Technical Support Document (TSD)

Carbon Pollution Emission Guidelines for Existing Stationary Sources: Electricity Utility

Generating Units

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

Incorporating RE and Demand-Side EE Impacts into

State Plan Demonstrations

U.S. Environmental Protection Agency

Office of Air and Radiation

July 31, 2015
2

I. Introduction

This technical support document details certain demonstration requirements for Clean Power 

Plan (CPP) state plan submittals that must include a projection of carbon dioxide (CO2) emission

performance by affected electric generating units (EGUs), as identified in section VIII.D.2.a(3) 

of the preamble.1 Development of a state’s CO2 emission performance projection begins with an 

electricity demand forecast, which, depending upon the type of analytical method or model used, 

the state may want to reflect the impacts of renewable energy (RE) and demand-side energy 

efficiency (EE) policies and programs. In order to develop this electricity demand forecast, first, 

the state would either select an existing base case electricity demand and supply forecast or 

develop its own. Section II below addresses how to choose or develop a base case demand and 

supply forecast as well as how to document any included RE or demand-side EE measures.

Second, the state may adjust this base case demand forecast to reflect the impacts of RE and 

demand-side EE measures included in the state plan. Section III describes how to quantify the 

impacts of RE and demand-side EE policies and programs and then adjust the base case demand 

forecast to reflect these impacts.

II. Base Case Electricity Demand and Supply Forecasts 

The CO2 emission performance projection of affected EGUs requires information from an 

electricity demand and supply forecast as a basis for predicting generation and emissions during 

the interim and final plan performance periods. This section describes the steps a state should

take to demonstrate that the base case demand forecast transparently represents future demand

and supply:

Step 1: Choose or develop a base case electricity demand and supply forecast. 

Step 2: Document RE and demand-side EE already included in the base case electricity 

demand and supply forecast.

 

1 This includes state measures type plans as well as some emission standards type plans.
3

Step 1: Choose or develop a base case electricity demand and supply forecast.

A state can develop its own base case electricity demand and supply forecast or use a forecast 

from the following information sources: 2

• U.S. Department of Energy, Energy Information Administration, Annual Energy Outlook 

(AEO),

• North American Electric Reliability Corporation (NERC),

• Regional transmission organizations (RTOs)/independent system operators (ISOs) (e.g., 

PJM Interconnection, ISO-New England, NYISO),

• Vertically integrated utilities (e.g., a large power company that operates the electricity 

system for a specific region), in combinations with another publically available source,

• State energy agencies (e.g., State Energy Office or Public Utility Commission (PUC)), 

and

• Regional councils that coordinate energy planning (e.g., Northwest Power and 

Conservation Council)

To develop its own state-specific base case electricity demand and supply forecast, a state would 

apply an annual average electricity demand growth rate derived from one of the above data 

sources to state or regional specific historical electricity sales data. States may also consider 

more comprehensive modeling approaches that calculate expected demand based on assumptions 

including: electricity prices, technology development, population, and economic forecasts. For 

the base case supply forecast, a state should inventory all generation resources available to meet 

state demand through the final plan performance periods, including in-state existing and 

anticipated capacity, and any expected imports.

Step 2: Document RE and demand-side EE measures included in the base case electricity 

demand and supply forecast.

Demand forecasts from different information sources reflect on-the-books RE and demandside EE policies to varying degrees in demand and supply forecasts. The state must therefore

research and document how on-the-books RE and demand-side EE programs included in the 

 

2 States can either adopt an existing forecast from one of these sources or use data from them to develop 

their own forecast. States may request to use a different source and EPA would review those requests on 

an individual basis. Any state-specific base case forecasts developed by states must be approved by EPA 

per the final emission guidelines. 
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demand or supply forecast used by the state are incorporated into that. This will clarify which

programs are influencing the growth rate assumptions, and the EPA will use this information to 

assess whether the demand and supply forecast is reasonable. This also helps ensure that impacts 

captured in the base case forecast are not double-counted in the base case forecast or duplicated 

in the state plan performance projection. A state should work with the source of the forecast to 

understand whether and how RE and demand-side EE policies and programs, including but not 

limited to the list below, are included in the base case electricity demand and supply forecast:

• EE policies or programs funded by utility ratepayers,

• Existing federal appliance and lighting efficiency standards that are already in effect,

• Forthcoming federal appliance and lighting standards,

• State appliance or lighting efficiency standards (if applicable),

• State building energy codes,

• Renewable portfolio standards, and

• Codified local policies.

There are at least two ways that these programs are captured in an existing forecast: 

1. Programs are explicitly identified, meaning the forecast shows a direct connection 

between the program and its impacts on energy demand or supply (MWhs),

2. Programs are indirectly, and either fully or partially, captured through econometric or 

other assumptions in the relevant economic model (e.g., as captured in National Energy 

Modeling System (NEMS)).

3

 

3 Demand-side EE programs explicitly included in a demand forecast are programs that the forecast’s 

documentation specifically states directly impact future demand levels. Some demand-side EE programs, 

however, are indirectly represented in the assumption and not explicitly identified. For example, the U.S. 

Energy Information Agency’s (EIA) Annual Energy Outlook (AEO) explicitly includes in the reference 

case for electricity demand and supply forecast existing federal appliance and equipment standards for 

residential and commercial sectors as well as state renewable portfolio standards. The AEO indirectly 

captures some impacts of state demand-side EE programs in the forecast and does not explicitly call out 

their impacts. Indirect impacts do not need to be quantified, but on a case-by case basis, a discount factor 

toward any incremental savings in the CPP performance projection may be required to adjust for potential 

double counting. For more information visit: 

http://www.epa.gov/statelocalclimate/state/statepolicies.html. 
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For all RE and demand-side EE programs included in the base case demand forecast, a state must 

document whether the program is captured explicitly or indirectly. In addition, a state must 

include the following information for on-the-books programs that are reflected in the base case

forecast:

1. Policy or program name,

2. Whether the policy is codified in state or local rule,

3. Year enacted,

4. When the policy requirements sunset.

The above requirements apply regardless of whether an RE or demand-side EE program will 

be used to meet the emission guidelines (e.g., to generate ERCs or as state measures). For 

example, assume a state with an Energy Efficiency Resource Standard (EERS) in state law 

adopts a rate-based emission standards type state plan that requires a projection. The impacts of 

the on-the-books EERS may already be included in the base case demand forecast, and if so, 

should be documented. If the affected EGUs in the state do not need to use the energy savings 

(e.g., emission rate credits (ERCs) from demand-side EE) from the state’s EERS to adjust their 

CO2 emission rates, then the state’s plan demonstration would include the four pieces of 

information noted above about its EERS to support the reasonableness of the electricity demand 

forecast.4 If the state expects affected EGUs to use the demand-side EE impacts from the EERS 

to adjust their rates, then the state plan should document the eight pieces of information noted at 

the end of this section. Similarly, under a mass-based state measures approach where the state 

EERS is not included as a state measure, the state plan demonstration would include the four 

pieces of information noted above. If the on-the-books EERS is included as a state measure, then 

the plan should document the eight pieces of information noted below. This information will 

inform the EPA's evaluation of whether the emission standards in the state plan are achievable.

In addition to documenting for on-the-books RE or demand-side EE measures the four pieces 

of information noted above and whether they are directly or indirectly captured in the base case 

demand and supply forecast, the state plan must provide additional information on certain types 

 

4 For example, affected units in the state might be able to achieve the rate-based emission standards with 

other measures or actions outside of the EERS.
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of on-the-books programs. There are at least two categories of on-the-books policies and 

programs that must be explicitly accounted for in the base case demand and/or supply forecast

and in the following manner: 

• Qualifying RE and demand-side EE programs that are implemented after 2012 and 

impact electricity generation in 2022 or later.

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o Quantify the (annual incremental and cumulative savings or generation (MWhs)) 

x (effective useful life) to estimate the savings that impacts demand or generation

in 2022 or later.

• Qualifying RE and demand-side EE programs that impact electricity generation in 2020 

or 2021 and meet eligibility requirements in the final rule regarding the Clean Energy 

Incentive Program.

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o Quantify the (annual incremental and cumulative savings or generation (MWhs)) 

x (effective useful life) to estimate the savings that impacts demand or generation

in 2020 and 2021. 

Because these on-the-books RE and demand-side EE measures or programs are explicitly

accounted for in the base case demand forecast, the same impacts must not be represented again

in the state plan performance projection. In other words, such impacts cannot be included in the 

CO2 emission performance projection, because they are already captured in that base case 

forecast. For any RE and demand-side EE programs that are explicitly included in an EGU base 

case forecast and will be used to meet the CPP emission guidelines, the state must document the 

following information:

1. Policy or program name,

2. Whether the program is codified in state or local rule,

3. Year enacted,

4. When the program requirements sunset,

5. Program requirements (e.g., targets in megawatt hours (MWh) or percentage),

 

5 Eligibility requirements related to the timing, geography and type of RE and demand-side EE measures 

that can be used to adjust a CO2 performance rate of an affected EGU under the final rule are detailed in 

section VIII.K.1. 6 For details refer to sections VIII.B.2 and VIII.K.1.a of the preamble.
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6. Annual energy savings or generation in the base year (MWh),

7. Annual and cumulative energy savings or generation in the future interim and final

periods (MWh), and

8. Estimated useful lives for programs.

III. Proper Characterization of Renewable Energy and Demand-Side

Energy Efficiency in a State Plan Performance Projection

Section VIII.D.2.a.(3)(a) of the preamble explains which types of state plans require CO2

emission performance projections for affected EGUs in order to show that the state plan will lead 

to achievement of the CO2 emission performance rates, state goal, or other emission guideline 

requirements. State plans that require such a projection must include a base case electricity 

demand and supply forecast as well as supporting documentation, as explained in section II 

above. In addition, such plans must quantify the combined future impact of all the emission 

standards and state measures included in the state plan. This section explains the proper 

characterization of expected RE and demand-side EE impacts in a CO2 emission performance 

projection.

States that plan to use RE and demand-side EE to meet the emission guidelines (e.g., to 

generate ERCs or as state measures) under applicable state plan types that require a performance 

projection will need to project the expected incremental direct generation impacts and electricity 

savings of RE and demand-side EE.

7 While RE and demand-side EE measures, programs and 

policies may impact the generation, construction, retirement and CO2 emissions of both affected 

and non-affected EGUs, a projection must demonstrate how RE and demand-side EE will enable 

affected EGUs to meet the emission guidelines. There are different approaches to projecting 

electricity savings and renewable generation, depending upon the design of an RE and demandside EE program. Regardless of the approach chosen, a state plan that includes RE and demand-

 

7 Incremental direct effects refers to RE and demand-side EE beyond any impacts that are in the base 

case. If a new program is more stringent than an existing program already in the base case, it may not be 

appropriate to use the full magnitude of the new program. 
8

side EE must document specific assumptions in their performance projections, as described 

below.

A. Approaches to Estimating Future RE Generation and EE Savings

Projections of expected annual electricity savings and/or renewable energy generation are 

necessary inputs when projecting EGU CO2 emission performance. This is because increased RE 

generation will impact the generation of affected EGUs and resulting CO2 emissions. Electricity 

savings estimates included in EE projections will lower electricity demand forecasts in the CO2

emission performance projections. The EE projection can be used as an input, or modifier, to 

various models or other tools in order to demonstrate that the state plan will achieve emission 

guideline requirements.

A CO2 emission performance projection must include the potential impacts of RE and 

demand-side EE, and the state must document how those RE and demand-side EE impacts are 

reflected in the projection. The state can incorporate RE and demand-side EE impacts at the

individual project or program level, or it can aggregate RE and demand-side EE impacts across a 

portfolio of programs.8 The EPA historically has accepted the estimation of RE and demand-side 

EE at an aggregated level as indicated in EPA’s Bundled Measures Guidance.9 The state must 

also verify that the assumptions about RE and demand-side EE availability are reasonable, such 

as based on an assessment of RE and demand-side EE potential.

As discussed above, a state plan CO2 emission performance projection must not include RE 

and demand-side EE impacts captured in the base case electricity demand forecast. 

Consequently, RE and demand-side EE impacts included in the CO2 emission performance 

projection must be incremental to and non-duplicative of impacts included in the base case

 

8 This can include state and local sponsored programs, and RE and demand-side EE projects, such as ones 

done under performance contracting, provided they meet the eligibility requirements specified in section 

VIII.K.1 of the preamble. Other types of programs and projects that may be eligible for inclusion are 

described in section VIII.K.1.a. 9 Guidance on Incorporating Bundled Measures in a State Implementation Plan, 

www.epa.gov/ttn/oarpg/t1/memoranda/10885guideibminsip.pdf.
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demand forecast. The performance projections, for example, could include impacts from RE and 

demand-side EE programs not reflected in the base case forecast or from the expansion of 

existing programs beyond levels reflected in the base case forecast. A state must use the 

following general equations to quantify the expected incremental impacts of RE and demandside EE during the future interim and final performance periods.

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Energy Efficiency:

• (Incremental first-year annual plus cumulative savings of EE program11) x (effective 

useful life) for each interim period and final period. Determine persistent level of savings 

for final period and beyond.

Renewable Energy: 

• (Incremental MW installed capacity) x (location12 and technology-specific capacity 

factors) x (8760 hours) for each interim period and final period. Determine persistent 

level of renewable energy generation for final period and beyond.

Several tools and methods are available to help states estimate the potential direct energy 

impacts of RE and demand-side EE that will be used to adjust a state’s electricity demand and 

supply forecast. States can base their electricity savings projections on past evaluation, 

measurement and verification (EM&V) reports that document impacts of similar projects or 

programs and that have been submitted to public service commissions or evaluated by third 

parties. States also can conduct their own surveys or studies to estimate the direct energy impacts 

 

10 The EPA recognizes that for unique situations, states may not be able to use these exact equations. In 

those unique circumstances, states can propose an alternative equation to EPA for approval on a case-bycase basis. 

11 Projections of demand-side EE impacts must reflect the annual impacts that occur due to new EE 

impacts in a given year plus the impacts of EE investments made in previous years that are still generating 

savings (i.e., have not exceed their measure life or otherwise ended). 

12 States can use location-specific capacity factors informed by historical data or weather-prediction 

models, such as the kind of data included in the National Renewable Energy Laboratory (NREL) Eastern 

Wind Integration and Transmission Study (EWITS) or in publicly available datasets from EIA and 

ISO/RTOs.
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of EE policies and/or use sophisticated methods, such as building simulation tools, vintaging 

models, production costing, and cost-of-energy analysis models.13 Any methodology used must 

be EPA-approved, and each state is encouraged to consult with the EPA early during the plan 

development process about the tools and methods it intends to employ.

Assessing the potential RE and demand-side EE impacts of measures, policies or programs 

can involve bottom-up economic and/or engineering-based estimation techniques that are based 

upon a representation of the fundamentals of the technology and economic behavior. These 

bottom-up approaches estimate potential energy savings at a very detailed level and roll these 

estimates up to the statewide level. Alternatively, the potential impacts of RE and demand-side 

EE can be quantified based upon the design and requirements of state-level policies and 

regulations specified over a future time frame. The next two sections describe how a state plan 

CO2 performance projection would calculate the generation impacts of two common state 

policies: energy efficiency resource standards and renewable portfolio standards.

B. Projecting Energy Savings from Energy Efficiency Resource Standards

Many states have adopted an EERS, which is a policy that sets targets for energy savings 

over a specified time frame from demand-side EE programs operated by utilities or other 

program administrators. States typically specify annual first-year or cumulative targets as 

percentages of electricity sales or as absolute energy savings. States use different bases for 

specifying EERS goals. Some specify goals based on electricity sales (in MWhs) from investorowned utilities, while others have mandated energy savings targets based on total MWh sales or 

a subset of total MWh sales.

A state can quantify energy savings for use in its CO2 emission performance projection using 

formulas specific to the state’s EERS, as described below.

14 For this approach a state would 

 

13 For more information about available tools for estimating direct energy impacts, see Assessing the 

Multiple Benefits Guide: A Resource for States, Chapter 2. 

http://www.epa.gov/statelocalclimate/documents/pdf/epa_assessing_benefits_ch2.pdf#page=4. 14 Savings from purely voluntary demand-side EE goals are not state enforceable measures and are not 

eligible for use in a CO2 emission performance projection for a state measures type plan. Quantification 

of eligible demand-side EE savings must be done in accordance with the requirements specified in section 

VIII.K.3 of the preamble.
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select the appropriate sales basis, and if the basis is not total sales, a state could use recent year 

utility-level sales data from EIA and growth rates from EIA, an RTO/ISO, NERC or other 

publicly available sources to develop base case forecasts of sales of the utilities required to 

comply with the EERS. The design of the EERS will affect whether a state, for purposes of its 

CO2 emission performance projection, should assume energy savings at the EERS target level.

For example, it may not be appropriate to assume full achievement of energy savings goals in an 

EERS that includes cost/rate caps or other design features that may not lead to incremental 

energy savings relative to the base case demand forecast (e.g., counting savings from building 

energy codes or historical EE programs). 

The general formulas a state must use to quantify first-year and cumulative energy savings 

from an EERS policy for each year (t) are shown below, though a state may propose a different 

methodology if it better represents the state’s EERS. Once these first-year and cumulative energy 

savings are quantified, the state can incorporate them into the demand forecast of its CO2

emission performance projection.

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1. EERS with Annual First-Year EE Savings Targets Specified in Percent Terms

A(t) = r(t) Z(t-1)

C(t) = A(t) + A(t-1) + ... + A(t-L+1)

I(t) = C(t) - E(t)

Z(t) = B(t) - I(t) 

Where:

r is the annual first-year percent savings target, 

A is the annual first-year energy savings, 

L is the measure lifetime, 

B is the base case sales of utilities affected by these specific policies, 

C is the cumulative energy savings, 

E is the cumulative savings embedded in the base case demand forecast,16

I is the cumulative savings incremental to the base case demand forecast, and 

Z is the adjusted sales after application of cumulative incremental savings.

 

15 These equations are the recommended calculation methods for inclusion in state plans. 

16 States using the AEO 2013 forecast should take note that it does not include state-level EERS policies 

but does embed EE savings of policies. These EE savings are not reported out by the AEO and need to be 

determined independently. 
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For example, a representative state has an EERS first-year target of 2% for each year 2016-

2018. Forecasted baseline sales of utilities in 2015 are 50,000 GWh, growing by 1% each year of 

the forecast period. Embedded savings are 50 GWh per year, applied to years in which first-year 

energy savings are realized. The measure lifetime assumed for both first-year energy savings and 

embedded savings is four years. Table 1 applies this example to the above formula. This is the 

most common type of EERS structure, and states having adopted some version of it include 

Arizona, Illinois, Indiana, and Ohio. 

Table 1: Example EERS with Annual First-Year EE Savings Targets Specified in Percent Terms

2015 2016 2017 2018 2019 2020 2021 2022

Baseline sales of affected 

utilities (GWh) (B)

50,000.0 50,500.0 51,005.0 51,515.1 52,030.2 52,550.5 53,076.0 53,606.8

First-year percent savings 

target (%) (r) 

2% 2% 2%

First-year energy savings 

(GWh) (A)

1,000.0 991.0 982.3

Cumulative energy savings 

(GWh) (C) 

1,000.0 1,991.0 2,973.3 2,973.3 1,973.3 982.3 0.0

Cumulative savings 

embedded (GWh) (E) 

50.0 100.0 150.0 150.0 100.0 50.0 0.0

Cumulative savings 

incremental (GWh) (I) 

950.0 1,891.0 2,823.3 2,823.3 1,873.3 932.3 0.0

Adjusted sales after 

incremental savings (GWh) (Z) 

50,000.0 49,550.0 49,114.0 48,691.8 49,206.9 50,677.2 52,143.7 53,606.8

2. EERS with Annual First-Year EE Savings Targets Specified in Absolute Terms

C(t) = A(t) + A(t-1) + ... + A(t-L+1)

I(t) = C(t) - E(t)

Z(t) = B(t) - I(t) 

Where: 

A is the annual first-year energy savings target,

L is the measure lifetime, 

B is the base case sales of utilities affected by these specific policies, 

C is the cumulative energy savings, 

E is the cumulative savings embedded in the base case demand forecast, 

I is the cumulative savings incremental to the base case demand forecast, and 

Z is the adjusted sales after application of cumulative incremental savings.

For example, a representative state has an EERS first-year target of 1,000 GWh in 2016, 

increasing by about 2% per year for 2017-2018 to the absolute targets shown in the table below.

Forecasted baseline sales of utilities in 2015 are 50,000 GWh, growing by 1% each year of the 
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forecast period. Embedded savings are 50 GWh per year, applied to years in which first-year 

energy savings are realized. The measure lifetime assumed for both first-year energy savings and 

embedded savings is four years. Table 2 applies this example to the above formula. States that 

applied this structure during their EERS implementation include Florida, Iowa, and Oregon. 

Table 2: Example EERS with Annual First-Year EE Savings Targets Specified in Absolute Terms

2015 2016 2017 2018 2019 2020 2021 2022

Baseline sales of utilities 

(GWh) (B)

50,000.0 50,500.0 51,005.0 51,515.1 52,030.2 52,550.5 53,076.0 53,606.8

First-year energy savings 

(GWh) (A)

1,000.0 1,020.0 1,040.4

Cumulative energy savings 

(GWh) (C) 

1,000.0 2,020.0 3,060.4 3,060.4 2,060.4 1,040.4 0.0

Cumulative savings 

embedded (GWh) (E) 

50.0 100.0 150.0 150.0 100.0 50.0 0.0

Cumulative savings 

incremental (GWh) (I) 

950.0 1,920.0 2,910.4 2,910.4 1,960.4 990.4 0.0

Adjusted sales after 

incremental savings (GWh) (Z) 

50,000.0 49,550.0 49,085.0 48,604.7 49,119.8 50,590.1 52,085.6 53,606.8

3. EERS with Cumulative EE Savings Targets Specified in Percent Terms

A(t) = C(t) – C(t-1) + A(t-L)

If r(t) available,

C(t) = r(t) x B(t)

I(t) = C(t) - E(t)

Z(t) = B(t) - I(t)

If r(t) not available,

Z(t) calculated by interpolation

I(t) = B(t) - Z(t)

C(t) = I(t) + E(t)

Where: 

r is the cumulative percent savings target, 

A is the annual first-year energy savings, 

L is the measure lifetime, 

B is the base case sales of utilities affected by these specific policies, 

C is the cumulative energy savings, 

E is the cumulative savings embedded in the base case demand forecast, 

I is the cumulative savings incremental to the base case demand forecast, and 

Z is the adjusted sales after application of cumulative incremental savings.
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For example, a representative state has an EERS cumulative target of 5% by 2018. 

Forecasted baseline sales of utilities in 2015 are 50,000 GWh, growing by 1% each year of the 

forecast period. Embedded savings are 50 GWh per year, applied to years in which first-year 

energy savings are realized. The measure lifetime assumed for both first-year energy savings and 

embedded savings is four years. Distribution of the cumulative energy savings in 2018 to the 

first-year savings for 2016-2018 applies the simple assumption of an equal share of savings 

being implemented in each year. Table 3 applies this example to the above formula. This 

approach is uncommon, and states that applied this structure in earlier years of their EERS 

policies include New York and Pennsylvania. 

Table 3: Example EERS with Cumulative EE Savings Targets Specified in Percent Terms

2015 2016 2017 2018 2019 2020 2021 2022

Baseline sales of utilities 

(GWh) (B)

50,000.0 50,500.0 51,005.0 51,515.1 52,030.2 52,550.5 53,076.0 53,606.8

Cumulative percent savings 

target (%) (r) 

5%

First-year energy savings 

(GWh) (A)

858.6 858.6 858.6

Cumulative energy savings 

(GWh) (C) 

858.6 1,717.2 2,575.8 2,575.8 1,717.2 858.6 0.0

Cumulative savings 

embedded (GWh) (E) 

50.0 100.0 150.0 150.0 100.0 50.0 0.0

Cumulative savings 

incremental (GWh) (I) 

808.6 1,617.2 2,425.8 2,425.8 1,617.2 808.6 0.0

Adjusted sales after 

incremental savings (GWh) (Z) 

50,000.0 49,691.4 49,387.8 49,089.3 49,604.4 50,933.3 52,267.4 53,606.8

4. EERS with Cumulative EE Savings Targets Specified in Absolute Terms

A(t) = C(t) – C(t-1) + A(t-L)

If C(t) available,

I(t) = C(t) - E(t)

Z(t) = B(t) - I(t)

If C(t) not available,

Z(t) calculated by interpolation

I(t) = B(t) - Z(t)

C(t) = I(t) + E(t)

Where:

C is the cumulative energy savings target, 

A is the annual first-year energy savings, 
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L is the measure lifetime, 

B is the base case sales of utilities affected by these specific policies, 

E is the cumulative savings embedded in the base case demand forecast, 

I is the cumulative savings incremental to the base case demand forecast, and 

Z is the adjusted sales after application of cumulative incremental savings.

For example, a representative state has an EERS cumulative target of 3,000 GWh by 2018. 

Forecasted baseline sales of utilities in 2015 are 50,000 GWh, growing by 1% each year of the 

forecast period. Embedded savings are 50 GWh per year, applied to years in which first-year 

energy savings are realized. The measure lifetime assumed for both first-year energy savings and 

embedded savings is four years. Distribution of the cumulative energy savings in 2018 to the 

first-year savings for 2016-2018 applies the simple assumption of an equal share of savings 

being implemented in each year. Table 4 applies this example to the above formula. States that 

utilized this structure during EERS implementation include California and Hawaii. 

Table 4: Example EERS with Cumulative EE Savings Targets Specified in Absolute Terms

2015 2016 2017 2018 2019 2020 2021 2022

Baseline sales of utilities 

(GWh) (B)

50,000.0 50,500.0 51,005.0 51,515.1 52,030.2 52,550.5 53,076.0 53,606.8

First-year energy savings 

(GWh) (A)

1,000.0 1,000.0 1,000.0

Cumulative energy savings 

(GWh) (C) 

1,000.0 2,000.0 3,000.0 3,000.0 2,000.0 1,000.0 0.0

Cumulative savings 

embedded (GWh) (E) 

50.0 100.0 150.0 150.0 100.0 50.0 0.0

Cumulative savings 

incremental (GWh) (I) 

950.0 1,900.0 2,850.0 2,850.0 1,900.0 950.0 0.0

Adjusted sales after 

incremental savings (GWh) (Z) 

50,000.0 49,550.0 49,105.0 48,665.1 49,180.2 50,650.5 52,126.0 53,606.8

C. Projecting Generation Impacts from Renewable Portfolio Standards

Renewable portfolio standards (RPS) set RE targets across a specified period of time. Most 

often these state policies require that a specified percentage of the electricity sold by a utility 

comes from eligible renewable technologies (e.g., wind, solar, biomass).

A state must project annual RE generation using formulas specific to the state’s RPS policy, 

as shown below, or an EPA-approved alternative method. Similar to the EERS approach 

described above, a state would select the appropriate sales basis, and if the basis is not total sales, 

a state could use a recent year of utility-level sales data from EIA and growth rates from EIA, an 
16

RTO/ISO, NERC or other publicly available sources to develop base case forecasts of sales for 

the utilities required to comply with the RPS. 

The design of the RPS will affect whether a state can assume full achievement of the RPS 

targets. Many RPSs include provisions for alternative compliance payments, which allow an 

entity to pay a fee in lieu of achieving the RPS. Additionally, RPS policies may include sources

that are not eligible for CPP compliance purposes. In such cases, only generation impacts from 

eligible RE sources should be included in a state’s CO2 emission performance projection.

17

The general formulas a state must use to quantify annual generation impacts of an RPS 

policy for each year (t) are shown below, though a state may propose a different methodology if 

it better represents the state’s RPS.18

1. RPS with Annual Targets Specified in Percent of Retail Sales Terms

A(t) = r(t) x Z(t) – MWhineligible(t)

Where:

A is the total MWh of CPP-qualifying renewable generation in a future year,

r is the annual RPS percent RE target,

Z is the forecasted electricity sales that fall under the RPS policy, and

MWhineligible is the MWh of generation from technologies ineligible under CPP

(t) is the year 

Note that each state should apply this general formula to its specific RPS design. For example, if 

a specified percentage of RE is required to be met by sales from investor-owned utilities and 

separate percentage from rural cooperatives, then the state should apply the formula individually 

 

17 States must represent measures in their projection in accordance with the accounting and eligibility 

requirements specified in the guidelines, irrespective of the ways that RE is counted under a state 

requirement, such as an RPS, or for the purposes of renewable energy certificates. For example, some 

RPS apply an adjustment factor or allow credit different from the accounting method included in the final 

rule. RE generation from purely voluntary RE goals are not state enforceable measures and are not 

eligible for use in a performance projection for a state measures plan type. Similarly, alternate compliance 

payments, state-level bonuses for RE and RE resources permitted under an RPS that are not permitted 

under the final guidelines are not eligible to demonstrate performance in a projection. For more 

information about acceptable accounting methods for RE, see sections VIII.K.1 and VIII.K.2 of the 

preamble. For information about addressing interactions between renewable energy credits (RECs) and 

emission rate credits, see section VIII.K.2.

18 The equations in this section are the recommended calculation methods for inclusion in state plans.
17

for each class and sum the MWh for each to calculate A(t). Additionally, each state plan should 

estimate the MWh of generation from any technologies that fall within the scope of its RPS but 

outside CPP. This estimate (MWhineligible) can be based on planned and/or expected new 

capacities for these technologies and best-available historical capacity factors.

For example, take a representative state with an RPS target of 10% in 2015, rising to 15% 

by 2020. Forecasted sales in 2015 are 75,000 gigawatthours (GWh), growing in subsequent 

years. In 2015, the renewable requirement is 7,500 GWh, but 500 GWh of the RPS is met by 

technologies ineligible under the final CPP. As a result, eligible renewable generation is 7,000 

GWh in 2015. Assuming the same MWhineligible in future years, the state would predict 11,500 

GWh of CPP eligible renewables in 2020. The table below applies this example to the above 

formula. This is a common type of RPS policy. States with structures similar to this include 

Massachusetts, North Carolina, and Illinois.

Table 5: Example Qualifying Renewable Energy Calculation

2015 2016 2017 2018 2019 2020

RPS Target (%) 10% 11% 12% 13% 14% 15%

Forecast Sales (GWh) 75,000 76,000 77,000 78,000 79,000 80,000

Required RE Gen (GWh) 7,500 8,360 9,240 10,140 11,060 12,000

CPP Ineligible RE Gen (GWh) 500 500 500 500 500 500

CPP Eligible RE Gen (GWh) 7,000 7,860 8,740 9,640 10,560 11,500

2. RPS with Annual Targets Specified in Absolute Capacity Terms (MW)

RPS policies often include technology “carve-outs” that specify required contributions of 

particular technology types. Even where these carve-outs are not specified, many different 

technologies can contribute to meet an RPS. The formula below illustrates three different 

technologies contributing to an RPS. The distinction between technology types is important in 

calculating RE generation from a capacity-based RPS due to the differences in the underlying 

operating characteristics of technologies (i.e., capacity factors). Each state should include the 

number of technology types that best applies to its own RPS design. In this example, each 
18

technology (1, 2, and 3) is an eligible RE resource per the final emission guidelines; a technology

that is not an eligible RE resource should not be included in the formula.

19

A(t) = [f1(t) x C1(t) + f2(t) x C2(t) + f3(t) x C3(t)] x H

Where: 

A is the total MWh of eligible renewable generation in a future year, 

f1, f2, and f3 are annual effective capacity factors for eligible technologies 1, 2, and 3, 

respectively, and

C1, C2, and C3 are the eligible renewable capacities for technologies 1, 2, and 3, respectively 

(in MW).

H is hours in the year (8760, except leap years)

For example, take a representative state with a target of 10,000MW of wind capacity in 2015, 

and 100MW of solar energy. The state average wind capacity factor is 28.4% and the state 

average solar capacity factor is 18.7%. Wind would be expected to produce 24,878,400 MWh of 

energy (10,000MW x 8760 hours x 28.4%), while solar would produce 163,812 MWh (100MW 

x 8760 hours x 18.7%). In total the state would estimate 25,042,212 MWh of renewable 

generation. Table 6 applies this example to the above formula. States with structures similar to 

this include Texas and Iowa. Some states have overall targets specified as a percentage of sales 

with a specific carve out for some amount (MWh) of wind or solar energy. In order to avoid 

double counting, the amount of the carve-out would not be added to the overall target, as it 

represents a subset of the overall generation (MWh) requirement.

Table 6: Example Qualifying Renewable Energy Calculation (Capacity Target)

2015 2016 2017 2018 2019 2020

Wind Target (MW) 1,000 1,100 1,200 1,300 1,400 1,500

Wind Capacity Factor 

(%) 28.4% 28.4% 28.4% 28.4% 28.4% 28.4%

Wind Energy (GWh) 2,488 2,737 2,985 3,234 3,483 3,732

Solar Target (MW) 150 175 200 225 250 275

Solar Capacity Factor 

(%) 18.2% 18.2% 18.2% 18.2% 18.2% 18.2%

 

19 For more information about what renewable resources are eligible under the emissions guidelines, see 

section VIII.K.3.
19

Solar Energy (GWh) 239 279 319 359 399 438

Total Eligible Gen 

(GWh) 2,727 3,016 3,304 3,593 3,882 4,170

The above equations are sufficient to calculate the expected annual energy output from 

renewable energy associated with an RPS. As previously noted, annual capacity factor 

projections vary by technology and even within a technology category, depending on the location 

of the resource. As a result, if annual energy projections are based on aggregate capacity factors, 

a state should specify the location of all assumed RE generation and the source of capacity factor 

projections.

D. Documentation of Assumptions Related to RE and Demand-Side EE in a 

State Plan CO2 Performance Projection

As explained above, states that plan to use RE and demand-side EE policies and programs 

under a state plan approach that requires a demonstration using projections (as described in 

section VIII.D.2.a.(3)(a) of the preamble) must quantify for each requirement and program the 

expected direct electricity savings and generation impacts on affected EGUs. Further, the state 

plan performance demonstration must document the underlying assumptions regarding the 

renewable electricity generation and electricity savings impacts on affected EGUs. Specific 

considerations and assumptions that should be described in the state plan, when relevant, include 

the following:

• Energy efficiency and/or renewable energy requirement or program description: What is 

the requirement/program? Who will administer it? Does it require new legislation or can 

a state implement it under existing authorities?

• Requirements/program time period: What year does each specific program start and end? 

What are the MWh targets for the interim and final performance periods, including 

interim steps and other applicable time periods? How will the program meet the 

permanent requirements in the CPP?

• Relationship to complementary or existing requirement/program(s): Will this program 

include any federally enforceable limits? Are state measures an expansion or extension of 

existing requirements or programs? If the plan includes an expansion of an existing 
20

program that allows for ineligible resources or unaffected EGUs, how does the 

demonstration address these impacts? 

• Program focus: What sector or consumer type is the focus of the measure? 

• Anticipated compliance or penetration rate: Which affected EGUs will be subject to the 

RE and demand-side EE policy or program? Does the projection reflect characteristics of 

applicable RE technologies and demand-side EE programs and policies?

• Technology performance: What technologies and/or generating capacity will be 

implemented? For how many years will the measure achieve electricity savings (e.g.,

measure life) or generate renewable electricity? How will measure performance degrade 

or decay over time?

• Transmission and distribution (T&D) loss: Is there an expected increase or decrease in 

T&D losses that would require adjustment of the energy savings estimate?

• Resource Costs: What is the cost of saved and/or generated electricity for the RE and 

demand-side EE measures? 

• Program Costs and Funding: What is the cost of the program, including administration 

costs? How it be funded?

• Resource availability: Are the projected electricity savings or renewable electricity 

generation levels realistic compared to the potential available? 
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Summary of Interagency Working Comments on Draft 

Language under EO12866/13563 Interagency Review. 

Subject to Further Policy Review.¶

Technical Support Document (TSD)

Carbon Pollution Emission Guidelines for Existing Stationary Sources: Electricity Utility

Generating Units

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

Incorporating RE and Demand-Side EE Impacts into

State Plan Demonstrations

U.S. Environmental Protection Agency

Office of Air and Radiation

July 31, 2015
2

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I. Introduction

This technical support document details certain demonstration requirements for Clean Power 

Plan (CPP) state plan submittals that must include a projection of carbon dioxide (CO2) emission

performance by affected electric generating units (EGUs), as identified in section VIII.D.2.a(3) 

of the preamble.1 Development of a state’s CO2 emission performance projection begins with an 

electricity demand forecast, which, depending upon the type of analytical method or model used, 

the state may want to reflect the impacts of renewable energy (RE) and demand-side energy 

efficiency (EE) policies and programs. In order to develop this electricity demand forecast, first, 

the state would either select an existing base case electricity demand and supply forecast or 

develop its own. Section II below addresses how to choose or develop a base case demand and 

supply forecast as well as how to document any included RE or demand-side EE measures.

Second, the state may adjust this base case demand forecast to reflect the impacts of RE and 

demand-side EE measures included in the state plan. Section III describes how to quantify the 

impacts of RE and demand-side EE policies and programs and then adjust the base case demand 

forecast to reflect these impacts.

II. Base Case Electricity Demand and Supply Forecasts 

The CO2 emission performance projection of affected EGUs requires information from an 

electricity demand and supply forecast as a basis for predicting generation and emissions during 

the interim and final plan performance periods. This section describes the steps a state should

take to demonstrate that the base case demand forecast transparently represents future demand

and supply:

Step 1: Choose or develop a base case electricity demand and supply forecast. 

Step 2: Document RE and demand-side EE already included in the base case electricity 

demand and supply forecast.

 

1 This includes state measures type plans as well as some emission standards type plans.

Deleted: projections,

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Deleted: projection will include both a

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Deleted: important elements of

Deleted: electricity 

Deleted: .

Deleted: covers proper characterization of renewable 

energy (RE) and demand-side energy efficiency (EE) 

policies and programs in a state plan CO2 emission 

performance projection, including projection approaches

Deleted: documentation requirements

Deleted: electric generating units (

Deleted: )

Deleted: renewable energy

Deleted: energy programs
3

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Step 1: Choose or develop a base case electricity demand and supply forecast.

A state can develop its own base case electricity demand and supply forecast or use a forecast 

from the following information sources: 2

• U.S. Department of Energy, Energy Information Administration, Annual Energy Outlook 

(AEO),

• North American Electric Reliability Corporation (NERC),

• Regional transmission organizations (RTOs)/independent system operators (ISOs) (e.g., 

PJM Interconnection, ISO-New England, NYISO),

• Vertically integrated utilities (e.g., a large power company that operates the electricity 

system for a specific region), in combinations with another publically available source,

• State energy agencies (e.g., State Energy Office or Public Utility Commission (PUC)), 

and

• Regional councils that coordinate energy planning (e.g., Northwest Power and 

Conservation Council)

To develop its own state-specific base case electricity demand and supply forecast, a state would 

apply an annual average electricity demand growth rate derived from one of the above data 

sources to state or regional specific historical electricity sales data. States may also consider 

more comprehensive modeling approaches that calculate expected demand based on assumptions 

including: electricity prices, technology development, population, and economic forecasts. For 

the base case supply forecast, a state should inventory all generation resources available to meet

state demand through the final plan performance periods, including in-state existing and 

anticipated capacity, and any expected imports.

Step 2: Document RE and demand-side EE measures included in the base case electricity 

demand and supply forecast.

Demand forecasts from different information sources reflect on-the-books RE and demandside EE policies to varying degrees in demand and supply forecasts. The state must therefore

research and document how on-the-books RE and demand-side EE programs included in the 

 

2 States can either adopt an existing forecast from one of these sources or use data from them to develop 

their own forecast. States may request to use a different source and EPA would review those requests on 

an individual basis. Any state-specific base case forecasts developed by states must be approved by EPA 

per the final emission guidelines. 

Commented [A1]: Is there any reason why EPA is 

excluding IPM as a choice for a forecast?

Deleted: . 

Deleted: existing 

Deleted: that can be used to serve the state’s forecasted 

base case demand. It is important to understanding which 

resource options are currently

Deleted: the

Deleted: for meeting future 

Deleted: .

Deleted: renewable energy

Deleted: energy efficiency

Deleted: Information

Deleted: , and a

Deleted: each

Deleted: program
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demand or supply forecast used by the state are incorporated into that. This will clarify which

programs are influencing the growth rate assumptions, and the EPA will use this information to 

assess whether the demand and supply forecast is reasonable. This also helps ensure that impacts 

captured in the base case forecast are not double-counted in the base case forecast or duplicated 

in the state plan performance projection. A state should work with the source of the forecast to 

understand whether and how RE and demand-side EE policies and programs, including but not 

limited to the list below, are included in the base case electricity demand and supply forecast:

• EE policies or programs funded by utility ratepayers,

• Existing federal appliance and lighting efficiency standards that are already in effect,

• Forthcoming federal appliance and lighting standards,

• State appliance or lighting efficiency standards (if applicable),

• State building energy codes,

• Renewable portfolio standards, and

• Codified local policies.

There are at least two ways that these programs are captured in an existing forecast: 

1. Programs are explicitly identified, meaning the forecast shows a direct connection 

between the program and its impacts on energy demand or supply (MWhs),

2. Programs are indirectly, and either fully or partially, captured through econometric or 

other assumptions in the relevant economic model (e.g., as captured in National Energy 

Modeling System (NEMS)).

3

 

3 Demand-side EE programs explicitly included in a demand forecast are programs that the forecast’s 

documentation specifically states directly impact future demand levels. Some demand-side EE programs, 

however, are indirectly represented in the assumption and not explicitly identified. For example, the U.S. 

Energy Information Agency’s (EIA) Annual Energy Outlook (AEO) explicitly includes in the reference 

case for electricity demand and supply forecast existing federal appliance and equipment standards for 

residential and commercial sectors as well as state renewable portfolio standards. The AEO indirectly 

captures some impacts of state demand-side EE programs in the forecast and does not explicitly call out 

their impacts. Indirect impacts do not need to be quantified, but on a case-by case basis, a discount factor 

toward any incremental savings in the CPP performance projection may be required to adjust for potential 

double counting. For more information visit: 

http://www.epa.gov/statelocalclimate/state/statepolicies.html. 

Deleted: is

Deleted: forecast

Deleted: the following policies

Deleted: Federal

Deleted: Other applicable policies/programs (e.g., 

codified

Deleted: ).

Deleted: )

Deleted: says that

Deleted: are explicitly included in the reference case for 

electricity demand and supply forecast.

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5

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For all RE and demand-side EE programs included in the base case demand forecast, a state must 

document whether the program is captured explicitly or indirectly. In addition, a state must 

include the following information for on-the-books programs that are reflected in the base case

forecast:

1. Policy or program name,

2. Whether the policy is codified in state or local rule,

3. Year enacted,

4. When the policy requirements sunset.

The above requirements apply regardless of whether an RE or demand-side EE program will 

be used to meet the emission guidelines (e.g., to generate ERCs or as state measures). For 

example, assume a state with an Energy Efficiency Resource Standard (EERS) in state law 

adopts a rate-based emission standards type state plan that requires a projection. The impacts of 

the on-the-books EERS may already be included in the base case demand forecast, and if so, 

should be documented. If the affected EGUs in the state do not need to use the energy savings

(e.g., emission rate credits (ERCs) from demand-side EE) from the state’s EERS to adjust their 

CO2 emission rates, then the state’s plan demonstration would include the four pieces of 

information noted above about its EERS to support the reasonableness of the electricity demand 

forecast.4 If the state expects affected EGUs to use the demand-side EE impacts from the EERS 

to adjust their rates, then the state plan should document the eight pieces of information noted at 

the end of this section. Similarly, under a mass-based state measures approach where the state 

EERS is not included as a state measure, the state plan demonstration would include the four 

pieces of information noted above. If the on-the-books EERS is included as a state measure, then 

the plan should document the eight pieces of information noted below. This information will 

inform the EPA's evaluation of whether the emission standards in the state plan are achievable.

In addition to documenting for on-the-books RE or demand-side EE measures the four pieces 

of information noted above and whether they are directly or indirectly captured in the base case 

demand and supply forecast, the state plan must provide additional information on certain types 

 

4 For example, affected units in the state might be able to achieve the rate-based emission standards with 

other measures or actions outside of the EERS.

Deleted: .

Deleted: requirement sunsets

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Deleted: plan.

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Deleted: But if

Deleted: at the end of this section.

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of on-the-books programs. There are at least two categories of on-the-books policies and 

programs that must be explicitly accounted for in the base case demand and/or supply forecast

and in the following manner: 

• Qualifying RE and demand-side EE programs that are implemented after 2012 and

impact electricity generation in 2022 or later.

5

o Quantify the (annual incremental and cumulative savings or generation (MWhs)) 

x (effective useful life) to estimate the savings that impacts demand or generation

in 2022 or later.

• Qualifying RE and demand-side EE programs that impact electricity generation in 2020 

or 2021 and meet eligibility requirements in the final rule regarding the Clean Energy 

Incentive Program.

6

o Quantify the (annual incremental and cumulative savings or generation (MWhs)) 

x (effective useful life) to estimate the savings that impacts demand or generation

in 2020 and 2021. 

Because these on-the-books RE and demand-side EE measures or programs are explicitly

accounted for in the base case demand forecast, the same impacts must not be represented again

in the state plan performance projection. In other words, such impacts cannot be included in the 

CO2 emission performance projection, because they are already captured in that base case 

forecast. For any RE and demand-side EE programs that are explicitly included in an EGU base 

case forecast and will be used to meet the CPP emission guidelines, the state must document the 

following information:

1. Policy or program name,

2. Whether the program is codified in state or local rule,

3. Year enacted,

4. When the program requirements sunset,

5. Program requirements (e.g., targets in megawatt hours (MWh) or percentage),

 

5 Eligibility requirements related to the timing, geography and type of RE and demand-side EE measures 

that can be used to adjust a CO2 performance rate of an affected EGU under the final rule are detailed in 

section VIII.K.1. 6 For details refer to sections VIII.B.2 and VIII.K.1.a of the preamble.

Deleted: have resulted or will result in eligible measures

Deleted: that

Deleted: have resulted or will result in implementation of 

eligible measures that meet Clean Energy Investment 

Partnership Program requirements that impacts

Deleted: differently

Deleted: “added” to

Deleted: base case forecast when making the state plan

Deleted: .

Deleted: requirement sunsets

Deleted: )

Deleted: Section VIII.K.1.(a) of 

Deleted: preamble provides that eligible

Deleted: actions and RE installations that occur after 2012 

Deleted: applied toward adjusting

Deleted: emission

Deleted: .

Deleted: Section

Deleted: Section 

Deleted: .(2)(a)
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6. Annual energy savings or generation in the base year (MWh),

7. Annual and cumulative energy savings or generation in the future interim and final

periods (MWh), and

8. Estimated useful lives for programs.

III. Proper Characterization of Renewable Energy and Demand-Side

Energy Efficiency in a State Plan Performance Projection

Section VIII.D.2.a.(3)(a) of the preamble explains which types of state plans require CO2

emission performance projections for affected EGUs in order to show that the state plan will lead 

to achievement of the CO2 emission performance rates, state goal, or other emission guideline 

requirements. State plans that require such a projection must include a base case electricity 

demand and supply forecast as well as supporting documentation, as explained in section II 

above. In addition, such plans must quantify the combined future impact of all the emission 

standards and state measures included in the state plan. This section explains the proper 

characterization of expected RE and demand-side EE impacts in a CO2 emission performance 

projection.

States that plan to use RE and demand-side EE to meet the emission guidelines (e.g., to 

generate ERCs or as state measures) under applicable state plan types that require a performance 

projection will need to project the expected incremental direct generation impacts and electricity 

savings of RE and demand-side EE.

7 While RE and demand-side EE measures, programs and 

policies may impact the generation, construction, retirement and CO2 emissions of both affected 

and non-affected EGUs, a projection must demonstrate how RE and demand-side EE will enable 

affected EGUs to meet the emission guidelines. There are different approaches to projecting 

electricity savings and renewable generation, depending upon the design of an RE and demandside EE program. Regardless of the approach chosen, a state plan that includes RE and demand-

 

7 Incremental direct effects refers to RE and demand-side EE beyond any impacts that are in the base 

case. If a new program is more stringent than an existing program already in the base case, it may not be 

appropriate to use the full magnitude of the new program. 

Deleted: )

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Deleted: requirement is designed
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side EE must document specific assumptions in their performance projections, as described 

below.

A. Approaches to Estimating Future RE Generation and EE Savings

Projections of expected annual electricity savings and/or renewable energy generation are 

necessary inputs when projecting EGU CO2 emission performance. This is because increased RE 

generation will impact the generation of affected EGUs and resulting CO2 emissions. Electricity 

savings estimates included in EE projections will lower electricity demand forecasts in the CO2

emission performance projections. The EE projection can be used as an input, or modifier, to 

various models or other tools in order to demonstrate that the state plan will achieve emission 

guideline requirements.

A CO2 emission performance projection must include the potential impacts of RE and 

demand-side EE, and the state must document how those RE and demand-side EE impacts are 

reflected in the projection. The state can incorporate RE and demand-side EE impacts at the

individual project or program level, or it can aggregate RE and demand-side EE impacts across a 

portfolio of programs.8 The EPA historically has accepted the estimation of RE and demand-side 

EE at an aggregated level as indicated in EPA’s Bundled Measures Guidance.9 The state must 

also verify that the assumptions about RE and demand-side EE availability are reasonable, such 

as based on an assessment of RE and demand-side EE potential.

As discussed above, a state plan CO2 emission performance projection must not include RE 

and demand-side EE impacts captured in the base case electricity demand forecast. 

Consequently, RE and demand-side EE impacts included in the CO2 emission performance 

projection must be incremental to and non-duplicative of impacts included in the base case

 

8 This can include state and local sponsored programs, and RE and demand-side EE projects, such as ones 

done under performance contracting, provided they meet the eligibility requirements specified in section 

VIII.K.1 of the preamble. Other types of programs and projects that may be eligible for inclusion are 

described in section VIII.K.1.a. 9 Guidance on Incorporating Bundled Measures in a State Implementation Plan,

www.epa.gov/ttn/oarpg/t1/memoranda/10885guideibminsip.pdf.

Deleted: estimating future energy efficiency savings 

and renewable energy generation

Deleted: energy efficiency

Deleted: state plan

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demand forecast. The performance projections, for example, could include impacts from RE and 

demand-side EE programs not reflected in the base case forecast or from the expansion of 

existing programs beyond levels reflected in the base case forecast. A state must use the 

following general equations to quantify the expected incremental impacts of RE and demandside EE during the future interim and final performance periods.

10

Energy Efficiency:

• (Incremental first-year annual plus cumulative savings of EE program11) x (effective 

useful life) for each interim period and final period. Determine persistent level of savings 

for final period and beyond.

Renewable Energy: 

• (Incremental MW installed capacity) x (location-12 and technology-specific capacity 

factors) x (8760 hours) for each interim period and final period. Determine persistent 

level of renewable energy generation for final period and beyond.

Several tools and methods are available to help states estimate the potential direct energy 

impacts of RE and demand-side EE that will be used to adjust a state’s electricity demand and 

supply forecast. States can base their electricity savings projections on past evaluation, 

measurement and verification (EM&V) reports that document impacts of similar projects or 

programs and that have been submitted to public service commissions or evaluated by third 

parties. States also can conduct their own surveys or studies to estimate the direct energy impacts 

 

10 The EPA recognizes that for unique situations, states may not be able to use these exact equations. In 

those unique circumstances, states can propose an alternative equation to EPA for approval on a case-bycase basis. 

11 Projections of demand-side EE impacts must reflect the annual impacts that occur due to new EE 

impacts in a given year plus the impacts of EE investments made in previous years that are still generating 

savings (i.e., have not exceed their measure life or otherwise ended). 12 States can use location-specific capacity factors informed by historical data or weather-prediction 

models, such as the kind of data included in the National Renewable Energy Laboratory (NREL) Eastern 

Wind Integration and Transmission Study (EWITS) or in publicly available datasets from EIA and 

ISO/RTOs.

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of EE policies and/or use sophisticated methods, such as building simulation tools, vintaging 

models, production costing, and cost-of-energy analysis models.13 Any methodology used must 

be EPA-approved, and each state is encouraged to consult with the EPA early during the plan 

development process about the tools and methods it intends to employ.

Assessing the potential RE and demand-side EE impacts of measures, policies or programs 

can involve bottom-up economic and/or engineering-based estimation techniques that are based 

upon a representation of the fundamentals of the technology and economic behavior. These 

bottom-up approaches estimate potential energy savings at a very detailed level and roll these 

estimates up to the statewide level. Alternatively, the potential impacts of RE and demand-side 

EE can be quantified based upon the design and requirements of state-level policies and 

regulations specified over a future time frame. The next two sections describe how a state plan 

CO2 performance projection would calculate the generation impacts of two common state 

policies: energy efficiency resource standards and renewable portfolio standards.

B. Projecting Energy Savings from Energy Efficiency Resource Standards

Many states have adopted an EERS, which is a policy that sets targets for energy savings 

over a specified time frame from demand-side EE programs operated by utilities or other 

program administrators. States typically specify annual first-year or cumulative targets as 

percentages of electricity sales or as absolute energy savings. States use different bases for 

specifying EERS goals. Some specify goals based on electricity sales (in MWhs) from investorowned utilities, while others have mandated energy savings targets based on total MWh sales or 

a subset of total MWh sales.

A state can quantify energy savings for use in its CO2 emission performance projection using 

formulas specific to the state’s EERS, as described below.

14 For this approach a state would 

 

13 For more information about available tools for estimating direct energy impacts, see Assessing the 

Multiple Benefits Guide: A Resource for States, Chapter 2. 

http://www.epa.gov/statelocalclimate/documents/pdf/epa_assessing_benefits_ch2.pdf#page=4. 14 Savings from purely voluntary demand-side EE goals are not state enforceable measures and are not 

eligible for use in a CO2 emission performance projection for a state measures type plan. Quantification 

of eligible demand-side EE savings must be done in accordance with the requirements specified in section 

VIII.K.3 of the preamble.

Deleted: timeframe

Commented [A2]: This discussion of computing savings 

from EERS should discuss how to account for the difference 

between net and gross savings where both are reported and 

where only one is

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select the appropriate sales basis, and if the basis is not total sales, a state could use recent year 

utility-level sales data from EIA and growth rates from EIA, an RTO/ISO, NERC or other 

publicly available sources to develop base case forecasts of sales of the utilities required to 

comply with the EERS. The design of the EERS will affect whether a state, for purposes of its 

CO2 emission performance projection, should assume energy savings at the EERS target level.

For example, it may not be appropriate to assume full achievement of energy savings goals in an 

EERS that includes cost/rate caps or other design features that may not lead to incremental 

energy savings relative to the base case demand forecast (e.g., counting savings from building 

energy codes or historical EE programs). 

The general formulas a state must use to quantify first-year and cumulative energy savings 

from an EERS policy for each year (t) are shown below, though a state may propose a different 

methodology if it better represents the state’s EERS. Once these first-year and cumulative energy 

savings are quantified, the state can incorporate them into the demand forecast of its CO2

emission performance projection.

15

1. EERS with Annual First-Year EE Savings Targets Specified in Percent Terms

A(t) = r(t) Z(t-1)

C(t) = A(t) + A(t-1) + ... + A(t-L+1)

I(t) = C(t) - E(t)

Z(t) = B(t) - I(t) 

Where:

r is the annual first-year percent savings target, 

A is the annual first-year energy savings, 

L is the measure lifetime, 

B is the base case sales of utilities affected by these specific policies, 

C is the cumulative energy savings, 

E is the cumulative savings embedded in the base case demand forecast,16

I is the cumulative savings incremental to the base case demand forecast, and 

Z is the adjusted sales after application of cumulative incremental savings.

 

15 These equations are the recommended calculation methods for inclusion in state plans. 16 States using the AEO 2013 forecast should take note that it does not include state-level EERS policies 

but does embed EE savings of policies. These EE savings are not reported out by the AEO and need to be 

determined independently. 

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For example, a representative state has an EERS first-year target of 2% for each year 2016-

2018. Forecasted baseline sales of utilities in 2015 are 50,000 GWh, growing by 1% each year of 

the forecast period. Embedded savings are 50 GWh per year, applied to years in which first-year 

energy savings are realized. The measure lifetime assumed for both first-year energy savings and 

embedded savings is four years. Table 1 applies this example to the above formula. This is the 

most common type of EERS structure, and states having adopted some version of it include 

Arizona, Illinois, Indiana, and Ohio. 

Table 1: Example EERS with Annual First-Year EE Savings Targets Specified in Percent Terms

2015 2016 2017 2018 2019 2020 2021 2022

Baseline sales of affected 

utilities (GWh) (B)

50,000.0 50,500.0 51,005.0 51,515.1 52,030.2 52,550.5 53,076.0 53,606.8

First-year percent savings 

target (%) (r) 

2% 2% 2%

First-year energy savings 

(GWh) (A)

1,000.0 991.0 982.3

Cumulative energy savings 

(GWh) (C) 

1,000.0 1,991.0 2,973.3 2,973.3 1,973.3 982.3 0.0

Cumulative savings 

embedded (GWh) (E) 

50.0 100.0 150.0 150.0 100.0 50.0 0.0

Cumulative savings 

incremental (GWh) (I) 

950.0 1,891.0 2,823.3 2,823.3 1,873.3 932.3 0.0

Adjusted sales after 

incremental savings (GWh) (Z) 

50,000.0 49,550.0 49,114.0 48,691.8 49,206.9 50,677.2 52,143.7 53,606.8

2. EERS with Annual First-Year EE Savings Targets Specified in Absolute Terms

C(t) = A(t) + A(t-1) + ... + A(t-L+1)

I(t) = C(t) - E(t)

Z(t) = B(t) - I(t) 

Where: 

A is the annual first-year energy savings target,

L is the measure lifetime, 

B is the base case sales of utilities affected by these specific policies, 

C is the cumulative energy savings, 

E is the cumulative savings embedded in the base case demand forecast, 

I is the cumulative savings incremental to the base case demand forecast, and 

Z is the adjusted sales after application of cumulative incremental savings.

For example, a representative state has an EERS first-year target of 1,000 GWh in 2016, 

increasing by about 2% per year for 2017-2018 to the absolute targets shown in the table below.

Forecasted baseline sales of utilities in 2015 are 50,000 GWh, growing by 1% each year of the 

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forecast period. Embedded savings are 50 GWh per year, applied to years in which first-year 

energy savings are realized. The measure lifetime assumed for both first-year energy savings and 

embedded savings is four years. Table 2 applies this example to the above formula. States that 

applied this structure during their EERS implementation include Florida, Iowa, and Oregon. 

Table 2: Example EERS with Annual First-Year EE Savings Targets Specified in Absolute Terms

2015 2016 2017 2018 2019 2020 2021 2022

Baseline sales of utilities 

(GWh) (B)

50,000.0 50,500.0 51,005.0 51,515.1 52,030.2 52,550.5 53,076.0 53,606.8

First-year energy savings 

(GWh) (A)

1,000.0 1,020.0 1,040.4

Cumulative energy savings 

(GWh) (C) 

1,000.0 2,020.0 3,060.4 3,060.4 2,060.4 1,040.4 0.0

Cumulative savings 

embedded (GWh) (E) 

50.0 100.0 150.0 150.0 100.0 50.0 0.0

Cumulative savings 

incremental (GWh) (I) 

950.0 1,920.0 2,910.4 2,910.4 1,960.4 990.4 0.0

Adjusted sales after 

incremental savings (GWh) (Z) 

50,000.0 49,550.0 49,085.0 48,604.7 49,119.8 50,590.1 52,085.6 53,606.8

3. EERS with Cumulative EE Savings Targets Specified in Percent Terms

A(t) = C(t) – C(t-1) + A(t-L)

If r(t) available,

C(t) = r(t) x B(t)

I(t) = C(t) - E(t)

Z(t) = B(t) - I(t)

If r(t) not available,

Z(t) calculated by interpolation

I(t) = B(t) - Z(t)

C(t) = I(t) + E(t)

Where: 

r is the cumulative percent savings target, 

A is the annual first-year energy savings, 

L is the measure lifetime, 

B is the base case sales of utilities affected by these specific policies, 

C is the cumulative energy savings, 

E is the cumulative savings embedded in the base case demand forecast, 

I is the cumulative savings incremental to the base case demand forecast, and 

Z is the adjusted sales after application of cumulative incremental savings.

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Deleted: AEO2013

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For example, a representative state has an EERS cumulative target of 5% by 2018. 

Forecasted baseline sales of utilities in 2015 are 50,000 GWh, growing by 1% each year of the 

forecast period. Embedded savings are 50 GWh per year, applied to years in which first-year 

energy savings are realized. The measure lifetime assumed for both first-year energy savings and 

embedded savings is four years. Distribution of the cumulative energy savings in 2018 to the 

first-year savings for 2016-2018 applies the simple assumption of an equal share of savings 

being implemented in each year. Table 3 applies this example to the above formula. This 

approach is uncommon, and states that applied this structure in earlier years of their EERS 

policies include New York and Pennsylvania. 

Table 3: Example EERS with Cumulative EE Savings Targets Specified in Percent Terms

2015 2016 2017 2018 2019 2020 2021 2022

Baseline sales of utilities 

(GWh) (B)

50,000.0 50,500.0 51,005.0 51,515.1 52,030.2 52,550.5 53,076.0 53,606.8

Cumulative percent savings 

target (%) (r) 

5%

First-year energy savings 

(GWh) (A)

858.6 858.6 858.6

Cumulative energy savings 

(GWh) (C) 

858.6 1,717.2 2,575.8 2,575.8 1,717.2 858.6 0.0

Cumulative savings 

embedded (GWh) (E) 

50.0 100.0 150.0 150.0 100.0 50.0 0.0

Cumulative savings 

incremental (GWh) (I) 

808.6 1,617.2 2,425.8 2,425.8 1,617.2 808.6 0.0

Adjusted sales after 

incremental savings (GWh) (Z) 

50,000.0 49,691.4 49,387.8 49,089.3 49,604.4 50,933.3 52,267.4 53,606.8

4. EERS with Cumulative EE Savings Targets Specified in Absolute Terms

A(t) = C(t) – C(t-1) + A(t-L)

If C(t) available,

I(t) = C(t) - E(t)

Z(t) = B(t) - I(t)

If C(t) not available,

Z(t) calculated by interpolation

I(t) = B(t) - Z(t)

C(t) = I(t) + E(t)

Where:

C is the cumulative energy savings target, 

A is the annual first-year energy savings, 
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L is the measure lifetime, 

B is the base case sales of utilities affected by these specific policies, 

E is the cumulative savings embedded in the base case demand forecast, 

I is the cumulative savings incremental to the base case demand forecast, and 

Z is the adjusted sales after application of cumulative incremental savings.

For example, a representative state has an EERS cumulative target of 3,000 GWh by 2018. 

Forecasted baseline sales of utilities in 2015 are 50,000 GWh, growing by 1% each year of the 

forecast period. Embedded savings are 50 GWh per year, applied to years in which first-year 

energy savings are realized. The measure lifetime assumed for both first-year energy savings and 

embedded savings is four years. Distribution of the cumulative energy savings in 2018 to the 

first-year savings for 2016-2018 applies the simple assumption of an equal share of savings 

being implemented in each year. Table 4 applies this example to the above formula. States that 

utilized this structure during EERS implementation include California and Hawaii. 

Table 4: Example EERS with Cumulative EE Savings Targets Specified in Absolute Terms

2015 2016 2017 2018 2019 2020 2021 2022

Baseline sales of utilities 

(GWh) (B)

50,000.0 50,500.0 51,005.0 51,515.1 52,030.2 52,550.5 53,076.0 53,606.8

First-year energy savings 

(GWh) (A)

1,000.0 1,000.0 1,000.0

Cumulative energy savings 

(GWh) (C) 

1,000.0 2,000.0 3,000.0 3,000.0 2,000.0 1,000.0 0.0

Cumulative savings 

embedded (GWh) (E) 

50.0 100.0 150.0 150.0 100.0 50.0 0.0

Cumulative savings 

incremental (GWh) (I) 

950.0 1,900.0 2,850.0 2,850.0 1,900.0 950.0 0.0

Adjusted sales after 

incremental savings (GWh) (Z) 

50,000.0 49,550.0 49,105.0 48,665.1 49,180.2 50,650.5 52,126.0 53,606.8

C. Projecting Generation Impacts from Renewable Portfolio Standards

Renewable portfolio standards (RPS) set RE targets across a specified period of time. Most 

often these state policies require that a specified percentage of the electricity sold by a utility 

comes from eligible renewable technologies (e.g., wind, solar, biomass).

A state must project annual RE generation using formulas specific to the state’s RPS policy, 

as shown below, or an EPA-approved alternative method. Similar to the EERS approach 

described above, a state would select the appropriate sales basis, and if the basis is not total sales, 

a state could use a recent year of utility-level sales data from EIA and growth rates from EIA, an 

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RTO/ISO, NERC or other publicly available sources to develop base case forecasts of sales for 

the utilities required to comply with the RPS. 

The design of the RPS will affect whether a state can assume full achievement of the RPS 

targets. Many RPSs include provisions for alternative compliance payments, which allow an 

entity to pay a fee in lieu of achieving the RPS. Additionally, RPS policies may include sources

that are not eligible for CPP compliance purposes. In such cases, only generation impacts from 

eligible RE sources should be included in a state’s CO2 emission performance projection.

17

The general formulas a state must use to quantify annual generation impacts of an RPS 

policy for each year (t) are shown below, though a state may propose a different methodology if 

it better represents the state’s RPS.18

1. RPS with Annual Targets Specified in Percent of Retail Sales Terms

A(t) = r(t) x Z(t) – MWhineligible(t)

Where:

A is the total MWh of CPP-qualifying renewable generation in a future year,

r is the annual RPS percent RE target,

Z is the forecasted electricity sales that fall under the RPS policy, and

MWhineligible is the MWh of generation from technologies ineligible under CPP

(t) is the year 

Note that each state should apply this general formula to its specific RPS design. For example, if 

a specified percentage of RE is required to be met by sales from investor-owned utilities and 

separate percentage from rural cooperatives, then the state should apply the formula individually 

 

17 States must represent measures in their projection in accordance with the accounting and eligibility 

requirements specified in the guidelines, irrespective of the ways that RE is counted under a state 

requirement, such as an RPS, or for the purposes of renewable energy certificates. For example, some 

RPS apply an adjustment factor or allow credit different from the accounting method included in the final 

rule. RE generation from purely voluntary RE goals are not state enforceable measures and are not 

eligible for use in a performance projection for a state measures plan type. Similarly, alternate compliance 

payments, state-level bonuses for RE and RE resources permitted under an RPS that are not permitted 

under the final guidelines are not eligible to demonstrate performance in a projection. For more 

information about acceptable accounting methods for RE, see sections VIII.K.1 and VIII.K.2 of the 

preamble. For information about addressing interactions between renewable energy credits (RECs) and 

emission rate credits, see section VIII.K.2. 18 The equations in this section are the recommended calculation methods for inclusion in state plans.

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for each class and sum the MWh for each to calculate A(t). Additionally, each state plan should 

estimate the MWh of generation from any technologies that fall within the scope of its RPS but 

outside CPP. This estimate (MWhineligible) can be based on planned and/or expected new 

capacities for these technologies and best-available historical capacity factors.

For example, take a representative state with an RPS target of 10% in 2015, rising to 15% 

by 2020. Forecasted sales in 2015 are 75,000 gigawatthours (GWh), growing in subsequent 

years. In 2015, the renewable requirement is 7,500 GWh, but 500 GWh of the RPS is met by 

technologies ineligible under the final CPP. As a result, eligible renewable generation is 7,000 

GWh in 2015. Assuming the same MWhineligible in future years, the state would predict 11,500 

GWh of CPP eligible renewables in 2020. The table below applies this example to the above 

formula. This is a common type of RPS policy. States with structures similar to this include 

Massachusetts, North Carolina, and Illinois.

Table 5: Example Qualifying Renewable Energy Calculation

2015 2016 2017 2018 2019 2020

RPS Target (%) 10% 11% 12% 13% 14% 15%

Forecast Sales (GWh) 75,000 76,000 77,000 78,000 79,000 80,000

Required RE Gen (GWh) 7,500 8,360 9,240 10,140 11,060 12,000

CPP Ineligible RE Gen (GWh) 500 500 500 500 500 500

CPP Eligible RE Gen (GWh) 7,000 7,860 8,740 9,640 10,560 11,500

2. RPS with Annual Targets Specified in Absolute Capacity Terms (MW)

RPS policies often include technology “carve-outs” that specify required contributions of 

particular technology types. Even where these carve-outs are not specified, many different 

technologies can contribute to meet an RPS. The formula below illustrates three different 

technologies contributing to an RPS. The distinction between technology types is important in 

calculating RE generation from a capacity-based RPS due to the differences in the underlying 

operating characteristics of technologies (i.e., capacity factors). Each state should include the 

number of technology types that best applies to its own RPS design. In this example, each 
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technology (1, 2, and 3) is an eligible RE resource per the final emission guidelines; a technology

that is not an eligible RE resource should not be included in the formula.

19

A(t) = [f1(t) x C1(t) + f2(t) x C2(t) + f3(t) x C3(t)] x H

Where: 

A is the total MWh of eligible renewable generation in a future year, 

f1, f2, and f3 are annual effective capacity factors for eligible technologies 1, 2, and 3, 

respectively, and

C1, C2, and C3 are the eligible renewable capacities for technologies 1, 2, and 3, respectively 

(in MW).

H is hours in the year (8760, except leap years)

For example, take a representative state with a target of 10,000MW of wind capacity in 2015, 

and 100MW of solar energy. The state average wind capacity factor is 28.4% and the state 

average solar capacity factor is 18.7%. Wind would be expected to produce 24,878,400 MWh of 

energy (10,000MW x 8760 hours x 28.4%), while solar would produce 163,812 MWh (100MW 

x 8760 hours x 18.7%). In total the state would estimate 25,042,212 MWh of renewable 

generation. Table 6 applies this example to the above formula. States with structures similar to 

this include Texas and Iowa. Some states have overall targets specified as a percentage of sales 

with a specific carve out for some amount (MWh) of wind or solar energy. In order to avoid 

double counting, the amount of the carve-out would not be added to the overall target, as it 

represents a subset of the overall generation (MWh) requirement.

Table 6: Example Qualifying Renewable Energy Calculation (Capacity Target)

2015 2016 2017 2018 2019 2020

Wind Target (MW) 1,000 1,100 1,200 1,300 1,400 1,500

Wind Capacity Factor 

(%) 28.4% 28.4% 28.4% 28.4% 28.4% 28.4%

Wind Energy (GWh) 2,488 2,737 2,985 3,234 3,483 3,732

Solar Target (MW) 150 175 200 225 250 275

Solar Capacity Factor 

(%) 18.2% 18.2% 18.2% 18.2% 18.2% 18.2%

 

19 For more information about what renewable resources are eligible under the emissions guidelines, see 

section VIII.K.3.

Deleted: *

Deleted: *

Deleted: *

Deleted: )

Commented [A3]: Should this formula not include the 

hours of generation (i.e. multiply by 8760 hrs)?

Deleted: Section
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Solar Energy (GWh) 239 279 319 359 399 438

Total Eligible Gen 

(GWh) 2,727 3,016 3,304 3,593 3,882 4,170

The above equations are sufficient to calculate the expected annual energy output from 

renewable energy associated with an RPS. As previously noted, annual capacity factor 

projections vary by technology and even within a technology category, depending on the location 

of the resource. As a result, if annual energy projections are based on aggregate capacity factors, 

a state should specify the location of all assumed RE generation and the source of capacity factor 

projections.

D. Documentation of Assumptions Related to RE and Demand-Side EE in a 

State Plan CO2 Performance Projection

As explained above, states that plan to use RE and demand-side EE policies and programs 

under a state plan approach that requires a demonstration using projections (as described in 

section VIII.D.2.a.(3)(a) of the preamble) must quantify for each requirement and program the 

expected direct electricity savings and generation impacts on affected EGUs. Further, the state 

plan performance demonstration must document the underlying assumptions regarding the 

renewable electricity generation and electricity savings impacts on affected EGUs. Specific 

considerations and assumptions that should be described in the state plan, when relevant, include 

the following:

• Energy efficiency and/or renewable energy requirement or program description: What is 

the requirement/program? Who will administer it? Does it require new legislation or can 

a state implement it under existing authorities?

• Requirements/program time period: What year does each specific program start and end? 

What are the MWh targets for the interim and final performance periods, including 

interim steps and other applicable time periods? How will the program meet the 

permanent requirements in the CPP?

• Relationship to complementary or existing requirement/program(s): Will this program 

include any federally enforceable limits? Are state measures an expansion or extension of 

existing requirements or programs? If the plan includes an expansion of an existing 

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Deleted: impacts 
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program that allows for ineligible resources or unaffected EGUs, how does the 

demonstration address these impacts? 

• Program focus: What sector or consumer type is the focus of the measure? 

• Anticipated compliance or penetration rate: Which affected EGUs will be subject to the 

RE and demand-side EE policy or program? Does the projection reflect characteristics of 

applicable RE technologies and demand-side EE programs and policies?

• Technology performance: What technologies and/or generating capacity will be 

implemented? For how many years will the measure achieve electricity savings (e.g.,

measure life) or generate renewable electricity? How will measure performance degrade 

or decay over time?

• Transmission and distribution (T&D) loss: Is there an expected increase or decrease in 

T&D losses that would require adjustment of the energy savings estimate?

• Resource Costs: What is the cost of saved and/or generated electricity for the RE and

demand-side EE measures? 

• Program Costs and Funding: What is the cost of the program, including administration 

costs? How it be funded?

• Resource availability: Are the projected electricity savings or renewable electricity 

generation levels realistic compared to the potential available? 

Deleted: required by the state measure?

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1

Incorporating RE and Demand-side EE Impacts into State Plan Demonstrations 

Technical Support Document for the Clean Power Plan

U.S. EPA response to OMB Comments from 7/28/2015

July 31, 2015

General Comments

1. Page 2 & throughout text: Reviewer recommends clarifying the text to indicate that any state 

choosing a state-measures approach must submit a CO2 emission performance projection. 

Recommended text: 

“This technical support document details demonstration requirements for Clean Power Plan 

(CPP) state plan submittals that must include carbon dioxide (CO2) emission projections, 

primarily states adopting a state measures plan or, as identified in section VIII.D.2.a.(3) of the 

preamble.” 

EPA Response: The EPA added the text requested in a footnote.

2. Pages 2-3: Reviewer recommends moving the references to NERC to after the discussion of a 

state using a growth rate from an organization to develop their own base case, since we do 

not believe that NERC has state-level demand projections so the only way to use this source 

is applying the demand growth rate. Additionally, reviewer is concerned with the use of a 

vertically integrated utility, which is likely to be a compliance entity as an owner of affected 

EGUs, to also be the source of a baseline used for the demonstration of a state plan. See 

below for suggested line edits.

“A state can develop its own base case electricity demand and supply forecast or use a 

forecast from the following information sources. 

• U.S. Department of Energy, Energy Information Administration, Annual Energy Outlook (AEO),

• North American Electric Reliability Corporation (NERC),

• Regional transmission organizations (RTOs)/independent system operators (ISOs) (e.g., PJM 

Interconnection, ISO-New England, NYISO),

• Vertically integrated utilities (e.g., a large power company that operates the electricity system for 

a specific region), in combination with another source

• State energy agencies (e.g., State Energy Office or Public Utility Commission (PUC)), and

• Regional councils that coordinate energy planning (e.g., Northwest Power and Conservation 

Council)

EPA Response: The EPA disagrees with the suggestion to remove NERC from the list of 

sources based on the fact that NERC does not have state level demand forecast information. 

AEO also does not have state level forecasts but states can use either AEO or NERC growth 

rates to inform state level projections. The TSD clearly states that forecasts from this list can 
2

be used to generate state-derived growth rates, based off of regional information from the 

sources above. 

3. Page 3: Reviewer recommends clarifying if electricity imports from other states and/or 

regions should be included in the inventory of “existing generation that can be used to serve 

the state’s forecasted base case demand.”

EPA response: The EPA made an edit to reflect this change.

4. Page 3: Reviewer recommends the following addition to ensure that states do not artificially 

inflate projected electricity demand in the base case (and thus GHG emissions savings in the 

state plan case). 

“To develop its own state-specific base case electricity demand and supply forecast, a state 

would apply an annual average electricity demand growth rate derived from one of the 

above data sources to state or regional specific historical electricity sales data. EPA must 

approve any state-created state-specific base case forecast.”

EPA response: The EPA agrees with this comment and added a footnote. However the TSD

already addresses the EPA-approvability concern in the preamble. In the preamble the 

demand forecast is a required key assumption that will be approved by EPA. 

5. Page 3: Reviewer recommends indicating that states may have to derive a forecast from 

these sources, as many of these sources do not provide state-specific forecasts (i.e. AEO only 

provides forecasts by NERC subregions)

EPA Response: The EPA addressed this in footnote 2.

6. Page 3 (third bullet at bottom of page): Reviewer suggests the following edit for clarification. 

“Forthcoming federal appliance and lighting standards,”

EPA Response: The EPA made this change.

7. Page 4: Reviewer recommends clarifying what it means that EGUs in the state “do not need 

to use” energy savings from the state’s EERS. Reviewer recommends clarifying if that means 

that the state has chosen a mass emission standard or a rate emission standard that does not 

credit EE or if a different scenario(s) was in mind.

EPA Response: The EPA addressed this comment with added text.

8. Page 4 (footnote 1): Reviewer suggests the following edit for clarification. 

“For example, the U.S. Energy Information Agency’s (EIA) Annual Energy Outlook (AEO) says 
3

that existing federal appliance and equipment standards for residential and commercial 

sectors...”

EPA Response: The EPA made this change.

9. Page 4: Reviewer notes that AEO2013 (and all AEO projections) include embedded decreased 

demand due to distributed photovoltaic generation in the demand forecast. Recommend 

indicating in a footnote that if AEO demand projections are used for a base case, the amount 

of distributed photovoltaics should be accounted for to avoid double-counting of these 

eligible resources in state projections. Suggested text: 

“Note that all AEO demand projections include embedded reduced demand due to projected 

deployment of distributed photovoltaic generation. States should account for this in their 

state plan performance projection if AEO demand projections are used for the base case 

forecast to prevent double-counting of these eligible resources.”

The EPA response: Edited text in Step 2 of TSD section II.

10. Page 4: Reviewer recommends that an additional example of a mass based plan be included 

on page 4 in the example of programs needing a projection, showing that the forecast is 

made for both a mass and rate-based plan, though actual EM&V and measurement of the 

savings would not be needed for compliance.

EPA Response: The EPA addressed this comment with an added example.

11. Page 5: Reviewer requests clarification as to whether projections for the on-the books 

policies and programs are required for mass-based program. For example, if a state elects to 

use a mass-based program and does not have an explicit EERS, do they need to quantify 

where the emissions reductions will take place beyond the allowance system?

EPA Response: This document is intended to only address the MWh impacts of EE/RE. The 

preamble describes which mass based plans need a projection, and therefore the EPA does

not repeat this information in this TSD. Mass based emission standard plans that adopt the 

CO2 goal that is in EPA emission guidelines do not need a projection. 

12. Page 5: Reviewer request clarification if the “eligible measures” referred to in the following 

sentence refers to measures eligible according to EPA or according to the submitted state 

plan, which may be a subset of those eligible according to EPA. The reviewer believes the 

intent is to refer to state eligible measures otherwise the EERS example that was mentioned 

on page 4 would also need this more extensive reporting.
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“RE and demand-side EE programs that have resulted or will result in state plan eligible 

measures implemented after 2012 that impact electricity in 2022 or later.”

EPA Response: Eligible measures can be projects, programs or policies. The EPA clarified this. 

13. Page 5-6: Reviewer requests clarification as to what it means for RE and EE to be represented 

“differently” in the state plan performance projection. It seems to the reviewer that if RE and 

EE measures are represented in the base case they should not be counted again in the state 

plan performance projection. Therefore, the reviewer recommends the following edits. 

“Because these one-the-books RE...the same impacts must not be represented differently

again in the state plan performance projection. In other words, such impacts cannot be 

“added” to the base case forecast when making the state plan performance projection, 

because they are already captured in that base case forecast.”

EPA Response: The EPA made this change. 

14. Page 8: Reviewer recommends clarifying the first term of this equation, perhaps by changing 

“and” to “plus”: “(Incremental first-year annual and cumulative savings of EE program) x 

(effective useful life) for each interim period and final period. Determine persistent level of 

savings for final period and beyond.”

EPA Response: The EPA edited text and added a footnote clarifying cumulative savings 

estimates in this equation. 

15. Page 9: Reviewer requests clarification on the use of “sales” on page 9 in “Some specify goals 

based on sales from investor-owned utilities, while others have mandated energy savings 

targets based on total sales or a subset of total sales” and throughout. Does this mean sales 

or MWh? Reviewer suggests substituting “MWh sold”

EPA Response: The EPA edited text to show MWhs.

16. Page 10: Reviewer recommends inserting language to indicate that the AEO2013 forecast 

does not include state level EERS policies. Reviewer also recommends indicating how states 

should derive the embedded AEO2013 EE savings as EE savings are not reported out in a 

simple table by the AEO and are also not reported out by state but by NERC subregion. 

Reviewer also recommends noting in a footnote why AEO2013 forecasts must be used for 

these equations. 

EPA Response: EPA has added tables that demonstrate the equations for each EERS formula. 

EPA explains in the text earlier that states must understand what is embedded in the forecast 

they plan to use to avoid double-counting of impacts. EPA does not require states to use a 

particular forecast but flags in the text here the notes on AEO2013, EERS and EE savings. 
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17. Pages 12-13: reviewer recommends also pointing out the fact that some state RPS rules 

about allowing RECs from other states may not be consistent with rules about affected EGUs 

claiming credit for RE generated in another state, for example, in a mass state with no 

demonstration that load was served in a rate state. Suggested text: “Further, some state RPSs 

allow for out-of-state renewable generation to be claimed for the state’s RPS. The state must 

demonstrate that provisions in the state policy allowing out-of-state procurement are 

consistent with the provisions allowing this type of procurement, as well as the restrictions 

on trading of ERCs based on state plan type, as described in the Preamble.” 

EPA Response: Edited text to reflect need to maintain consistency with accounting methods 

in the emission guidelines irrespective of RPS and REC rules. 

18. Page 13: Reviewer recommends indicating that state level bonuses applied to crediting RE 

generation (for example, bonuses applied to in-state generation) to RPS compliance, would 

not be included in the calculations in Section C(2).

EPA Response: The EPA added a footnote that addresses this recommendation.

19. Reviewer recommends clarification on what happens to state RPSs that include alternative 

compliance payments (ACPs)? If ERCs are purchased with ACP funds, can that be approvable?

EPA Response: Edited footnote to flag that ACPs are not acceptable.

20. Reviewer suggests EPA publish a list (and note here in text its intent to do so) of methods as 

they are approved to provide greater transparency and increase confidence in likelihood of 

approval for states still in the submittal process.

EPA Response: The equations in this TSD are approvable methods for inclusion in a state 

plan CO2 performance projection. The EPA has stated this more clearly in the document.

21. Page 28: "In 2014, an LBNL analyzed the program cost of saved energy based on data from 

their DSM Program Impacts Database." Reviewer recommends clarifying that the referenced 

LBNL work analyzed the "program administrator" cost of saved energy.

EPA Response: The EPA believes this comment is related to a different TSD because this TSD 

is only 20-pages long (has not page 28) and does not include this reference. 

Reviewer also recommends considering the follow-on to this study that looked at the 

participant costs, available at http://emp.lbl.gov/what-it-costs-save-energy. Note that this 

newer report is cited as "LBNL. 2015b. The Total Cost of Saving Electricity through Utility 

Customer-Funded Energy Efficiency Programs: Estimates at the National, State, Sector and 

Program Level. Lawrence Berkeley National Laboratory. Available 

at http://emp.lbl.gov/sites/all/files/total-cost-of-saved-energy.pdf." but doesn't appear to be 

referenced in the document. EPA should update the reference.
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EPA Response: The EPA believes this comment is related to a different TSD because this TSD 

is only 20 pages and does not include this reference. 

Technical & Editorial Comments

22. Page 3: Technical edit: “It is important to understanding which resource options are 

currently available to the state for meeting future demand.”

EPA Response: Completed as requested.

23. Page 5: “Because these one-the-books RE and demand-side EE measures or programs”

EPA Response: Completed as requested.

24. Page 5 & throughout text: Reviewer recommends replacing “*” and “x” in equations with 

multiplication symbol “×”

EPA Response: Completed as requested.

25. Page 8: Reviewer recommends modifying the equation for Renewable Energy to reflect 

accurate calculation of MWh: 

“(Incremental MW installed capacity) × (location and technology-specific capacity factors) × 

(8760 h) for each interim period and final period.”

EPA Response: Completed as requested.

26. Page 13: Reviewer recommends updating equation to demonstrate correct calculation of 

annual MWhs:

“A(t) = [f1(t) × C1(t) + f2(t) × C2(t) + f3(t) × C3(t)] × 8760 hours”

EPA Response: Completed as requested.

Additional Comments (added by the EPA)

27. Section III.B.: OMB reviewer comment bubble in TSD stated, “This discussion of computing 

savings from EERS should discuss how to account for the difference between net and gross 

savings where both are reported and where only one is”. 
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EPA Response: This comment was not listed in the OMB summary of comments, and so the 

EPA is adding it this this list rather than respond to the comment bubble in the TSD. Footnote 

has been edited to ensure EE savings are quantified in accordance with the EM&V guidelines.