### 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 Emissi ons from Existing Stationary Sources: Electric

Utility Generating Units

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



# State Plan Considerations

U.S. Environmental Protection Agency

Office of Air and Radiation

June 2014I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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2 Table of Contents

I. Introduction .................................................................................................................. ......3

II. Description of State Plan Pathways .................................................................................4

A. Direct Emission Limits .............................................................................................6

B. Portfolio Approach ....................................................................................................8

III. Enforceability Considerations under Different State Plan Scenarios .........................12

A. Parties Regulated by the State other than Affected EGUs ......................................13

B. Private or Public Third-Party Entity not Regulated by the State ............................15

C. State Agency, Authority, or Entity ..........................................................................16

D. Multi-State Approaches

............................... ........................ ........................ ...........17

IV. Incorporating End-Use Energy Efficiency and Renewable Energy Programs and

Measures under a Rate-Based Approach ......................................................................19

A. Concept of Adjusting EGU CO 2 Emission Rates based on the Effects of End-Use

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

B. Approaches for Adjusting EGU CO 2 Emission Rates ............................................20

C. Methods and Tools for Quantifying Avoided CO 2 Emissions from End-Use Energy

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

V. Quantification, Monitoring, and Verifica tion of End-Use Energy Efficiency and

Renewable Energy Programs and Measures .................................................................32

A. Quantification, Monitoring, and Verification for End-Use Energy Efficiency .....35

B. Quantification, Monitoring, and Verification for Renewable Energy Measures ...45

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

Energy Programs and Measures ....................................................................................71

A. Reporting for End-Use Energy Efficiency Programs and Measures .....................72

B. Reporting for Renewable Energy Programs and Measures ...................................74

VII. Treatment of Interstate Emission Effects ......................................................................79

A. Background ............................................................................................................81

B. Summary of Possible Approaches for Treat ment of Interstate Emission Effects..83

VIII. Appendix ...................................................................................................................... .....92I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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3 I. Introduction

As discussed in the preamble, in section VIII. F, the EPA is proposing to give states

broad discretion to develop state plans that best suit their circumstances and policy objectives. In

developing its plan, a state will need to make a number of decisions th at will require careful

consideration, in order to ensure that its plan both meets a state’s policy objectives and is

approvable by EPA. The preamble, in section VIII. F, identified several key decision points and

factors that states should consider when developi ng their plans. In this section of the preamble,

the EPA also raised a number of considerations for how it will apply the proposed general plan

approvability criteria to different types of state plan approaches. This includes a number of

considerations related to appropriate approaches, methods, and materials that are submitted for

state plan components in an approvable plan, under different types of state plans. This technical

support document (TSD) explains and discusses these considerations in depth, and elaborates

options proposed in the preamble where relevant. Topics addressed in this TSD include:

 Description of state plan pathways

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

 Enforceability considerations un der different plan scenarios

o Summary of potential enforceable mechanisms under different state plan

scenarios

 Incorporating energy efficiency and re newable energy (EE/RE) requirements and

programs in state plans, including:

o Options for adjusting EGU CO 2 emission rates based on the effect of EE/RE

requirements and programs

o Methods for estimating avoided CO 2 emissions that result from EE/RE

requirements and programs

 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 CO 2

calculations conflates two separate issues:

their use as part of an ex ante determination of

whether a state plan (such as a portfolio approach)

will achieve a given level of emissions (or emissions

rate) as part of an equivalency determination and

their use ex post to ‘adjust’ emissions. It would help

clarify things if this distinction were discussed. With

regards to the ex post use, all emissions are already

measured at the stack, so an avoided emissions

calculation is unnecessary and would constitute

double counting of emissions reductions.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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4 o Discussion of possible approaches for minimum requirements or guidance for

quantification, monitoring, and verification for EE/RE requirements and programs

included in state plans, building off existing state processes and infrastructure

o Discussion of areas where supplement al information would be useful for

estimating avoided CO 2 emissions from EE/RE requirements and programs

 Reporting and recordkeeping for responsible parties subject to EE/RE requirements or

implementing EE/RE programs included in state plans

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

requirements and programs

o Discussion of possible approaches for EE/RE reporting requirements for state

plans, building off existing state processes and infrastructure

o Discussion of areas where supplement al information would be useful for

estimating avoided CO 2 emissions from EE/RE requirements and programs

 Treatment of interstate emission effects

o Further elaboration of proposed approaches and alternatives discussed in the

preamble

It should be noted that the preamble discusses, and solicits comment on, legal issues

concerning whether CAA section 111(d) authorizes some of the types of state plans described in

this TSD and whether it authorizes state plans to include some of these types of measures. This

TSD does not further discuss those legal issues, but solely for the purpose of describing all of the

available types of state plans and measures, assu mes that all of them are authorized under CAA

section 111(d).

II. Description of State Plan Pathways

As discussed in the preamble, the EPA is proposing a state plan approach that could

accommodate a diverse set of state requirements, programs, and measures, through two basic

approaches – direct emission limits and a po rtfolio approach. These two basic approaches

provide four distinct state plan “pathways” under CAA section 111(d). These pathways include:I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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5  Rate-based CO 2 emission limits applied to affected EGUs;

 Mass-based CO 2 emission limits applied to affected EGUs;

 A state-driven portfolio approach

 A utility-driven por tfolio approach

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

CO 2 emissions at affected EGUs through the appli cation of emission limits as well as measures

that involve actions within the interconnected electri city system that reduce utilization at affected

EGUs and thereby avoid EGU CO 2 emissions. Examples of these latter measures include, among

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

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

on CO 2 emission limits that are enforceable against affected EGUs or, alternatively, rely on a

portfolio approach, which would include those limits as well as other enforceable measures.

Table 1 provides practical examples of possibl e state plan approaches under each of these

pathways, which are discussed in more detail below.

This section elaborates the different plan appr oaches that are discussed in section VIII.B

of the preamble, to provide context for the applied considerations that are discussed throughout

the remainder of the TSD. In particular, some of these considerations apply to different types of

state plan approaches. For example, section III of this TSD addresses enforceable legal

mechanisms that might apply under different types of state plans, such as utility- and state-driven

portfolio approaches, which would apply enforceable obligations to different entities. Section IV

of this TSD applies to state pl ans that implement rate-based CO 2 emission limits for affected

EGUs that also provide for the adjustment of CO 2 emission rates based on the effect of

enforceable end-use energy efficiency and renewable energy requirements and programs that are

incorporated in a plan. Section V of this TSD addresses quantification, monitoring, and

verification of end-use energy efficiency an d renewable energy programs and measures.

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

emission limit approach that provides for adjustment of CO 2 emission rates based on the effect of

end-use energy efficiency and renewable energy, as well as states implementing utility- or statedriven portfolio approaches that incorporate en d-use energy efficiency and renewable energyI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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6 requirements and programs. Likewise, section VI of this TSD addresses considerations for

reporting and recordkeeping for end-use energy efficiency and renewable energy requirements

and programs, which would apply for these types of state plans.

Table 1. Different Illustrative Plan Approaches

A. Direct Emission Limits

The first basic state plan approach is CO 2 emission limits that apply directly to affected

EGUs, and includes two pathways: 1.) rate-based CO 2 emission limits applied to affected EGUs;

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

limits, end-use energy efficiency and rene wable energy measures that avoid EGU CO 2 emissions

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

emissions.

1. Rate-Based CO 2 Emission Limits Applied to Affected EGUs Comment [A3]: It would be helpful to have the

equivalent formula for rate

‐ based equivalency. In

particular, all of the above considerations apply to

the numerator of this formula. In addition, the

contributions to the denominator should be

specified. Specific questions include:

 Does generation from new NGCC units

count? New nuclear or CCS?

 What amount of generation from existing

clean units (including non

‐ hydro RE, hydro,

nuclear, etc.) is included in the denominator?

How are uprates dealt with?

 Is the EE generation included in the

denominator gross savings or net savings?I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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7 Rate-based emission limits would apply a lb CO 2 /MWh emission limit to affected EGUs.

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

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

CO 2 emissions resulting from end-use energy effi ciency and renewable energy measures as

discussed below. In the case of the latter approach, such credits could be used by an affected

EGU to adjust its CO 2 emission rate when demonstrating compliance with a rate-based emission

limit. 1 Rate-based emission limits could be implemen ted on a state-by-state basis, or through

multi-state averaging or trading. Rate-based em ission limits might also be a component of a

portfolio approach (described below), where the emission rate limit would not assure full

achievement of the required leve l of emission performance specified for affected EGUs in the

state plan, in which case the emission limit would be supplemented with other enforceable

measures.

Rate-based emissions limits could incorporat e end-use energy efficiency and renewable

energy measures that avoid EGU CO 2 emissions, through an administrative adjustment by the

state or tradable crediting system. 2 These adjustment credits could be used by an affected EGU to

comply with the rate-based emission li mit, by adjusting the unit’s reported CO 2 emission rate. 3

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

CO 2 emissions would be enforceable components of a state plan. These actions would need to be

enforceable components of a state plan to pr ovide assurance that a sufficient amount of

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

1 Section IV of this TSD discusses possi ble approaches for such adjustments.

2 Under a tradable credit system, a state would issue adjustment credits based on avoided CO 2 emissions achieved

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

adjustment credits when demonstrat ing compliance with a rate-based CO 2 emission limit. These tradable credits

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

renewable energy actions undertaken by private parties (i ncluding EGU owners and operato rs) might be eligible for

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

might administratively adjust an affected EGU’s CO 2 emission rate based on avoided CO 2 emissions achieved

through state end-use energy efficiency and renewabl e energy deployment programs or utility compliance with

energy efficiency resource standards or renewable energy portfolio standards. These adjustments might be

apportioned to affected EGUs based on a predetermined me tric. Affected EGUs would then begin with an adjusted

CO 2 emission rate when considering additional actions necessary for compliance with the rate-based CO 2 emission

limit.

3 Section IV of this TSD discusses po ssible approaches for such adjustments.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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8 and that end-use energy efficiency and renewable energy measures that generate adjustment

credits are properly quantified, monitored, and verified. 4

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

Mass-based emission limits would apply either an individual limit on CO 2 tons emitted

from an affected EGU or establish a finite CO 2 emissions budget for a group of affected EGUs.

The latter approach is typically implemented through a tradable allowance system.

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

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

reducing EGU CO 2 emissions, but would be complementary to the enforceable state plan ( i.e.

,

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

cost-effectively achieve the CO 2 emissions limits, or to achieve other policy goals, but CO 2

emissions performance would be assured through the enforceable limit on mass emissions from

affected EGUs.

B. Portfolio Approach

The second basic state plan approach uses a portfolio of actions, in which a state plan

includes multiple programs and measures that are designed to achieve either a rate-based or

mass-based emissions performance goal for affected EGUs. This approach includes two

pathways: 1.) a state-driven portfolio approach; and 2.) a utility-driven portfolio approach. A

portfolio approach would include emission limits for affected EGUs along with other enforceable

end-use energy efficiency and renewable energy measures that avoid EGU CO 2 emissions. A

portfolio approach could be state-driven or utility-driven, dependi ng on the utility regulatory

structure in a state.

In general, a portfolio approach is distinguished from an emission limit approach by the

fact that achievement of the full level of required emission performance for affected EGUs

4 Section V of this TSD addresses considerations for quant ification, monitoring, and verification of end-use energy

efficiency and renewable energy measures. Comment [A4]: It would be very helpful to have

the explicit formula that is the basis for determining

mass

‐ based equivalence. In particular, the precise

list of sources whose emissions count needs to be

specified. Specific questions include:

 Do emissions from new NGCC units count?

 Do emissions from new CCS units count?

 Do emissions from units with a capacity

factor of less than 1/3 or other uncovered

sources count?

 How will biomass emissions be incorporated

when the final guidance on this is available?I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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

affected EGUs.

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

EGUs and other indirect measures that avoid EGU CO 2 emissions. Under a portfolio approach,

end-use energy efficiency and renewable energy measures that avoid EGU CO 2 emissions would

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

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

emission performance specified in the state plan. 5

As discussed below, due to differences in st ate utility regulatory st ructure, a portfolio

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

different from one implemented in a state with ve rtically integrated, regulated electric utilities.

This includes the process for developing the portfolio approach, the mechanisms for

implementing it, the responsible parties, and the regulatory and legal relationships among parties

and state regulators.

1. State-Driven Portfolio Approach

A state-driven portfolio approach – rather than a utility-driven approach – is more likely

to be adopted in a state with a restructured el ectricity sector. In these states, rate-regulated

electric utilities have typically divested electric generation assets and there is often also retail

competition where non-utility entities can s upply retail customers with electricity. 6 Electric

distribution utilities in these states typically purchase electricity from competitive wholesale

markets. As a result, utilities in these states ty pically do not engage in a utility integrated

resource planning (IRP) process. IRP processes, which are a natural fit for implementing a

5 Under a portfolio approach, either a rate-based or mass- based emission limit might be applied. Such plans might

also include application of a direct emission limit to a subset of affected EGUs. Both scenarios would necessitate

inclusion of supplemental measures, such as end-use energy efficiency and renewable energy, or other measures that

directly apply to affected EGUs (e.g., repowering or retirement of one or more high-emitting EGUs), in order to

achieve the required level of emission performance for affected EGUs specified in the state plan.

6 In some restructured states, the holding company that ow ns the distribution utility may also own generating assets

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

mandate the independent management and opera tion of generation and distribution assets.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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10 portfolio approach, are mu ch more common in states with regu lated vertically integrated utilities

that own and operate electric generating assets.

In restructured states, policies for increasing end-use energy efficiency and renewable

energy are often established throu gh regulations that apply to electric distribution utilities, such

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

these states have also established independent n on-profit entities to administer end-use energy

efficiency and renewable energy deployment programs funded through regulated electricity

rates.

Under a state-driven portfolio approach a mix of entities might have enforceable

obligations under a state plan. This includes owne rs and operators of affected EGUs subject to

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

entities, and state agencies or authorities th at administer end-use energy efficiency and

renewable energy deployment programs or are subject to portfolio requirements.

2. Utility-Driven Portfolio Approach

A state with vertically integrated, state-regulate d electric utilities is more likely to adopt a

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

generation, transmission, and distribution system s necessary to supply retail customers with

electricity. 7 These utilities are overseen by state public utility commissions that approve utility

capital investments and oversee utility opera tions, and allow utilities to recover approved

investments and operating costs, along with a specifi ed financial rate of return, through regulated

retail electricity rates. State utility commissions often require regulated utilities to engage in an

integrated resource planning (IRP) process, which seeks to identify the least-cost set of resources

available to provide electricity to retail customers over a multi-year period, and often includes

evaluation of measures such as end-use energy efficiency, demand-side management, and

7 In some instances these regulated utilities may supplem ent electric generation with purchases through wholesale

electricity markets and may also sell surplus generati on in these wholesale markets on a competitive basis.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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11 renewable energy. 8 Once an IRP is approved by a state public utility commission, a utility’s cost

recovery and rate of return is often linked to identified measures and metrics in the IRP. 9

Under a utility-driven portfolio approach, a vertically integrated utility would develop

and implement a portfolio of measures designed to meet the rate-based or mass-based emission

performance level for its affected EGUs specified in the state plan. This plan would likely be

developed and approved through an IRP-like process overseen by the state public utility

commission. If there is more than one rate-regulat ed electric utility in the state, the state might

apportion the state emission performance le vel for affected EGUs among utilities.

A utility plan under this approach might rely heavily on end-use energy efficiency and

renewable energy actions, but also might focus on direct actions at af fected EGUs, such as

repowering to fire a lower-carbon fuel or retirement of high-emitting units. Such plans might

also include direct emission limits on affected EGUs, or implementation of an environmental

dispatch approach that incorporates CO 2 emission rate into the dispatch protocol used by the

utility to schedule electric generation. 10

Under a utility-driven portfolio approach, the entire suite of obligations under the plan

would be enforceable against the utility company, which would also be an owner and operator of

affected EGUs. If there are other affected EGUs in the state that are not owned and operated by a

vertically integrated utility, a state plan might need to include other measures that address CO 2

emission performance by these affected EGUs.

A similar approach could be taken by munici pally owned utilities or utility cooperatives,

which often also engage in an IRP process. However, state public utility commissions (PUCs)

8 Depending on the state, an IRP process may also a ssess factors such as fuel diversity and environmental

performance, among others, when identifying th e least-cost mix of resources for a utility.

9 In some cases, an IRP prescribes or authorizes specific actions. In others, an IRP serves as a guide for the utility

and the public utility commission when evaluating acquisiti on or implementation of specific utility resources or

programs. In such cases, the specific resource or progra m is approved through a PUC order that authorizes or

requires actions and identifies performance obligations. Thes e orders may or may not be fully consistent with

provisions in an IRP.

10 Vertically integrated utilities, even if they operate within the footprint of a competitive wholesale electricity

market, may self-schedule generation assets.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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12 often do not regulate th ese utilities. As a result, implementati on of a portfolio approach by these

entities would introduce practical enforceab ility considerations under a state plan.

III. Enforceability Considerations under Different State Plan Scenarios

As discussed in the preamble of the propos al, in section VIII.F.1, a state plan must

include enforceable measures. To ensure that its plan is enforceable, a state will need to:

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

enforceable obligations under the plan

 Include mechanisms for demonstrating compliance with plan requirements or

demonstrating that other binding obligations are met

 Provide a mechanism(s) for legal action if aff ected EGUs are not in compliance with plan

requirements or if other entities fail to meet enforceable plan obligations

As discussed in the preamble, responsible entities in an approvable state plan may include

an owner or operator of an affected EGU, other entities with responsibilities assigned by a state,

or the state itself. Other entities might include an en tity that is regulated by the state, such as an

electric distribution utility, or a private or pub lic third-party entity. State responsibility might

include obligations that are assumed directly by a state agency, authority, or other state entity to

carry out aspects of a state plan.

While this approach provides states with broad discretion to develop plans that best suit

their circumstances and policy objectives, assigni ng responsibility to other parties regulated by

the state, private or public third-party enti ties, or state entities raises enforceability

considerations. This section discusses how the general enforceability approach discussed in the

preamble, and described above, might apply in practice under different state plan approaches.

This section describes possible scenarios of responsible entities and legal mechanisms

and approaches that might be used to address en forceability considerations under different types

of state plans. These s cenarios were developed to capture th e range of entities that are currently

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

are subject to states requirements such as end- use energy efficiency resource standards (EERS)I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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13 or renewable portfolio standards (RPS). For each of these examples, this section describes

current legal relationships between these entities and the state, and discusses possible legal

instruments that might provide the state with the authority to ensure that obligations in a state

plan are met and to address failure to meet those obligations. The mechanisms discussed take

different forms, but would specify the three el ements described above: obligations, compliance

demonstration, and enforcement mechanisms. This section also discusses enforceability

considerations in cases where states act jointly through a multi-state plan.

A. Parties Regulated by the State other than Affected EGUs

One likely state plan scenario involves incl usion of enforceable obligations for stateregulated entities other than affected EGUs. An exam ple of a state-regulated entity that is not an

owner or operator of affected EGUs may be an electric distribution utility. 11 These entities are

typically regulated by a state public utility commi ssion. An example of an enforceable state plan

measure that might apply to an electric distribution utility is a compliance obligation under a

state end-use energy efficiency resource standard (EERS) or renewable portfolio standard (RPS),

or implementation of incentive programs for the deployment of end-use energy efficiency and

renewable energy technologies.

Another example is where a vertically integr ated, state-regulated utility implements a

portfolio of enforceable actions under a state plan , which may include actions that apply directly

to affected EGUs as well other actions such as end-use energy efficiency and renewable energy

deployment programs. While vertically integrat ed utilities may own and operate affected EGUs,

some of the measures implemented may require different enforceability mechanisms than an

emission limit applied to an affected EGU.

11 Electric distribution utilities are also often referred to as local distribution companies (LDCs). Here we refer to an

electric distribution utility as an entity that owns and oper ates an electric distribution network but is not the owner

and operator of EGUs. As discussed further, vertically integrated utilities own and operate electric distribution

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

to State Regulations

EERS and RPS requirements are typically implemented through state regulations, but

may also be implemented through a public u tility commission order. State EERS and RPS

regulations provide legal instruments generally comparable in enforceability to regulatory

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

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

include alternative compliance paym ent (ACP) provisions that prov ide the utility with the option

of making a payment in lieu of full compliance with the portfolio requirement. Thus, state EERS

and RPS mandates may not guarantee achievement of a given level of end-use energy efficiency

or renewable energy deployment during a plan performance period. 12

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

Integrated Resource Plan

A utility integrated resource plan (IRP) may include a number of direct and indirect

actions that affect EGU CO 2 emissions, and may also include compliance with EERS and RPS

regulations. Broadly, IRPs may prescribe or au thorize actions for which utilities can recover

capital investments and operating costs through regulated retail electricity rates. 13 This creates

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

For a state plan under this scenario, an enforceability consideration is whether an IRP,

and related public utility commission orders, must include additional requirements to implement

12 We note that some direct emission limits for CO 2 emissions include somewhat similar provisions. For example,

both the RGGI state CO 2 emission budget trading programs and the California GHG emission budget trading

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

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

regulations would need to be taken into account when projecting the CO 2 emission performance that will be

achieved by affected EGUs under the state plan.

13 In some cases, an IRP prescribes or authorizes specific actions. In others, an IRP serves as a guide for the utility

and the public utility commission when evaluating acquisiti on or implementation of specific utility resources or

programs. In such cases, the specific resource or program is approved through a PUC order that authorizes or

requires actions and identifies performance obligations. Thes e orders may or may not be fully consistent with

provisions in an IRP.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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15 certain actions, beyond denial of rate recovery or a change to utility tariffs if a utility fails to

meet specified obligations in the IRP. If so, this may require state legislation to provide

additional authority to state public utility commis sions in some states, or confer additional

authority to other agencies (e.g., a state environmental agency).

B. Private or Public Third-Party Entity not Regulated by the State

Another state plan scenario involves public or private third-party entities with

enforceable obligations under a state plan. A private or public third-party entity could be a utility

entity that is not regulated by a state public u tility commission, such as a municipal utility or a

utility cooperative. 14 It could also be a private non-profit en tity established to administer end-use

energy efficiency and renewable energy deployment programs. 15 In most cases, since they often

expend electricity ratepayer funds, such non-profit entities are created by state legislation and

overseen by state public utility commission s or state-regulated private utilities.

An appropriate legal instrument or agreement applicable to such entities included in a

state plan might include legal arrangements similar to those currently used to establish

independent entities that expend el ectricity ratepayer dollars in multiple states. For entities not

subject to state oversight, such a mechanism might also include mechanisms where an entity

voluntarily submits to the authority of a state, pursuant to state statutory or regulatory authority

specified in a state plan. Such agreements might be attached to a funding source. For example,

the entity would voluntarily submit to such authority as a condition of receiving certain funds,

such as state appropriated funds or funds coll ected through state-regulated electricity rates.

Alternatively, a municipal utility or utility cooper ative might voluntarily su bmit to state authority

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

application of certain direct CO 2 emission limits for affected EGUs owned and operated by such

entities through a state regulation. In some cases , new state statutory authority might be enacted

14 Here, “not regulated” refers to regulation of electricity rates by a state public utility commission. To the extent

that such entities are owners and oper ators of affected EGUs, these EGUs may be subject to state environmental and

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

under state law.

15 Examples include the Energy Trust of Oregon, the Delawa re Sustainable Energy Utility, and Efficiency Vermont.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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

entities under the plan.

An additional consideration is whether such le gal instruments or agreements, if related to

a renewable energy or end-use energy efficiency deployment program, should specify a stable

budget authority and funding source through each plan performance period. Such authority and

funding might be necessary to ensure that suitable funds are made available to achieve the level

of energy savings or renewable energy deployme nt projected in the state plan, which may be

necessary to achieve the level of emission performance by affected EGUs that is projected will

be achieved through implementation of the plan.

C. State Agency, Authority, or Entity

This state plan scenario involves a state entity with an enforceable obligation in a state

plan. For example, state authorities in some states implement renewable energy and end-use

energy efficiency deployment programs. 16 In this scenario, the requirement for the state entity

would be an enforceable component of the state plan.

One type of legal arrangement that might be applied under this scenario is legislation

directing state executive branch agencies or i ndependent state authorities to follow through on

obligations under a state plan.

Such legislation might provide independent legal authority under state law to compel

executive branch actions, or actions by independent state authorities under the plan, if

obligations are not met. Depending on the form of legislation, this could also provide citizens

with the ability to compel state action under stat e law, if obligations are not met under a state

plan. 17

16 A prominent example is the New Yo rk State Energy Research and Development Authority (NYSERDA), which

administers energy efficiency and renewable energy deployment programs.

17 We note that under the CAA, measures included in an ap proved 111(d) state plan woul d be federally enforceable

by EPA, and that citizens would also have the ability to file citizen suits to compel enforcement of state plan

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17 An additional consideration is whether such legal arrangements, if related to a renewable

energy or end-use energy efficiency deployment program, should also specify a stable budget

authority and funding source through the plan performance period, or other provisions, to ensure

that programs are implemented as projected under the state plan.

D. Multi-State Approaches

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

For these multi-state approaches, states would demonstrate emission performance from

affected EGUs in aggregate jointly with partner states. For states participating in a multi-state

approach, the individual state performance goals in the emission guidelines would be replaced

with an equivalent multi-state performance goal. For example, states taking a rate-based

approach would demonstrate that all affected E GUs subject to the multi-state plan achieve a

weighted average CO 2 emission rate that is consistent, in aggregate, with an aggregation of the

state-specific rate-based CO 2 emission performance goals establis hed in the emission guidelines

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

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

a total tonnage of CO 2 emissions consistent with a translat ed multi-state mass-based goal. This

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

rate-based CO 2 emission performance goals established in the emission guidelines that apply to

each of the participating states.

1. Multi-State Emission Budget or Rate-Based Emission Trading Programs

The Regional Greenhouse Gas In itiative (RGGI) is an example of a multi-state approach

to regulation of CO 2 emissions. Through this initiative, nine states are currently implementing

coordinated CO 2 emission budget trading programs. The program works as a coordinated

regional whole through a shared emission and allowance tracking system and allowance auction

process, but is implemented in accordance with materially consistent stand-alone state

regulations and individual statutory au thority. These regulations recognize CO 2 allowances

issued by other participating states for use by affected EGUs when comp lying with each state’sI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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18 emission limitation, but contain all the nece ssary components to administer the program

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

regionally, each CO 2 emission budget trading program regula tion is enforceable against affected

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

As a result, a multi-state emission budget trad ing program approach, such as RGGI, is

enforceable in practice at the state level. A multi-state rate-based emission trading program could

also be established in much the same manner as a multi-state emission budget trading program,

and could therefore be enforceable at the state level. 19

2. Multi-State Portfolio Approaches

A multi-state portfolio approach could intr oduce novel enforceability considerations. If it

were based on interdependent emission reduction strategies among states that are not tied to

emission limits that directly apply to affected EGUs, the emission performance of affected EGUs

in one participating state may be dependent, in pa rt, on actions taken in other participating states.

If a state (or states) failed to implement commitmen ts under the multi-state plan, this raises the

question of whether the EPA should address non-performance of one or more participating states

in the context of failure to achieve the required level of multi-state emission performance under

the plan, or instead enforce actions at the individua l state level for those states that are failing to

meet commitments under the multi-state plan.

18 The emission limitation consists of a requirement to submit CO 2 allowances equal to reported CO 2 emissions

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

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

CO 2 emission constraint is regional, based on the sum of state CO 2 emission budgets.

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19 IV. Incorporating End-Use Energy Efficiency and Renewable Energy Programs and

Measures under a Rate-Based Approach

A. Concept of Adjusting EGU CO 2 Emission Rates based on the Effects of End-Use

Energy Efficiency and Renewable Energy

As discussed in the preamble, in section VIII.F.3, the EPA is proposing that RE and

demand-side EE requirements, programs, and measures may be incorporated into a rate-based

plan approach. 20 Measures that avoid CO 2 emissions from affected EGUs, such as quantified and

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

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

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

administratively adjusting the average CO 2 emission rate of affected EGUs when demonstrating

achievement of the required emission rate performance level in a state plan.

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

through actions at the EGU, 21 as well as through the use of credits 22 for actions that occur

elsewhere in the interconnected electricity system that avoid CO 2 emissions from affected EGUs.

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

average CO 2 emission rate of affected EGUs through a similar process when demonstrating

achievement of the required emission rate performance level in the state plan.

This section explores in depth the mechanic s and implications of the different possible

approaches for adjusting CO 2 emission rates that are summarized in the preamble. Aspects of

this discussion may apply to both retrospective demonstration of CO 2 emission performance

20 The EPA is also proposing that RE and demand-side EE measures could be used under a mass-based portfolio

approach in an approvable state plan. However, the focus of this section is limited to application of such measures

under a rate-based approach.

21 This could include an individual affected EGU or group of affected EGUs if a rate-based averaging or trading

approach is used.

22 These credits could be tradable, or represent non-tradable credits administratively apportioned to affected EGUs.

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

performance by affected EGUs included in a submitted state plan.

B. Approaches for Adjusting EGU CO 2 Emission Rates

As discussed in the preamble, cred its or adjustment to an EGU CO 2 emission rate, based

on the effect of RE and demand-side EE programs and measures, might represent avoided MWh

of electric generation or avoided tons of CO 2 emissions. 23 If adjustment or credits represent

avoided MWh, they would be added to the denominator of the lb CO 2 /MWh emission rate when

determining an adjusted lb CO 2 /MWh emission rate. If adjustment or credits represent avoided

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

CO 2 /MWh emission rate. The approach chosen could affect the amount of credit or adjustment

provided for RE and demand-side EE programs and measures. These implications are discussed

below.

1. Adjustment of CO 2 Emission Rate based on Avoided MWh

One approach is to adjust an EGU’s CO 2 emission rate based on avoided MWh of

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

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

CO 2 emissions come directly from the particular affected EGU (or group of EGUs) to which the

adjustment or credits are applied. It assumes, in effect, that an additional emission-free MWh is

being generated by that respective EGU, and that the RE or demand-side EE measure reduces

CO 2 emissions from that individual EGU or group of EGUs. 25 In practice, the average or

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

CO 2 emissions from the generating sources being displaced by a MWh of energy savings or a

23 The preamble solicits comment on the appropriateness of these different approaches, which are further elaborated

in this section.

24 It should be noted that this was the process used by EPA for incorporating end-use energy efficiency, renewable

energy, and nuclear energy when calculating state CO 2 emission performance goals for affected EGUs. As discussed

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

measures in a rate-based state plan.

25 As a result, the assumed avoided CO 2 emissions from an individual MWh of energy savings or generation from

renewable energy will differ based on the reported CO 2 emission rate of the individual EGU to which the MWh is

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

CO 2 emissions derived by adjusting the MWh output of an affected EGU. The following

examples highlight these concepts.

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

1,000 MWh. Also assume that 1,000 emission-free MWh credits for the effect of demand-side

EE measures are added to the denominator when calculating the EGU’s adjusted CO 2 emission

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

CO 2 emission rate of 750 lb CO 2 /MWh. In this example, each MWh credit represents 750 lb of

avoided CO 2 emissions.

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

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

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

example, each MWh credit represents 1,000 lb of avoided CO 2 emissions.

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

An alternative approach is to provide an adjustment to the CO 2 emission rate of an EGU,

or cohort of EGUs, based on the estimated CO 2 emissions that are avoided in the power pool or

identified region as a result of RE and demand-side EE programs and measures. This approach

acknowledges that the avoided CO 2 emissions may come from the electric power pool or other

identified region as a whole, rather than an individual EGU. The avoided CO 2 emissions are

determined based on the MWh saved or generated, multiplied by a CO 2 emission rate for the

power pool or region.

This CO 2 emission rate could be based on the average or marginal emission rate in the

power pool, region, or state. A marginal avoided emission rate represents the generation that is

displaced at the margin for every MWh saved or generated through an RE or demand-side EE

program or measure. An average avoided emision ra te is based on either all fossil generation in a

region or total generation. This approach assumes that every MWh saved or generated equally

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22 Another approach that has been suggested by some stakeholders is crediting or

adjustment based on the level of the rate-based emission limit for affected EGUs (or the overall

rate-based level of emission performance for affected EGUs specified in a state plan). For

example, under this approach, if the emission rate limit were 1,500 lb CO 2 /MWh, one MWh of

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

representing 1,500 lb of CO 2 that could be subtracted from the numerator of an EGU’s CO 2

emission rate. This approach assumes that affected EGUs jointly emit CO 2 from the stack on an

average basis at this required compliance level (i.e., consistent with a “closed” averaging

system), and that a MWh saved or generated avoids CO 2 emissions from affected EGUs at this

average compliance level. 26

3. Other Considerations

Some of the CO 2 emissions avoided through RE and demand-side EE measures may be

from non-affected EGUs. This may result because affected EGUs are only a subset of the fossil

fuel-fired EGU fleet, which also includes (or will in clude) existing non-affected fossil fuel-fired

EGUs, such as simple-cycle combustion turbines used to meet peak demand, as well as new

fossil fuel-fired EGUs subject to emission standards under CAA section 111(b). Furthermore, as

the fleet capital stock slowly turns over, affect ed EGUs under section 111(d) will comprise a

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

addressed in a state plan when crediting or adjusting CO 2 emission rates of affected EGUs based

on the effects of RE and demand-side EE measures. The approaches described in more detail

later in this section may be able make these di stinctions between affected and non-affected fossil

fuel-fired EGUs.

26 This outcome might be expected in a closed averaging system, without the use of crediting or adjustment for the

avoided emission effects of RE and demand-side EE meas ures. In this instance an EGU that emitted above the

compliance rate would need to averag e its performance with (or submit tradable credits obtained from) an EGU that

performed below the required rate. On balance, all EGUs subject to the emission rate limit would perform at or

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23 C. Methods and Tools for Quantifying Avoided CO 2 Emissions from End-Use Energy

Efficiency and Renewable Energy

1. Introduction

There are a number of approaches for quantifying the avoided CO 2 emissions resulting

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

measures 27 in the electric sector. These approaches ra nge from the application of basic avoided

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

rates have often been used for rough approximations of CO 2 emissions avoided from reduced

electric energy use. 29 An annual average avoided emission rate assumes that EE/RE programs

and measures reduce electric generation from all generating types on a proportional basis

consistent with the generation mix in a region. A marginal emission rate represents the emission

rate of an electric generating unit (EGU) or cohort of EGUs likely to be displaced by EE/RE

measures (i.e., a marginal avoided emissions rate), based on the last unit(s) to come online to

meet electricity load and the first unit(s) to be brought offline when electricity load is reduced.

The primary question underlying estimating CO 2 emissions reductions from EE/RE

measures is the determination of which electric generators will be displaced (i.e. , cease

generation or reduce generation output) in the presence of incremental EE/RE. This section

briefly describes a range of avoided emission rates approaches, their underlying assumptions,

and considerations associated with the use of different avoided emission rate approaches.

2. Average Emission Rate Approach

An average emission rate (typically expressed in tons of CO 2 /MWh) is usually

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

generation. The rate (r

avg ) is calculated as:

27 As used here, the term “EE/RE measures” refers to any program actions or regulatory requirements that result in

the increased use of energy-efficient equipment or practices, or renewable energy generating resources.

28 Electric sector models include simulation dispatch m odels (i.e. production-cost models) and capacity expansion

planning models.

29 See, for example, EPA “Household Carbon Footprint Calculator,” available at

http://www.epa.gov/climatechange/ghgemissions/ind-calculator.html

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24 ݎ ௔௩௚ ൌ ∑ ݁ ௜ ௜

∑ ݃ ௜

௜

Where:

e = annual emissions (tCO 2 ) from all sources i and

g = annual generation (MWh) from all sources i

.

Because the average emission rate puts the sum of all generation in the denominator (as MWh),

including nuclear, hydroelectric, and renewable generating resources, the rate fundamentally

assumes that EE/RE reduces all generating types by an equal proportion, regardless of their type

or contribution to the margin. 30 EGUs are generally dispatched on an economic merit order,

where the least-cost EGUs (on a variable cost basis) are dispatched first, and higher cost

resources are dispatched later. Since nuclear, hydr o, wind, and solar resources operate at a very

low cost, 31 they are generally dispatched before most fossil units. 32 Under current and historical

operating conditions, there are few circumstances in which non-fossil resources reduce output in

the presence of lower demand. As a result, in states with a moderate contribution of non-emitting

resources to total generation, the average emission rate may be lower than could reasonably be

expected for reductions from EE/RE programs and measures. 33 Conversely, in states that have

significant baseload fossil generation and few no n-emitting resources, a state-average emission

rate may reflect an emission rate that is too high. This may occur by incorporating emissions

from coal-fired EGUs that are less likely to reduce generation with a reduction in electricity load,

compared with other lower-emitt ing fossil fuel-fired EGUs.

30 In other words, a two-percent reduction in energy use would cause all EGUs in the system to reduce generation

output by two percent, including coal, gas, nucl ear, hydro, and renewable generating resources.

31 For representative variable costs for new EGU, see supporting documentation for the Electricity Market Module

of the Annual Energy Outlook (AEO) 2013, table 8.2., “Cos t and performance characteristics of new central station

electricity generating technologies”. Geothermal, wind, and solar generating resources are assumed to have a

variable operating cost of $0/MWh. Hydroelectric generati ng resources have an assumed variable operating cost of

$2.60/MWh and incur no fuel cost, while nuclear generating resources have an assumed variable operating cost of

$2.10/MWh (exclusive of fuel costs). In contrast, gas a nd coal units are assumed to have variable operating costs

from $3-$7/MWh (exclusive of fuel costs.

32 The exception is rare curtailment events for renewable resources when more energy is produced than required, and

due to operational constraints, where wind turbines are stal led to maintain system energy balance. Renewable energy

generators, such as wind and solar, are sometimes referred to as “non-dispatchable” resources, since the renewable

energy resource is intermittent and these generators cannot be called upon to run when the renewable energy

resource is unavailable. However, here we refer to ec onomic dispatch of these resources at times when the

renewable energy resource is available. In these instances, th ese generators are often one of the first resources to be

called upon, due to their low variable operating costs.

33 Counting hydroelectric, nuclear, and renewable resources in the denominator would re nder the emissions rate too

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25 3. Marginal Emission Rate Approach

A marginal emission rate represents the emi ssion rate of the EGU or cohort of EGUs

likely to be displaced by EE/RE ( i.e., an avoided emission rate). A marginal unit is the highestcost unit dispatched at any point in time. 34 Under most circumstances, and at any given time, the

marginal unit is the last unit to be brought online to meet electricity demand and the first unit to

be brought offline when electricity load is reduced. Due to constraints on generating unit ramp

rates 35 and transmission availability, it is not unc ommon for multiple units to be dispatched

incrementally simultaneously, thus creating a cohort of marginal units. Marginal unit(s) change

on a moment-to-moment basis, determined by load requirements and the variable cost of each

unit available to generate another unit of power. A marginal unit can either be a unit brought

online to meet load or may be an EGU that is alr eady operating, but that is dispatched at a greater

level of output to meet load.

The marginal emission rate ( r marginal ) can be expressed for any given hour ( t ) as a function

of the difference between two distinct cases – the reference case ( i.e., in the absence of

incremental EE/RE programs and measures) and the change case, where the EE/RE programs

and measures have been implemented. A formula describing this rate is written as follows:

ݎ ௟௔௡௜௚௥௔௠,௧ ൌ ∑ ݁ ௥௘௙,௜,௧ ௜ െ ∑ ݁ ாாோா,௜,௧ ௜

∑ ݃ ௥௘௙,௜,௧

௜ െ ∑ ݃ ாாோா,௜,௧ ௜

Where:

e ref and e EERE = emissions (tCO 2 ) from EGUs i in hour t in the reference case ( ref ) and the change

case ( EERE ), respectively; and

g ref and g EERE = generation (MWh) from EGUs i in hour t in the reference case ( ref ) and the

change case ( EERE ), respectively.

34 See EPA’s Roadmap for Incorporating EE/RE Policies and Programs in State Implementation Plans: Appendix B,

available at http://www.epa.gov/statelocalclimate/doc uments/pdf/overview_paper_4-28-2011.pdf

35 Ramp rate refers to the ability of an EGU to respond to increasing load, based on its ability to increase output.

Ramp rates are typically determined by technology type, wi th some technologies, such as combustion turbines, able

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

element in determining marginal emissions reductions . In order to obtain a valid estimate of the

emission reduction effect of an EE/RE program, an annual marginal avoided emission rate

should be calculated that reflects the EE/RE program’s load impact shape and magnitude. This

annual marginal avoided emission rate may then be applied to other EE/RE programs with

similar load impact shapes and magnitudes. The ma rginal emission rate is highly time sensitive,

as are the impacts of EE/RE programs and measur es. For example, the EGU that is on the margin

and is most likely to be displaced from EE/RE in each hour of the year. In addition, different

EE/RE programs may have very different load impact shapes, reducing energy requirements in

different hours of the year. The interaction between the pattern of EGUs on the margin and the

load impact shape of EE/RE programs and measures results in a specific marginal avoided

emission rate. Applying an annual marginal avoided emission rate calculated based on the impact

of one specific set of EE/RE programs and measures to another set of EE/RE programs and

measures that is substantively different in timi ng or magnitude of energy savings or generation

(i.e ., with a different load impact shape and magnitude) may result in erroneous results ( i.e. the

assumption that the wrong EGUs are displaced). 37

Several mechanisms have been proposed to estimate the marginal emission rate without

the use of a formal electric dispatch simulation model. These mechanisms rely on historic hourly

generation and emissions data, collected by EP A’s Clean Air Markets Division, to estimate

hourly marginal emissions rates for a past historical year. The benefit of these mechanisms is that

they are simple to apply, but (a) are difficult to verify or validate without the benefit of a formal

model and (b) rely on historical data and patterns of dispatch, which may not represent future

patterns of dispatch.

36 The load impact shape of an EE/RE program or measure is the hourly (or, if necessary, daily or seasonal) pattern

of either energy savings from an EE program or measure, or generation from an RE generator that is supplied to the

grid.

37 For example, an EE program focused on measures that reduce peak electricity demand, such as more efficient air

conditioning, or a solar RE program, may result in significan t reductions in electricity use from the grid during peak

demand hours, and little electricity use reduction during ov ernight “trough” hours. In contrast, an industrial EE

program may result in a relatively constant electricity load reduction over most hours. An EE program focused on

peak reduction measures may reduce generating output from primarily peaking units, while an EE program targeting

EE measures with a more constant load impact shape ma y significantly reduce baseload generation during overnight

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27 4. Methods and Tools for Estimating Avoided CO 2 Emission Rates and Avoided

CO 2 Emissions

4.1. Calculation Tool Method

The EPA has developed a user-friendly tool to estimate the emission reduction impacts of

EE/RE requirements, programs and measures. The AVoided Emissions and geneRation Tool

(AVERT) 38 was developed to help air quality planners quantify NOx and SO 2 emission impacts,

as specified in EPA’s Roadmap for Incorporating EE/RE Programs in NAAQS SIPs. 39 AVERT

can also be used to quantify the displaced CO 2 emissions of EE/RE measures within the

continental United States.

The AVERT method uses historical hourly emissions rates based on recent the EPA data

on fossil fuel-fired EGUs’ hourly generation and emissions reported through EPA’s Acid Rain

Program. 40 This method couples historical hourly generation and emissions with the hourly load

reduction profiles of EE/RE programs and measures to determine hourly emissions reductions on

the margin. AVERT can be used to estimate EE/RE-related emissions reductions in a current or

near-future year. However, AVERT estimates for current or future years are based on historical

behavior rather than projected economic behavi or. As a result, AVERT does not use projections

of future fuel or electricity market prices that affected EGU dispatch, and is therefore not an

appropriate tool for longer-term projections.

Users of AVERT can analyze how the different load profiles of a variety of EE programs

and measures, as well as wind and solar technologies, affect the magnitude and location of CO 2

emissions at the county, state, and regional level. AVERT has a flexible framework with a

simple user interface designed specifically to meet the needs of state air quality planners and

other interested stakeholders.

38 More information about AVERT, including documentation and a user’s manual, is available at

(http://www.epa.gov/avert).

39 See Appendix I of the Roadmap for Incorporating Energy Efficiency/Renewable Energy Policies and Programs

,

available at http://epa.gov/airquality/eere/pdfs/appendixI.pdf ), for details about how this approach can be used in

the different NAAQS SIP pathways.

40 http://ampd.epa.gov/ampd/.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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

and emissions data, which can be used to derive a marginal avoided CO 2 emission rate.

However, AVERT does not quantify average emis sions rates. AVERT approximates historical

dispatch behavior using a statisti cal algorithm. It does not repres ent transmission constraints, or

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

historical marginal CO 2 emissions reduction from existing EE/RE programs or measures, a user

would input the MWh related to results from EE/RE programs or measures (representing either

MWh of electricity savings or MWh of generation) in a representative historical baseline year as

a positive increment to electricity load, and record the emissions incrementally added in the

tool. 41 The calculated marginal CO 2 emission rate is the incremental CO 2 emissions added by

AVERT, based on historical EGU dispatch pattern s, divided by the incremental MWh of EE/RE

savings or generation input to AVERT as an increase in electricity load. This approach reflects

the marginal impact of EE/RE measures based on historical recorded patterns of emissions and

generation. 42

4.2. Electricity Sector Modeling Method

Quantification of avoided CO 2 emissions from EE/RE requirements, programs, and

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

calculate avoided CO 2 emissions by comparing actual realized EGU CO 2 emissions to projected

EGU CO 2 emissions that would have occurred in a historical reference case that does not include

implementation of the EE/RE that is being evaluated. The appropriate choice of model depends

on the look-back period. For short look-back periods of one to three years, an electricity system

simulation dispatch model can de termine the marginal generation contribution to emissions in a

41 Because AVERT represents a historical baseline year, EE and RE programs that occurred in a past year are

already recorded by the statistics of AVERT. To estimate the emissions impacts of historic EE/RE programs, a user

would increase the load by the EE/RE in crement to estimate what generation and emissions would have been in the

reference case look-back year.

42 AVERT reflects fuel and emission control technologies to the extent they have influenced dispatch during the

base year chosen. However, AVERT cannot change dispat ch based on future economic or regulatory conditions,

such as expected fuel prices, emission allowance prices, or specific emissions limits. AVERT should not be used for

this type of analysis. When used to review historical da ta, AVERT will capture the impact of historical fuel prices

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29 historical reference case ( i.e. absent incremental EE/RE programs). 43 Over the short term,

simulation dispatch models properly account for EGU economic dispatch considerations, such as

fuel and emission allowance prices, and operational constraints, such as ramp rates, outages, and

heat rate curves. Look-back periods beyond three to five years would benefit from use of a

utility-scale capacity expansion and dispatch plan ning model to understand the change in build

out of new generating capacity, as well as transm ission and distribution infrastructure, and its

impact on generation between the historical reference case and actual realized historical

outcome.

Electricity System Simulation Dispatch Models

Quantifying the CO 2 emissions reductions achieved by EE/RE measures through

modeling of a near-term look-back period require s a counterfactual historical reference case

model run, which examines how the electric system would have operated in the absence of the

EE/RE emission reduction measures under considera tion. The emissions projected in this model

run may be compared against actual realized emissions during the historical period. The lookback model should be calibrated by running the same model with the EE/RE measures in place

and comparing the outcome of that model against realized generation and emissions at an

appropriate spatial scale. 44

Simulation dispatch models can be readily run for historical years provided they are

loaded with the accurate input assumptions, incl uding actual historic fuel costs, emission

allowance prices, and transmission constraints. Wh ile these models will not choose economically

optimal EGU retrofit or retirement decisions, they will provide a change in EGU dispatch and the

associated change in emissions across a large region in a more detailed manner than capacity

expansion planning models.

43 “Reference case” here refers to the case in which addi tional incremental carbon emi ssions reduction mechanisms

are not employed, in this case resulting from EE/RE programs and measures.

44 Generally, simulation models will not capture exact output of individual EGUs relative to reality due to a variety

of factors, including outages and other non-economic considerations not reflected in the model. Therefore, a

comparison at an individual EGU scale may not be meani ngful, but aggregate emissions at a state or regional scale

should be expected to be comparable.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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30 Simulation dispatch models may be most relevant as part of ex-post plan reporting, for

estimating the avoided CO 2 emissions from affected EGUs that occurred as a result of EE/RE

measures included in a plan, during a specified plan reporting period.

Utility-Scale Capacity Expansion and Dispatch Planning Models

Quantifying the CO 2 emissions reductions achieved by EE/RE measures through

modeling over a longer-term look-back period requires a counterfactual historical reference case

model run, which examines how the electric syst em would have operated and have been built

out, in the absence of the EE/RE measures under consideration. The critical difference between

this type modeling approach and the use of a simulation dispatch model is the assessment of

changes made at the “build margin” – i.e.

, new additions to generating capacity that may have

been avoided or compelled, or retirements of existing units that may not have occurred in the

reference case. The emissions projected in this model run may be compared against actual

realized emissions during the historical period . The look-back model should be calibrated by

running the same model with the EE/RE measures in place and comparing the outcome of that

model run against actual realized generation and emissions at an appropriate spatial scale.

Capacity expansion and dispatch planni ng models could be run for a longer-term

historical period to better reflect what the el ectricity system would have looked like in the

absence of the EE/RE measures. When EE or RE resources have been added over the course of

three to five years, these models will reflect ho w these resources have avoided new power plants,

retrofits, or fuel switch decisions. Some models may also be able to reflect avoided transmission

investments.

Capacity expansion and dispatch planning models may be more relevant than simulation

dispatch models for projecting the emission perform ance that will be achieved by affected EGUs

under a plan. As discussed below, these models are able to assess both the “operating” and

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31 5. Considerations Associated with use of an Avoided Emissions Rate

Operational versus Build Margin

Avoided emission rates approaches that do not include a capacity expansion model all

assume that EE/RE measures only impact the operational margin – i.e., they impact moment-tomoment operations of EGUs in the existing grid. While this is true, deployment of EE/RE over a

period of years may have impacts beyond the operational margin. Deployment of significant

EE/RE measures over time often impacts decision s to build new fossil ge nerating capacity, retire

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

These different decisions about what infrastructu re to build or retire are known as the “build

margin,” and may ultimately have a greater impact on long-term emissions outcomes than the

operational margin.

While a new wind farm brought online next year has an impact on patterns of generation

from existing fossil EGUs, decadal-scale planning associated with a policy meant to encourage

EE/RE has an impact on the choice of whether or not to pursue the construction of new fossil

generating capacity. A utility pursuing aggressive EE/RE programs may avoid the construction

of new fossil generating capacity and expansion of transmission and distribution capability, and

may even allow the utility to retire non-economic generating units no longer required for

generation or reliability purposes.

The use of an avoided emissions rate calculated based on the operational margin alone

may fail to represent the impact of EE/RE measures that occur at the build margin. This

differentiation is particularly important in re gions where the pursuit of EE/RE measures may

result in the retirement of high-emitting, non-economic generating assets. The use of a capacity

expansion and dispatch planning model would he lp accurately assess avoided emissions due to

changes at both the build and operational margins.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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

The electric system is not confined by stat e boundaries, and emissions displaced by

EE/RE measures may occur over a wide geographic area, 45 including outside of the state that

implemented the EE/RE measures. Without the use of a simulation dispatch model (or, under

some circumstances, use of a tool such as AVERT) 46 it can be challenging to attribute emissions

reductions that occur within th e implementing state versus emissions reductions that occur across

state boundaries. If a state sought to recognize the effect of EE/RE measures and quantified

emissions reductions using an approach that did not account for avoided emissions at an

appropriate spatial scale, it may inappropriately account for emissions reductions that occur in

other states, or conclude that all emissions reductions occur within the state’s boundaries. 47 In

interconnected areas in which some states pursue mass-based emissions reductions approaches

through their state plans while other states pursue rate-based approaches that include adjustment

or crediting for avoided CO 2 emissions from implementation of EE/RE measures, avoiding

double-counting of emission eff ects among states will be an important consideration when

quantifying the avoided emissions resulting from EE/RE measures. These considerations are

discussed below in section VII of this TSD.

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

Renewable Energy Programs and Measures

As discussed in the preamble, in section VII.F.4, a key consideration for state plans is the

process and requirements for quantifying, monito ring, and verifying the effect of renewable

45 See California Energy Commission, Emissions Reductions from Renewable Energy and Energy Efficiency in

California Air Quality Management Districts (2011), available at

( http://ucciee.org/downloads/CAEmissionsReductions.pdf ).

46 AVERT captures the magnitude of in-state versus out-of -state emissions reductions, but may not be an accurate

assessment tool for edge-cases – i.e. states that fall near the boundaries of the AVERT regions – because AVERT

does not capture inter-regional transmission.

47 In the simplest case, a state without any fossil genera ting capacity that implements EE/RE measures would cause

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

predominantly baseload fossil generation may also cause littl e in-state emissions reductions from implementation of

EE/RE measures because those emissions reductions may occur at marginal generators located outside of the state.

Conversely, a state with significant marginal fossil gene rating capacity might realize reductions in emissions from

EE/RE measures implemented in other states. These complications may arise regardless of if a state is a net importer

or net exporter of energy. The key differentiation is if th e state’s EGUs are generally on the margin relative to

interconnected EGUs in neighboring states. Comment [A5]: 2. Can renewable energy that

is physically located in a state with a mass

‐ based

policy be used for out

‐ of

‐ state compliance in a

state with a rate

‐ based policy?

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.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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

savings. 48 In the preamble, the EPA seeks comment on the suitability of current state and utility

quantification, monitoring, and verification a pproaches 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 pro cedures, should be required in an approvable

state plan. The preamble also discusses gene rally 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 CO 2 emission

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

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

through CO 2 emission monitoring, reporting, and record-keeping requirements applied to

affected EGUs. However, for states implementi ng a rate-based plan approach, an approvable

plan will need to include quantification, monito ring, 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 ev aluation 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 impl ementing a rate-based emission limit approach that provides

for adjustment of CO 2 emission rates based on the effect of end-use en ergy efficiency and renewable energy, as well

as states implementing utility- or state-driven portfolio ap proaches that incorporate e nd-use energy efficiency and

renewable energy requirements and programs.

49 There could be exceptions, for example where a st ate plan includes acknowledgement of avoided CO 2 emissions

that occur outside state borders as a result of state plan measures. See section VII of this TSD for further discussion

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34 based on multiple factors, including the measure and program type being evaluated, the level and

nature of regulatory oversight, the degree of stat e and utility experience with these measures and

programs, and the overall magnitude of program impacts.

This section of the TSD discusses current st ate and utility evaluation, monitoring, and

verification approaches for end-use energy efficiency and renewable energy programs and

mandates. This section also discusses the potential suitability of these approaches in the context

of an approvable state plan, and whether harmon ization of state approaches, or supplemental

actions and procedures, might be warranted in an approvable state plan. In particular, this section

discusses considerations related to the establishment of 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 st ate 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 establis hed nationally for quantific ation, 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 meas ures, 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.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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

1. Introduction

For rate-based state plans, a key element of the plan is a demonstration of how the state,

and related entities with enforceable obligations under the plan, will measure and verify energy

savings to be achieved the through the implementation of end-use energy efficiency measures

incorporated in the plan. 50 In the context of demand-side energy efficiency programs currently

overseen by state PUCs, this function is typically addressed through an evaluation, measurement,

and verification plan (EM&V plan). This sec tion discusses current state and utility EM&V

practice for end-use energy efficiency programs and discusses considerations related to 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 verifica tion (EM&V) industry. This industry includes

many professional firms, protocols and guid elines, training and certification programs,

regulatory oversight, and established conferences with a rich library of published reports and

publically available data and analyses.

State agencies responsible for planning, implementing, and evaluating demand-side

energy efficiency programs and polici es utilize EE savings values, as follows: 52

50 In this section we use the term “end-use energy efficien cy measure” or “energy efficien cy measure” to refer to an

end-use energy efficiency requirement (such as an EERS), and energy efficiency program, or individual installed

energy efficiency measure, such as installation of an energy-efficient air conditioner through an energy efficiency

program.

51 National Energy Program Fact Sheet on the President's Program, April 20, 1977.

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

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

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36  Projected savings: values reported by a program implementer or administrator before the

efficiency activities are completed

 Claimed savings: values reported by a program implementer or administrator after the

efficiency activities have been completed, prior to independent evaluation of savings

 Evaluated savings: values reported by an in dependent third-party evaluator after the

efficiency activities and an impact evaluation have been completed.

Both claimed and evaluated energy savings involve real-time and/or retrospective

assessments of the performance and implementation of an energy efficiency program or a

portfolio of programs. Important impacts for evaluation include energy and demand savings and

non-energy benefits (e.g., avoided emissions, health benefits, job creation and local economic

development, energy security, transmission and distribution benefits, and water savings). Impact

evaluations also support cost-effectiveness analys es aimed at determining the value of energy

efficiency programs to utility cu stomers and identifying relative program costs an d benefits of

energy efficiency compared to other energy resources, including both demand- and supply-side

options.

Regardless of how the energy savings of an energy efficiency measure are determined, all

energy savings values are estimates of savings and not directly measured. Savings are

determined by comparing energy use after an ener gy efficiency project or measure is installed

(the reporting period) with what is assumed to be the energy use in the absence of the project or

measure (the “counterfactual” scenario, or baseline). Savings therefore depend critically on

baseline assumptions, which are necessarily estimated with varying degrees of accuracy. Figure

1-1 illustrates this concept.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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

3. Current EM&V Practices in States

3.1 EM&V for Demand-Side Energy Efficiency Programs Overseen by State PUCs

Current practice with EM&V for demand-side energy efficiency programs in the U.S. is

primarily defined by state utility commission (PUC) 54 requirements for customer-funded

efficiency programs. The level of PUC oversight varies from state to state, but this oversight

process has generated the majority of the industry guidance and protocols for documenting

energy savings from energy efficiency programs. Typically, impact evaluation reports are

prepared based on the requirements established by PUCs and submitted (usually annually) for

PUC review, approval, and use in resource planning and performance assessment. According to a

recent survey, most states (79 percent) rely on independent consultants and contractors to

conduct evaluations, while some states (21 percent) use utility and/or government agency staff. 55

53 Ibid.

54 In some states these government entities are referred to as a public service commission (PSCs) or board of public

utilities (BPU), as well as other names.

55 Kushler, M.; Nowak, S.; Witte, P. , A National Survey of State Policies and Practices for the Evaluation of

Ratepayer-Funded Energy Efficiency Programs, American Council for an Energy-Efficient Economy (ACEEE)

(February 2012), Report Number U122 Available at http://www.aceee.org/ research-report/u122.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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38 The range of EM&V budgets varies signifi cantly between states, typically from two

percent to six percent of total energy efficiency program expenditures. 56 The average EM&V

budget in 2011 was about 3.6 percent of program expenditures. Reasons for this disparity may

include the fact that as states expand energy efficiency programs, they may implement more

complex programs, which require additional EM&V. EM&V effort in states also typically

increases as the magnitude of program expenditures and energy savings impacts increase, and as

states and utilities gain experience in im plementing energy efficiency programs.

States at the low end of this EM&V expenditure range typically rely heavily on deemed

savings approaches, which are a common and relatively low-cost strategy for documenting

energy savings. Deemed savings are measure-sp ecific stipulated values based on historical and

verified data (in some cases using the results of prior EM&V studies). Unlike other EM&V

approaches, with deemed savings there are no – or very limited – measurement activities.

Instead, only the quantity of energy efficiency measures implemented is verified (e.g., number of

motors installed correctly, number of energy-efficient air conditioners that were purchased using

a program rebate). The verified installed energy efficiency measures are then multiplied by the

estimated (or deemed) energy savings per measure to derive energy savings for each measure

and energy savings for the total number of measures installed through an energy efficiency

program. The use of deemed energy savings is only considered appropriate for efficiency actions

with well-known characteristics. A variant of this approach is the deemed savings calculation

,

which involves the use of one or more agreed-upon (stipulated) engineering algorithms used to

generate energy and/or demand savings associated with energy efficiency measures. These

calculations may include predetermined assumptions for one or more parameters in the

algorithm, but typically require users to input data associated with the actual installed measure

into the algorithm. 57

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

2011. Consortium for Energy Efficiency. www.cee1.org/files/2011 CEE An nual Industry Report.pdf

. 57 Examples of equipment types that are commonly evaluate d using deemed savings values and calculations include

energy-efficient washing machines, computer equipment, and refrigerators, and lighting retrofit projects with wellunderstood operating hours. For deemed savings calculati ons, evaluators collect information about the actual

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

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39 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 a ssumptions, and input variables. Some of these

differences are expected based on relevant differences in weather and baseline assumptions (e.g.,

existing building stock and common practices vary from one state to another). However, other

differences are related to out-of-date input assu mptions and calculation errors. In the context of

state plans, this variation, and in particular data quality issues with some TRMs, raises

consideration of whether complete reliance on ex isting TRM resources for state plans is prudent

and appropriate, including how such reliance could or should be circumscribed.

In addition to the use of deemed savings, states on the higher end of the EM&V

expenditure range rely to a greater extent on a variety of direct measurement approaches for

documenting energy savings. Rather than mandating which EM&V methods must be used in a

particular situation, PUCs typically allow uti lities 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

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40 from a range of appropriate EM&V approaches that are consistent with standard practice in the

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

by an independent, third-party evaluator, throu gh a process that is unbiased, uses technically

rigorous methods, effective peer review, and is subject to public review and comment. In

addition, energy savings are frequently certified by the PUC as compliant with requirements

defined in a pre-approved EM&V plan.

EM&V requirements in states with the most experience implementing and overseeing

energy efficiency programs are typically based upon the following industry best practices:

 Use of one or more of the industry-standard EM&V protocols or guidelines (listed

below), as well as the use of deemed sa vings values for well-understood energy

efficiency programs and measures

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

 Involvement of stakeholders and solicitation of expert advice regarding EM&V processes

and resulting energy savings impacts.

 Conduct of EM&V activities (e.g., direct equipment measurements, application of

deemed savings, and reporting of impacts) on a regular basis.

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

Despite this well-defined and generally accepted set of industry best practices, many

states with energy efficiency programs use different input values and assumptions (e.g., net

versus gross savings, run-time of equipment, measure lifetime) in applying these practices. This

can result in significant differences in claimed energy savings values for similar energy

efficiency measures between states, even when the same measure type is installed under

otherwise identical circumstances. In response to a growing awareness of this lack of cross-state

comparability, policy makers, regulatory agencies, and other stakeholders are increasingly

advocating for the use of common evaluation approaches across jurisdictions. Several national

and regional EM&V efforts have emerged to promote collaboration and information sharing

across states. These initiatives include the Northeast Energy Efficiency Partnership’s (NEEP)

EM&V Forum, which is active in New England, New York, and the Mid-Atlantic, and theI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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41 Pacific Northwest’s Regional Technical Forum (R TF). Both efforts aim to promote multi-state

coordination in EM&V practices, make EM&V results more transparent and publicly available,

and support the adoption of similar definitions, methods, and input assumptions. 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) Protocols 63

c. Federal Energy Management Program (FEMP) M&V Guidelines 64

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

Guideline 14, Measurement of Energy and Demand Savings 65

e. California Evaluation Protocols 66

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

Resources 67

g. PJM Energy Efficiency Measurement and Verification Manual 68

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

http://www1.eere.energy.gov/seeaction/evaluation.html

. 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, Refrigerati ng and Air-Conditioning Engineers (ASHRAE), Guideline 14:

Measurement of Energy and Demand Savings (June 2002) , available at:

https://gaia.lbl.gov/people/ryin/public/Ashrae_guideline14-

2002_Measurement%20of%20Energy%20and%20Demand%20Saving%20.pdf

. 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/EvaluatorsProtoco ls_Final_AdoptedviaR uling_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_proced s/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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42 h. State and Local Energy Efficiency Action Ne twork, Energy Efficiency Program Impact

Evaluation Guide 69

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 imp act evaluations achieve ±10 percent statistical

precision at the 80% confidence interval (see below for more on FCMs).

Regardless of the evaluation approach followed, the majority of state PUCs and energy

efficiency program administrators aim to strike a balance between the transaction costs of

EM&V activities (i.e., expense, time, staff effo rt) and the resulting reliability, validity, and

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

costs and the rigor of EM&V – and the related cer tainty of energy savings estimates – is often

determined based on the type of program (including program purpose and goals), level of

program expenditures, and magnitude of anticipated energy savings.

3.2 EM&V for Energy Efficiency Measures used in ISO Forward Capacity Markets

Two Independent System Operators (ISOs) re sponsible for operating regional electricity

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

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

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43 delivered over the contract period (typically three years into the future), and documents how the

requirements of the ISO’s M&V standards manual will be satisfied.

Based on experience to-date, states bidding their energy efficiency programs into both the

ISO-NE and PJM forward capacity markets are typically subjected to EM&V requirements that

go beyond the evaluation already conducted for the purpose of meeting PUC requirements. This

is because, while PUCs typically require evaluation protocols and procedures for documenting

the cost-effectiveness of annual energy (MWh ) savings, FCMs require the measurement and

verification of capacity (MW) savings during specific peak demand hours. In addition to the

evaluation of energy savings, a separate set of measurement techniques and data collection

protocols are required to document peak demand reduction impacts. Furthermore, attaining the

level of statistical precision and confidence de scribed above typically requires additional

sampling 70 than is required by PUCs. One considerat ion is whether EM&V requirements in ISO

capacity markets include components that woul d facilitate better estimation of avoided CO 2

emissions related to energy efficiency programs include in state plans.

For the states located in ISO-NE and PJM, the common evaluation requirements for FCM

participation have created an impetus for regional collaboration on EM&V practices. New

England and Mid-Atlantic states continue to wo rk together to establish consistent evaluation

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

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 challeng es 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 instal led within the total population of all measures installed

through an energy e fficiency 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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44 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 Ener gy Efficiency Programs and Measures in

State Plans

4.1 Accuracy of Energy Savings Estimates

To document and verify that avoided CO 2 emissions from energy efficiency programs

and measures are real and persistent, impact eval uation must be rigorous and transparent. Impact

assessment should also consider the appropriate balance between certainty of results and the

EM&V costs to achieve a specified level of certainty. Because energy savings data are estimates

,

their use as part of the basis for determining the avoided CO 2 emissions resulting from energy

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

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45 necessary level of certainty is balanced with the amount of effort (e.g., resources, time, money)

used to obtain that level of certainty.

4.2 EM&V Technical Considerations for State Plans

Using energy efficiency requirements, program s, and measures as an emission reduction

approach in state plans requires considerat ion of several evaluation-related technical

considerations. The following sections describe these considerations.

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46 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 programs 73 ) 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 cons umer 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 en ergy-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 en ergy-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_

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47 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 Polices 74

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 proce dures 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, ba sed upon numerous conversations with professional energy

efficiency program evaluators. It should be noted that there are states with building energy codes, behavior

programs, and market transformation programs that are well documented and subject to rigorous EM&V. 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

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48 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 m easure 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 de livered 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 sy stem in the United States. For every unit of energy use avoided at the

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

delivered to consumers through the T&D system. 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 pr ograms and measures for which there is significant experience with EM&V, a

robust set of existing EM&V studies and reports, and relatively straightforward EM&V approaches.

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 throu gh, as well as reactive power losses in alternating current

systems due to inductance and capacitance. Most of this lost energy is converted to heat. The magnitude of losses in

the T&D system depends on the physical ch aracteristics of the system in question, as well as how it is operated.

77 U.S. EPA, Assessing the Multiple Benefits of Clean Energy: A Resource for States (February 2010), available at:

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49 4.2.3 Reported Energy Savings Values

Energy savings results for energy efficiency programs are often expressed in terms of

annual MWh of savings per year. However, for an assessment of the associated avoided CO 2

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

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

estimating the avoided CO 2 emissions that result from an efficiency program or portfolio 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 CO 2 emissions. In particular time-differentiated data is

necessary to estimate the marginal avoided CO 2 emissions related to electric generation, as

discussed above in section IV.C.3.

In practice, state PUCs around the country have substantially different requirements and

recommendations for evaluating and reporting time-differentiated energy savings. Some energy

efficiency program administrators report annual energy savings impacts, where savings are

typically based on either tracking data (i.e., data used to estimate savings for planning purposes)

or evaluated (i.e., ex-post) savings data. Other programs supplement reporting of annual energy

savings with data on the timing of energy savi ngs, which can be used to identify the marginal

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

energy savings. This supplemental data can be used to more accurately estimate avoided CO 2

emissions that result from program energy savings. Due to improved evaluation software and

data availability, it is increasingly common for energy efficiency program EM&V plans to

include calculation of estimated seasonal or even hourly energy savings as part of the program

evaluation process. A consideration for EM&V requirements or guidance for state plans is the

extent to which time-differentia ted 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.

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50 A related consideration is metr ics reported for electricity savings. The primary metric

required to understand the avoided CO 2 emissions impacts of energy efficiency programs and

measures is annual MWh of energy saved. In addition, a secondary metric is MW demand

reduction impacts, which may be desirable because it is helpful in identifying the marginal EGU

or cohort of EGUs, in particular units on the build margin. This information is necessary to

estimate the marginal avoided CO 2 emissions related to electric generation, when reporting on

avoided CO 2 emissions achieved through energy efficiency programs and measures during a plan

reporting period, as discussed above in section IV.C.3. Identifying EGUs on the build margin,

based on estimates of MW demand savings that will be achieved through the implementation of

energy efficiency programs and measures included in a state plan, may also be useful in

projecting emission performance by affected EGUs that will be achieved under the state plan.

4.2.4 Savings Definitions: Net and Gross Savings

As described above, state PUCs typically specify whether energy efficiency program

administrators are required to report either gross or net energy savings, or both. Gross savings

are the change in energy use (MWh) and demand (MW) that results directly from programrelated actions taken by program participants, rega rdless 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 pr omote 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 ev en though they would have taken the efficiency action

anyway), or adjusting energy savings estimates to account for these effects. Free riders increase program costs

without producing additional energy savings impacts beyond what would have occurred in the absence of the EE

program. Free ridership may also be addressed in the setting of baselines that are used to calculate energy savings.

Estimates of net energy savings may also involve an assessment of "free drivers" (sometimes referred to as

"spillover effects"). These are individuals who do not di rectly participate in an EE program, but who 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

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51 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 thei r assumed measure lives, these energy-savings

benefits may extend from 10 to 15 years, or more into the future from the point of measure

installation. In practice, evaluators determin e measure lifetimes on the basis of engineering

judgment, manufacturer specifications, and some empirical field studies. These values are

frequently entered into PUC-managed state technical databases for ongoing and repeated use in

evaluation studies. For state plans, a key consider ation is whether measure life and persistence

values for energy efficiency measures docume nted 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 de pth in this section, utilities and

states have conducted ongoing evaluation of en d-use energy efficiency and renewable energy

measures and programs for several decades. These evaluations, which include quantification,

monitoring and verification of results, gene rally rely upon a well-defined set of industry -standard

practices and procedures. As a result, existi ng state and utility EM&V requirements and

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

80 If both gross and net savings were requi red to be reported, this would increase the transparency of reported energy

savings estimates, but only one savings value would be used to evaluate the effect of energy efficiency programs and

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52 established by the EPA for state plans. However, measurement approaches vary by state based

on multiple factors, including the measure and pr ogram type being evaluated, the level and

nature of regulatory oversight, the degree of stat e and utility experience with these measures and

programs, and the overall magnitude of program impacts. 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 uncerta inty 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 consiste nt 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 documenti ng 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

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53 At one end of this spectrum, establishing sp ecific 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 c ould 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 sp ectrum, 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, usi ng general guidance, and/or establishing EM&V

criteria for specific widely used energy effici ency 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 savi ngs 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 th e qualifications, integrity, and independence of Comment [A14]: Though this comment

bookends the options, a lack of EM&V requirements

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54 those conducting EM&V of energy efficiency programs and measures, and preparing energy

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

may not ensure sufficient evaluation rigor.

5.1 Use of EM&V Protocols

Establishing requirements 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 in clude in its plan. In addition, because existing

state and utility EM&V infrastructure and protocol s were established to support the goals of state

energy efficiency programs, in current form they may not adequately support the level of EM&V

required for state plans under CAA section 111(d). In particular, this may include the form and

precision of energy savings data and reporting necessary to evaluate avoided CO 2 emissions that

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

5.2 EPA Review of EM&V Plans as Part of the State Plan Review Process

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

state- or utility-level review and approval pr ocesses, 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 submitte d 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 EPAI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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55 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 appr oach 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 wi th 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 effect s would require greater EM&V effort. 81

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

such as lighting retrofits might require only veri fication 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 effo rt” could refer to greater reliance on deemed savings

values, smaller sample sizes for measured savings, fewer direct measurements, and pro portionately greater reliance

on ex-ante estimates. “Medium” and “high” levels of EM&V effort could require incrementally more effort in each

of these areas. Other interpretations of this concept are possible.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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56 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 incremen ts 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 transp arency, and the level of EM&V effort required.

Excessive documentation requirements may not add value in terms of transparency, but may

discourage the inclusion of cost-effective energy efficiency options in state plans. However, two

basic criteria for EM&V documentation should be applied in state plans:

 Energy savings documentation should be provided at a level of detail that allows for

recalculation of program energy savings totals; and

 EM&V information in state plans should be provided in a consistent manner across states

to allow for comparison, benchmarking, and more efficient review of plans by the public

and EPA

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

Measures in a State Plan

The following is an example of a possible outline of the type s of information that might

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

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

relevant energy efficiency programs and measur es during a state plan performance period. AnI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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57 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 report ed (e.g., annual MWh, monthly MWh, hourly

MWh, average MW), and whether gross or net savings, or both, will be reported

 Name of impact evaluation protocols, guid ance documents, and other methods that will

be followed in preparing evaluated energy savings reports

 Description of the range of uncertainty for energy savings estimates indicated in

evaluated energy savings reports, including sources of uncertainty

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

 Indicate how the following issues, if applicable, will be addressed in the claimed and

evaluated savings estimates:

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

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

o Sources of uncertainty Comment [A15]: Incomplete sentence

– please

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58 B. Quantification, Monitoring, and Verifi cation for Renewable Energy Measures

For rate-based state plans, a key element of the plan is a demonstration of how the state,

and related entities with enforceable obligations under the plan, will measure and verify electric

generation that is achieved through the implementation of renewable energy measures

incorporated in the plan. 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 investme nt level), and other policies (R&D support;

manufacturing incentives; workforce training; net me tering; etc.). Experience to date indicates

that RPSs have led to the vast majority of the increase in renewable energy generating capacity

and generation resulting from state policies. However, FITs and production-based tax incentives

have been among the most important incentives used by states and utilities to help achieve RPS

requirements, as well as to spur additional production and use of renewable energy. Further,

these types of programs rely on measurable electric generation as the basis for compliance or

incentive payments. As a result, the following discussion focuses on quantification, monitoring,

and verification mechanisms related to these stat e policies. Other types of programs (e.g., certain

grant and rebate programs) may not currently qu antify electric generation output from funded

renewable energy projects. However, if such programs were modified to require the collection of

such data, many of the quantification, monitoring, and verification considerations discussed in

this section would also generally apply.

82 In this section we use the term “renewable energy meas ure” to refer to a renewable energy requirement (such as

an RPS), a renewable energy deployment program, or indi vidual installed renewable energy measures, such as

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59 1. Renewable Portfolio Standards

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

load-serving entity provides to retail electricity customers. 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 utilit ies and electric cooperatives are exempt from state RPS, have

lower RPS requirements, or are required to develop their own renewable energy procurement

targets. Additionally, some states have created separate renewable energy requirements for each

of their affected distribution utilities.

The absolute amount of renewable energy that each distribution utility is obligated to

deliver will vary, with requirements in the form of a fixed amount of renewable energy (either

MWh or MW of capacity) or percentage of retail sales.

There are several pathways that affected distri buted utilities typically have to meet state

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

purchasing electricity from renewable energy ge nerators, and purchasing the attributes from

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

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

utility may supply electricity to a retail customer. These en tities use a regulated distribution utility’s network to

deliver electricity to a retail consumer. These entities either generate their own electricity or contract for supply from

wholesale electricity market participants. In this section, we use the term “distribution utility” to refer broadly to

both local distribution companies (LDCs) and other load-serving entities that supply electricity to retail customers.

84 “Voluntary” renewable energy purchases, as used here, refers to renewable energy purchases in addition to the

renewable energy required by RPSs.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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60 each distribution utility to gene rate electricity from its own renewable energy facilities or

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

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

renewable electricity produced. 85

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

state RPS requirements. Renewable energy generato rs can sell RECs as another product bundled

with the underlying power they produce or sell RECs separately to different customers. Once the

RECs are separated from the power generated, the power has no attributes associated with it and

is considered generic or “null” power. 86

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

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

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

will result in avoided CO 2 emissions from fossil fuel-fired EGUs, some RPS-eligible

resources in some states are responsible for greenhouse gas (GHG) emissions or do not

meet common definitions of renewable energy (e.g., waste coal, coal-bed methane, and

fuel cell operation using fossil-fuel feedstocks).

 Existing and new resources. RPS-eligible re sources can include facilities that began

operation prior to the enactment of the RPS and, more importantly, prior to the proposal

of the emission guidelines by EPA. 87

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

represent the energy itself. The attri butes conveyed with RECs include info rmation about the generator, such as:

type of resource (e.g., wind), plant-level air emissions (if any), geographic location, nameplate capacity (MW),

commercial operation date, ownership, and the eligibility for RPS compliance or voluntary market certification.

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 su pplied from by the distribution utility. “Generic power” or

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

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

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

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

assignment of attributes as described above.

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

apply toward its required emission performance level th e emission reductions that existing state programs andI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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61  Scope of coverage . In some states a RPS applies to all retail sales in a state, but in others

only a subset of retail sales (e.g., only invest or-owned utility retail sales) are subject to a

RPS.

 Credit multipliers . Some states provide additional incentives for specific eligible

resources in the form of bonus credit toward compliance in their RPS accounting

framework. For example, these states may favor certain resources (e.g., distributed solar

PV), or locally-important resources or t echnologies. The MWh produced or renewable

energy certificates (RECs) related to MW h production from such facilities may be

counted twice or three times toward compliance with a RPS in such states. However,

these credit multipliers and bonuses are not an accurate representation of the amount of

renewable energy generation that is attributable to a RPS. For the purpose of quantifying

the amount of renewable energy produced as a result of a RPS included as a measure in a

state plan, only the actual renewable energy generation used to comply with an RPS is

relevant.

 Banking . Some states permit the carryover of renewable energy produced in one year to

satisfy RPS requirements in a subsequent year. Accounting for year-to-year carryover

should be addressed in a state plan, in order to determine the renewable energy

generation that occurred in a respective reporting year or compliance period.

 Alternative compliance payments (ACP) . Many states allow a compliance alternative

which requires obligated entities to pay a pred etermined fee to the state for each MWh of

RPS shortfall. Although these ACP payments may be directed to programs to promote the

deployment of renewable energy technologies, these payments are not equivalent to

renewable energy generation and should not be accounted as such.

 Interstate issues . While treatment of interstate emission effects is discussed in detail in

section VII, for quantification, monitoring, and verification of renewable energy

measures achieve during the plan period due to actions taken after the date on which the emission guidelines are

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62 generation under a RPS it is important to note that most states allow use of eligible

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

Considerations related to the quantif ication, monitoring, and verification of renewable

energy generation used to meet a RPSs depends on the design and implementation of the RPS.

Distribution utilities subject to a RPS may meet their RPS oblig ations by building and operating

their own renewable energy generating facilities , entering into bilateral contracts with other

parties to purchase renewable energy, and participating in the REC market. Each compliance

method has specific implications for the quantification, monitoring, and verification of

renewable energy generation used to meet RPS obligations. Implications under these different

pathways are discussed below.

Build renewable generating facilities

In many states, utilities with RPS obligatio ns may build, own, and operate their own

renewable energy generating facilities. This pathway is often used by vertically integrated

utilities subject to a RPS. For large renewabl e energy generating facilities, production is

measured through a revenue-grade utility meter as it enters the grid at the point of

interconnection. This meter is subject to the same verification standards as for any other

generator participating in the wholesale market.

Some utilities with RPS obligations also bu ild, own, and operate smaller distributed

renewable energy generating facilities. Smaller generators, such as residential rooftop solar PV

systems of less than 10 kW capacity, often don’t have discrete metering of their total

generation. 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 genera tors 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 el ectricity supply to or from the grid, representing either

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

if the system does not meet a building’s total electricity load. Comment [A16]: Suggest including this

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63 Bilateral contract model

Under the bilateral contract mo del, distribution utilities with RPS obligations contract

with renewable energy generators for supply. These contracts typically specify a delivery amount

in MWh over a specified contract period. Thes e supply contracts may be short- or long-term,

may specify generation from certain renewable energy EGUs, and may be solicited through an

RFP or entered into through negotiation. Quantification of renewable energy generation (in

MWh) is accomplished through the use of a revenue-grade meter that measures the flow of

electricity from the generator into the transmi ssion grid. A contract may also stipulate an

adjustment to the metered MWh generation data to account for transmission losses that occur

between the point of injection of electricity to th e transmission grid and the point of receipt at a

utility transmission or distribution system. A rene wable energy supply contract also generally

addresses the ownership of the RECs related to the renewable energy generation. Under such a

contract, purchase of the RECs should accompany the purchase of the electricity, in order for the

utility to satisfy its RPS obligations through the contract. 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 purch asing utility also reports their purchase and

delivery of RPS-compliant renewable energy pursuant to the contract to the state agency

responsible for RPS enforcement, typically the st ate PUC or state energy office. Verification is

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

RECs held by the utility and submitted for retireme nt by the tracking system administrator. Some

state RPS require that electricity from qualifying renewable energy sources be produced within

the state or a specified grid region, or if outside the state or specified grid region, that electricity

be delivered to the state or grid region. In such cases, the verification of electricity delivery is

typically done by the REC tracking system admi nistrator before issuing RECs for the imported

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

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

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64 through the ISO or RTO serving the state or region, through demonstration that the seller holds

transmission rights for delivery or poss ession of NERC tags for the energy. 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 genera tors register their EGU with a renewable

energy tracking system, which have been established by several regional groupings of states, as

well as a few individual states. 92 The registration process collects data about the generator’s

attributes: type of resource (e.g., wind), plant- level emissions, geograph ic location, nameplate

capacity (MW), commercial operation date, ownership, and the eligibility for RPS compliance or

voluntary market certification. After the generator is registered, revenue-meter data is

transmitted to the tracking system. Meter accuracy is verified for renewable energy generators in

the same manner as for any other generator pa rticipating in wholesale electricity markets.

Each MWh of renewable energy generation reported to the tracking system by a

registered generator results in the issuance of a REC, with its own unique serial number and

information about the generator, location, resource type, and the month in which the MWh was

generated, and the month or quarter in which the certificate was issued. The renewable energy

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 physi cal path of an electricity transaction from the point of

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

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

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

NERC Tags, system operators can curtail transfers if reliabili ty issues would arise as a result of the transfer. NERC

tags are issued through an electronic system in accordance with specifications established by the North American

Electric Reliability Corporation (NERC).

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 Info rmation System (WREGIS), Midwest Renewable Energy

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

Certification System (MIRECS), Nevada Tracks Rene wable Energy Credits (NVTREC), and North Carolina

Renewable Energy Tracking System (NC-RETS). For more information see

http://apps3.eere.energy.gov/greenpower /markets/certificates.shtml?page=3

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65 generator can then sell the renewable electricity as a bundle (both the commodity electricity and

the associated REC) or unbundle the RECs fro m the electricity and sell the two products

separately. Other market participants, such as brokers, REC marketers, and load-serving entities

also maintain accounts with the tracking system so that REC electronic transactions can be

recorded within the tracking system platfo rm. The system tracks each REC through these

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

retirement. Retirement could result from the REC bein g used to satisfy a state RPS, or as a result

of a voluntary buyer retiring the REC to demonstrate that they had purchased and used

renewable energy to meet their electricity demand.

Because the tracking system follows the REC from the point of issuance to retirement,

including all interim transactions, it minimizes the opportunity for renewable energy to be

double-counted across, for example, two diff erent state RPSs, or between two voluntary

purchasers. In recent years, the various tracking systems have developed interchange standards

so that RECs generated within one tracking system can be transferred to and used within another

tracking system. 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 reside ntial rooftop solar PV systems of less than

10 kW capacity, often don’t have discrete metering of their total generation. State RPS

requirements may permit these distributed genera tors to qualify for use in meeting utility RPS

obligations based on an engineering estimate of their renewable energy generation output ,

provided the distributed generators are registered with a REC tracking system and the generation

output is verified according to tracking system and RPS rules. Where such projects are third-

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

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66 party owned and operated, the pr oject developer will own the RE Cs and factor their revenue

value into their pricing offered to the site host for electricity suppl y. Note also that many utilitysponsored renewable energy incentive programs sti pulate that all RECs resulting from the project

must be transferred from the generation owner to the utility as a condition of participation in the

incentive program. These RECs can then be used by the utility to meet its RPS obligations, or

can be sold to other parties.

State agency role

In many states, the Public Utilities Commissi on (PUC) or its equivalent is responsible for

establishing the detailed rules and procedures that obligated parties must fo llow 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 diversit y, and market operations. The list of eligible

resources and MWh requirements are often set thr ough state legislation, but these decisions may

also be delegated to the PUC for study and promulgation through regulations of commission

orders.

In some states the energy office may be responsible for certifying the eligibility of

specific generators to participate in the RPS a nd for making siting determinations. In New York,

for example, the New York State Energy Research and Development Authority (NYSERDA) is

responsible for the centralized procurement of the renewable energy needed to meet the RPS for

all of the state’s investor-owned utilities.

2. Feed-in Tariffs

Feed-in tariffs (FITs) are offered by some individual electric dist ribution utilities and

some states for renewable energy systems that meet eligibility criteria. 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 Ca lifornia, Hawaii, Maine, Oregon, Rhode Island, South

Carolina, Vermont and Washington, as well as numerous electric utilities.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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67 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 measur e the generator’s injection of electricity into

the grid. The utility’s tariff will typically specify the minimum performance characteristics

and/or certifications that a meter must meet in orde r to be used on its system. Utilities retain the

right to inspect and test the calibration of meters connected to their systems. As the utility will be

paying the generator each month based on the meter reading, it is in the utility’s interest to

ensure that the meter is reading precisely and accurately through time.

Both the utility and the state will need to consider the ownership of the environmental

attributes arising from the renewable energy ge neration purchased by a utility through a FIT, and

whether the renewable energy can be counted toward RPS compliance. If renewable energy

generation purchased by a utility through a FIT may be counted toward RPS compliance, then it

should not be counted separately as another renewable energy program in a state plan.

State agency role

FITs are usually authorized by state statutes that specify which utilities must offer a FIT,

eligibility criteria (e.g., renewable energy resource type, location, project MW generating

capacity limits), and sometimes overall program ta rgets (e.g., total installed MW of generating

capacity subject to the FIT). State statutes may al so specify whether the utilities offering a FIT

will receive the RECs related to purchased electricity generation output for use in complying

with a state RPS, and whether customers recei ving FIT payments may also receive incentivesI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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68 under other utility and state programs. Typically st ate 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 se tting FIT payment levels. Based on this statutory

authority, PUCs develop detailed rules governing implementation, which can include payment

levels and contract length. PUCs may direct the affected utilities to develop standard contracts

with all the terms and conditions spelled out, and these standard contracts must be approved by

the PUC. As with state RPS, the PUC is respons ible for receipt and review of the utility’s

periodic status reports, approving changes to a tariff if needed, and evaluating the impacts of the

tariff on retail prices, generation diversity, and electricity system operations.

Several FITs are offered by distribution utili ties not overseen by PUCs, such as municipal

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

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

these situations will be responsible for receipt an d review of the utility’s status reports, taking

corrective action if needed, and evaluating the impacts of the tariff.

3. State Tax Incentives

Several states offer a variety of tax incentives to promote the production and use of

renewable energy. These currently include sales tax exemptions for certain kinds of equipment

(e.g., PV panels), property tax abatement for impr ovements to a building or facility related to the

asset value of the renewable energy generating system, and income tax credits for the

installation of renewable energy systems based on capacity or investment level. Several states

provide a renewable energy production tax credit based on the amount of renewable energy

generated. This approach is useful because it results in a measureable quantity of renewable

energy electricity generation.

With a production-based tax incentive, the renewable energy generator might claim a tax

credit for each MWh of qualifying renewable energy generation within the state. One design

consideration for a production-based tax incentive th at affects quantification of renewable energy

generation output is whether the electricity must be sold to a third party as opposed to being used

by the site host. In the former case, a revenue-gra de utility meter would be present at the point ofI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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69 interconnection to the electricity grid, which pr ovides 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 gene ration resulting from production-based tax

incentives might be used for RPS compliance. If that were to become the case, then it should not

be counted separately in a state plan from MWh generation used to comply with a state RPS.

4. Options for Quantification, Monitoring , and Verification of Renewable Energy

Measures in State Plans

As summarized in the preamble, and discussed in more de pth in this section, utilities and

states have conducted ongoing evaluation of renewable energy measures and programs for

several decades. These evaluations, which include quantification, monitoring and verification of

results, generally rely upon a set of standard practices and procedures. In addition, states have

designed and implemented REC tracking systems to facilitate compliance with state RPS. This

resource provides the ability to track the location and attributes of renewable energy generators,

and the electric generation from these generators , as well as the parties that use RECs for

compliance with state RPS. As a result, existing state and utility requirements and processes forI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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70 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 ot her key information, to determine eligibility and

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

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

estimates for small distributed generators. Thes e data are essential to program management,

verification of compliance or payments, budget control, and tracking progress toward goals. For

example, PUCs overseeing compliance with state RPS receive compliance information from

each obligated utility, including retail sales, compliance status based on MWh of electricity

generated by eligible utility-owned renewable en ergy sources, or electricity or RECs purchased

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

alternative compliance payments. 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 no rmal program management and accountability.

Current state data requirements under RPS, FIT, and production-based tax incentives are

tailored to the objectives of these programs a nd facilitating effective regulatory oversight.

Typically, avoiding CO 2 emissions, while considered a relevant co-benefit, is not a primary

objective of these regulations and programs. As a result, additional information and reporting

may be necessary to accurately quantify the avoided CO 2 emissions associated with the

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

included in a state plan.

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

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

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

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71 The following types of information will incr ease the accuracy and verifiability of avoided

CO 2 emission estimates related to renewable energy requirements, programs, and measures

included in a state plan. For example, information on the location of the renewable energy

generation (e.g., in-by state or within a specified grid region) of the renewable energy generation

used for compliance with state requirements and programs would be helpful in determining

avoided CO 2 emissions. Information about the locati on of electric generators that supplied

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

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

avoided CO 2 emissions related to electric generation. Such time-differentiated data could be

based on metering or engineering estimates for a technology type that indicate the typical

generation profile for the renewable energy resource. This could include time differentiation on

an hourly, daily, or seasonal basis. If RECs can be banked and used or RPS compliance at a later

time than the year in which the electricity ge neration related to the REC occurred, information

about the quantity and vintage of RECs from prior year(s) generation that is used for RPS

compliance will also be useful.

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

Energy Programs and Measures

As discussed in the preamble, in section VIII.F.5, reporting and recordkeeping for enduse energy efficiency and renewable energy requ irements and programs will be an important

component of certain types of sate plans. If a state plan incorporates renewable energy and

demand-side energy efficiency requirements and programs under a rate-based approach or

implements a mass-based portfolio approach with such measures, reporting and recordkeeping

requirements for an approvable plan would differ from those applicable to an affected EGU. For

example, these requirements may include complian ce reporting by an electric distribution utility

subject to an end-use energy efficiency res ource standard (EERS) or renewable portfolio

standard (RPS). They may also include reporting by a vertically integrated utility implementing

an approved integrated resource plan. In the latte r instance, the utility may also be the owner and

operator of affected EGUs, but additional reporting of quantified effects of renewable energy andI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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72 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 technologie s that are incorporated in a state plan. In each

of these instances, reporting of program compliance or program outcomes is a necessary part of

an approvable plan to demonstrate performance under the plan.

In the preamble, the EPA seeks comment on appropriate reporting and recordkeeping

requirements for entities implementing end-us e energy efficiency and renewable energy

programs included as enforceable measures in a stat e plan, or for entities subject to requirements,

such as an EERS or RPS, that are included as an enforceable state plan measure. This section

provides examples of current reporting and r ecordkeeping under state energy efficiency

requirements and programs, such as EERS, RPS, and utility and state deployment programs for

energy efficiency and renewable energy. The section then examines the suitability of these

reporting and recordkeeping practices as potent ial approaches in an approvable state plan.

A. Reporting for End-Use Energy Efficiency Programs and Measures

Reporting requirements and time frames (i.e. how often reports are required) for entities

implementing energy efficiency programs and measur es are key considerations for state plans. In

a state-regulatory context with PUC oversight, impact reports are the mechanism by which

utilities and other program administrators doc ument energy (MWh) and demand (MW) savings.

These reports serve as basis for PUC review of total achieved energy savings relative to program

goals or regulatory requirements, as well as for determining financial perf ormance incentives for

utilities, where they exist.

In most states, impact reporting is initially conducted at the level of efficiency

“programs” (each consisting of numerous “project” installations or efficiency measures

occurring at individual homes, commercial buildings , or industrial facilities). Program level data

are then aggregated to the “portfolio” level to capture the full impact of energy efficiency

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73 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. Th ese reporting elements and practices – which

raise important considerations for the reporting of energy-efficiency impacts in state plans –

include:

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

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

o Short description of the polic ies or programs implemented

o Implementation schedules and timeframes

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

o Incremental annual and lifetime MWh savings for reporting (in the case of an

energy efficiency program) or compliance years ( in the case of utility compliance

with a multi-year Energy Efficiency Resource Standard)

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

 Verification documentation, which shows that installation of energy efficiency measures

occurred, and the installed measures are capable of generating energy savings

 EM&V process followed:

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

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

plan, and EM&V results

o Information about evaluators:

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

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74  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 savings 98 are estimated, definitions used for gross

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

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

The energy savings EM&V reporting elements listed above vary from state to state in

terms of type and level of documentation, and reports are provided in different formats from state

to state. This significant variation among states in reporting contents an d format raises several

considerations for states utilizing demand-side en ergy efficiency programs in state plans. One is

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

described above, are sufficient and appropriat e in the context of state plans. Another

consideration is whether lead state agencies that oversee energy efficiency programs should be

required to certify reported energy efficiency savings impacts on behalf of the state, potentially

including certification that the values are approp riate 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 th ey participated in the program. Net savings refer to the

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75 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 oblig ations are typically specified in authorizing

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

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

implementation plan describing how they will comp ly with the state RPS rules in the future.

Data requirements for reporting may vary based on the design and implementation of a

RPS. However, for nearly all state RPS requirements, annual compliance report data is based on

measurable electric generation results and verified through tracking system data. 99 In some

states, compliance reports may also include st ate-level projections of renewable energy

generation resulting from current or proposed state RPS policies.

The most common form of tracking system for RPS compliance is a regional or state

REC tracking system or registry. These systems track RECs for both the compliance and

voluntary markets. RECs are typically provided with a unique identification number and may be

certified by a third-party verifier. Annual comp liance reports containing REC data typically

include the number of RECs the utility or load -serving entity procured and retired, what

renewable energy generators supplied the RECs, and how much the utility spent on procuring the

RECs.

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

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76 2. Typical Reporting for Renewable Energy Deployment Programs 100

Renewable energy deployment programs involve the provision of a payment or credit for

a renewable energy project, or for a quantified amount of electricity generation, in the case of

performance-based incentives. Qualification of eligible projects and payment for qualifying

electric generation (or related attributes) require reporting of electric generation and other project

for each specific program. Program administrators use this information to track program progress

and report to PUCs or other oversight entities. The summary below addresses typical reporting

required for utility-administered programs, as well as programs administered by non-profit

entities and state agencies and authorities.

Reporting for utility administered renewable energy incentive programs

Some utilities offer incentives to electricity consumers to acc elerate the deployment of

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

mentioned previously, it is easier to quantify th e renewable electricity generation resulting from

some programs than it is for others. Utilities administering FITs, for example, will track the

number of customer contracts, resource type , capacity of each contracted project, MWh

generated, and utility expenditures for that ge neration under the tariff. In contrast, utilities

administering a rebate or loan program are more likely to track the number of customer

participants, the type and size of the projects, the cost of the projects, and the amount of rebates

paid or loans provided. Measuring the electric generation output of these projects may not

necessary to evaluate program status.

Net-metering is a renewable energy incentive program that is based on performance, but

where the total output of the net-metered devi ce is often unknown. Utilities reporting on netmetering programs track the number of participating customers, the type and size of net-metered

systems, and overall net-metered capacity. However, the gross amount of electricity generated

may not be known if a single bi-directional meter is used. Such meters only record net electricity

withdrawn from the grid or net electricity productio n supplied to the grid during an identified

100 In this section, “deployment programs” refers to incentive programs and market transformation programs

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77 time period. Utilities and the customers where the renewable energy generating system is located

may not necessarily know the total electric generation from the renewable energy system, unless

two meters are installed – one to measure to tal output from the customer-sited system, and

another to measure the total electricity purchased from the utility.

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

requirements by PUCs, and therefore utilities mu st provide reporting on a routine basis to the

PUC about program expenditures and outcomes (typically quarterly or annually). These records

should be readily accessible to states for estimating the impacts of their renewable energy

deployment programs included in a state plan. However, some utility incentive programs are

administered by distribution util ities that are not regulated by a state PUC (e.g., municipal and

cooperative electric utilities). In these instan ces program reporting data may not be readily

available to a state, unless separately required by a state if such programs are included in a state

plan.

Renewable energy deployment programs may be designed and implemented under the

auspices of a utility integrated resource plan (IRP). 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 inte grated electric utilities, but are less common in states that

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78 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 gene rated by a renewable energy installation, which

may be tracked and verified through utility or third-party metering protocols. These reports,

which are currently used for internal reporting for budgetary control and performance evaluation,

and to track other performance metrics for regular public program reporting, could form much of

the basis for reporting under state plans for such measures.

3. Considerations for Reporting Requirements for Renewable Energy Measures

in State Plans

State renewable energy requirements, such as RPS and FITs, and incentive programs

typically include robust reporting requirements. For nearly all state RPS requirements, annual

compliance report data is based on measureable electric generation, using revenue quality

meters, and verified through tracking system data. 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 repor ting 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 CO 2 emissions. In many instances, net meteri ng programs only track the net electricity

supplied to a customer or supplied to the grid by the re newable energy system, rather than total generation output.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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79 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 CO 2 emissions associated with these requirements, programs,

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

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

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

estimating the avoided CO 2 emissions from renewable energy generation, especially if a

marginal avoided emission rate approach is used. This includes reporting of the typical

generating profile of a renewable energy generating unit, group of units, or renewable energy

resource type. 104 For distributed renewable energy resources, reporting of the MW capacity of

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

reporting period would also be useful for estimating avoided CO 2 emissions. These distributed

resources, since they are located “behind” the utility meter at a customer location, have a similar

effect in reducing the demand for electricity supplied from the grid as end-use energy efficiency

measures.

Example reporting requirements that provide sufficient data for estimating the avoided

CO 2 emissions from renewable energy requirements and programs might include the following:

 Metered MWh generation, using a revenue quality meter, or estimates of annual output

for small systems below 10 kW in capacity

 MW capacity of “behind-the-meter” distributed renewable energy generating systems

added during a reporting period as the result of a state program

 For renewable energy resources reported, including through REC data, the typical

generating profile of a renewable energy generating unit, group of units, or renewable

energy resource type

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

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80  For REC data, information including the follow ing generator attributes: type of resource

(e.g., wind), plant-level emissions, geographic location, nameplate capacity (MW),

commercial operation date, ownership, and the eligibility for RPS compliance or

voluntary market certification

VII. Treatment of Interstate Emission Effects

Programs and measures in a state plan, such as RE and demand-side EE measures, may

affect the emission performance of the interconnect ed electricity system beyond a state border. In

addition, many state measures allow for actions in neighboring states to meet the in-state

requirement, or explicitly address CO 2 emissions in neighboring states. For example, many state

renewable portfolio standards allow for generation by qualifying renewable energy sources in

other states to count toward meeting the state po rtfolio requirement. Some states also apply CO 2

emission requirements related to the generation of power purchased by regulated utilities,

including power imported from out of state.

As discussed in the preamble to the proposal, in section VIII.F.6, the EPA recognizes the

complexity of accounting for interstate effects as sociated with measures in a state plan in a

consistent manner, to minimize the likelihood of double counting. The EPA also realizes that

interstate effects on CO 2 emissions from affected EGUs could be attributed in different ways in

the context of an approvable state plan. This section discusses in more detail the options and

alternatives for treatment of interstate CO 2 emission effects presented in the preamble. These

options and alternatives could be applied to both projections of plan performance and

demonstration of achieved emission performance under a plan. These options and alternatives

may not be mutually exclusive – in some instances states could apply different approaches,

without introducing the potential for double coun ting of emission effects. One option presented

could lead to double counting of em ission effects, and we highlight these aspects of this option in

the discussion below.

In general, the options and alternatives address different possible state plan scenarios, and

consider the range of interstate approaches that states are currently using to implement electricity

sector policies, such as multi-state emission bu dget trading programs and regional renewableI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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81 energy certificate markets for state RPSs. The options and alternatives reflect possible

accounting approaches for interstate emission effects under CAA section 111(d) that could

potentially align with these current state program s and measures that we anticipate states may

want to include in a state plan.

A. Background

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

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

result, some states are net exporters or import ers of electricity on an annual basis. Reducing

electricity load through improved end-use energy efficiency (e.g., through state energy efficiency

programs) or deploying new renewable energy el ectric generating capacity (e.g., through a state

RPS) therefore can result in CO 2 emission effects that are realized outside the state that

implements the regulation or program that produ ces the effects. Reducing electricity demand or

increasing available electric generating capacity also often impacts the economic dispatch curve

and locational economics that are used to dispatch EGUs on a regional basis. As a result, state

end-use energy efficiency and renewable energy regulations and programs often have regional

effects on electricity generation and avoided CO 2 emissions. In addition, many state regulations

explicitly address CO 2 emissions in neighboring states, or a llow for actions in neighboring states

to meet an in-state regulatory requirement. For example, many state RPS allow for generation in

other states to count toward meeti ng a utility portfolio requirement.

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

generation. In some instances improving en d-use energy efficiency will reduce electric

generation nearby a load center (e.g., in the case of a load pocket with limited access to

electricity transmission capacity). In such cases, it may be feasible to directly link in-state enduse energy efficiency programs and measures to avoided CO 2 emissions from specific in-state

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

generation control area, based on factors such as power plant economics and electricityI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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82 transmission capability, and could also impact flows between control areas. 105 In these cases,

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

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

State RPS regulations also impact electricity generation at a regional level. Over time,

state RPSs result in the introduction of new, incremental renewable energy generating capacity to

regional generation control areas, which affects EG U dispatch at the regional level. State RPSs

are typically applied to electric distribution utiliti es as a percentage of sales (e.g., a specified

percentage of delivered electricity must come from qualifying renewable energy sources). Many

state RPSs do not require the qualifying renewabl e energy electric generation to take place

within the state, or even be delivered into the state, but instead require that the renewable energy

be supplied within (or delivered into) the ISO/RTO in which the state resides. Often, utility

compliance with state RPS is through the submis sion of renewable energy credits (RECs), which

represent the attributes of renewable energy generation but not the actual electricity generated.

As a result, in many cases the intent of the state policy is often to affect the characteristics of the

regional electric generation mix, rather than the state generation mix.

The approach to implementing an RPS may differ in vertically integrated, cost-of-service

states where the distribution utility also owns electric generating capacity and dispatches

generation resources within its se rvice territory. In such cases, the RPS may require a utility to

increase its renewable energy generating capacity, rather than supplying a percentage of the

electricity it delivers to retail customers from renewable energy sources to meet load. A number

of state RPS also include “carve-outs” or “set-a sides” where a portion of the renewable energy

supplied to retail customers must come from renewable energy generating capacity located inside

the state. Most of these carve-outs are for distributed solar photovoltaic generating capacity,

which are located at the point of customer end-use (e.g., rooftop mounted solar PV on residential

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

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

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83 homes and commercial buildings). 106 Distributed solar PV capacity of ten provides benefits to the

electric distribution system by im proving distribution system reliability and avoiding the need for

distribution system capacity upgrades. This type of distributed renewable energy generation has

effects similar to end-use energy efficiency, as it reduces the customer electricity load that must

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 CO 2 emissions, beyond

the state border.

B. Summary of Possible Approaches for Treatment of Interstate Emission Effects

As discussed in the preamble, the EPA is proposing a set of approaches for addressing

interstate emission effects that result from the implementation of state plans that incorporate enduse energy efficiency and renewable energy programs. The preamble also solicits comment on

additional alternatives. The proposed approaches in the preamble include:

 For EE programs and measures:

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

occurring in the state that result from demand-side energy efficiency programs

and measures implemented in the state.

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

CO 2 emission reductions among st ates in the multi-state area.

o States could jointly demonstrate CO 2 emission performance by affected EGUs

through a multi-state plan in a contiguous electric grid region, in which case

attribution among states of emission reductions from demand-side energy

efficiency measures would not be necessary.

 For RE programs and measures:

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

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84 o Consistent with existing state RPS policies, a state could take into account all of

the CO 2 emision reductions from renewable energy programs and measures

implemented by the state, whether they occur in the state and/or in other states.

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

CO 2 emission reductions among states in the multi-state area.

o States could jointly demonstrate CO 2 emission performance by affected EGUs

through a multi-state plan in a contiguous electric grid region, in which case

attribution among states of emission reduc tions from renewable energy measures

would not be necessary

This section surveys the range of potential approaches that could be applied for

individual state plans, as well as approaches that could be applied on a regional basis. The

surveyed approaches include those proposed, as well as alternatives. These basic approaches,

including variants of some approaches, include:

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

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

and programs, estimating the avoided CO 2 emissions from in-state versus out-of-state

EGUs could be addressed through modeling, other analytical tools, or proxy metrics (e.g.,

net import factor).

 State that implements the measure cl aims the emissions reduction benefit

Under this approach, the state that impl ements the measure (e.g., end-use energy

efficiency and renewable energy regulations or programs, or an emission limit that

addresses out-of-state generation) claims the avoided CO 2 emissions, regardless of where

they occur.

 Cooperative multi-state accounting

Multiple states are allowed to mutually ag ree to how they will distribute avoided CO 2

emissions from state plan measures (e.g., end-use energy efficiency and renewable

energy regulations or programs, or an emission limit that addresses out-of-state

generation) across their respective EGU fleets. Avoided CO 2 emissions are distributed

among states by agreed formula they derive – an accounting “credit” in one state forI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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85 out-of-state avoided CO 2 emissions is complemented by an accounting “debit” in

the other state where the avoided CO 2 emissions occurred (i.e., through an increase in

reported CO 2 emissions or CO 2 emission rate).

 Tradable regional EE/RE credit market

This is a variant of the multi-state accounting approach, which could be applicable where

multiple states in a region are implementing rate-based state plans. Under this approach,

state end-use energy efficiency and renewable energy regulations and programs that meet

EM&V guidelines or requirements are allowed to generate credits, based on MWh of

energy savings or renewable energy generation. These credits, which are denoted in

avoided tons of CO 2 or avoided MWh, could be used by affected EGUs toward

demonstration of compliance with state rate-based CO 2 emission limits within a

designated region. EE/RE credit issuance could be on a project and/or program basis.

State accounting for interstate emission effects would be addressed through the credit

market and determined based on credits held by affected EGUs.

 Regional demonstration by states of EGU emission performance

States are allowed to regionally demonstrat e emission performance by affected EGUs.

Stets jointly demonstrate emission performan ce for affected EGUs, in terms of total CO 2

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

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

 The EPA jointly assesses regional performance achieved in aggregate by all individual

state plans in a grid region

The EPA assesses interstate effects on a region al basis during the plan review process.

The EPA requires states to agree to an interstate attribution process only if necessary (i.e.,

if regional performance falls short of the aggregated identified performance levels for

affected EGUs in individual st ate plans). Alternatively, the EPA requires plan revisions if

regional performance falls short of the aggregated regional performance level (i.e., the

aggregated identified performance levels for affected EGUs in individual state plans).

Table 3 includes illustrative examples of the application of some of the different

approaches for addressing interstate emission eff ects summarized above. The table explains howI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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86 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 CO 2 Emissions from Affected EGUs

Within its Borders

Under this approach, the effect of a state measure could be applied to help demonstrate

emission performance by affected EGUs in th e state if it has the effect of avoiding CO 2

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

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

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87 obligation would still be a valid state plan action, provided the out-of-state renewable energy

generation has the effect of avoiding CO 2 emissions from affected EGUs inside the state. As

another example, for a state that is a net impor ter of electricity, improvements in demand-side

EE and related reductions in electricity demand may reduce the need for generation from both

affected in-state and out-of-state EGUs. These electricity demand reductions could be applied to

help demonstrate emission performance by affected EGUs in the state if the reduction in

electricity demand has the effect of avoiding CO 2 emissions from those in-state EGUs.

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

EGU CO 2 emissions could be addressed through modeling, other analytical tools, or proxy

metrics such as a net import factor.

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

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

demonstration of performance achieved. Under th is approach, both projected plan performance

and performance achieved is assessed on a state-by-state basis.

Ex ante projections of plan performance

To project the effect of EE/RE measures un der a state plan, a dispatch model would be

applied to a grid region to estimate the marginal or average avoided CO 2 emissions impact of the

plan measures on a state-by-state basis within the region. To the extent that a state’s EE/RE

measures were projected to avoid CO 2 emissions from its own in-state EGUs, these effects could

be applied to meet the required level of CO 2 emission performance for affected EGUs in the state

plan. (See section IV.C of this TSD for a full discussion of using a dispatch modeling approach

to projected avoided CO 2 emissions that will be achieved through a plan.)

Ex post demonstration of plan performance

To assess the state-by-state avoided CO 2 emissions that result from the implementation of

a plan, a dispatch model would also be applied to a grid region, on a retrospective “look-back”

basis. This modeling would assess the avoided CO 2 emissions resulting from reported MWh of

energy savings and MWh of reported renewable energy generation, as a result of implementation

of EE/RE measures in the plan. Under a rate-based plan approach, modeled estimates of avoidedI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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88 CO 2 emissions, based on reported EE savings and RE generation, could be applied through an

administrative adjustment by the state program ad ministrator or through the issuance of tradable

EE/RE credits within the state. For ex post demonstration under a mass-based plan approach,

performance would be determined based on reported stack CO 2 emissions from affected EGUs—

no further analysis would be necessary. (See section IV.C of this TSD for a full discussion of

using a modeling look-back appr oach to estimate avoided CO 2 emissions.)

Use of simplified proxy metrics to apportion effects among states

Simplified metrics, such as a net electricity import or export factor, might also be applied

to assess the impact of state actions in avoiding CO 2 emissions from in-state affected EGUs. For

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

EE measures might be multiplied by a factor of 0.70. 108 Avoided CO 2 emissions might then be

calculated by multiplying this adjusted energy savings number by the average or marginal CO 2

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

projections of plan performance and ex post de monstrations of performance. However, this

method would be subject to uncertainty, as electri city net imports may vary significantly on an

annual basis, due to changes in system dispatch. (See section IV.C of this TSD for a discussion

of dispatch dynamics that affect avoided CO 2 emissions.)

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

states. However, it could reduce incentives for states to employ measures that have a systemwide, regional effect in reducing EGU CO 2 emissions. In effect, because an adjustment factor

would be applied to energy savings under this approach, a net importer state would need to

achieve greater energy savings through end-use energy efficiency requirements and programs to

achieve a ton of avoided CO 2 emissions under its plan than a state that is not a net importer.

108 In this instance, it would be assumed that 30% of th e reduction in electricity load resulted in avoided CO 2 emissions from out-of-state EGUs that serve electricity load in the importing state.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866

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89 2. State that Implements the Meas ure Claims the Emission Effects

Under this approach, the state that implements the measure (e.g., an EERS or RPS, or an

emission limit that addresses the attributes of purchased electricity from out-of-state generation)

claims the avoided CO 2 emissions, regardless of where they occur.

If the avoided CO 2 emissions from state plan measures at the regional level are greater

than avoided emissions from affected EGUs within the state, these interstate effects would need

to be accounted for and applied to affected EGUs within the state. This could be achieved

through an administrative adjustment by the state, or through a tradable credit system that is

limited to affected EGUs in the state.

Under an administrative adjustment approach , out-of-state avoided emissions would be

applied to the in-state EGU fleet by the state program administrator when determining average

fleet CO 2 emission rate or tonnage CO 2 emissions. Under a tradable credit approach, credits

would be issued for all avoided CO 2 emissions resulting from appl icable state plan measures,

without regard to where the avoided emissions occurred. Since the tradable credit system would

be limited to affected EGUs in the state, use of the credits by affected EGUs when demonstrating

compliance with a rate-based emission limi ts would functionally apply the avoided CO 2

emissions to the state that was responsible for the measure.

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

reduce EGU CO 2 emissions on a system-wide, regional basis. However, this approach, absent

cooperative accounting among states in a grid region, as described below, will likely lead to

double counting of emission impacts among states, which could reduce the overall emissions

reductions achieved through state plans on a national basis under CAA section 111(d). We also

note below that other approaches could also provide incentives for a regional, system-based

approach to achieving CO 2 emissions reductions from affected EGUs, without raising the

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90 3. Cooperative Multi-State Accounting of Interstate Emission Effects

Under this approach, multiple states would be allowed to mutually agree on how they

will distribute avoided CO 2 emissions from RE and demand-side EE measures across their

respective EGU fleets. Avoided CO 2 emissions would be distribute d among states according to a

formula that they specify. Based on this agreed formula, each state would adjust its demonstrated

emission performance by affected EGUs accordin gly. In effect, a “credit” for out-of-state

emission effects in one state would be complemented by a “debit” for such effects in another

state.

This approach provides states with discretion about how to attribute interstate effects,

based on their situations and policy preferences in a grid region. Importantly, this approach also

avoids the potential for double counting of interstate emission effects among states. However,

this approach is premised on regional collaboration among all states in a grid region. Not all

states in a grid region may be willing to cooperate in implementing such an accounting approach.

4. Tradable Regional EE/RE Credit Market

Under this approach, RE and demand-side EE ac tions that meet applicable quantification,

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

by affected EGUs to their reported CO 2 emission rates when demonstrating compliance with an

emission limitation in a state plan. 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 CO 2 emissions or MWh of electricity savings or electricity generation,

as described above in Section VI.E.3., incorporating RE and demand-side EE measures under a rate-based approach.

Depending on a state’s circumstances and its plan approach, these tradable credits might represent a new instrument

created for use under a state plan, or a state might use an existing instrument, such as RECs.

110 Credits could be issued on a program or project basis. The types of measures for which credits could be issued

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91 EGU marginal emissions abatement costs. In eff ect, accounting of interstate effects would be

allocated among states based on prices in the credit market.

This approach is applicable if multiple states are implementing rate-based state plans.

Where states were implementing a mix of rate-based and mass-based state plans in a shared grid

region, this approach would lead to double 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 st ates implementing a mass-based approach, where

credits for avoided CO 2 emissions are transferred to affected EGUs located in another state for

compliance purposes, the state from which credits were transferred would adjust its reported CO 2

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

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

5. Regional Demonstration by States of Emission Performance

Under this approach, multiple states would demonstrate CO 2 emission performance by

affected EGUs on a regional basis. 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 CO 2 emissions. Instead, states would asse ss the impact of state measures in

avoiding CO 2 emissions from the fleet of affected EGUs in the multi-state region.

This approach creates incentives for the implementation of system-based approaches that

collaboratively reduce EGU CO 2 emissions on a regional basis, while also avoiding the need to

attribute interstate emission effects among states . However, regional collaboration will require

more time for the development of multi-state pl ans. This approach is also premised on the

111 Note that in this example, state reporting of overall achieved CO 2 emission performance by affected EGUs

under a state plan is distinct from demonstration of compliance by affected EGUs subject to a mass-based CO 2 emission limit. For EGU compliance, no adjustment would be made to CO 2 emissions reported by affected EGUs

subject to the mass-based emission limit, even though emis sions from these affected EGUs may have been reduced

as a result of EE/RE regulations and programs implemented in a neighboring state. In this case, the state would

adjust the overall CO 2 emissions from the affected fleet to account for the “export” of avoided CO 2 emission credits,

in order to demonstrate the overall level of CO 2 emission performance that is assumed to have been achieved by the

affected EGU fleet under the plan.

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92 willingness of all states in a gr id region to participate in the development and implementation of

a multi-state plan. Some states in a grid re gion may be unwilling to collaborate regionally.

6. Assessment of Interstate Effects by the EPA in the Course of State Plan Review

Under this approach, the EPA would evaluate interstate effects on a regional basis during

the plan review process. 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 regi on are projected to achieve the required level

of performance represented in individual state pl ans, or are projected to achieve an aggregate

regional level of performance consistent with the level of required performance included in all

state plans in the region, instances of double count ing of interstate effects among states are less

important. The EPA could indicate as part of pl an approval that it will review actual emission

performance achieved by affected EGUs during the plan period on a regional basis.

VIII. Appendix

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

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

Programs that Reduce Power Sector CO 2 Emissions. This draft document was submitted to OMB

on April 3, 2014.]

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

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## Appendix for State Plan Considerations

Technical Support Document (TSD)

Survey of Existing State Policies and Programs that

Reduce Power Sector CO 2 

## 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

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### Contents

I. Overview of state climate and energy policies and programs that reduce power sector CO 2

............. 6

II. Existing state and utility policies, programs, and measures that affect EGU CO 2 emissions

............... 8

a. Actions that reduce EGU CO 2 Directly............................................................................................... 9

i. Market

‐ based Emission Limits

...................................................................................................... 9

ii. CO 2 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

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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

CO 2 – Carbon Dioxide

CO 2 e

– 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

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– Renewable Portfolio Standard

PUC

– Public Utility Commission

SO 2 – Sulfur Dioxide

VEIC

– Vermont Energy Investment Corporation

WAP

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### Survey of Existing State Policies and Programs that

Reduce Power Sector CO 2 

### Emissions

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

power sector CO 2

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.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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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/electric ity/policies/restructurin g/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

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– Do Not Cite, Quote or Distribute June 12, 2014 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

CO 2 

### emissions

Some state and utility policies, programs and measures directly target CO 2 emissions by

creating specific limits or standards for CO 2 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 CO 2 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 CO 2 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.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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– Do Not Cite, Quote or Distribute June 12, 2014 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 CO 2 

### Directly

Existing state actions that directly reduce EGU CO 2 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 CO 2 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/ca pandtrade/capandtrade.htm Greenhouse Gas Cap and Trade

Last updated 3/24/2014I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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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.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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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 CO 2 equivalent

(CO

2 e) 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 CO 2 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 CO 2

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 CO 2 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/capa ndtrade/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=searchlistI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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– Do Not Cite, Quote or Distribute June 12, 2014 if price per ton exceeds $10.75 21 5 percent per year including inflation. 22

Banking  Allows unlimited allowance banking 23  Allows unlimited banking of allowances. 24

Offsets  Power plants covered under RGGI are

allowed to use offsets within the RGGI

region 25 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/Progra mReview/_FinalProgramReviewMat erials/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 CO 2 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 (SF

6 ) 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/capa ndtrade/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

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– Do Not Cite, Quote or Distribute June 12, 2014 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 CO 2 e. 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

CO 2 e 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 CO 2 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

34 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

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– Do Not Cite, Quote or Distribute June 12, 2014 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 CO 2 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 CO 2 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 CO 2 Allowance Proceeds, 2012” (2014), available at) http://www.rggi.org/docs/Documents/2012

‐

Investment

‐ Report.pdf

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DRAFT Deliberative Document

– Do Not Cite, Quote or Distribute June 12, 2014 Between 2005, when RGGI was first announced, and 2012, power sector CO 2 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 CO 2 emission

level in 2014 by 45 percent, setting a multi

‐ state CO 2 emission limit for affected EGUs of 91

million short tons of CO 2 in 2014 and 78 million short tons of CO 2 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 CO 2 emission limits for EGUs, began on January 1,

2009.

42 2014 U.S. Greenhouse Gas Inventory http://www.epa.gov/clim atechange/ghgemissions/usinventoryreport.html

43 RGGI Press Release, January 13, 2014, http://www.rggi.org/docs/PressRel eases/PR011314_AuctionNotice23.pdf

. 44 California Air Resources Board: http://www.arb.ca.gov/cc/ca pandtrade/capandtrade.htm

45 The California program was developed in coordination with U.S. state and Canadian province WCI partners.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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

reports that it reduced CO 2 power sector emissions by 16 percent from 2005 to a 2010

‐ 2012

averaging period, a reduction of 16 million metric tons of CO 2 equivalent. 47



### ii. CO 2 

### emission performance standards

Description

CO 2 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 CO 2 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/de fault/files/EP A_Submission_from_States

‐ FinalCompl.pdf

47 Ibid.

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 unitsI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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– Do Not Cite, Quote or Distribute June 12, 2014 Policy Mechanics

Design

States have implemented three different types of CO 2 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 CO 2 emissions. Table 2 provides state examples for each of the types of

CO 2 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 CO 2 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

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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

Facilities http://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

Facilities http://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 CO 2 /MWh (output based) or 120 lbs

CO 2 /MMBTU (input based). Non

‐ baseload plants (25 MW and larger) must meet an

emission rate of either 1450 lbs CO 2 /MWh (output based) or 160 lbs CO 2 /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 CO 2 /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 CO 2 mitigation plan that results in mitigation of 20 percent of the total CO 2

emissions over the life of the facility. Includes modifications to existing EGUs that

result in an increase in CO 2 emissions of 15 percent or more. The CO 2 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 CO 2 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 CO 2 /MWh. 53 By comparison, the average emissions rate of

gas plants in the U.S. is 945 lb CO 2 /MWh, while the average emissions rate of

pulverized coal plants is 2,154 lb CO 2 /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 CO 2 emission rate of 1,100 lb CO 2 /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 plantsI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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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  CO 2 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 CO 2 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 CO 2 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

CO 2 emissions over a 30 year lifetime of the proposed facility to determine whether it

meets the CO 2 performance standard.

 During the operation phase of approved facilities, there are CO 2 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 CO 2

emissions constructed after January 2007 that are primarily coal

‐ fired unless at least 50 percent

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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 test 63

, 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 CO 2 e/MWh for fossil generation (considering both in

‐ state and

imported power) and 875 lbs CO 2 e/MWh for all power in 2005 to an average of approximately

1,090 lbs CO 2 e/MWh and 775 lbs CO 2 e/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 MMTCO 2 e in 2020 from energy efficiency programs

targeting electricity reductions. Taking into account expected reductions of 21.3 MMTCO 2 e

expected from California's RPS and 2.1 MMTCO 2 e 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/Siti ng/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 CO 2 performance requirements can be validated during this test.

64 Oregon Department of Energy

‐ Oregon’s Carbon Dioxide Emission Standards For New Energy

Facilities http://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

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– Do Not Cite, Quote or Distribute June 12, 2014 Change Scoping Plan. 67 Another state, Washington, expects to reduce 9.7 MMTCO 2 e from

energy efficiency measures in 2020. Taking into account expected reductions of 4.1 MMTCO 2 e

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 CO 2 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/scopingpla n/document/adopted_scoping_plan.pdf

68 Growing Washington's Economy in a Carbon

‐ Constrained World:

https://fortress.wa. gov/ecy/publications/p ublications/0801025.pdf

69 State Energy Efficiency Resource Standards: Policy Design, Status, and Impacts, D.C. Steinberg, O. Zinaman, NREL

Technical Report NREL/TP

‐ 6A20

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‐ 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 s tates is a statutory requirement for utilities to acquire

"all cost-effective energy efficiency". This pol icy typically requires uti lities and other program

administrators to pursue energy efficiency up to the poi nt 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% re duction 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/incen tive.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

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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/incent ive.cfm?Incentive_Code=OH16R&re=0&ee=0

.

75 DSIREUSA http://www.dsireusa.org/inc entives/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

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– Do Not Cite, Quote or Distribute June 12, 2014 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.” Am erican 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

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– Do Not Cite, Quote or Distribute June 12, 2014 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

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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

CO 2 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/elec tricity/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/i ei/ourwork/Pages/issuebriefs.aspx

. 87 2011 National GHG Inventory: http://www.epa.gov/climatecha nge/Downloads/ghgemissions/US

‐ GHG

‐

Inventory

‐ 2013

‐ ES.pdf Comment [A10]: The preamble says 12 states

have achieved or have established requirements to

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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...”I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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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/rep orts/legislature/2011/energy_plan_2011

‐ 13.pdf

90 EIA, State Electricity Profiles. http://www.eia.gov/electricity/state/oregon/I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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### A

pplian

ce and

equip

ment

efficie

ncy

standa

rds

Descrip

tion

State

applian

ce

standa

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– Do Not Cite, Quote or Distribute June 12, 2014 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

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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/in centives/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”. insteadI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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– Do Not Cite, Quote or Distribute June 12, 2014 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/s ummarytables/finee.cfm Comment [A13]: Recommend changing

“generation incentive” to “program funds” for

consistency with the rest of the document.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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– Do Not Cite, Quote or Distribute June 12, 2014 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/s ummarytables/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

‐

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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 CO 2 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.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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– Do Not Cite, Quote or Distribute June 12, 2014 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

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– Do Not Cite, Quote or Distribute June 12, 2014 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.pdfI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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– Do Not Cite, Quote or Distribute June 12, 2014 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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– Do Not Cite, Quote or Distribute June 12, 2014 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.

I n 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)I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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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.”I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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– Do Not Cite, Quote or Distribute June 12, 2014 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 NO

x , SO 2 , particulates, mercury, and CO 2

. 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)I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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– Do Not Cite, Quote or Distribute June 12, 2014 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.”I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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– Do Not Cite, Quote or Distribute June 12, 2014 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

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– Do Not Cite, Quote or Distribute June 12, 2014 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 NO

x levels 88% and CO 2 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 SO 2 , 91% reduction in NO

x , 81% reduction in mercury, 55% reduction in

particulates, and 21% reduction in CO 2 from 2007

‐ 2009. 119

116 PacifiCorp 2013 Integrated Resource Plan:

http://www.pacificorp.com/content/d am/pacificorp/doc/Energy_Sources/I ntegrated_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/staticf iles/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

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1 Technical Support Document (TSD) for

Carbon Pollution Guidelines for Existing Power Plants:

Emission Guidelines for Greenhouse Gas Emissi ons from Existing Stationary Sources: Electric

Utility Generating Units

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

Projecting EGU CO 2 Emission Performance in State Plans

U.S. Environmental Protection Agency

Office of Air and Radiation

June 2014I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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2 Table of Contents

I. Introduction .................................................................................................................. ......3

II. Analytic Approaches for Projecting CO 2 Emissions from Affected EGUs ..................5

A. Electricity System Modeling Approaches for Projecting EGU CO 2 Emissions .......5

B. Growth Tools for Projecting Future EGU Utilization and CO 2 Emissions...............9

III. Translating from a Rate-Based Emission Performance Goal to a Mass-Based

Emission Performance Goal ............................................................................................11

A. Concept ...................................................................................................................1 1

B. Projection Scenarios ................................................................................................13

IV. Projecting CO 2 Emission Performance under a State Plan .........................................17

V. Applied Considerations for Different Types of State Plans .........................................18

A. End-Use Energy Efficiency and Renewable Energy .............................................18

B. Emission Budget Trading Programs ......................................................................32

VI. Process Considerations ....................................................................................................38

A. Provision of the EPA Guidance .............................................................................38

B. Party that Translates the Rate-Based Goal to a Mass-Based Goal ........................40I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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3 I. Introduction

As discussed in the preamble, in section VIII. F.7, all state plans will need to include a

projection of the CO 2 emission performance by affected EGUs that will be achieved under a state

plan (inclusive of plan measures that avoid CO 2 emissions from affected EGUs, such as end-use

energy efficiency and renewable energy). Depending on the type of plan approach, this will

include either a projection of the average CO 2 emission rate achieved by affected EGUs or total

CO 2 emissions from affected EGUs.

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

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

goal. If this translation option is used, a state pl an must also include a projection used to derive

the mass-based CO 2 emission performance goal. This transl ation will involve a projection of CO 2

emissions from affected EGUs during the plan pe riod, 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 th at the emission performance required by CAA

section 111(d) is properly defined in state plan s and that plan performance projections have

technical integrity. The credibility of state plans under section 111(d) will depend in large part on

ensuring credible and consistent emission performa nce projections in state plans. Therefore, the

use of appropriate methods, tools, and assu mptions for such projections is critical.

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

emission projections might be conducted in an a pprovable state plan, and how different types of

state plan approaches are represented in thes e projections. These options include the use of

historical data and parameters for estimating th e future impact of individual state programs and

measures. Alternatively, a projection could be based on modeling, such as use of a capacity

expansion and dispatch planning model, or a dispatch simulation model. 1 This latter approach

would be able to capture dynamic interactions within the electricity sector, based on system

1 In many cases, this approach will also require the developm ent of parameters for estimati ng the effect of individual

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4 operation and market forces, including interactions among state programs and measures and the

dynamics of market-based measures.

In the preamble, the EPA further seeks comment on whether the EPA should develop

guidance that describes acceptable projection approaches, tools, and methods for use in an

approvable plan, as well as whether the EPA sh ould provide technical resources for conducting

projections.

This technical support document (TSD) elabor ates these options and considerations. The

TSD discusses possible analytic approaches for translating from a rate-based CO 2 emission

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

be achieved through a state plan. It discusses both modeling and non-modeling approaches, such

as electricity sector capacity expansion and di spatch planning models, dispatch simulation

models, and growth tools that base projections on historical data and algorithms. The TSD also

discusses possible approaches for developing inpu ts that are used for emission projections and

applied considerations for different types of state plans. Topics addressed include:

 Section II discusses analytic approaches for projecting CO 2 emissions from affected

EGUs

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

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

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

performance under a state plan

 Section V discusses applied considerations for projecting EGU CO 2 emission

performance under different types of state plans, including:

o Considerations that should be addressed in conducting projections of emission

performance for different types of plans

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

different types of state plans

 Section VI discusses process considerations for conducting EGU CO 2 emission

projections for state plans, including:

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5 o Whether the EPA should provide guidance and other analytic support for conducting

projections in state plans and translation of rate-based CO 2 emission performance

goals to mass-based goals

II. Analytic Approaches for Projecting CO 2 Emissions from Affected EGUs

This section surveys different types of methods and tools for projecting CO 2 emissions

from affected EGUs, including modeling tools and other tools that base projections on historical

data and use algorithms to extrapolate future CO 2 emissions performance based on past

performance.

A. Electricity System Modeling Approaches for Projecting EGU CO 2 Emissions

1. National-scale capacity expansion and dispatch planning models

National-scale electricity capacity expansion and dispatch planning models are typically

used for fundamentals-based projections of the po wer sector (i.e., projections of the expected

response of the sector to factors such as electri city demand, fuel prices, and emission constraints)

that may extend over a period of several decades. These models are built to evaluate the impacts

of market, technical, and regulatory factors on the electric power sector and related markets.

Typical outputs of such models include EGU disp atch, fuel consumption, fuel prices, wholesale

electricity prices, emissi ons, EGU retirements, and infrastructu re expenditures (e.g., addition of

new EGU capacity and installation of retrofit pollution control technologies).

National-scale electricity capacity expansion and dispatch planning models have

moderate spatial detail with broad scope, generally encompassing the entire country or

transmission system interconnects (i.e. Eastern, Western, and ERCOT), which are subdivided

into smaller areas, such as balancing authorities or control areas. 2 For computational efficiency,

these models generally model several representative hours of the year, or aggregate hours into

representative bundles with similar electricity de mand profiles (i.e. peak, shoulder, off-peak). In

these models, to reduce model size, existing EGUs may be aggregated into “model plants” to the

extent that such EGUs share key unit characteristic s, such as location, size, efficiency, operating

2 A “balancing area” or “control area” refers to a specified portion of the transmission system where electricity

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6 costs, pollution retrofit control status, age, and fu el type use/availability. These types of models

are well suited to project dynamic entry and exit (capacity expansion and unit retirement) to meet

energy and capacity requirements while minimizing system costs, maintainin g reliability criteria,

and following other constraints, such as mi nimum build times, transmission constraints,

renewable energy availability, or emission limitations.

2. Utility-Scale Capacity Expansion and Dispatch Planning Models

Utility-scale capacity expansion and dispatch pl anning models are similar in concept to

related national-scale models. However, utility-scale capacity expansion and dispatch planning

models are typically used for evaluating narrower utility planning and investment decisions, such

as procurement of a specific new electric generati ng facility and retirement or retrofit decisions

for existing capacity within a specific utility’s te rritory. Utility planning m odels typically project

outcomes for periods of up to two decades. Utility-scale capacity expansion and dispatch

planning models are an industry-standard, us ed regularly in state electricity regulatory

proceedings. Within the electricity sector there is broad familiarity with these models at state

PUCs. Multiple vertically integrated utilities use capacity expansion and dispatch planning

models to conduct forward planning and re view the economics of specific EGU retrofit

decisions. Utilities that submit integrated resource plans (IRP) typically use a utility-scale

capacity expansion and dispatch planning model to examine long-term strategies and develop

short-term action plans. 3 Utilities have experience using these models to examine CO 2 emission

reduction strategies or CO 2 emission constraints, as IRP scenarios may include greater

penetration of end-use energy efficiency or renewable energy, proxy CO 2 emission prices,

emission trading, and limits on CO 2 mass emissions.

3 See, for example: The Duke Energy Caroli nas IRP (Annual Report), September 2012, available

at http://www.energy.sc.gov/file s/view/Duke_IRP 2012.pdf ; PacifiCorp 2013 IRP (Vol 1), April 2013, available

at http://www.pacificorp.com/es/irp.html ; TVA IRP, March 2011, available at

http://www.tva.gov/environment/reports/irp/archive/index.htm ; Georgia Power Company 2013 IRP, January 31,

2013, available at http://facts.psc.state.ga.us/Pu blic/GetDocument.aspx?ID=145981 ; 2011 Joint IRP of Louisville

Gas and Electric and Kentucky Utilities Company, April 2011, available at

http://psc.ky.gov/PSCSCF/2011% 20cases/2011-00140/20110421_L G%26E-KU_IRP_Volume%20I.pdf ; Great

River Energy IRP, November 2012, available at

http://www.greatriverenergy.com/makinge lectricity/resourceplan/pdoc295631.pdf ; Public Service Company of

Oklahoma IRP, October 2012, available at http://occeweb.com/pu/PSO%202012%20IRP.pdf

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7 Utility-scale capacity expansion and dispatch planning models tend to have relatively

high spatial detail with limited geographic scope, generally encompassing a utility service

territory or a sub-regional scale. These models generally have better temporal resolution than the

national-scale capacity expansion and dispatch planning models, with each model year typically

dispatched based on an annual hourly load duration curve. 4 Utility-scale capacity expansion and

dispatch planning models typically represen t individual EGUs, where each EGU has specific

operational characteristics.

Due to the additional spatial and temporal re solution of these models as compared to the

national-scale models, the number of technology options for capacity expansion is generally

limited to reduce the runtime of the model. This can be done through an outside-the-model

screening analysis to pre-select the resources most likely to be economic in a planner’s area of

interest, or by running the model iteratively to eliminate rarely chosen technology alternatives.

3. Electricity System Dispatch Simulation Models

Dispatch simulation models are regularly used by utilities, grid operators, and

independent power producers (IPP) for short-term planning, ratemaking, dispatch decisions, and

market intelligence. Dispatch si mulation models are typically driven by near-term economics,

system restrictions and market constraints, incl uding a typically more detailed representation of

an EGU’s operational constraints ( e.g. , ramp rates, heat input curves, and unit downtime for

maintenance). These models typically do not add or retire generating capacity on an economic

basis, although EGU additions and retirements may be exogenously input to these models. As a

result, projections from these models tend to be considered more robust in the shorter term. 5 Grid

operators, including utilities, and independent sy stem operators (ISO) use dispatch simulation

models in near real-time to match demand with electric generation from available generating

units and dispatch EGUs on a least-cost basi s. EGU owners and operators run dispatch

4 Load duration curves typically represent electricity load during a typical week for each month.

5 Some planners use dispatch simulation models in conjun ction with national or utility-scale capacity expansion and

dispatch planning models, where the capacity expansion and dispatch planning model indicates the disposition of

new and existing generating resources, and the dispatch simula tion model is used to simulate operation of individual

EGUs. In this case, these models can be used in the same time horizon as a capacity expansion and dispatch

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8 simulation models to assist in fuel procurement, forecast revenues and costs, and calculate the

avoided generation supply costs related to procurement of end-use energy efficiency and

renewable energy resources. 6 . Other utilities use dispatch simulation models to forecast retail

rates for ratemaking proceedings and other planning purposes.

Electricity system dispatch simulation mode ls (also called production cost models) utilize

security constrained economic dispatch (SCED) algorithms to determine which EGUs operate on

an hourly (or shorter) basis to meet electricity demand. 7 These models typically have a very

broad spatial scope, generally covering multiple Regional Transmission Organization (RTO)

regions, and often modeling entire interconnects (i.e. Western, Eastern, and ERCOT). While

individual EGUs are modeled in detail, including fuel and variable costs and operational

constraints, transmission is simplified to char acterize thermal constraints between zones, which

typically represent control areas or balancing 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, wher e transmission constraints between individual

EGUs and load are modeled as well. 8 Dispatch simulation m odels typically operate

chronologically, modeling either all 8760 hours of the year, or typical weeks of the year. These

models contain substantially more detail about individual EGUs than regional or national

capacity expansion and dispatch planning models , including EGU ramp rates, minimum outages,

maintenance schedules, emission rates, fuel use constraints, and heat rate curves depicting

expected efficiency changes at various levels of output.

6 For example, see Hornby, R., P. Chernick, D. White, et al., 2013. Avoided Energy Supply Costs in New England:

2013 Report. http://www.rieermc.ri.gov/documents/2013%20Evaluation%20Studies/AESC%20Report%20-

%20With%20Appendices%20Attached.pdf

7 The Federal Energy Regulatory Commission (FERC) define s security constrained economi c dispatch as “the level

at which each available resource should be operated, given act ual load and grid conditions, such that reliability is

maintained and overall production costs are minimized”. SCED optimizes dispatch based not only on the marginal

costs of all available generating resources, but also constr aints on transmission availability and ancillary services.

See FERC, “Security Constrained Economic Dispatch: Defi nition, Practices, Issues, and Recommendations” (2006),

available at http://www.ferc.gov/industries/electric/indus-act/joint-boards/final-cong-rpt.pdf

. 8 “A “nodal” model represents the entire transmission network in a given area, without making the simplifying

assumptions that load is served on a more aggregate “zona l” level.” A caveat is that while a nodal model has more

“links” and places where supply must meet demand, it is still an approximation in terms of the electrical operation of

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9 4. Multi-Sector Models

Multi-sector energy models are typically used to examine the effect of energy and

environmental policies that affected multiple ec onomic 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 change s over a period of decades.

Multi-sector models cover a broad range of energy sectors beyond the electricity sector,

and can better reflect energy demand and technology choices by energy end-users. Such models

typically have relatively limited spatial detail with broad scope, generally encompassing the

entire country subdivided into from one to 30 regions. Such models tend to have much more

limited temporal resolution and treatment of EGU dispatch. EGUs are typically aggregated to a

few broad technology types. A ke y strength of multi-sector energy models is the ability to

provide multi-sectoral feedback between energy resource use and price ( i.e. , tracking national

fuel supplies and adjusting price to account for demand).

The range of national- and utility scale 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 secto r-specific questions. Multi-sector energy models

attempt to include many other energy-using sectors of the economy in order to better capture

interactions between these sectors. The more aggr egate representation of the electricity sector in

multi-sector models may limit their use to providi ng input data for more specific analysis in an

electricity sector model, and to better understand variations in electricity load that may result

from changes outside the electricity sector.

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

Organizations use growth tools for a variet y 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 a nd 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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10 emissions, and county, state, 10 and regional emissions rates. 11 Because these algorithms are

generally based on publicly available data 12 and do not rely on economic data or proprietary

information regarding individual EGUs, they prov ide 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-f ired EGUs under differ ent assumed growth,

retrofit, and load-reduction scenarios. These forecast tools do not simulate economic EGU

dispatch, but could use demand growth rates and el ectricity production trends from other energy

modeling forecasts as an input assumption. 13 The algorithms in these forecast tools assume that

EGU dispatch behavior generally follows simple rules based on past operation. In the absence of

significant shifts in fuel prices and electrici ty demand, EGUs may be expected to behave

similarly in the future as they did in the past. Several common features of these forecast tools are

that they (a) generally build on historical gene ration and emissions output from individual EGUs,

(b) are insensitive to fuel and emission price forecasts, (c) do not solve for optimal economic

EGU dispatch or EGU capacity expansion, and (d ) do not capture transmission constraints or

limits. The algorithms in these forecast tools generally divide the contiguous US 14 into regional

power markets, following ISO boundaries, eGRID boundaries, NERC regional boundaries, or

similar designations. These algorithms generally seek to examine how operation and emissions

from individual EGUs could be expected to cha nge with changes in environmental regulations or

installed pollution control retrofits and additio nal or reduced hourly electricity demand. Some

algorithms use the observed historical behavior of individual EGUs to approximate future

behavior, while others add additional steps of differentiating EGUs into fuel groups and unit

10 See EPA’s AVERT (Avoided Emissions and Generation Tool), available at

http://epa.gov/statelocalclimate/resources/avert/index.html

. 11 See Flexibility Weighted Ho urly Average Emissions Rate (FW-HAER) tool, available at

http://nepis.epa.gov/Adobe/PDF/P1002UQO.pdf ; Time Matched Marginal (TMM) emissions tool, a proprietary

algorithm used to estimate avoided emissions; D. Jacobson and C. High, “U.S. Policy Action Necessary to Ensure

Accurate Assessment of the Air Emission Reduction Benefits of Increased Use of Energy Efficiency and Renewable

Energy Technologies,” Journal of Energy & Environmental Law (2010)

. 12 Hourly emissions and generation data for all fossil fuel -fired EGUs greater than 25 MW are available from EPA’s

Clean Air Markets Division (CAMD) through its Air Markets Program Data (AMPD).

13 For example, EIA’s AEO 2013 electricity load growth rates and EGU production trends are available at

http://www.eia.gov/forecasts/aeo/assumptions/pdf/0554(2013).pdf.

14 Hawaii and Alaska do not report hourly generation and emission data from individual EGUs to EPA, and are

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11 types, with implicit differentiation of economic outcomes for these different groups. Some of

these algorithms may contain subroutines to a dd new generating capacity automatically to meet

load requirements.

III. Translating from a Rate-Based Emission P erformance Goal to a Mass-Based Emission

Performance Goal

As discussed in the preamble, in section VIII. C.2, the EPA is proposing that the projected

CO 2 emission performance by affected EGUs (taking into account the qualifying impacts of plan

measures that avoid CO 2 emissions from affected EGUs) must be equivalent to, or better than,

the required CO 2 emission performance level in the stat e plan. This required level of emission

performance in the state plan will reflect the rate-based goal for the state in the emission

guidelines, or a translated mass-based goal if th e state chooses to use this approach. State plans

that are projected to achieve an average CO 2 emission rate (CO 2 lb/MWh) or tonnage CO 2

emission outcome by all affected EGUs equal to, or lower than, the required level of CO 2

emission performance in the state plan would be considered to meet this plan approvability

criterion. States may demonstrate such emission pe rformance by affected EGUs either by state or

jointly on a multi-state basis.

This section of the TSD discusses the concept of a mass-based CO 2 emission

performance goal, considerations for constructing projection scenarios for such a translation,

methods for conducting such a translation, and key input assumptions for such a translation.

A. Concept

A mass-based CO 2 emission performance goal translates the application of a rate-based

emission performance goal to an expected CO 2 emissions outcome in tons during a plan

performance period. A mass-based CO 2 emission performance goal is calculated by projecting

the tons of CO 2 that would be emitted during a state plan performance period (e.g., 2020-2029,

2030-2032) by affected EGUs in the state if they hypothetically were meeting the state ratebased CO 2 emission performance goal for affected EGUs established in the emission guidelines.

The translation of a rate-based goal (expressed in lb CO 2 /MWh of useful energy output from

affected EGUs) to tons (expressed as total tons of CO 2 emissions from affected EGUs over a Comment [A1]: Is it possible to provide an

example or equation as to how this is done? Would

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12 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 th e rate-based goal in the emission guidelines as

a proxy emission limit for affected EGUs. State pr ograms and measures in the state plan are not

included in this projection, because the purpose of this analysis is to determine the tonnage CO 2

emissions that corresponds to the state-specific rate-based CO 2 emission performance goal for

affected EGUs in the emission guidelines, without the eligible state programs and measures that

are included in the state plan.

Translation of a rate goal to a mass goal seeks to answer the question, “What would

happen to EGU CO 2 emissions if one applied the rate goals in the emissions guidelines instead of

the measures in the state plan?” Because the emission guidelines do not specify the emissions

reduction measures that a state must use in its plan, only the level of emission performance that

must be achieved through a plan, there is no specified “policy” or set of emission reduction

measures in the emission guidelines to apply when conducting this projection. However, a proxy

policy can be applied to project the emission performance in tons that would be achieved if the

state plan were to include suitable measures to achieve the required level of emission

performance established through the state rate-based CO 2 emission performance goals in the

emission guidelines. This proxy involves applying the rate-based emission goal for a state as a

rate-based average CO 2 emission limit for affected EGUs in a state and then projecting the CO 2

emissions that would occur if such a limit were applied.

When demonstrating projected emission performance under a mass-based plan, a state

would project the CO 2 emissions outcome that would be achieved under the suite of

requirements, programs, and measures in its plan. The state plan requirements, programs, and

measures substitute for EPA’s application of the best system, which is represented by the ratebased goal in the emission guidelines. If the CO 2 emissions outcome, in total tons of CO 2

emissions over each plan performance period, is equal to or less than what would be emitted by

affected EGUs through the application of the rate-based goal in the emission guidelines ( i.e.

,

equal to or less than the translated mass-based goal), the plan would be deemed to achieve the

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14 B. Projection Scenarios

As described above, the projection scenar io for translating from a rate-based CO 2

emission performance goal to a mass-based CO 2 emission performance goal does not include

requirements, programs, and measures included in a state plan. Construction of this scenario

must therefore carefully consider treatment of eligible “on-the-books” state requirements,

programs and measures included in the state plan. 15

Projection scenarios for translating from a rate-based CO 2 emission performance goal to a

mass-based CO 2 emission performance goal, and comparing projected emission performance

under a state plan to this goal, include the following:

1. A Reference Case Scenario . This scenario projects the average CO 2 emission rate and

CO 2 emissions from affected EGUs in the ab sence of the EPA emission guidelines or any

enforceable requirements, programs, and measures included in a state plan. This scenario

does, however, include all current on-the-books state requirements, programs, and

measures that are not included as enforceable measures in a state plan. These measures

are complementary to the state plan. Becau se these measures will influence EGU CO 2

emissions, they should, however, be included in the reference case projection scenario.

2. A Mass-Based CO 2 Emission Goal Policy Scenario . This projection scenario is used to

translate a rate-based goal to a mass-based goal. The scenario applies a rate-based CO 2

emission limit to affected EGUs that is equi valent to the state-specific rate-based lb

CO 2 /MWh emission goal in the EPA emission guidelines. 16 The CO 2 emissions from

affected EGUs projected during the specified plan performance period in this scenario

represents the translated mass-based CO 2 emission performance goal for the state plan.

15 An “existing measure” refers to a state or utility re quirement, program, or measure that is currently “on the

books.” For the purposes of this discussion, this may incl ude a legal requirement that includes current and future

obligations or current programs and measur es that are in place and are anticipated to be continued or expanded in the

future in accordance with established plans. Existing meas ures may have past, current, and future impacts on EGU

CO 2 emissions.

16 The proxy emission limit applied includes crediting for end- use energy efficiency, rene wable energy, and nuclear

generation included in building blocks three and four, which were used by EPA when calculating the state-specific

CO 2 emission performance goals for affected EGUs in the proposed emission guidelines. 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

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15 To construct this scenario, this emission limit is added to the underlying reference case

scenario described above.

3. A State Plan Policy Scenario . This projection scenario includes the enforceable

requirements, programs, and measures included in the state plan, and is used to project

CO 2 emission performance by affected EGUs under the state plan. To construct this

scenario, the enforceable requirements, programs, and measures included in the state plan

are added to the underlying reference case scenario described above.

1. Constructing the Reference Case

A key consideration for translating from a rate-based CO 2 emission performance goal to a

mass-based CO 2 emission performance goal is proper construction of a reference case scenario.

This includes assumptions for key variables that may drive EGU CO 2 emission projections, 17

such as:

 Electricity load growth projections (energy and peak demand)

 Fuel supply, delivery, and pricing assumptions

 Cost and performance of electric generating technologies

 EGU firm builds and retirements (those scheduled with a regional transmission

organization or independent system operator (RTO/ISO) 18

 Transmission capability and ISO/RTO transmission expansion plans

 Applicable federal regulations (other than the EPA emission guidelines)

 Applicable state regulations and programs (other than those that are included in the state

plan)

It may be necessary in many instances to include assumptions about other state programs

implemented by neighboring states in the same region. This would be especially relevant for

states that are located within the same electri c power pool (or adjoining power pools) that are

administered by a common RTO/ISO.

17 Process considerations related to constructing reference case scenarios are addressed in section VI of this TSD.

18 ISOs and RTOs are independent organizations that administer a regional electric power pool (EGU dispatch and

electricity transmission systems), and often also administer related wholesale electricity markets for electric energy

and capacity

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17 2. Treatment of Existing State Regulations and Programs in the Reference Case

A key aspect of the reference case is proper treatment of existing state regulations,

programs, and measures. As discussed previously, existing state regulations, programs, and

measures that are not enforceable measures in a state plan are complementary to the state plan –

as a result, they should be included in the reference case scenario rather than the state plan

scenario. These state regulations, programs, an d measures should not, however, be ignored

altogether, as they influence EGU CO 2 emissions. Instead, these stat e actions are occurring in the

background – either when a proxy rate-based CO 2 emission limit is applied in the Mass-Based

CO 2 Emission Goal Policy Scenario ; or when the state plan requirements, programs, and

measures are applied in the State Plan Policy Scenario . As a result, these state actions are

properly addressed in the reference case scenario.

In effect, when evaluating whether a state plan will meet the mass-based CO 2 emission

performance goal, the two policy scenarios described above, each of which involve adding a

different CO 2 emission reduction policy on top of the reference case scenario, are compared to

one another. If the State Plan Policy Scenario achieves projected tonnage CO 2 emissions equal

to or lower than the projected CO 2 emissions in the Mass-Based CO 2 Emission Goal Policy

Scenario , then the state plan can be deemed to meet the translated mass-based CO 2 emission

performance goal.

As discussed in the preamble, the EPA is proposing that a state may apply toward its

required emission performance level the emission reductions that are achieved by existing state

requirements, programs, and measures during the plan period, due to actions 19 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 progr am to meet the utility’s obligations under a state energy efficiency resource

standard (EERS), would constitute an “action” taken pursuant to an existing state requirement.

20 The preamble also takes comment on alternative dates for eligible actions, including: the start date of the plan

period, the date of promulgation of emission guidelines, th e end date of the base period for the EPA’s BSER-based

goals analysis (e.g., beginning of 2013 for blocks 1-3 and be ginning of 2017 for block 4, end-use energy efficiency),

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18 performance in a state plan if these actions occu r after proposal of the emission guidelines (e.g.,

as of June 2014 and in subsequent years). Fo r 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 CO 2 emissions from affected EGUs. Measures installed

after the eligibility date could generate MWh generation or MWh savings during the plan period,

and related avoided CO 2 emissions, that could be applied toward meeting a required rate-based

emission performance level. Under the proposed option, the eligibility date would be the date of

proposal of the emission guidelines. 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 CO 2 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

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19 (e.g., as of June 2014). Renewable energy generation that is used to meet a state RPS, but that is

incremental to the amount of generation used to meet the existing RPS obligation included in the

reference case as of June 2014, could be used toward demonstration of CO 2 emission

performance under a state plan. This renewable energy generation would be incremental to the

renewable energy generation already assumed in the reference case scenario.

IV. Projecting CO 2 Emission Performance under a State Plan

As discussed in the preamble, in section V III.D.4, one of the required components of a

state plan is a projection that a plan will achieve the required level of CO 2 emission performance

by affected EGUs that is specified in the plan . (This identified level of performance must be

consistent with either the state-specific rate-based CO 2 emission performance goals for affected

EGUs identified in the emission guidelines, or an equivalent translated mass-based CO 2 emission

performance goal.)

This emission projection is based on a scenar io that includes the suite of requirements,

programs, and measures in the state plan – the State Plan Policy Scenario described above.

Depending on the plan approach, construction of th is state plan scenario may be straightforward.

For example, if the state plan consists solely of an emission limit, the state plan scenario would

apply this emission limit to the underlying reference case scenario. Other types of state plan

approaches are more involved, in particular wh en the use of end-use energy efficiency and

renewable energy regulations, programs, or measures are included in a state plan. This could

include a state plan that applies a rate-based CO 2 emission limit that provides credit for end-use

energy efficiency and renewable energy measures that avoided CO 2 emissions, or the inclusion

of such measures through a portfolio approach. These types of plans will require input

assumptions for the amount of end-use energy efficiency and renewable energy resource (in

MWh over the plan period) that will be reali zed through implementati on of the plan. Utilitydriven portfolio approaches may also include a di verse set of actions taken directly at affected

EGUs that will need to be properly represented in the state plan scenario.

Considerations for developing estimates of energy savings and energy generation that

will be achieved through end-use energy efficiency and renewable energy regulations, programs,

and measures included in a state plan are discussed below in section VI.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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20 V. Applied Considerations for Different Types of State Plans 21

There are a number of considerations for properly representing different state plan

approaches in CO 2 emission projection scenarios. This includes both accurate representation of

the attributes of state regulations, programs, and m easures in the scenario, as well as the methods

and data sources used to derive certain input assumptions that are used in CO 2 emission

projections. This includes:

 Estimating the future effects of end-use energy efficiency and renewable energy

requirements, programs, and measures

 Properly characterizing flexibilities included in emission limits, such as emission budget

trading programs

 Properly addressing characteristics of multi-state regulations and programs

A. End-Use Energy Efficiency and Renewable Energy

Evaluating the impact of a state end-use energy efficiency requirement or program as part

of a projection of CO 2 emissions from affected EGUs under a state plan involves projections of

the impact of the requirement or program on energy and capacity savings, and the impact of this

reduction in electricity load and peak demand on EGU dispatch and CO 2 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 rele vant for state plans that implement a rate-based CO 2 emission limit

applicable to affected EGUs that provi des for adjustment or crediting of the CO 2 emission rate of an affected EGU

based on the effects of end-use energy efficiency and renewabl e energy. It is also relevant for state plans that take

either a rate-based or mass-based po rtfolio approach. Descriptions of these plan approaches are provided in the

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21 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 CO 2 emissions from

affected EGUs.

Similar considerations apply for projecting the impact of renewable energy requirements

and programs included in a state plan on CO 2 emissions from affected EGUs. The renewable

energy generation and generating capacity in a state or region that results from renewable energy

requirements, programs, and measures in a st ate plan will affect EGU dispatch and CO 2

emissions from affected EGUs. This section disc usses these considerations in more depth,

including approaches and data sources for estimating the impact of end-use energy efficiency

and renewable energy requirements and programs as part of state plan projections of CO 2

emission performance by affected EGUs.

1. Potential Approaches for Estimating the Future Effects of State Energy

Efficiency Requirements, Programs, and Measures

There are two basic approaches for developing a ten-year or longer forecast of end-use

energy efficiency resources that will result from state energy efficiency requirements and

programs: a bottom-up or a top-down approach. Th ese forecasts would contain data that could be

used to develop inputs to EGU CO 2 emission projections in a st ate plan, using modeling or an

EGU growth tool, both of which are summarized above.

A bottom-up approach is based on annual evaluated and reported data from state and

utility energy efficien cy programs, and program-level util ity compliance reports under state

energy efficiency requirements, such as an end- use energy efficiency resource standard (EERS).

One example of a bottom-up approach is the state- by-state end-use energy efficiency projection

developed by ISO New England for use in its system planning process. 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) byI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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22 New England develops production cost curves for en ergy efficiency measures based on historical

performance of energy efficiency as documented in evaluation, measurement, and verification

(EM&V) studies. ISO New England then applies those production cost curves (with adjustments

for inflation and other factors) to future state or utili ty energy efficiency program budgets for

each of the six New England states over a ten-year horizon. The ISO New England energy

efficiency forecast includes both reductions in annual energy use (MWh) and peak demand

(MW). ISO New England has produced an energy ef ficiency forecast for the last three Regional

System Plans (2011, 2012, and 2013), and the near-term estimates in these forecasts have been

validated by the actual quantity of end-use energy efficiency that has qualified for the annual

capacity auctions conducted by ISO New England as part of its forward capacity market. Other

approaches to projecting energy efficiency impacts, such as those used by New York ISO

(NYISO), PJM Interconnection, and the Ca lifornia Public Utilities Commission (CPUC),

estimate the effects of energy efficiency requirements and programs over a shorter time frame. In

these cases, energy efficiency projections are ty pically consistent with the periods for which

energy efficiency programs or program budgets have been approved by state PUCs, or consistent

with the period for which energy and demand savings acquired in ISO and RTO forward

capacity markets.

Top-down projection methods analyze aggreg ate energy use changes resulting from enduse energy efficiency requirements or programs, often for a geographic region, entire industry, or

economic sector. A top-down approach is determined on the basis of state energy efficiency

policy requirements, and assumes that utilities an d other parties implement efficiency programs

necessary to achieve required energy and demand savings. In this way, a top-down approach is

typically based on an estimated annual percentage reduction in energy use that results from state

energy efficiency requirements and programs. One example of a top-down approach is the EPA’s

state-level projection of the impacts of “on-the-books” 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 (IS O-NE) Energy-Efficiency Forecast Working Group, Draft Final

Energy-Efficiency Forecast 2018-2023 (March 2014), availa ble at: http://www.isone.com/committees/comm_wkgrps/othr/enrgy_effncy_frcst/

24 As used here, “on the books” refers to state energy-efficiency requirement s and programs currently in place and

specified in state legislation or administrative order. These requirements include energy efficiency resource

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23 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 necessa ry, to reflect known increases or decreases in

energy efficiency program budgets and other factors likely to affect whether state energy

efficiency requirements are achieved. In addition to EPA’s projections, a top-down approach is

used to develop EE forecasts by LBNL, NREL 27 , and some state energy offices and

commissions.

The LBNL 28 and the EPA forecast models are useful for comparison with the bottom-up

ISO/RTO approaches. Where discrepancies between the national top-down analyses of end-use

energy efficiency savings and the more granular bottom-up energy efficiency forecasts

conducted by ISOs and RTOs exist, review of key assumptions regarding state policies for the

different approaches may be warranted. Ideally, using the two approaches as complementary

analyses may provide for helpful comparison and reconciliation of energy savings estimates used

in state plan projections of EGU CO 2 emission performance.

The electricity load forecasts developed by ISOs and RTOs are important because they

are often the base case from which adjusted load forecasts that incorporate projected energy

efficiency program savings are developed. Fo r reasons described above, ISOs and RTOs are

beginning to include some adjustments to their base case load forecasts to account for energy

efficiency program impacts. In most cases, thes e efforts are focused on including the future

25 While EPA’s approach utilizes AEO forecasts of electri city use and peak loads, other credible and long-term

forecasts could be used in a similar manner. U.S. EPA, Background and Draft Methodology for Estimating Energy

Impacts of EE/RE Policies (March 2014), available at: http://epa.gov/statelocalclimate/state/statepolicies.html

. 26 For example, annual incremental and cumulative ener gy 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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24 anticipated impacts of existing “on the books” energy efficiency requirements and programs and

adjusting load forecasts accordingly. However, in so me cases there is also an effort to anticipate

new incremental energy efficiency investments in th e future that are not tied to existing energy

efficiency requirements and programs. 29 When conducting a projection of EGU CO 2 emission

performance as part of a state plan that include s energy efficiency requirements and programs, it

will be important to know how the base electri city load forecast for the state or region was

developed, whether it al ready includes the effect of state and utility energy efficiency

requirements and programs, and whether and how it should be adjusted to account for the future

effects of existing on-the-books and incremental (i.e., new) energy efficiency requirements and

programs that are included in the state plan.

1.1 Potential Uses of Energy Efficien cy Projections for State Plan Emission

Projections

Whether developed through a bottom-up or top-down approach, projections of annual

energy and peak load reductions that result from state energy efficiency requirements and

programs included in a state plan are nece ssary inputs to projections of EGU CO 2 emission

performance under the state plan. Energy and peak demand savings estimates included in energy

efficiency projections are used as a decrement to fu ture electricity load forecasts that are used in

conducting EGU CO 2 emission performance projections. The energy efficiency projection is

used as an input, or modifier, to various models or other tools used to project the impact of

energy efficiency resources on state or regional CO 2 emissions. For example capacity expansion

and dispatch planning models are capable of incorporating energy efficiency program impact

data, such as annual energy and peak load reductions, when projecting EGU dispatch and

capacity additions, and the avoided CO 2 emissions that are projected to result from these

requirements and programs.

1.2 Data Issues and Considerations for Using and Developing Energy Efficiency

29 In New England states that have policies to pursue “all cost-effective energy effici ency,” the ISO-NE energy

efficiency forecast assumes that energy efficiency program investments will continue beyond the approved program

funding period (typically documented three-year plans), either at a constant level or so me discounted level based on

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25 Projections

Depending on what data sources and approaches are used to project the future energy and

demand savings from energy efficiency requirements and programs, there are certain strengths

and limitations regarding the a pproach and methodology used. Generally, these strengths and

limitations relate to data availability and en ergy efficiency forecast assumptions, such as:

 Energy efficiency requirements and programs included

 Jurisdictions covered

 Planning timeframe

 Embedded energy and demand savings from energy efficiency requirements and

programs in base electricity load forecasts

 Cost of saved energy for different energy efficiency measures

 Energy efficiency measure life and measure energy performance decay

 Time of energy and demand savings for energy efficiency measures (availability of

hourly data necessary to derive a load reduction profile for an energy efficiency measure)

Bottom-up versus top-down forecasting approaches have different strengths and

limitations related to the data and assumptions described above. In the case of bottom-up

approaches, state energy efficiency requirements and programs can be fully addressed in the

analysis. In top-down approaches, such as EIA AEO analysis, greater focus is placed on federal

policies (e.g., codes and standards) but less data is incorporated to reflect state energy efficiency

requirements and programs. Bottom-up approaches typically include state-specific data that are

rolled up to a regional level, while top-down national electricity load forecasts do not have a

comparable level of granular state data detail. ISO New England provides energy and demand

savings forecasts for state energy efficiency programs (average annual and peak demand

coincident with the ISO defined peak load peri ods). The ISO NE energy efficiency forecast is

informed by data collected at the energy ef ficiency measure, individual program, program

portfolio, sector, and state levels.

An important consideration with both top-down and bottom-up energy efficiency

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26 the long-range economic forecasts used as an input in developing electricity load forecasts. In

some cases the economic forecast includes the eff ect of historical energy efficiency policies,

either implicitly or explicitly, while in othe r cases the economic forecast may also anticipate

some limited quantity of future energy effici ency 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 installi ng 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 asso ciated deeper levels of energy saving s, to increasing cost of saved energy.

Economies of scale, and expertise gained by program ad ministrators from managing larger programs for multiple

years, can lead to cost reductions. However, at some point, as program administrators move away from initial lowcost strategies and end-use en ergy efficiency measures, it is assumed that the cost of saved energy will increase.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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27 applied to energy efficiency projections to provide a better estimate of the timing of energy and

demand savings. Such time-diffe rentiated data is valuable for identifying the marginal EGU or

cohort of marginal EGUs that are affected by energy efficiency requirements and programs,

which can be used to provide more refined estimates of avoided CO 2 emissions due to changes in

EGU dispatch and the addition of new generating capacity.

2. Potential Approaches for Estimating the Future Effects of State Renewable

Energy Requirements, Programs, and Measures

This section describes data and analytic considerations for the representation of

renewable energy requirements and programs included in state plans, when conducting

projections of EGU CO 2 emission performance that will be achieved under a plan. A range of

data and analytic considerations are examined that may be relevant when using different

modeling approaches, including use of capacity expansion and dispatch planning models, and

less sophisticated statistical or top-down projection approaches. Examples of specific

considerations are described for three renewable energy policies that may be used as enforceable

measures in a state plan— renewable portfolio standards (RPS), feed-in tariffs (FIT), and

performance-based tax incentives.

2.1 Renewable Portfolio Standards

RPS requirements are typically set at the state level with an increasing percentage of total

retail sales over a set schedule. The RPS requirement defines the eligible resource types (e.g.,

wind, solar, etc.) and in some cases, may specify resource-specific requirements, such as a

percentage of the overall RPS target that is set-aside for a specific resource. It also defines the

allowable geographic boundary for obtaining renewa ble energy or RECs. W ith this context, the

following issues may be important to consider when projecting the impact of state RPS on EGU

CO 2 emissions.

2.1.1 RPS as an Input to Electricity Sector Modeling

Electricity sector modeling includes the use of dispatch simulation models and capacity

expansion and dispatch planning models that simulate the operation of individual EGUs (or

aggregations of EGUs) on the electric system ove r time based on a detailed characterization ofI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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28 those EGUs, engineering and market operating constr aints, other market factors (e.g., fuel prices,

transmission constraints), emission constraints, and the requirement to meet a certain level

energy and peak demand. These models may be based on a small control area, but more likely

are regional or national in scope. Some, such as capacity expansion and dispatch planning

models, simulate EGU dispatch and also consider the impact of long-term generating capacity

investment decisions when optimizing system operation and buildout over a long-term planning

horizon. These are typically optimization framew orks that have as their objective meeting

electricity demand subject to a broad range of operating, environmental and market constraints,

including meeting RPS requirements.

When using these types of analytic tools to project EGU CO 2 emissions, a number of

analytic and data considerations are relevant for analysis of RPS impacts on EGU CO 2

emissions. These analytic and data considerations are summarized below.

Translation of RPS Requirements to Re newable Energy Generation Requirements

Most RPS are retail sales-based requirements, while most electricity sector analytic tools

are generation-based models. When projecting CO 2 emission performance by affected EGUs

using a generation-based analysis tool, it is necessary to translate the RPS sales-based

requirement to a generation requirement using a transmission and distribution loss rate to “ gross

up” the sales estimate. For example, if an RPS requires 100 MWh of sales be met with eligible

renewable energy resources, then the required renewable energy generation necessary to meet

the RPS is 100 MWh / (1 + T&D Loss rate). 31

RPS-Eligible Resources vs. St ate Plan-Eligible Resources

Some RPS rules define a broad range of eligible renewable energy generating resources.

These could include renewable energy EGUs that emit CO 2 , and EGUs that were constructed and

began operation recently or many years ago. Some of these specific EGUs may not be eligible

for use in a plan, in particular units that began operation prior to eligibility dates for actions that

31 According to EIA data, nationally, annual electricity tr ansmission and distribution losses are equivalent to about

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29 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 analys is should explicitly address these resources. This

could be done either through an adjustment of the MWh needed to meet the RPS, to account for

renewable energy resources that are not eligible for use in a state plan, or through the use of two

modeled RPS requirements for each class of renewable energy resource, with the RPS that

addresses resources not eligible in a state plan addressed in the modeling reference case.

In/Out-of-State Contribution

Some RPS allow some of the requirement to be met by out-of-state resources. Some

modeling frameworks may allow the user to exp licitly specify the source region of eligible

renewables. From a modeling perspective, this means a state would allow a broader supply area

and model a broader area generally. If the renewable energy resources have different

characteristics across the relevant geographic area , then data is needed on the characteristics of

these resources by region (e.g., resource availability, performance, and capital and production

costs). EIA (for NEMS), EPA (for IPM), and NREL (ReEDS) provide information on the

characteristics and performance of renewable energy resources by region. 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 s ubstantially 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 ta ken pursuant to an existing state requirement, program, or

measure could be applied toward meeting the required level of emission performance in a state plan if these actions

occur after proposal of the emission guidelines (e.g., as of June 2014 and in subsequent years).

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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30 of electricity to the grid from the EGU is based on availability of the renewable energy resource.

The time during which electricity generation is s upplied will influence the marginal fossil fuelfired EGU (or cohort of EGUs) that is displaced by renewable energy generation. Understanding

the renewable energy resource base, including the energy profile of the relevant renewable

energy resource types will improve the modeling of EGU dispatch and projections of avoided

CO 2 emissions that result from renewable energy generation. Data may include a detailed 8760

energy output profile for renewable energy resour ces, 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 economi cs. This requires understanding the relative

economics (e.g., capital costs, fixed operation and maintenance (FOM) costs, variable operation

and maintenance (VO&M) costs, and fuel costs) and operating conditions for different types of

renewable energy generators, as well as rene wable energy resource availability (e.g., MW

capacity available at different wind classes, sola r insolation levels, and the characteristics of

biomass). Having this information allows for be tter projections of the level and quality of

renewable resources likely to be brought forward as the result of a state RPS. This will result in

better emissions projections.

34 NREL’s datasets are intended for use by energy professionals, such as transmission planners, utility planners,

project developers, and university rese archers who perform wind and solar inte gration studies and need to estimate

power production from hypothetical wind a nd solar plants. The Eastern Wind Dataset

( http://www.nrel.gov/electricity/transmission/eastern_wind_methodology.html ) contains modeled wind farm data

points for the eastern United States for 2004, 2005, and 2006. The Western Wind Dataset

( http://www.nrel.gov/electricity/transmission/western_wind_methodology.html ) includes information about the

methodology used to develop the datase t, the accuracy of the data, site selection, and power output. The Solar

Integration Datasets (http://www.nrel.gov/electricity/transmissi on/solar_integration_methodology.html ) are solar

photovoltaic (PV) power plant five-minute and hourly day- ahead forecasts of generation output for approximately

6,000 simulated PV plants in the Un ited States for the year 2006.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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31 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 requ ired after-tax ra te 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 l east a regional, if not national, modeling framework.

A broader framework captures co mpetition for renewables (and incr eased prices, gr eater reliance

on poorer resources), as well as market-wide im pacts on EGU dispatch and capacity expansion.

2.1.2 Data Needs for Estimating Generation Resulting from State RPS

Projections of renewable energy generation will require assembling the following data:

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-ener gy-models) makes performance predictions and cost of

energy estimates for grid-connected power projects based on system design parameters that the user specifies. The

SAM cash flow model (http://sam.nrel.gov/) helps assess so lar, wind, or geothermal projects, design cost-based

incentives, and evaluate the impact of tax incentives or other support structures on renewable energy projects.

36 The CREST model is a product of a 2009-2010 partners hip between the National Renewable Energy Laboratory

(NREL), the U.S. Department of Energy (DOE) Solar Energy Technologies Program (SETP), and the National

Association of Regulatory Utility Commissioners (NARUC ). The model was developed by Sustainable Energy

Advantage (SEA) under the direction of NREL. The report, user manual, and CREST models are free and available

for download at: https://financere.nrel.gov/finance/content/crest-cost-energy-models.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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32  Resource availability, resource performance, and resource costs will be necessary for the

more sophisticated modeling approaches described above.

 Projections of retail sales, by year, adjusted to account for any exclusions from the RPS

obligation (e.g. small utilities, cooperatives , municipalities, or perhaps certain large

industrial loads). These covered sales must be calculated and projected using forecasts of

annual retail demand.

 RPS requirements by year, so the annual forecas t of covered retail sales can be multiplied

by these percentages.

 The extent to which credit multipliers are used for compliance. Credit multipliers reduce

the number of MWh needed for RPS compliance, and a downward adjustment should be

made based on the percentage of comp liance achieved by credit multipliers.

 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 sati sfy the RPS is expected to come from out

of state, the basis for these assumptions should be documented.

 CO 2 emission rate associated with renewable energy generation, by resource type (if

applicable).

 Generation profile, by renewable energy resource type

2.2 Feed-in Tariff (FIT) and Ot her Performance-Based Incentives

A feed-in-tariff is a performance-based incen tive (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 sp ecific 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 tariffI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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33 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 rene wable energy generation that will be provided by year for the FIT,

along with estimates of payments to be made. These should capture the impacts of

interactions with other policies, including RPS requirements, net metering, and federal

investment and production tax credits. If generators receiving FIT payments are also

eligible to satisfy an RPS, states should en sure their estimates of renewable electricity

generation are not double-counted. For analysis using a detailed capacity expansion and

dispatch planning model, market penetration of renewable energy generation to meet an

RPS may be an output of the model. In this case, information is required on the capital

costs, FOM costs, and VOM costs of the renewable energy generating technology. This is

the same information required for modeling an RPS; however, the modeling or analysis

mechanism may differ. For example, these costs may be reduced directly in a modeling

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 pr ice 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.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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34 generation subject to the tariff based on rate impacts. If retail electricity rate impacts or

budgetary impacts become unsustainable, the projected generation resulting from the FIT

will be overstated.

2.2.1 Data Needs for Estimating Genera tion Resulting from Feed-In Tariff and

Performance-Based Tax Incentives

Projections of renewable gene ration that will occur as the result of FITs and other

performance-based incentives will require asse mbling the following data about the specific

incentive programs that will suppor t renewable energy generation:

 Caps on generating capacity, if any, by year, because such caps will limit the amount of

renewable energy generation resulting from the tariff or tax incentive.

 Capacity amounts by renewable energy resour ce type that will be subject to a FIT or

other performance-based incentives, and the capacity factors for these resource types, so

that total generation in MWh can be calculated.

 Payment levels per kWh or MWh for each year of the FIT or other production-based

incentive.

 Budget amounts, if known, by year, which may be expended to support renewable

generation. When divided by the incentive payment levels, on a per-kWh or per-MWh

basis, these budget amounts will yield an estim ate of the total electric generation that will

be supported by the FIT or other production-based incentive.

 State experience and trends with FITs a nd other production-based incentives. Lacking

budget or capacity limits, prior experience in the state, or the experience of other states

and utilities, normalized for state or util ity size, could be the basis for estimated

renewable energy generation at a given incentive level.

 Because performance is metered at the busbar (i.e., the point of interconnection to the

electricity transmission or dist ribution system), no adjustments would be needed for T&D

losses.

 Estimates of the geographic origin, by state, of generation that receives support from

these programs. In most cases, eligible generation will be in-state, but if generation isI NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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35 expected to come from out of state, the basis for these assumptions should be

documented.

 CO 2 emission of renewable energy generation, by resource type (if applicable).

B. Emission Budget Trading Programs

Emission budget trading programs establish an emission limit for a group of emission

sources and establish a budget of tradable emission allowances equal to the emission constraint

for the group of sources. An emission allowance typically represents a limited authorization to

emit one ton of a regulated pollutant. These programs also typically include a number 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 fo r source categories in addition to EGUs. As a

result, state plan emission projections will need to accurately account for and represent these

compliance flexibilities, as well as the scope of affected sources if they are broader than EGUs

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

CO 2 emissions from affected sources, considering these compliance flexibilities.

1. Addressing the Sectoral Scope of Emission Budget Trading Programs

Some existing state emission budget trad ing programs addressing GHG emissions

38 Depending on the program, these cost containment allowa nce reserves make additional allowances available from

within the base emission budget (i.e., from “within the emission cap”), or add to the base emission budget (i.e.,

increase the emission cap).

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)”?I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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36 regulate emission sources in addition to EGUs, such as industrial sources. 40 We refer to these

here as multi-sector emission budget trading progr ams. All existing state emission budget trading

programs addressing GHG emissions include out-of -sector project based emission offsets, which

may be used to cover a portion of the compliance obligation of affected sources.

For multi-sector emissions budg et trading programs, state plan emission projections

would need to evaluate projected CO 2 emissions across all source categories covered by the state

or multi-state program. This would be necessary to project the CO 2 emissions performance of

affected EGUs under the multi-sector emissions budget trading program.

For emissions budget trading programs that re gulate EGUs and include offsets, which we

define here as emissions reductions from sources not regulated by the trading program, emissions

reductions from offsets would not be counted when evaluating CO 2 emission performance of

affected EGUs, because those reductions would not come from those affected EGUs. However,

state plan emissions projections would need to ev aluate the use and impact of offsets, because

the availability of offsets would affect the amount of CO 2 emissions from affected EGUs.

Addressing Multi-Sector Emission Trading

A state or regional emissions budget trading program could potentially regulate sources

from multiple emissions sectors beyond the electric generating sector that is the focus of the EPA

emission guidelines. For example, the California GHG emissions budget trading program is a

multi-sector emissions trading program that address emission sources outside the scope of the

EPA emission guidelines for EGUs. If a multi- sector emissions budget trading program is

included in a state plan, CO 2 emission projections provided as part of the state plan will need to

evaluate projected CO 2 emissions across all covered emissions sectors under the program. This

would be necessary to project the CO 2 emissions or weighted average CO 2 emission rate of

affected EGUs that will be achieved under th e multi-sector emissions budget trading program

included in the state plan.

40 The California GHG emission trading program also includ es large industrial sources and as of 2015 will include

distributors of transportation, natural gas, and other fuels.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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37 Evaluating the projected impact of a multi-sector emissions budget trading program on

the CO 2 emissions performance of affected EGUs introduces an additional level of analytical

complexity to emissions projections. For example, additional modeling capabilities may be

necessary to adequately evaluate CO 2 emissions performance across sectors in a multi-sector

emissions budget trading program.

Adequately projecting the CO 2 emissions of affected EGUs subject to a multi-sector

emissions budget trading program may require modeling using a multi-sector energy model. 41

The use of an electricity sector dispatch and cap acity expansion planning model, might also be

required, as a complement to a multi-sector model. Some multi-sector models, include an

electricity sector dispatch and capacity expans ion planning module. However, use of a standalone electricity sector model, might also be n ecessary as a supplement to a multi-sector energy

model, in order to project CO 2 emissions or the weighted average CO 2 emission rate from

affected EGUs at a sufficient level of resoluti on for state plan emission projections. Under this

approach, a multi-sector energy model might be used to project the level of CO 2 emissions

abatement achieved across the multiple emission s ectors covered by the program. This multisector projection could be used to develop a CO 2 marginal abatement cost curve representing

cost-effective, non-electricity sector emission re duction opportunities at increasing cost levels.

The marginal abatement cost curve would then serve as an input assumption for the electricity

sector capacity expansion and dispatch planning model, which would be used to project the CO 2

emission performance of affected EGUs (e.g., the CO 2 emissions or CO 2 emission rate of

individual affected EGUs, or the total CO 2 emissions or weighted average CO 2 emission rate

across multiple affected EGUs). 42

41 For example, the Energy 2020 model was used by Cali fornia to evaluate the impacts of its multi-sector GHG

emissions budget trading program. Other multi-sector models are available with similar capabilities, such as the

National Energy Modeling System (NEMS) developed and implemented by the U.S. Energy Information

Administration (EIA).

42 This marginal abatement co st curve would be applied in a similar manne r as marginal abatem ent cost curves are

applied for GHG emission offsets in modeling analyses of emission budget trading programs. Form a modeling

perspective, emission reductions from other sectors could be used by affected EGUs to demonstrate compliance with

the emission limit. When economic to do so, emission re ductions from affected EGUs would be foregone and

replaced by emission reductions from emission sources in othe r sectors that are also subject to the multi-sector

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38 Multi-sector emission budget trading programs also often address GHGs beyond CO 2 . If

this is the case, emission projections in a state plan would need to account for emissions

abatement opportunities for each of the GHGs regulated under the program, and project

emissions reductions for each of the regulated GHGs. This would be necessary to project the

extent to which affected emission sources in di fferent industrial sectors reduce emissions of nonCO 2 GHGs, which could impact projected CO 2 emissions from affected EGUs.

Addressing Emission Offsets

Emission offsets in CO 2 or GHG emissions budget trading programs represent projectbased GHG emissions reductions outside the sector or sectors regulated by the program. 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 “CO 2 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 CO 2 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 CO 2 emissions from

EGUs regulated under the emissions budget trading program may exceed the base CO 2 emissions

budget established for the program. Offset allowances or credits are awarded in addition to the

existing CO 2 emissions budget, in exchange for CO 2 -equivalent emissions reductions achieved

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 CO 2 emissions from affected EGUs in a state plan, because the

43 “Offsets” as used in the context of CO 2 or GHG emissions budget trading programs are distinct from offsets in the

NSR permitting context under the CAA, where in certain in stances emissions of a criteria pollutant from a proposed

new facility must be offset with creditable emissions reduc tions at an existing facility, if the state or jurisdiction

where the proposed facility would be located is in non-attainment status for the pollutant.

44 This percentage increases to five and ten percent of a CO 2 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 occurr ed absent the incentive provid ed 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.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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39 use of offsets functionally expands the CO 2 emissions budget for affected EGUs. This allows

affected EGUs to emit more CO 2 while meeting their compliance obligation under the emissions

budget trading program, in exchange for CO 2 -eq. emissions reductions achieved outside of the

affected source category. As a result, to properly project the CO 2 emissions from affected EGUs

in a state plan that includes an emissions budget trading program that allows for the use of

offsets, it is necessary for modeling to also project the extent to which offsets are used by

affected EGUs for compliance. 46

Under this approach, state plans could demonstrate how would ignore the CO 2 -equivalent

emissions reductions projected to be achieved through offsets, when projecting the CO 2

emissions performance that will be achiev ed 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

CO 2 emissions or weighted average CO 2 emission rate for affected EGUs under the state plan

,

would not incorporate a credit for the CO 2 -equivalent emissions reductions represented by offset

allowances or credits used by affected EGUs for compliance with the emission budget trading

program. 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 CO 2 emissions budgets

in state regulations. However, there is no requirement limiting total CO 2 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 re present 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 CO 2 emissions or weighted average CO 2 emission rate for affected EGUs would be

based on the direct emissions from these EGUs alone, with no calculation of “net” EGU CO 2 emissions that factor in

the CO 2 -eq. 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.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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40 sources in an individual state. State regulations include reciproc ity provisions allowing emission

sources to use CO 2 allowances issued by another participating state for compliance with the state

program. This provides for state-to-state CO 2 allowance flows (and the potential for differences

in state-by-state CO 2 emissions relative to state emi ssions budgets) based on where the

allowance market determines it is most economical to achieve CO 2 emissions reductions.

However, in aggregate, the CO 2 emissions budgets in each of the participating state regulations

establish a regional cap on CO 2 emissions from affected EGUs. As a result, while a multi-state

emission budget trading program may be projected to result in CO 2 emissions from affected

EGUs consistent with a multi-state mass-based CO 2 emission performance goal, the CO 2

emissions outcomes may vary by state. This necessitates evaluating a multi-state emission

budget trading program as a whole, because the individual regulations of participating states

function together as single integrated program.

To address these issues, states participati ng in a multi-state emission budget trading

program would jointly demonstrate that the multi- state program is achieving the required level of

CO 2 emission performance on a multi-state basis, based on the CO 2 emission performance of all

affected EGUs in the multi-state group implementing the program.

Some state emission budget trading prog rams also include international partner

jurisdictions. 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 CO 2 emission performance of

affected EGUs in the subset of the program represented by U.S. states. Although the CO 2

emission performance of EGUs (or other emission sources) in a foreign country would not be

addressed in the state plan, the entire international program would be evaluated as part of the

emission projection included in the state plan. This would be necessary in order to project

international allowance flows and CO 2 emissions across all participating jurisdictions, as these

cross-jurisdictional flows would impact projected CO 2 emissions from affected EGUs in U.S.

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.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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41 states.

VI. Process Considerations

As discussed in the preamble, in section VIII.F.7, the credibility of state plans under

section 111(d) will depend in large part on ensuring credible and consistent emission

performance projections in state plans. Therefore, the use of appropriate methods, tools, and

assumptions for such projections is critical. Fu rthermore, considerations for projecting emission

performance under a state plan will differ depe nding on the type of plan. This includes

differences in how inputs to projections are derived; how projections are conducted, including

tools and methods; and how aspects of a plan are represented in these projections.

In the preamble, the EPA seeks comment on whether the EPA should develop guidance

that describes acceptable projection approaches, tools, and methods for use in an approvable

plan, as well as provide technical resources for conducting projections. This section of the TSD

elaborates on these considerations.

A. Provision of the EPA Guidance

One approach to address these considerations is for the EPA to provide recommended

guidance for EGU CO 2 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 jus tify 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.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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42  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 (oth er than the alternative standards that are

included in the state plan)

It would be necessary in many instances to include assumptions about other state

programs implemented by neighboring states in the same region. This would be especially

relevant for states that are located within the same electric power pool (or adjoining power pools)

that are administered by a common RTO/ISO. To address this need, the EPA technical guidance

could provide documentation of state programs and policies included in a reference case, as well

as those that are eligible for inclusion in a stat e 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 pl ans on a regional basis. The ISO/RTO Council,

an organization of electric grid operators, ha s suggested that ISOs and RTOs could provide

analytic support to help states develop and implement their plans. The ISOs and RTOs have the

capability to model the system-wide effects of indi vidual state plans. Providing assistance in this

way, they felt, would allow states with borders th at fall within an RTO or ISO footprint to assess

the system-wide impacts of potent ial state plan approaches. In a ddition, 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 potentiall y support and be expanded

upon to develop this component of EPA technical modelin g guidance. In particular, see Appendix I: EPA’s Draft

Methodology for Estimating Energy Impacts of EE/RE Policies. The draft manual is available at

http://www.epa.gov/airquality/eere.html . State environmental regulations addressing EGUs are itemized in the

modeling documentation for the EPA IPM Base Case v.5.13.I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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43 its plan, ISO/RTO analytic support would allow the state to monitor the effects of its plan on the

regional electricity system. ISO/RTO analytic capability could help states assure that their plans

are consistent with region-wide system reliabilit y. The ISO/RTO Council suggested that the EPA

ask states to consult with the applicable IS O/RTO in developing their state plans.

B. Party that Translates the Rate-Based Goal to a Mass-Based Goal

In the preamble, in section VIII.F.7, The EPA seeks comment on whether it should

develop guidance that describes acceptable projection approaches, tools, and methods for use in

an approvable plan, as well as provide technical resources for conducting projections.

One consideration for state plans that use a mass-based CO 2 emission performance goal

is the party that conducts the translation of the rate-based CO 2 emission performance goal in the

emission guidelines to a mass-based goal—either the EPA or the state. In the preamble, in

section VIII.D.3, The EPA seeks co mment on whether to assist states that seek to translate the

rate-based goal into a mass-based goal.

One approach is for the EPA to provide a pr esumptive translation of the state-specific

rate-based CO 2 emission performance goal to an equivalent mass-based goal for all states, for

those states that request it, and/or for multi- state regions. This could include default modeling

assumptions and results of modeling runs for a Reference Case Scenario and an EPA MassBased CO 2 Emission Goal Policy Scenario , as described above in section III.B. A state could

utilize the presumptive mass-based CO 2 emission performance goal for the state or multi-state

region identified through these EPA modeling runs. If a state proposed modifications to EPA

default modeling assumptions, it would need to ju stify these modifications as part of the CO2

emission projection included in its state plan, and present an emission projection that supports a

proposed modified mass-based CO 2 emission performance goal.

Another approach is for the EPA to provide guidance for states to use in translating a

rate-based goal to a mass-based goal. This could include information about acceptable analytical

methods and tools, as well as default input assu mptions for key parameters that will likely

influence projections, such as electricity load forecasts and projected fossil fuel prices. Under

this approach, the EPA might also provide a coor dinating 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

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44 applied by multiple states within a grid re gion, acknowledging that assumptions about state

programs across a broader grid region that are included in an analysis scenario will influence

projections of CO 2 emissions by affected EGUs in any particular state.

Under this approach, states could deviate from these default methods and assumptions

with justification. Following the guidance could provide a streamlined path for the EPA approval

of emissions projections, but states would still ha ve flexibility to use other approaches, which the

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1 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 co nditions with and without the proposed rule.

IPM is a multi-regional, dynamic, determin istic linear programming model of the U.S.

electric power sector. It provides forecasts of leas t 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 po wer 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

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2 The EPA is proposing emission guidelines for st ates 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 us e 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 capacity 3 changes from the

base case in 2020 are summarized below:

2 For more detail on the economic impacts, and more disc ussion of the compliance scenarios, see Chapter 3 of the

RIA for this proposal.

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3 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 970,150 4

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 n eeded 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 region 5 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 curr ent 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

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4 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 reductio n 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 ar e 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 rese rve 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 ta rget reserve margin in each region, through

changes in the level of retiremen ts, 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

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5 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 concer ns. 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 tr ansfer reserves, subject to summer and winter

limits that are designed to ensure that these rese rves 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 neighborin g 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 differen t), 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

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6 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 m odeling 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 region s, 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

considered 9 , combining all the individual SERC regions, the shift as a percentage of load drops

to 4.8% of the total SERC load. These overall ch anges 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

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7 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 with in 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 ne w 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 in dicate 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 be tween the options and no further reliability

issues arise in the regional case.

A similar indication of greater flexibility is s een in the transfers. The two cases with the

largest percentage shift examined above are re duced 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

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8 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 NE RC Assessment Region in 2020I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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9 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 -34,905 242,283 193,279I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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10 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 779,558 755,995 927,000 884,435I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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11 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%I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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12 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 70,649I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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13 A5. New Capacity Policy Case Incr emental 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 32,470I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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14

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%I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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15 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 2020I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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16 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 -46,118I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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17 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 779,558 755,995 927,000 885,404I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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18 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%I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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19 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 68,353I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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20 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 30,894I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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21

B6. Net Reserves Sent by NERC Asse ssment 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%I NTERAGENCY W ORKING C OMMENTS ON D RAFT L ANGUAGE UNDER EO12866 I NTERAGENCY R EVIEW

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22 Appendix C: Maps

C1. IPM Regions

C2. . NERC Assessment RegionsINTERAGENCYWORKINGCOMMENTSONDRAFTLANGUAGEUNDEREO12866INTERAGENCYREVIEW.SUBJECTTOFURTHERPOLICYREVIEW.23C1: IPM v5.13 RegionsINTERAGENCYWORKINGCOMMENTSONDRAFTLANGUAGEUNDEREO12866INTERAGENCYREVIEW.SUBJECTTOFURTHERPOLICYREVIEW.24C2:NERCAssessmentAreasinLongTermReliabilityAssessment.Source:NERC2012LongTermReliabilityAssessmentINTERAGENCYWORKINGCOMMENTSONDRAFTLANGUAGEUNDEREO12866INTERAGENCYREVIEW.SUBJECTTOFURTHERPOLICYREVIEW.25