## 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

- S ide EE Impacts in to 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 (CO 2 

## ) emission performance by affected electric generating units (EGUs) , as identified in section VIII.D.2.a(3) of the prea mble. 1 

## Development of a state’s CO 2 

## emission performance projection begins with a n electricity demand forecast , which, depending upon the type o f 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 choo se 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 c ase demand forecast to reflect these impacts.



# I I

. Base C ase Electricity Demand and Supply Forecasts

The CO 2 

## emission performance projection of affe cted 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 meas ures 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 energ y 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 regiona l specific historical electricity sales data

. States may also consider more comprehensive modeling approaches that calculate expected demand based on assumptions including: electrici ty 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 existi ng 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 demand

side 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 program s 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 s tate

- specific base ca se forecasts developed by states must be approved by EPA per the final emission guidelines.

### 4 

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

program s 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 effec t , • Forthcoming f ederal appliance and lighting standards
,
• State appliance or lighting efficiency standards (if applicable)
, • State building energy codes
, • Renewable portfolio standards
, and

• C odified local policies

.
There are at least two ways that these programs are captured in an existing forecast:
1. Programs are explicitly identifie d , meaning the forecast show s a direct connection between the program and its impacts on energy demand or supply (MWhs)
, 2. Programs are in directly, 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 deman d 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 include s 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 de mand

- 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 requ ired to adjust for potential double counting. For more information visit: http://www.epa.gov/statelocalclimate/state/statepolicies.html.

### 5 

## For all RE and demand

- side EE program s 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 requirement s 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 adopt s a rate

- based emission standards type state plan that requires a projection . T he 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
CO 2 

## emission rate s , 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 

## I f the state expect s affected EGUs to use the demand

- side EE impacts from the EERS to adjust the ir rate s, 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 EP A'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 measu res or actions outside of the EERS.

### 6 

## 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
CO 2 

## emission performance projection, because they are already captured in that base case
forecast. For a ny 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 informatio n :

1. Policy or program name , 2. Whether the program is codified in state or local rule
, 3. Year enacted
, 4. When the p rogram requirement s sunset , 5. P rogram 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 CO 2 

### performance rate of an affected EGU under the final rule are detailed in

s ection VII I.K.1

. 6 

### For details refer to s ection s VIII.B.2 and VIII.K.1.a of the preamble

.

### 7 

## 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 CO 2 

## emission performance projections for affected EGUs in order to show that the state plan will lead
to achievement of the CO 2 

## emission performance rates, state goal, or other emission guideline requirements

. S tate plans that require such a projection must include a base case electricity
demand and supply forecast as well as supporting documentation
, as explain ed 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. T his section explains the proper
characterization of expected RE and demand

- side EE impacts in a CO 2 

## 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 CO 2 

## 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 emiss ion guidelines. There are different approaches to projecting electricity savings and renewable generation , depending up on the design of an RE and demand

side 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 p rogram.

### 8 

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



## A. Approaches to E stimating F uture RE Generation and EE S avings
Projections of expected annual electricity savings and/or renewable energy generation are necessary inputs when projecting EGU CO 2 

## emission performance. This is because i ncreased RE generation will impact the generation of affected EGUs and resulting CO 2 

## emissions

. Electricity savings estimates included in EE projections will lower electricity demand forecasts in the CO 2 

## emission performance projections. The EE projection can be used as an input, or modifier, to
various models or ot her tools in order to demonstrate that the state plan will achieve emission guideline requirement s.

A CO 2 

## emission pe rformance projection must include the potential impacts of RE and
demand

- side EE
, and the state must document how th ose RE and demand

- side EE impacts are reflect ed 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 discuss ed above, a state plan CO 2 

## 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 CO 2 

## 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 eligibi lity requirements specified in s ection VIII.K.1 of the preamble . Other types of programs and projects that may be eligible for inclusion are described in s ection VIII.K.1.a

. 9 

### Guidance on Incorporating Bundled Measures in a State Implementation Plan, www.epa.gov/ttn/oarpg/t1/memoranda/10885guideibminsip.pdf.

### 9 

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

- side EE programs not reflected in the base case forec ast 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 demand

side EE during the future interim and final performance periods

. 10


## Energy Efficiency:

• (Incremental first

- year annual plus cumulative savings of EE program 11 

## ) 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 adjus t 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 st udies to estimate the direct energy impacts

10 

### The EPA recognizes th at 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

- by

case 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.

### 10 

## 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 a nd/or engineering

- based estimation techniques that are based

up on 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 u p to the statewide level

. Alternatively, the potential impacts of RE and demand

- side
EE can be quantified based up on 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
CO 2 

## 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. S ome specify goals based on electricity sales (in MWhs) from investor

owned utilities, whil e others have mandated en ergy savings targets based on total MWh sales or
a subset of total MWh sales.
A state can quantify energy savings for use in its CO 2 

## 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 

### Savi ngs from purely voluntary demand

- side EE goals are not state enforceable measures and are not eligible for use in a CO 2 

### emission performance projection for a state measures type plan

. Quantification of eligible demand

- side EE savings must be done in accord ance with the requirements specified in s ection VIII.K.3 of the preamble.

### 11 

## select the appropriate sales basis
, and if the basis is not total sales, a state could u se recent year utility

- level sales data from EIA and growth rates from EIA, an RTO/ ISO, NERC or other publicl y available sources to develop base case foreca sts 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
CO 2 

## emission performance projection, should assume energy savings at the EERS target level. For example, it may not be a ppropriate to assume full achievement of energy saving s 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 EER S policy for each year (t) are shown below , though a state may propose a different methodology if it better repr esents the state’s EER S. Once these first

- year and cumulative energy savings are quantified, the state can incorporate them into the demand forecast of its CO 2 

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

### 12 

## 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 Pe rcent 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

- 20 18 to the absolute targets shown in the table below

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

### 13 

## 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. S tates 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 specifi c 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.

### 14 

## 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, app lied 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

- 20 18 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 incl ude 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,

### 15 

## 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 representati ve 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 s avings 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

- 20 18 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 p ortfolio s tandards (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

come s 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 public ly available sources to develop base case forecasts of sales for the utilities required to comply with the RPS.
The design of the RPS will affec t whether a state can assume full achievement of the RPS targets. Many RPS s include p rovisions for a lternative c ompliance p ayments, 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 case s , only generation impacts from eligible RE sources should be included in a state’s CO 2 

## 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)

– MWh ineligible 

## (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 MWh ineligible 

## is the MWh of generation from t echnologies 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 requiremen ts 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 s e ction s 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 s ection VIII.K.2.
18 

### The equations in this section are the recommended calculation methods for incl usion 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 (MWh ineligible 

## ) 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 fina l CPP. As a result, eligible renewable generation is 7,000 GWh in 2015. Assuming the same MWh ineligible 

## 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

. E ven 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 underl ying 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 a n eligible RE re source per the final emission guidelines ; a technolog y that is not an eligible RE resource should not be included in the formula

. 19



## A(t) = [ f 1 

## (t) x C 1 

## (t) + f 2 

## (t) x C 2 

## (t) + f 3 

## (t) x C 3 

## (t) ] x H

Where: A is the total MWh of eligible renewable generation in a future year, f 1 

## , f 2 

## , and f 3 

## are annual effective capacity factors for eligible technologies 1, 2, and 3, respectively, and C 1 

## , C 2 

## , and C 3 

## 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 (MW h ) 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

s ection 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 reso urce. 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

- S ide EE in a State Plan CO 2 

## Performance Projection
As explained above, s tates 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

s ection VIII.D.2.a.(3)(a) of the preamble) must quantify for each requirement and program the expected direct electricity savings and genera tion impacts on affected EGUs. Further, t he state plan performance demonstration must document the underlying assumptions regarding the

renew able 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 e fficiency and/or renewable energy r equirement or p rogram 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/ p rogram time period: What year does each specific program star t and e nd?
What are the MWh target s for the interim and final performance periods, including interim steps and other applicable time periods ? How will the program meet the permanent requirement s in the CPP ?

• Relationship to complementary or existing requirement/program(s): Will this program include any fed erally enforceable limits ? Are state measure s an expansion or extension of existing requirement s or program s ? If the plan includes an expansion of an existing

### 20 

## program that allows for ineligible resou rces or unaffected EGUs , how does t he
demonstration address the se 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

- sid e 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 h ow many years will th e 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 w ould 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: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review *** ¶ 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

- S ide EE Impacts in to State Plan Demonstrations

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

July 31, 20152 Deleted: *** E.O. 12866 Review

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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 (CO 2 ) emission performance by affected electric generating units (EGUs)
, as identified in section VIII.D.2.a ( 3) of the prea mble. 1 Development of a state’s CO 2 emission performance projection begins with a n electricity demand forecast , which, depending upon the type o f 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

.


### I I

. Base C ase Electricity Demand and Supply Forecasts

The CO 2 emission performance projection of affe cted 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 meas ures type plans as well as some emission standards type plans

. Deleted: projections,
Deleted: .(
Deleted: A
Deleted: projection will include both a

Deleted: and a state plan pe rformance projection

. 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 CO 2 emission performance projection , including projection approaches
Deleted: documentation requirements

Deleted: electric generating units (
Deleted: )

Deleted: renewable energy
Deleted: energy programs3 Deleted: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review *** ¶ 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 regiona l 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 anticipat ed 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 demand

side 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 program s 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 differe nt source and EPA would review those requests on an individual basis. Any s tate

- 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 curr ently
Deleted: the
Deleted: for meeting future
Deleted:

. Deleted: renewable energy
Deleted: energy efficiency
Deleted: Information
Deleted:
, and a Deleted: each
Deleted: program4 Deleted: *** E.O. 12866 Review

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demand or supply forecast used by the state are incorporated into that

. This will clarify which

program s 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 ho w 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 f ederal appliance and lighting standards
,
• State appliance or lighting efficiency standards (if applicable)
, • State building energy codes
, • Renewable portfolio standards
, and

• C odified local policies

.
There are at least two ways that these programs are captured in an existing forecast:
1. Programs are explicitly identifie d , meaning the forecast show s a direct connection between the program and its impacts on energy demand or supply (MWhs ) , 2. Programs are in directly, 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 Inform ation Agency’s (EIA) Annual Energy Outlook (AEO) explicitly include s 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 renewa ble 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. In direct 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: F ederal

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

. Deleted:
,5 Deleted: *** E.O. 12866 Review

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For all RE and demand

- side EE program s 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 requirement s 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 adopt s a rate

- based emission standards type state plan that requires a projection . T he 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
CO 2 emission rate s , 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 I f the state expect s affected EGUs to use the demand

- side EE impacts from the EERS to adjust the ir rate s, 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

Deleted: the
Deleted: is included
Deleted: a component of the
Deleted: plan.
Deleted: an Deleted: type Deleted: will
Deleted:

.

Deleted: the

Deleted: But if

Deleted: at the end of this section.

Deleted: whether6 Deleted: *** E.O. 12866 Review

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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
CO 2 emission performance projection, because they are already captured in that base case
forecast. For a ny 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 do cument the following informatio n :

1. Policy or program name , 2. Whether the program is codified in state or local rule
, 3. Year enacted
, 4. When the p rogram requirement s sunset , 5. P rogram 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 CO 2 performance rate of an affected EGU under the final rule are detailed in

s ection VIII.K.1

. 6 For details refer to s ection s 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)7 Deleted: *** E.O. 12866 Review

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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 CO 2 emission performance projections for affected EGUs in order to show that the state plan will lead
to achievement of the CO 2 emission performance rates, state goal, or other emission guideline requirements

. S tate plans that require such a projection must include a base case electricity
demand and supply forecast as well as supporting documentation
, as explain ed 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. T his section explains the proper
characterization of expected RE and demand

- side EE impacts in a CO 2 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 CO 2 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 emiss ion guidelines. There are different approaches to projecting electricity savings and renewable generation , depending up on the design of an RE and demand

side 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 p rogram. Deleted: )

Deleted: )

Deleted: and

Deleted: / or Deleted: how
Deleted: requirement is designed8 Deleted: *** E.O. 12866 Review

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



### A. Approaches to E stimating F uture RE Generation and EE S avings
Projections of expected annual electricity savings and/or renewable energy generation are necessary inputs when projecting EGU CO 2 emission performance. This is because i ncreased RE generation will impact the generation of affected EGUs and resulting CO 2 emissions

. Electricity savings estimates included in EE projections will lower electricity demand forecasts in the CO 2 emission performance projections. The EE projection can be used as an input, or modifier, to
various models or ot her tools in order to demonstrate that the state plan will achieve emission guideline requirements.

A CO 2 emission pe rformance projection must include the potential impacts of RE and
demand

- side EE , and the state must document how th ose RE and demand

- side EE impacts are reflect ed 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 CO 2 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 CO 2 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 eligibi lity requirements specified in s ection VIII.K.1 of the preamble . Other types of programs and projects that may be eligible for inclusion are described in s ection 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 ge neration

Deleted: energy efficiency

Deleted: state plan

Deleted: A

Deleted: state plan9 Deleted: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review *** ¶ demand forecast. The performance project ions, 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 demand

side EE during the future interim and final performance periods

. 10
Energy Efficiency:

• (Incremental first

- year annual plus cumulative savings of EE program 11 ) 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 dema nd

- side EE that will be used to adjus t 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

- by

case basis.
11 Projections of demand

- side EE im pacts 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 av ailable datasets from EIA and ISO/RTOs. Deleted: and

Deleted: specific10 Deleted: *** E.O. 12866 Review

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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
deve lopment 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

up on 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 up on 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
CO 2 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 cumulativ e targets as percentages of electricity sales or as absolute energy savings

. States use different bases for specifying EERS goals. S ome specify goals based on electricity sales (in MWhs) from investor

owned utilities, whil e 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 CO 2 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_a ssessing_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 CO 2 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 s ection 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
Deleted: ene rgy efficiency resource standard

Deleted: type

.11 Deleted: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review *** ¶ select the appropriate sales basis
, and if the basis is not total sales, a state could u se recent year utility

- level sales data from EIA and growth rates from EIA, an RTO / ISO, NERC or other publicl y available s ources 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
CO 2 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 saving s 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 s tate must use to quantify first

- year and cumulative energy savings
from an EER S policy for each year (t) are shown below , though a state may propose a different methodology if it better represents the state’s EER S. Once these first

- year and cumulative energy savings are quantified, the state can incorporate them into the demand forecast of its CO 2 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 polici es, 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. Deleted:
, Deleted:
, Deleted: publically

Deleted: full achievement of
Deleted: targets

Deleted: *

Deleted: AEO2013
Deleted: AEO201312 Deleted: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review *** 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 th e
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 cumulati ve 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

- 20 18 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 Deleted: AEO2013
Deleted: AEO201313 Deleted: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review *** ¶ 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 increme ntal to the base case demand forecast , and Z is the adjusted sales after application of cumulative incremental savings. Deleted: *

Deleted: AEO2013
Deleted: AEO201314 Deleted: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review *** 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 saving s is four years. Distribution of the cumulative energy savings in 2018 to the
first

- year savings for 2016

- 20 18 applies the simple assumption of an equal share of savings being implemented in each year. Table 3 applies this example to the above formula. Thi s approach is uncommon, and states that applied this structure in earlier years of their EERS policies incl ude 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,15 Deleted: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review *** ¶ 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 ener gy savings in 2018 to the
first

- year savings for 2016

- 20 18 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 impleme ntation 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 p ortfolio s tandards (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

come s 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 Deleted: AEO2013
Deleted: AEO2013

Deleted: come

Deleted:
,16 Deleted: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review ***
RTO / ISO, NERC or other public ly 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 RPS s include p rovisions for a lternative c o mpliance p ayments, 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 case s , only generation impacts from eligible RE sources should be included in a state’s CO 2 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)

– MWh ineligible (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 MWh ineligible 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 indivi dually

17 States must represe nt 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 certi ficates. 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 per formance 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 i n a projection. For more information about acceptable accounting methods for RE, see s e ctions 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 s ectio n VIII.K.2.
18 The equations in this section are the recommended calculation methods for inclusion in state plans. Deleted:
, Deleted: publically

Deleted: state plan

Deleted: *17 Deleted: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review *** ¶
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 (MWh ineligible ) 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 s ame MWh ineligible 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
Massach usetts, 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

. E ven 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., cap acity factors)

. Each state should include the number of technology types that best applies to its own RPS design

. In this example , each18 Deleted: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review *** technology (1, 2, and 3) is a n eligible RE re source per the final emission guidelines ; a technolog y that is not an eligible RE resource should not be included in the formula

. 19

A(t) = [ f 1 (t) x C 1 (t) + f 2 (t) x C 2 (t) + f 3 (t) x C 3 (t ) ] x H

Where: A is the total MWh of eligible renewable generation in a future year, f 1 , f 2 , and f 3 are annual effective capacity factors for eligible technologies 1, 2, and 3, respectively, and C 1 , C 2 , and C 3 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 24,8 78,400 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 wi th 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 (MW h ) of wind or solar energy. In order to avoid double counting, the amount of the carve

- ou t 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

s ection VIII.K.3

. Deleted: *
Deleted: *
Deleted: *
Deleted: ) Commented [A3]: Should this for mula not include the hours of generation (i.e. multiply by 8760 hrs)?

Deleted: Section19 Deleted: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review *** ¶

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 loc ation 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 CO 2 

### Performance Projection
As explained above, s tates 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

s ection VIII.D.2.a.(3)(a) of the preamble) must quantify for each requirement and program the expected direct electricity savings and genera tion impacts on affected EGUs. Further, t he 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 e fficiency and/or renewable energy r equirement or p rogram description: What is the requirement/progr am? Who will administer it? Does it require new legislation or can a state implement it under existing authorities?

• Requirements/ p rogram time period: What year does each specific program start and e nd?
What are the MWh target s for the interim and final performance periods, including interim steps and other applicable time periods ? How will the program meet the permanent requirement s in the CPP ?

• Relationship to complementary or existing requirement/program(s): Will this program include any fed erally enfor ceable limits ? Are state measure s an expansion or extension of existing requirement s or program s ? If the plan includes an expansion of an existing Deleted: R enewable E nergy Deleted: Energy Efficiency

Deleted: S ection

Deleted: impacts20 Deleted: *** E.O. 12866 Review

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– Do Not Cite, Quote or Release During Review *** program that allows for ineligible resources or unaffected EGUs , how does t he
demonstration address the se imp acts?

• 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? F or h ow 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 dec rease 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 Fundin g: 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?

Deleted: the
Deleted: end

- use sector/or renewable energy technology

Deleted:

.

Deleted: energy efficiency
Deleted: /or renewable energy

Deleted: will

### 1 

# Incorporating RE and Demand

- side EE Impacts into State Plan Demonstrations Technical Support Document for the Clean Power Plan

U.S. EPA r esponse to OMB Comments from 7/28/2015
July 3 1 , 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 CO 2 

### emission performance projection. Recommended text:

“This technical support document details demonstration requirements for Clean Power Plan (CPP) state pl an submittals that must include carbon dioxide (CO 2 

### ) emission projections, primarily states adopting a state measures plan or, as identified in section VIII.D.2.a.(3) of the prea mble.”

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 f orecast or use a forecast from the following information sources.

• U.S. Department of Energy, Energy Information Ad ministration, 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 coordina te 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 doe s not have state level forecasts but states can use either AEO or NERC growth
rates to inform state level projections. The TSD clearly state s that forecasts from this list can

### 2 be used to generate state

- derived growth rates, based off of regional informatio n 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 e lectricity 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 TS D already address es th e 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 add ressed 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 tha t 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 amoun t 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 distri buted 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 i n S tep 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: T he EPA addressed t his 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 quanti fy 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 review er 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.

### 4 “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 p rojects, programs or policies. The EPA clarif ied 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 rec ommends the following edits.

“Because these on e

- 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 sta te plan performance projection, because they are already captured in that base case forecast.”

EPA R e sponse : 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 sa vings 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 e dited 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 si mple 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 f or 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 t he notes on AEO2013, EERS and EE savings

.

### 5 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 dem onstration 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 p rocurement 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 wit h 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 complian ce, 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 t o 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 CO 2 

### 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: Th e EPA believe s 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. Ava ilable
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.

### 6 EPA R esponse: The EPA believe s 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 understand ing which resource options are currently available to the state for meeting future demand.”

EPA Response: Completed as requested.

23. Page 5: “Because these on e

- 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 whe re only one is”.

### 7 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.