately “retires” the REC when the final purchaser designates it for 

retirement. Retirement could result from the REC being 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 different 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.93 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 residential 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 generators 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-

                                                            

93 Additional linkages between tracking systems are being established. More information can be found at 

http://www.narecs.com/resources/registries/ 
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party owned and operated, the project developer will own the RECs and factor their revenue 

value into their pricing offered to the site host for electricity supply. Note also that many utilitysponsored renewable energy incentive programs stipulate 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 Public Utilities Commission (PUC) or its equivalent is responsible for 

establishing the detailed rules and procedures that obligated parties must follow 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 and 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 distribution utilities and 

some states for renewable energy systems that meet eligibility criteria.94 Under a FIT, the utility 

offers to purchase specific kinds of electricity (e.g., solar) from sellers at posted prices or under a 

                                                            

94 There are several states that offer FITs, including California, Hawaii, Maine, Oregon, Rhode Island, South 

Carolina, Vermont and Washington, as well as numerous electric utilities. 
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published pricing formula for a specified period of time. FITs typically have caps on the amount 

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 formulae 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 measure 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 order 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 generation 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 targets (e.g., total installed MW of generating 

capacity subject to the FIT). State statutes may also 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 receiving FIT payments may also receive incentives 
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under other utility and state programs. Typically state statutes leave implementation details to the 

PUC (or other utility governing body, if applicable, for municipal and cooperative utilities), but 

may provide guidance on what to consider in setting 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 responsible 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 utilities not overseen by PUCs, such as municipal 

utilities and rural electric cooperatives. These utilities have a variety of governance structures 

(e.g., municipal government, cooperative board of directors). The utility governing bodies in 

these situations will be responsible for receipt and 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 improvements 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 that 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-grade utility meter would be present at the point of 
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interconnection to the electricity grid, which provides measurement of MWh generation output 

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 generation 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 depth 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 
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quantification, monitoring, and verification of renewable energy programs and measures 

generally provide a solid foundation for minimum requirements or guidance that might be 

established by the EPA for state plans. 

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 other key information, to determine eligibility and 

track program activity or compliance with regulatory requirements (if applicable). Quantification 

of electricity generation is typically through the use of revenue-quality meters,95 or engineering 

estimates for small distributed generators. These 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 energy sources, or electricity or RECs purchased 

from eligible renewable energy generators, which may also consider application of multipliers or 

alternative compliance payments.96 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 and facilitating effective regulatory oversight. 

Typically, avoiding CO2 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 CO2 emissions associated with the 

renewable energy generated through an RPS, FIT, or production-based tax incentive that is 

included in a state plan. 

                                                            

95 “Revenue-quality meter” refers to a meter used for billing purposes in wholesale electricity markets, which 

typically need to meet ISO or RTO precision requirements or other specifications. 

96 Compliance status will also consider the application of credit multipliers or alternative compliance payments, if 

relevant under an RPS. 
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The following types of information will increase the accuracy and verifiability of avoided 

CO2 emission estimates related to renewable energy requirements, programs, and measures 

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 CO2 emissions. Information about the location of electric generators that supplied 

electricity generation that was imported to a state or grid region, will also be important. Timedifferentiated information related to electricity generation is also useful in estimating avoided 

CO2 emissions. In particular time-differentiated data is necessary to estimate the marginal 

avoided CO2 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 generation 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 requirements 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 compliance reporting by an electric distribution utility 

subject to an end-use energy efficiency resource 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 latter instance, the utility may also be the owner and 

operator of affected EGUs, but additional reporting of quantified effects of renewable energy and 
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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 

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-use energy efficiency and renewable energy 

programs included as enforceable measures in a state 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 recordkeeping 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 potential 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 measures 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 document 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 performance 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 jurisdiction for the timeframe of interest. 
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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 

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. These 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 policies 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 
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 Certification that evaluators were selected through a public bid process, 

and are third-parties unaffiliated with efficiency program administrators or 

the state government 

 EM&V methods used: 

o Deemed savings values - name, date, and public location of technical reference 

manual (TRM)97 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 savings98 are estimated, definitions used for gross 

and net savings, and the basis for gross to net calculations, if applicable 

o Avoided transmission and distribution (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 energy efficiency programs in state plans. One is 

whether the reporting processes, timeframes, and documentation required by state PUCs, 

described above, are sufficient and appropriate 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 savings impacts on behalf of the state, potentially 

including certification that the values are appropriate and conservative, and meet their approval. 

                                                            

97 A technical reference manual (TRM) is a document consisting 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. 

98 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 they 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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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 

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 obligations are typically specified in authorizing 

legislation, regulations, or PUC orders. Compliance is typically on an annual basis, and includes 

a list of required reporting elements. Some states also require distribution utilities to provide an 

implementation plan describing how they will comply 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.99 In some 

states, compliance reports may also include state-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 compliance 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. 

                                                            

99 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. 
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2. Typical Reporting for Renewable Energy Deployment Programs100 

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 accelerate the deployment of 

renewable energy technologies, such as rebates, feed-in tariffs, and net metering programs. As 

mentioned previously, it is easier to quantify the 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 generation 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 device 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 production supplied to the grid during an identified 

                                                            

100 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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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 total output from the customer-sited system, and 

another to measure the total electricity purchased from the utility. 

Many of these renewable energy deployment programs are developed as part of 

requirements by PUCs, and therefore utilities must 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 utilities that are not regulated by a state PUC (e.g., municipal and 

cooperative electric utilities). In these instances 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).101 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. 

                                                            

101 IRPs are typically required in states with vertically integrated electric utilities, but are less common in states that 

have deregulated their electricity sectors and introduced competition for the supply of electricity to retail customers. 
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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 

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 generated 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.102 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.103 State 

and utility incentive programs where payment of incentives is not based on electric generation 

may not currently be sufficient for reporting under a state plan. Additional reporting 

                                                            

102 Small distributed renewable energy systems, such as those below 10 kW in capacity, are often allowed to use 

engineering estimates to determine annual output. 

103 Some of these programs, such as net metering, may also require supplemental reporting in order to track total 

generation that avoids CO2 emissions. In many instances, net metering programs only track the net electricity 

supplied to a customer or supplied to the grid by the renewable energy system, rather than total generation output. 
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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 

plans to demonstrate the avoided CO2 emissions associated with these requirements, programs, 

and measures. States may need to require additional reporting detail, such as the location of 

renewable energy generating units that supplied output used to comply with a state RPS. 

Additional reporting detail about when renewable energy was generated may also be valuable for 

estimating the avoided CO2 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.104 For distributed renewable energy resources, reporting of the MW capacity of 

generating systems that are installed as a result of state requirements or programs during a 

reporting period would also be useful for estimating avoided CO2 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 

CO2 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 

                                                            

104 This might include information about the seasonal or daily generating profile of the generating unit or renewable 

energy resource type. 
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 For REC data, information including the following 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 

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 interconnected 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 CO2 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 portfolio requirement. Some states also apply CO2

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 associated 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 CO2 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 CO2 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 counting of emission effects. One option presented 

could lead to double counting of emission 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 budget trading programs and regional renewable 
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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 programs and measures that we anticipate states may 

want to include in a state plan. 

A. Background 

Electricity flows across state lines. Often electricity load centers (i.e., areas of high 

electricity demand) in one state are supplied in part by generating units in another state. As a 

result, some states are net exporters or importers 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 electric generating capacity (e.g., through a state 

RPS) therefore can result in CO2 emission effects that are realized outside the state that 

implements the regulation or program that produces 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 CO2 emissions. In addition, many state regulations 

explicitly address CO2 emissions in neighboring states, or allow 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 meeting a utility portfolio requirement. 

End-use energy efficiency actions reduce electricity load, and ultimately impact electric 

generation. In some instances improving end-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 CO2 emissions from specific in-state 

EGUs. More often, reduction of electricity load will impact EGU dispatch across a regional 

generation control area, based on factors such as power plant economics and electricity 
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transmission capability, and could also impact flows between control areas.105 In these cases, 

state end-use energy efficiency programs and measures will affect electricity generation in the 

state that reduces load, as well as in neighboring states. 

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 EGU dispatch at the regional level. State RPSs 

are typically applied to electric distribution utilities 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 renewable 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 submission 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 service 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-asides” 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 

                                                            

105 Often these dispatch economics differ by location, based on electricity demand, transmission constraints, and 

generation economics of individual power plants necessary for meeting demand (e.g., in competitive wholesale 

markets, these factors are represented through locational marginal prices (LMPs), which determine dispatch). 
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homes and commercial buildings).106 Distributed solar PV capacity often provides benefits to the 

electric distribution system by improving 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 

be met through large EGUs connected to the grid.107 Regardless of the approach taken, state RPS 

regulations typically have impacts on EGU dispatch, and related avoided CO2 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 CO2 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 would have the flexibility to distribute the 

CO2 emission reductions among states in the multi-state area. 

o States could jointly demonstrate CO2 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: 

                                                            

106 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. 

107 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 output exceeds building electricity demand. 
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o Consistent with existing state RPS policies, a state could take into account all of 

the CO2 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 would have the flexibility to distribute the 

CO2 emission reductions among states in the multi-state area. 

o States could jointly demonstrate CO2 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 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 CO2 emissions 

For plan measures such as end-use energy efficiency and renewable energy regulations 

and programs, estimating the avoided CO2 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 claims the emissions reduction benefit 

Under this approach, the state that implements 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 CO2 emissions, regardless of where 

they occur. 

 Cooperative multi-state accounting 

Multiple states are allowed to mutually agree to how they will distribute avoided CO2 

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 CO2 emissions are distributed 

among states by agreed formula they derive – an accounting “credit” in one state for 
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out-of-state avoided CO2 emissions is complemented by an accounting “debit” in 

the other state where the avoided CO2 emissions occurred (i.e., through an increase in 

reported CO2 emissions or CO2 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 

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 CO2 or avoided MWh, could be used by affected EGUs toward 

demonstration of compliance with state rate-based CO2 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 demonstrate emission performance by affected EGUs. 

Stets jointly demonstrate emission performance for affected EGUs, in terms of total CO2 

emissions (under a mass-based multi-state plan) or weighted average CO2 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 regional 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 state 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 effects summarized above. The table explains how 
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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 

1. State May Claim the Impact of a Measure on CO2 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 the state if it has the effect of avoiding CO2

emissions from those in-state EGUs. This could be done regardless of whether the action taken to 

implement the state measure occurs within or outside the state. For example, renewable energy 

generation that occurs outside the state as a result of a state renewable portfolio standard 
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obligation would still be a valid state plan action, provided the out-of-state renewable energy 

generation has the effect of avoiding CO2 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 CO2 emissions from those in-state EGUs. 

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

EGU CO2 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 CO2

emissions, both for projections of emission performance under the plan and ex post 

demonstration of performance achieved. Under this 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 under a state plan, a dispatch model would be 

applied to a grid region to estimate the marginal or average avoided CO2 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 CO2 emissions from its own in-state EGUs, these effects could 

be applied to meet the required level of CO2 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 CO2 emissions that will be achieved through a plan.) 

Ex post demonstration of plan performance

To assess the state-by-state avoided CO2 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 CO2 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 
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CO2 emissions, based on reported EE savings and RE generation, could be applied through an 

administrative adjustment by the state program administrator 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 CO2 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 approach to estimate avoided CO2 emissions.) 

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 CO2 emissions from in-state affected EGUs. For 

example, in a state that imports 30% of electricity on average during a year, energy savings from 

EE measures might be multiplied by a factor of 0.70.108 Avoided CO2 emissions might then be 

calculated by multiplying this adjusted energy savings number by the average or marginal CO2

emission rate for affected EGUs in the state. This type of approach could be employed in both 

projections of plan performance and ex post demonstrations of performance. However, this 

method would be subject to uncertainty, as electricity 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 CO2 emissions.) 

This approach would avoid double counting of emission effects of state measures among 

states. However, it could reduce incentives for states to employ measures that have a systemwide, regional effect in reducing EGU CO2 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 CO2 emissions under its plan than a state that is not a net importer. 

 

                                                            

108 In this instance, it would be assumed that 30% of the reduction in electricity load resulted in avoided CO2

emissions from out-of-state EGUs that serve electricity load in the importing state. 
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2. State that Implements the Measure 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 CO2 emissions, regardless of where they occur. 

If the avoided CO2 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 CO2 emission rate or tonnage CO2 emissions. Under a tradable credit approach, credits 

would be issued for all avoided CO2 emissions resulting from applicable 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 limits would functionally apply the avoided CO2

emissions to the state that was responsible for the measure. 

This approach provides a clear policy signal and incentives that reward state actions that 

reduce EGU CO2 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 CO2 emissions reductions from affected EGUs, without raising the 

prospect of double counting of emission effects among state. 

 
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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 CO2 emissions from RE and demand-side EE measures across their 

respective EGU fleets. Avoided CO2 emissions would be distributed 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 accordingly. 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 actions that meet applicable quantification, 

monitoring, and verification requirements would be issued tradable credits that could be applied 

by affected EGUs to their reported CO2 emission rates when demonstrating compliance with an 

emission limitation in a state plan.109 A credit issued in one state could be used by an affected 

EGU in another state toward meeting its respective rate limit.110

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 

                                                            

109 These credits might be denoted in avoided CO2 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. 

110 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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91 

EGU marginal emissions abatement costs. In effect, 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 counting 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 states implementing a mass-based approach, where 

credits for avoided CO2 emissions are transferred to affected EGUs located in another state for 

compliance purposes, the state from which credits were transferred would adjust its reported CO2

mass emission from affected EGUs when demonstrating achievement of the required CO2

emission performance level by affected EGUs identified in the state plan.111

5. Regional Demonstration by States of Emission Performance 

Under this approach, multiple states would demonstrate CO2 emission performance by 

affected EGUs on a regional basis.112 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 CO2 emissions. Instead, states would assess the impact of state measures in 

avoiding CO2 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 CO2 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 plans. This approach is also premised on the 

                                                            

111 Note that in this example, state reporting of overall achieved CO2 emission performance by affected EGUs 

under a state plan is distinct from demonstration of compliance by affected EGUs subject to a mass-based CO2

emission limit. For EGU compliance, no adjustment would be made to CO2 emissions reported by affected EGUs 

subject to the mass-based emission limit, even though emissions 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 CO2 emissions from the affected fleet to account for the “export” of avoided CO2 emission credits, 

in order to demonstrate the overall level of CO2 emission performance that is assumed to have been achieved by the 

affected EGU fleet under the plan. 

112 This approach could be applied for CO2 emission performance on either a rate or mass basis. 
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willingness of all states in a grid region to participate in the development and implementation of 

a multi-state plan. Some states in a grid region 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.113 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 region are projected to achieve the required level 

of performance represented in individual state plans, 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 counting of interstate effects among states are less 

important. The EPA could indicate as part of plan 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 CO2 Emissions 

[This appendix will include the content in the document, Survey of Existing State Policies and 

Programs that Reduce Power Sector CO2 Emissions. This draft document was submitted to OMB 

on April 3, 2014.] 

                                                            

113 For example, this assessment could be for a multi-state region that generally aligns with a contiguous grid 

region.
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Appendix for State Plan Considerations

Technical Support Document (TSD)  

Survey of Existing State Policies and Programs that  

Reduce Power Sector CO2 Emissions

DRAFT

April 3, 2014

For Carbon Pollution Guidelines for Existing Power Plants:  

Emission Guidelines for Greenhouse Gas Emissions from Existing Stationary

Sources: Electric Utility Generating Units

Docket ID No. EPA‐HQ‐OAR‐2013‐0602
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Contents

I. Overview of state climate and energy policies and programs that reduce power sector CO2.............6

II. Existing state and utility policies, programs, and measures that affect EGU CO2 emissions ...............8

a. Actions that reduce EGU CO2 Directly............................................................................................... 9

i. Market‐based Emission Limits...................................................................................................... 9

ii. CO2 emission performance standards........................................................................................ 16

b. Energy Efficiency Policies, Programs and Measures....................................................................... 20

i. Energy Efficiency Resource Standards........................................................................................ 21

ii. Demand‐side Energy Efficiency Programs.................................................................................. 24

iii. Building codes............................................................................................................................. 27

iv. Appliance and equipment efficiency standards......................................................................... 29

v. Incentives and Finance Mechanisms for Energy Efficiency ........................................................ 31

c. Renewable Energy Policies and Programs...................................................................................... 33

i. Renewable Portfolio Standards.................................................................................................. 33

ii. Performance‐Based Incentives and Finance Mechanisms For Renewable Energy ....................36

d. Utility Planning Approaches and Requirements............................................................................. 38

    
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List of Acronyms

ACEEE ‐ American Council for an Energy Efficient Economy

ACP ‐ Alternative Compliance Payment

BSER – Best System of Emission Reduction

CACJA ‐ Clean Air Clean Jobs Act

CCR – Cost Containment Reserve

CHP – Combined Heat and Power

CEMS – Continuous Emissions Monitoring System

CO2 – Carbon Dioxide

CO2e – Carbon Dioxide Equivalent

CDPHE – Colorado Department of Public Health and Environment

DOE – Department of Energy

DSIRE ‐ Database of State Incentives for Renewable Energy

EERS – Energy Efficiency Resource Standard

EGU – Electricity Generating Unit

EIA – Energy Information Administration

EM&V – Evaluation, Measurement, and Verification

EPA – Environmental Protection Agency

ERP – Electric Resource Plan

ESCO – Energy Service Company

GDP – Gross Domestic Product

GHG – Greenhouse Gas

GW – Gigawatt (1 GW = 1,000 MW)

GWh – Gigawatt‐hour (1 GWh = 1,000 MWh)

IECC ‐ International Energy Conservation Code

IOU – Investor‐Owned Utility

IRP – Integrated Resource Planning

kWh – Kilowatt‐hour

LBNL – Lawrence Berkeley National Laboratory

LDC – Local Distribution Company

MERP ‐ Metropolitan Reduction Proposal

MMBTU – Million British Thermal Units

MW – Megawatt

MWh – Megawatt‐hour (1 MWh = 1,000 kWh)

NOx – Nitrogen Oxides

PBF – Public Benefit Funds

PBI – Performance‐based Incentives

RGGI – Regional Greenhouse Gas Initiative

REC – Renewable Energy Certificate

RES – Renewable Energy Standard
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RPS – Renewable Portfolio Standard

PUC – Public Utility Commission

SO2 – Sulfur Dioxide

VEIC – Vermont Energy Investment Corporation

WAP – Weatherization Assistance Program
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Survey of Existing State Policies and Programs that  

Reduce Power Sector CO2 Emissions

I. Overview of state climate and energy policies and programs that reduce

power sector CO2

Across the nation, many states and regions have shown strong leadership in creating and

implementing policies, programs and measures that reduce greenhouse gas (GHG) emissions

from the power sector, while achieving other economic, environmental, and energy benefits.

These policies and programs can serve as a strong foundation as states develop plans to meet

goals under the Carbon Pollution Standards for existing sources.  

This document provides a survey of many of these activities. Policies and programs range from

market‐based programs and GHG performance standards that require direct GHG emission

reductions from EGUs, to others, such as renewable portfolio standards (RPS) and energy

efficiency resource standards (EERS), that reduce GHG emissions by altering the mix of energy

supply and reducing energy demand. States have developed their policies and programs with

stakeholder input and tailored them to their own circumstances and priorities. Their leadership

and experiences provided the EPA with important information about best practices to build

upon in this proposed rule.

States vary in their regulatory structures, electricity generation and consumption patterns,

while geography affects factors such as the availability of fuels, transmission networks, and

seasonal energy demand. States have tailored their climate and energy policies and programs

accordingly. For example, in some states, utilities are vertically integrated, meaning that the

one company is responsible for electricity generation, transmission, and distribution over a

given service territory.  The state utility regulators have authority over these utilities.  In other

states, where the electric power industry has been restructured, generation has been

decoupled from distribution, and retail customers have their choice of electricity suppliers. In

actively restructured states (see Figure 1), the utility regulators do not have authority or control

over the utilities responsible for generation, only over the distribution utilities. States rely upon

and have access to different fuel types and house a variety of EGU types within state borders.  

States are part of regional electricity grids that do not align with state boundaries.  Electricity is

imported and exported by utilities across states throughout each regional grid.     
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Figure 1: Status of Electricity Restructuring by State (September 2010)1

States also have different economic considerations, drivers and approaches when

implementing climate change, energy efficiency and/or renewable energy policies, programs or

measures.  Actions can be motivated by state environmental, energy and/or economic concerns.  

For example, ten states have passed legislation requiring GHG emission reductions are using a

combination of climate change, energy efficiency and renewable energy strategies to achieve

these targets.2 Other state policies are motivated by public utility commission (PUC)

requirements to achieve all cost‐effective energy efficiency improvements and still others by

renewable energy generation requirements.  Policies, programs and measures vary from state

to state in their implementation levels and administration, some run by state agencies and

others by utilities with varying mechanisms for ensuring compliance.  

This appendix is not exhaustive and is only intended to provide information about strategies

states have used to achieve GHG emission reductions, advance energy efficiency and/or

increase the use of renewable resources.   Policies and programs included in this appendix are

                                                            

1 U.S. DOE, Energy Information Administration,

http://www.eia.gov/electricity/policies/restructuring/restructure_elect.html 2 States include California, Connecticut, Hawaii, Maine, Maryland, Massachusetts, Minnesota, New Jersey, Oregon,

and Washington. Targets are typically defined on a 1990 base year, aiming to achieve reductions of between 0 and

10 percent by 2020, although Maryland and Minnesota have chosen targets of 25 percent below 2006 levels by

2020, and 15 percent below 2005 levels by 2015 respectively.

Comment [A1]: It is unclear what’s meant by

“climate change ... strategies”.   

Comment [A2]: This document should also

address policies used to further other forms of clean

generation. For example, one that should be added

is Construction Work in Progress for new nuclear

plants.  It is unlikely that the four AP1000s under

construction in the Southeast would have been

pursued in the fashion that they were without this

state policy to offset some of the up‐front

construction risk.
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not necessarily approvable in the context of a 111(d) state plan.  In order to be approvable,

they must meet criteria laid out in this proposed rule, as described in the earlier part of this

Technical Support Document, State Plans Considerations.

II. Existing state and utility policies, programs, and measures that affect EGU

CO2 emissions

Some state and utility policies, programs and measures directly target CO2 emissions by

creating specific limits or standards for CO2 in the power sector. Other policies and programs,

such as those that advance energy efficiency and renewable energy, are designed to reduce

energy demand or promote an increase of supply from low or non‐GHG emitting sources which

reduces CO2 emissions.  While states often enact energy efficiency and renewable energy

programs for economic or reliability purposes, such as for reducing electricity rates or avoiding

the need to build new generation, many of the states aggressively pursuing climate change

mitigation look to both energy efficiency and renewable energy for the bulk of their reductions.   

For example, according to California, “the integrated nature of the grid means that policies

which displace the need for fossil generation can often cut emissions from covered sources

more deeply, and more cost‐effectively than can engineering changes at the plants alone,

though these source‐level control efforts are a vital starting point.”3 In working to meet its

statewide goal of reducing GHG emissions to 1990 levels by 2020 and 80 percent below 1990

levels by 2050, the state calls their energy efficiency standards “the bedrock upon which

climate policies are built” and uses renewable energy to fill any remaining energy needs.”4

  

Compared to the costs of other climate policies, they find that “energy efficiency provides

substantial emissions reductions and should be an essential element of the BSER CO2 reduction

target.”5

  Another state, Connecticut, has a law that requires the state to reduce GHG emissions

to 10 percent below 1990 emissions levels by 2020 and 80 percent from 2001 levels by 2050.6

  

They consider energy efficiency investments, expanded renewable energy and participation in

the Regional Greenhouse Gas Initiative among its top ten strategies to reduce GHGs when

considering cost‐effectiveness and GHG‐reduction potential.7

   

                                                            

3 December 27, 2013 Letter from Mary D. Nichols, Chairman of California Air Resources Board, to EPA

Administrator Gina McCarthy.   4 Ibid.

5 Ibid.

6 Connecticut Global Warming Solutions Act, http://www.env‐

ne.org/public/resources/pdf/CT_Global_Warming_Bill_Summary.pdf   7 States’ §111(d) Implementation Group Input to EPA on Carbon Pollution Standards for Existing Power Plants,

Joint comments from 15 states on Carbon Pollution Standards for Existing Power Plants sent to USEPA

Administrator McCarthy on December 16, 2013. Signatories include: Mary D. Nichols, Chairman of California Air

Comment [A3]: Can EPA provide an example of

when a state has enacted energy efficiency and

renewable energy programs to reduce electricity

rates? Improving system resilience could be a goal

of an EERS, however.
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Beyond these specific policies and programs, some states implement planning requirements

that can affect emissions both directly and indirectly.  This section describes a range of existing

state actions that fall into all of these categories.

a. Actions that reduce EGU CO2 Directly

Existing state actions that directly reduce EGU CO2 emissions tend to fall in one of two

categories: market‐based emission limits or emission performance standards.   

i. Market‐based Emission Limits  

Description

An emissions budget trading program (or “cap‐and‐trade” program) is a market‐based tool for

reducing pollution. The basic approach, which involves the allocation and trade of

environmental permits, has been used across environmental media, including air pollution

control, clean water regulation, and land‐use applications.   

Ten states have implemented emissions budget trading programs addressing CO2 and other

GHG emissions. These include California’s cap and trade program and the nine northeast and

mid‐Atlantic states participating in the Regional Greenhouse Gas Initiative (RGGI), consisting of

Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New York, Rhode

Island, and Vermont. .

89

                                                                                                                                                                                               

Resources Board, Robert B. Weisenmiller, California Energy Commission, Michael R. Peevey, Chair of California

Public Utilities Commission, Larry Wolk, MD, MSPH, Executive Director and Chief Medical Offices of Colorado

Department of Public Health and Environment, Dan Esty, Commissioner of Connecticut Department of

Environmental Protection, Collin O’Mara, Secretary of Delaware Department of Natural Resources and

Environmental Control, Dallas Winslow, Chairman of Delaware Public Service Commission, Douglas Scott, Chair of

Illinois Commerce Commission, David Littell, Commissioner of Maine Public Utilities Commission, Robert M.

Summers, Secretary of Maryland Department of the Environment, Kelly Speakes‐Backman, Commissioner of

Maryland Public Service Commission, Ken Kimmell,  Commissioner of Massachusetts Department of Environmental

Protection, Mark Sylvia, Commissioner of Massachusetts Department of Energy resources, John Linc Stine,

Commissioner of Minnesota Pollution Control Agency, Mike Rothman, Commissioner of Minnesota Department of

Commerce, Thomas S. Burack, Commissioner of New Hampshire Department of Environmental Service, Joseph

Martens, Commissioner of New York State Department of Environmental Conservation, Audrey Zibelman, Chief of

New York State Public Commission, Dick Pederson, Director Oregon department of Environmental Quality, Janet

Coit, Director of Rhode Island Department of Environmental Management, Marion Gold, Commissioner of Rhode

Island Office of Energy resources, Deborah Markowitz, Secretary of Vermont Agency of Natural Resources, James

Volz, Chairman of Vermont Public Service Board, Maia Bellon, Director of Washington State Department of Ecology.    8 RGGI website: http://www.rggi.org/rggi   9 California Air Resources Board: http://www.arb.ca.gov/cc/capandtrade/capandtrade.htm  

Greenhouse Gas Cap and Trade

Last updated 3/24/2014
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Policy Mechanics

Design

An emissions budget trading program establishes an aggregate limit on pollution through an

emissions cap that specifies the total allowable emissions for all of the sources subject to the

program. To comply with the program, each source must acquire allowances, through

purchases or by allocation from the state, equal to their emissions and surrender them at the

end of each compliance period.

Allowances may be traded among both regulated and non‐regulated parties, creating a market

for emission allowances. In turn, the allowance market establishes a price signal for emissions

(a market price for emitting a unit of pollution), which triggers broad economic incentives for

reducing emissions across the covered sector(s) and encourages innovation in developing

emissions control strategies and new pollution control technologies.

There are several key design elements that can vary from program to program:

 Scope of coverage (e.g., sectors and types of facilities covered)

 Applicability (criteria for inclusion of emitting facilities and units in the program)

 Emissions budget (i.e., “cap”) and emissions reduction schedule

 Flexibility provisions in addition to ability to trade emission allowances, including:  

o Multi‐year compliance periods,  

o Allowance banking,  

o Offsets (e.g., project‐based emissions reductions occurring outside the capped

sector/sources)

 Additional provisions to mitigate price volatility and overall costs  

o Auction reserve price  

o Cost containment reserve of allowances provided for sale at set price thresholds.

Once the allowance price hits a threshold, an extra supply of allowances are made

available

Table 1 summarizes some of the key design elements of the RGGI and California programs.
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Table 1: Comparison of RGGI and California Emissions Budget Trading Programs  

Element RGGI California

Applicability  All fossil fuel fired power plants with a

capacity of 25 MW or greater. 10

 All facilities in covered sectors emitting at

least 25,000 metric tons CO2 equivalent

(CO2e) or greater.11

Scope  Facilities in electric utility sector.12  Facilities in utility and large industrial sectors

(plus fuel distributors in 2015)13

Emissions

budget  Recently reduced 45 percent to 91

million tons CO2 in 2014.  Beginning in

2014, cap was reduced a further 2.5

percent per year to 2020.14

 Emissions cap was set at 2 percent below

expected 2012 emissions, declining by 2

percent in 2014 and 3 percent annually from

2015 to 2020. 15

Compliance

period  Must demonstrate compliance every

three years and hold at least 50 percent

of their obligations during first two

years of each period. 16

 Facilities must demonstrate full compliance

every three years, but the must surrender

allowances and offsets to cover 30 percent

of their compliance obligations during the

first two years of each three year cycle.17

Allowance

allocation

method

 Each state distributes their share of

allowances in an amount determined by

their applicable statute or regulation.  

Approximately 90 percent of CO2

allowances are auctioned off to EGUs or

the secondary market.18

 Large industrial facilities and electric utilities

are allocated the majority of their

allowances for free, set at 90 percent of the

average efficiency of a given sector. The

remaining allowances are auctioned off. The

share of allowances allocated for free

declines over time.19

Cost

containment

provisions

 An additional five million allowances

became available March 2014 when

market price exceeded $4 per ton.20  

 Trigger price increases until 2020 when

10 million allowances become available

 A strategic reserve is starting at 1 percent of

allowances, rising over the years to 7

percent.  Shares of allowances held in the

reserve will be released at three price trigger

points; $40, $45, and $50 per ton and rise by

                                                            

10 RGGI – Overview of RGGI CO2 Budget Trading Program:

http://www.rggi.org/docs/program_summary_10_07.pdf 11 CARB ‐ Cap and Trade Regulaiton Instructional Guidance, Chapter 2:

http://www.arb.ca.gov/cc/capandtrade/guidance/chapter2.pdf 12 RGGI Fact Sheet – Regional Greenhouse Gas Initiative; http://www.rggi.org/docs/RGGI_Fact_Sheet.pdf 13 CARB: ARB Emissions Trading Program Fact Sheet:

http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf 14 RGGI Press Release, January 13, 2014, http://www.rggi.org/docs/PressReleases/PR011314_AuctionNotice23.pdf 15 CARB: ARB Emissions Trading Program Fact Sheet:

http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf 16 Regional Greenhouse Gas Initiative  http://www.rggi.org/market/offsets 17 CARB: ARB Emissions Trading Program Fact Sheet:

http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf 18 Regional Greenhouse Gas Initiative 2013 Allowance Allocation http://rggi.org/design/overview/allowance‐

allocation/2013‐allocation.    19 CARB: ARB Emissions Trading Program Fact Sheet:

http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf 20 Reuters Point Carbon article

http://www.pointcarbon.com/research/promo/research/1.4523252?&ref=searchlist
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if price per ton exceeds $10.7521 5 percent per year including inflation.22

Banking  Allows unlimited allowance banking23  Allows unlimited banking of allowances.24

Offsets  Power plants covered under RGGI are

allowed to use offsets within the RGGI

region25 to meet 3.3 percent of their

compliance obligation.26.

 Facilities may use domestic offsets for up to

8 percent of their compliance obligations.27

A framework has been established to include

international offsets but these are currently

not allowed in the program. 28

Authority

State and regional GHG emissions budget trading programs are authorized through individual

state legislation and implemented through state regulations. For example, California

implemented their emissions trading program under the authority of its 2006 Global Warming

Solutions Act, which requires the state to reduce its 2020 GHG emissions to 1990 levels.29   Each

RGGI state has separate authorizing legislation, and in some cases their legislation specifically

directs the use of auction proceeds. For example, Maine authorized its participation in RGGI

through Stature 580‐A. Title 38 Chapter 3B: Regional Greenhouse Gas Initiative. This statute

also requires that 100 percent of auction proceeds to go towards carbon reduction and energy

conservation efforts.30  

                                                            

21 Regional Greenhouse Gas Initiative, Summary of RGGI Model Rule Changes: February 2013

http://www.rggi.org/docs/ProgramReview/_FinalProgramReviewMaterials/Model_Rule_Summary.pdf   22 CARB: Proposed Regulation to Implement the California Cap and Trade Program:

http://www.arb.ca.gov/regact/2010/capandtrade10/capisor.pdf   23 RGGI – Overview of RGGI CO2 Budget Trading Program http://www.rggi.org/docs/program_summary_10_07.pdf 24 CARB: Proposed Regulation to Implement the California Cap and Trade Program:

http://www.arb.ca.gov/regact/2010/capandtrade10/capisor.pdf

25 http://www.rggi.org/market/offsets   26 Eligible offsets under RGGI include: landfill methane capture and destruction, sulfur hexafluoride (SF6) reduction

from power transmission, afforestation, end use energy efficiency, and agricultural manure management;

http://www.rggi.org/market/offsets

27 CARB: ARB Emissions Trading Program Fact Sheet:

http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf;   Offsets are initially limited to forestry, urban

forestry, livestock methane capture and destruction, and destruction of ozone depleting substances. However, rice

cultivation and coal mine methane are proposed for inclusion in the program. See: CARB – Potential New

Compliance Offset Projects: http://www.arb.ca.gov/cc/capandtrade/offsets/offsets.htm for more information. 28 CARB: ARB Emissions Trading Program Fact Sheet:

http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf 29 State of California Global Warming Solutions Act of 2006, Assembly Bill 32, Chapter

http://www.leginfo.ca.gov/pub/05‐06/bill/asm/ab_0001‐0050/ab_32_bill_20060927_chaptered.pdf   30 Maine revised statutes: http://www.mainelegislature.org/legis/statutes/38/title38sec580‐B.html
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The regulatory authority issues individual authorizations to emit a specific quantity of emissions

(“allowances”), which typically represent one ton of a pollutant, in an amount that equals the

emissions cap.

Obligated Parties

Obligated parties in trading programs are generally the covered facilities. It is the facilities that

are responsible for acquiring enough emission allowances to cover their emissions at the end of

each compliance period. For example, as stated above, RGGI covers fossil fuel fired power

plants 25 megawatts or greater in size.31 The California cap and trade program covers electricity

generators, importers of electricity, and industrial facilities whose annual emissions exceed

25,000 metric tons CO2e. Starting in 2015, the California trading program will cover distributors

of transportation, natural gas, and other fuels with emissions greater than 25,000 metric tons

CO2e as well as electricity imports from all sources.32

Measurement and Verification

Emissions budget trading programs include requirements for emissions monitoring and

reporting, holding and transfer of allowances, and surrender of allowances (and offsets) in an

amount equal to reported emissions.  This is often referred to, generally, as the program

“compliance obligation”).   

For example, facilities obligated under the RGGI program must report emissions quarterly to

environmental agencies in their respective state as well as annually to the U.S. EPA Greenhouse

Gas Reporting Program.33 They must provide verification of emissions as well as third party

verification of emission reductions from CO2 offsets. GHG emissions reporting for affected

sources in California is addressed through the California mandatory GHG reporting regulations,

using a modified version of the reporting platform administered through the EPA Greenhouse

Gas Reporting Program.34

                                                            

31 RGGI Fact Sheet – Regional Greenhouse Gas Initiative http://www.rggi.org/docs/RGGI_Fact_Sheet.pdf

California Environmental Protection Agency  Air Resources Board, Overview of Air Resources Board Emissions

Trading Program, 10/20/11,  http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf   33 Regional Greenhouse Gas Initiative  ‐ Overview of RGGI CO2 Budget Trading Program

http://www.rggi.org/docs/program_summary_10_07.pdf   34California Environmental Protection Agency  Air Resources Board, Overview of Air Resources Board Emissions

Trading Program, 10/20/11,  http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf.  
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Penalties for Non‐compliance

Failure to submit allowances in an amount equal to reported emissions can result in emissions

penalties. Penalties can come in the form of additional allowance submission requirements (e.g.,

three‐to‐one submission requirements to account for any shortfall), as well as other

administrative fines and penalties.  For example, if facilities are found to be short of the

allowances necessary to meet their obligation under the RGGI program, they can be fined for

up to three times the price of the value of the allowances they lack. Additional penalties may

also be applied at the state level.35 If facilities under the California program are unable to meet

their compliance obligations in time, they must surrender four allowances for every one

allowance they lack.36

Implementation Status

The RGGI program was established in 2009. From 2009 through 2012, the nine RGGI states

invested auction proceeds of more than $700 million in programs that lower costs for energy

consumers and reduce CO2 emissions, including approximately $460 million into energy

efficiency programs.37,38 The participating RGGI states estimate that those investments are

providing benefits of more than $1.8 billion in lifetime energy savings to energy consumers in

the region.39

                                                            

35 Regional Greenhouse Gas Initiative  ‐ Center for Climate and Energy Solutions

http://www.c2es.org/docUploads/rggi‐brief‐12‐18‐13‐updated.pdf 36 C2ES; available at http://www.c2es.org/docUploads/California‐Cap‐Trade‐Summary.pdf 37 Programs include residential, commercial, and industrial programs; Regional Investments of RGGI CO2 Allowance

Proceeds, 2012 (2014), available at http://www.rggi.org/docs/Documents/2012‐Investment‐Report.pdf   38 Of the $707 million in auction proceeds invested by RGGI participating states through 2012, 65 percent

supported end‐use energy efficiency programs. See Regional Greenhouse Gas Initiative, “Regional Investments of

RGGI CO2 Allowance Proceeds, 2012” (2014), available at) http://www.rggi.org/docs/Documents/2012‐

Investment‐Report.pdf   39 Ibid.
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Between 2005, when RGGI was first announced, and 2012, power sector CO2 emissions

in the RGGI participating states fell by more than 40 percent while GDP in the region grew.4041

By contrast, total U.S. power sector CO2 emissions fell by 16 percent during the same period of

time.42 In January 2014, the participating states lowered the overall allowable CO2 emission

level in 2014 by 45 percent, setting a multi‐state CO2 emission limit for affected EGUs of 91

million short tons of CO2 in 2014 and 78 million short tons of CO2 in 2020, more than 50 percent

below 2008 levels.43  

The California economy‐wide market‐based GHG emissions trading program, which addresses

GHG emissions from multiple sectors, was implemented in 2012 with emissions limitations

beginning in 2013. 44,45 While California’s emission trading program, like its state emission limit,

is multi‐sector in scope, the state projects that the emissions trading program and related

complementary measures will reduce power sector GHG emissions to less than 80 million

                                                            

40 Regional Greenhouse Gas Initiative, Report on Emission Reduction Efforts of the States Participating in the

Regional Greenhouse Gas Initiative and Recommendations for Guidelines under Section 111(d) of the Clean Air Act

(2013).http://www.rggi.org/docs/RGGI_States_111d_Letter_Comments.pdf 41 The first three‐year control period under RGGI, establishing CO2 emission limits for EGUs, began on January 1,

2009.

42 2014 U.S. Greenhouse Gas Inventory http://www.epa.gov/climatechange/ghgemissions/usinventoryreport.html 43 RGGI Press Release, January 13, 2014, http://www.rggi.org/docs/PressReleases/PR011314_AuctionNotice23.pdf.   44 California Air Resources Board: http://www.arb.ca.gov/cc/capandtrade/capandtrade.htm   45 The California program was developed in coordination with U.S. state and Canadian province WCI partners.
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metric tons of CO2 equivalent by 2025, a 25 percent reduction from 2005 power sector

emission levels. 46 Prior to the implementation of the emission trading program, California

reports that it reduced CO2 power sector emissions by 16 percent from 2005 to a 2010‐2012

averaging period, a reduction of 16 million metric tons of CO2 equivalent.47    

ii. CO2 emission performance standards

Description

CO2 emission performance standards can apply either directly to EGUs or to the local

distribution company (LDC) that sells electricity to the customers. (For more information about

electricity is generated and distributed, see Chapter 2 of the Regulatory Impact Analysis).

As of March 2014, four states ‐ California, New York, Oregon and Washington ‐ have enacted

mandatory GHG emission

standards that impose

enforceable emission limits on

new and/or expanded electric

generating units. Three states ‐ 

California, Oregon and

Washington ‐ have enacted

mandatory GHG emission

performance standards that

set an emission rate for

electricity purchased by

electric utilities. 48 In addition

to these states, Illinois and

Montana have requirements

that new coal plants capture at

least 50 percent of their CO2 emissions. 49

                                                            

46 Preliminary California Air Resources Board analyses, based in part on CARB 2008 to 2012 Emissions for

Mandatory GHG reporting Summary (2013), cited in Letter to the EPA Administrator, “States' Roadmap on

Reducing Carbon Pollution,” December 16, 2013,

http://www.georgetownclimate.org/sites/default/files/EPA_Submission_from_States‐FinalCompl.pdf   47Ibid.

48 C2ES: http://www.c2es.org/us‐states‐regions/policy‐maps/electricity‐emissions‐caps 49 C2ES: http://www.c2es.org/us‐states‐regions/policy‐maps/electricity‐emissions‐caps

Greenhouse Gas Performance Standards

Applies to new units and power purchase agreements

Last updated 8/8/2013 Requires carbon capture and storage at new coal-fired power 

Applies only to new units
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Policy Mechanics

Design  

States have implemented three different types of CO2 performance standards that affect EGUs

and/or LDCs differently.  The first requires power plant emissions per electricity generated to

be less than or equivalent to an established standard and is directly applicable to EGUs. The

second type places conditions on the emissions attributes of electricity procured by electric

utilities.  It consists of standards that are applicable to LDCs that provide electricity to retail

customers. A third type requires that new coal‐fired power plants must capture and store a

specific percentage of CO2 emissions. Table 2 provides state examples for each of the types of

CO2 performance standards.  

Authority  

In some states, programs are regulated through the Public Utilities Commission (California,

Oregon). New York’s program is regulated through the Department of Environmental

Conservation. Washington’s program is regulated through two different sets of entities

depending on the ownership of the utilities.  The Washington Utilities and Transportation

Commission regulate investor owned utilities, and the utility's governing board, Washington

Department of Ecology, and the State Auditor oversees consumer owned utilities.

Obligated Parties

The emission performance standard can apply either directly to EGUs or to the local distribution

company (LDC) that sells electricity to the customer.

Measurement and Verification

Obligated parties must measure and report on electricity generation and CO2 emissions on a

regular basis to verify their compliance with the standard. The reporting requirements and

timing varies from state to state and are typically set by the agency that oversees the program

as described under authority above. Table 3 provides examples regarding measurement and

verification requirements across California, New York, Oregon, and Washington
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Table 2: Examples of State CO2 Performance Standards

                                                            

50 NY Department of Environmental Conservation, Part 251: CO2 Performance Standards for Major Electric

Generating Facilities http://www.dec.ny.gov/regs/83094.html#83097 51 Oregon Department of Energy ‐ Oregon’s Carbon Dioxide Emission Standards For New Energy

Facilitieshttp://www.oregon.gov/energy/Siting/docs/Reports/CO2Standard.pdf. 52 Washington State Legislature ‐ Chapter 80.70 RCW: Carbon Dioxide Mitigation

http://apps.leg.wa.gov/rcw/default.aspx?cite=80.70&full=true. 53 California bill SB 1368: http://www.energy.ca.gov/emission_standards/ 54 eGRID 2010 data files ‐ http://www.epa.gov/cleanenergy/energy‐resources/egrid/index.html#   55 Oregon Department of Energy ‐ Oregon’s Carbon Dioxide Emission Standards For New Energy

Facilitieshttp://www.oregon.gov/energy/Siting/docs/Reports/CO2Standard.pdf 56 Washington State Legislature ‐ Chapter 80.70 RCW: Carbon Dioxide Mitigation

http://apps.leg.wa.gov/rcw/default.aspx?cite=80.70&full=true

57 Illinois General Assembly Clean Coal Portfolio Standard Law. http://ilga.gov/legislation/publicacts/95/PDF/095‐

1027.pdf  

What It Does State Examples

Requires power

plant emissions

per electricity

generated to be

less than or

equivalent to the

established

standard; Applies

to EGUs

 New York (Part 251, 2012) ‐ New or expanded baseload plants (25 MW and larger)

must meet an emission rate of either 925 lb CO2/MWh (output based) or 120 lbs

CO2/MMBTU (input based).  Non‐baseload plants (25 MW and larger) must meet an

emission rate of either 1450 lbs CO2/MWh (output based) or 160 lbs CO2/MMBTU

(input based).50  

 Oregon (HB 3283; 1997, 2007) ‐ New natural gas‐fired power plants (baseload and

non‐baseload) must meet an emission rate of 675 lb CO2/MWh.  Cogeneration and

offsets may be used to comply with the emission standard.51

 Washington (RCW 80‐70‐010; 2004) ‐ New EGUs 25 MW and larger must have an

approved CO2 mitigation plan that results in mitigation of 20 percent of the total CO2

emissions over the life of the facility.  Includes modifications to existing EGUs that

result in an increase in CO2 emissions of 15 percent or more.  The CO2 mitigation plan

may include one or more of a list of eligible measures (includes indirect measures,

such as EE/RE and offsets). 52

Places conditions

on the emissions

attributes of

electricity

procured by

electric utilities;

Applies to LDCs

 California (SB 1368; 2006) ‐ Electric utilities may only enter into long‐term power

purchase agreements for baseload power if the electric generator supplying the power

has a CO2 emission rate that does not exceed that of a natural gas combined cycle

plant.  The California Energy Commission promulgated regulations establishing an

emission rate of 1,100 lb CO2/MWh.53 By comparison, the average emissions rate of

gas plants in the U.S. is 945 lb CO2/MWh, while the average emissions rate of

pulverized coal plants is 2,154 lb CO2/MWh.54

 Oregon (HB 101; 2009) and Washington (SB 6001; 2007) ‐ Electric utilities may only

enter into long‐term power purchase agreements for baseload power if the electric

generator supplying the power has a CO2 emission rate of 1,100 lb CO2/MWh or

less.5556

Requires that new

coal‐fired power

plants must

capture and store

a specific

 Illinois (SB 1987; 2009) Illinois utilities and retailers must purchase at least 5 percent of

their electricity from Clean Coal Facilities in 2015 and beyond. To be designated a

Clean Coal Facility, new coal‐fired power plants must capture and store 50 percent of

carbon emissions from 2009‐2015, 70 percent for 2016‐2017, and 90 percent after

2017.57

 Montana (HB 25; 2007). The Public Service Commission may not approve new plants
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Table 3: Examples of Measurement and Verification Requirements for CO2 Performance

Standards

State Measurement and Verification Details

California  The California PUC is responsible for approving any long term financial commitment by

an electric utility and must adopt rules to enforce these requirements as well as

verification procedures.59

New York  CO2 emission regulations require recordkeeping, monitoring and reporting consistent

with existing state and federal regulations.  

 Each applicable emissions source must install Continuous Emissions Monitoring Systems

(CEMS) subject to Federal CO2 reporting requirements for 40 CFR part 75, successfully

complete certification tests, and record, report, and quality assure the data from the

CEMS.  

 The owner or operator must report the CO2 mass emissions data and heat input data on

a semi‐annual basis to the Department of Environmental Conservation.  

 On a quarterly basis, the owner or operator must report all of the data and information

required in either 40 CFR part 60 or subpart H of 40 CFR part 75.60

Washington  Mitigation projects must be approved by the appropriate council, department, or

authority, and made a condition of the proposed and final site certification agreement

or order of approval.  

 Direct investment projects are approved if they provide reasonable certainty that the

performance requirements of the projects will be achieved and that they were

implemented after July 1, 2004.  

 For facilities under the jurisdiction of a council, the implementation of a carbon dioxide

mitigation project, other than purchase of carbon credits, is monitored by an

independent entity for conformance with the performance requirements of the carbon

dioxide mitigation plan.  The independent entity shares the project monitoring results

with the council.  

 For facilities under jurisdiction of the department or authority, the implementation of a

carbon dioxide mitigation project, other than a purchase of carbon credits, is monitored

by the department or authority issuing the order of approval.61

Oregon  It is up to the Council during the certificate application phase to determine the gross

CO2 emissions over a 30 year lifetime of the proposed facility to determine whether it

meets the CO2 performance standard.  

 During the operation phase of approved facilities, there are CO2 reporting requirements

to the Oregon Department of Environmental Quality and US EPA.  

 New facilities must pass a 100 hour test in their first year of operation to show they

meet the performance standards.62

                                                            

58 Montana State Legislature – H.B.25, 2007. http://leg.mt.gov/bills/2007/billpdf/HB0025.pdf 59 California bill SB 1368: http://www.energy.ca.gov/emission_standards/ 60 NY Department of Environmental Conservation, Part 251: CO2 Performance Standards for Major Electric

Generating Facilities http://www.dec.ny.gov/regs/83094.html#83097 61 Washington State Legislature ‐ Chapter 80.70 RCW: Carbon Dioxide Mitigation

http://apps.leg.wa.gov/rcw/default.aspx?cite=80.70&full=true

62 Oregon Department of Energy ‐ Oregon’s Carbon Dioxide Emission Standards For New Energy Facilities

percentage of CO2

emissions

constructed after January 2007 that are primarily coal‐fired unless at least 50 percent

of the plant’s CO2 emissions are captured and stored.58
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Penalties for Noncompliance

For policies that affect target new electric generating units, utilities must prove any proposed

units are in compliance at the time of permitting. In Oregon, if facilities do not meet the

performance standard in their first year of operation during a 100 hour test63, they must

purchase offsets to account for any excess emissions.64

Implementation Status

Since enacting the performance standard, California’s carbon emissions rates have fallen from

approximately 1,245 lbs CO2e/MWh for fossil generation (considering both in‐state and

imported power) and 875 lbs CO2e/MWh for all power in 2005 to an average of approximately

1,090 lbs CO2e/MWh and 775 lbs CO2e/MWh in the three years before 2012.65  

b. Energy Efficiency Policies, Programs and Measures

Demand‐side energy efficiency policies and programs reduce utilization of EGUs and avoid

greenhouse gas emissions associated with electricity generation.  These electricity demand

reductions can be achieved through enabling policies that incentivize investment in demand‐

side energy efficiency improvements by overcoming market barriers that otherwise prevent

these investments, such as lack of information on energy efficient options, high transaction

costs, split‐incentives, lack of product availability, and perceptions of organizational risks.

Reducing electricity demand also enhances system efficiency by reducing the transmission and

distribution losses that occur across the grid between the sites of electricity generation and the

end use.  

Demand‐side energy efficiency is considered a central part of climate change mitigation in

states that currently have mandatory GHG targets, accounting for roughly 35 percent to 70

percent of expected reductions of state's power sector emissions.66 For example, California

expects to achieve reductions of 21.9 MMTCO2e in 2020 from energy efficiency programs

targeting electricity reductions. Taking into account expected reductions of 21.3 MMTCO2e

expected from California's RPS and 2.1 MMTCO2e from the million solar roofs program, energy

efficiency makes up 48 percent of power sector reductions based on California's Climate

                                                                                                                                                                                               

http://www.oregon.gov/energy/Siting/docs/Reports/CO2Standard.pdf 63 During the first year of operation new power plants test their equipment to ensure compliance with standards

for commercial equipment. Initial CO2 performance requirements can be validated during this test. 64 Oregon Department of Energy ‐ Oregon’s Carbon Dioxide Emission Standards For New Energy

Facilitieshttp://www.oregon.gov/energy/Siting/docs/Reports/CO2Standard.pdf 65 States’ §111(d) Implementation Group Input to EPA on Carbon Pollution Standards for Existing Power Plants 66 These reduction target ranges are based on a review of state GHG reduction laws in California, Connecticut,

Hawaii, Maine, Maryland, Massachusetts, Minnesota, New Jersey, Oregon, and Washington.

Comment [A4]: Any reduction in T&D losses

should be proportional to the demand reduction –

it’s not making the system more efficient; it’s just

minimizing demand.  
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Change Scoping Plan.67 Another state, Washington, expects to reduce 9.7 MMTCO2e from

energy efficiency measures in 2020. Taking into account expected reductions of 4.1 MMTCO2e

from Washington's RPS, energy efficiency makes up 70 percent of expected emission reductions

from stationary energy within the state.68

States have employed a variety of strategies to increase investment in demand‐side energy

efficiency technologies and practices, including (1) energy efficiency resource standards, (2)

demand‐side energy efficiency programs, (3) building energy codes, (4) appliance standards and

(5) tax credits.  Each of these strategies are described below.  

i. Energy Efficiency Resource Standards  

Description

Energy Efficiency Resource Standards (EERS) set multiyear targets for energy savings that

utilities or third‐party program administrators typically meet through customer energy

efficiency programs but also through other approaches, such as peak demand reductions,

building codes and combined heat and power (CHP). An EERS can apply to retail distributors of

either electricity or natural gas, or both, depending on the state.  To date, at least 29 states

have some type of EE requirement or goal.69   

Policy Mechanics

Design

EERS design and implementation details vary by state, and may be expressed as a percentage

reduction in annual retail electricity sales, as a percentage reduction in retail electricity sales

growth, or as a specific electricity savings amount over a long‐term period.  A typical EERS sets

multiyear targets for energy savings that drive investment in EE programs implemented by

utilities or third party administrators.  Over the compliance period, an EERS reduces electricity

demand by a target amount that utilities must meet.  As a result, an EERS indirectly affects

utility CO2 emissions by reducing the use of fossil‐fuel‐fired EGUs.

Authority

Most state EERS policies are established through legislation.  However, there are several

instances in which they have been established by PUC orders under broader statutory authority,

                                                            

67 CA Climate Change Scoping Plan http://www.arb.ca.gov/cc/scopingplan/document/adopted_scoping_plan.pdf 68 Growing Washington's Economy in a Carbon‐Constrained World:

https://fortress.wa.gov/ecy/publications/publications/0801025.pdf   69 State Energy Efficiency Resource Standards: Policy Design, Status, and Impacts, D.C. Steinberg, O. Zinaman, NREL

Technical Report NREL/TP‐6A20‐61023, April 2014.
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such as by setting quantitative targets consistent with the achievement of ‘all cost‐effective

energy efficiency.70   

Obligated Parties

Retail electricity suppliers, which are utilities that sell electricity to customers for end‐use

purposes, are the obligated parties under an EERS.

Measurement and Verification

PUCs generally oversee EERS.  Retail electricity suppliers comply with EERS requirements by

developing a portfolio of end‐use energy efficiency programs that encourage electric utility

customers to invest in more energy efficient technologies and practices as described below.  

PUCs typically rely on independent program evaluators to perform evaluation, measurement

and verification (EM&V) activities that estimate the incremental annual and cumulative energy

savings attributable to the programs.71  These estimates are typically the basis for compliance

reports submitted by retail electricity suppliers. For more information about measurement and

verification of energy efficiency policies or programs, see earlier in the State Plan

Considerations Technical Support Document.

                                                            

70 An important policy driver for EE programs in six states is a statutory requirement for utilities to acquire 

"all cost-effective energy efficiency". This policy typically requires utilities and other program 

administrators to pursue energy efficiency up to the point at which it is no longer cost effective, as defined 

by cost-benefit tests and procedures REQUIRED by state PUCs. States with all-cost effective energy 

efficiency policies include: CA, CT, MA, RI, VT, WA. For MA, this goals has translated into achieving 

annual electric energy savings equivalent to a 2.4% reduction in retail sales from energy efficiency 

programs in 2012. (Cite: http://emp.lbl.gov/sites/all/files/REPORT%20lbnl-3833e.pdf) 71 Evaluation, measurement, and verification (EM&V) refers to set of techniques and approaches used to estimate

the quantity of energy savings from an EE program or policy.  Since energy savings cannot be directly measured,

efficiency program impacts are estimated by taking the difference between: (a) actual energy consumption after

efficiency measures are installed, and (b) the energy consumption that would have occurred during the same

period had the efficiency measures not been installed (i.e., the baseline). 72 DSIREUSA, http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=PA14R&re=0&ee=0.  

State Direct Financial Penalties

Pennsylvania Failure to achieve the requisite reductions in electricity

consumption and peak demand during Phase 1 results in one‐time

fines from $1 million to $20 million. Failure to file a plan with the

public utilities commission is also punishable by a fine of $100,000

per day. Costs associated with any such fines may not be passed

on to ratepayers.72

Table 3: Examples of Penalties for Noncompliance

Comment [A5]: Some state EERS, for example

Ohio, allow transmission and distribution

infrastructure improvements to count towards their

EERS.

http://www.dsireusa.org/incentives/incentive.cfm?I

ncentive_Code=OH16R&re=0&ee=0  
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Penalties for

Noncompliance

If the obligated parties

do not demonstrate

compliance with the

EERS, they may face

financial penalties. The

existence and amount of

penalties varies across

the states.   Table 3

provides examples of financial penalties in three states, Pennsylvania, Ohio and Illinois.

Implementation Status

As of January 2014, more than 20 states had an active EERS in place, while at least four have EE

targets or goals that are voluntary, underfunded or uncertain at this time. In addition, two

states have renewable portfolio standard that allow the option for energy efficiency to meet

requirements.76  

                                                            

73 RECs represent the non‐energy attributes, including all the environmental attributes, of electricity generation

from renewable energy sources. RECs are typically issued in single MWh increments. See the section on Renewable

Portfolio Standards for more detail. 74 DSIREUSA http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=OH16R&re=0&ee=0 .

75 DSIREUSA http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=IL19R&re=0&ee=0. 76 State Energy Efficiency Resource Standards: Policy Design, Status, and Impacts, D.C. Steinberg, O. Zinaman, NREL

Technical Report NREL/TP‐6A20‐61023, April 2014.  

Ohio Failure to comply with energy efficiency or peak demand reduction

requirements results in the state public utilities commission

assessing a forfeiture upon the utility, to be credited to the

Advanced Energy Fund. The amount of the forfeiture is either: an

amount, per day per under‐compliance or non‐compliance, not

greater than $10,000 per violation; or an amount equal to the then

existing market value of one renewable energy credit (REC)73 per

megawatt hour of under‐compliance or noncompliance. 74

Illinois For both natural gas and electric utilities, failure to submit an

energy reduction plan will result in a fine of $100,000 per day until

the plan is filed. This penalty is deposited in the Energy Efficiency

Trust Fund and may not be recovered by rate payers. 75

Status of State EERS, as of January 2014
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Most states are meeting or on track to meet their incremental savings goals, which typically

range from an annual reduction in electricity of about 0.25 ‐ 2.5 percent. 77 In 2011, across the

50 states, incremental savings were equivalent to 0.62 percent of retail electricity sales.78 For

those states with EERS policies in place for more than two years, thirteen of twenty states are

achieving 100 percent or more of their goals, three states are achieving over 90 percent of their

goals, and only three states are realizing savings below 80 percent of their goals.79  

ii. Demand‐side Energy Efficiency Programs  

Description  

Demand‐side energy efficiency programs are programs designed to advance energy efficiency

improvements within a state or utility service area.  They are typically implemented to help

meet state policies, standards or objectives, such as energy efficiency resource standards (EERS),

‘all cost effective’ energy efficiency goals, integrated resource planning, and other demand‐side

management program and budget processes. As of January 2013, utilities in 48 states

implement demand‐side energy efficiency programs.80

Policy Mechanics

Design

Demand‐side energy efficiency programs include financial incentives to use energy efficient

products, make energy efficiency upgrades to residential and commercial buildings, and

technical assistance and information programs to address market and information barriers.  

                                                            

77 State Policy Table – Internal estimate drawing on multiple sources 78 2013 Scorecard 79 Sciortino, M., Nowak, S., White, P., York, D., Kushler, M. (2011). “Energy Efficiency Resource 

Standards: A Progress Report on Sate Experience.” American Council for an Energy Efficient Economy, 

Washington, DC.

80 2013 State Energy Efficiency Scorecard, ACEEE, November 2013. http://www.aceee.org/researchreport/e13k 

Comment [A6]: Recommend starting the

sentence with “As of 2011,”

Comment [A7]: Demand‐side energy efficiency

financial incentives are also used to improve

industrial facilities, not just residential and

commercial buildings.
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Funding for these programs typically comes from charges added to customer utility bills and

from revenues raised through emission allowance auctions, such as under RGGI. The RGGI

auction proceeds go to a variety of sources with the authority to run demand‐side energy

efficiency programs, including those also funded via independent trusts, DOE’s Weatherization

Assistance Program (WAP), and state‐run energy efficiency grant programs for municipalities.81

Funding may also come from “forward capacity markets” operated by regional electricity

operators. Forward capacity markets allow energy suppliers to bid against each other for the

amount of capacity they can supply into the electricity market in a future year. Demand‐side

management programs have been allowed to bid into these markets as an energy source,

demonstrating that energy efficiency programs can compete with more traditional forms of

electricity supply in meeting the needs of the power grid.  

Authority

Demand‐side programs that are a part of EERS programs and integrated resource planning are

established through legislation or PUC authority. Additional demand‐side management

program and budget processes also exist via utility planning, as well as state and local

government efforts to ensure all cost‐effective energy efficiency and other policy goals are met.  

Obligated Parties

Energy efficiency programs can be administered by investor‐owned, municipal or cooperative

utilities; third party administrators; or state and local government agencies.    

Measurement and Verification

PUCs generally oversee demand‐side energy efficiency programs.  Program administrators

typically rely on independent evaluators to perform evaluation, measurement and verification

(EM&V) activities that estimate the incremental annual and cumulative energy savings

attributable to the programs.  These estimates are typically the basis for annual performance

reports submitted by retail electricity suppliers or third party administrators to the PUCs. In the

case of state and local government agency run programs that are not overseen by the PUC,

energy savings are typically estimated to assure proper use of grants or other funds.  For more

information about the evaluation, measurement and verification of energy efficiency policies

and programs, see earlier in the State Plan Considerations Technical Support Document.

                                                            

81 RGGI - Regional Investment of RGGI CO2 Allowance Proceeds, 2012 

http://www.rggi.org/docs/Documents/2012-Investment-Report.pdf

Comment [A8]: This sentence mischaracterizes

forward capacity markets (FCM) as providing

funding for EE programs. Energy efficiency programs

can be bid into the FCM but the FCM does not

provide funding in the same way that ratepayers

fund efficiency programs.  

Comment [A9]: This paragraph incorrectly uses

IRP and utility planning as two different concepts.
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Penalties for Noncompliance

As discussed above, some states with an EERS levy direct fines for missing energy efficiency

targets or failure to submit an energy efficiency plan. For some programs under PUC oversight,

failure to reach certain performance levels may result in an inability to receive an incentive

payment or recover all incurred costs. Demand‐side programs funded by RGGI proceeds or

grants typically do not have penalties for noncompliance. However, state agencies play a role in

evaluating these programs and deciding whether funding should continue to flow to them.

Implementation Status

Well‐established state demand‐side energy efficiency programs have demonstrated their ability

to reduce electricity demand.82  For example, data reported to the U.S. Energy Information

Administration (EIA) show that in 2012 California avoided 35,482 GWh of electricity

consumption through its demand‐side efficiency programs, while Illinois avoided 3,084 GWh

and Maryland avoided 1,528 GWh, .

83 These reductions are equivalent to 13.7 percent, 2.1

percent, and 2.5 percent of total 2012 retail electricity sales in those states, respectively.84  

According to data and analyses from sources including Lawrence Berkeley National Lab (LBNL),

the U.S. Department of Energy’s Energy Information Administration, and the American Council

for an Energy Efficient Economy (ACEEE), as well as the EPA’s own analysis, ten leading states

have either achieved – or have established requirements that will lead them to achieve ‐ annual

incremental savings rates of at least 1.5 percent of the electricity consumption that would

otherwise have occurred.85

In 2011, state demand‐side energy efficiency programs are estimated to have reduced

CO2 emissions by 75 million metric tons, or 3.5 percent of national power sector emissions.8687

                                                            

82 LBNL The Future of Utility Customer‐Funded Energy Efficiency Programs in the United States

http://emp.lbl.gov/publications/future‐utility‐customer‐funded‐energy‐efficiency‐programs‐united‐states‐

projected‐spend 83 Energy Information Administration Form 861, 2012, available at http://www.eia.gov/electricity/data/eia861/ . 84 EIA: EIA Form 861: http://www.eia.gov/electricity/data/state/ 85 See the Greenhouse Gas Abatement Measures TSD for more information. 86 Innovation, Electricity, Efficiency (an Institute of the Edison Foundation), Summary of Customer‐Funded Electric

Efficiency Savings, Expenditures, and Budgets (2011‐2012) (March 2013), available at

http://www.edisonfoundation.net/iei/ourwork/Pages/issuebriefs.aspx.   87 2011 National GHG Inventory: http://www.epa.gov/climatechange/Downloads/ghgemissions/US‐GHG‐

Inventory‐2013‐ES.pdf

Comment [A10]: The preamble says 12 states

have achieved or have established requirements to

achieve savings of 1.5%.
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iii. Building codes

Description

Energy codes establish minimum efficiency requirements for new and renovated residential

and commercial buildings.  These measures are intended to eliminate inefficient technologies

with minimal impact on up‐front project costs.  This can reduce the need for energy generation

capacity and new infrastructure while reducing energy bills. Energy codes lock in future energy

savings during the building design and construction phase, rather than through a renovation.  

Policy Mechanics

Design

Codes specify “thermal resistance” improvements to the building shell and windows, minimum

air leakage, and minimum efficiency for heating and cooling equipment.

Mandatory building energy codes establish minimum efficiency requirements for residential

and commercial construction.  The International Energy Conservation Code (IECC) is the

prevailing model code for the residential sector.  ASHRAE 90.1‐2010 is the model commercial

code.   

By locking in efficiency measures at the time of construction, codes are intended to capture

energy savings that are more cost‐effective than retrofit opportunities available after a building

has been constructed.  Energy code requirements are also intended to overcome market

barriers to efficient construction in both the commercial and residential sectors, such as the

complexity of advanced codes, lack of local‐level implementation resources, and a shortage of

empirical data on the costs and benefits of codes.   

Authority

Model building codes are typically developed at the national or international level, adopted at

the state and/or local level, and implemented and enforced locally.

Obligated Parties

Local parties, such as developers and property owners requiring building permits, are the most

common obligated parties.

Comment [A11]: This section should be titled

Building Energy Codes, not just “building codes”.

Similarly, the first paragraph should begin with

“Building energy codes establish...”
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Measurement and Verification

Program implementation steps, including builder training, compliance assurance, and

enforcement, are typically the responsibility of state and local governments. These steps,

however, are often not fully or uniformly implemented for numerous reasons, including an

emphasis on health and safety issues over the proper functioning of mechanical equipment, a

lack of trained staff to review building plans and conduct onsite inspections, and limited

funding to carry out key implementation activities. As a result, most jurisdictions do not have

the capacity to analyze code compliance and to identify the measures and strategies that

should be targeted for improved implementation. For more information about measurement

and verification of energy efficiency, see earlier in the State Plan Considerations Technical

Support Document.

Penalties for Noncompliance

In order to get building permits approved, the relevant developer or property owners must

show they are in compliance with standards. Since permitting is done at the local level, the use

of penalties and the ability to enforce standards vary significantly by region. DOE has been

working with states and localities to improve compliance practice

Implementation Status

To date, 28 states have adopted IECC 2009 while four states have gone further by adopting the IECC

2012.  In the commercial sector, 33 states have adopted ASHRAE 90.1‐2007 and five states have

adopted ASHRAE 90.1‐2010.   Currently, 11 states have outdated or no state‐wide residential energy

code, and 9 states have outdated or no state‐wide energy codes for commercial construction.88 The

State of Oregon, which has adopted residential and commercial codes based on the IECC 2009,

estimated total savings in 2009 from building energy codes of 1.17 GWh and 2.3 GWh in the residential

and commercial sectors, respectively.89 This was equivalent to more than 7 percent of total retail

electricity sales in Oregon in 2009.90

                                                            

88 Online Code Environment & Advocacy Network http://energycodesocean.org/code‐status 89 2011‐2013 State of Oregon Energy Plan, Oregon Department of Energy,

http://www.oregon.gov/energy/docs/reports/legislature/2011/energy_plan_2011‐13.pdf 90 EIA, State Electricity Profiles. http://www.eia.gov/electricity/state/oregon/  
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iv. A

pplian

ce and

equip

ment

efficie

ncy

standa

rds

Descrip

tion

State

applian

ce

standa

rds
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establish minimum energy‐efficiency levels for those appliances and other energy‐consuming

products that are not already covered by the federal government. These standards typically

prohibit the sale of less efficient models within a state. States are finding that appliance

standards offer a cost‐effective strategy for improving energy efficiency and lowering energy

costs for businesses and consumers, though these standards are superseded when Federal

standards are enacted for new product categories,.

While state appliance standards can be useful in testing and exploring the effectiveness of

standards for new products, states cannot preempt or supersede existing Federal standards.

States may apply to DOE for a waiver to implement more stringent standards.  This is

sometimes granted if a certain period of time has passed since the federal standard has been

updated.

Policy Mechanics

Design

When states implement appliance and equipment standards, they are establishing a minimum

efficiency for products, such as refrigerators or air conditioners, thereby reducing the energy

associated with using the product. Standards prohibit the production and sale of products less

efficient than the minimum requirements, encouraging manufacturers to focus on how to

incorporate energy‐efficient technologies into their products at the least cost and hastening the

development of innovations that bring improved performance.

Authority

State energy offices, which typically administer the federal state energy program funds, have

generally acted as the administrative lead for standards implementation. In contrast, inspection

and enforcement of appliance standards regulations has typically involved self‐policing.

Industry competition is such that competitive manufacturers usually report violations.

Obligated Parties

Manufacturers of products being sold in a given state are typically obligated to ensure their

appliances meet the appropriate energy efficiency standards.

Measurement and Verification

Evaluating the benefits and costs of the standards is important during the standards‐setting

process. Once enacted, however, little field evaluation is performed. For more information

about measurement and verification of energy efficiency, see earlier in the State Plan

Considerations Technical Support Document.
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Penalties for Noncompliance

Appliances and equipment found in violation of the minimum energy performance standards

are not allowed to be sold or manufactured in the state.

Implementation Status

Currently, fifteen states and the District of Columbia have enacted appliance efficiency

standards. However, most of these standards have been superseded by federal standards. Still,

nine states (AZ, CA, CT, MD, NV, NY, OR, RI, WA) and the District of Columbia have either

enacted standards for equipment not covered federally or obtained waivers to enact tougher

appliance standards where the federal regulations have become outdated. California currently

leads all states in active state standards, covering 13 products, including consumer audio and

video products, pool pumps and hot tubs, vending machines, televisions, battery chargers, and

various lighting applications.91

v. Incentives and Finance Mechanisms for Energy Efficiency  

Description

States offer a diverse portfolio of financing and incentive approaches that are designed to

address specific financing challenges and barriers and help specific markets and customer

groups invest in energy efficiency. These programs include revolving loan funds, energy

performance contracting, tax incentives, rebates, grants, and other incentives.   

Policy Mechanics  

Design

Revolving loan funds provide low‐interest loans for energy efficiency improvements.  The funds

are designed to be self‐supporting. States create a pool of capital that “revolves” over a multi‐

year period, as payments from borrowers are returned to the capital pool and are subsequently

lent to other borrowers. Revolving loan funds can be created from several sources, including

public benefits funds (PBFs),92 utility program funds, general state revenues, or federal funding

sources. Revolving funds can grow in size over time, depending on repayment interest rates and

program administrative costs.  

                                                            

91 DSIREUSA, http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=CA48R&re=0&ee=0 . 92 Public benefit funds (PBFs) are dedicated funds used for supporting research and development of energy

efficiency and renewable energy projects. Funds are normally collected either through a small charge for every

electric customer or through specified contributions from utilities.  

Comment [A12]: Suggest “encourage” or

“incentivize”. instead
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Energy performance contracting allows the public sector to contract with private energy service

companies (ESCOs) to provide building owners with energy‐related efficiency improvements

that are guaranteed to save more than they cost over the course of the contracting period.

ESCOs provide energy auditing, engineering design, general contracting, and installation

services, and help arrange project financing.93 The contracts are privately funded and do not

involve state funding or financial incentives.

State tax incentives for energy efficiency are available as personal or corporate income tax

credits, tax exemptions (e.g., sales tax exemptions on energy‐efficient appliances), and tax

deductions (e.g., for construction programs). Tax incentives aim to spur private sector

innovation to develop more energy efficient technologies and practices and increase consumer

choice of energy‐efficient products.94  

Rebates (also known as “buy‐downs”) are used to promote demand‐side energy efficiency

reductions by providing direct incentives to customers who purchase or make upgrades to

approved efficient appliances or retrofit their homes (e.g., a utility may refund part of the cost

for a homeowner to improve attic insulation or purchase a high‐efficiency furnace). Funding for

rebates may come from PBFs, direct grants, or utility generation incentives.  

Grants from the federal government, state government, regional agency, or private source may

be used to start or finance energy efficiency programs. A grant may be used to provide funding

for a specific construction project (e.g., retrofit of a school), finance a rebate program, initiate a

revolving fund, conduct a behavior change campaign (e.g., educate public about the benefits of

off‐peak energy use), or any other type of program that meets the specific grant requirements.  

Authority

Financial mechanisms and incentives for energy efficiency are run by utilities and state and local

governments. Utilities primarily offer rebates, grants, and loans. Personal, corporate, sales, and

property tax incentives are mainly offered by state and local governments.95  

Implementation Status

Financial mechanisms and incentives for energy efficiency exist in all 50 states, with the most

prevalent financial mechanisms and incentives for energy efficiency are rebates and loan

programs. There are 43 tax incentives and over one‐thousand rebate, grant, and loan

                                                            

93 EPA. 2004. Integrating State and Local Environmental and Energy Goals: Energy Performance Contracting. Fact

Sheet. EPA. September. 94 Brown, E., P. Quinlan, H.M. Sachs, and D. Williams. 2002. Tax Credits for Energy Efficiency and Green Buildings:

Opportunities for State Action. Report #E021. ACEEE. March. 95 http://www.dsireusa.org/summarytables/finee.cfm  

Comment [A13]: Recommend changing

“generation incentive” to “program funds” for

consistency with the rest of the document.
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programs.96 In the first 3 years of Alaska’s Home Energy Rebate Program, the State provided an

estimated $110 million to help finance energy efficiency retrofits for 16,500 homeowners.

Retrofitted housed are currently saving an estimated 1.6 trillion BTUs of energy annually, or 5

percent of the Alaska’s total annual energy demand for residential space heating.97

c. Renewable Energy Policies and Programs

States have adopted a range of requirements and programs to advance the deployment of

renewable energy technologies, including renewable portfolio standards, performance‐based

incentives and public benefit funds.98 These renewable energy policies and programs reduce

GHG emissions by increasing the use of renewable energy and altering the mix of energy supply.

i. Renewable Portfolio Standards

Description

                                                            

96 http://www.dsireusa.org/summarytables/finee.cfm   97 Cold Climate Housing Research Center, http://cchrc.org/docs/snapshots/HERP_snapshot.pdf 98 Feed‐in tariffs offer long‐term purchase agreements to renewable energy electricity generators. Public benefit

funds are typically created by levying a small fee as a part of retail electricity rates and are used to support rebate,

loan, and other programs that support renewable energy deployment. For more information, see Database of

State Incentives for Renewables and Efficiency, available at http://www.dsireusa.org/.

Comment [A14]: 

Recommend changing the opening sentence for this

footnote to “Feed‐in tariffs, a performance‐based

incentive, offer...”  This footnote is before the

reader is told that feed‐in tariffs are a performance‐

based incentive.  
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Renewable Portfolio Standards

Mandatory -

Voluntary -

29

9

Last updated 8/8/2013

A renewable portfolio standard (RPS), also known as a renewable electricity standard (RES), is a

mandatory requirement for retail electricity suppliers to supply a minimum percentage or

amount of their retail electricity load with electricity generated from eligible sources of

renewable energy.  An RPS indirectly affects EGU CO2 emissions by reducing the utilization of

fossil‐fuel‐fired EGUs. As of June 2013, 29 states and Washington, DC have adopted a

mandatory RPS, although designs vary (e.g., applicability, targets and timetables, geographic

and resource eligibility, alternative compliance payments) and an additional nine have

voluntary renewable goals.99

Policy Mechanics

Design  

RPS requirements typically start at modest levels and ramp up over a period of several years.

An RPS relies on market mechanisms to increase electricity generation from eligible sources of

                                                            

99 Ibid.
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renewable energy.  

Retail electricity suppliers can comply with RPS requirements through several mechanisms,

which vary by state, including:

 Ownership of a qualifying renewable energy facility and its electric generation output,  

 Purchasing electricity bundled with renewable energy certificates (RECs)100 from a

qualifying renewable energy facility, and  

 Purchasing RECs separately from electricity generators.  Unlike bundled renewable

energy, which is dependent on physical delivery via the power grid, renewable energy

certificates (RECs) can be traded between any two parties, regardless of their location.

However, state RPS rules typically condition the use of RECs based on either location of

the associated generation facility or whether it sells power into the state or to the

regional grid.

Authority

Most state RPS are established through legislation and administered by state PUCs.  

Obligated Parties

RPS applicability varies by state. All state RPS apply to investor‐owned utilities, while some

state RPS obligate municipal utilities, rural cooperatives, and/or other retail providers, often

depending on a minimum number of customers served.   

Measurement and Verification

Some state RPS include an alternative compliance payment (ACP) option, where a retail

electricity supplier may purchase compliance credits from the state at a known price, which

acts as a de facto price cap, if it has not procured sufficient electricity from renewable energy

sources or RECs to meet the RPS compliance requirement.  State PUCs typically require annual

compliance reports from retail electricity suppliers subject to a RPS. Most states use regional

tracking systems (e.g., Western Renewable Energy Generation Information System, PJM

Generation Attribute Tracking System) to issue, track, and retire RECs for RPS compliance

                                                            

100 RECs represent the non‐energy attributes, including all the environmental attributes, of electricity generation

from renewable energy sources. RECs are typically issued in single MWh increments.  
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purposes.101  For more information about measurement and verification of renewable energy,

see earlier in the State Plan Considerations Technical Support Document.

Penalties for Noncompliance

States have developed a range of compliance enforcement and flexibility mechanisms. As of

2007, despite the fact that several states had not achieved the RPS targets, only Connecticut

and Texas had levied fines. A $5.6 million penalty was incurred in Connecticut in 2006. In 2003

and 2005, two competitive electricity service providers in Texas were penalized a total of

$4,000 and $28,000 respectively. Flexible enforcement and opportunities to “make‐up”

shortfalls in subsequent years or ACPs that are recycled to support other renewable and

efficiency measures have helped other states avoid penalties for noncompliance.102      

Implementation Status

States with RPS policies have demonstrated higher levels of renewable energy capacity

development. From 1998‐2012, 67 percent (46 GW) of all non‐hydro renewable capacity

additions occurred in states with active or impending RPS requirements, although other factors

may contribute to the growth in renewable capacity.103

ii. Performance‐Based Incentives and Finance Mechanisms For Renewable

Energy  

Description

States offer a diverse portfolio of financing and performance based incentive approaches that

are designed to address specific financial challenges and barriers and help specific markets and

customer groups produce clean energy.  

                                                            

101 For a summary of REC tracking systems, see Federal Energy Regulatory Commission, “Renewable Power &

Energy Efficiency Market: Renewable Certificate Tracking” (September 2010); available at

http://www.ferc.gov/market‐oversight/othr‐mkts/renew/othr‐rnw‐rec‐trk.pdf. 102 Ryan Wiser and Galen Barbose, Renewables Portfolio Standards in the United States – A Status Report with Data

Through 2007 (April 2008). http://emp.lbl.gov/sites/all/files/REPORT%20lbnl‐154e‐revised.pdf 103 Barbose, Galen. (2013). Renewables Portfolio Standards in the United States: A Status Update. Lawrence

Berkeley National Laboratory.

http://www.renewableenergymarkets.com/docs/presentations/2013/REM_Sept2013_Barbose.pdf
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Policy Mechanics

Design

States support the advancement of clean generation technologies through performance‐based

incentives, including feed‐in tariffs and other payments, or tax incentives.  Performance‐based

incentives are paid based on the actual energy production of a system. Feed‐in tariffs establish

temporarily elevated price per kWh in order to encourage renewable energy innovation using

high cost technologies. Tax incentives are used to lower financial barriers to renewable energy

production.  

A major source of funding for renewable energy activities comes from PBFs, but states also

fund these activities through alternative sources including direct grants, rebates and generation

incentives provided by utilities.  

State tax incentives for renewable energy and Combined Heat and Power (CHP) take the form

of personal or corporate income tax credits and tax exemptions. State tax incentives for

renewable energy are a common policy tool, mainly using credits on personal or corporate

income tax and exemptions from sales tax, excise tax, and property tax.  

Authority

Financial mechanisms and incentives for renewables are run by utilities, non‐profits, and state

and local government. Personal, corporate, sales, and property tax incentives are mainly

offered by state and local government.104  

Implementation Status

Financial mechanisms and incentives for renewable energy of some form exist in most states.

According to the Database of State Incentives for Renewable Energy (DSIRE), there are over 200

tax incentives. In addition, nearly a hundred performance based incentives are offered from

state and local governments, as well as utilities and non‐profits.105  

There are currently 18 states that have state‐wide performance‐based policies, and in several

other states utilities have adopted programs based on performance‐based incentives, including

feed‐in tariffs, standard offer payments, and payments in exchange for RECs.106 In many cases,

however, PBI is limited to customer‐sited projects or limited by size eligibility.

                                                            

104 http://www.dsireusa.org/summarytables/finre.cfm 105 http://www.dsireusa.org/summarytables/finre.cfm    106 http://www.dsireusa.org/summarytables/finre.cfm.
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Financial incentives, working in concert with a strong RPS and net metering policies, have

contributed to the rapid growth in solar power deployment in New Jersey. The state’s RPS

includes a minimum carve‐out for solar sources, and allows solar energy generators to earn

Solar Renewable Energy Certificates (SRECs) that can then be sold to electricity suppliers trying

to meet the minimum solar production and/or purchase requirement. As a result of these

interdependent policies, solar photovoltaic facilities are increasing, with installations more than

doubling from 2010 through 2011.107 New Jersey ranks second only to California in terms of

total installed capacity.108  

d. Utility Planning Approaches and Requirements

Description

Some public utility commissions require utilities to conduct portfolio management or

integrated resource planning to provide least cost and stable electric service to customers over

the long term.  Portfolio management refers to energy resource planning that incorporates a

variety of energy resources, including supply‐side (e.g., traditional and renewable energy

sources) and demand‐side (e.g., energy efficiency) options. The term "portfolio management"

typically describes resource planning and procurement in states that have restructured their

electric industry. However, it can also include the more traditional integrated resource planning

(IRP) approaches applied to vertically integrated utilities.   

In addition to energy resource planning, two states have policies or requirements for utilities to

specifically factor pollution reduction requirements into their planning.  In Colorado, the Clean

Air Clean Jobs Act (CACJA), signed into law on April 19, 2010, required utilities to submit a plan

to the PUC showing how they would meet EPA standards for a variety of pollutants. The law

was passed because the state was out of compliance with the national Ambient Air Quality

Standard for Ozone, and the EPA threatened to propose more stringent standards for the state.  

In 2001, Minnesota enacted Minnesota Statute 216B.1692, which encourages utilities to make

voluntary emission reductions and provides them with a mechanism to recover the costs

through customer rate increases outside of the normal rate review cycle.109  

                                                            

107 Solar New Jersey, http://www.solar‐new‐jersey.org/2012/08/15/why‐has‐new‐jersey‐become‐a‐leader‐in‐solar‐

in‐the‐us/   108 NREL Open PV Project, https://openpv.nrel.gov/rankings 109 Minnesota PUC ‐ Report To The Legislature On Emissions Reduction Projects Under Minnesota Statutes

216B.1692 http://www.puc.state.mn.us/portal/groups/public/documents/pdf_files/000661.pdf

Comment [A15]: This section (section d)

confuses portfolio management with IRP.

Recommend EPA review the SEE Action Using

Integrated Resource Planning to Encourage

Investment in Cost‐Effective Energy Efficiency

Measures Guide

[http://www1.eere.energy.gov/seeaction/pdfs/rate

payer_efficiency_irpportfoliomanagement.pdf].

Comment [A16]: This sentence equates

portfolio management with resource planning for all

energy resources. Portfolio management is used

generally for default service only, so it is not the

same thing as IRP. This should be clarified. For

example, this sentence could read: “The term

‘portfolio management’ typically describes resource

planning and procurement in states that have

restructured their electric industry and applies to

default services.”

Comment [A17]: Commenters recommend

changing this sentence to “Related is integrated

resource planning (IRP) which is generally used by

vertically‐integrated utilities and is a long‐range

utility plan for meeting the forecasted demand for

energy within a defined geographic area through a

combination of supply side resources and demand

side resources.” (SEE Action IRP Guide)

They also recommend adding a sentence that

describes the goal of IRP. For example: “Generally

speaking, the goal of an IRP is to identify the mix of

resources that will minimize future energy system

costs while ensuring safe and reliable operation of

the system.” (SEE Action IRP Guide)
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Policy Mechanics

Design

 Portfolio Management ‐ Portfolio management involves deliberately choosing among a

variety of electricity products and contracts. The approach emphasizes diversity—fuels,

technologies, and power supply contract durations. In its fullest form, energy efficiency

and renewable generation are key strategic components. Portfolio management

typically involves a multi‐step process of forecasting, resource identification, scenario

analysis, and resource procurement. Several states as well as vertically integrated

utilities use IRP, a specialized form of portfolio management. Since these utilities own

their own generation assets, they use their IRPs to weigh the benefits of building their

own generation plants against procuring energy from other entities. The plans also

evaluate how best to balance peak versus off‐peak electric load requirements. In

addition, they compare various supply‐ and demand‐side options and contract and

financial hedging options. Companies achieve these goals simultaneously by analyzing

different scenarios. The IRPs detail fuel and electricity price information, customer

demand forecasts, existing plant performance, other plant additions in the region, and

legislative decisions. The following examples show how various states have designed

their programs:

o Montana is a deregulated state that has established least cost planning rules and

policy guidelines for default electricity suppliers. These rules and guidelines

target long‐term electricity supply and require utilities to submit electric supply

resource plans every two years with the aim of providing a balanced,

environmentally responsible electricity portfolio. These plans must include

supply‐side and demand‐side resources, and they must address the need to

supply power in a way that minimizes the environmental cost by estimating the

cost to the environment of alternatives. In addition, utilities must account for the

costs of complying with existing and future environmental regulations. When

considering various resource options, Montana requires a competitive

solicitation process, allowing resource operators and developers to submit their

proposals to the default electricity supplier for consideration. Montana also

requires the portfolio management plans to be subject to an advisory committee

review and a public review.110

                                                            

110 EPA – Clean Energy Guide to Action: http://epa.gov/statelocalclimate/resources/action‐guide.html

Comment [A18]: This bullet should also include

IRP.

Comment [A19]: This set of sentences isn’t

necessary and isn’t entirely accurate as written,

since IRP and PM are not the same thing. Also,

deciding between building generation or buying

from others isn’t the primary focus of IRP. Rather,

the purpose is to analyze resource options over a

20‐30 yr timeframe, including supply and demand

side resources. This paragraph should be adjusted

or deleted, since it is not essential.

Comment [A20]: Is this the most current

information on Montana?  See the Synapse report  

[http://www.cleanskies.org/wp‐

content/uploads/2011/05/ACSF_IRP‐

Survey_Final_2011‐04‐28.pdf]  

for more nuances on how Montana IRP is

accomplished, including that Montana is unique in

that it has separate rules for vertically‐integrated

utilities and restructured utilities. For vertically‐

integrated utilities, the focus is on “long‐term”

planning, which some consider to mean 20‐25 years.

For restructured utilities, the planning horizon is

“the longer of: 1) the longest remaining contract

term in a utility’s supply resource portfolio; 2) the

period of the longest lived electricity supply

resource being considered for acquisition; or 3) ten

years.”  
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o Oregon electric utilities, submit IRPs every two years, covering a 20 year

timeframe. The goal of these plans is to consider the acquisition of resources at

least cost while keeping the public interest in mind. Potential risk factors must be

considered, including price volatility, weather, the cost of meeting existing and

future federal environmental regulations. Quantifiable environmental

externalities are included, as are less quantifiable developments such as changes

in market structure and the establishment of a renewable portfolio standard. As

for energy efficiency requirements during the planning process, Oregon

determines these on a utility by utility basis. 111

 Multi‐Pollutant Utility Planning – Two states, Minnesota and Colorado, have worked

collaboratively with their investor‐owned utilities to develop multi‐pollutant emission

reduction plans on a utility‐wide basis. This multi‐pollutant, collaborative approach

enables utilities to determine the least cost way to meet long term and comprehensive

energy and environmental goals.

o The Colorado CACJA required investor‐owned utilities (IOUs) with coal plants to

submit a multi‐pollutant plan to the PUC to meet the EPA standards for NOx, SO2,

particulates, mercury, and CO2. Utilities were not required to adopt a specific

plan set by the state, but had to meet with Colorado Department of Public

Health and Environment (CDPHE) and PUC approval. Xcel Energy’s plan was

submitted and approved in 2010.112

o The Minnesota Emission Reductions Rider allows utilities to submit plans for

projects that reduce emissions and go beyond federal requirements outside of a

general rate case.  It allows them to recover the costs of those actions as an

incentive.113  The specific design and process of the projects vary by utility, but

typically involve installing additional pollution control equipment at coal‐fired

power plants, or repowering them with natural gas.  

Authority

State utility commissioners oversee utilities’ and default service providers’ procurement

practices in their states. Typically, the commissions solicit comments and input as they develop

portfolio management practices from a wide variety of stakeholders. The utility regulator may

                                                            

111 EPA – Clean Energy Guide to Action: http://epa.gov/statelocalclimate/resources/action‐guide.html 112 The Regulatory Assistance Project (RAP). (2013). “Addressing the Effects of Environmental Regulations: Market

Factors, Integrated Analyses, and Administrative Processes.” The Regulatory Assistance Project, Montpelier, VT.   113 Minn. Stat.§216B.1692 (2013)
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also play a role in reviewing and approving utilities’ planning procedures, selection criteria,

and/or their competition solicitation processes.

Obligated Parties

Vertically integrated utilities are obligated under integrated resource planning, while in

restructured markets, the default utility service provider is obligated to conduct portfolio

management.

For multi‐pollutant planning, Colorado IOUs, Xcel Energy and Black Hills Energy, were required

to file plans with the Department of Public Health and Environment and the PUC in order to be

compliant with the CACJA. Plans needed to meet the National Ambient Air Quality Standards

for a number of air pollutants.

As the Minnesota multi‐pollutant legislation is voluntary for state utilities, there is neither

compliance nor reporting requirements.

Measurement and Verification

Regulatory oversight aims to ensure utilities are following through with their plans. Regulators

sometimes require utilities to submit portfolio management plans and progress reports at

regular intervals. These plans and reports describe in detail the assumptions used, the

opportunities assessed, and the decisions made when developing resource portfolios.

Regulators then carefully review these plans and either approve them or reject them and

recommend changes needed for approval. California, for example, requires utilities to submit

biennial IRPs and quarterly reports on their plans.

Penalties for Noncompliance

There are no penalties for noncompliance, however there is usually significant interaction with

the regulator during the planning and implementation process as is described above.  

Implementation Status

Currently more than half of the states have integrated resource or other long‐term planning

requirements, 114 while Minnesota and Colorado have multi‐pollutant planning policies or

requirements.

                                                            

114 Wilson, Rachel and  Bruce Biewald, Best Practices in Electric Utility Integrated Resource Planning Examples of

State Regulations and Recent Utility Plans, June 2013, www.raponline.org.

Comment [A21]: Recommend changing this to

read “Vertically integrated utilities are often

obligated to conduct resource planning, while in

restructured markets the default utility service

provider may be obligated to conduct portfolio

management for default service.”

Comment [A22]: Recommend changing to

“Regulators often require utilities to submit

resource plans and progress reports at regular

intervals.”
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In Montana, for example, the 2011 Electric Supply Resource Plan for NorthWestern Energy calls

for:

 Shortening the length of power supply contracts from seven years to a more

competitive, staged process of between three to five years.

 Diversifying Montana’s resource mix with the recent addition of a 150MW gas‐fired

power plant.

 Improving the integration of intermittent power sources into the power supply as new

wind turbines play a larger role in the state’s resource mix.

 Meet state RPS requirements.

 Acquire cost‐effective demand side management resources, targeting 6MW of

additional energy conservation per year.

 Monitor market, regulatory, and technology changes to better manage risks and

opportunities.115

                                                            

115 Northwestern Energy Electric Supply Resource Plan: https://www.northwesternenergy.com/our‐

company/tariffs‐and‐rates/montana‐tariffs‐and‐rates/electric‐supply‐resource‐procurement‐plan  
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In Oregon, PacifiCorp has filed its 2013 integrated resource plan. Key highlights from the report

include:

 Demand–side energy efficiency efforts are expected to meet 67 percent of electricity

load growth from 2013 to 2022

 Market analyses for integrating Wind resources into the grid, and pursuing

opportunities for combined heat and power resources.

 Goals to obtain 1,425 – 1,876 GWh of energy efficiency resources by 2015 and 2,034 –

3,180 GWh by 2017.

 Permitting and development efforts to convert a unit of the Naughton power plant from

coal to gas.116

To meet Colorado’s multi‐pollutant planning requirement, Xcel Energy submitted a plan that

was approved by the Colorado PUC on December 9, 2010. Implementation of the plan will

reduce NOx levels 88% and CO2 levels 28% relative to 2008 levels by 2018. 117   Black Hills Energy

has also filed its electric resource plan (ERP). This plan includes the retirement of a coal‐fired

power plant and two older natural gas‐fired gas units, as well as a proposal to build a 40 MW

natural gas turbine. It plans to add 100 MW of capacity by 2017, Black Hills Energy will use

competitive bidding to meet the remaining 60 MW.118

In Minnesota, projects currently implemented under the multi pollutant legislation include the

Minnesota Power’s Arrowhead Regional Emissions Abatement (AREA) Project, Minnesota

Power’s Boswell 3 Emissions Reduction Plan, Xcel Energy’s Mercury Reduction Plan, and Xcel

Energy’s Metropolitan Reduction Proposal (MERP). MERP, authorized in 2002, has shown a 93%

reduction in SO2, 91% reduction in NOx, 81% reduction in mercury, 55% reduction in

particulates, and 21% reduction in CO2 from 2007‐2009.119

                                                            

116 PacifiCorp 2013 Integrated Resource Plan:

http://www.pacificorp.com/content/dam/pacificorp/doc/Energy_Sources/Integrated_Resource_Plan/2013IRP/Pac

ifiCorp‐2013IRP_Vol1‐Main_4‐30‐13.pdf 117 Public Service Company of Colorado, an Xcel Energy Company , Xcel Energy‐Emissions Reduction Plan, 11‐06‐

325_6E_FS, 2011. https://www.xcelenergy.com/staticfiles/xe/Corporate/Environment/10‐12‐303_CACJ‐6E_FS.pdf   118 Black Hill Energy files plan for ongoing reliable, cost‐effective energy for years to come in Colorado:

http://www.blackhillsenergy.com/node/34671#.UzHkuIXYhIt   119 Update/add citation
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Technical Support Document (TSD) for 

Carbon Pollution Guidelines for Existing Power Plants: 

Emission Guidelines for Greenhouse Gas Emissions from Existing Stationary Sources: Electric 

Utility Generating Units 

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

Projecting EGU CO2 Emission Performance in State Plans 

U.S. Environmental Protection Agency 

Office of Air and Radiation 

June 2014 

 
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Table of Contents 

I. Introduction ........................................................................................................................3 

II. Analytic Approaches for Projecting CO2 Emissions from Affected EGUs ..................5 

A. Electricity System Modeling Approaches for Projecting EGU CO2 Emissions .......5 

B. Growth Tools for Projecting Future EGU Utilization and CO2 Emissions...............9 

III. Translating from a Rate-Based Emission Performance Goal to a Mass-Based 

Emission Performance Goal ............................................................................................11 

A. Concept ...................................................................................................................11 

B. Projection Scenarios ................................................................................................13 

IV. Projecting CO2 Emission Performance under a State Plan .........................................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 ........................40 

 
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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 CO2 emission performance by affected EGUs that will be achieved under a state 

plan (inclusive of plan measures that avoid CO2 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 CO2 emission rate achieved by affected EGUs or total 

CO2 emissions from affected EGUs. 

The EPA is also proposing that a state may translate the state rate-based CO2 emission 

performance goal for affected EGUs to an equivalent mass-based CO2 emission performance 

goal. If this translation option is used, a state plan must also include a projection used to derive 

the mass-based CO2 emission performance goal. This translation will involve a projection of CO2

emissions from affected EGUs during the plan period, under a scenario that assumes the ratebased 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 that the emission performance required by CAA 

section 111(d) is properly defined in state plans 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 performance projections in state plans. Therefore, the 

use of appropriate methods, tools, and assumptions for such projections is critical. 

The preamble, at section VIII.F.7, seeks comment on options presented for how CO2

emission projections might be conducted in an approvable state plan, and how different types of 

state plan approaches are represented in these projections. These options include the use of 

historical data and parameters for estimating the 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 

                                                            

1

 In many cases, this approach will also require the development of parameters for estimating the effect of individual 

state programs and measures, for use as input assumptions for modeling. 
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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 should provide technical resources for conducting 

projections. 

This technical support document (TSD) elaborates these options and considerations. The 

TSD discusses possible analytic approaches for translating from a rate-based CO2 emission 

performance goal to a mass-based goal, and projecting the CO2 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 dispatch planning models, dispatch simulation 

models, and growth tools that base projections on historical data and algorithms. The TSD also 

discusses possible approaches for developing inputs 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 CO2 emissions from affected 

EGUs 

 Section III discusses the concept and practice of translating from a rate-based CO2

emission performance goal to a mass-based CO2 emission performance goal 

 Section IV discusses the concept and practice of projecting EGU CO2 emission 

performance under a state plan 

 Section V discusses applied considerations for projecting EGU CO2 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 CO2 emission projections, for 

different types of state plans 

 Section VI discusses process considerations for conducting EGU CO2 emission 

projections for state plans, including: 

o Regional coordination among states in conducting projections 
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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 CO2 emission performance 

goals to mass-based goals 

II. Analytic Approaches for Projecting CO2 Emissions from Affected EGUs 

This section surveys different types of methods and tools for projecting CO2 emissions 

from affected EGUs, including modeling tools and other tools that base projections on historical 

data and use algorithms to extrapolate future CO2 emissions performance based on past 

performance. 

A. Electricity System Modeling Approaches for Projecting EGU CO2 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 power sector (i.e., projections of the expected 

response of the sector to factors such as electricity 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 dispatch, fuel consumption, fuel prices, wholesale 

electricity prices, emissions, EGU retirements, and infrastructure 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 demand 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 characteristics, such as location, size, efficiency, operating 

                                                            

2

 A “balancing area” or “control area” refers to a specified portion of the transmission system where electricity 

demand and generation are balanced in real time by a system administrator to maintain grid reliability. 
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costs, pollution retrofit control status, age, and fuel 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, maintaining reliability criteria, 

and following other constraints, such as minimum 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 planning 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 generating facility and retirement or retrofit decisions 

for existing capacity within a specific utility’s territory. Utility planning models 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 review 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 CO2 emission 

reduction strategies or CO2 emission constraints, as IRP scenarios may include greater 

penetration of end-use energy efficiency or renewable energy, proxy CO2 emission prices, 

emission trading, and limits on CO2 mass emissions. 

                                                            

3

 See, for example: The Duke Energy Carolinas IRP (Annual Report), September 2012, available 

athttp://www.energy.sc.gov/files/view/Duke_IRP 2012.pdf; PacifiCorp 2013 IRP (Vol 1), April 2013, available 

athttp://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/Public/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_LG%26E-KU_IRP_Volume%20I.pdf; Great 

River Energy IRP, November 2012, available at 

http://www.greatriverenergy.com/makingelectricity/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 represent individual EGUs, where each EGU has specific 

operational characteristics. 

Due to the additional spatial and temporal resolution 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 simulation models are typically driven by near-term economics, 

system restrictions and market constraints, including 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 system 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 basis. 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 conjunction 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 simulation 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). 
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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 models (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 characterize thermal constraints between zones, which 

typically represent control areas or balancing authorities. 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, where transmission constraints between individual 

EGUs and load are modeled as well.8

 Dispatch simulation models 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) defines security constrained economic dispatch as “the level 

at which each available resource should be operated, given actual 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 constraints on transmission availability and ancillary services. 

See FERC, “Security Constrained Economic Dispatch: Definition, 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 “zonal” 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).
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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 affected multiple economic 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 changes 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 key 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 capacity 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 sector-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 representation of the electricity sector in 

multi-sector models may limit their use to providing input data for more specific analysis in an 

electricity sector model, and to better understand variations in electricity load that may result 

from changes outside the electricity sector. 

B. Growth Tools for Projecting EGU Utilization and CO2 Emissions 

Organizations use growth tools for a variety of reasons; to estimate future emissions 

inventories for state and regional air quality modeling,9

 to estimate the impact of load-reduction 

measures such as end-use energy efficiency and distributed renewable energy on individual EGU 

                                                            

9

 See, for example, the ERTAC Load Growth Model, available at http://www.ertac.us/index_egu.html. 
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emissions, and county, state,10 and regional emissions rates.11 Because these algorithms are 

generally based on publicly available data12 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 will respond to changing system conditions. 

Non-modeling approaches, such as growth tools, approximate future emissions and 

generation from existing and new fossil fuel-fired EGUs under different assumed growth, 

retrofit, and load-reduction scenarios. These forecast tools do not simulate economic EGU 

dispatch, but could use demand growth rates and electricity 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 electricity 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 generation 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 US14 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 change with changes in environmental regulations or 

installed pollution control retrofits and additional 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 Hourly 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. 
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types, with implicit differentiation of economic outcomes for these different groups. Some of 

these algorithms may contain subroutines to add new generating capacity automatically to meet 

load requirements. 

III. Translating from a Rate-Based Emission Performance 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 

CO2 emission performance by affected EGUs (taking into account the qualifying impacts of plan 

measures that avoid CO2 emissions from affected EGUs) must be equivalent to, or better than, 

the required CO2 emission performance level in the state plan. This required level of emission 

performance in the state plan will reflect 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 CO2 emission rate (CO2 lb/MWh) or tonnage CO2

emission outcome by all affected EGUs equal to, or lower than, the required level of CO2

emission performance in the state plan would be considered to meet this plan 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 CO2 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 CO2 emission performance goal translates the application of a rate-based 

emission performance goal to an expected CO2 emissions outcome in tons during a plan 

performance period. A mass-based CO2 emission performance goal is calculated by projecting 

the tons of CO2 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 CO2 emission performance goal for affected EGUs established in the emission guidelines. 

The translation of a rate-based goal (expressed in lb CO2/MWh of useful energy output from 

affected EGUs) to tons (expressed as total tons of CO2 emissions from affected EGUs over a 

Comment [A1]: Is it possible to provide an 

example or equation as to how this is done? Would 

be helpful in clarifying the approach. 
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specified time period) is based on a projection of affected EGU utilization and dispatch mix. 

Importantly, this projection is conducted assuming the absence of qualifying state programs and 

measures contained in a state plan, and applying the rate-based goal in the emission guidelines as 

a proxy emission limit for affected EGUs. State programs and measures in the state plan are not 

included in this projection, because the purpose of this analysis is to determine the tonnage CO2

emissions that corresponds to the state-specific rate-based CO2 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 CO2 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 CO2 emission performance goals in the 

emission guidelines. This proxy involves applying the rate-based emission goal for a state as a 

rate-based average CO2 emission limit for affected EGUs in a state and then projecting the CO2

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 CO2 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 CO2 emissions outcome, in total tons of CO2

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. 
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B. Projection Scenarios 

As described above, the projection scenario for translating from a rate-based CO2

emission performance goal to a mass-based CO2 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 CO2 emission performance goal to a 

mass-based CO2 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 CO2 emission rate and 

CO2 emissions from affected EGUs in the absence 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. Because these measures will influence EGU CO2

emissions, they should, however, be included in the reference case projection scenario. 

2. A Mass-Based CO2 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 CO2

emission limit to affected EGUs that is equivalent to the state-specific rate-based lb 

CO2/MWh emission goal in the EPA emission guidelines.16 The CO2 emissions from 

affected EGUs projected during the specified plan performance period in this scenario 

represents the translated mass-based CO2 emission performance goal for the state plan. 

                                                            

15 An “existing measure” refers to a state or utility requirement, program, or measure that is currently “on the 

books.” For the purposes of this discussion, this may include a legal requirement that includes current and future 

obligations or current programs and measures that are in place and are anticipated to be continued or expanded in the 

future in accordance with established plans. Existing measures may have past, current, and future impacts on EGU 

CO2 emissions. 16 The proxy emission limit applied includes crediting for end-use energy efficiency, renewable energy, and nuclear 

generation included in building blocks three and four, which were used by EPA when calculating the state-specific 

CO2 emission performance goals for affected EGUs in the proposed emission guidelines. As a result, the proxy 

emission limit is able to capture all four building blocks included by EPA when calculating these 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. 

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. 
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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 

CO2 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. 

1. Constructing the Reference Case 

A key consideration for translating from a rate-based CO2 emission performance goal to a 

mass-based CO2 emission performance goal is proper construction of a reference case scenario. 

This includes assumptions for key variables that may drive EGU CO2 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 (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 electric 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, and measures should not, however, be ignored 

altogether, as they influence EGU CO2 emissions. Instead, these state actions are occurring in the 

background – either when a proxy rate-based CO2 emission limit is applied in the Mass-Based 

CO2 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 CO2 emission 

performance goal, the two policy scenarios described above, each of which involve adding a 

different CO2 emission reduction policy on top of the reference case scenario, are compared to 

one another. If the State Plan Policy Scenario achieves projected tonnage CO2 emissions equal 

to or lower than the projected CO2 emissions in the Mass-Based CO2 Emission Goal Policy 

Scenario, then the state plan can be deemed to meet the translated mass-based CO2 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 the plan period, due to actions19 taken after the 

date of the proposal of the emission guidelines.20 In practice, this means that emission 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 

                                                            

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 program 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, the end date of the base period for the EPA’s BSER-based 

goals analysis (e.g., beginning of 2013 for blocks 1-3 and beginning of 2017 for block 4, end-use energy efficiency), 

the end of 2005, or another date. 
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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). For example, emission reductions during the plan 

period that result from end-use energy efficiency or renewable energy technologies and measures 

installed beginning in June 2014 could be applied toward meeting the required level of emission 

performance during the plan period. These investments might be made to meet requirements 

under an existing end-use energy efficiency resource standard (EERS) or renewable portfolio 

standard (RPS). 

Under a rate-based plan, the approach described above would address the eligibility date 

for qualifying renewable energy and demand-side energy efficiency measures that, through 

MWh generation or MWh savings, avoid CO2 emissions from affected EGUs. Measures installed 

after the eligibility date could generate MWh generation or MWh savings during the plan period, 

and related avoided CO2 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. For example, under this approach, new renewable energy 

generating capacity installed in June 2014 or later to meet an existing, on-the-books RPS would 

be a qualifying measure in a state plan. However, only MWh generation beginning in 2020 and 

related avoided CO2 emissions could be applied toward meeting a required emission rate 

performance level. 

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, qualifying renewable energy and demand-side energy efficiency 

measures after a respective eligibility date would not be included in the reference case scenario. 

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. This treatment would represent past actions taken under existing state programs and 

measures that are not eligible for inclusion in a state plan. 

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 
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(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 CO2 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. 

IV. Projecting CO2 Emission Performance under a State Plan 

 As discussed in the preamble, in section VIII.D.4, one of the required components of a 

state plan is a projection that a plan will achieve the required level of CO2 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 CO2 emission performance goals for affected 

EGUs identified in the emission guidelines, or an equivalent translated mass-based CO2 emission 

performance goal.) 

This emission projection is based on a scenario 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 this 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 when 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 CO2 emission limit that provides credit for end-use 

energy efficiency and renewable energy measures that avoided CO2 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 realized through implementation of the plan. Utilitydriven portfolio approaches may also include a diverse 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. 
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V. Applied Considerations for Different Types of State Plans21

There are a number of considerations for properly representing different state plan 

approaches in CO2 emission projection scenarios. This includes both accurate representation of 

the attributes of state regulations, programs, and measures in the scenario, as well as the methods 

and data sources used to derive certain input assumptions that are used in CO2 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 as part 

of a projection of CO2 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 

reduction in electricity load and peak demand on EGU dispatch and CO2 emissions from affected 

EGUs.22 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), and the 

effective useful life of those energy and capacity savings (e.g., the life of installed measures 

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 transformation impacts that result from the program. These 

                                                            

21 Different potential state plan approaches are described in detail in the accompanying State Plan Considerations 

TSD. 

22 The evaluation discussed in this section is relevant for state plans that implement a rate-based CO2 emission limit 

applicable to affected EGUs that provides for adjustment or crediting of the CO2 emission rate of an affected EGU 

based on the effects of end-use energy efficiency and renewable energy. It is also relevant for state plans that take 

either a rate-based or mass-based portfolio approach. Descriptions of these plan approaches are provided in the 

accompanying State Plan Considerations TSD. 
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energy efficiency program projections would then be used to adjust electricity 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 CO2 emissions from 

affected EGUs. 

Similar considerations apply for projecting the impact of renewable energy requirements 

and programs included in a state plan on CO2 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 state plan will affect EGU dispatch and CO2

emissions from affected EGUs. This section discusses 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 CO2

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. These forecasts would contain data that could be 

used to develop inputs to EGU CO2 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 efficiency programs, and program-level utility 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.23 In simple terms, ISO 

                                                            

23 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) by 
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New England develops production cost curves for energy 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 utility 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 efficiency 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 California 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 typically 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 acquired in ISO and RTO forward 

capacity markets. 

Top-down projection methods analyze aggregate 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 and 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”24 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 (ISO-NE) Energy-Efficiency Forecast Working Group, Draft Final 

Energy-Efficiency Forecast 2018-2023 (March 2014), available at: http://www.isone.com/committees/comm_wkgrps/othr/enrgy_effncy_frcst/ 

24 As used here, “on the books” refers to state energy-efficiency requirements 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.  
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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.25 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.26 These energy savings requirements are examined 

on a state-by-state basis and adjusted, as necessary, 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, NREL27, and some state energy offices and 

commissions. 

The LBNL28 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 CO2 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. For 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, these efforts are focused on including the future 

                                                            

25 While EPA’s approach utilizes AEO forecasts of electricity 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. 26 For example, annual incremental and cumulative energy savings requirements for utilities included in a state 

EERS. 

27 [Forthcoming April 2014 – Citation TBD] 

28 Lawrence Berkeley National Laboratory (LBNL), The Future of Utility Customer-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. 
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anticipated impacts of existing “on the books” energy efficiency requirements and programs and 

adjusting load forecasts accordingly. However, in some cases there is also an effort to anticipate 

new incremental energy efficiency investments in the future that are not tied to existing energy 

efficiency requirements and programs.29 When conducting a projection of EGU CO2 emission 

performance as part of a state plan that includes 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 already 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 Efficiency 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 necessary inputs to projections of EGU CO2 emission 

performance under the state plan. Energy and peak demand savings estimates included in energy 

efficiency projections are used as a decrement to future electricity load forecasts that are used in 

conducting EGU CO2 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 CO2 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 CO2 emissions that are projected to result from these 

requirements and programs. 

1.2 Data Issues and Considerations for Using and Developing Energy Efficiency 

                                                            

29 In New England states that have policies to pursue “all cost-effective energy efficiency,” 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. 
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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 approach and methodology used. Generally, these strengths and 

limitations relate to data availability and energy 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 periods). The ISO NE energy efficiency forecast is 

informed by data collected at the energy efficiency 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 into 
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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 effect of historical energy efficiency policies, 

either implicitly or explicitly, while in other cases the economic forecast may also anticipate 

some limited quantity of future 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 policies “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 through stakeholder discussions. 

Additionally, assumptions are made about how the overall cost of saved energy for a portfolio of 

energy efficiency programs will change over time. It is generally assumed 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).30 

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 

                                                            

30 Evidence to date is mixed as to a relationship of larger scale energy efficiency programs and broader energy 

efficiency measure portfolios, and the associated deeper levels of energy savings, to increasing cost of saved energy. 

Economies of scale, and expertise gained by program administrators from managing larger programs for multiple 

years, can lead to cost reductions. However, at some point, as program administrators move away from initial lowcost strategies and end-use energy efficiency measures, it is assumed that the cost of saved energy will increase. 
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applied to energy efficiency projections to provide a better estimate of the timing of energy and 

demand savings. Such time-differentiated 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 CO2 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 CO2 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 renewable energy or RECs. With this context, the 

following issues may be important to consider when projecting the impact of state RPS on EGU 

CO2 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) on the electric system over time based on a detailed characterization of 
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those EGUs, engineering and market operating constraints, 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 frameworks 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 CO2 emissions, a number of 

analytic and data considerations are relevant for analysis of RPS impacts on EGU CO2

emissions. These analytic and data considerations are summarized below. 

Translation of RPS Requirements to Renewable Energy Generation Requirements

Most RPS are retail sales-based requirements, while most electricity sector analytic tools 

are generation-based models. When projecting CO2 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 Loss rate).31

RPS-Eligible Resources vs. State Plan-Eligible Resources 

Some RPS rules define a broad range of eligible renewable energy generating resources. 

These could include renewable energy EGUs that emit CO2, 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 

                                                            

31 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 system in the United States. 
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may be included in a state plan.32 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 analysis 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 explicitly 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.33 

Characteristics of Renewable Resources 

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 substantially in generation profile, as the supply 

                                                            

32 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 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 these actions 

occur after proposal of the emission guidelines (e.g., as of June 2014 and in subsequent years). 

33 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. 
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of electricity to the grid from the EGU is based on availability of the renewable energy resource. 

The time during which electricity generation is supplied 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 

CO2 emissions that result from renewable energy generation. Data may include a detailed 8760 

energy output profile for renewable energy resources, 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 is available from NREL.34 

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 economics. 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 renewable energy resource availability (e.g., MW 

capacity available at different wind classes, solar insolation levels, and the characteristics of 

biomass). Having this information allows for better 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. 

                                                            

34 NREL’s datasets are intended for use by energy professionals, such as transmission planners, utility planners, 

project developers, and university researchers who perform wind and solar integration studies and need to estimate 

power production from hypothetical wind and 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 dataset, the accuracy of the data, site selection, and power output. The Solar 

Integration Datasets (http://www.nrel.gov/electricity/transmission/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 United States for the year 2006. 
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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.35 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 required after-tax rate of return. 36 

Retail Rate Impacts

Many state RPSs have 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 

increases in the RPS targets, depending on RPS implementation rules. This would lower 

estimates of renewable energy generation needed to satisfy the RPS requirements. 

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 least a regional, if not national, modeling framework. 

A broader framework captures competition for renewables (and increased prices, greater reliance 

on poorer resources), as well as market-wide impacts 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: 

                                                            

35 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-energy-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 solar, wind, or geothermal projects, design cost-based 

incentives, and evaluate the impact of tax incentives or other support structures on renewable energy projects. 36 The CREST model is a product of a 2009-2010 partnership 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. 
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 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 forecast 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 compliance achieved by credit multipliers. 

 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 expansion 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. 

 CO2 emission rate associated with renewable energy generation, by resource type (if 

applicable). 

 Generation profile, by renewable energy resource type 

2.2 Feed-in Tariff (FIT) and Other Performance-Based Incentives 

A feed-in-tariff 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 
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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.37 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: 

 An estimate of the renewable 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 ensure 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 

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 (8760 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 price impacts of the FIT will lead to lowering 

the amount paid to eligible renewable energy generators, if a FIT includes caps on 

                                                            

37 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. 
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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 Generation Resulting from Feed-In Tariff and 

 Performance-Based Tax Incentives 

Projections of renewable generation that will occur as the result of FITs and other 

performance-based incentives will require assembling the following data about the specific 

incentive programs that will support 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 resource 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 estimate of the total electric generation that will 

be supported by the FIT or other production-based incentive. 

 State experience and trends with FITs and 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 utility 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 distribution 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 
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expected to come from out of state, the basis for these assumptions should be 

documented. 

 CO2 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 of 

additional 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.38 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 for 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 

affected under CAA section 111(d).39 In general, most electricity sector capacity expansion and 

dispatch planning models can be configured to evaluate these program flexibilities and project 

CO2 emissions from affected sources, considering these compliance flexibilities. 

1. Addressing the Sectoral Scope of Emission Budget Trading Programs 

Some existing state emission budget trading programs addressing GHG emissions 

                                                            

38 Depending on the program, these cost containment allowance 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). 

39 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). 

Comment [A4]: Here and throughout this TSD, 

has EPA considered using “system” instead of 

“program(s)”? 
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regulate emission sources in addition to EGUs, such as industrial sources.40 We refer to these 

here as multi-sector emission budget trading programs. 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 budget trading programs, state plan emission projections 

would need to evaluate projected CO2 emissions across all source categories covered by the state 

or multi-state program. This would be necessary to project the CO2 emissions performance of 

affected EGUs under the multi-sector emissions budget trading program. 

For emissions budget trading programs that regulate 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 CO2 emission performance of 

affected EGUs, because those reductions would not come from those affected EGUs. However, 

state plan emissions projections would need to evaluate the use and impact of offsets, because 

the availability of offsets would affect the amount of CO2 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 

included in a state plan, CO2 emission projections provided as part of the state plan will need to 

evaluate projected CO2 emissions across all covered emissions sectors under the program. This 

would be necessary to project the CO2 emissions or weighted average CO2 emission rate of 

affected EGUs that will be achieved under the multi-sector emissions budget trading program 

included in the state plan. 

                                                            

40 The California GHG emission trading program also includes large industrial sources and as of 2015 will include 

distributors of transportation, natural gas, and other fuels. 
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Evaluating the projected impact of a multi-sector emissions budget trading program on 

the CO2 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 CO2 emissions performance across sectors in a multi-sector 

emissions budget trading program. 

Adequately projecting the CO2 emissions of affected EGUs subject to a multi-sector 

emissions budget trading program may require modeling using a multi-sector energy model.41

The use of an electricity sector dispatch and capacity 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 expansion planning module. However, use of a standalone electricity sector model, might also be necessary as a supplement to a multi-sector energy 

model, in order to project CO2 emissions or the weighted average CO2 emission rate from 

affected EGUs at a sufficient level of resolution for state plan emission projections. Under this 

approach, a multi-sector energy model might be used to project the level of CO2 emissions 

abatement achieved across the multiple emission sectors covered by the program. This multisector projection could be used to develop a CO2 marginal abatement cost curve representing 

cost-effective, non-electricity sector emission reduction 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 CO2

emission performance of affected EGUs (e.g., the CO2 emissions or CO2 emission rate of 

individual affected EGUs, or the total CO2 emissions or weighted average CO2 emission rate 

across multiple affected EGUs).42

                                                            

41 For example, the Energy 2020 model was used by California 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). 

42 This marginal abatement cost curve would be applied in a similar manner as marginal abatement 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 reductions from affected EGUs would be foregone and 

replaced by emission reductions from emission sources in other sectors that are also subject to the multi-sector 

emission budget trading program. 
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Multi-sector emission budget trading programs also often address GHGs beyond CO2. 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 different industrial sectors reduce emissions of nonCO2 GHGs, which could impact projected CO2 emissions from affected EGUs. 

Addressing Emission Offsets 

Emission offsets in CO2 or GHG emissions budget trading programs represent projectbased GHG emissions reductions outside the sector or sectors regulated by the program.43

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 “CO2 offset allowances” awarded for GHG 

emissions reductions achieved through approved offset projects may be initially used by affected 

sources to meet up to 3.3 percent of their CO2 allowance compliance obligation.44 This 

percentage increases to five and ten percent of a CO2 allowance compliance obligation at 

specified $7 and $10 price triggers, respectively. 

The ability to use GHG emission offsets for compliance means that CO2 emissions from 

EGUs regulated under the emissions budget trading program may exceed the base CO2 emissions 

budget established for the program. Offset allowances or credits are awarded in addition to the 

existing CO2 emissions budget, in exchange for CO2-equivalent emissions reductions achieved 

outside the capped emissions sector.45 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 CO2 emissions from affected EGUs in a state plan, because the 

                                                            

43 “Offsets” as used in the context of CO2 or GHG emissions budget trading programs are distinct from offsets in the 

NSR permitting context under the CAA, where in certain instances emissions of a criteria pollutant from a proposed 

new facility must be offset with creditable emissions reductions at an existing facility, if the state or jurisdiction 

where the proposed facility would be located is in non-attainment status for the pollutant. 44 This percentage increases to five and ten percent of a CO2 allowance compliance obligation at specified $7 and 

$10 price triggers, respectively. 

45 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 occurred absent the incentive provided through the award of the 

offset allowance or credit). 

Comment [A5]: 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

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.  

Comment [A6]: 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.

Comment [A7]: Can EPA take comment on how 

to incorporate offsets when gross emissions may 

exceed the base cO2 emissions budget. 
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use of offsets functionally expands the CO2 emissions budget for affected EGUs. This allows 

affected EGUs to emit more CO2 while meeting their compliance obligation under the emissions 

budget trading program, in exchange for CO2-eq. emissions reductions achieved outside of the 

affected source category. As a result, to properly project the CO2 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.46

Under this approach, state plans could demonstrate how 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 meets the state plan goals. This does not mean that an emission budget 

trading program included in a state plan could not include an offset component. Effectively, such 

a system,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.47 

2. Multi-State Emission Trading Programs 

Emission budget trading programs may be multi-state in nature. For such programs, 

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 CO2 emissions budgets 

in state regulations. However, there is no requirement limiting total CO2 emissions from affected 

                                                            

46 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. 47 In other words, the projected CO2 emissions or weighted average CO2 emission rate for affected EGUs would be 

based on the direct emissions from these EGUs alone, with no calculation of “net” EGU CO2 emissions that factor in 

the CO2-eq. emissions reductions represented by offset credits or allowances used by an EGU to meet a portion of 

its compliance obligation. 

Comment [A8]: 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. 

 
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sources in an individual state. State regulations include reciprocity provisions allowing emission 

sources to use CO2 allowances issued by another participating state for compliance with the state 

program. This provides for state-to-state CO2 allowance flows (and the potential for differences 

in state-by-state CO2 emissions relative to state emissions budgets) based on where the 

allowance market determines it is most economical to achieve CO2 emissions reductions. 

However, in aggregate, the CO2 emissions budgets in each of the participating state regulations 

establish a regional cap on CO2 emissions from affected EGUs. As a result, while a multi-state 

emission budget trading program may be projected to result in CO2 emissions from affected 

EGUs consistent with a multi-state mass-based CO2 emission performance goal, the CO2

emissions outcomes may vary by state. This necessitates evaluating a multi-state emission 

budget trading program as a whole, because the individual regulations of participating states 

function together as single integrated program. 

To address these issues, states participating in a multi-state emission budget trading 

program would jointly demonstrate that the multi-state program is achieving the required level of 

CO2 emission performance on a multi-state basis, based on the CO2 emission performance of all 

affected EGUs in the multi-state group implementing the program. 

Some state emission budget trading programs also include international partner 

jurisdictions.48 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 CO2 emission performance of 

affected EGUs in the subset of the program represented by U.S. states. Although the CO2

emission performance of EGUs (or other emission sources) in a foreign country would not be 

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 CO2 emissions across all participating jurisdictions, as these 

cross-jurisdictional flows would impact projected CO2 emissions from affected EGUs in U.S. 

                                                            

48 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. 
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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. Furthermore, considerations for projecting emission 

performance under a state plan will differ depending 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 recommended 

guidance for EGU CO2 emission projections included in state plans. Such guidance could include 

default modeling assumptions, or data sources for key assumptions. State modeling projections 

included in a state plan could include assumptions that deviate from the EPA’s recommended 

default assumptions, but a state plan would justify the 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 

 Cost and performance of pollution control equipment 

Comment [A9]: Suggest EPA consider 

developing guidance on best practices and other 

ways to encourage standardization. 
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 EGU firm builds and retirements (those scheduled with a regional transmission 

organization or independent system operator (RTO/ISO)49

 Transmission capability and ISO/RTO transmission expansion plans 

 Applicable federal regulations (other than the EPA emission guidelines) 

 Applicable state regulations and programs (other 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).50 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 plans on a regional basis. The ISO/RTO Council, 

an organization of electric grid operators, has suggested that ISOs and RTOs could provide 

analytic support to help states develop and implement their plans. The ISOs and RTOs have the 

capability to model the system-wide effects of individual state plans. Providing assistance in this 

way, they felt, would allow states with borders that fall within an RTO or ISO footprint to assess 

the system-wide impacts of potential state plan approaches. In addition, as the state implements 

                                                            

49 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. 

50 EPA’s manual, Roadmap for Incorporating Energy Efficiency/Renewable Energy Policies and Programs into 

State Implementation Plans/Tribal Implementation Plans (July 2012), could potentially support and be expanded 

upon to develop this component of EPA technical modeling 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. 
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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 reliability. The ISO/RTO Council suggested that the EPA 

ask states to consult with the applicable ISO/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 CO2 emission performance goal 

is the party that conducts the translation of the rate-based CO2 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, The 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 presumptive translation of the state-specific 

rate-based CO2 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 CO2 Emission Goal Policy Scenario, as described above in section III.B. A state could 

utilize the presumptive mass-based CO2 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 justify 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 CO2 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 assumptions for key parameters that will likely 

influence projections, such as electricity load forecasts and projected fossil fuel prices. Under 

this approach, the EPA might also provide a coordinating function in addressing the assumptions 

Comment [A10]: 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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applied by multiple states within a grid region, acknowledging that assumptions about state 

programs across a broader grid region that are included in an analysis scenario will influence 

projections of CO2 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 have flexibility to use other approaches, which the 

EPA would review. 
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Technical Support Document: 

Resource Adequacy and Reliability Analysis 

[DRAFT Results Subject to Change] 

This document describes resource adequacy and reliability impacts in 2020 for the base 

case and selected 111d scenarios. As used here, the term resource adequacy means the provision 

of adequate generating resources to meet projected load and generating reserve requirements in 

each region, while reliability includes the ability to deliver the resources to the loads, such that 

the overall power grid remains stable. The EPA uses the Integrated Planning Model (IPM) to 

project likely future electricity market conditions with and without the proposed rule. 

IPM is a multi-regional, dynamic, deterministic linear programming model of the U.S. 

electric power sector. It provides forecasts of least cost capacity expansion, electricity dispatch, 

and emission control strategies while meeting energy demand and environmental, transmission, 

dispatch, and reliability constraints. The model is designed to reflect electricity markets as 

accurately as possible. The EPA uses the best available information from utilities, industry 

experts, gas and coal market experts, financial institutions, and government statistics as the basis 

for the detailed power sector modeling in IPM. The model documentation provides additional 

information on the assumptions discussed here as well as all other model assumptions and 

inputs.1 

IPM is specifically designed to ensure generation resource adequacy, either by using 

existing resources or through the construction of new resources. IPM addresses reliable delivery 

of generation resources for the delivery of electricity between the 64 IPM regions, by setting 

limits to the ability to transfer power between regions using the bulk power transmission system. 

Within each model region, IPM assumes that adequate transmission capacity exists to deliver any 

resources located in, or transferred to, the region. For a more complete presentation of the power 

sector impacts of the proposed rule, see the Regulatory Impact Analysis. 

Overview 

                                                            

1

 Detailed information and documentation of EPA’s Base Case using IPM (v5.13), including all the underlying 

assumptions, data sources, and architecture parameters can be found on EPA’s website at: 

http://www.epa.gov/powersectormodeling/BaseCasev513.html 

Comment [A1]: General Comments: This TSD

would be a good opportunity for EPA to discuss the

provisions in State plans that are desirable to help

maintain system reliability. Some examples could

include:

Flexibility that recognizes the need to allow

carbon‐intensive generation to run for short

periods of time to maintain system reliability

(while maintaining overall emissions limits)

The desirability of consultations, including with

ISO/RTOs or the relevant planning authorities,

during the formulation of a state plan

Multi‐state approaches

1.Assuming that the starting point for this

analysis is 2012 data, as noted in the preamble (if

not please clarify this), when discussing

projections for retired capacity, it should be

made clear how those numbers relate to BAU

retirements and also those retirements that have

already been announced or filed.  
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The EPA is proposing emission guidelines for states to use in developing plans to address 

greenhouse gas emissions from existing fossil fuel-fired electric generating units. Specifically, 

the EPA is proposing state-specific rate-based goals for carbon dioxide emissions from the 

power sector, as well as guidelines for states to use in developing plans to attain the state-specific 

goals. This rule, as proposed, would set in motion actions to lower the carbon intensity of power 

generation in the United States. The agency is proposing one option (Option 1) for state-specific 

goals and requesting comment on a second option (Option 2). For purposes of this resource 

adequacy and reliability assessment, estimates and projections are taken from the Option 1 State 

scenario. This option was chosen because it limits compliance choices more than the 

corresponding regional option, and is more likely than the regional option to pose challenges to 

resource adequacy.2

 The Option 1 Regional scenario results are discussed relative to the results 

from the Option 1 State scenario. 

Option 1 (State) Policy Scenario 

Summary of Changes in Operational Capacity 

Total operational capacity is lower in the policy scenario, primarily from reduced need 

for existing and new capacity as a result of increases in energy efficiency. These increases in 

energy efficiency make possible increases in retirements compared to the base case. Since most 

regions currently have capacity above their target reserve margins, most of these retirements are 

absorbed by a reduction in excess reserves over time. Operational capacity3

 changes from the 

base case in 2020 are summarized below: 

 

                                                            

2

 For more detail on the economic impacts, and more discussion of the compliance scenarios, see Chapter 3 of the 

RIA for this proposal. 

3

 Operational capacity is any existing, new or retrofitted capacity that is not retired. 
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T able 1. Operational Capacity Summary in 2020 

Base case operational capacity (MW) 1,004,942

 Minus Retirements in Policy Case: 

 (-) Coal -48,996

 (-) Oil-Gas Steam -16,131

 (-) Combustion Turbine -2,328

 (-) Combined Cycle -3,455

 Plus New Capacity 36,118

Equals Policy Case Operational Capacity 970,1504

Since the model must maintain adequate reserves in each region, a portion of the reduced 

operational capacity in the policy case is taken from reserves that currently exceed the target 

reserve margin and will not be needed in the future. In order to maintain resource adequacy in 

each region where existing resources retire, the model relies on this excess reserve reduction, 

additions of new capacity, and reduced total resource requirements from increases in energy 

efficiency. As the table shows, the reduced resource needs permit lower capacity additions even 

though there are substantial increases in retirements. Each of these policy case changes is 

discussed further below. 

Reduction in Excess Reserves 

IPM uses a target reserve margin in each region5

 as the basis for determining how much 

capacity to keep operational in order to preserve resource adequacy. IPM retires capacity if it is 

no longer needed to provide energy for load or to provide capacity to meet reserve margin during 

the planning horizon of the projections. Since current regional reserves are generally higher than 

the target reserve margin for the region, and increased energy efficiency will reduce the need for 

reserves, IPM may retire reserve capacity in 2020 if it is not economic to use it to maintain 

adequate reserve margins. Existing resources may also be more expensive, compared to 

                                                            

4

 Numbers in this table may not sum to numbers in Table A1 due to independent rounding and small classification 

differences between the base and policy cases. 

5

 Reserve margin targets are generally based on the NERC 2010 10 Year Assessments for the region, except in cases 

where there are more stringent state requirements or other exceptions. 
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alternatives such as building new capacity or transferring capacity from another region. As a 

result, many of the plants that are projected to retire in 2020 will not need to be replaced. 

Table 1 above shows that operational capacity is reduced by approximately 3.5 percent 

nationwide in 2020 under the policy.6

 The majority of this reduction is the result of decreases in 

load; in 2020 summer peak loads are reduced by around 3 percent nationwide, or approximately 

24 GW (see Table A1). At the projected 2020 reserves margins in 2020 of 19 percent in the base 

case, these reductions reduce reserve capacity needs by around 28 GW, or about 80 percent of 

the overall reduction in load of 35 GW shown in Table 1. Moreover, these reductions are from 

energy efficiency that is available in all hours, not just at peak, so it can substitute for existing or 

new baseload capacity. A reduction of 3.5 percent in 2020 will therefore have little overall 

impact. Moreover, retirements are distributed throughout the power grid, so there will be only 

small impacts at the regional level.7

 Excess regional reserves above the target margin can be 

shared among sub-regions to ensure adequate reserve margins within a larger reliability region. 

IPM permits these transfers of reserves, but limits their level to ensure the reliability of the bulk 

power system. These interregional transfers are discussed further below. 

Although there are substantial existing regional variations in reserve margin, IPM adjusts 

regional capacities in 2020 to meet the specific target reserve margin in each region, through 

changes in the level of retirements, construction of new generating capacity, or transfers of 

capacity among regions to meet the specific reserve margin in each region. Each of these 

adjustments in the 2020 projections is described below. 

Changes in Retirements and New Capacity Additions 

Although there are significant retirements of 49 GW of coal and 16 GW of Oil-Gas 

Steam plants in the policy case in 2020 compared to the base case, these are offset by 28 GW of 

capacity from load reductions discussed above and by changes in new capacity additions. 

Retiring coal units are generally older and smaller, and retiring oil/gas steam units are generally 

older, less efficient and infrequently used units. Where needed for reserve margin, this retiring 

                                                            

6

 Regional data on operational capacity is shown in Table A1 of the Appendix. 7

 See maps of IPM regions and NERC Assessment Regions, and the table of target and projected reserve margins in 

the Appendix C. IPM regions are based on the regions NERC uses for regional assessments. These Assessment 

Regions are used for the Appendix tables in this document. 
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capacity is replaced by 23 GW of Natural Gas Combined Cycle capacity, 2 GW of Combustion 

Turbine capacity and 10 GW of wind capacity (See Table A5). This new capacity of 35 GW 

amounts to approximately 4% of the current reserve capacity (See Table A2 for current summer 

reserve capacity); adding this amount of capacity to replace retiring coal and oil/gas steam units 

is unlikely to present resource adequacy concerns. Although there can be local grid reliability 

issues in replacing some units, these can be managed within the normal reliability planning and 

management time frames provided by the flexible resource options and time frames in the rule. 

The distribution of these retirements across NERC Assessment regions is shown in Appendix C. 

Reserve Transfers 

In cases where it is economic to transfer reserves from a neighboring region, rather than 

supply reserves from within a region, IPM will transfer reserves, subject to summer and winter 

limits that are designed to ensure that these reserves can be transferred reliably. The transfer of 

reserves can occur, for example, if a region retires capacity that was used in the base case to meet 

reserve requirements, but a neighboring region has lower cost reserves that are not needed for its 

own reserve requirements. To examine these transfers, the EPA analyzed the change in net 

transfers from each region, where the net transfer for the base and policy cases is measured by 

the reserves sent to neighboring regions. In these cases, a positive value signifies the reserve 

capacity sent to other regions is larger than the reserve capacity received from other regions 

(sending and receiving regions can be different), while a negative value signifies that the 

capacity received is larger than the capacity sent. Thus, the value measures the degree to which 

resources in the region were reserved for use by other regions (positive value), or where the 

capacity to meet load in the region was served by resources in other regions (negative value). In 

each case these reserve transfers represent the use of the transmission system on a firm basis for 

at least a season. 

To look at the impact of the policy case on transfers, the measure used was the change in 

the summer reserves sent in the policy case compared to the base case. To develop a relative 

measure of the impact of the policy, the change in reserves was measured as a percentage of load 

in the sending region. This percentage gives an indication of the significance of the policy for 

changes in the grid. The results of this measurement are shown in Table A6. As the Table shows, 

Comment [A2]: New or currently under

construction?  Please specify.

Comment [A3]: Does this analysis assume that

the replacement units can also provide

grid/ancillary services otherwise provided by the

retiring units?
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only three regions are at or above a 5%. The EPA believes changes below 5% are unlikely to 

raise concerns over reliability; the three changes at or above 5% are discussed further below. 

Using this measure, the largest change in reserves are in the Northeast in ISO-NE, and in 

the Southeast in SERC-SE and FRCC. In ISO-NE the change in reserves is additional receipts of 

1947 MW, increasing net reserves received from 938 MW to 2,885 MW. The majority of this 

change resulted from a net decrease of 1261MW in the reserves sent from ISO-NE regions to 

regions in the NYISO; the remainder resulted from a net increase in the reserves received from 

Canada and from NYISO. In projecting these shifts, IPM is constraining flows within the transfer 

limits between IPM regions, but also limiting the total flow between all the IPM regions in 

NYISO (New York State) and ISO-NE (all the states in New England).8

 The modeling thus 

considers both basic line limits and broader transmission system limits on overall flows. The 

shifts in grid transfers exhibited in the IPM modeling suggest overall grid adjustment that is 

shared by these RTOs within manageable limits, and do not appear to be a cause for concern. 

In the Southeast, the largest percentage change occurs in SERC-SE. In the base case, 

SERC-SE sends a net 2,071 MW to other regions, while in the policy case it receives a net 2,092 

MW from other regions. This change amounts to a shift of in increased receipts relative to the 

base case of 4, 163 MW (8.3% of load in the base case). Although this shift is relatively large 

compared to other regions, there is little change in the absolute magnitude of transfers that need 

to be managed, since transfers shift from reserves sent to reserves received – in both cases the 

transfer is around 2,000 MW. The shift to receipts corresponds to the other large shift in the 

Southeast, as shift in FRCC from zero MW sent to 3,420 MW sent. All of these transfers are to 

SERC-SE, the only region to which FRCC is connected. When the larger SERC region is 

considered9

, combining all the individual SERC regions, the shift as a percentage of load drops 

to 4.8% of the total SERC load. These overall changes fall within the planning areas of SERC 

and are related to the placement of new capacity; within this planning area the shifts of this 

magnitude should be manageable. 

Alternative Case: Option 1 (Regional) 

                                                            

8

 For details on these limits, see the IPM documentation. 

9

 This the entire SERC region, consisting of SERC-SE, SERC-N, SERC-E and SERC-W. See map in Appendix for 

details. 
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As discussed above, the Option 1 (State) was chosen for the basic impact analysis 

because it provides a stricter test of potential reliability impacts. The EPA also examined the 

preferred Option 1 (Regional) case to identify differences with the State case and assess potential 

impacts. Tables B1 through B5 in Appendix B present results that correspond to Option 1 (State) 

Tables A1 through A5. As expected, both cases showed very similar patterns in total operating 

and reserve capacity, since the IPM model must serve the same loads and ensure the same 

reserve margins in each case. Total operating capacity differs by less than one percent and 

regional operating capacities are within 5 percent except for MAPP.10 Reserve capacity and 

projected reserve margins for Option 1 (Regional) (Tables B2 and B3) follow a pattern similar to 

operating capacity: totals are within 1% of the projections for the corresponding outputs from 

Option 1 (State) and regional reserve capacities are under 5 percent. 

Differences between the cases develop in the types of capacity that are retired and in the 

amount and types of new capacity built in2020. The Regional results show fewer incremental 

retirements of coal capacity (46.1 GW compared to 49.0 GW) and in the total retired capacity 

(68.4 GW compared to 70.6 GW). Retirements of Oil-Gas capacity remain essentially unchanged 

between the two cases (16.3 GW) and other retirements are small (see Tables A4 and B4.) The 

decrease in retired coal capacity of 2.8 GW are offset by a decrease in new combined cycle 

capacity of the 2.1 GW. Overall, these results indicate a greater flexibility in the choice of which 

units are used to serve capacity needs, a result that indicates general flexibility over capacity 

choices. Managing these increases and decreases should raise no reliability issues. Retirements 

of Oil/Gas Steam capacity remain unchanged between the options and no further reliability 

issues arise in the regional case. 

A similar indication of greater flexibility is seen in the transfers. The two cases with the 

largest percentage shift examined above are reduced in magnitude. The shift in ISO-NE is 

reduced from -7.7% to -5.4%, and the shift in SERC-SE is reduced from -8.3% to -6.7%. 

                                                            

10 MAPP has only 9 GW and the policy cases differ by 9.0 percent. An additional 848 MW of Wind capacity is 

added in the regional scenario compared to the state scenario. 
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Appendix A: Tables by IPM Region 

Option 1 (State) 

A1. Projected Operational Capacity in 2020 

A2. . Summary of Summer Peak Loads and Reserve Capacity in 2020 

A3. Summary of Target and Projected Reserve Margins in 2020 

A4. Policy Case Retired Capacity Incremental to Base Case in 2020 

A5. New Capacity in Policy Case Incremental to Base Case in 2020 

A6. Net Reserves Sent by NERC Assessment Region in 2020 
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A1. Projected Operational Capacity in 2020(MW) 

All Generation Sources Coal Only 

Region Base Policy Change Base Policy 

Basin (BASN) 14,163 12,864 -1,298 5,315 4,133 

Desert Southwest (DSW) 42,191 39,847 -2,344 9,278 6,894 

ERCOT 89,531 89,277 -255 19,052 10,734 

FRCC 54,766 56,723 1,956 7,893 2,291 

ISO-NE 30,239 28,533 -1,706 141 141 

MAPP 9,176 9,090 -85 3,424 3,339 

MISO 121,440 117,492 -3,948 50,983 45,646 

Northern California (CALN) 32,878 31,092 -1,786 71 71 

Northwest (NORW) 51,947 49,373 -2,574 2,354 2,354 

NYISO 38,779 37,227 -1,552 443 594 

PJM 180,193 175,676 -4,517 55,964 51,175 

Rockies (Rock) 23,509 22,163 -1,346 10,584 9,239 

SERC-E 52,311 52,086 -225 14,056 10,055 

SERC-N 47,824 48,498 675 16,260 15,786 

SERC-SE 60,084 55,023 -5,061 15,794 9,670 

SERC-W 41,035 35,965 -5,069 6,909 3,224 

Southern California (CALS) 43,004 40,920 -2,084 57 57 

SPP 71,871 68,188 -3,683 23,704 17,877 

Grand Total 1,004,942 970,037 -34,905 242,283 193,279 
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A2. Summary of Summer Peak Loads and Reserve Capacity in 2020 

Projected Reserve 

Margins 

Assessment Region 

Peak 

Demand 

Base 

Peak 

Demand 

Policy 

Reserve 

Capacity 

Base 

Reserve 

Capacity 

Policy 

Basin (BASN) 11,893 11,487 13,739 12,935

Desert Southwest 

(DSW) 34,249 32,675 39,549 37,086

ERCOT 72,034 70,790 81,938 80,523

FRCC 45,199 44,260 54,595 53,131

ISO-NE 25,142 24,040 28,913 27,646

MAPP 5,383 5,304 6,943 6,099

MISO 90,613 87,001 106,325 101,182

Northern California 

(CALN) 22,308 21,295 28,451 26,667

Northwest (NORW) 25,442 24,350 40,590 37,994

NYISO 29,876 28,504 34,656 33,065

PJM 155,743 150,641 179,728 173,839

Rockies (Rock) 16,025 15,446 19,952 17,991

SERC-E 44,545 43,525 51,227 50,054

SERC-N 40,177 39,390 46,203 45,299

SERC-SE 50,246 49,465 57,783 56,885

SERC-W 29,834 29,514 37,940 33,941

Southern California 

(CALS) 29,514 27,866 36,244 32,798

SPP 51,336 50,440 62,225 57,300

US Total 779,558 755,995 927,000 884,435
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A3. Summary of Target and Projected Reserve Margins in 2020 

Projected Reserve Margins 

NERC Assessment 

Region 

Target 

Reserve 

Margin Base Case 

Policy 

Case 

Policy % 

Above 

Margin 

Policy 

Change 

from Base 

Basin (BASN) 12.60% 15.52% 12.60% 0.0% -2.9% 

Desert Southwest 

(DSW) 13.50% 15.47% 13.50% 0.0% -2.0% 

ERCOT 13.75% 13.75% 13.75% 0.0% 0.0% 

FRCC 19.25% 20.79% 20.04% 0.8% -0.7% 

ISO-NE 15.00% 15.00% 15.00% 0.0% 0.0% 

MAPP 15.00% 28.99% 15.00% 0.0% -14.0% 

MISO 16.30% 17.34% 16.30% 0.0% -1.0% 

Northern California 

(CALN) 14.71% 27.54% 25.23% 10.5% -2.3% 

Northwest (NORW) 17.90% 35.58% 32.63% 14.7% -2.9% 

NYISO 16.00% 16.00% 16.00% 0.0% 0.0% 

PJM 15.40% 15.40% 15.40% 0.0% 0.0% 

Rockies (Rock) 14.65% 24.51% 16.48% 1.8% -8.0% 

SERC-E 15.00% 15.00% 15.00% 0.0% 0.0% 

SERC-N 15.00% 15.00% 15.00% 0.0% 0.0% 

SERC-SE 15.00% 15.00% 15.00% 0.0% 0.0% 

SERC-W 15.00% 27.17% 15.00% 0.0% -12.2% 

Southern California 

(CALS) 15.14% 22.80% 17.70% 2.6% -5.1% 

SPP 13.60% 21.21% 13.60% 0.0% -7.6% 

Grand Total 15.29% 18.91% 16.99% 1.7% -1.9% 
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A4. Policy Case Retired Capacity Incremental to the Base Case in 2020 (MW) 

 

CC Coal CT NU 

OG 

Steam Total 

Basin (BASN) 46 1,175 0 0 345 1,567

Desert Southwest (DSW) 0 2,392 0 0 0 2,392

ERCOT 0 8,358 0 0 0 8,358

FRCC 243 5,602 0 0 3,395 9,239

ISO-NE 1,029 0 0 0 2,671 3,700

MAPP 0 85 0 0 0 85

MISO 0 5,350 0 -261 0 5,089

Northern California (CALN) 209 0 1,592 0 0 1,800

Northwest (NORW) 1,885 0 690 0 0 2,574

NYISO 81 -151 0 0 1,656 1,586

PJM 0 4,622 0 0 0 4,622

Rockies (Rock) 0 1,349 0 0 0 1,349

SERC-E 0 4,004 0 0 0 4,004

SERC-N 0 468 0 0 0 468

SERC-SE 0 6,148 0 0 0 6,148

SERC-W -513 3,718 -7 0 4,417 7,615

Southern California (CALS) 766 0 54 0 1,493 2,313

SPP -292 5,874 0 0 2,154 7,737

Grand Total 3,455 48,996 2,328 -261 16,131 70,649
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A5. New Capacity Policy Case Incremental to Base Case in 2020 

(MW) 

Region CC CT Wind Other Total 

Basin (BASN) 0 -8 4 271 267

Desert Southwest (DSW) 0 0 6 34 40

ERCOT 6,831 0 1,233 0 8,064

FRCC 11,196 0 0 -95 11,101

ISO-NE 99 -7 1,903 -33 1,961

MAPP 0 -110 0 0 -110

MISO 0 -65 1,161 -63 1,033

Northern California (CALN) 0 0 1 13 14

Northwest (NORW) -11 -17 0 -5 -33

NYISO 0 -14 -37 0 -52

PJM -912 -1,729 1,633 -295 -1,304

Rockies (Rock) -1,023 265 537 0 -221

SERC-E 2,242 -56 0 1,524 3,709

SERC-N 500 0 9 0 509

SERC-SE 1,062 0 0 0 1,062

SERC-W 2,512 -31 0 0 2,481

Southern California (CALS) 183 0 6 38 227

SPP 47 -283 3,961 -3 3,722

Grand Total 22,724 -2,056 10,416 1,385 32,470
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A6. Net Reserves Sent by NERC Assessment Region in Base and Policy 

Scenarios in 2020 (MW) 

NERC Assessment 

Region Base Policy 

Change from 

Base to 

Policy 

Change as 

Percent of 

Summer Peak 

Basin (BASN) -1,430 -1,926 -496 -4.2%

Desert Southwest 

(DSW) 204 289 86 0.3%

ERCOT -1,942 -1,913 29 0.0%

FRCC 0 3,420 3,420 7.6%

ISO-NE -938 -2,885 -1,947 -7.7%

MISO 1,135 1,470 335 0.3%

Northern California 

(CALN) 0 0 0 0.0%

Northwest (NORW) 309 330 21 0.1%

NYISO 1,397 1,295 -102 -0.3%

PJM -12,061 -11,872 189 0.1%

Rockies (Rock) 208 426 217 1.4%

SERC-E -256 -570 -314 -0.7%

SERC-N 807 2,379 1,572 3.9%

SERC-SE 2,071 -2,092 -4,163 -8.3%

SERC-W 3,011 1,928 -1,084 -3.6%

Southern California 

(CALS) 251 1,622 1,371 4.6%

SPP 3,528 1,818 -1,709 -3.3%

 
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Appendix B: Tables by IPM Region 

Option 1 (Regional) 

B1. Projected Operational Capacity in 2020 

B2. Summer Peak Loads and Reserve Capacity in 2020 

B3. Summary of Target and Projected Reserve Margins in 2020 

B4. Policy Case Retired Capacity Incremental to Base Case in 2020 

B5. New Capacity in Policy Case Incremental to Base Case in 2020 
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B1. Projected Operational Capacity in 2020(MW) 

All Generation Sources Coal Only 

Region Base Policy Change Base Policy Change

Basin (BASN) 14,163 13,467 -696 5,315 4,838 -478

Desert Southwest 

(DSW) 42,191 41,810 -382 9,278 8,433 -845

ERCOT 89,531 88,511 -1,020 19,052 13,246 -5,806

FRCC 54,766 56,372 1,606 7,893 3,094 -4,799

ISO-NE 30,239 27,928 -2,311 141 141 0

MAPP 9,176 9,972 796 3,424 3,372 -52

MISO 121,440 115,908 -5,532 50,983 45,609 -5,374

Northern California 

(CALN) 32,878 30,909 -1,969 71 17 -54

Northwest (NORW) 51,947 49,473 -2,474 2,354 2,354 0

NYISO 38,779 36,716 -2,063 443 55 -388

PJM 180,193 175,000 -5,193 55,964 50,082 -5,882

Rockies (Rock) 23,509 22,342 -1,167 10,584 9,889 -695

SERC-E 52,311 52,522 212 14,056 8,264 -5,792

SERC-N 47,824 48,516 692 16,260 15,119 -1,142

SERC-SE 60,084 55,797 -4,287 15,794 11,390 -4,404

SERC-W 41,035 35,710 -5,325 6,909 2,352 -4,557

Southern California 

(CALS) 43,004 40,091 -2,913 57 57 0

SPP 71,871 69,754 -2,117 23,704 17,853 -5,851

Grand Total 1,004,942 970,799 

-

34,143 242,283 196,164 -46,118
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B2. Summary of Summer Peak Loads and Reserve Capacity in 2020 

Projected Reserve 

Margins 

Assessment Region 

Peak 

Demand 

Base 

Peak 

Demand 

Policy 

Reserve 

Capacity 

Base 

Reserve 

Capacity 

Policy 

Basin (BASN) 11,893 11,487 13,739 12,935

Desert Southwest 

(DSW) 34,249 32,675 39,549 37,765

ERCOT 72,034 70,790 81,938 80,523

FRCC 45,199 44,260 54,595 52,781

ISO-NE 25,142 24,040 28,913 27,646

MAPP 5,383 5,304 6,943 6,099

MISO 90,613 87,001 106,325 101,182

Northern California 

(CALN) 22,308 21,295 28,451 25,654

Northwest (NORW) 25,442 24,350 40,590 37,962

NYISO 29,876 28,504 34,656 33,065

PJM 155,743 150,641 179,728 173,839

Rockies (Rock) 16,025 15,446 19,952 18,722

SERC-E 44,545 43,525 51,227 50,054

SERC-N 40,177 39,390 46,203 45,299

SERC-SE 50,246 49,465 57,783 56,885

SERC-W 29,834 29,514 37,940 33,941

Southern California 

(CALS) 29,514 27,866 36,244 33,752

SPP 51,336 50,440 62,225 57,300

US Total 779,558 755,995 927,000 885,404
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B3. Summary of Target and Projected Reserve Margins in 2020 

Projected Reserve Margins 

NERC Assessment 

Region 

Target 

Reserve 

Margin Base Case 

Policy 

Case 

Policy % 

Above 

Margin 

Policy 

Change 

from Base 

Basin (BASN) 12.60% 15.52% 12.60% 0.0% -2.9% 

Desert Southwest 

(DSW) 13.50% 15.47% 15.58% 2.1% 0.1% 

ERCOT 13.75% 13.75% 13.75% 0.0% 0.0% 

FRCC 19.25% 20.79% 19.25% 0.0% -1.5% 

ISO-NE 15.00% 15.00% 15.00% 0.0% 0.0% 

MAPP 15.00% 28.99% 15.00% 0.0% -14.0% 

MISO 16.30% 17.34% 16.30% 0.0% -1.0% 

Northern California 

(CALN) 14.71% 27.54% 20.47% 5.8% -7.1% 

Northwest (NORW) 17.90% 35.58% 32.57% 14.7% -3.0% 

NYISO 16.00% 16.00% 16.00% 0.0% 0.0% 

PJM 15.40% 15.40% 15.40% 0.0% 0.0% 

Rockies (Rock) 14.65% 24.51% 21.21% 6.6% -3.3% 

SERC-E 15.00% 15.00% 15.00% 0.0% 0.0% 

SERC-N 15.00% 15.00% 15.00% 0.0% 0.0% 

SERC-SE 15.00% 15.00% 15.00% 0.0% 0.0% 

SERC-W 15.00% 27.17% 15.00% 0.0% -12.2% 

Southern California 

(CALS) 15.14% 22.80% 21.12% 6.0% -1.7% 

SPP 13.60% 21.21% 13.60% 0.0% -7.6% 

Grand Total 15.29% 18.91% 17.12% 1.8% -1.8% 
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B4. Policy Case Retired Capacity Incremental to the Base Case in 2020 

(MW) 

CC Coal CT NU

OG 

Steam Total 

Basin (BASN) 104 479 0 0 244 827

Desert Southwest (DSW) 0 848 0 0 0 848

ERCOT 0 5,832 0 0 0 5,832

FRCC 135 4,799 0 0 2,248 7,182

ISO-NE 621 0 0 0 2,100 2,722

MAPP 0 52 0 0 0 52

MISO 21 5,405 0 -70 384 5,740

Northern California 

(CALN) 697 54 1,291 0 0 2,042

Northwest (NORW) 2,071 0 690 0 0 2,761

NYISO 254 388 0 0 1,903 2,545

PJM 0 5,730 0 0 0 5,730

Rockies (Rock) 0 696 0 0 0 696

SERC-E 0 5,796 0 0 0 5,796

SERC-N 0 1,145 0 0 0 1,145

SERC-SE 0 4,428 0 0 0 4,428

SERC-W -513 4,596 -7 0 4,036 8,112

Southern California 

(CALS) 963 0 -32 0 3,109 4,041

SPP -292 5,906 0 0 2,243 7,857

Grand Total 4,062 46,152 1,941 -70 16,268 68,353
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B5. New Capacity Policy Case Incremental to Base Case in 2020 

(MW) 

Region CC CT Wind Other Total 

Basin (BASN) 0 -8 0 130 122

Desert Southwest (DSW) 0 0 277 186 463

ERCOT 4,661 0 125 0 4,786

FRCC 8,788 0 0 -95 8,693

ISO-NE 0 -7 418 -33 377

MAPP 0 -110 848 0 738

MISO 0 -65 199 -52 82

Northern California 

(CALN) 0 0 30 42 73

Northwest (NORW) -11 -17 162 119 254

NYISO 357 -14 53 0 396

PJM -677 

-

1,729 1,832 -313 -887

Rockies (Rock) -1,210 370 147 0 -693

SERC-E 4,387 -56 0 1,606 5,937

SERC-N 1,183 0 11 0 1,194

SERC-SE 117 0 0 0 117

SERC-W 2,749 -31 0 0 2,717

Southern California 

(CALS) 263 0 812 52 1,126

SPP 171 -283 5,515 -3 5,401

Grand Total 20,777 

-

1,951 10,430 1,638 30,894
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B6. Net Reserves Sent by NERC Assessment Region in Base and Policy 

Scenarios in 2020 (MW) 

NERC Assessment 

Region Base Policy 

Change from 

Base to 

Policy 

Change as 

Percent of 

Summer Peak 

Basin (BASN) -1,430 -1,316 114 1.0%

Desert Southwest 

(DSW) 204 1,388 1,185 3.5%

ERCOT -1,942 -1,658 284 0.4%

FRCC 0 3,420 3,420 7.6%

ISO-NE -938 -2,305 -1,367 -5.4%

MISO 1,135 558 -577 -0.6%

Northern California 

(CALN) 0 808 808 3.6%

Northwest (NORW) 309 345 36 0.1%

NYISO 1,397 752 -645 -2.2%

PJM -12,061 -12,723 -662 -0.4%

Rockies (Rock) 208 163 -46 -0.3%

SERC-E -256 -192 64 0.1%

SERC-N 807 2,395 1,589 4.0%

SERC-SE 2,071 -1,318 -3,389 -6.7%

SERC-W 3,011 1,681 -1,330 -4.5%

Southern California 

(CALS) 251 -785 -1,036 -3.5%

SPP 3,528 2,238 -1,290 -2.5%
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Appendix C: Maps 

C1. IPM Regions 

C2. . NERC Assessment Regions 
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C1: IPM v5.13 Regions
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C2: NERC Assessment Areas in Long Term Reliability Assessment.

Source: NERC 2012 Long Term Reliability Assessment
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