From: Culligan, Kevin [mailto:Culligan.Kevin@epa.gov] Sent: Sunday, June 01, 2014 5:46 PM To: Higgins, Cortney; Wayland, Robertj Subject: Fw: State Plan TSDs

<< TSD_Projecting_EGU_CO2_Emission_Performance_In_State_Plans.pdf >> << TSD Projecting EGU CO2 Emission Performance in State Plans.docx >> << TSD_State_Plan_Considerations.pdf >> << State Plan Considerations TSD_Final_5.31.14.docx >>

From: Higgins, Cortney <Cortney_Higgins@omb.eop.gov> Sent: Sunday, June 1, 2014 3:47:53 PM To: Culligan, Kevin Cc: Wayland, Robertj Subject: RE: State Plan TSDs

Hi Kevin,
Can you send clean versions of these TSDs – St ate Plan Considerations and Projecting Emissions Performance TSDs?
Thanks, CortneyTechnical Support Document (TSD) for

Carbon Pollution Emission Guidelines fo r Existing Stationary Sources: Electric Utility Generating Units

Docket ID No. EPA

- HQ

- OAR

- 2013

- 0602



# Projecting EGU CO 2 

# Emission Performance in

State Plans

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

June 20142 Table of Contents

I. Introduction

................................ ................................ ................................ ........................ 3 II. Analytic Approaches for Projecting CO 2 Emissions from Affected EGUs

.................. 6

A. Electricity System Modeling Approaches for Projecting EGU CO 2 Emissions

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

............. 10 III. Translating from a Rate

- Based Emission Performance Goal to a Mass

- Based Emission Performance Goal

................................ ................................ ............................ 1 3 A. Concept

................................ ................................ ................................ ................... 1 3 B. Projection Scenarios

................................ ................................ ................................ 1 5 IV. Projecting CO 2 Emission Performance under a State Plan

– Overview

..................... 20 V. Applied Considerations for Different Types of State Plans

................................ ......... 21

A. End

- Use Energy Efficiency and Renewable Energy

................................ ............. 21 B. Emission Budget Trading Programs

................................ ................................ ...... 36 VI. Process Considerations

................................ ................................ ................................ .... 43

A. Provision of the EPA Guidance

................................ ................................ ............. 43 B. Party that Translates the Rate

- Based Goal to a Mass

- Based Goal

........................ 453

I

. Introduction
As discussed in the preamble, in section VIII.F.7 , all state plans will need to include a projection of the CO 2 emission performance by affected EGUs that will be achieved under a state plan (inclusive of plan measures that avoid CO 2 emissions from affected EGUs, such as end

- use energy efficiency and renewable energy). D epending on the type of plan approach, this will include either a projection of the average CO 2 emission rate achieved by affected EGUs or total
CO 2 emissions from affected EGUs.

The EPA is also proposing that a state may translate the state rate

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

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

- based CO 2 emission performance goal. This trans lation will involve a projection of CO 2 emissions from affected EGUs during the initial 2020

- 2029 plan performance period and in
2030 , under a scenario that assumes the rate

- based goal in the emission guidelines is met.

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

The preamble, at section VIII.F.7, seeks comment on options presented for how CO 2 emission projections might be conducted in an approvable state plan, and how different types of state plan approaches are represented in these projections. These options include the use of historical data and parameters for estimating the future impact of individual state programs and measures. Alternatively, a projection could be based on modeling, such as use of a capacity expansion and dispatch planning model, or a dispatch simulation model. 1 This latter approach would be able to capture dynamic interac tions within the electricity sector, based on system

1 In many cases, this approach will also require the development of parameters for estimating the effect of individual state programs and measures, for use as input assumptions for modeling.4

operation and market forces, including interactions among state programs and measures and the dynamics of market

- based measures.

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

This technical support document (TSD) elaborates these options and considerations. The
TSD discusses possible analytic approaches for translating from a rate

- based CO 2 emission performance goal to a mass

- based goal, and projecting the CO 2 emission performance that will be achieved through a state plan. I t discusses both modeling and non

- modeling approaches, such as electricity sector capacity expansion and dispatch planning models, dispatch simulation models, and growth tools that base projections on historical data and algorithms. The TSD also
discusses possible approaches for developing inputs that are used for emission projections and applied considerations for different types of state plans. Topics addressed include:

 Section II discusses a nalytic approaches for projecting CO 2 emissions from affected
EGUs

 Section III discusses the concept and practice of t ranslating from a rate

- based CO 2 emission performance goal to a mass

- based CO 2 emission performance goal

 Section IV discusses the concept and practice of p rojecting EGU CO 2 emission performance under a state plan

 Section V discusses a pplied considerations for projecting EGU CO 2 emission performance under different types of state plans , including:

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

o Data needs and methods for developing inputs to EGU CO 2 emission projections, for different types of state plans

 Section VI discusses process considerations for conducting EGU CO 2 emission projections for state plans, including :

o R egional coordination among states in conducting projections5

o W hether the EPA should provide guidance and other analytic support for conducting projections in state plans and translat ion of rate

- based CO 2 emission performance goals to mass

- based goals6

II

. Analytic Approaches for Projecting CO 2 Emissions from Affected EGUs
This section surveys different types of methods and tools for projecting CO 2 emissions from affected EGUs, including modeling tools and other tools that base projections on historical data and use algorithms to extrapolate future CO 2 emissions performance based on past performance.

A

. Electricity System Modeling Approaches for Projecting EGU CO 2 Emissions

1

. National

- scale capacity expansion and dispatch planning models

National

- scale electricity capacity expansion and dispatch planning models are typically
used for fundamentals

- based projections of the power se ctor (i.e., projections of the expected response of the sector to factors such as electricity demand, fuel prices, and emission con s traints) that may extend over a period of several decades. These models are built to evaluate the impacts of market, technic al, and regulatory factors on the electric power sector and related markets

. Typical outputs of such models include EGU dispatch, fuel consumption, fuel prices, wholesale electricity prices, emissions, EGU retirements, and infrastructure expenditures ( e.g., addition of

new EGU capacity and installation of retro fit pollution control technologies ).

National

- scale electricity capacity expansion and dispatch planning models have moderate spatial detail with broad scope, generally encompassing the entire c ountry or transmission system interconnects (i.e. Eastern, Western, and ERCOT), which are subdivided into smaller areas, such as balancing authorities or control areas. 2 For computational efficiency, these models generally model several representative hour s of the year, or aggregate hours into representative bundles with similar electricity demand profiles (i.e. peak, shoulder, off

- peak)

. In these models, to reduce model size, existing EGUs may be aggregated into “model plants” to the
extent that such EGUs share key unit characteristics, such as location, size, efficiency, operating costs, pollution retrofit control status, age, and fuel type use/availability. These types of models are well suited to project dynamic entry and exit (capacity expansion and uni t retirement) to meet energy and capacity requirements while minimizing system costs, maintaining reliability criteria,

2 A “balancing area” or “control area” refers to a spe cified portion of the transmission system where electricity demand and generation are balanced in real time by a system administrator to maintain grid reliability.7

and following other constraints, such as minimum build times, transmission constraints, renewable energy availability, or emission limit ations.

2. Utility

- Scale Capacity Expansion and Dispatch Planning Models
Utility

- scale capacity expansion and dispatch planning models are similar in concept to
related national

- scale models. However, utility

- scale capacity expansion and dispatch planni ng models are typically used for evaluating narrower utility planning and investment decisions, such as procurement of a specific new electric generating facility and retirement or retrofit decisions for existing capacity within a specific utility’s territory. Utility planning models typically project outcomes for periods of up to two decades. Utility

- scale capacity expansion and dispatch planning models are an ind ustry standard, used regularly in state electricity regulatory proceedings. Within the electricity sector there is broad familiarity with these models at state PUCs. Multiple vertically integrated utilities use capacity expansion and dispatch planning
mode ls to conduct forward planning and review the economics of specific EGU retrofit decisions. Utilities that submit integrated resource plans (IRP) typically use a utility

- scale capacity expansion and dispatch planning model to examine long

- term strategies a nd develop
short

- term action plans. 3 Utilities have experience using these models to examine CO 2 emission reduction strategies or CO 2 emission constraints, as IRP scenarios may include greater penetration of end

- use energy efficiency or renewable energy, p roxy CO 2 emission prices, emission trading, and limits on CO 2 mass emissions.

Utility

- scale capacity expansion and dispatch planning models tend to have relatively high spatial detail with limited geographic scope, generally encompassing a utility service territory or a sub

- regional scale. These models generally have better temporal resolution than the
national

- scale capacity expansion and dispatch planning models, with each model year typically

3 See, for example: The Duke Energy Carolinas IRP (Annual Report), September 2012, available at http://www.energy.sc.gov/files/view/Duke_IRP 2012.pdf ; PacifiCorp 2013 IRP (Vol 1), April 2013, available at http://www.pacificorp.com/es/irp.html ; TVA IRP, March 2011, available at http://www.tva.gov/environment/reports/irp/archive/index.htm ; Georgia Power Company 2013 IRP, January 31, 2013, available at http://facts.psc.state.ga.us/Public/GetDocument.aspx?ID=145981 ; 2011 Joint IRP of Louisville Gas and Electric and Kentucky Utilities Company, April 2011, avai lable at http://psc.ky.gov/PSCSCF/2011%20cases/2011

- 00140/20110421_LG%26E

- KU_IRP_Volume%20I.pdf ; Great River Energy IRP, November 2012, available at http://www.greatriverenergy.com/makingelectricity/resourceplan/pdoc295631.pdf ; Public Service Company of Oklahoma IRP, October 2012, available at http://occeweb.com/pu/PSO%202012%20IRP.pdf

.8

dispatched based on an annual hourly load duration curve. 4 Ut ility

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

Due to the additional spatial and temporal resolution of these models as compared to the
national

- sca le models, the number of technology options for capacity expansion is generally limited to reduce the runtime of the model. This can be done through an outside

- the

- model screening analysis to pre

- select the resources most likely to be economic in a planner ’s area of interest, or by running the model iteratively to eliminate rarely chosen technology alternatives.

3

. Electricity System Dispatch Simulation Models
Dispatch simulation models are regularly used by utilities, grid operators, and independent power producers (IPP) for short

- term planning, ratemaking, dispatch decisions, and market intelligence. Dispatch simulation models are typically driven by near

- term economics
, system restrictions and market constraints, including a typically more detailed representation of
an EGU’s operational constraints ( e.g. , ramp rates, heat input curves, and unit downtime for maintenance). These models typically do not add or retire generating capacity on an economic basis, although EGU additions and retirements may be exogenously input to these models. As a result, projections from these models tend to be considered more robust in the shorter term

. 5 Grid operators, incl uding utilities, and independent system operators (ISO) use dispatch simulation
models in near real

- time to match demand with electric generation from available generating units and dispatch EGUs on a least

- cost basis. EGU owners and operators run dispatch simulation models to assist in fuel procurement, forecast revenues and costs, and calculate the avoided generation supply costs related to procurement of end

- use energy efficiency and

4 Load duration curves typically represent electricity load during a typical week for each month. 5 Some planners use dispatch simulation models in conjunction with nationa l or utility

- scale capacity expansion and dispatch planning models, where the capacity expansion and dispatch planning model indicates the disposition of new and existing generating resources, and the dispatch simulation model is used to simulate operation of individual EGUs. In this case, these models can be used in the same time horizon as a capacity expansion and dispatch planning model ( i.e ., decades).9

renewable energy resources. 6 Other utilities use dispatch simulation mo dels to forecast retail rates for ratemaking proceedings and other planning purposes.

Electricity system dispatch simulation models (also called production cost models) utilize security constrained economic dispatch (SCED) algorithms to determine which E GUs operate on an hourly (or shorter) basis to meet electricity demand. 7 These models typically have a very broad spatial scope, generally covering multiple Regional Transmission Organization (RTO) regions, and often modeling entire interconnects (i.e. Wes tern, Eastern, and ERCOT). While individual EGUs are modeled in detail, including fuel and variable costs and operational constraints, transmission is simplified to characterize thermal constraints between zones, which typically represent control areas or balancing authorities. Zones contain both load (electricity demand) and EGUs; EGU dispatch and electricity demand are balanced to maintain transmission system reliability while providing least

- cost service on a variable cost basis. Some versions of
these m odels operate at a “nodal” level, where transmission constraints between individual
EGUs and load are modeled as well. 8 Dispatch simulation models typically operate chronologically, modeling either all 8760 hours of the year, or typical weeks of the year. These models contain substantially more detail about individual EGUs than regional or national capacity expansion and dispatch planning models, including EGU ramp rates, minimum outages, maintenance schedules, emission rates, fuel use constraints, and heat rate curves depicting expected efficiency changes at various levels of output.

6 For example, see Hornby, R., P. Chernick, D. White, et al., 2013. Avoided Energy Supply Costs in New England: 2013 Report. http://www.rieermc.ri.gov/documents/2013%20Evaluation%20Studies/AESC%20Report%20

- %20With%20Appendice s%20Attached.pdf
7 The Federal Energy Regulatory Commission (FERC) defines security constrained economic dispatch as “the level at which each available resource should be operated, given actual load and grid conditions, such that reliability is maintained and overall production costs are minimized”. SCED optimizes dispatch based not only on the marginal costs of all available generating resources, but also constraints on transmission availability and ancillary services. See FERC, “Security Constrained Econ omic Dispatch: Definition, Practices, Issues, and Recommendations” (2006), available at http://www.ferc.gov/industries/electric/indus

- act/joint

- boards/final

- c ong

- rpt.pdf

. 8 “A “nodal” model represents the entire transmission network in a given area, without making the simplifying assumptions that load is served on a more aggregate “zonal” level.” A caveat is that while a nodal model has more “links” and places where supply must meet demand, it is still an approximation in terms of the electrical operation of the transmission network (the network is represented as a DC flow network, not an AC flow network).10

4

. Multi

- Sector Models

Multi

- sector energy models are typically used to examine the effect of energy and environmental policies that affect multiple economic sectors, such a s multi

- sector emission trading systems. Multi

- sector models are used to review trends in emissions, expected broad

scale resource use, and energy sector impacts under changing regulatory and economic conditions, and often review changes over a period of decades.

Multi

- sector models cover a broad range of energy sectors beyond the electricity sector, and can better reflect energy demand and technology choices by energy end

- users. Such models typically have relatively limited spatial detail with broad scope, generally encompassing the entire country subdivided into from one to 30 regions. Such models tend to have much more limited temporal resolution and treatment of EGU dispatch. EGUs are typically aggregated to a few broad technology types. A key strength of multi

- sector energy models is the ability to provide multi

- sectoral feedback between energy resource use and price ( i.e. , tracking national fuel supplies and adjusting price to account for demand).

The range of national

- and utility scale capacity expansion and dispatch planning models, and dispatch simulation models identified above all tend to focus on properly characterizing the electricity sector in order to answer sector

- specific questions. Multi

- sector energy models attempt to include many other energy

- using sectors of the economy in order to better capture interactions between these sectors. The more aggregate d representation of the electricity sector i n multi

- sector models may limit their use to providing input data for more specific analysis in an electricity sector model, and to better understand ing variations in electricity load that may result from changes outside the electricity sector.

B

. Gro wth Tools for Projecting EGU Utilization and CO 2 Emissions
Organizations use growth tools for a variety of reasons
, including to estimate future emissions inventories for state and regional air quality modeling
, 9 and to estimate the impact of
load

- reducti on measures such as end

- use energy efficiency and distributed renewable energy on

9 See, for example, the ERTAC Load Growth Model, availa ble at http://www.ertac.us/index_egu.html

.11

individual EGU emissions, and county, state, 10 and regional emissions rates. 11 Because these algorithms are generally based on publicly available data 12 and do not rely on econo mic data or proprietary information regarding individual EGUs, they provide a low

- cost, simple, and often transparent framework for estimating how EGUs will respond to changing system conditions.

Non

- modeling approaches , such as growth tools, approximate future emissions and generation from existing and new fossil fuel

- fired EGUs under different assumed growth, retrofit, and load

- reduction scenarios. These forecast tools do not simulate economic EGU dispatch, but could use demand growth rates and electrici ty production trends from other energy modeling forecasts as an input assumption. 13 The algorithms in these forecast tools assume that EGU dispatch behavior generally follows simple rules based on past operation. In the absence of significant shifts in fuel prices and electricity demand, EGUs may be expected to behave similarly in the future as they did in the past. Several common features of these forecast tools are that they (a) generally build on historical generation and emissions output from individual EGUs, (b) are insensitive to fuel and emission price forecasts, (c) do not solve for optimal economic EGU dispatch or EGU capacity expansion, and (d) do not capture transmission constraints or limits. The algorithms in these forecast tools generally divide the contiguous US 14 into regional power markets, following ISO boundaries, eGRID boundaries, NERC regional boundaries, or similar designations. These algorithms generally seek to examine how operation and emissions from individual EGUs could be expected to change with changes in environmental regulations or installed pollution control retrofits and additional or reduced hourly electricity demand. Some algorithms use the observed historical behavior of individual EGUs to approximate future behavior, while ot hers add additional steps of differentiating EGUs into fuel groups and unit

10 See EPA’s AVERT (Avoided Emissions and Generation Tool), available at http://epa.go v/statelocalclimate/resources/avert/index.html

. 11 See Flexibility Weighted Hourly Average Emissions Rate (FW

- HAER) tool, available at http://nepis.epa.gov/Adobe/PDF/P1002UQO.pdf ; Time Matched Marginal (TMM) emissions tool, a proprietary algorithm used to estimate avoided emissions; D. Jacobson and C. High, “U.S. Policy Action Necessary to Ensure Accurate Assessment of the Air Emission Reduction Benefits of Increased Use of Energy Efficiency and Renewable Energy Technologies,” Journal of Energy & Environmental Law (2010)

. 12 Hourly emissions and generation data for all fossil fuel

- fired EGUs greater than 25 MW are available from EPA’s Clean Air Markets Division (CAMD) through its Ai r Markets Program Data (AMPD). 13 For example, EIA’s AEO 2013 electricity load growth rates and EGU production trends are available at http://www.eia.gov/forecasts/aeo/assumptions/pdf/0554(2013).pdf. 14 Hawaii and Alaska do not report hourly generation and e mission data from individual EGUs to EPA, and are therefore generally excluded from these forecast tools.12

types, with implicit differentiation of economic outcomes for these different groups. Some of these algorithms may contain subroutines to add new generating capacity automatically to meet load requirements.13

III. Translating from a Rate

- Based Emission Performance Goal to a Mass

- Based Emission Performance Goal
As discussed in the preamble, in section VIII.C.2 , the EPA is proposing that the projected
CO 2 emission performance by affected EGUs (taking into account the qualifying impacts of plan
measures that avoid CO 2 emissions from affected EGUs) must be equivalent to, or better than, the required CO 2 emission performance level in the state plan. This requ ired level of emission performance in the state plan is the rate

- based goal for the state in the emission guidelines, or a
translated mass

- based goal if the state chooses to use this approach. State plans that are projected to achieve an average CO 2 emissi on rate (CO 2 lb/MWh) or tonnage CO 2 emission outcome by all affected EGUs equal to, or lower than, the required level of CO 2 emission performance in the state plan would be considered to meet this pl a n approvability criterion. States may demonstrate
such e mission performance by affected EGUs either by state or jointly on a multi

- state basis.

This section of the TSD discusses the concept of a mass

- based CO 2 emission performance goal, considerations for constructing projection scenarios for such a translatio n, methods for conducting such a translation , and key input assumptions for such a translation

.

A

. Concept

A mass

- based CO 2 emission performance goal translates the application of a rate

- based
emission performance goal to an expected CO 2 emissions outcome in tons during a plan performance period. A mass

- based CO 2 emission performance goal is calculated by projecting
the tons of CO 2 that would be emitted during a state plan performance period (e.g., 2020

- 2029,
2030

- 2032) by affected EGUs in the state if they hypothetically were meeting the state rate

based CO 2 emission performance goal for affected EGUs established in the emission guidelines.
The translation of a rate

- based goal (expressed in lb CO 2 /MWh of useful energy output from
affecte d EGUs) to tons (expressed as total tons of CO 2 emissions from affected EGUs over a specified time period) is based on a projection of affected EGU utilization and dispatch mix

. Importantly, this projection is conducted assuming the absence of qualifying s tate progra ms and
measures contained in a state plan, and applying the rate

- based goal in the emission guidelines as a proxy emission limit for affected EGUs

. State programs and measures in the state plan are not included in this projection
, because the purpose of this analysis is to determine the tonnage CO 214

emissions that corresponds to the state

- specific rate

- based CO 2 emission performance goal for
affected EGUs in the emission guidelines , without the eligible state programs and measures that
are inclu ded in the state plan

.
Translation of a rate goal to a mass goal seeks to answer the question, “What would happen to EGU CO 2 emissions if one applied the rate goals in the emissions guidelines instead of the measures in the state plan?” Because the emiss ion guidelines do not specify the emissions reduction measures that a state must use in its plan, only the level of emission performance that must be achieved through a plan, there is no specified “policy” or set of emission reduction
measures in the emiss ion guidelines to apply when conducting this projection. However, a proxy policy can be applied to project the emission performance in tons that would be achieved if the state plan were to include suitable measures to achieve the required level of emission performance established through the state rate

- based CO 2 emission performance goals in the emission guidelines. This proxy involves applying the rate

- based emission goal for a state as a

rate

- based average CO 2 emission limit for affected EGUs in a state a nd then projecting the CO 2 emissions that would occur if such a limit were applied.

When d emonstrating projected emission performance under a mass

- based plan, a state would project the CO 2 emissions outcome that would be achieved under the suite of requirements, programs , and measures in its plan

. The state plan requirements, programs , and

measures substitut e for EPA’s application of the best system
, which is represented by the rate

based goal in the emission guidelines . If the CO 2 emissions outcome
, in total tons of CO 2 emissions over each plan performance period, is equal to or less than what would be emitted by
affected EGUs through the application of the rate

- based goal in the emission guidelines ( i.e. , equal to or less than the translated mass

- based goal), the plan would be deemed to achieve the required emission performance criterion.15

B

. Projection Scenario s As described above, the projection scenario for translating from a rate

- based CO 2 emission performance goal to a mass

- based CO 2 emission performance goal does not include requirements, programs, and measures included in a state plan. Construction of this scenario must therefore carefully consider treatment of eligible “on

- the

- books” state requirements, programs and measures included in the state plan. 15

Projection scenarios for translating from a rate

- based CO 2 emission performance goal to a

mass

- based CO 2 emission performance goal, and comparing projected emission performance under a state plan to this goal, include the following:

1. A Reference Case Scenario . This scenario projects the average CO 2 emission rate and
CO 2 emissions from affected EGUs in the absence of the EPA emission guidelines or any enforceable requirements, programs, and measures included in a state plan. This scenario does, however, include all current on

- the

- books state requirements, programs, and

me asures that are not included as enforceable measures in a state plan. These measures are complementary to the state plan. Because these measures will influence EGU CO 2 emissions, they should, however, be include d in the reference case projection scenario.
2. A Mass

- Based CO 2 Emission Goal Policy Scenario . This projection scenario is used to
translate a rate

- based goal to a mass

- based goal. The scenario app lies a rate

- based CO 2 emission limit to affected EGUs that is equivalent to the state

- specific rate

- based lb
CO 2 /MWh emission goal in the EPA emission guidelines. 16 The CO 2 emissions from affected EGUs projected during the specified plan performance period in this scenario represents the translated mass

- based CO 2 emission performance goal for the state plan.

15 An “existing measure” refers to a state or utility requirement, program, or measure that is currently “on the books.” For the purposes of this discu ssion, this may include a legal requirement that includes current and future obligations or current programs and measures that are in place and are anticipated to be continued or expanded in the future in accordance with established plans. Existing measure s may have past, current, and future impacts on EGU CO 2 emissions. 16 The proxy emission limit applied includes crediting for end

- use energy efficiency, renewable energy, and nuclear generation included in building blocks three and four, which were used by EPA when calculating the state

- specific CO 2 emission performance goals for affected EGUs in the proposed emission guidelines. In essence, these measures can be used by affected EGUs as “ compliance ” flexibility mechanisms when “complying” with the proxy emi ssion rate limit in this projection scenario. As a result, the proxy rate

- based emission limit is able to capture all four building blocks included by EPA when calculating the rate

- based CO 2 emission performance goals.16

To construct this scenario, t his emission limit is added to the underlying reference case
scenario described above.
3. A State Plan Policy Scenario . This projection scenario includes the enforceable requirements, programs, and measures included in the state pla n , and is used to project
CO 2 emission performance by affected EGUs under the state plan

. To construct this scenario, t he enforceable requiremen ts, programs, and measures included in the state plan

are added to the underlying reference case scenario descri bed above.

An applied example is provided below in Box 1.
Box 1. Example Mass

- Based Goal Translation and Projection of Plan Performance

Example State Rate

- Based CO 2 Emi s sion Performance Goal Assumptions :

 State interim rate

- based CO 2 emission performance goal for affected EGUs: 1,100 lb CO 2 /MWh

 State final rate

- based CO 2 emission performance goal for affected EGUs: 1,000 lb CO 2 /MWh
Reference Case Scenario :

 Under this scenario, the projected average CO 2 emission rate for affected EGUs is 1,500 lb CO 2 /MWh during the 2020

- 2029 interim performance period and 1,500 lb CO 2 /MWh in 2030.

Mass

- Based CO 2 Emission Goal Policy Scenario :

 A proxy emission rate limit is applied to affected EGUs (1,100 lb CO 2 /MWh on average during 2020

- 2029; 1,000 l b CO 2 /MWh in 2030 and subsequent years during the projection period).

 Under this scenario, the projected CO 2 mass emissions from affected EGUs during the 2020

- 2029 interim performance period are 100,000,000 tons of CO 2 (an average of 10,000,000 tons per ye ar during this period) and 9,000,000 tons of CO 2 in 2030.

 The mass

- based interim emission performance goal for affected EGUs is 100,000,000 tons of cumulative CO 2 emissions during the 2020

- 2029 interim plan performance period.

 The mass

- based final emission performance goal for affected EGUs is 9,000,000 tons of CO 2 per year, in 2030 and subsequent years. During plan implementation, this final goal can be met on a three

- year rolling average basis, beginning with the period 2030

- 2032, as discussed in the preamble at section VIII.B.2.c.
State Plan Policy Scenario:

 This scenario includes the suite of requirements, programs, and measures included in the state plan.

 Under this scenario, the projected CO 2 mass emissions from affected EGUs during the 2020

- 2029 interim plan performance period are 98,000,000 tons of CO 2 and 8,800,000 tons of CO 2 in 2030.

 Based on this analysis, the state plan is projected to achieve both the translated interim and final mass

based CO 2 emission performance goals for affected EGUs.

1

. Constructing the Reference Case
A key consideration for translating from a rate

- based CO 2 emission performance goal to a

mass

- based CO 2 emission performance goal is proper construction of a reference case scenario.17

This includes assumptions for key variables that may drive EGU CO 2 emission projections, 17
such as:

 Electricity load growth projections (energy and peak demand)

 Fuel supply, de livery, and pricing assumptions

 Cost and performance of electric generating technologies

 EGU firm builds and retirements ( e.g., those scheduled with a regional transmission organization or independent system operator (RTO/ISO) ) 18

 Transmission capability and ISO/RTO transmission expansion plans

 Applicable federal regulations (other than the EPA emission guidelines)

 Applicable state regulations and programs (othe r than those that are included in the state plan)

It may be necessary in many instances to include assumptions about other state programs implemented by neighboring states in the same region. This would be especially relevant for states that are located within the same electric power pool (or adjoining power pools) that are administered by a common RTO /ISO.

2

. Treatment of Existing State Regulations and Programs in the Reference Case
A key aspect of the reference case is proper treatment of existing state regulations, programs, and measures. As discussed previously, existing state regulations, programs, and measures that are not enforceable measures in a state plan are complementary to the state plan

– as a result, they should be included in the reference case scenario rather than the state plan scenario. These state regulations, programs, and m easures should not , however, be ignored altog ether , as they in fluence EGU CO 2 emissions. Instead , these state actions are occurring in the background

– either when a proxy rate

- based CO 2 emission limit is applied in the Mass

- Based
CO 2 Emission Goal Policy Scenario ; or when the state plan requi rements, programs, and

17 Process considerations related to c onstructing reference case scenarios are addressed in section VI of this TSD. 18 ISOs and RTOs are independent organizations that administer a regional electric power pool (EGU dispatch and electricity transmission systems), and often also administer relate d wholesale electricity markets for electric energy and capacity

.18

measures are applied in the State Plan Policy Scenario

. As a result, these state actions ar e properly addressed in the ref erence case scenario.

In effect, when evaluating whether a state plan w ill meet the mass

- based CO 2 emission performance goal, the two policy scenarios described above , each of which involve adding a
different CO 2 emission reduction policy on top of the reference case scenario, are compared to
one another. If the State P lan Policy S cenario achieves projected tonnage CO 2 emissions equal
to or lower than the projected CO 2 emissions in the Mass

- Based CO 2 Emission Goal Policy
Scenario , then the state plan can be deemed to meet the translated mass

- based CO 2 emission performance go al.

As discussed in the preamble, the EPA is proposing t hat a state may apply toward its required emission performance level the emission reductions that are achieved by existing state requirements, programs , and measures during a plan performance period
, due to actions 19 taken
after the dat e of the proposal of the emission guidelines

. 20 , 21 In practice, this means that emission
reductions that occur in 2020 and later due to actions taken pursuant to an existing state requirement, program, or measure could be applied toward meeting the required level of emission performance in a state plan if these actions occur after proposal of the emission guidelines (e.g

. , as of June 2014 and in subsequent years )

. For example, emission reductions during the initial plan performance period that result from end

- use energy efficiency technologies and measures installed beginning in June 2014 could be applied toward meeting the required level o f emission performance during the plan performance period. These investments might be made to meet requirements under an existing end

- use energy efficiency resource
standard (EERS)

.

19 An “action” as used here refers to an action taken pursuant to a state requirement, program, or measure. For example, the installation of an end

- use energy efficiency measure, such as an e nergy

- efficient refrigerator installed through a utility energy efficiency program to meet the utility’s obligations under a state energy efficiency resource standard (EERS), would constitute an “action” taken pursuant to an existing state requirement.
20 T he preamble also takes comment on alternative dates for eligible actions, including: the start date of the plan period, the date of promulgation of emission guidelines, the end date of the base period for the EPA’s BSER

- based goals analysis (e.g., beginnin g of 2013 for blocks 1

- 3 and beginning of 2017 for block 4, end

- use energy efficiency), the end of 2005, or another date.
21 As discussed in the preamble, at section VIII .F.2.b , the EPA is also proposing that this proposed limitation would not apply to existing renewable energy requirements, programs
, and measures because existing renewable energy generation prior to the date of proposal of the emission guidelines was factored into the stat e

- specific CO 2 goals as part of BSER building block three

.19

Under a rate

- based plan , the approach described above would address the eligibility date
for demand

- side energy efficiency measures that, through MWh savings, avoid CO 2 emissions from affected EGUs. Measures installed after the eligibility date could generate MWh savings during the plan perio d, and related avoided CO 2 emissions, that could be applied toward meeting a required rate

- based emission performance level. Under the proposed option, the eligibility date would be the date of proposal of the emission guidelines. 22

Under a mass

- based plan , the approach described above would be applied when establishing a reference case scenario projection that is used to translate a rate

- based goal to a

mass

- based goal. For example, the assumed amount of energy savings from demand

- side energy
efficienc y measures installed subsequent to the eligibility date that are used to meet an existing
EERS would not be included in the electricity load forecast used in the reference case scenario. Energy efficiency measures installed prior to the eligibility date to meet an existing EERS would be factored into the electricity load forecast used in the reference case scenario. This treatment would represent in the reference case past actions taken under existing state programs and measures that are not eligible for in clusion in a state plan.

22 Although such a limitation is not proposed for RE measures, we also describe here how such a limitation could be applied to RE measures under such an approach. For example, under this approach in the context of a rate

- based plan , new renewable energy generating capacity installed in June 2014 or later to meet an existing, on

- the

- bo oks RPS would be a qualifying measure in a state plan. However, only MWh generation beginning in 2020 and related avoi ded CO 2 emissions could be applied toward meeting a required emission rate performance level in a state plan

. Similarly, under this approach in the context of a mass

- based plan
, the reference case might include the required MWh of renewable energy generation necessary to meet a state RPS as of the date of proposal of the emission guidelines (e.g., as of June 2014). Renewable energy generation that is used to meet a state RPS, but that is incremental to the amount of generation used to meet the exist ing RPS obligation included in the reference case as of June 2014, could be used toward demonstration of CO 2 emission performance under a state plan. This renewable energy generation would be incremental to the renewable energy generation already assumed i n the reference case scenario.20

IV

. Projecting CO 2 Emission Performance under a State Plan

– Overview
As discussed in the preamble, in section VIII.D.4 , one of the required components of a state plan is a projection that a plan will achieve the required level of CO 2 emission performance by affected EGUs that is specified in the plan. (This identified level of performance must be
consistent with either the state

- specific rate

- based CO 2 emission performance goals for affected
EGUs identified in the emission guidelines, or an equivalent translated mass

- based CO 2 emission performance goal.)

This emission projection is based on a scenario that includes the suite of requirements, programs, and measures in the state plan

– the State Plan Policy Scenario described above. Depending on the plan approach, construction of this state plan scenario may be straightforward. For example, if the state plan consists solely of an emission limit, the state plan scenario would apply this emission limit to the underlyin g reference case scenario. O ther types of state plan approaches are more involved , in particular when the use of end

- use energy efficiency and renewable energy re gulations, programs, or measure s are included in a state plan. This could include a state plan that applies a rate

- based CO 2 emission limit that provides credit for end

- use energy efficiency and renewable energy measures that avoided CO 2 emissions, or the inclusion of such measures through a portfolio approach. These types of plans will require inp ut assumptions for the amount of end

- use energy efficiency and renewable energy resource (in MWh over the plan period) that will be realized through implementation of the plan. Utilit y

driven portfolio approaches m ay also include a diverse set of actions t aken directly at affected EGUs that will need to be properly represented in the state plan scenario.

Considerations for developing estimates of energy savings and energy generation that will be achieved through end

- use energy efficiency and renewable ener gy regulations, programs, and measures included in a state plan are discussed below in section VI.21

V

. Applied Considerations for Different Types of State Plans 23
There are a number of considerations for properly representing different state plan approaches in CO 2 emission projection scenarios. This includes both accurate representation of the attributes of state regulations, programs, and measures in the scenario, as well as the methods and data sources used to derive certain input assumptions tha t are used in CO 2 emission projections. This includes:

 Estimating the future effects of end

- use energy efficiency and renewable energy requirements, programs, and measures

 Properly characterizing flexibilities included in emission limits, such as emission budget trading programs

 Properly addressing characteristics of multi

- state regulations and programs

A. End

- Use Energy Efficiency and Renewable Energy
Evaluating the impact of a state end

- use energy efficiency requirement or program included in a state plan, as part of a projection of CO 2 emissions from affected EGUs under a state plan
, involves projections of the impact of the requirement or program on energy and capacity savings, and the impact of this reduction in electricity load and peak demand on EGU dispatch and CO 2 emissions from affected EGUs. 24 This involves projections of the level of current and future energy and capacity savings achieved through program investment or activities in each year, the distribution of those saving s on a daily and seasonal basis (e.g., the load shape of the energy and capacity savings), and the effective useful life of those energy and capacity savings (e.g., the life of installed measures representing the persistence of energy savings). S uch projec tions may also need to address net program energy savings after accounting for potential “free

- ridership,” which involves energy savings that were likely to have occurred in the absence of program incentives, and “spillover,” which involves broader market

23 Different potential state plan approaches are described in detail in the accompanying State Plan Considerations TSD. 24 The evaluation discussed in this section is relevant for state plans that implement a rate

- based CO 2 e mission limit applicable to affected EGUs that provides for adjustment or crediting of the CO 2 emission rate of an affected EGU based on the effects of end

- use energy efficiency and renewable energy. It is also relevant for state plans that take either a r ate

- based or mass

- based portfolio approach. Descriptions of these plan approaches are provided in the accompanying State Plan Considerations TSD.22

transformation impacts that result from the program. These energy efficiency program projections would then be used to adjust electricity load forecasts, as necessary, for modeling runs using an electricity sector dispatch and capacity expansion planning m odel. This modeling would evaluate the impact of the energy and capacity savings on the dispatch of EGUs, construction and retirement of EGUs, and related CO 2 emissions from affected EGUs.

Similar considerations apply for projecting the impact of renewabl e energy requirements and programs included in a state plan on CO 2 emissions from affected EGUs. The renewable

energy generation and generating capacity in a state or region that results from renewable energy requirements, programs, and measures in a state plan will affect EGU dispatch and CO 2 emissions from affected EGUs. This section discusses these considerations in more depth, including approaches and data sources for estimating the impact of end

- use energy efficiency and renewable energy requirements a nd programs as part of state plan projections of CO 2 emission performance by affected EGUs.

1

. Potential Approaches for Estimating the Future Effects of State Energy Efficiency Requirements, Programs, and Measures
There are two basic approaches for developing a ten

- year or longer forecast of end

- use energy efficiency resources that will result from state energy efficiency requirements and programs: a bottom

- up or a top

- down approach. These forecasts would contain data that could be used to develop in puts to EGU CO 2 emission projections in a state plan, using modeling or an EGU growth tool, both of which are summarized above.

A bottom

- up approach is based on annual evaluated and reported data from state and utility energy efficiency programs, and prog ram

- level utility compliance reports under state energy efficiency requirements, such as an end

- use energy efficiency resource standard (EERS). One example of a bottom

- up approach is the state

- by

- state end

- use energy efficiency projection developed by ISO New England for use in its system planning process. 25 In simple terms, ISO

25 Each year, ISO New England produces a Regional System Plan (RSP) that provides a comprehensive assessment of the New England bulk power system that is used as input data for evaluating the future reliability of the grid. One component of the annual RSP is a future estimate of peak loads and annual energy use that is modified (reduced) by the energy efficiency fo recast

. Information about the ISO New England energy efficiency forecasting method and assumptions is included in, ISO

- New England (ISO

- NE) Energy

- Efficiency Forecast Working Group, Draft Final23

New England develops production cost curves for energy efficiency measures based on historical performance of energy efficiency as documented in evaluation, measurement, and verification (EM&V) studies. ISO New England then applies those production cost curves (with adjustments for inflation and other factors) to future state or utility energy efficiency program budgets for each of the six New England states over a ten

- year ho rizon. The ISO New England energy efficiency forecast includes both reductions in annual energy use (MWh) and peak demand (MW)

. ISO New England has produced an energy efficiency forecast for the last three Regional System Plans (2011, 2012, and 2013), and the near

- term estimates in these forecasts have been validated by the actual quantity of end

- use energy efficiency that has qualified for the annual capacity auctions conducted by ISO New England as part of its forward capacity market. Other approaches to projecting energy efficiency impacts, such as those used by New York ISO (NYISO), PJM Interconnection, and the California Public Utilities Commission (CPUC), estimate the effects of energy efficiency requirements and programs over a shorter time frame

. In these cases, energy efficiency projections are typically consistent with the periods for which energy efficiency programs or program budgets have been approved by state PUCs, or consistent with the period for which energy and demand savings are acquired in ISO and RTO forward capacity markets.

Top

- down projection methods analyze aggregate energy use changes resulting from end

use energy efficiency requirements or programs, often for a geographic region, entire industry, or
economic sector. A top

- down appr oach is determined on the basis of state energy efficiency policy requirements, and assumes that utilities and other parties implement efficiency programs necessary to achieve required energy and demand savings. In this way, a top

- down approach is typicall y based on an estimated annual percentage reduction in energy use that results from state energy efficiency requirements and programs. One example of a top

- down approach is the EPA’s

state

- level projection of the impacts of “on

- the

- books” 26 energy requireme nts and programs

. EPA’s approach uses these state requirements and program commitments as the basis for

Energy

- Efficiency Forecast 2018

- 2023 (March 2014), available at: http://www.iso

ne.com/committees/comm_wkgrps/othr/enrgy_effncy_frcst/ 26 As used here, “on the books” refers to state energy

- efficiency requirements and programs currently in place and specified in state legislation or admini strative order

. These requirements include energy efficiency resource standards (EERS) and dedicated sources of energy efficiency program funding.24

adjusting national electricity load forecasts for use in electricity system modeling. 27 In this case, EIA Annual Energy Outlook (AEO) projections of futu re electricity use (MWh) and peak loads (MW) are modified to account for the reduction in energy sales due to state and utility programs and associated energy savings requirements. 28 These energy savings requirements are examined

on a state

- by

- state basis a nd adjusted, as necessary, to reflect known increases or decreases in energy efficiency program budgets and other factors likely to affect whether state energy efficiency requirements are achieved

. In addition to EPA’s projections, a top

- down approach is

u sed to develop EE forecasts by LBNL 29 , NREL 30 , and some state energy offices and
commissions.

The LBNL and the EPA forecast models are useful for comparison with the bottom

- up ISO/RTO approaches. Where discrepancies between the national top

- down analyses o f end

- use energy efficiency savings and the more granular bottom

- up energy efficiency forecasts conducted by ISOs and RTOs exist, review of key assumptions regarding state policies for the different approaches may be warranted. Ideally, using the two appro aches as complementary analyses may provide for helpful comparison and reconciliation of energy savings estimates used in state plan projections of EGU CO 2 emission performance

.
The electricity load forecasts developed by ISOs and RTOs are important because they are often the base case from which adjusted load forecasts that incorporate projected energy efficiency program savings are developed. For reasons described above, ISOs an d RTOs are beginning to include some adjustments to their base case load forecasts to account for energy efficiency program impacts. In most cases, these efforts are focused on including the future anticipated impacts of existing “on the books” energy effi ciency requirements and programs and

27 While EPA’s approach utilizes AEO forecasts of electricity use and peak loads, other credible and long

- te rm forecasts could be used in a similar manner. U.S. EPA, Background and Draft Methodology for Estimating Energy Impacts of EE/RE Policies (March 2014), available at: http://epa.gov/ statelocalclimate/state/statepolicies.html

. 28 For example, annual incremental and cumulative energy savings requirements for utilities included in a state EERS. 29 Lawrence Berkeley National Laboratory (LBNL), The Future of Utility Customer

- Funded Energy E fficiency Programs in the United States: Projected Spending and Savings to 2015 (January 2013), available at: http://emp .lbl.gov/publications/future

- utility

- customer

- funded

- energy

- efficiency

- programs

- united

- states

- projected

spend

. 30 National Renewable Energy Laboratory, State Energy Efficiency Resource Standards: Policy Design, Status, and Impacts (May 2014), available at: http://www.nrel.gov/publications/

.25

adjusting load forecasts accordingly. However, in some cases there is also an effort to anticipate new incremental energy efficiency investments in the future that are not tied to existing energy efficiency requirements and programs. 31 When conducting a projection of EGU CO 2 emission performance as part of a state plan that includes energy efficiency requirements and programs, it will be important to know how the base electricity load forecast for the state or region was developed, whether it already includes the effect of state and utility energy efficiency requirements and programs, and whether and how it should be adjusted to account for the future effects of existing on

- the

- books and incremental (i.e., new) energy effi ciency requirements and programs that are included in the state plan.

1.1 Potential Uses of Energy Efficiency Projections for State Plan Emission Projections
Whether developed through a bottom

- up or top

- down approach, projections of annual energy and peak load reductions that result from state energy efficiency requirements and programs included in a state plan are necessary inputs to projections of EGU CO 2 emission performance under the state plan. Energy and peak demand savings esti mates included in energy efficiency projections are used as a decrement to future electricity load forecasts that are used in conducting EGU CO 2 emission performance projections. The energy efficiency projection is used as an input, or modifier, to various models or other tools used to project the impact of energy efficiency resources on state or regional CO 2 emissions. For example
, capacity expansion and dispatch planning models are capable of incorporating energy efficiency program impact data, such as an nual energy and peak load reductions, when projecting EGU dispatch and capacity additions, and the avoided CO 2 emissions that are projected to result from these requirements and programs

.

31 In N ew England states that have policies to pursue “all cost

- effective energy efficiency,” the ISO

- NE energy efficiency forecast assumes that energy efficiency program investments will continue beyond the approved program funding period (typically documented three

- year plans), either at a constant level or some discounted level based on assumptions about an increase in the cost of saved energy over time.26

1.2 Data Issues and Considerations for Using and Developing Energy Efficiency Projections
Depending on what data sources and approaches are used to project the future energy and demand savings from energy efficiency requirements and programs, there are certain strengths and limitations regarding the approach and methodology used

. Generally, these strengths and limitations relate to data availability and energy efficiency forecast assumptions, such as:

 Energy efficiency requirements and programs included

 Jurisdictions covered

 Planning timeframe

 Embedded energy and demand savings from energy efficiency requirements and programs in base electricity load forecasts

 Cost of saved energy for different energy efficiency measures

 Energy ef

ficiency measure life and measure energy performance decay

 Time of energy and demand savings for energy efficiency measures (availability of hourly data necessary to derive a load reduction profile for an energy efficiency measure)

Bottom

- up versus top

- down forecasting approaches have different strengths and limitations related to the data and assumptions described above

. In the case of bottom

- up approaches, state energy efficiency requirements and programs can be fully addressed in the analysis

. In top

- down approaches, such as EIA AEO analysis, greater focus is placed on federal policies (e.g., codes and standards) but less data is incorporated to reflect state energy efficiency requirements and programs

. Bottom

- up approaches typically include state

- specific data that are rolled up to a regional level, while top

- down national electricity load forecasts do not have a comparable level of granular state data detail

. ISO New England provides energy and demand savings forecasts for state energy efficiency programs (average annual and peak demand coincident with the ISO defined peak load periods)

. The ISO NE energy efficiency forecast is informed by data collected at the energy efficiency measure, individual program, program portfolio, sector, and state leve ls

.27

An important consideration with both top

- down and bottom

- up energy efficiency forecasts is the extent to which energy efficiency program effects have become embedded into the long

- range economic forecasts used as an input in developing electricity lo ad forecasts. In some cases the economic forecast includes the effect of historical energy efficiency policies, either implicitly or explicitly, while in other cases the economic forecast may also anticipate some limited quantity of future energy efficienc y investment that is incremental to the anticipated effect of existing energy efficiency requirements and programs. An additional consideration is whether and how building energy codes and appliance standards (both current and future) are accounted for in the base electricity load forecast.

Another consideration , for all energy efficiency projections, is energy efficiency program spending

. While “on the books” energy efficiency requirements and programs may include
multi

- year approved energy efficiency pr ogram budgets, actual program expenditures may differ

. This has been the case in some of the New England states, for example, where ISO New England has made adjustments to “ discount ” the spending levels to reflect actual spending trends, and not
used the s tate approved budgets identified through stakeholder discussions

. Additionally, assumptions are made about how the overall cost of saved energy for a portfolio of energy efficiency programs will change over time. It is generally assumed in most energy effi ciency projections that the cost of installing energy efficiency measures will become more expensive into the future as state programs move beyond “low

- hanging fruit” and increasingly focus on achieving deeper and broader energy savings through whole

- build ing, multi

- fuel programs addressing new buildings and building retrofits). 32

While many existing sources of energy efficiency projection data do not account for hourly savings, it is becoming increasingly possible for states to examine and incorporate
information about the time dimension of energy efficiency impacts

. Smart meters combined with
data

- sharing and analysis technologies are making it easier for utilities and other energy

32 Evidence to d ate is mixed as to a relationship of larger scale energy efficiency programs and broader energy efficiency measure portfolios, and the associated deeper levels of energy savings, to increasing cost of saved energy. Economies of scale, and expertise gained by program administrators from managing larger programs for multiple years, can lead to cost reductions. However, at some point, as program administrators move away from initial low

cost strategies and end

- use energy efficiency measures, it is assumed that the cost of saved energy will increase.28

efficiency program administrators to more accurately determine how the total energy savings achieved in a calendar year are spread out across the hours of that year

. These data can be applied to energy efficiency projections to provide a better estimate of the timing of energy and demand savings. Such time

- differentiated data is valuable for identifying the marginal EGU or cohort of marginal EGUs that are affected by energy efficiency requirements and programs, which can be used to provide more refined estimates of avoided CO 2 emissions due to changes in EGU dispatch and the a ddition of new generating capacity.

2

. Potential Approaches for Estimating the Future Effects of State Renewable Energy Requirements, Programs, and Measures
This section describes data and analytic considerations for the representation of
renewable energy requirements and programs included in state plans, when conducting projections of EGU CO 2 emission performance that will be achieved under a plan. A range of data and analytic considerations are examined that may be relevant when using different
mod eling approaches, including use of capacity expansion and dispatch planning models, and less sophisticated statistical or top

- down projection approaches. Examples of specific considerations are described for three renewable energy policies that may be used as enforceable measures in a state plan

— renewable portfolio standards (RPS), feed

- in tariffs (FIT), and performance

- based tax incentives.

2.1 Renewable Portfolio Standards
RPS requirements are typically set at the state level with an increasing percentage of total retail sales over a set schedule. The RPS requirement defines the eligible resource types (e.g., wind, solar, etc.) and in some cases, may specify resource

- specific requirements, such as a percentage of the overall RPS target that is se t

- aside for a specific resource. It also defines the allowable geographic boundary for obtaining renewable energy or RECs. With this context, the following issues may be important to consider when projecting the impact of state RPS on EGU
CO 2 emissions.29

2.1.1 RPS as an Input to Electricity Sector Modeling
Electricity sector modeling includes the use of dispatch simulation models and capacity expansion and dispatch planning models that simulate the operation of individual EGUs (or aggregations of EGUs ) in the electric system over time based on a detailed characterization of those EGUs, engineering and market operating constraints, other market factors (e.g., fuel prices, transmission constraints), emission constraints, and the requirement to meet a cer tain level energy and peak demand. These models may be based on a small control area, but more likely are regional or national in scope. Some, such as capacity expansion and dispatch planning models, simulate EGU dispatch and also consider the impact of lo ng

- term generating capacity investment decisions when optimizing system operation and buildout over a long

- term planning
horizon

. These are typically optimization frameworks that have as their objective meeting electricity demand subject to a broad range o f operating, environmental and market constraints, including meeting RPS requirements.

When using these types of analytic tools to project EGU CO 2 emissions, a number of analytic and data considerations are relevant for analysis of RPS impacts on EGU CO 2 emissions. These analytic and data considerations are summarized below.

Translation of RPS Requirements to Renewable Energy Generation Requirements
Most RPS are retail sales

- based requirements, while most electricity sector analytic tools

are generation

- based models. When projecting CO 2 emission performance by affected EGUs using a generation

- based analysis tool, it is necessary to translate the RPS sales

- based requirement to a generation requirement using a transmission and distribution loss r ate to “ gross up” the sales estimate. For example, if an RPS requires 100 MWh of sales be met with eligible renewable energy resources, then the required renewable energy generation necessary to meet the RPS is 100 MWh / (1 + T&D l oss rate). 33

33 According to EIA data, nationally, annual electricity transmission and distribution losses are equivalent to about seven percent of the electricity that is input to the transmission system in the United States

.30

RPS

- Eligible Resources vs. State Plan

- Eligible Resources Some RPS rules define a broad range of eligible renewable energy generating resources. These could include renewable energy EGUs that emit CO 2 , and EGUs that were constructed and began operation rece ntly or many years ago

. Some of these specific EGUs may not be eligible for use in a plan, in particular units that began operation prior to eligibility dates for actions that may be included in a state plan (if such limitations were applied to renewable e nergy measures in

st a te plans )

. 34 Thus, the RPS requirement would need to be adjusted to reflect the use of only those resources eligible for use in state plans. This would be addressed through the treatment of existing RPS in the analysis base case, as des cribed above in section III.B.2.

RPS Vintage Rules Some RPS requirements provide that only renewable energy EGUs that began operation after a certain date are eligible. To the extent these renewable energy EGUs are eligible under a
state RPS but not under the state plan, the analysis should explicitly address these resources. This could be done either through an adjustment of the MWh needed to meet the RPS, to account for renewable energy resources that are not eligible for use in a state plan, or through the use of two modeled RPS requirements for each class of renewable energy resource, with the RPS that addresses resources not eligible in a state plan addressed in the modeling reference case.

In/Out

- of

- State Contribution Some RPS allow some of the requi rement to be met by out

- of

- state resources

. Some modeling frameworks may allow the user to explicitly specify the source region of eligible
renewables

. From a modeling perspective, this means a state would allow a broader supply area
and model a broader ar ea generally. If the renewable energy resources have different characteristics across the relevant geographic area, then data is needed on the characteristics of these resources by region (e.g., resource availability, performance, and capital and productio n

34 As discussed in the preamble, and explained in section III.B.2 of this TSD, EPA is proposing that emission reductions that occur in 2020 and later due to actions taken pursuant to an existing state requirement, program, or measure could be applied toward meeting the required level of emission performance in a state plan if these actions occur after proposal of the emission guidelines (e.g., as of June 2014 and in subsequent years). As discussed in the preamble, at section VIII .F.2.b , the EPA is also proposing that this proposed limitation would not apply to existing renewable energy requirements, programs and measures because existing renewable energy generation prior to the date of proposal of the emission guidelines was factored into the state

- specific CO 2 goals as part of BSER building block three

.31

costs). EIA (for NEMS), EPA (for IPM), and NREL (ReEDS) provide information on the characteristics and performance of renewable energy resources by region. 35

Characteristics of Renewable Resources In a dispatch modeling framework, better emission proje ctions will result when the source of renewable energy is known and the energy profile is modeled. Renewable energy resources, such as wind or solar PV, may differ substantially in generation profile, as the supply of electricity to the grid from the EGU i s based on availability of the renewable energy resource. The time during which electricity generation is supplied will influence the marginal fossil fuel

fired EGU (or cohort of EGUs) that is displaced by renewable energy generation. Understanding
the ren ewable energy resource base, including the energy profile of the relevant renewable energy resource types will improve the modeling of EGU dispatch and projections of avoided
CO 2 emissions that result from renewable energy generation. Data may include a de tailed 8760

- hour energy output profile for renewable energy resources, or at a minimum, a seasonal diurnal profile for such resources. If no state

- specific data is available, generic output profiles for different renewable energy resources are available from NREL. 36

Renewable Energy Resource Availability and Economics Emission projections will be enhanced by a representation of the new renewable energy EGUs that are likely to be brought online as a result of a state RPS, based on an analysis o f available renewable energy resources and economics. This requires understanding the relative economics (e.g., capital costs, fixed operation and maintenance (FOM) costs, variable operation and maintenance (VO&M) costs, and fuel costs) and operating condi tions for different types of renewable energy generators, as well as renewable energy resource availability (e.g., MW

35 EPA’s Integrated Planning Model generation profiles for wind and solar in the EPA IPM v.5.13 base case are available at htt p://www.epa.gov/powersectormodeling/BaseCasev513.html

. 36 NREL’s datasets are intended for use by energy professionals, such as transmission planners, utility planners, project developers, and university researchers who perform wind and solar integration s tudies and need to estimate power production from hypothetical wind and solar plants. The Eastern Wind Dataset ( http://www.nrel.gov/electricity/transmission/eastern_ wind_methodology.html ) contains modeled wind farm data points for the eastern United States for 2004, 2005, and 2006. The Western Wind Dataset ( http://www.nrel.gov/e lectricity/transmission/western_wind_methodology.html ) includes information about the methodology used to develop the dataset, the accuracy of the data, site selection, and power output. The Solar Integration Datasets (http://www.nrel.gov/electricity/transmission/solar_integration_meth odology.html ) are solar photovoltaic (PV) power plant five

- minute and hourly day

- ahead forecasts of generation output for approximately 6,000 simulated PV plants in the United States for the year 2006.32

capacity available at different wind classes, solar insolation levels, and the characteristics of biomass). Having this information allows for better projections of the level and quality of renewable resources likely to be brought forward as the result of a state RPS

. This will result in better emissions projections.

NREL has a suite of tools that can be used to estimate the potential costs of renewable energy under various assumptions. 37 For example, the CREST model is a cost

- of

- energy analysis tool intended to assist policy makers evaluating the appropriate payment rate for a cost

- based renewable energy incentive policy. The model aims to d etermine the cost

- of

- energy, or minimum revenue per unit of production, needed for a sample (modeled) renewable energy project to meet its investors' assumed minimum required after

- tax rate of return. 38

Retail Rate Impacts Many state RPSs have cost containment mechanisms or effective caps on the allowable impact on retail rates or on customer bills that can result from implementation of an RPS. If these caps are triggered, it will delay further increases in the RPS targets, depending on RPS impl ementation rules. This would lower estimates of renewable energy generation needed to satisfy the RPS requirements

. Likewise, to limit rate impacts, many state RPS include an alternative compliance payment (ACP) provision
, which requires obligated entities to pay a predetermined fee to the state for each MWh of RPS shortfall. Although these ACP payments may be directed to programs to promote the deployment of renewable energy technologies, these payments are not equivalent to renewable energy generation and should not be accounted as such.

37 NREL's Energy Analysis web site ( http://www.nrel.gov/analysis/models_tools.html ) has links to tools such as the Cost of Renewable Energy Spreadsheet Tool (CREST) and the System Advisor Model (SAM). CREST (https://financere.nrel.gov/finance/cont ent/crest

- cost

- energy

- models) makes performance predictions and cost of energy estimates for grid

- connected power projects based on system design parameters that the user specifies. The SAM cash flow model (http://sam.nrel.gov/) helps assess solar, wind, o r geothermal projects, design cost

- based incentives, and evaluate the impact of tax incentives or other support structures on renewable energy projects. 38 The CREST model is a product of a 2009

- 2010 partnership between the National Renewable Energy Laborat ory (NREL), the U.S. Department of Energy (DOE) Solar Energy Technologies Program (SETP), and the National Association of Regulatory Utility Commissioners (NARUC). The model was developed by Sustainable Energy Advantage (SEA) under the direction of NREL. T he report, user manual, and CREST models are free and available for download at: https://financere.nrel.gov/finance/content/crest

- cost

- energy

- models.33

Market Impacts

– Multiple State Players One important issue is to account for actions of others. Modeling results that consider the
RPS

- related actions of other states could differ substantially from those that consider a state’s actions in isolation. This requires having at least a regional, if not national, modeling framework

. A broader framework captures competition for renewables (and increased prices, greater reliance on poorer resources), as well as market

- wide imp acts on EGU dispatch and capacity expansion.

2.1.2 Data Needs for Estimating Generation Resulting from State RPS
Projections of renewable energy generation will require assembling the following data:

 Resource availability, resource performance, and resource costs will be necessary for the more sophisticated modeling approaches described above.

 Projections of retail sales, by year, adjusted to account for any exclusions from the RPS obligation (e.g. small utilities, cooperatives, municipalities, or pe rhaps certain large industrial loads)

. These covered sales must be calculated and projected using forecasts of
annual retail demand.

 RPS requirements by year, so the annual forecast of covered retail sales can be multiplied by these percentages.

 The exte nt to which credit multipliers are used for compliance. Credit multipliers reduce the number of MWh needed for RPS compliance, and a downward adjustment should be made based on the percentage of compliance achieved by credit multipliers.

 Representation of alternative compliance payment (ACP) provisions, if applicable, and other relevant compliance flexibility provisions provided through the RPS.

 Estimates of transmission and distribution (T&D) losses, so that retail sales can be “grossed up” as described a bove. T&D losses estimates are available at the national level and can also be obtained for various grid regions from the appropriate regional grid operator.

 If an electricity sector capacity expansion and dispatch planning model is not used,
estimates of the geographic origin, by state and grid

- region, of generation used to satisfy the RPS will be necessary. If generation to satisfy the RPS is expected to come from out of state, the basis for these assumptions should be documented.34

 CO 2 emission rate associated with renewable energy generation, by resource type (if applicable).

 Generation profile, by renewable energy resource type

2.2 Feed

- in Tariff and Other Performance

- Based Incentives

A feed

- in

- tariff (FIT) is a performance

- based i ncentive (similar to production tax credits) that typically guarantees utility customers who own a eligible renewable electricity generation system (e.g., roof

- top solar PV system) will be paid a specific amount by their utility for the electricity the sys tem generates and provides to the grid over a fixed period of time. Such tariffs usually offer a fixed payment amount per kWh, but variations may require competitive bids. In some cases, FIT payments may be in addition to other incentives (suc h as a produc tion tax credit). With a FIT, the amount of renewable energy that will be generated is not specified in the tariff schedule. A similar uncertainty about the amount of renewable energy generation that will occur exists for production

- based tax credits. In t he case of an RPS, the amount of renewable energy generation necessary to meet the RPS is known given the required RPS level and a utility sales projection. 39 In the case of FITs the response to the program may be more uncertain. The remainder of the discussion focuses on estimating these impacts

.
The key information required to estimate the generation that will occur as a result of a
FIT include s :

 An estimate of the renewable energy generation that will be provided by year for the FIT, along with estimates of payments to be made. These should capture the impacts of interactions with other policies, including RPS requirements, net metering, and feder al investment and production tax credits. If generators receiving FIT payments are also eligible to satisfy an RPS, states should ensure their estimates of renewable electricity generation are not double

- counted. For analysis using a detailed capacity expa nsion and dispatch planning model, market penetration of renewable energy generation to meet an RPS may be an output of the model. In this case, information is required on the capital

39 Most state RPS schedules are established as a percentage of utility sales in a given year, although some include specified MWh amounts or are based on MW of generating capacity.35

costs, FOM costs, and VOM costs of the renewable energy generating techn ology. This is the same information required for modeling an RPS; however, the modeling or analysis mechanism may differ. For example, these costs may be reduced directly in a modeling framework to reflect the FIT payment (e.g., reducing VOM to reflect the FIT in the years it is available).

 Information on the types of renewable energy resources, including their location, output levels, energy output profiles ( across all 8 , 760 hours of the year or seasonally), and operating life of the EGU (by technology, so that they can be included in an electric dispatch model or mapped to an appropriate load shape or marginal avoided emission rate if using simpler analytical methods.

 An estimate of whether the projected retail price impacts of the FIT will lead to loweri ng the amount paid to eligible renewable energy generators, if a FIT includes caps on generation subject to the tariff based on rate impacts

. If retail electricity rate impacts or budgetary impacts become unsustainable, the projected generation resulting f rom the FIT
will be overstated

.
2.2.1 Data Needs for Estimating Generation Resulting from Feed

- In Tariff and Performance

- Based Tax Incentives
Projections of renewable generation that will occur as the result of FITs and other performance

- based incentives will require assembling the following data about the specific incentive programs that will support renewable energy generation:

 Caps on generating capacity, if any, by year, because such caps will limit the amount of
renewable energy generation resulting from the tariff or tax incentive.

 Capacity amounts by renewable energy resource type that will be subject to a FIT or other performance

- based incentives, and the capacity factors for these resource types, so that total generat ion in MWh can be calculated.

 Payment levels per kWh or MWh for each year of the FIT or other production

- based
incentive.

 Budget amounts, if known, by year, which may be expended to support renewable generation. When divided by the incentive payment level s, on a per

- kWh or per

- MWh36

basis, these budget amounts will yield an estimate of the total electric generation that will be supported by the FIT or other production

- based incentive.

 State experience and trends with FITs and other production

- based incentiv es. Lacking budget or capacity limits, prior experience in the state, or the experience of other states and utilities, normalized for state or utility size, could be the basis for estimated renewable energy generation at a given incentive level.

 Because pe rformance is metered at the busbar (i.e., the point of interconnection to the electricity transmission or distribution system), no adjustments would be needed for T&D
losses.

 Estimates of the geographic origin, by state, of generation that receives support from these programs. In most cases, eligible generation will be in

- state, but if generation is expected to come from out of state, the basis for these assumptions should be
documented.

 CO 2 emission of renewable energy generation, by resource type (if appl icable).

B. Emission Budget Trading Programs
Emission budget trading programs establish an emission limit for a group of emission sources and establish a budget of tradable emission allowances equal to the emission constraint for the group of sources. An emission allowance typically represents a limited authorization to emit one ton of a regulated pollutant. These programs also typ ically include a number of additional flexibility mechanisms beyond the ability to trade allowances. These include multi

year compliance periods, the ability to bank allow ances issued in a previous compliance period
for use in a subsequent compliance period, the use of out

- of

- sector project

- based emission offsets, and cost

- containment allowance reserves that make addit ional allowances available to the market if pre

- established allowance price thresholds are achieved. 40 As a result, annual emissions from affected sources subject to an emission budget trading program often differ from the established annual emission budget for affected sources. In addition, these programs may be
multi

- sector in nature, regulating emissions for source categories in addition to EGUs. As a

40 Depending on the program, these cost containment allowance reserves make ad ditional allowances available from within the base emission budget (i.e., from “within the emission cap”), or add to the base emission budget (i.e., increase the emission cap).37

result, state plan emission projections will need to accurately account for and represent these complianc e flexibilities , as well as the scope of affected sources if they are broader than EGUs affected under CAA section 111(d)

. 41 In general, most electricity sector capacity expansion and dispatch planning models can be configured to evaluate these program flex ibilities and project
CO 2 emissions from affected sources, considering these compliance flexibilities.

1. Addressing the Sectoral Scope of Emission Budget Trading Programs
Some existing state emission budget trading programs addressing GHG emissions regulate emission sources in addition to EGUs, such as industrial sources. 42 We refer to these
here as multi

- sector emission budget trading programs. All existing state emission budget trading programs addressing GHG emissions include out

- of

- sector project

- based emission offsets, which may be used to cover a portion of the compliance obligation of affected sources.

For multi

- sector emissions budget trading programs, state plan emission projections would need to evaluate projected CO 2 emissions across all so urce categories covered by the state
or multi

- state program. This would be necessary to project the CO 2 emissions performance of
affected EGUs under the multi

- sector emissions budget trading program.

For emission budget trading programs that regulate EGU s and include offsets, which we define here as emissions reductions from sources not regulated by the trading program, emissions reductions from offsets would not be counted when evaluating CO 2 emission performance of affected EGUs, because those reduction s would not come from those affected EGUs. However, state plan emissions projections would need to evaluate the use and impact of offsets, because the availability of offsets would affect the amount of CO 2 emissions from affected EGUs.

Addressing Multi

- Se ctor Emission Trading A state or regional emission budget trading program could potentially regulate sources from multiple emissions sectors beyond the electric generating sector that is the focus of the EPA emission guidelines. For example, the Californ ia GHG emission budget trading program is a

41 For example, the Regional Greenhouse Gas Initiative (RGGI), which is an emiss ion budget trading program limited to EGUs, includes EGUs that are not subject to CAA section 111(d). 42 The California GHG emission trading program also includes large industrial sources and as of 2015 will include distributors of transportation, natural g as, and other fuels.38

multi

- s ector emissions trading program that address emission sources outside the scope of the EPA emission guidelines for E GUs. If a multi

- sector emission budget trading program is
include d in a state plan, CO 2 emi ssion projections provided as part of the state plan will need to evaluate projected CO 2 emissions across all covered emissions sectors under the program. This would be necessary to project the CO 2 emissions or weighted average CO 2 emission rate of
affecte d EGUs that will be achieved under the multi

- sector emission budget trading program included in the state plan

.
Evaluating the projected im pact of a multi

- sector emission budget trading program on the
CO 2 emission pe rformance of affected EGUs introduce s an additional level of analytical complexity to emissions projections . For example, additional modeling capabilities may be necessary to adequately evaluate CO 2 emission performance across sec tors in a multi

- sector emission budget trading program.

Adequa tely p rojecting the CO 2 emissions of affected EGUs subject to a multi

- sector emissio ns budget trading program may require modeling using a multi

- s ector energy model

. 43 The use of an electricity sector dispatch and capacity expan sion planning model , might also be required, as a complement to a multi

- sector mod el. Some multi

- sector models , include an electricity sector dispatch and capacit y expansion planning module . However, use of a stand

alone elect ricity sector model , might also be necessary as a supplem ent to a multi

- sector energy model, in order to project CO 2 emissions or the weighted average CO 2 emission rate from
affected EGUs at a sufficient level of resol ution for state plan emission projections

. Under this approach, a multi

- sector energy model mig ht be used to project the level of CO 2 emissions
abatement achiev ed across the multiple emission sectors covered by the program. This multi

sector projection could be us e d to develop a CO 2 marginal abatement cost curve representing

cost

- effective, non

- elec tricity sector emission reduction opportunities at increasing cost levels. The marginal abatement cost curve would then serve as an input assumption for the electricity sector capacity expansion and dispatch planning model, which would be used to project t he CO 2

43 For example, the Energy 2020 model was used by California to evaluate the impacts of its multi

- sector GHG emissions budget trading program. Other multi

- sector models are available with similar capabilities, such as the National Ener gy Modeling System (NEMS) developed and implemented by the U.S. Energy Information Administration (EIA).39

emission performance of affected EGUs (e.g., the CO 2 emissions or CO 2 emission rate of individual affected EGUs, or the total CO 2 emissions or weighted average CO 2 emission rate across multiple affected EGUs). 44

Multi

- sector emission budget trading programs also often address GHGs beyond CO 2 . If this is the case, emission projections in a state plan would need to account for emissions abatement opportunities for each of the GHGs regulated under the program, and project
emissions reductions for each o f the regulated GHGs. This would be necessary to project the
extent to which affected emission sources in different industrial sectors reduce emissions of non

CO 2 GHGs, which could impact projected CO 2 emissions from affected EGUs.

Addressing Emission Of

fsets
Emission offsets in CO 2 or GHG emission budget trading programs represent project

based GHG emissions reductions outside the sector or sectors regulated by the program. 45 Emissions reductions achieved through eligible offset projects are awarded allowances or “credits” that may be used by an affected source to meet a portion of its allowance compliance obligation. For example, under the RGGI program “CO 2 offset allowances” awarded for GHG emissions reductions achieved through approved offset projects may be used by affected sources to meet up to 3.3 percent of their CO 2 allowance compliance obligation. 46

.
The ability to use GHG emission offsets for compliance means that CO 2 emissions from
EG Us regulated under the emission budget trading program may exceed the base CO 2 emissions budget established for the program. Offset allowances or credits are awarded in addition to the existing CO 2 emission budget, in exchange for CO 2 - equivalent emissions reductions achieved

44 This marginal abatement cost curve would be applied in a similar manner as marginal abatement cost curves are applied for GHG emission offsets in mod eling analyses of emission budget trading programs. Form a modeling perspective, emission reductions from other sectors could be used by affected EGUs to demonstrate compliance with the emission limit. When economic to do so, emission reductions from affec ted EGUs would be foregone and replaced by emission reductions from emission sources in other sectors that are also subject to the multi

- sector emission budget trading program. 45 “Offsets” as used in the context of CO 2 or GHG emissions budget trading progr ams are distinct from offsets in the NSR permitting context under the CAA, where in certain instances emissions of a criteria pollutant from a proposed new facility must be offset with creditable emissions reductions at an existing facility, if the state o r jurisdiction where the proposed facility would be located is in non

- attainment status for the pollutant. 46 This percentage increases to five and ten percent of a CO 2 allowance compliance obligation at specified $7 and $10 price triggers, respectively.40

outside the capped emissions sector. 47 Consequently, the use of offsets by affected sources to meet a portion of their complian ce obligation under an emission budget trading program could result in higher projected C O 2 emissions from affected EGUs in a state plan, because the use of offsets functionally expands the CO 2 emission budget for affected EGUs. This allows affected
EGUs to emit more CO 2 while meeting their complianc e obligation under the emission budget
tradi ng program, in exchange for CO 2 - eq uivalent emissions reductions achieved outside of the affected source category. As a result, to properly project the CO 2 emissions from affected EGUs in a state plan that includes an emissions budget trading program that a llows for the use of offsets, it is necessary for modeling to also project the extent to which offsets are used by affected EGUs for compliance. 48

Under this approach, state plans would ignore the CO 2 - equivalent emissions reductions projected to be achieved through offsets, when projecting the CO 2 emissions performance that will be achieved by the affected EGU source category through implementation of the state plan

. This does not mean that an e mission budget tra ding program included in a state plan could not
include an offset component. Rather , when demonstrating emission performance by affected
EGUs , the projected CO 2 emissions or weighted average CO 2 emission rate for affected EGUs
under the state plan would no t incorporate a credit for the CO 2 - equivalent emissions reductions represented by offset allowances or credits used by affected EGUs for compliance with the emission budget trading program

. 49

2 . Multi

- State Emission Trading Programs
Emission budget trading programs may be multi

- state in nature. For such programs, emissions reductions are achieved on a regional, rather than a state

- by

- state basis.

47 A key criterion that must be met for the award of offset allowances or credits is a demonstration that the offset project is “additional” (i.e., that it would not have occurred absent the incentive provided through the award of the offset allowance or cred it). 48 Existing capacity expansion and dispatch planning models can project the use of offsets for compliance based on specified offset marginal abatement supply curves, which represent the amount of offset credits/allowances assumed to be available from different categories of offset projects at different GHG emissions abatement costs. 49 In other words, the projected CO 2 emissions or weighted average CO 2 emission rate for affected EGUs would be based on the direct emissions from these EGUs alone, with no calculation of “net” EGU CO 2 emissions that factor in the CO 2 - eq uivalent emissions reductions represented by offset credits or allowances used by an EGU to meet a portion of its compliance obligation.41

For example, in the multi

- state Regional Greenhouse Gas Initiative (RGGI) emission budget trading progra m, individual participating states have established CO 2 emission budgets in state regulations. However, there is no requirement limiting total CO 2 emissions from affected sources in an individual state. State regulations include reciprocity provisions allo wing emission
sources to use CO 2 allowances issued by another participating state for compliance with the state program. This provides for state

- to

- state CO 2 allowance flows (and the potential for differences
in state

- by

- state CO 2 emissions relative to sta te emissions budgets) based on where emission

sources determine it is most economical to achieve CO 2 emissions reductions. However, in aggregate, the CO 2 emission budgets in each of the participating state regulations establish a regional cap on CO 2 emissi ons from affected EGUs. As a result, while a multi

- state emission budget trading program may be projected to result in CO 2 emissions from affected EGUs
consistent with a multi

- state mass

- based CO 2 emission performance goal, the CO 2 emissions outcomes may v ary by state. This necessitates evaluating a multi

- state emission budget trading program as a whole, because the individual regulations of participating states function together as single integrated program.

To address these issues, states participating i n a multi

- state emission budget trading program would jointly demonstrate that the multi

- state program is achieving the required level of
CO 2 emission performance on a multi

- state basis, based on the CO 2 emission performance of all
affected EGUs in the mul ti

- state group implementing the program.

Some state emission budget trading programs also include international partner jurisdictions

. 50 In such instances, the program could be treated in a similar fashion as a multi

state program that involves only U. S. states. In this instance, emission projections evaluating an international program would include all jurisdictions participating in the pr ogram, but emission performance for state plans would be assessed based only on the CO 2 emission performance of
affect ed EGUs in the subset of the program represented by U.S. states. Although the CO 2 emission perform ance of EGUs (or other emission sources) in a foreign country would not be addressed in the state plan , the entire intern ational program would be evaluated as part of the

50 Currently, the EPA is only aware of one such instance , which is the linkage of the California GHG emission budget trading program with a similar program in Quebec.42

emission projection included in the state plan. This would be necessary in order to project
international allowance flows and CO 2 emissions across all participating jurisdictions, as these

cross

- jurisdictional flows would impact projected CO 2 emissions from affected EGUs in U.S.

states.43

VI

. Process Considerations
As discussed in the preamble, in section VIII.F. 7, t he credibility of state plans under section 111(d) will depend in large part on ensuring credible and consistent emission performance projections in state plans. Therefore, the use of appropriate methods, tools, and assumptions for such projections is critical. Furthermore, c onsiderations for projecting emission performance under a st ate plan will differ depending on the type of plan. This includes differences in how inputs to projections are derived; how projections are conducted, in cluding tools and methods; and how aspects of a plan are represented in these projections.

In the pre amble, the EPA seeks comment on whether the EPA should develop guidance that describes acceptable projection approaches, tools, and methods for use in an approvable plan, as well as provide technical resources for conducting projections. This section of th e TSD
elaborates on these considerations.

A . Provision of the EPA Guidance
One approach to address these considerations is for the EPA to provide guidance for
EGU CO 2 emission projections included in state plans. Such guidance could include default modeling assumptions, or data sources for key assumptions. State modeling projections included in a state plan could include assumptions that deviate from the EPA’s recommen ded default assumptions, but a state plan would justify the reason for using alternative assumptions. The EPA technical guidance could specify recommended reference case assumptions for use with modeling or EGU utilization growth tools, for example:

 Elect ricity load growth projections (energy and peak demand)

 Fuel supply, delivery, and pricing assumptions

 Cost and performance of electric generating technologies

 Cost and performance of pollution control equipment44

 EGU firm builds and retirements (those scheduled with a regional transmission organization or independent system operator (RTO/ISO) 51

 Transmission capability and ISO/RTO transmission expansion plans

 Applicable federal regulations (other than the EPA emission guidelines)

 Applicable state regulati ons and programs (other than the alternative standards that are included in the state plan)

It would be necessary in many instances to include assumptions about other state programs implemented by neighboring states in the same region. This would be espec ially relevant for states that are located within the same electric power pool (or adjoining power pools) that are administered by a common RTO/ISO. To address this need, the EPA technical guidance could provide documentation of state programs and policies included in a reference case, as well as those that are eligible for inclusion in a state plan as alternative standards. The guidance could compile information about state programs and provide model input assumptions related to these programs (e.g., MWh o f electric generation needed to meet a state renewable portfolio standard). 52 The EPA might also play a role in facilitating coordination among states as they develop their plans, to harmonize regional assumptions.

ISOs and RTOs, in discussions with the EP A have also offered to support states in evaluating the emission performance of state plans on a regional basis. The ISO/RTO Council, an organization of electric grid operators, has suggested that ISOs and RTOs could provide analytic support to help states develop and implement their plans. The ISOs and RTOs have the capability to model the system

- wide effects of individual state plans. Providing assistance in this way, they felt, would allow states with borders that fall within an RTO or ISO footprint to a ssess the system

- wide impacts of potential state plan approaches. In addition, as the state implements

51 ISOs and RTOs are independent organizations that administer a regional electric power pool (EGU dispatch and electricity transmission systems), and often also administer related wholesale electricity markets for electric energy and capacity. 52 EPA’s manual, Roadmap for Incorporating Energy Efficiency/Renewable Energy Policies and Programs into State Implementation Plans/Tribal Implementation Plan s (July 2012), could potentially support and be expanded upon to develop this component of EPA technical modeling guidance. In particular, see Appendix I: EPA’s Draft Methodology for Estimating Energy Impacts of EE/RE Policies. The draft manual is availabl e at http://www.epa.gov/airquality/eere.html . State environmental regulations addressing EGUs are itemized in the modeling documentation for the EPA IPM Base Case v.5.13.45

its plan, ISO/RTO analytic support would allow the state to monitor the effects of its plan on the regional electricity system. ISO/RTO analytic capabili ty could help states assure that their plans are consistent with region

- wide system reliability. The ISO/RTO Council suggested that the EPA ask states to consult with the applicable ISO/RTO in developing their state plans

.
B. Party that T ranslates the Rate

- Based G oal to a Mass

- Based G oal
In the preamble, in section VIII.F.7, The EPA seeks comment on whether it should develop guidance that describes acceptable projection approaches, tools, and methods for use in an approvable plan, as well as provide te chnical resources for conducting projections.

One consideration for state plans that use a mass

- based CO 2 emis sion performance goal is the party that conducts the translatio n of the rate

- based CO 2 emission performance goal in the emission guidelines to a mass

- based goal

— either the EPA or the state. In the preamble, in
section VIII.D.3, t he EPA seeks comment on whether to assist states that seek to translate the

rate

- based goal into a mass

- based goa l

.

One approach is for the EPA to provide a presumptive translation of the state

- specific

rate

- based CO 2 emission performance goal to an equivalent mass

- based goal for all states, for
those states that request it, and/ or for multi

- s tate regions. This cou ld include default modeling assumptions and results of modeling runs for a Reference Case S cenario and an EPA Mass

Based CO 2 Emission Goal Policy Scenario , as described above in section III.B

. A state could
utiliz e the presumptive mass

- based CO 2 emission performance goal for the state or multi

- state region identified through these EPA modeling runs

. If a state proposed modifications to EPA default modeling a ssumptions, it would need to justify these modifications as part of the CO2 emission proje ction included in its state plan, a nd present an emission projection that supports a proposed modified mass

- based CO 2 emission performance goal

.
Another approach is for the EPA to provide guidance for states to use in translating a

rate

- based goal to a mass

- based goal. This could include information about acceptable analytical methods and tools, as well as default input assumptions for key parameters that will likely influence proje ctions, such as electricity load forecasts and projected fossil fuel prices. Under this approach, the EPA might also provide a coordinating function in addressing the assumptions46

applied by multiple states within a grid region, acknowledging that assumptio ns about state programs across a broader grid region that are included in an analysis scenario will influence projections of CO 2 emissions by affected EGUs in any particular state.

Under this approach, states could deviate from these default methods and assumptions with justification. Following the guidance could provide a streamlined path for the EPA approval of emissions projections, but states would still have flexibility to use other approaches, which the
EPA would review.Technical Support Document (TSD) for Carbon Pollution Guidelines for Existing Power Plants: Emission Guidelines for Greenhouse Gas Emissions from Existing Stationary Sources: Electric Utility Generating Units
Docket ID No. EPA-HQ-OAR-2013-0602



# Projecting EGU CO 2 

# Emission Performance in State Plans

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

June 20142 Table of Contents

I. Introduction .................................................................................................................. ......3 II. Analytic Approaches for Projecting CO 2 Emissions from Affected EGUs ..................6 A. Electricity System Modeling Approaches for Projecting EGU CO 2 Emissions .......6 B. Growth Tools for Projecti ng Future EGU Utilization and CO 2 Emissions.............10 III. Translating from a Rate-Based Emission Performance Goal to a Mass-Based Emission Performance Goal ............................................................................................13 A. Concept ...................................................................................................................1 3 B. Projection Scenarios ................................................................................................15 IV. Projecting CO 2 Emission Performance under a State Plan – Overview .....................20 V. Applied Considerations for Different Types of State Plans .........................................21 A. End-Use Energy Efficien cy and Renewable Energy .............................................21 B. Emission Budget Trading Programs ......................................................................36 VI. Process Considerations ....................................................................................................43 A. Provision of the EPA Guidance .............................................................................43 B. Party that Translates the Rate-B ased Goal to a Mass-Based Goal ........................453 I. Introduction
As discussed in the preamble, in section VIII. F.7, all state plans will need to include a projection of the CO 2 emission performance by affected EGUs that will be achieved under a state plan (inclusive of plan measures that avoid CO 2 emissions from affected EGUs, such as end-use energy efficiency and renewable energy). Depending on the type of plan approach, this will include either a projection of the average CO 2 emission rate achieved by affected EGUs or total
CO 2 emissions from affected EGUs.

The EPA is also proposing that a state may translate the state rate-based CO 2 emission performance goal for affected EGUs to an equivalent mass-based CO 2 emission performance goal. If this translation option is used, a state pl an must also include a projection used to derive
the mass-based CO 2 emission performance goal. This translation will involve a projection of CO 2 emissions from affected EGUs during the in itial 2020-2029 plan performance period and in 2030, under a scenario that assumes the rate-bas ed goal in the emission guidelines is met.

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

The preamble, at section VIII.F.7, seeks comment on options presented for how CO 2 emission projections might be conducted in an a pprovable state plan, and how different types of state plan approaches are represented in thes e projections. These opti ons include the use of historical data and parameters for estimating th e future impact of individual state programs and measures. Alternatively, a projection could be based on modeling, such as use of a capacity expansion and dispatch planning mode l, or a dispatch simulation model. 1 This latter approach would be able to capture dynamic interactions within the electricity sector, based on system

1 In many cases, this approach will also require the developm ent of parameters for estimating the effect of individual state programs and measures, for use as input assumptions for modeling.4 operation and market forces, including interact ions among state programs and measures and the dynamics of market-based measures.

In the preamble, the EPA further seeks co mment on whether the EPA should develop guidance that describes acceptable projection ap proaches, tools, and methods for use in an approvable plan, as well as wh ether the EPA should provide t echnical resources for conducting projections.

This technical support document (TSD) elabor ates these options and considerations. The TSD discusses possible analytic approaches for translating from a rate-based CO 2 emission performance goal to a mass-base d goal, and projecting the CO 2 emission performance that will be achieved through a state plan. It discusses both modeling and non-modeling approaches, such as electricity sector capacity expansion and dispatch planning models, dispatch simulation models, and growth tools that ba se projections on historical data and algorithms. The TSD also discusses possible approaches fo r developing inputs that are us ed for emission projections and applied considerations for di fferent types of state plans. Topics addressed include:

 Section II discusses analytic approaches for projecting CO 2 emissions from affected
EGUs

 Section III discusses the concept and practice of translating from a rate-based CO 2 emission performance goal to a mass-based CO 2 emission performance goal

 Section IV discusses the concept and pr actice of projecting EGU CO 2 emission performance under a state plan

 Section V discusses applied considerations for projecting EGU CO 2 emission performance under different type s of state plans, including:

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

o Data needs and methods for developing inputs to EGU CO 2 emission projections, for different types of state plans

 Section VI discusses process considerations for conducting EGU CO 2 emission projections for state plans, including:

o Regional coordination among states in conducting projections5 o Whether the EPA should provide guidance and other analytic support for conducting projections in state plans and translation of rate-based CO 2 emission performance goals to mass-based goals6 II. Analytic Approaches for Projecting CO 2 Emissions from Affected EGUs
This section surveys different types of methods and tools for projecting CO 2 emissions from affected EGUs, including modeling tools and ot her tools that base pr ojections on historical data and use algorithms to extrapolate future CO 2 emissions performance based on past performance.

A. Electricity System Modeling Approaches for Projecting EGU CO 2 Emissions
1. National-scale capacity expansion and dispatch planning models
National-scale electricity capacity expansion and dispatch planning models are typically used for fundamentals-based projections of the pow er sector (i.e., projections of the expected response of the sector to factors such as electricity de mand, fuel prices, and emission constraints) that may extend over a period of several decades. These models are built to evaluate the impacts of market, technical, and regulat ory factors on the electric powe r sector and related markets. Typical outputs of such models include EGU dispatch, fuel cons umption, fuel prices, wholesale electricity prices, emissions, EGU retirements, and infrastructure expenditures (e.g., addition of new EGU capacity and installation of re trofit pollution cont rol technologies).

National-scale electricity capacity expans ion and dispatch planning models have moderate spatial detail with broad scope, ge nerally encompassing the entire country or transmission system interconnects (i.e. Easter n, Western, and ERCOT), which are subdivided into smaller areas, such as balanc ing authorities or control areas. 2 For computational efficiency, these models generally model several representativ e hours of the year, or aggregate hours into representative bundles with simila r electricity demand profiles (i.e . peak, shoulder, off-peak). In these models, to reduce model size, existing EGUs may be aggregated into “model plants” to the
extent that such EGUs share ke y unit characteristics, such as location, size, efficiency, operating costs, pollution retrofit control status, age, and fu el type use/availabilit y. These types of models are well suited to project dynamic entry and exit ( capacity expansion and un it retirement) to meet energy and capacity requirements while minimizing system costs, maintaining reliability criteria,

2 A “balancing area” or “control area” refers to a specifi ed portion of the transmissi on system where electricity demand and generation are balanced in real time by a system administrator to maintain grid reliability.7 and following other constraints, such as mini mum build times, transmission constraints, renewable energy availabilit y, or emission limitations.

2. Utility-Scale Capacity Expansion and Dispatch Planning Models
Utility-scale capacity expansion and dispatch planning models are similar in concept to
related national-scale models. Ho wever, utility-scale capacity e xpansion and dispatch planning models are typically used for evaluating narrower utility planning and investment decisions, such as procurement of a specific new electric generating facility and re tirement or retrofit decisions for existing capacity within a specific utility’s te rritory. Utility planning models typically project outcomes for periods of up to two decades. Ut ility-scale capacity expansion and dispatch planning models are an industry standard, used regularly in state el ectricity regulatory proceedings. Within the electricity sector there is broad familiarity with these models at state PUCs. Multiple vertically integrated utilitie s use capacity expansion and dispatch planning models to conduct forward planning and revi ew the economics of specific EGU retrofit decisions. Utilities that submit integrated res ource plans (IRP) typically use a utility-scale capacity expansion and dispatch planning model to examine long-term strategies and develop short-term action plans. 3 Utilities have experience using these models to examine CO 2 emission reduction strategies or CO 2 emission constraints, as IRP scenarios may include greater penetration of end-use energy effici ency or renewable energy, proxy CO 2 emission prices, emission trading, and limits on CO 2 mass emissions.

Utility-scale capacity expansion and dispatch planning models tend to have relatively high spatial detail with limited geographic sc ope, generally encompassing a utility service territory or a sub-regional scale. These models ge nerally have better temporal resolution than the national-scale capacity expansion and dispatch planning models, w ith each model year typically

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

.8 dispatched based on an annua l hourly load duration curve. 4 Utility-scale capacity expansion and dispatch planning models typically represen t individual EGUs, where each EGU has specific operational characteristics.

Due to the additional spatial and temporal resolution of these models as compared to the national-scale models, the numbe r of technology options for capacity expansion is generally
limited to reduce the runtime of the model. This can be done through an outside-the-model screening analysis to pr e-select the resources most likely to be economic in a planner’s area of interest, or by running the model iteratively to eliminate rarely chosen technology alternatives.

3. Electricity System Dispatch Simulation Models
Dispatch simulation models are regularly used by utilities, grid operators, and independent power producers (IPP) for short-te rm planning, ratemaking, di spatch decisions, and market intelligence. Dispatch simulation models are typically driven by near-term economics, system restrictions and market constraints, including a typically more detailed representation of an EGU’s operational constraints ( e.g. , ramp rates, heat input curves, and unit downtime for maintenance). These models typically do not ad d or retire generating capacity on an economic basis, although EGU additions a nd retirements may be exogenously input to these models. As a result, projections from these models tend to be considered more robus t in the shorter term. 5 Grid operators, including utili ties, and independent system operato rs (ISO) use dispatch simulation
models in near real-time to match demand with electric genera tion from available generating units and dispatch EGUs on a least-cost basi s. EGU owners and operators run dispatch simulation models to assist in fuel procuremen t, forecast revenues and costs, and calculate the avoided generation supply costs related to pr ocurement of end-use energy efficiency and

4 Load duration curves typically represent electri city load during a typical week for each month. 5 Some planners use dispatch simulation models in conj unction with national or utility-scale capacity expansion and dispatch planning models, where the capacity expansion and dispatch planning model indicates the disposition of new and existing generating resources, and the dispatch simula tion model is used to simulate operation of individual EGUs. In this case, these models can be used in the same time horizon as a capac ity expansion and dispatch planning model ( i.e ., decades).9 renewable energy resources. 6 Other utilities use dispatch simulation models to forecast retail rates for ratemaking proceedings and other planning purposes.

Electricity system dispatch simulation models (also called production cost models) utilize security constrained economic dispatch (SCED) algorithms to determine which EGUs operate on an hourly (or shorter) basis to meet electricity demand. 7 These models typically have a very broad spatial scope, generally covering multip le Regional Transmission Organization (RTO) regions, and often modeling entire interconnect s (i.e. Western, Eastern, and ERCOT). While individual EGUs are modeled in detail, incl uding fuel and variable costs and operational constraints, transmission is simplified to characterize thermal constraints between zones, which typically represent control areas or balancing authorities. Zones contain both load (electricity demand) and EGUs; EGU dispatch and electricity demand are balanced to maintain transmission system reliability while providing least-cost servi ce on a variable cost basis. Some versions of these models operate at a “nodal” level, wh ere transmission constraints between individual
EGUs and load are modeled as well. 8 Dispatch simulation models typically operate chronologically, modeling either all 8760 hours of the year, or typi cal weeks of the year. These models contain substantially more detail a bout individual EGUs than regional or national capacity expansion and dispatch planning models , including EGU ramp rates, minimum outages, maintenance schedules, emission rates, fuel use constraints, and heat rate curves depicting expected efficiency changes at various levels of output.

6 For example, see Hornby, R., P. Chernick, D. White, et al., 2013. Avoided Energy Supply Costs in New England: 2013 Report. http://www.rieermc.ri.gov/documents/2013%20 Evaluation%20Studies/AESC%20Report%20- %20With%20Appendices%20Attached.pdf 7 The Federal Energy Regulatory Commission (FERC) define s security constrained economic dispatch as “the level at which each available resource should be operated, given actual load and grid conditions, such that reliability is maintained and overall production costs are minimized”. SCED optimizes dispat ch based not only on the marginal costs of all available generating resources, but also constr aints on transmission availability and ancillary services. See FERC, “Security Constrained Economic Dispatch: De finition, Practices, Issues, and Recommendations” (2006), available at http://www.ferc. gov/industries/electric/indus-ac t/joint-boards/final-cong-rpt.pdf

. 8 “A “nodal” model represents the entire transmission network in a given area, without making the simplifying assumptions that load is served on a more aggregate “zona l” level.” A caveat is that while a nodal model has more “links” and places where supply must meet demand, it is stil l an approximation in terms of the electrical operation of the transmission network (the network is represented as a DC flow network, not an AC flow network).10 4. Multi-Sector Models
Multi-sector energy models are typically us ed to examine the effect of energy and environmental policies that affect multiple ec onomic sectors, such as multi-sector emission trading systems. Multi-sector models are used to review trends in emissions, expected broadscale resource use, and energy sector im pacts under changing regulatory and economic conditions, and often review cha nges over a period of decades.

Multi-sector models cover a broad range of energy sectors beyond the electricity sector, and can better reflect energy demand and technol ogy choices by energy end-users. Such models typically have relatively limited spatial detail with broad scope, generally encompassing the entire country subdivided into from one to 30 regions. Such models tend to have much more limited temporal resolution and treatment of EGU dispatch. EGUs are typically aggregated to a few broad technology types. A key strength of multi-sector energy models is the ability to provide multi-sectoral feedback between energy resource use and price ( i.e. , tracking national fuel supplies and adjusting pr ice to account for demand).

The range of national- and u tility scale capacity expansion and dispatch planning models, and dispatch simulation models identified above all te nd to focus on properly characterizing the electricity sector in order to answer sector-specific questi ons. Multi-sector energy models attempt to include many other en ergy-using sectors of the economy in order to better capture interactions between these sectors. The more aggreg ated representation of th e electricity sector in multi-sector models may limit their use to providin g input data for more specific analysis in an electricity sector model, and to better understandi ng variations in electrici ty load that may result from changes outside th e electricity sector.

B. Growth Tools for Projecting EGU Utilization and CO 2 Emissions
Organizations use growth tools for a variety of reasons, including to estimate future
emissions inventories for state and regional air quality modeling, 9 and to estimate the impact of load-reduction measures such as end-use energy efficiency and distribut ed renewable energy on

9 See, for example, the ERTAC Lo ad Growth Model, available at http://www.ertac.us/index_egu.html

.11 individual EGU emissi ons, and county, state, 10 and regional emissions rates. 11 Because these algorithms are generally base d on publicly available data 12 and do not rely on economic data or proprietary information regarding individual EGUs , they provide a low-cost, simple, and often transparent framework for estimating how EGUs will respond to changing system conditions.

Non-modeling approaches, such as growth tools, approximate future emissions and generation from existing and new fossil fuel-f ired EGUs under different assumed growth, retrofit, and load-reduction scenarios. These forecast tools do not simulate economic EGU dispatch, but could use demand growth rates and electricity production trends from other energy modeling forecasts as an input assumption. 13 The algorithms in these forecast tools assume that EGU dispatch behavior generally follows simple rules based on pa st operation. In the absence of significant shifts in fuel pri ces and electricity demand, EGUs may be expected to behave similarly in the future as they did in the past. Several common features of these forecast tools are that they (a) generally build on historical generation and emi ssions output from individual EGUs, (b) are insensitive to fuel and emission price forecasts, (c) do not solve for optimal economic EGU dispatch or EGU capacity expansion, and (d ) do not capture transmission constraints or limits. The algorithms in these forecast t ools generally divide the contiguous US 14 into regional power markets, following ISO boundaries, eG RID boundaries, NERC regional boundaries, or similar designations. These algori thms generally seek to exam ine how operation and emissions from individual EGUs could be expected to chan ge with changes in environmental regulations or installed pollution control retr ofits and additional or reduced hourly electricity demand. Some algorithms use the observed historical behavior of individual EGUs to approximate future behavior, while others add addi tional steps of differentiating E GUs into fuel groups and unit

10 See EPA’s AVERT (Avoided Emissions and Generation Tool), available at http://epa.gov/statelocalclimate/resources/avert/index.html

. 11 See Flexibility Weighted Hourly Average Em issions Rate (FW-HAER) tool, available at http://nepis.epa.gov/Adobe/PDF/P1002UQO.pdf ; Time Matched Marginal (TMM) emissions tool, a proprietary algorithm used to estimate avoided em issions; D. Jacobson and C. High, “U .S. Policy Action Necessary to Ensure Accurate Assessment of the Air Emission Reduction Benefits of Increased Use of Energy Efficiency and Renewable Energy Technologies,” Journal of Energy & Environmental Law (2010)

. 12 Hourly emissions and generation data for all fossil fuel -fired EGUs greater than 25 MW are available from EPA’s Clean Air Markets Division (CAMD) throug h its Air Markets Program Data (AMPD). 13 For example, EIA’s AEO 2013 elect ricity load growth rates and EGU production trends are available at http://www.eia.gov/forecasts/aeo/a ssumptions/pdf/0 554(2013).pdf. 14 Hawaii and Alaska do not report hourly generation and emission data from individual EGUs to EPA, and are therefore generally excluded from these forecast tools.12 types, with implicit differentiation of economic outcomes for these different groups. Some of these algorithms may contain subroutines to add new generating capacity automatically to meet load requirements.13 III. Translating from a Rate-Based Emi ssion Performance Goal to a Mass-Based Emission Performance Goal
As discussed in the preamble, in section VIII.C.2, the EPA is proposing that the projected
CO 2 emission performance by affected EGUs (taki ng into account the qualif ying impacts of plan
measures that avoid CO 2 emissions from affected EGUs) must be equivalent to, or better than, the required CO 2 emission performance level in the state plan. This required level of emission performance in the state plan is the rate-based go al for the state in the emission guidelines, or a translated mass-based goal if the state chooses to use this approach. State plans that are projected to achieve an average CO 2 emission rate (CO 2 lb/MWh) or tonnage CO 2 emission outcome by all affected EGUs equal to, or lowe r than, the requir ed level of CO 2 emission performance in the state plan would be considered to meet this pl an approvability criterion. States may demonstrate such emission performance by affected EGUs either by state or jointly on a multi-state basis.

This section of the TSD discusse s the concept of a mass-based CO 2 emission performance goal, considerations for constructing projection scen arios for such a translation, methods for conducting such a translation, and ke y input assumptions for such a translation.

A. Concept

A mass-based CO 2 emission performance goal translates the application of a rate-based emission performance goal to an expected CO 2 emissions outcome in tons during a plan performance period. A mass-based CO 2 emission performance goal is calculated by projecting
the tons of CO 2 that would be emitted during a stat e plan performance period (e.g., 2020-2029, 2030-2032) by affected EGUs in the state if they hypothetically were meeting the state ratebased CO 2 emission performance goal for affected EGUs established in the emission guidelines.
The translation of a rate-bas ed goal (expressed in lb CO 2 /MWh of useful energy output from affected EGUs) to tons (expr essed as total tons of CO 2 emissions from affected EGUs over a specified time period) is based on a projection of affected EGU utilization and dispatch mix. Importantly, this projection is conducted assumi ng the absence of qualifying state programs and measures contained in a state pl an, and applying the rate-based goa l in the emission guidelines as a proxy emission limit for affected EGUs. State pr ograms and measures in the state plan are not included in this projection, because the purpose of this analysis is to determine the tonnage CO 214 emissions that corresponds to the state-specific rate-based CO 2 emission performance goal for affected EGUs in the emission guidelines, withou t the eligible state programs and measures that are included in the state plan.

Translation of a rate goal to a mass goal seeks to answer the question, “What would happen to EGU CO 2 emissions if one applied the rate goal s in the emissions guidelines instead of the measures in the state plan?” Because the emission guidelines do not specify the emissions
reduction measures that a state mu st use in its plan, only the leve l of emission performance that must be achieved through a plan, there is no sp ecified “policy” or set of emission reduction measures in the emission guidelines to apply when conducting this projection. However, a proxy policy can be applied to project the emission performance in tons that would be achieved if the state plan were to include suitable measur es to achieve the requi red level of emission performance established thr ough the state rate-based CO 2 emission performance goals in the emission guidelines. This proxy involves applying the rate-based emission goal for a state as a rate-based average CO 2 emission limit for affected EGUs in a state and then projecting the CO 2 emissions that would occur if such a limit were applied.

When demonstrating projected emission pe rformance under a mass- based plan, a state would project the CO 2 emissions outcome that would be achieved under the suite of requirements, programs, and measures in its pl an. The state plan requ irements, programs, andmeasures substitute for EPA’s application of the best system, which is represented by the ratebased goal in the emission guidelines. If the CO 2 emissions outcome, in total tons of CO 2 emissions over each plan performance period, is e qual to or less than what would be emitted by affected EGUs through the application of the rate-based goal in the emission guidelines ( i.e. , equal to or less than the translated mass-based go al), the plan would be deemed to achieve the required emission performance criterion.15 B. Projection Scenarios
As described above, the projection scenar io for translating from a rate-based CO 2 emission performance goal to a mass-based CO 2 emission performance goal does not include requirements, programs, and measures included in a state plan. Construction of this scenario must therefore carefully consider treatment of eligible “on-the-books” state requirements, programs and measures included in the state plan. 15

Projection scenarios for translating from a rate-based CO 2 emission performance goal to a
mass-based CO 2 emission performance goal, and comp aring projected emission performance under a state plan to this goal, include the following:

1. A Reference Case Scenario . This scenario projects the average CO 2 emission rate and
CO 2 emissions from affected EGUs in the ab sence of the EPA emission guidelines or any enforceable requirements, programs, and measur es included in a state plan. This scenario does, however, include all current on-the -books state requirements, programs, and

measures that are not included as enforceable measures in a state plan. These measures are complementary to the state plan. Because these measures will influence EGU CO 2 emissions, they should, however, be included in the reference case projection scenario.
2. A Mass-Based CO 2 Emission Goal Policy Scenario . This projection scenario is used to translate a rate-based goal to a mass-based goal. The scenario applies a rate-based CO 2 emission limit to affected EGUs that is equivalent to the state-specific rate-based lb
CO 2 /MWh emission goal in the EPA emission guidelines. 16 The CO 2 emissions from affected EGUs projected during the specified plan performance peri od in this scenario represents the translated mass-based CO 2 emission performance goal for the state plan.

15 An “existing measure” refers to a state or utility requi rement, program, or measure that is currently “on the books.” For the purposes of this discussion, this may in clude a legal requirement that includes current and future obligations or current pr ograms and measures that are in place and are an ticipated to be continue d or expanded in the future in accordance with established plans. Existing measures may have past, current, and future impacts on EGU CO 2 emissions. 16 The proxy emission limit applied includes crediting for end-use energy efficiency, renewable energy, and nuclear generation included in building blocks three and four, which were used by EPA when calculating the state-specific CO 2 emission performance goals for affected EGUs in the proposed emission guid elines. In essence, these measures can be used by affected EGUs as “compliance” flexibility mechanisms when “complyi ng” with the proxy emission rate limit in this projection scenario. As a result, the prox y rate-based emission limit is able to capture all four building blocks included by EPA when calculating the rate-based CO 2 emission performance goals.16 To construct this scenario, this emission lim it is added to the underlying reference case
scenario described above.
3. A State Plan Policy Scenario . This projection scenario includes the enforceable requirements, programs, and measures included in the state plan, and is used to project
CO 2 emission performance by affected EGUs und er the state plan. To construct this scenario, the enforceable requirements, programs, and measures included in the state plan are added to the underlying referenc e case scenario described above.

An applied example is provided below in Box 1.
Box 1. Example Mass-Based Goal Translati on and Projection of Plan Performance

Example State Rate-Based CO 2 Emission Performance Goal Assumptions :

 State interim rate-based CO 2 emission performance goal for affected EGUs: 1,100 lb CO 2 /MWh

 State final rate-based CO 2 emission performance goal for affected EGUs: 1,000 lb CO 2 /MWh
Reference Case Scenario :

 Under this scenario, the projected average CO 2 emission rate for affected EGUs is 1,500 lb CO 2 /MWh during the 2020-2029 interim performance period and 1,500 lb CO 2 /MWh in 2030.

Mass-Based CO 2 Emission Goal Policy Scenario :

 A proxy emission rate limit is applied to affected EGUs (1,100 lb CO 2 /MWh on average during 2020-2029; 1,000 lb CO 2 /MWh in 2030 and subsequent years during the projection period).

 Under this scenario, the projected CO 2 mass emissions from affected EGUs during the 2020-2029 interim performance period are 100,000,000 tons of CO 2 (an average of 10,000,000 tons per year during this period) and 9,000,000 tons of CO 2 in 2030.

 The mass-based interim emission performance goal for affected EG Us is 100,000,000 tons of cumulative CO 2 emissions during the 2020-2029 int erim plan performance period.

 The mass-based final emission performance goal for affect ed EGUs is 9,000,000 tons of CO 2 per year, in 2030 and subsequent years. During plan implementation, this final goal can be met on a three-year rolling average basis, beginning with the period 2030-2032, as discussed in the preamble at section VIII.B.2.c.
State Plan Policy Scenario:

 This scenario includes the suite of requirements, programs, and measures included in the state plan.

 Under this scenario, the projected CO 2 mass emissions from affected EG Us during the 2020-2029 interim plan performance period a re 98,000,000 tons of CO 2 and 8,800,000 tons of CO 2 in 2030.

 Based on this analysis, the state plan is projected to achieve both the translated interim and final massbased CO 2 emission performance goals for affected EGUs.

1. Constructing the Reference Case
A key consideration for transl ating from a rate-based CO 2 emission performance goal to a
mass-based CO 2 emission performance goal is proper cons truction of a reference case scenario.17 This includes assumptions for key variables that may drive EGU CO 2 emission projections, 17
such as:

 Electricity load growth projec tions (energy and peak demand)

 Fuel supply, delivery, and pricing assumptions

 Cost and performance of electr ic generating technologies

 EGU firm builds and retirements (e.g., thos e scheduled with a regional transmission organization or independent system operator (RTO/ISO)) 18

 Transmission capability and ISO/RTO transmission expansion plans

 Applicable federal regulations (other than the EPA emission guidelines)

 Applicable state regulations and programs (other than those that are included in the state plan)

It may be necessary in many instances to in clude assumptions about other state programs implemented by neighboring states in the same region. This would be especially relevant for
states that are located within the same electr ic power pool (or adjoini ng power pools) that are administered by a common RTO/ISO.

2. Treatment of Existing State Regulations and Programs in the Reference Case
A key aspect of the reference case is prope r treatment of existi ng state regulations, programs, and measures. As discussed previous ly, existing state regulations, programs, and
measures that are not enforceable measures in a state plan are complement ary to the state plan – as a result, they should be included in the refe rence case scenario rather than the state plan scenario. These state regulations, programs, a nd measures should not, however, be ignored altogether, as they influence EGU CO 2 emissions. Instead, these stat e actions are occurring in the background – either when a proxy rate-based CO 2 emission limit is applied in the Mass-Based
CO 2 Emission Goal Policy Scenario ; or when the state plan requirements, programs, and

17 Process considerations related to constructing reference case scenarios are addressed in section VI of this TSD. 18 ISOs and RTOs are independent organizations that admini ster a regional electric powe r pool (EGU dispatch and electricity transmission systems) , and often also administer related wholesal e electricity markets for electric energy and capacity

.18 measures are applied in the State Plan Policy Scenario . As a result, these state actions are properly addressed in the re ference case scenario.

In effect, when evaluating whether a state plan will meet the mass-based CO 2 emission performance goal, the two policy scenarios desc ribed above, each of which involve adding a
different CO 2 emission reduction policy on top of the reference case scenario, are compared to
one another. If the State Plan Policy Scenario achieves projected tonnage CO 2 emissions equal to or lower than the projected CO 2 emissions in the Mass-Based CO 2 Emission Goal Policy
Scenario , then the state plan can be deemed to meet the translated mass-based CO 2 emission performance goal.

As discussed in the preamble, the EPA is proposing that a state may apply toward its required emission performance level the emission reductions that are achieved by existing state requirements, programs, and measures dur ing a plan performance period, due to actions 19 taken after the date of the proposal of the emission guidelines. 20, 21 In practice, this means that emission
reductions that occur in 2020 and later due to actions taken pursuant to an existing state requirement, program, or measure could be a pplied toward meeting the required level of emission performance in a state plan if these actions occur after proposal of the emission guidelines (e.g., as of June 2014 and in subseque nt years). For example, emission reductions during the initial plan performance period th at result from end-use energy efficiency technologies and measures instal led beginning in June 2014 could be applied toward meeting the required level of emission performance during th e plan performance period. These investments might be made to meet requirements under an existing end-use ener gy efficiency resource standard (EERS).

19 An “action” as used here refers to an action taken pursuant to a state requirement, program, or measure. For example, the installation of an end-use energy efficiency measure, such as an energy-efficient refrigerator installed through a utility energy efficiency program to meet the u tility’s obligations under a state energy efficiency resource standard (EERS), w ould constitute an “action” taken pursua nt to an existing state requirement. 20 The preamble also takes comment on alternative dates for eligible actions, including: the start date of the plan period, the date of promulgation of emission guidelines, the end date of the base period for the EPA’s BSER-based goals analysis (e.g., beginning of 2013 for blocks 1-3 and beginning of 2017 for block 4, end-use energy efficiency), the end of 2005, or another date. 21 As discussed in the preamble, at sec tion VIII.F.2.b, the EPA is also propos ing that this proposed limitation would not apply to existing renewable energy requirements, pr ograms, and measures because existing renewable energy generation prior to the date of proposal of the emission guidelines was factored into the state-specific CO 2 goals as part of BSER building block three.19 Under a rate-based plan, the approach descri bed above would address the eligibility date for demand-side energy efficiency meas ures that, through MW h savings, avoid CO 2 emissions
from affected EGUs. Measures in stalled after the eligibility date could generate MWh savings during the plan period, and related avoided CO 2 emissions, that could be applied toward meeting a required rate-based emission performance level. Under the proposed option, the eligibility date would be the date of propos al of the emission guidelines. 22

Under a mass-based plan, the approach described above woul d be applied when establishing a reference case scenario projection th at is used to translat e a rate-based goal to a mass-based goal. For example, the assumed amo unt of energy savings from demand-side energy efficiency measures installed subs equent to the eligibility date that are used to meet an existing EERS would not be included in the electricity load forecast used in the reference case scenario. Energy efficiency measures installed prior to the eligibility date to meet an existing EERS would be factored into the electricity load forecast us ed in the reference case scenario. This treatment would represent in the reference case past actions taken under existing state programs and measures that are not eligible for inclusion in a state plan.

22 Although such a limitation is not proposed for RE measures, we also describe here how such a limitation could be applied to RE measures under such an approach. For example, under this appr oach in the context of a rate-based plan, new renewable energy generating capacity installed in June 2014 or later to meet an existing, on-the-books RPS would be a qualifying measure in a state plan. However, only MWh generation beginning in 2020 and related avoided CO 2 emissions could be applied toward meeting a required emission rate performance level in a state plan. Similarly, under this approach in the context of a mass-based plan, the reference case might include the required MWh of renewable energy generation necessary to meet a state RPS as of the date of proposal of the emission guidelines (e.g., as of June 2014). Renewable energy gene ration that is used to meet a state RPS, but that is incremental to the amount of generation used to meet the existing RPS obligation included in the reference case as of June 2014, could be used toward demonstration of CO 2 emission performance under a state plan. This renewable energy generation would be incremental to the renewable energy generation already assumed in the reference case scenario.20 IV. Projecting CO 2 Emission Performance under a State Plan – Overview
As discussed in the preamble, in section VIII.D.4, one of the required components of a state plan is a projection that a plan will achieve the required level of CO 2 emission performance by affected EGUs that is specified in the pla n. (This identified level of performance must be consistent with either the state-specific rate-based CO 2 emission performance goals for affected EGUs identified in the emission guidelines, or an equivalent tr anslated mass-based CO 2 emission performance goal.)

This emission projection is based on a scenario that includes the suite of requirements, programs, and measures in the state plan – the State Plan Policy Scenario described above. Depending on the plan approach, construction of this state plan scenario may be straightforward. For example, if the state plan consists solely of an emission limit, the state plan scenario would apply this emission limit to the underlying refere nce case scenario. Other types of state plan approaches are more involved, in particular wh en the use of end-use energy efficiency and renewable energy regulations, prog rams, or measures are included in a state plan. This could include a state plan that applies a rate-based CO 2 emission limit that provides credit for end-use energy efficiency and renewable energy measures that avoided CO 2 emissions, or the inclusion of such measures through a portfolio appro ach. These types of plans will require input assumptions for the amount of end-use energy efficiency and renewable energy resource (in MWh over the plan period) that will be realized through implem entation of the plan. Utilitydriven portfolio approaches may also include a di verse set of actions take n directly at affected EGUs that will need to be properly re presented in the state plan scenario.

Considerations for developing estimates of energy savings and energy generation that will be achieved through end-use energy efficien cy and renewable energy regulations, programs, and measures included in a state plan are discussed below in section VI.21 V. Applied Considerations for Different Types of State Plans 23

There are a number of considerations for properly representing di fferent state plan approaches in CO 2 emission projection scenarios. This includes both accurate representation of the attributes of state regulations, programs, and measures in the scenario, as well as the methods
and data sources used to derive certain input assump tions that are used in CO 2 emission projections. This includes:

 Estimating the future effects of end-us e energy efficiency and renewable energy requirements, programs, and measures

 Properly characterizing flexibilities included in emission limits, such as emission budget trading programs

 Properly addressing characteristics of multi-state regulations and programs

A. End-Use Energy Efficiency and Renewable Energy
Evaluating the impact of a state end-use energy efficiency requirement or program included in a state plan, as part of a projection of CO 2 emissions from affected EGUs under a state plan, involves projections of the impact of the requirement or program on energy and capacity savings, and the impact of this reducti on in electricity load and peak demand on EGU dispatch and CO 2 emissions from affected EGUs. 24 This involves projections of the level of current and future energy and capacity savings achieved through pr ogram investment or activities in each year, the distribution of thos e savings on a daily and seasonal basis (e.g., the load shape of the energy and capacity savings), an d the effective useful life of those energy and capacity savings (e.g., the life of installed measures represen ting the persistence of energy savings). Such projections may also need to address net program ener gy savings after accounting for potential “free-ridership,” wh ich involves energy savings that we re likely to have occurred in the absence of program incentives, and “s pillover,” which involves broader market

23 Different potential state plan approaches are described in detail in the accompanying State Plan Considerations TSD. 24 The evaluation discussed in this section is relevant for state plans that implement a rate-based CO 2 emission limit applicable to affected EGUs that provides for adjustment or crediting of the CO 2 emission rate of an affected EGU based on the effects of end-use energy efficiency and renewable energy. It is also relevant for state plans that take either a rate-based or mass-based port folio approach. Descriptions of these plan approaches are provided in the accompanying State Plan Considerations TSD.22 transformation impacts that result from the program. These energy efficiency program projections would then be used to adjust elec tricity load forecasts, as necessary, for modeling runs using an electricity sector dispatch and capacity expansi on planning model. This modeling would evaluate the impact of the energy a nd capacity savings on the dispatch of EGUs, construction and retirement of EGUs, and related CO 2 emissions from affected EGUs.

Similar considerations apply for projecting the impact of renewable energy requirements and programs included in a state plan on CO 2 emissions from affected EGUs. The renewable energy generation and generating capacity in a stat e or region that result s from renewable energy requirements, programs, and measures in a st ate plan will affect EGU dispatch and CO 2 emissions from affected EGUs. This section di scusses these considerations in more depth, including approaches and data sources for estimating the impact of end-use energy efficiency and renewable energy requirements and programs as part of state plan projections of CO 2 emission performance by affected EGUs.

1. Potential Approaches for Estimating the Future Effects of State Energy Efficiency Requirements, Programs, and Measures
There are two basic approaches for developing a ten-year or longer forecast of end-use energy efficiency resources that will result from state energy efficiency requirements and programs: a bottom-up or a top-down approach. Thes e forecasts would contain data that could be used to develop inputs to EGU CO 2 emission projections in a stat e plan, using modeling or an EGU growth tool, both of which are summarized above.

A bottom-up approach is based on annual eval uated and reported data from state and utility energy efficiency programs, and progr am-level utility compliance reports under state energy efficiency requirements, such as an end- use energy efficiency resource standard (EERS). One example of a bottom-up approach is the stat e-by-state end-use energy efficiency projection developed by ISO New England for us e in its system planning process. 25 In simple terms, ISO

25 Each year, ISO New England produces a Regional System Plan (RSP) that provides a comprehensive assessment of the New England bulk power system that is used as input data for evaluating the future reliability of the grid. One component of the annual RSP is a future estimate of peak loads and annual energy use th at is modified (reduced) by the energy efficiency forecas t. Information about the ISO New England energy efficiency forecasting method and assumptions is included in, ISO-New England (IS O-NE) Energy-Efficiency Forecast Working Group, Draft Final23 New England develops production cost curves for en ergy efficiency measures based on historical performance of energy efficiency as documented in evaluation, measurement, and verification (EM&V) studies. ISO New England then applies those production cost curves (with adjustments for inflation and other factors) to future state or utility energy efficiency program budgets for each of the six New England states over a ten-year horizon. The ISO New England energy efficiency forecast includes both reductions in annual energy use (MWh) and peak demand (MW). ISO New England has produced an energy e fficiency forecast for the last three Regional System Plans (2011, 2012, and 2013), and the near-ter m estimates in these forecasts have been validated by the actual quantity of end-use ener gy efficiency that has qualified for the annual capacity auctions conducted by ISO New England as part of its forward capacity market. Other approaches to projecting energy efficiency im pacts, such as those used by New York ISO (NYISO), PJM Interconnection, and the Calif ornia Public Utilit ies Commission (CPUC), estimate the effects of energy efficiency requireme nts and programs over a shorter time frame. In these cases, energy efficiency projections are t ypically consistent with the periods for which energy efficiency programs or program budgets have been approved by state PUCs, or consistent with the period for which energy and demand sa vings are acquired in ISO and RTO forward capacity markets.

Top-down projection methods analyze aggregat e energy use changes resulting from enduse energy efficiency requirements or programs, often for a geographic re gion, entire industry, or
economic sector. A top-down approach is determined on the basis of state energy efficiency policy requirements, and assumes that utilities and other parties implement efficiency programs necessary to achieve required en ergy and demand savings. In th is way, a top-down approach is typically based on an estimated annual percentage reduction in energy use that results from state energy efficiency requirements and programs. On e example of a top-down approach is the EPA’s state-level projection of th e impacts of “on-the-books” 26 energy requirements and programs. EPA’s approach uses these state requirements and program commitments as the basis for

Energy-Efficiency Forecast 2018-2023 (March 2014), available at: http://www.isone.com/committees/comm_wkgrps/othr/enrgy_effncy_frcst/ 26 As used here, “on the books” refers to state energy-e fficiency requirements and pr ograms currently in place and specified in state legislation or admi nistrative order. These requirements include energy efficiency resource standards (EERS) and dedicated sources of energy efficiency program funding.24 adjusting national electricity load forecasts for use in electricity system modeling. 27 In this case, EIA Annual Energy Outlook (AEO) projections of fu ture electricity use (MWh) and peak loads (MW) are modified to account for the reduction in energy sales due to state and utility programs and associated energy savings requirements. 28 These energy savings requirements are examined on a state-by-state basis and adjusted, as necessa ry, to reflect known increases or decreases in energy efficiency program budgets and other f actors likely to affect whether state energy efficiency requirements are achieved. In additi on to EPA’s projections, a top-down approach is used to develop EE forecasts by LBNL 29 , NREL 30 , and some state energy offices and
commissions.

The LBNL and the EPA forecast models are useful for comparison with the bottom-up ISO/RTO approaches. Where discrepancies between the national top-down analyses of end-use energy efficiency savings and the more granular bottom-up energy efficiency forecasts conducted by ISOs and RTOs exist, review of key assumptions regarding state policies for the different approaches may be warranted. Ideall y, using the two approaches as complementary analyses may provide for helpful comparison and r econciliation of energy savings estimates used in state plan proj ections of EGU CO 2 emission performance.

The electricity load forecasts developed by ISOs and RTOs are important because they are often the base case from which adjusted lo ad forecasts that inco rporate projected energy efficiency program savings are developed. For reasons described above, ISOs and RTOs are beginning to include some adjustments to their base case load forecasts to account for energy efficiency program impacts. In most cases, th ese efforts are focused on including the future anticipated impacts of existing “on the books” energy efficiency requirements and programs and

27 While EPA’s approach utilizes AEO fo recasts of electricity use and peak loads, other credible and long-term forecasts could be used in a similar manner. U.S. EPA, Background and Draft Methodology for Estimating Energy Impacts of EE/RE Policies (March 2014), available at: http://epa.gov/statelocalclimate/state/statepolicies.html

. 28 For example, annual incremental and cumulative energy savings requirements for utilities included in a state EERS. 29 Lawrence Berkeley National Laboratory (LBNL), The Future of Utility Custom er-Funded Energy Efficiency Programs in the United States: Projected Spending and Savings to 2015 (January 2013), available at: http://emp.lbl.gov/publications/future-utility-customer-funde d-energy-efficiency-programs -united-states-projectedspend

. 30 National Renewable Energy Laboratory, State Energy Efficiency Resource Standards: Policy Design, Status, and Impacts (May 2014), available at: http://www.nrel.gov/publications/

.25 adjusting load forecasts accordingly. However, in so me cases there is also an effort to anticipate new incremental energy efficiency investments in the future that are not tied to existing energy efficiency requirements and programs. 31 When conducting a projection of EGU CO 2 emission performance as part of a state plan that incl udes energy efficiency requirements and programs, it will be important to know how the base electricity load forecast for the state or region was developed, whether it already includes the eff ect of state and utility energy efficiency requirements and programs, and whether and how it should be adjusted to account for the future effects of existing on-the-books and incremental (i.e., new) energy efficiency requirements and programs that are included in the state plan.

1.1 Potential Uses of Energy Efficien cy Projections for State Plan Emission Projections
Whether developed through a bottom-up or top-down approach, projections of annual energy and peak load reductions that result fr om state energy efficiency requirements and programs included in a state plan are n ecessary inputs to projections of EGU CO 2 emission performance under the state plan. Energy and peak demand savings estimates included in energy efficiency projections are used as a decrement to fu ture electricity load forecasts that are used in conducting EGU CO 2 emission performance projections. Th e energy efficiency projection is used as an input, or modifier, to various models or other tools used to project the impact of energy efficiency resources on state or regional CO 2 emissions. For example, capacity expansion and dispatch planning models are capable of in corporating energy efficiency program impact data, such as annual energy and peak load re ductions, when projecting EGU dispatch and capacity additions, and the avoided CO 2 emissions that are projec ted to result from these requirements and programs.

31 In New England states that have policies to pursue “a ll cost-effective energy effici ency,” the ISO-NE energy efficiency forecast assumes that energy efficiency program investments will continue beyond the approved program funding period (typically documented three-year plans), either at a constant level or some discounted level based on assumptions about an increase in the cost of saved energy over time.26 1.2 Data Issues and Considerations for Using and Developing Energy Efficiency Projections
Depending on what data sources and approaches are used to project the future energy and demand savings from energy efficiency requireme nts and programs, there are certain strengths and limitations regarding the approach and me thodology used. Generally, these strengths and limitations relate to data availability and en ergy efficiency forecast assumptions, such as:

 Energy efficiency requireme nts and programs included

 Jurisdictions covered

 Planning timeframe

 Embedded energy and demand savings from energy efficiency requirements and programs in base electricity load forecasts

 Cost of saved energy for differe nt energy efficiency measures

 Energy efficiency measure life and measure energy performance decay

 Time of energy and demand savings for ener gy efficiency measures (availability of hourly data necessary to derive a load reducti on profile for an energy efficiency measure)

Bottom-up versus top-down forecasting approaches have different strengths and limitations related to the data and assumptions described above. In the case of bottom-up approaches, state energy efficiency requirement s and programs can be fully addressed in the analysis. In top-down approaches, such as EIA AE O analysis, greater focus is placed on federal policies (e.g., codes and standards) but less data is incorporated to reflect state energy efficiency requirements and programs. Bottom-up approaches t ypically include state-specific data that are rolled up to a regional level, while top-down national electricity load fore casts do not have a comparable level of granular state data de tail. ISO New England provides energy and demand savings forecasts for state energy efficiency programs (average annual and peak demand coincident with the ISO defined peak load peri ods). The ISO NE energy efficiency forecast is informed by data collected at the energy e fficiency measure, indi vidual program, program portfolio, sector, and state levels.27 An important consideration with both top-down and bottom-up energy efficiency forecasts is the extent to which energy efficien cy program effects have become embedded into the long-range economic forecasts used as an inpu t in developing electric ity load forecasts. In
some cases the economic forecast includes the eff ect of historical energy efficiency policies, either implicitly or explicitly, while in other cases the economic forecast may also anticipate some limited quantity of future energy effici ency investment that is incremental to the anticipated effect of existing energy efficiency requirements and programs. An additional consideration is whether and how building energy codes and appliance standards (both current and future) are accounted for in the base electricity load forecast.

Another consideration, for all energy efficien cy projections, is ener gy efficiency program spending. While “on the books” energy efficiency requirements and programs may include multi-year approved energy efficiency program b udgets, actual program expenditures may differ. This has been the case in some of the New Engl and states, for example, where ISO New England has made adjustments to “discount” the spending le vels to reflect actual spending trends, and not used the state approved budgets identified thr ough stakeholder discussions. Additionally, assumptions are made about how the overall co st of saved energy for a portfolio of energy efficiency programs will change over time. It is generally assumed in most energy efficiency projections that the cost of installing energy e fficiency measures will become more expensive into the future as state programs move beyond “low-hanging fruit” and increasingly focus on achieving deeper and broader energy savings through whole-building, multi-fuel programs addressing new buildings and building retrofits). 32

While many existing sources of energy effi ciency projection data do not account for hourly savings, it is becoming increasingly possible for states to examine and incorporate information about the time dimension of energy e fficiency impacts. Smart meters combined with data-sharing and analysis technologies are making it easier for util ities and other energy

32 Evidence to date is mixed as to a relationship of larg er scale energy efficiency programs and broader energy efficiency measure portfolios, and the asso ciated deeper levels of energy savings, to increasing cost of saved energy. Economies of scale, and expertise gained by program administrators from managing larger programs for multiple years, can lead to cost reductions. Ho wever, at some point, as program administrators move away from initial lowcost strategies and end-use energy efficiency measures, it is assumed that the cost of saved energy will increase.28 efficiency program administrators to more accu rately determine how the total energy savings achieved in a calendar year are spread out acros s the hours of that year . These data can be applied to energy efficiency projections to provi de a better estimate of the timing of energy and demand savings. Such time-differentiated data is valuable for identifying the marginal EGU or cohort of marginal EGUs that are affected by energy efficiency requirements and programs, which can be used to provide more refined estimates of avoided CO 2 emissions due to changes in EGU dispatch and the addition of new generating capacity.

2. Potential Approaches for Estimating the Future Effects of State Renewable Energy Requirements, Programs, and Measures
This section describes data and analytic considerations for th e representation of renewable energy requirements and programs included in state plans, when conducting projections of EGU CO 2 emission performance that will be achieved under a plan. A range of data and analytic considerations are examined that may be relevant when using different modeling approaches, including us e of capacity expansion and di spatch planning models, and less sophisticated statistical or top-down projection appro aches. Examples of specific
considerations are described for three renewable energy policies that may be used as enforceable measures in a state plan— renewable portfolio standards (RPS), feed-in tariffs (FIT), and performance-based tax incentives.

2.1 Renewable Portfolio Standards
RPS requirements are typically se t at the state level with an increasing percentage of total retail sales over a set schedule. The RPS require ment defines the eligible resource types (e.g., wind, solar, etc.) and in some cases, may specify resource-specific requirements, such as a percentage of the overall RPS targ et that is set-aside for a specific resource. It also defines the allowable geographic boundary for obtaining renewa ble energy or RECs. With this context, the following issues may be important to consider when projecting the impact of state RPS on EGU
CO 2 emissions.29 2.1.1 RPS as an Input to Electricity Sector Modeling
Electricity sector modeling includes the use of dispatch simulation models and capacity expansion and dispatch planning models that simulate the operation of individual EGUs (or aggregations of EGUs) in the el ectric system over time based on a detailed characterization of those EGUs, engineering and market operating constr aints, other market fa ctors (e.g., fuel prices, transmission constraints), emission constraints, and the requirement to meet a certain level energy and peak demand. These models may be ba sed on a small control area, but more likely are regional or national in scope. Some, such as capacity expansion and dispatch planning models, simulate EGU dispatch and also consid er the impact of long-term generating capacity investment decisions when optimizing system op eration and buildout over a long-term planning horizon. These are typically optimization framew orks that have as their objective meeting electricity demand subject to a broad range of operating, environmental and market constraints, including meeting RPS requirements.

When using these types of anal ytic tools to project EGU CO 2 emissions, a number of analytic and data considerations are rele vant for analysis of RPS impacts on EGU CO 2 emissions. These analytic and data c onsiderations are summarized below.

Translation of RPS Requirements to Re newable Energy Generation Requirements Most RPS are retail sales-based requirements, wh ile most electricity sector analytic tools are generation-based mode ls. When projecting CO 2 emission performance by affected EGUs using a generation-based analysis tool, it is necessary to translate the RPS sales-based requirement to a generation requirement using a transmission and distri bution loss rate to “ gross up” the sales estimate. For example, if an RPS requires 100 MWh of sales be met with eligible renewable energy resources, then the required re newable energy generation necessary to meet the RPS is 100 MWh / (1 + T&D loss rate). 33

33 According to EIA data, nationally, annual electricity transmission and distribution losses are equivalent to about seven percent of the electricity that is input to the transmission system in the United States.30 RPS-Eligible Resources vs. State Plan-Eligible Resources Some RPS rules define a broad range of elig ible renewable energy generating resources. These could include renewable energy EGUs that emit CO 2 , and EGUs that were constructed and began operation recently or many years ago. Some of these specific EGUs may not be eligible for use in a plan, in particular un its that began operation prior to eligibility dates for actions that may be included in a state plan (if such limitation s were applied to renewable energy measures in state plans). 34 Thus, the RPS requirement would need to be adjusted to reflect the use of only those resources eligible for use in state plans. This would be addressed through the treatment of existing RPS in the analysis base case, as described above in section III.B.2.

RPS Vintage Rules Some RPS requirements provide that only renewable energy EGUs that began operation after a certain date are eligible. To the extent these renewable energy E GUs are eligible under a state RPS but not under the state plan, the analysis should explicitly address these resources. This could be done either through an adjustment of the MWh needed to meet the RPS, to account for renewable energy resources that ar e not eligible for use in a stat e plan, or through the use of two modeled RPS requirements for each class of rene wable energy resource, with the RPS that
addresses resources not eligible in a state plan addresse d in the modeling reference case.

In/Out-of-State Contribution Some RPS allow some of the requirement to be met by out-of-state resources. Some modeling frameworks may allow the user to exp licitly specify the source region of eligible renewables. From a modeling perspective, this means a state would allo w a broader supply area and model a broader area generally. If the renewable energy resources have different
characteristics across the relevant geographic area, then data is needed on the characteristics of these resources by region (e.g., resource availab ility, performance, and capital and production

34 As discussed in the preamble, and explained in section III.B.2 of this TSD, EPA is proposing that emission reductions that occur in 2020 and later due to actions taken pursuant to an existing state requirement, program, or measure could be applied toward meeting the required level of emission performance in a state plan if these actions occur after proposal of the emission guidelines (e.g., as of June 2014 and in subsequent years). As discussed in the preamble, at section VIII.F.2.b, the EPA is also proposing that this proposed limitation would not apply to existing renewable energy requirements, programs and measures because existing renewable energy generation prior to the date of proposal of the emission guidelin es was factored into the state-specific CO 2 goals as part of BSER building block three.31 costs). EIA (for NEMS), EPA (for IPM), a nd NREL (ReEDS) provide information on the characteristics and performance of renewable energy resources by region. 35

Characteristics of Renewable Resources In a dispatch modeling framework, better emission projections will result when the source of renewable energy is known and the energy profile is modeled. Renewable energy resources, such as wind or solar PV, may differ substantially in generation profile, as the supply of electricity to the grid from the EGU is based on availability of the renewable energy resource. The time during which electricity generation is s upplied will influence the marginal fossil fuelfired EGU (or cohort of EGUs) that is displa ced by renewable energy generation. Understanding the renewable energy resource base, including th e energy profile of the relevant renewable energy resource types will improve the modeling of EGU dispatch and projections of avoided
CO 2 emissions that result from renewable ener gy generation. Data may include a detailed 8760- hour energy output profile for rene wable energy resources, or at a minimum, a seasonal diurnal profile for such resources. If no state-specific da ta is available, generic output profiles for different renewable energy resour ces are available from NREL. 36

Renewable Energy Resource Availability and Economics Emission projections will be enhanced by a representation of the new renewable energy EGUs that are likely to be brought online as a result of a state RPS, based on an analysis of available renewable energy resources and econo mics. This requires understanding the relative economics (e.g., capital costs, fi xed operation and maintenance (F OM) costs, variable operation and maintenance (VO&M) costs, and fuel costs) and operating conditions for different types of renewable energy generators, as well as re newable energy resource availability (e.g., MW

35 EPA’s Integrated Planning Model generation profiles for wind and solar in the EPA IPM v.5.13 base case are available at http://www.epa.gov/powersector modeling/BaseCasev513.html

. 36 NREL’s datasets are intended for use by energy profe ssionals, such as transmission planners, utility planners, project developers, and university researchers who perform wind and solar integration studies and need to estimate power production from hypothetical wind and solar plants. The Eastern Wind Dataset ( http://www.nrel.gov/electricity/transmission/eastern_wind_methodology.html ) contains modeled wind farm data points for the eastern United States for 2004, 2005, and 2006. The Western Wind Dataset ( http://www.nrel.gov/electricity/transm ission/western_wind_methodology.html ) includes information about the methodology used to develop the dataset, the accuracy of the data, site selection, and power output. The Solar Integration Datasets (http://www.nrel.gov/electricity/transmission/solar_integration_methodology.html ) are solar photovoltaic (PV) power plant five-minute and hourly day-ahead forecasts of generation output for approximately 6,000 simulated PV plants in the United States for the year 2006.32 capacity available at different wind classes, sola r insolation levels, and the characteristics of biomass). Having this information allows for be tter projections of th e level and quality of renewable resources likely to be brought forward as the result of a state RPS. This will result in better emissions projections.

NREL has a suite of tools that can be used to estimate the potential costs of renewable energy under various assumptions. 37 For example, the CREST model is a cost-of-energy analysis tool intended to assist policy makers evaluating the appropriate payment rate for a cost-based renewable energy incentive policy. The model aims to determine the cost-of-energy, or minimum revenue per unit of production, ne eded for a sample (modeled) re newable energy project to meet
its investors' assumed minimum re quired after-tax ra te of return. 38

Retail Rate Impacts Many state RPSs have cost containment mech anisms or effective caps on the allowable impact on retail rates or on customer bills that ca n result from implementation of an RPS. If these caps are triggered, it will delay further incr eases in the RPS targets, depending on RPS implementation rules. This would lower estimat es of renewable energy generation needed to satisfy the RPS requirements. Likewise, to limit rate impacts, many state RPS include an alternative compliance payment (ACP) provision, which requires ob ligated entities to pay a pr edetermined fee to the state for each MWh of RPS shortfall. Although these ACP payments may be directed to programs to promote the deployment of renewable energy technologies, these payments are not equivalent to renewable energy generation and should not be accounted as such.

37 NREL's Energy Analysis web site ( http://www.nrel.gov/analysis/models_tools.html ) has links to tools such as the Cost of Renewable Energy Spreadsheet Tool (CRE ST) and the System Advisor Model (SAM). CREST (https://financere.nrel.gov/finance/content/crest-cost-ener gy-models) makes performance predictions and cost of energy estimates for grid-conn ected power projects based on system design parameters that the user specifies. The SAM cash flow model (http://sam.nrel.gov/) helps assess solar, wind, or geothermal projects, design cost-based incentives, and evaluate the im pact of tax incentives or other support structures on renewable energy projects. 38 The CREST model is a product of a 2009-2010 partners hip between the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE) Solar Energy Technologies Program (SETP), and the National Association of Regulatory Utility Commissioners (NARUC). The model was developed by Sustainable Energy Advantage (SEA) under the direction of NREL. The report , user manual, and CREST models are free and available for download at: https://financere.nrel.gov/ finance/content/crest-cost-energy-models.33 Market Impacts – Multiple State Players One important issue is to account for actions of others. Modeling result s that consider the
RPS-related actions of other stat es could differ substa ntially from those that consider a state’s actions in isolation. This require s having at least a re gional, if not national, modeling framework. A broader framework captures competition for rene wables (and increased pr ices, greater reliance on poorer resources), as well as market-wide im pacts on EGU dispatch an d capacity expansion.

2.1.2 Data Needs for Estimating Generation Resulting from State RPS
Projections of renewable en ergy generation will require assembling the following data:

 Resource availability, resource performance, a nd resource costs will be necessary for the more sophisticated modeling approaches described above.

 Projections of retail sales, by year, adjusted to account for any ex clusions from the RPS obligation (e.g. small utilities, cooperatives, municipalities, or perhaps certain large industrial loads). These covered sales must be calculated and projecte d using forecasts of
annual retail demand.

 RPS requirements by year, so the annual forecas t of covered retail sales can be multiplied by these percentages.

 The extent to which credit multipliers are used for compliance. Credit multipliers reduce the number of MWh needed for RPS compliance, and a downward adjustment should be made based on the percentage of compliance achieved by credit multipliers.

 Representation of alternative compliance pa yment (ACP) provisions, if applicable, and other relevant compliance flexibilit y provisions provided through the RPS.

 Estimates of transmission and distribution (T &D) losses, so that retail sales can be “grossed up” as described above. T&D losses es timates are available at the national level and can also be obtained for various grid regions from the appropriate regional grid operator.

 If an electricity sector ca pacity expansion and dispatch planning model is not used, estimates of the geographic origin, by state a nd grid-region, of generation used to satisfy the RPS will be necessary. If generation to sa tisfy the RPS is expected to come from out of state, the basis for these assumptions should be documented.34  CO 2 emission rate associated with renewa ble energy generation, by resource type (if applicable).

 Generation profile, by renewa ble energy resource type

2.2 Feed-in Tariff and Other Performance-Based Incentives
A feed-in-tariff (FIT) is a performance-based in centive (similar to production tax credits) that typically guarantees utility customers who own a eligib le renewable electricity generation system (e.g., roof-top solar PV system) will be pa id a specific amount by their utility for the electricity the system generates a nd provides to the grid over a fixe d period of time. Such tariffs usually offer a fixed payment amount per kWh, but variations may require competitive bids. In some cases, FIT payments may be in addition to other incentives (s uch as a production tax credit). With a FIT, the amount of renewable energy that will be generated is not specified in the tariff schedule. A similar uncertainty about the amount of renewable energy generation that will occur exists for production-based tax credits. In the case of an RPS, the amount of renewable energy generation necessary to meet the RPS is known given the required RPS level and a utility sales projection. 39 In the case of FITs the response to the program may be more uncertain. The
remainder of the discussion focuse s on estimating these impacts.

The key information required to estimate the generation that will occur as a result of a
FIT includes:

 An estimate of the renewable energy generation that will be provided by year for the FIT, along with estimates of payments to be made. These should capture the impacts of interactions with other policies, including RPS requirements, net metering, and federal investment and production tax credits. If ge nerators receiving FIT payments are also eligible to satisfy an RPS, states should en sure their estimates of renewable electricity generation are not double-counted. For analysis using a detailed capacity expansion and dispatch planning model, market penetration of renewable energy generation to meet an RPS may be an output of the model. In this case, information is required on the capital

39 Most state RPS schedules are established as a percentage of utility sales in a given year, although some include specified MWh amounts or are based on MW of generating capacity.35 costs, FOM costs, and VOM costs of the re newable energy generating technology. This is the same information required for modeling an RPS; however, the modeling or analysis mechanism may differ. For example, these co sts may be reduced directly in a modeling
framework to reflect the FIT payment (e.g., reducing VOM to re flect the FIT in the years it is available).

 Information on the types of renewable energy resources, including their location, output levels, energy output profiles (across all 8,760 hours of the year or seasonally), and operating life of the EGU (by technology, so th at they can be included in an electric dispatch model or mapped to an appropriate lo ad shape or marginal avoided emission rate if using simpler analytical methods.

 An estimate of whether the projected retail price impacts of the FIT will lead to lowering the amount paid to eligible renewable en ergy generators, if a FIT includes caps on generation subject to the tariff ba sed on rate impacts. If retail electricity rate impacts or budgetary impacts become unsustainable, the pr ojected generation resulting from the FIT
will be overstated.

2.2.1 Data Needs for Estimating Generatio n Resulting from Feed-In Tariff and Performance-Based Tax Incentives
Projections of renewable gene ration that will occur as th e result of FITs and other performance-based incentives wi ll require assembling the followi ng data about the specific incentive programs that will suppor t renewable energy generation:

 Caps on generating capacity, if any, by year, because such caps will limit the amount of renewable energy generation resulting from the tariff or tax incentive.

 Capacity amounts by renewable energy resource type that will be subject to a FIT or other performance-based incentives, and the cap acity factors for these resource types, so that total generation in MWh can be calculated.

 Payment levels per kWh or MWh for each year of the FIT or other production-based
incentive.

 Budget amounts, if known, by year, which may be expended to support renewable generation. When divided by the incentive payment levels , on a per-kWh or per-MWh36 basis, these budget amounts will yield an estimat e of the total electric generation that will be supported by the FIT or othe r production-based incentive.

 State experience and trends with FITs a nd other production-based incentives. Lacking budget or capacity limits, prior experience in the state, or the experien ce of other states and utilities, normalized for state or util ity size, could be the basis for estimated renewable energy generation at a given incen tive level.

 Because performance is metered at the busbar (i.e., the point of interconnection to the electricity transmission or di stribution system), no adjustme nts would be needed for T&D
losses.

 Estimates of the geographic origin, by state, of generation that receives support from these programs. In most cases, eligible generation will be in-state, but if generation is expected to come from out of state, the basis for th ese assumptions should be
documented.

 CO 2 emission of renewable energy generation, by resource type (if applicable).

B. Emission Budget Trading Programs
Emission budget trading programs establish an emission limit for a group of emission sources and establish a budget of tradable emission allowances e qual to the emission constraint for the group of sources. An emission allowance t ypically represents a limited authorization to emit one ton of a regulated pollutant. These programs also typically include a number of additional flexibility mechanisms beyond the abi lity to trade allowances. These include multiyear compliance periods, the ability to bank allo wances issued in a previous compliance period for use in a subsequent compliance period, the use of out-of-sector project-based emission offsets, and cost-containment allowance reserves that make additional allowances available to the market if pre-established allowance price thresholds are achieved. 40 As a result, annual emissions from affected sources subject to an emission budget trading program often differ from the established annual emission budget for affected sources. In addition, th ese programs may be multi-sector in nature, regulating emissions fo r source categories in addition to EGUs. As a

40 Depending on the program, these cost containment allowa nce reserves make additional allowances available from within the base emission budget (i.e., from “within the em ission cap”), or add to the base emission budget (i.e., increase the emission cap).37 result, state plan emission projections will ne ed to accurately account for and represent these compliance flexibilities, as well as the scope of affected sources if they are broader than EGUs affected under CAA section 111(d). 41 In general, most electricity sector capacity expansion and dispatch planning models can be configured to evaluate these program flexibilities and project
CO 2 emissions from affected sources, cons idering these compliance flexibilities.

1. Addressing the Sectoral Scope of Emission Budget Trading Programs
Some existing state emission budget trad ing programs addressing GHG emissions regulate emission sources in addition to EGUs, such as industrial sources. 42 We refer to these here as multi-sector emission budget trading pr ograms. All existing state emission budget trading programs addressing GHG emissions include out-of -sector project-based emission offsets, which may be used to cover a portion of the co mpliance obligation of affected sources.

For multi-sector emissions budget trading pr ograms, state plan emission projections would need to evaluate projected CO 2 emissions across all source ca tegories covered by the state or multi-state program. This would be necessary to project the CO 2 emissions performance of
affected EGUs under the multi-sector emissions budget trading program.

For emission budget trading programs that regul ate EGUs and include offsets, which we
define here as emissions reductions from sources not regulated by the trading program, emissions
reductions from offsets would not be counted when evaluating CO 2 emission performance of affected EGUs, because those reductions would not come from those affected EGUs. However, state plan emissions projections would need to ev aluate the use and impact of offsets, because the availability of offsets would affect the amount of CO 2 emissions from affected EGUs.

Addressing Multi-Sector Emission Trading A state or regional emission budget trading pr ogram could potentially regulate sources from multiple emissions sectors beyond the electric ge nerating sector that is the focus of the EPA emission guidelines. For example, the Califor nia GHG emission budget trading program is a

41 For example, the Regional Greenhouse Gas Initiative (RGGI), which is an emission budget trading program limited to EGUs, includes EGUs that are not subject to CAA section 111(d). 42 The California GHG emission trading program also include s large industrial sources and as of 2015 will include distributors of transportation, natural gas, and other fuels.38 multi-sector emissions trading program that addr ess emission sources outside the scope of the EPA emission guidelines for EGUs. If a multi- sector emission budget trading program is included in a state plan, CO 2 emission projections provided as part of the state plan will need to evaluate projected CO 2 emissions across all covered emissions sectors under the program. This would be necessary to project the CO 2 emissions or weighted average CO 2 emission rate of
affected EGUs that will be achieved under the multi-sector emission budget trading program included in the state plan.

Evaluating the projected impact of a multi- sector emission budget trading program on the
CO 2 emission performance of affected EGUs introduces an additional level of analytical complexity to emissions projections. For exam ple, additional modeling capabilities may be necessary to adequately evaluate CO 2 emission performance across sectors in a multi-sector emission budget trading program.

Adequately projecting the CO 2 emissions of affected EGUs subject to a multi-sector emissions budget trading program may require modeling using a multi-sector energy model. 43 The use of an electricity sector dispatch and capacity expansion planning model, might also be required, as a complement to a multi-sector mo del. Some multi-sector models, include an electricity sector dispatch and capacity expans ion planning module. However, use of a standalone electricity sector model, might also be necessary as a supplement to a multi-sector energy model, in order to project CO 2 emissions or the weighted average CO 2 emission rate from
affected EGUs at a sufficient level of resoluti on for state plan emission projections. Under this approach, a multi-sector energy model might be used to project the level of CO 2 emissionsabatement achieved across the multiple emission sectors covered by the program. This multisector projection could be used to develop a CO 2 marginal abatement cost curve representing cost-effective, non-electricity se ctor emission reduction opportunities at increasing cost levels. The marginal abatement cost curve would then se rve as an input assumption for the electricity sector capacity expansion and di spatch planning model, which w ould be used to project the CO 2

43 For example, the Energy 2020 model was used by Calif ornia to evaluate the impacts of its multi-sector GHG emissions budget trading program. Other multi-sector mode ls are available with similar capabilities, such as the National Energy Modeling System (NEMS) developed and implemented by the U.S. Energy Information Administration (EIA).39 emission performance of affected EGUs (e.g., the CO 2 emissions or CO 2 emission rate of individual affected EGUs, or the total CO 2 emissions or weighted average CO 2 emission rate across multiple affected EGUs). 44

Multi-sector emission budget trading progr ams also often address GHGs beyond CO 2 . If this is the case, emission projections in a st ate plan would need to account for emissions abatement opportunities for each of the GHGs regulated under the program, and project emissions reductions for each of the regulated GHGs. This would be necessary to project the
extent to which affected emissi on sources in different industria l sectors reduce emissions of nonCO 2 GHGs, which could impact projected CO 2 emissions from affected EGUs.

Addressing Emission Offsets
Emission offsets in CO 2 or GHG emission budget trading programs represent projectbased GHG emissions reductions outside the sect or or sectors regulated by the program. 45
Emissions reductions achieved th rough eligible offset project s are awarded allowances or “credits” that may be used by an affected sour ce to meet a portion of its allowance compliance obligation. For example, under the RGGI program “CO 2 offset allowances” awarded for GHG
emissions reductions achieved thr ough approved offset projects ma y be used by affected sources to meet up to 3.3 percent of their CO 2 allowance compliance obligation. 46

.
The ability to use GHG emission offsets for compliance means that CO 2 emissions from EGUs regulated under the emission budget trading program may exceed the base CO 2 emissions budget established for the program. Offset allowances or credits are awarded in addition to the existing CO 2 emission budget, in exchange for CO 2 -equivalent emissions reductions achieved

44 This marginal abatement co st curve would be applied in a similar manne r as marginal abatement cost curves are applied for GHG emission offsets in modeling analyses of emission budget trading programs. Form a modeling perspective, emission reductions from other sectors could be used by affected EGUs to demonstrate compliance with the emission limit. When economic to do so, emission reductions from affected EGUs would be foregone and replaced by emission reductions from emi ssion sources in other sectors that are also subject to the multi-sector emission budget trading program. 45 “Offsets” as used in the context of CO 2 or GHG emissions budget trading prog rams are distinct from offsets in the NSR permitting context under the CAA, where in certain inst ances emissions of a criteria pollutant from a proposed new facility must be offset with creditable emissions reduc tions at an existing facility, if the state or jurisdiction where the proposed facility would be located is in non-attainment status for the pollutant. 46 This percentage increases to five and ten percent of a CO 2 allowance compliance obligation at specified $7 and $10 price triggers, respectively.40 outside the capped emissions sector. 47 Consequently, the use of offsets by affected sources to meet a portion of their compliance obligation under an emission budget trading program could result in higher projected CO 2 emissions from affected EGUs in a state plan, because the use of offsets functionally expands the CO 2 emission budget for affected EGUs. This allows affected
EGUs to emit more CO 2 while meeting their compliance obligation under the emission budget trading program, in exchange for CO 2 -equivalent emissions reducti ons achieved outside of the affected source category. As a re sult, to properly project the CO 2 emissions from affected EGUs in a state plan that includes an emissions budge t trading program that allows for the use of offsets, it is necessary for modeling to also pr oject the extent to which offsets are used by affected EGUs for compliance. 48

Under this approach, stat e plans would ignore the CO 2 -equivalent emissions reductions projected to be achieved through offsets, when projecting the CO 2 emissions performance that will be achieved by the affected EGU source cate gory through implementation of the state plan. This does not mean that an emission budget tradi ng program included in a state plan could not include an offset component. Rather, when demonstrating emission performance by affected EGUs, the projected CO 2 emissions or weighted average CO 2 emission rate for affected EGUs under the state plan would not in corporate a credit for the CO 2 -equivalent emissions reductions represented by offset allowances or credits us ed by affected EGUs for compliance with the emission budget trading program. 49

2. Multi-State Emission Trading Programs
Emission budget trading programs may be mu lti-state in nature. For such programs, emissions reductions are achieved on a region al, rather than a state-by-state basis.

47 A key criterion that must be met for the award of offset allowances or credits is a demonstration that the offset project is “additional” (i.e., that it would not have occurred absent the incentive provided through the award of the offset allowance or credit). 48 Existing capacity expansion and dispatch planning models can project the use of offsets for compliance based on specified offset marginal abatement su pply curves, which represent the amount of offset credits/allowances assumed to be available from different categ ories of offset projects at differe nt GHG emissions abatement costs. 49 In other words, the projected CO 2 emissions or weighted average CO 2 emission rate for affected EGUs would be based on the direct emissions from these EG Us alone, with no calculation of “net” EGU CO 2 emissions that factor in the CO 2 -equivalent emissions reductions represented by offset credits or allowances used by an EGU to meet a portion of its compliance obligation.41 For example, in the multi-state Regional Greenhouse Gas Initiative (RGGI) emission budget trading program, individual partic ipating states have established CO 2 emission budgets in state regulations. However, there is no requirement limiting total CO 2 emissions from affected
sources in an individual state. State regulations include recipr ocity provisions allowing emission
sources to use CO 2 allowances issued by anot her participating state for compliance with the state program. This provides for state-to-state CO 2 allowance flows (and the potential for differences in state-by-state CO 2 emissions relative to state emi ssions budgets) based on where emission
sources determine it is most economical to achieve CO 2 emissions reductions. However, in aggregate, the CO 2 emission budgets in each of the partic ipating state regulations establish a regional cap on CO 2 emissions from affected EGUs. As a result, while a multi-state emission budget trading program may be projected to result in CO 2 emissions from affected EGUs
consistent with a multi-state mass-based CO 2 emission performance goal, the CO 2 emissions outcomes may vary by state. This necessitates evaluating a multi-state emission budget trading program as a whole, because the individual regulati ons of participating states function together as single integrated program.

To address these issues, states particip ating in a multi-state emission budget trading program would jointly demonstrate that the multi-s tate program is achieving the required level of
CO 2 emission performance on a multi-state basis, based on the CO 2 emission performance of all affected EGUs in the multi-state group implementing the program.

Some state emission budget trading program s also include international partner jurisdictions. 50 In such instances, the program could be treated in a similar fashion as a multistate program that involves only U.S. states. In this instance, emission pr ojections evaluating an international program would incl ude all jurisdictions participa ting in the program, but emission performance for state plans would be assessed based only on the CO 2 emission performance of affected EGUs in the subset of the progr am represented by U.S. states. Although the CO 2 emission performance of EGUs (or other emission sources) in a foreign country would not be addressed in the state plan, the entire international program woul d be evaluated as part of the

50 Currently, the EPA is only aware of one such instance, which is the linkage of the California GHG emission budget trading program with a similar program in Quebec.42 emission projection included in the state plan. Th is would be necessary in order to project
international allowance flows and CO 2 emissions across all participating jurisdictions, as these cross-jurisdictional flows would impact projected CO 2 emissions from affected EGUs in U.S.

states.43 VI. Process Considerations
As discussed in the preamble, in section V III.F.7, the credibility of state plans under section 111(d) will depend in large part on ensuring credible and consistent emission performance projections in state plans. Therefore, the use of appropriate methods, tools, and assumptions for such projections is critical. Furt hermore, considerations for projecting emission performance under a state plan will differ de pending on the type of plan. This includes differences in how inputs to projections are de rived; how projections are conducted, including tools and methods; and how aspects of a plan are represented in these projections.

In the preamble, the EPA seeks comment on whether the EPA should develop guidance that describes acceptable projecti on approaches, tools, and methods for use in an approvable plan, as well as provide techni cal resources for conducting projec tions. This section of the TSD
elaborates on these considerations.

A. Provision of the EPA Guidance
One approach to address these considerati ons is for the EPA to provide guidance for
EGU CO 2 emission projections included in state pl ans. Such guidance could include default modeling assumptions, or data sources for key as sumptions. State modeling projections included in a state plan could include assumptions th at deviate from the EPA’s recommended default assumptions, but a state plan would justify th e reason for using altern ative assumptions. The EPA technical guidance could specify recommen ded reference case assumptions for use with modeling or EGU utilization growth tools, for example:

 Electricity load growth projec tions (energy and peak demand)

 Fuel supply, delivery, and pricing assumptions

 Cost and performance of electr ic generating technologies

 Cost and performance of pollution control equipment44  EGU firm builds and retirements (those scheduled with a regional transmission organization or independent system operator (RTO/ISO) 51

 Transmission capability and ISO/RTO transmission expansion plans

 Applicable federal regulations (other than the EPA emission guidelines)

 Applicable state regulations and programs (oth er than the alternative standards that are included in the state plan)

It would be necessary in many instances to include assumptions about other state programs implemented by neighboring states in the same region. This would be especially
relevant for states that are located within the same electric power pool (or adjoining power pools) that are administered by a common RTO/ISO. To address this need, the EPA technical guidance could provide documentation of state programs and policies included in a reference case, as well as those that are eligible for in clusion in a state plan as alternative standards. The guidance could compile information about state programs and pr ovide model input assumptions related to these programs (e.g., MWh of electric generation need ed to meet a state renewable portfolio standard). 52 The EPA might also play a role in faci litating coordination am ong states as they develop their plans, to ha rmonize regional assumptions.

ISOs and RTOs, in discussions with the EP A have also offered to support states in evaluating the emission performance of state pl ans on a regional basis. The ISO/RTO Council, an organization of electric grid operators, has suggested that ISOs a nd RTOs could provide analytic support to help states develop and implement their plans. The ISOs and RTOs have the capability to model the system-wide effects of indi vidual state plans. Providing assistance in this way, they felt, would allow states with borders that fall within an RTO or ISO footprint to assess the system-wide impacts of poten tial state plan approaches. In addition, as the state implements

51 ISOs and RTOs are independent organizations that admini ster a regional electric powe r pool (EGU dispatch and electricity transmission systems) , and often also administer related wholesal e electricity markets for electric energy and capacity. 52 EPA’s manual, Roadmap for Incorporating Energy Efficiency/Re newable Energy Policies and Programs into State Implementation Plans/Tribal Implementation Plans (July 2012), could potentially support and be expanded upon to develop this component of EPA technical modelin g guidance. In particular, s ee Appendix I: EPA’s Draft Methodology for Estimating Energy Impacts of EE/ RE Policies. The draft manual is available at http://www.epa.gov/airquality/eere.html . State environmental regulations ad dressing EGUs are itemized in the modeling documentation for the EPA IPM Base Case v.5.13.45 its plan, ISO/RTO analytic support would allow the state to monitor the effects of its plan on the regional electricity system. ISO/RTO analytic capability could help states assure that their plans are consistent with region-wide system reliab ility. The ISO/RTO Council suggested that the EPA ask states to consult with the applicable IS O/RTO in developing th eir state plans.

B. Party that Translates the Rate -Based Goal to a Mass-Based Goal
In the preamble, in sect ion VIII.F.7, The EPA seeks comment on whether it should develop guidance that describes a cceptable projection approaches, tools, and methods for use in an approvable plan, as well as provide t echnical resources for conducting projections.

One consideration for state pl ans that use a mass-based CO 2 emission performance goal is the party that conducts the tr anslation of the rate-based CO 2 emission performance goal in the emission guidelines to a mass-based goal—either the EPA or the state. In the preamble, in section VIII.D.3, the EPA seeks comment on whether to assist states that seek to translate the rate-based goal into a mass-based goal.

One approach is for the EPA to provide a pr esumptive translation of the state-specific
rate-based CO 2 emission performance goal to an equivale nt mass-based goal for all states, for those states that request it, and/or for multi-state regions. This could include default modeling assumptions and results of modeling runs for a Reference Case Scenario and an EPA MassBased CO 2 Emission Goal Policy Scenario , as described above in section III.B. A state could utilize the presumptive mass-based CO 2 emission performance goal for the state or multi-state region identified through these EPA modeling runs. If a state proposed modifications to EPA default modeling assumptions, it would need to ju stify these modifications as part of the CO2 emission projection included in its state plan, an d present an emission pr ojection that supports a proposed modified mass-based CO 2 emission performance goal.

Another approach is for the EPA to provide guidance for states to use in translating a rate-based goal to a mass-based goal. This coul d include information about acceptable analytical methods and tools, as well as default input a ssumptions for key parameters that will likely influence projections, such as el ectricity load forecasts and proj ected fossil fuel prices. Under this approach, the EPA might also provide a co ordinating function in ad dressing the assumptions46 applied by multiple states within a grid re gion, acknowledging that assumptions about state programs across a broader grid region that are in cluded in an analysis scenario will influence projections of CO 2 emissions by affected EGUs in any particular state.

Under this approach, states could deviate from these default methods and assumptions with justification. Following the guidance could provide a streamlined path for the EPA approval of emissions projections, but states would still have flexibility to use other approaches, which the
EPA would review.Technical Support Document (TSD) for

Carbon Pollution Emission Guidel ines for Existing Stationary Sources: Electric Utility Generating Units

Docket ID No. EPA

- HQ

- OAR

- 2013

- 0602



# State Plan Considerations

U.S. Environmental Protection A gency Office of Air and Radiation

June 20142 Table of Contents

I. Introduction

................................ ................................ ................................ ........................ 3 II. Desc ription of State Plan Pathways

................................ ................................ .................. 5

A. Direct Emission Limits

................................ ................................ ............................. 7 B. Portfolio Approach

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

......................... 1 3

A. Parties Regulated by the State other than Affected EGUs

................................ ...... 1 4 B. Private or Public Third

- Party Entity n ot Regulated by the State

............................ 1 6 C. State Agency, Authority, or Entity

................................ ................................ .......... 1 7 D . Multi

- State Approaches

................................ ................................ .......................... 1 8 IV. Incorporating End

- Use Energy Efficiency and Renewable Ene rgy Programs and Measures under a Rate

- Based Approach

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

- Use Energy Efficiency and Renewable Energy

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

................................ ............ 21 C. Methods and Too ls for Quantifying Avoided CO 2 Emissions from End

- Use Energy Efficiency and Renewable Energy

................................ ................................ ......... 2 4 V. Quantification, Monitoring, and Verification of End

- Use Energy Efficiency and Renewable Energy Programs and Measures

................................ ................................ . 34 A. Quantification, Monitoring, and Verif ication for End

- Use Energy Efficiency

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

... 60 VI. Reporting and Recordkeeping for End

- Use Energy Efficiency and Renewable Energy Programs and Measures

................................ ................................ .................... 75 A. Reporting for End

- Use Energ y Efficiency Programs and Measures

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

................................ ... 78 VII. Treatment of Interstate Emission Effects

................................ ................................ ...... 84

A. Background

................................ ................................ ................................ ............ 85 B. Summary of Possible Approaches for Treatment of Interstate Emission Effects

.. 87 VIII. Appendix

................................ ................................ ................................ ........................... 973

I

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

 Description of state plan pathways

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

 Enforceability cons iderations under different plan scenarios

o Summary of potential enforceable mechanisms under different state plan
scenarios

 Incorporating energy efficiency and r enewable energy (EE/RE) requirements and

programs in state plans, including:

o Options for adjust ing EGU CO 2 emission rates based on the effect of EE/RE requirements and programs

o Methods for estimating avoided CO 2 emissions that result from EE/RE requirements and programs , for use in projecting emi s sion perform a nce under a

state plan and in ex post ad justment of CO 2 emission rates during plan implementation

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

o Survey of quantification, monitoring, and verification under existing state and utility EE/RE requirements and progra ms4 o Discussion of possible approaches for minimum requirements or guidance for quantification, monitoring, and verification for EE/RE requirements and programs included in state plans, building off existing state processes and infrastructure

o Discussion of a reas where supplemental information would be useful for estimating avoided CO 2 emissions from EE/RE requirements and programs

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

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

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

o Discu ssion of areas where supplemental information would be useful for estimating avoided CO 2 emissions from EE/RE requirements and programs

 Treatment of interstate emission effects

o Further elaboration of proposed approaches and alternatives discussed in the

pr eamble

It should be noted that the preamble discusses, and solicits comment on, legal issues concerning whether CAA section 111(d) authorizes some of the types of state plans described in this TSD and whether it authorizes state plans to include some of t hese types of measures

. This TSD does not further discuss those legal issues, but solely for the purpose of describing all of the available types of state plans and measures, assumes that all of them are authorized under CAA section 111(d).5

II. Description of State Plan Pathways
As discussed in the preamble, the EPA is proposing a state plan approach that could accommodate a diverse set of state requirements, programs, and measures, through two basic approaches

– direct emission limits and a po rtfolio approach. These two basic approaches provide four distinct state plan “pathways” under CAA section 111(d). These pathways include:

 Rate

- based CO 2 emission limits applied to affected EGUs;

 Mass

- based CO 2 emission limits applied to affected EGUs;

 A state

- driven portfolio approach

 A utility

- driven portfolio approach

Under this flexible approach, a state plan could include a combination of measures that reduce
CO 2 emissions at affected EGUs through the application of emission limits as well as measu res that involve actions within the interconnected electricity system that reduce utilization at affected EGUs and thereby avoid EGU CO 2 emissions. Examples of these latter measures include, among others, end

- use energy efficiency resource standards and re newable energy portfolio standards, as well as certain components of utility integrated resource plans

. A state could either rely solely
on CO 2 emission limits that are enforceable against affected EGUs or, alternatively, rely on a portfolio approach, whic h would include those limits as well as oth er enforceable measures.
Table 1 provides practical examples of possible state plan approaches under each of these pathways, which are discussed in more detail below.

This section elaborates the different plan ap proaches that are discussed in section VIII. B of the preamble , to provide context for the applied considerations that are discussed throughout
the remainder of the TSD. In particular, some of these considerations apply to different types of state plan appr oaches. For example, section III of this TSD addresses enforceable legal mechanisms that might apply under different types of state plans , such as utility

- and state

- driven portfolio approaches, which would apply enforceable obligations to different entiti es. S ection IV
of this TSD applies to state plans that implement rate

- based CO 2 emission limits f or affected EGUs that also provide for the adjustment of CO 2 emission rate s based on the effect of6

enforceable end

- use energy efficiency and renewable energy r equirements and programs t hat are incorporated in a plan. Section V of this TSD add r esses quantification, monitoring, and
verification of end

- use energy efficiency and renewable energy programs and measures.
Considerations addressed in this section would a pply to states implementing a rate

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

- use energy efficiency and renewable energy, as well as states implementing utility

- or state

driven portfolio app roaches that incorporate end

- use energy efficiency and renewable energy requirements and programs. Likewise, section VI of this TSD addresses considerations for reporting and recordkeeping for end

- use energy efficiency and renewable energy requirements
and programs , which would apply for these types of state plans

.
Table 1. Different Illustrative Plan Approaches7

A

. Direct Emission Limits
The first basic state plan approach is CO 2 emission limits that apply directly to affected EGUs, and includes t wo pathways: 1.) rate

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

- based CO 2 emission limits applied to affected EGUs. For both types of emission limits, end

- use energy efficiency and renewable energy measures that avoid EGU CO 2 emissio ns could be a major component of a state’s overall strategy for cost

- effectively reducing EGU CO 2 emissions

.

1

. Rate

- Based CO 2 Emission Limits Applied to Affected EGUs

Rate

- based emission limits would apply a lb CO 2 /MWh emission limit to affected EGUs. Depending on a state ’s approach, complianc e flexibility could be provided through different mechanisms, such as averaging among affected sources, or the use of tradable credits for avoided
CO 2 emissions resulting from end

- use energy efficiency and renewabl e energy measures as discussed below

. I n the case of the latter approach , such credits could be used by an affected EGU to adjust its CO 2 emission rate when demonstrating compliance with a rate

- based emission
limit. 1 Rate

- based emission limits could be imp lemented on a state

- by

- state basis, or through
multi

- state averaging or trading. Rate

- based emission limits might also be a component of a portfolio approach (described below), where the emission rate limit would not assure full achievement of the required level of emission performance specified for affected EGUs in the state plan, in which case the emission limit would be supplemented with other enforceable

measures.

Rate

- based emissions limits could incorporate end

- use energy efficiency and renewable

en ergy measures that avoid EGU CO 2 emissions, through an administrative adjustment by the state or tradable crediting system. 2 These adjustment credits could be used by an affected EGU to

1 Section IV of thi s TSD discusses possible approaches for such adjustments. 2 Under a tradable credit system, a state would issue adjustment credits based on avoided CO 2 emissions achieved through end

- use energy efficiency and renewable energy measures. EGUs could then appl y these tradable adjustment credits when demonstrating compliance with a rate

- based CO 2 emission limit. These tradable credits might be issued to affected EGUs for free or through purchase. Alternatively, end

- use energy efficiency and renewable energy acti ons undertaken by private parties (including EGU owners and operators) might be eligible for the issuance of adjustment credits. Under an administrative adjustment approach, a state program administrator might administratively adjust an affected EGU’s CO 2 emission rate based on avoided CO 2 emissions achieved8

comply with the rate

- based emission limit, by adjusting the unit’s rep orted CO 2 emission rate. 3 Under this approach, end

- use energy efficiency and renewable energy measures that avoid EGU
CO 2 emissions would be enforceable components of a state plan. These actions would need to be enforceable components of a state plan to pr ovide assurance that a sufficient amount of adjustment credits will be available to facilitate EGU compliance with the emission rate limit,
and that end

- use energy efficiency and renewable energy measures that generate adjustment credits are properly quant ified, monitored, and verified. 4

2

. Mass

- Based CO 2 Emission Limits Applied to Affected EGUs

Mass

- based emission limits would apply either an individual limit on CO 2 tons emitted
from an affected EGU or establish a finite CO 2 emissions budget for a group of affected EGUs. The latter approach is typically implemented through a tradable allowance system.

With mass

- based emission limits, end

- use energy efficiency measures that avoid EGU
CO 2 emissions could be a major component of a state’s overall strategy for cost

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

cost

- effectively achieve the CO 2 emissions l imits, or to achieve other policy goals, but CO 2 emissions performance would be assured through the enforceable limit on mass emissions from
affected EGUs.

B

. Portfolio Approach
The second basic state plan approach uses a portfolio of actions, in which a state plan includes multiple programs and measures that are designed to achieve either a rate

- based or

mass

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

through state end

- use energy efficiency and renewable energy deployment programs or utility compliance with energy efficiency resource standards or renewable energy portfolio standards. These adjustment s might be apportioned to affected EGUs based on a predetermined metric. Affected EGUs would then begin with an adjusted CO 2 emission rate when considering additional actions necessary for compliance with the rate

- based CO 2 emission limit. 3 Section IV of this TSD discusses possible approaches for such adjustments. 4 Section V of this TSD addresses considerations for quantification, monitoring, and verification of end

- use energy efficiency and renewable energy measures.9

pathways: 1.) a state

- driven portfolio approach; and 2.) a utility

- d riven portfolio approach. A portfolio approach would include emission limits for affected EGUs along with other enforceable
end

- use energy efficiency and renewable energy measures that avoid EGU CO 2 emissions. A portfolio approach could be state

- driven or utility

- driven, depending on the utility regulatory
structure in a state.

In general, a portfolio approach is distinguished from an emission limit approach by the fact that achievement of the full level of required emission performance for affected EGUs specified in the plan is not ensured through the application of direct emission limits that apply to
affected EGUs.

A portfolio approach would include both direct emission limits that apply to affected
EGUs and other indirect measures that avoid EGU CO 2 e missions. Under a portfolio approach,
end

- use energy efficiency and renewable energy measures that avoid EGU CO 2 emissions would be enforceable components of a state plan. This would be necessary because the emission limit applied directly to affected EGUs would not assure full achievement of the required level of emission performance specified in the state plan. 5

As discussed below, due to differences in state utility regulatory structure, a portfolio approach implemented in a restructured state with reta il competition will likely look quite different from one implemented in a state with vertically integrated, regulated electric utilities. This includes the process for developing the portfolio approach, the mechanisms for implementing it, the responsible p arties, and the regulatory and legal relationships among parties and state regulators.

1

. State

- Driven Portfolio Approach

A state

- driven portfolio approach

– rather than a utility

- driven approach

– is more likely to be adopted in a state with a restruct ured electricity sector. In these states, rate

- regulated

5 Under a portfolio approach, either a rate

- based or mass

- based emission limit might be applied. Such plans might also include application of a direct emission limit to a subset of affected EGUs. Both scenarios would necessitate inclusion of supplemental measures, such as end

- use energy effi ciency and renewable energy, or other measures that directly apply to affected EGUs (e.g., repowering or retirement of one or more high

- emitting EGUs), in order to achieve the required level of emission performance for affected EGUs specified in the state plan.10

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

- utility entities can supply retail customers with electricity. 6 Electric
dis tribution utilities in these states typically purchase electricity from competitive wholesale markets. As a result, utilities in these states typically do not engage in a utility integrated resource planning (IRP) process. IRP processes, which are a natura l fit for implementing a portfolio approach, are much more common in states with regulated vertically integrated utilities that own and operate electric generating assets.

In restructured states, policies for increasing end

- use energy efficiency and rene wable energy are often established through regulations that apply to electric distribution utilities, such
as end

- use energy efficiency resource standards and renewable portfolio standards. Many of these states have also established independent non

- profit entities to administer end

- use energy efficiency and renewable energy deployment programs funded through regulated electricity

rates.

Under a state

- driven portfolio approach a mix of entities might have enforceable obligations under a state plan. This inc ludes owners and operators of affected EGUs subject to direct emission limits, as well as electric distribution utilities, private or public third

- party entities, and state agencies or authorities that administer end

- use energy efficiency and
renewable ene rgy deployment programs or are subject to portfolio requirements.

2

. Utility

- Driven Portfolio Approach
A state with vertically integrated, state

- regulated electric utilities is more likely to adopt a utility

- driven portfolio approach . In such states, pr ivate utilities own and operate electric generation, transmission, and distribution systems necessary to supply retail customers with electricity. 7 These utilities are overseen by state public utility commissions that approve utility capital investments an d oversee utility operations, and allow utilities to recover approved

6 In some restructured states, the holding company that owns the distribution utility may also own generating assets which are operated on a competitive basis. In these instances, there typically are legal provisions in place that mandate the indepen dent management and operation of generation and distribution assets. 7 In some instances these regulated utilities may supplement electric generation with purchases through wholesale electricity markets and may also sell surplus generation in these wholesa le markets on a competitive basis.11

investments and operating costs, along with a specified financial rate of return, through regulated retail electricity rates. State utility commissions often require regulated utilities to engage in an integrated resource planning (IRP) process, which seeks to identify the least

- cost set of resources available to provide electricity to retail customers over a multi

- year period, and often includes
evaluation of measures such as end

- use ene rgy efficiency, demand

- side management, and renewable energy. 8 Once an IRP is approved by a state public utility commission, a utility’s cost recovery and rate of return is often linked to identified measures and metrics in the IRP. 9

Under a utility

- drive n portfolio approach, a vertically integrated utility would develop and implement a portfolio of measures designed to meet the rate

- based or mass

- based emission performance level for its affected EGUs specified in the state plan. This plan would likely be developed and approved through an IRP

- like process overseen by the state public utility
commission. If there is more than one rate

- regulated electric utility in the state, the state might apportion the state emission performance level for affected EGUs amo ng utilities.

A utility plan under this approach might rely heavily on end

- use energy efficiency and renewable energy actions, but also might focus on direct actions at affected EGUs, such as repowering to fire a lower

- carbon fuel or retirement of high

- em itting units. Such plans might also include direct emission limits on affected EGUs, or implementation of an environmental dispatch approach that incorporates CO 2 emission rate into the dispatch protocol used by the utility to schedule electric generation. 10

Under a utility

- driven portfolio approach, the entire suite of obligations under the plan would be enforceable against the utility company, which would also be an owner and operator of
affected EGUs. If there are other affected EGUs in the state that ar e not owned and operated by a

8 Depending on the state, an IRP process may also assess factors such as fuel diversity and environmental performance, among others, when identifying the least

- cost mix of resources for a utility. 9 In some cases, an IRP prescribes or authorizes specific actions. In others, an IRP serves as a guide for the utility and the public utility commission when evaluating acquisition or implementation of specific utility resources or programs. In such cases, the specific resource o r program is approved through a PUC order that authorizes or requires actions and identifies performance obligations. These orders may or may not be fully consistent with provisions in an IRP. 10 Vertically integrated utilities, even if they operate within the footprint of a competitive wholesale electricity market, may self

- schedule generation assets.12

vertically integrated utility , a state plan might need to include other measures that address CO 2 emission performance by these affected EGUs.

A similar approach could be taken by municipally owned utilities or utility cooper atives, which often also engage in an IRP process. However, state public utility commissions (PUCs) often do not regulate these utilities . As a result, implementation of a portfolio approach by these entities would introduce practical enforceability consid erations under a state plan.13

III. Enforceability Considerations under Different State Plan Scenarios
As discussed in the preamble of th e proposal, in section VIII.F.1, a state plan must
include enforceable measures. To ensure that its plan is enforceable, a state will need to:

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

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

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

As discussed in the preamble, responsible e ntities in an approvable state plan may include an owner or operator of an affected EGU, other entities with responsibilities assigned by a state, or the state itself. Other entities might include an entity that is regulated by the state, such as an
electr ic distribution utility, or a private or public third

- party entity. State responsibility might include obligations that are assumed directly by a state agency, authority, or other state entity to carry out aspects of a state plan.

While this approach prov ides states with broad discretion to develop plans that best suit their circumstances and policy objectives, assigning responsibility to other parties regulated by the state, private or public third

- party entities, or state entities raises enforceability

c onsiderations. This section discusses how the general enforceability approach discussed in the preamble , and described above, might apply in practice under different state plan approaches.

This section describes possible scenarios of responsible entities and legal mechanisms and approaches that might be used to address enforceability considerations under different types of state plans. These scenarios were developed to capture t he range of entities that are currently implementing end

- use energy efficiency and renewable energy deployment programs in states , or are subject to states requirements such as end

- use energy efficiency resource standards (EERS) or renewable portfolio standards (RPS). For each of these examples, this section describes current legal r elationships between these entities and the state, and discusses possible legal14

instruments that might provide the state with the authority to ensure that obligations in a state plan are met and to address failure to meet those obligations. The mechanisms discussed take different forms, but would specify the three elements described above: obligations, compliance demonstration, and enforcement mechanisms. This section also discusses enforceability considerations in cases where states act jointly through a m ulti

- state plan.

A. Parties Regulated by the State other than Affected EGUs
One likely state plan scenario involves inclusion of enforceable obligations for state

regulated entities other than affected EGUs. An example of a state

- regulated entity that is n ot an owner or operator of affected EGUs may be an electric distribution utility. 11 These entities are typically regulated by a state public utility commission. An example of an enforceable state plan measure that might apply to an electric distribution uti lity is a compliance obligation under a
state end

- use energy efficiency resource standard (EERS) or renewable portfolio standard (RPS), or implementation of incentive programs for the deployment of end

- use energy efficiency and renewable energy technologie s.

Another example is where a vertically integrated, state

- regulated utility implements a portfolio of enforceable actions under a state plan, which may include actions that apply directly
to affected EGUs as well other actions such as end

- use energy eff iciency and renewable energy deployment programs. While vertically integrated utilities may own and operate affected EGUs, some of the measures implemented may require different enforceability mechanisms than an emission limit applied to an affected EGU.

11 Electric distribution utilities are also often referred to as local distribution companies (LDCs). Here we refer to an electric distribution utility as an e ntity that owns and operates an electric distribution network but is not the owner and operator of EGUs. As discussed further, vertically integrated utilities own and operate electric distribution networks as well as EGUs.15

1

. Electric Distribution Utility with Obligations to Meet an EERS or RPS Pursuant to State Regulations

EERS and RPS requirements are typically implemented through state regulations, but may also be implemented through a public utility commission o rder. State EERS and RPS regulations provide legal instruments generally comparable in enforceability to regulatory emission limits applied to EGUs. These regulations typically specify compliance obligations, reporting, and enforcement. However, many state RPS regulations and some EERS regulations include alternative compliance payment (ACP) provisions that provide the utility with the option of making a payment in lieu of full compliance with the portfolio requirement. Thus, state EERS and RPS mandates may not guarantee achievement of a given level of end

- use energy efficiency or renewable energy deployment during a plan performance period. 12

2

. Vertically Integrated Electric Utility with Obligations under a State

- Approved Integrated Resource Plan

A utili ty integrated resource plan (IRP) may include a number of direct and indirect
actions that affect EGU CO 2 emissions, and may also include compliance with EERS and RPS regulations. Broadly, IRPs may prescribe or authorize actions for which utilities can rec over capital investments and operating costs through regulated retail electricity rates. 13 This creates strong financial incentives for implementing an action, but may not mandate an action.

For a state plan under this scenario, an enforceability considera tion is whether an IRP, and related public utility commission orders, must include additional requirements to implement certain actions, beyond denial of rate recovery or a change to utility tariffs if a utility fails to

12 We note that some direct emissi on limits for CO 2 emissions include somewhat similar provisions. For example, both the RGGI state CO 2 emission budget trading programs and the California GHG emission budget trading program include cost containment provisions where more emission allowances are made available to affected sources at certain allowance price thresholds. In both these instances, such relevant characteristics of the state regulations would need to be taken into account when projecting the CO 2 emission performance that will be ach ieved by affected EGUs under the state plan. 13 In some cases, an IRP prescribes or authorizes specific actions. In others, an IRP serves as a guide for the utility and the public utility commission when evaluating acquisition or implementation of specific utility resources or programs. In such cases, the specific resource or program is approved through a PUC order that authorizes or requires actions and identifies performance obligations. These orders may or may not be fully consistent with provisions in an IRP.16

meet specified obligations in the I RP. If so, this may require state legislation to provide additional authority to state public utility commissions in some states, or confer additional authority to other agencies (e.g., a state environmental agency).

B

. Private or Public Third

- Party Entit y not Regulated by the State
Another state plan scenario involves public or private third

- party entities with enforceable obligations under a state plan. A private or public third

- party entity could be a utility entity that is not regulated by a state pub lic utility commission, such as a municipal utility or a utility cooperative. 14 It could also be a private non

- profit entity established to administer end

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

expen d electricity ratepayer funds, such non

- profit entities are created by state legislation and overseen by state public utility commissions or state

- regulated private utilities.

An appropriate legal instrument or agreement applicable to such entities includ ed in a state plan might include legal arrangements similar to those currently used to establish independent entities that expend electricity ratepayer dollars in multiple states. For entities not subject to state oversight, such a mechanism might also inc lude mechanisms where an entity voluntarily submits to the authority of a state, pursuant to state statutory or regulatory authority specified in a state plan. Such agreements might be attached to a funding source. For example, the entity would voluntarily submit to such authority as a condition of receiving certain funds, such as state appropriated funds or funds collected through state

- regulated electricity rates. Alternatively, a municipal utility or utility cooperative might voluntarily submit to state authority as a condition of the state agreeing to let the entity implement a portfolio approach, in lieu of the application of certain direct CO 2 emission limits for affected EGUs owned and operated by such entities through a state regulation. In some case s, new state statutory authority might be enacted to support a state plan, specifying enforceable obligations for these private or public third

- party entities under the plan.

14 Here, “not regulated” refers to regulation of electricity rates by a state public utility commission. To the extent that such entities are owners and operators of affected EGUs, these EGUs may be subject to state environmental and other regulations . In some cases these utility entities are also subject to state EERS and RPS regulations, as specified under state law. 15 Examples include the Energy Trust of Oregon, the Delaware Sustainable Energy Utility, and Efficiency Vermont.17

An additional consideration is whether such legal instruments or agreements, if related to a renewable energy or end

- use energy efficiency deployment program, should specify a stable budget authority and funding source through each plan performance period. Such authority and funding might be necessary to ensure that suitable funds are made available to achieve the level of energy savings or renewable energy deployment projected in the state plan, which may be necessary to achieve the level of emission performance by affected EGUs that is projected will be achieved through implementatio n of the plan.

C

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

- use energy efficiency deployment programs. 16 In this scenario, the requirement for the state entity would be an enforceable component of the state plan.

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

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

An additional consideration is whether such l egal arrangements, if related to a renewable energy or end

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

16 A prominent example i s the New York State Energy Research and Development Authority (NYSERDA), which administers energy efficiency and renewable energy deployment programs. 17 We note that under the CAA, measures included in an approved 111(d) state plan would be federally enfo rceable by EPA, and that citizens would also have the ability to file citizen suits to compel enforcement of state plan obligations, under CAA Section 304 (42 U.S. Code Section 7604).18

authority and funding source through the plan performance period, or other provisions, to ensure that programs are impl emented as projected under the state plan.

D

. Multi

- State Approaches
As discussed in the preamble, in section VIII.F.1, m ulti

- state approaches introduce cross

cutting enforceability considerations.

For these multi

- state approaches, states would demon strate emission performance from affected EGUs in aggregate jointly with partner states. For states participating in a multi

- state approach, the individual state performance goals in the emission guidelines would be replaced with an equivalent multi

- state performance goal. For example, states taking a rate

- based approach would demonstrate that all affected EGUs subject to the multi

- state plan achieve a weighted average CO 2 emission rate that is consistent, in aggregate, with an aggregation of the

state

- spec ific rate

- based CO 2 emission performance goals established in the emission guidelines that apply to each of the participating states. If states were taking a mass

- based approach, participating states would demonstrate that all affected EGUs subject to the multi

- state plan emit a total tonnage of CO 2 emissions consistent with a translated multi

- state mass

- based goal . This
multi

- state mass

- based goal would be base d on translation of an aggregation of the state

- specific

rate

- based CO 2 emission performance goal s established in the emission guidelines that apply to each of the participating states.

1

. Multi

- State Emission Budget or Rate

- Based Emission Trading Programs
The Regional Greenhouse Gas Initiative (RGGI) is an example of a multi

- state approach to regu lation of CO 2 emissions. Through this initiative, nine states are currently implementing
coordinated CO 2 emission budget trading programs. The program works as a coordinated regional whole through a shared emission and allowance tracking system and allowan ce auction process, but is implemented in accordance with materially consistent stand

- alone state regulations and individual statutory authority. These regulations recognize CO 2 allowances issued by other participating states for use by affected EGUs when complying with each state’s emission limitation, but contain all the necessary components to administer the program19

requirements on an individual state basis. 18 As a result, while the initiative is implemented regionally, each CO 2 emission budget trading pr ogram regulation is enforceable against affected EGUs at the state level and functions as a discrete program.

As a result, a multi

- state emission budget trading program approach, such as RGGI, is enforceable in practice at the state level. A multi

- state rate

- based emission trading program could
also be established in much the same manner as a multi

- state emission budget trading program,
and could therefore be enforceable at the state level. 19

2

. Multi

- State Portfolio Approaches

A multi

- state portfolio a pproach could introduce novel enforceability considerations. If it were based on interdependent emission reduction strategies among states that are not tied to emission limits that directly apply to affected EGUs, the emission performance of affected EGUs in one participating state may be dependent, in part, on actions taken in other participating states. If a state (or states) failed to implement commitments under the multi

- state plan, this raises the question of whether the EPA should address non

- performa nce of one or more participating states in the context of failure to achieve the required level of multi

- state emission performance under the plan, or instead enforce actions at the individual state level for those states that are failing to
meet commitmen ts under the multi

- state plan.

18 The emission limitation consists of a requirement to submit CO 2 allow ances equal to reported CO 2 emissions during a compliance period. While states have individual emission budgets, representing the total number of allowances issued for a given year that are available for allocation, there are no individual state emission l imits. The CO 2 emission constraint is regional, based on the sum of state CO 2 emission budgets. 19 Enforceability would be contingent, in part, on states having comparable enforcement mechanisms.20

I V. Incorporating End

- U se Energy Efficiency and Renewable Energy Programs and Measures under a Rate

- B ased Approach

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

- Use Energy Efficiency and Renewable Energy
As discussed in the preamble, in section VIII.F.3, the EPA is proposing that RE and
demand

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

- based plan approach. 20 M easures that avoid CO 2 emissions from affected EGUs, such as quantified and
verified end

- use energy savings and renewable energy generation, could be used to adjust the
CO 2 emission rate of an affected EGU when demonstrating compliance with a rate

- based CO 2 emission limit. Alter natively, a state could use the effect of such measures as a basis for administratively adjusting the average CO 2 emission rate of affected EGUs when demonstrating achievement of the required emission rate performance level in a state plan.

Under this ap proach, affected EGUs could comply with a rate

- based CO 2 emission limit through actions at the EGU, 21 as well as through the use of credits 22 for actions that occur elsewhere in the interconnected electricity system that avoid CO 2 emissions from affected EGU s. If a state is implementing a portfolio approach, then the state could administratively adjust the average CO 2 emission rate of affected EGUs through a similar process when demonstrating achievement of the required emission rate performance level in the state plan.

This section explores in depth the mechanics and implications of the different possible approaches for adjusting CO 2 emission rates that are summarized in the preamble. Aspects of this discussion may apply to both retrospective demonstration of CO 2 emission performance achieved by affected EGUs under an approved state plan and projections of CO 2 emission performance by affected EGUs included in a submitted state plan.

20 The EPA is also proposing that RE and demand

- side EE measur es could be used under a mass

- based portfolio approach in an approvable state plan. However, the focus of this section is limited to application of such measures under a rate

- based approach. 21 This could include an individual affected EGU or group of affec ted EGUs if a rate

- based averaging or trading approach is used. 22 These credits could be tradable, or represent non

- tradable credits administratively apportioned to affected EGUs. This latter approach effectively represents an administrative adjustment app lied by the state.21

B. Approaches for Adjusting EGU CO 2 Emission Rates
As discussed in the p reamble, c redits or adjustment to an EGU CO 2 emission rate, based
on the effect of RE and demand

- side EE programs and measures, might represent avoided MWh of electric generation or avoided tons of CO 2 emissions. 23 If adjustment or credits represent
avoided MWh, they would be added to the denominator of the lb CO 2 /MWh emission rate when determining an adjusted lb CO 2 /MWh emission rate. If adjustment or credits represent avoided
CO 2 emissions, they would be subtracted from the numerator when determining an ad justed lb
CO 2 /MWh emission rate. The approach chosen could affect the amount of credit or adjustment provided for RE and demand

- side EE programs and measures. These implications are discussed
below.

1

. Adjustment of CO 2 Emission Rate based on Avoided MWh
One approach is to adjust an EGU’s CO 2 emission rate based on avoided MWh of generation from an EGU, or cohort of EGUs, resulting from RE and demand

- side EE programs
and measures. 24 A MWh crediting or adjustment approach implicitly assumes that the avoid ed
CO 2 emissions come directly from the particular affected EGU (or group of EGUs) to which the adjustment or credits are applied. It assumes, in effect, that an additional emission

- free MWh is being generated by that respective EGU, and that the RE or dem and

- side EE measure reduces
CO 2 emissions from that individual EGU or group of EGUs. 25 In practice, the average or marginal CO 2 emission rate in the power pool or identified region

– representing the avoided
CO 2 emissions from the generating sources being d isplaced by a MWh of energy savings or a MWh of renewable energy generation

– could differ significantly from the calculated avoided
CO 2 emissions derived by adjusting the MWh output of an affected EGU. The following examples highlight these concepts.

23 The preamble solicits comment on the appropriateness of these different approaches, which are further elaborated in this section. 24 It should be noted that this was the process used by EPA for incorporating end

- use energy efficiency, r enewable energy, and nuclear energy when calculating state CO 2 emission performance goals for affected EGUs. As discussed in the preamble, states may have flexibility to use a different approach when demonstrating the effect of these measures in a rate

- bas ed state plan. 25 As a result, the assumed avoided CO 2 emissions from an individual MWh of energy savings or generation from renewable energy will differ based on the reported CO 2 emission rate of the individual EGU to which the MWh is applied as an adjustm ent to its MWh output.22

Exa mple 1 : A ssume an EGU with a stack emission rate of 1,500 lb CO 2 /MWh generates 1,000 MWh. Also assume that 1,000 emission

- free MWh credits for the effect of demand

- side EE measures are added to the denominator when calculating the EGU’s adjusted CO 2 emissi on rate. The adjusted CO 2 emission rate is 1,500,000 lb CO 2 divided by 2,000 MWh, which equals a
CO 2 emission rate of 750 lb CO 2 /MWh. In this example, each MWh credit represents 750 lb of
avoided CO 2 emissions.

Example 2 : The same calculation applied to an affected EGU with a 2,000 lb CO 2 /MWh rate would yield a different result. I n this instance the adjusted emission rate is 2,000,000 lb CO 2 divided by 2,000 MWh, which equals a CO 2 emission rate of 1,000 lb CO 2 /MWh. In this example, each MWh credit repres ents 1,000 lb of avoided CO 2 emissions

.

2

. Adjustment of CO 2 Emission Rate based on Avoided CO 2 Emissions
An alternative approach is to provide an adjustment to the CO 2 emission rate of an EGU, or cohort of EGUs, based on the estimated CO 2 emissions tha t are avoided in the power pool or identified region as a result of RE and demand

- side EE programs and measures. This approach acknowledges that the avoided CO 2 emissions may come from the electric power pool or other identified region as a whole, rather t han an individual EGU. The avoided CO 2 emissions are determined based on the MWh saved or generated, multiplied by a CO 2 emission rate for the power pool or region.

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

pow er pool, region, or state

. A marginal avoided emission rate represents the generation that is displaced at the margin for every MWh saved or generated through an RE or demand

- side EE program or measure. An average avoided emision rate is based on either al l fossil generation in a region or total generation. This approach assumes that every MWh saved or generated equally displaces generation from every generator in a power pool or region.

Another approach that has been suggested by some stakeholders is cre diting or adjustment based on the level of the rate

- based emission limit for affected EGUs (or the overall

rate

- based level of emission performance for affected EGUs specified in a state plan). For23

example, under this approach, if the emission rate limit w ere 1,500 lb CO 2 /MWh, one MWh of energy savings or renewable energy generation would result in a credit or adjustment representing 1,500 lb of CO 2 that could be subtracted from the numerator of an EGU’s CO 2 emis s ion rate. This approach assumes that affecte d EGUs jointly emit CO 2 from the stack on an average basis at this required compliance level (i.e., consistent with a “closed” averaging system), and that a MWh saved or generated avoids CO 2 emissions from affected EGUs at this average compliance level. 26

3

. Other Considerations

Some of the CO 2 emissions avoided through RE and demand

- side EE measures may be
from non

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

- fired EGU fleet, which also includes (or will includ e) existing non

- affected fossil fuel

- fired EGUs, such as simple

- cycle combustion turbines used to meet peak demand, as well as new
fossil fuel

- fired EGUs subject to emission standards under CAA section 111(b). Furthermore, as the fleet capital stock slowly turns over, affected EGUs under section 111(d) will comprise a slowly shrinking subset of the total fossil fuel

- fired EGU fleet. These dynamics may need to be addressed in a state plan when crediting or adjusting CO 2 emission rates of affected EGUs based
on the effects of RE and demand

- side EE measures. The approaches described in more detail later in this section may be able make these distinctions between affected and non

- affected fossil
fuel

- fired EGUs.

26 This outcome might be expected in a closed averaging system, without the use of crediting or adjustment for the avoided emission effects of RE and demand

- side EE measures. In this instance an EGU that emitted above the compliance r ate would need to average its performance with (or submit tradable credits obtained from) an EGU that performed below the required rate. On balance, all EGUs subject to the emission rate limit would perform at or below the compliance rate.24

C

. Methods and Tools for Quantifying Avoided CO 2 Emissions from End

- Use Energy Efficiency and Renewable Energy

1. Introduction

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

- use energy efficiency and renewable energy (EE/RE) programs, requ irements and

measures 27 in the electric sector

. These approaches range from the application of basic avoided
emission rates to using sophisticated electric sector models. 28 Annual average avoided emission rates have often been used for rough approximations o f CO 2 emissions avoided from reduced electric energy use. 29 An annual average avoided emission rate assumes that EE/RE programs and measures reduce electric generation from all generating types on a proportional basis consistent with the generation mix in a region

. A marginal emission rate represents the emission rate of an electric generating unit (EGU) or cohort of EGUs likely to be displaced by EE/RE measures (i.e., a marginal avoided emissions rate), based on the last unit(s) to come online to
meet elect ricity load and the first unit(s) to be brought offline when electricity load is reduced.

The primary question underlying estimating CO 2 emissions reductions from EE/RE measures is the determination of which electric generators will be displaced (i.e. , c ease generation or reduce generation output) in the presence of incremental EE/RE. This section briefly describes a range of avoided emission rates approaches, their underlying assumptions,
and considerations associated with the use of different avoided em ission rate approaches.

2

. Average Emission Rate Approach
An average emission rate (typically expressed in tons of CO 2 /MWh) is usually understood to mean the average of all generators’ emissions rates, weighted by annual generation. The rate (r avg ) is ca lculated as:

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

- efficient equipment or practices, or renewable energy generating resources. 28 Electric sector models include simulation dispatch models (i.e. production

- cost models) and capacity expansion planning models. 29 See, for example, EPA “Household Carbon Footprint Calculator,” available at http://www.epa.gov/cli matechange/ghgemissions/ind

- calculator.html

.25

Where :
e = annual emissions (tCO 2 ) from all sources i and g = annual generation (MWh) from all sources i

. Because the average emission rate puts the sum of all generation in the denominator (as MWh), including nu clear, hydroelectric, and renewable generating resources, the rate fundamentally assumes that EE/RE reduces all generating types by an equal proportion, regardless of their type or contribution to the margin. 30 EGUs are generally dispatched on an economic m erit order,
where the least

- cost EGUs (on a variable cost basis) are dispatched first, and higher cost resources are dispatched later. Since nuclear, hydro, wind, and solar resources operate at a very low cost, 31 they are generally dispatched before most fo ssil units. 32 Under current and historical operating conditions, there are few circumstances in which non

- fossil resources reduce output in the presence of lower demand. As a result, in states with a moderate contribution of non

- emitting
resources to total generation, the average emission rate may be lower than could reasonably be expected for reductions from EE/RE programs and measures. 33 Conversely, in states that have significant baseload fossil generation and few non

- emitting resources, a state

- average em ission rate may reflect an emission rate that is too high

. This may occur by incorporating emissions
from coal

- fired EGUs that are less likely to reduce generation with a reduction in electricity load, compared with other lower

- emitting fossil fuel

- fired E GUs

.

30 In other words, a two

- percent reduction in energy use would cause all EGUs in the system to reduce generation output by two percent, including coal, gas, nuclear, hydro, and renewable generating resources. 31 For representative variable costs for new EGU, see supporting documentation for the Electricity Market Module of the Annual Energy Outlook (AEO) 2013, table 8.2., “Cost and performance characteristics of new central station electricity generating technolo gies”. Geothermal, wind, and solar generating resources are assumed to have a variable operating cost of $0/MWh. Hydroelectric generating resources have an assumed variable operating cost of $2.60/MWh and incur no fuel cost, while nuclear generating resour ces have an assumed variable operating cost of $2.10/MWh (exclusive of fuel costs). In contrast, gas and coal units are assumed to have variable operating costs from $3

- $7/MWh (exclusive of fuel costs. 32 The exception is rare curtailment events for renewab le resources when more energy is produced than required, and due to operational constraints, where wind turbines are stalled to maintain system energy balance. Renewable energy generators, such as wind and solar, are sometimes referred to as “non

- dispatcha ble” resources, since the renewable energy resource is intermittent and these generators cannot be called upon to run when the renewable energy resource is unavailable. However, here we refer to economic dispatch of these resources at times when the

renewa ble energy resource is available. In these instances, these generators are often one of the first resources to be called upon, due to their low variable operating costs. 33 Counting hydroelectric, nuclear, and renewable resources in the denominator would re nder the emissions rate too low, and thus the avoided emissions smaller than actually realized.26

3

. Marginal Emission Rate Approach
A marginal emission rate represents the emission rate of the EGU or cohort of EGUs likely to be displaced by EE/RE ( i.e., an avoided emission rate). A marginal unit is the highest

cost unit dispatched at any point in time. 34 Under most circumstances, and at any given time, the marginal unit is the last unit to be brought online to meet electricity demand and the first unit to be brought offline when electricity load is reduced. Due to constraints on generating unit r amp
rates 35 and transmission availability, it is not uncommon for multiple units to be dispatched incrementally simultaneously, thus creating a cohort of marginal units. Marginal unit(s) change

on a moment

- to

- moment basis, determined by load requirements an d the variable cost of each unit available to generate another unit of power. A marginal unit can either be a unit brought online to meet load or may be an EGU that is already operating, but that is dispatched at a greater level of output to meet load.

Th e marginal emission rate ( r marginal ) can be expressed for any given hour ( t ) as a function
of the difference between two distinct cases

– the reference case ( i.e., in the absence of incremental EE/RE programs and measures) and the change case, where the EE /RE programs and measures have been implemented. A formula describing this rate is written as follows:

Where :
e ref and e EERE = emissions (tCO 2 ) from EGUs i in hour t in the reference case ( ref ) and the change case ( EERE ), respectively; and g ref and g EERE = generation (MWh) from EGUs i in hour t in the reference case ( ref ) and the change case ( EERE ), respectively.

34 See EPA’s Roadmap for Incorporating EE/RE Policies and Programs in State Implementation Plans: Appendix B, available at http://www.epa.gov/statelocalclimate/documents/pdf/overview_paper_4

- 28

- 2011.pdf 35 Ramp rate refers to the ability of an EGU to respond to increasing load, based on its ability to increase output. Ramp rates are typically determined by technology type, with some technologies, such as combustion turbines, able to more quickly increase output in response to increasing load.27

The magnitude of the EE/RE program and the EE/RE load impact shape 36 is a key element in determining marginal emissions reductions. In order to obtain a valid estimate of the emission reduction effect of an EE/RE program, an annual marginal avoided emission rate
should be calculated that reflects the EE/RE program’s load impact shape and magnitude. This annual marginal avoided emission rate may then be applied to other EE/RE programs with similar load impact shapes and magnitudes. The marginal emission rate is highly time s ensitive,

as are the impacts of EE/RE programs and measures. For example, the EGU that is on the margin and is most likely to be displaced from EE/RE in each hour of the year

. In addition, different EE/RE programs may have very different load impact shapes
, reducing energy requirements in different hours of the year. The interaction between the pattern of EGUs on the margin and the load impact shape of EE/RE programs and measures results in a specific marginal avoided emission rate. Applying an annual margi nal avoided emission rate calculated based on the impact of one specific set of EE/RE programs and measures to another set of EE/RE programs and measures that is substantively different in timing or magnitude of energy savings or generation (i.e ., with a d ifferent load impact shape and magnitude) may result in erroneous results ( i.e. the assumption that the wrong EGUs are displaced). 37

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

36 The load impact shape of an EE/RE program or measure is the hourly (or, if neces sary, daily or seasonal) pattern of either energy savings from an EE program or measure, or generation from an RE generator that is supplied to the grid. 37 For example, an EE program focused on measures that reduce peak electricity demand, such as more eff icient air conditioning, or a solar RE program, may result in significant reductions in electricity use from the grid during peak demand hours, and little electricity use reduction during overnight “trough” hours. In contrast, an industrial EE program may result in a relatively constant electricity load reduction over most hours. An EE program focused on peak reduction measures may reduce generating output from primarily peaking units, while an EE program targeting EE measures with a more constant load impa ct shape may significantly reduce baseload generation during overnight trough hours.28

4

. Methods and Tools for Estimating Avoid ed CO 2 Emission Rates and Avoided CO 2 Emissions

4.1

. Calculation Tool Method

The EPA has developed a user

- friendly tool to estimate the emission reduction impacts of EE/RE requirements, programs and measures

. The “ AVoided Emissions and geneRation Too l ” (AVERT) 38 was developed to help air quality planners quantify NOx and SO 2 emission impacts, as specified in EPA’s Roadmap for Incorporating EE/RE Programs in NAAQS SIPs. 39 AVERT can also be used to quantify the displaced CO 2 emissions of EE/RE measures wi thin the
continental United States.

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

- fired EGUs’ hourly generation and emissions reported through EPA’s Acid Rain Program. 40 This method couples historical hourly generation and emissions with the hourly load reduction profiles of EE/RE programs and measures to determine hourly emissions reductions on the margin. AVERT can be used to estimate EE/RE

- related emissions reductions in a current or

near

- future year . However, AVERT estimates for current or future years are based on historical behavior rather than projected economic behavior

. As a result, AVERT does not use projections of future fuel or electricity market prices that affected EGU dispatch, and is ther efore not an appropriate tool for longer

- term projections.

Users of AVERT can analyze how the different load profiles of a variety of EE programs and measures, as well as wind and solar technologies, affect the magnitude and location of CO 2 emissions at t he county, state, and regional level. AVERT has a flexible framework with a simple user interface designed specifically to meet the needs of state air quality planners and
other interested stakeholders.

38 More information about AVERT, including documentation and a user’s manual, is available at (http://www.epa.gov/avert). 39 See Appendix I of the Roadmap for Incorporating Energy Efficiency/Renewable Energy Policies and Programs
, available at http://epa.gov/airquality/eere/pdfs/appendixI.pdf ), for details about how this approach can be used in the different NAA QS SIP pathways. 40 http://ampd.epa.gov/ampd/

.29

AVERT may be used to derive marginal emission reduc tions from historical generation and emissions data, which can be used to derive a marginal avoided CO 2 emission rate. However, AVERT does not quantify average emissions rates. AVERT approximates historical dispatch behavior using a statistical algorithm. It does not represent transmission constraints, or significant changes in grid structures or future economic conditions. To estimate a recent historical marginal CO 2 emissions reduction from existing EE/RE programs or measures, a user would input the MWh r elated to results from EE/RE programs or measures (representing either MWh of electricity savings or MWh of generation) in a representative historical baseline year as

a positive increment to electricity load, and record the emissions incrementally added i n the
tool. 41 The calculated marginal CO 2 emission rate is the incremental CO 2 emissions added by AVERT, based on historical EGU dispatch patterns, divided by the incremental MWh of EE/RE savings or generation input to AVERT as an increase in electricity lo ad. This approach reflects the marginal impact of EE/RE measures based on historical recorded patterns of emissions and generation. 42

4.2

. Electricity Sector Modeling Method
Quantification of avoided CO 2 emissions from EE/RE requirements, programs, and

me asures can be achieved through retrospective modeling approaches. Models can be used to
calculate avoided CO 2 emissions by comparing actual realized EGU CO 2 emissions to projected
EGU CO 2 emissions that would have occurred in a historical reference case th at does not include implementation of the EE/RE that is being evaluated. The appropriate choice of model depends
on the look

- back period. For short look

- back periods of one to three years, an electricity system simulation dispatch model can determine the m arginal generation contribution to emissions in a

41 Because AVERT represents a historical baseline year, EE and RE programs that occurred in a past year are already recorded by the statistics of AVERT. To estimate the e missions impacts of historic EE/RE programs, a user would increase the load by the EE/RE increment to estimate what generation and emissions would have been in the reference case look

- back year. 42 AVERT reflects fuel and emission control technologies to th e extent they have influenced dispatch during the base year chosen. However, AVERT cannot change dispatch based on future economic or regulatory conditions, such as expected fuel prices, emission allowance prices, or specific emissions limits. AVERT should not be used for this type of analysis. When used to review historical data, AVERT will capture the impact of historical fuel prices and other impacts on the variable cost of production, but cannot capture specific emission limits.30

historical reference case ( i.e. absent incremental EE/RE programs). 43 Over the short term, simulation dispatch models properly account for EGU economic dispatch considerations, such as
fuel and emission allo wance prices, and operational constraints, such as ramp rates, outages, and
heat rate curves. Look

- back periods beyond three to five years would benefit from use of a utility

- scale capacity expansion and dispatch planning model to understand the change in build out of new generating capacity, as well as transmission and distribution infrastructure, and its impact on generation between the historical reference case and actual realized historical

outcome.

Electricity System Simulation Dispatch Models Quantif ying the CO 2 emissions reductions achieved by EE/RE measures through modeling of a near

- term look

- back period requires a counterfactual historical reference case model run, which examin es how the electric system would have operated in the absence of the
EE /RE emission reduction measures under consideration. The emissions projected in this model run may be compared against actual realized emissions during the historical period. The look

back model should be calibrated by running the same model with the EE/RE measures in place and comparing the outcome of that model against realized generation and emissions at an appropriate spatial scale. 44

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

43 “Reference case” here refers to the case in which additional incremental carbon emissions reduction mechanisms are not employed, in this case resulting from EE/RE programs and measures. 44 Generally, simulation models will not capture exact output of individual EGUs relative to reality due to a variety of factors, including outages and other non

- economic considerations not reflected in the model. Therefore, a comparison at an individual EGU scale may not be meaningful, but aggregate emissions at a state or regional scale should b e expected to be comparable.31

Simulation dispatch models may be most relevant as part of ex

- post plan reporting, for estimating the avoided CO 2 emissions from affected EGUs that occurred as a result of EE/RE measures included in a plan, during a specified plan reporting period.

Utility

- Scale Capacity Expansion and Dispatch Planning Models Quantifying the CO 2 emissions reductions achieved by EE/RE measures through modeling o ver a longer

- term look

- back period requires a counterfactual historical reference case model run, which examin es how the electric system would have operated and have been built out, in the absence of the EE/RE measures under consideration. The critical dif ference between this type modeling approach and the use of a simulation dispatch model is the assessment of changes made at the “build margin”

– i.e. , new additions to generating capacity that may have been avoided or compelled, or retirements of existing units that may not have occurred in the reference case. The emissions projected in this model run may be compared against actual realized emissions during the historical period. The look

- back model should be calibrated by running the same model with the EE /RE measures in place and comparing the outcome of that model run against actual realized generation and emissions at an appropriate spatial scale.

Capacity expansion and dispatch planning models could be run for a longer

- term historical period to better reflect what the electricity system would have looked like in the
absence of the EE/RE measures. When EE or RE resources have been added over the course of three to five years, these models will reflect how these resources have avoided new power plants,

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

Capacity expansion and dispatch planning models may be more relevant than simulation dispatch models for projecting the emission performance that will be achieved by affected EGUs under a plan. As discussed below, these models are able to assess both the “operating” and “build” margins that impact EGU CO 2 emissions as the result of EE/RE measures.32

5. Considerations Associated with use of an Avoid ed Emissions Rate
Operational versus Build Margin
A voided emission rates approaches that do not include a capacity expansion model all assume that EE/RE measures only impact the operational margin

– i.e., they impact moment

- to

moment operations of EGUs in the existing grid. While this is true, deployment of EE/RE over a period of years may have impacts beyond the operational margin. Deployment of significant EE/RE measures over time often impacts decisions to build new fossil generating capacity, retire

ex isting aging generating capacity, and make different decisions about transmission expansion. These different decisions about what infrastructure to build or retire are known as the “build margin
, ” and may ultimately have a greater impact on long

- term emiss ions outcomes than the operational margin.

While a new wind farm brought online next year has an impact on patterns of generation from existing fossil EGUs, decadal

- scale planning associated with a policy meant to encourage EE/RE has an impact on the cho ice of whether or not to pursue the construction of new fossil generating capacity. A utility pursuing aggressive EE/RE programs may avoid the construction of new fossil generating capacity and expansion of transmission and distribution capability, and

may even allow the utility to retire non

- economic generating units no longer required for generation or reliability purposes.

The use of an avoided emissions rate calculated based on the operational margin alone may fail to represent the impact of EE/RE mea sures that occur at the build margin. This differentiation is particularly important in regions where the pursuit of EE/RE measures may result in the retirement of high

- emitting, non

- economic generating assets. The use of a capacity expansion and dispatch planning model would help accurately assess avoided emissions due to changes at both the build and operational margins.33

Quantifying In

- State versus Out

- of

- State Emissions Reductions The electric system is not confined by state boundaries, and emissions displaced by EE/RE measures may occur over a wide geographic area, 45 including outside of the state that implemented the EE/RE measures. Without the use of a simulation dispatch model (or, under some circumstances, use of a tool such as AVERT) 46 it can be c hallenging to attribute emissions reductions that occur within the implementing state versus emissions reductions that occur across
state boundaries. If a state sought to recognize the effect of EE/RE measures and quantifi ed emissions reductions using an a pproach that did not account for avoided emissions at an appropriate spatial scale, it may inappropriately account for emissions reductions that occur in other states, or conclude that all emissions reductions occur within the state’s boundaries. 47 In
inter connected areas in which some states pursue mass

- based emissions reductions approaches through their state plans while other states pursue rate

- based approaches that include adjustment or crediting for avoided CO 2 emissions from implementation of EE/RE mea sures, avoiding
double

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

45 See California Energy Commission, Emissions Reductions from Renewable Energy and Energy Efficiency in California Air Quality Management Districts (2011), available at ( http://ucciee.org/downloads/CAEmissionsReductions.pdf ). 46 AVERT captures the magnitude of in

- state versus out

- of

- state emissions reductions, but may not be an accurate assessment tool for edge

- cases

– i.e. states that fall near the boundaries of the AVERT regions

– because AVERT does not capture inter

- regional transmission. 47 In the simplest case, a state without any fossil generating capacity that implements EE/RE measures would cause emissions reductions in neighboring states, and none within it s own borders. Similarly, a state with significant, predominantly baseload fossil generation may also cause little in

- state emissions reductions from implementation of EE/RE measures because those emissions reductions may occur at marginal generators locat ed outside of the state. Conversely, a state with significant marginal fossil generating capacity might realize reductions in emissions from EE/RE measures implemented in other states. These complications may arise regardless of if a state is a net importe r or net exporter of energy. The key differentiation is if the state’s EGUs are generally on the margin relative to interconnected EGUs in neighboring states.34

V

. Quant ification, Monitoring, and Verification of End

- Use Energy Efficiency and Renewable Energy Programs and Measures
As discussed in the preamble, in section VII.F.4, a key consideration for state plans is the process and requirements for quantifying, monitor ing, and verifying the effect of renewable

energy and demand

- side energy efficiency measures that result in electricity generation or savings. 48 In the preamble, the EPA proposes that a state plan that includes enforceable RE and
demand

- side EE measures mus t include an evaluation, measurement, and verification (EM&V) plan that explains how the effect of these measures will be determined in the course of plan implementation. An EM&V plan will specify the analytic methods, assumptions, and data
sources that th e state will employ during the state plan performance periods to determine the energy generation and energy savings related to RE and demand

- side EE measures. As discussed in the preamble, a n EM&V plan would be subject to EPA approval as part of a state pl an. In the preamble, the EPA also discusses its intent to develop guidance for acceptable EM&V methods that could be incorporated in an approvable EM&V plan included as part of an approvable state plan. The EPA seeks comment in the preamble on the critical features of such guidance, including scope, applicability, and minimum requirements , as well as the appropriate basis for and technical resources used to establish such guidance, including existing state and utility protocols and existing international, n ational, and regional consensus standards or protocols. This section further elaborates these considerations discussed in the preamble , with individual sub

sections addressing RE and demand

- side EE programs and measures

.

The appropriate type of EM&V for R E and demand

- side EE programs and measures will depend on the state plan approach. For states implementing a mass

- based portfolio approach, the
effect of renewable energy and demand

- side energy efficiency requirements, programs, and measures in helping to achieve the required level of CO 2 emission performance under a state

48 In particular, this consideration applies to states implementing a rate

- based emission limit ap proach that provides for adjustment of CO 2 emission rates based on the effect of end

- use energy efficiency and renewable energy, as well as states implementing utility

- or state

- driven portfolio approaches that incorporate end

- use energy efficiency and

ren ewable energy requirements and programs.35

plan will be directly evident in reductions in the monitored CO 2 emissions from affected EGUs. 49 In effect, the overall impact of these measures could be tracked through CO 2 emission
monit oring, reporting, and record

- keeping requirements applied to affected EGUs. However, for states implementing a rate

- based plan approach, an approvable plan will need to include quantification, monitoring, and reporting requirements related to RE and demand

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

Utilities and states have conducted ongoing EM&V of end

- use energy efficiency and renewable energy measures and programs for several decades. These evaluations, which include

quan tification, monitoring and verification of results, generally rely upon a well

- defined set of industry

- standard practices and procedures. However, measurement approaches vary by state based on multiple factors, including the measure and program type being evaluated, the level and nature of regulatory oversight, the degree of state and utility experience with these measures and programs, and the overall magnitude of program impacts.

This section of the TSD discusses current state and utility evaluation, mo nitoring, and verification approaches for end

- use energy efficiency and renewable energy programs and mandates. This section also discusses the potential suitability of these approaches in the context of an approvable state plan, and whether harmonization of state approaches, or supplemental actions and procedures, might be warranted in an approvable state plan. In particular, this section discusses considerations related to the establishment of requirements and guidance for quantification, monitoring, and verification of end

- use energy efficiency and renewable energy measures for an approvable state plan. It also discusses the possible appropriate basis for and
resources used to establish such requirements and guidance. This discussion includes
consideratio n of existing state and utility protocols, as well as any international, national, and regional consensus standards or protocols.

This section also discusses the types of end

- use energy efficiency and renewable energy measures and programs for which EM&V of results is relatively straightforward. Such

49 There could be exceptions, for example where a state plan includes acknowledgement of avoided CO 2 emissions that occur outside state borders as a result of state plan measures. See section VII of this TSD for furt her discussion of the treatment of interstate effects.36

approaches might be subject to streamlined review of EM&V protocols included in an approvable plan, provided that such protocols are applied in accordance with EPA requirements and guidance . For example, many utilities have implemented a similar core set of end

- use energy efficiency and renewable energy measures and programs for utility customers. For these types of measures and programs, a substantial base of experience has been established nationally for

qua ntification, monitoring, and verification of measure and program outcomes.

In the preamble, at section VIII.F.4 , the EPA notes that it is not proposing to limit the types of RE and demand

- side EE programs and measures that may be included in a state plan

. However, less established types of measures and programs, such as new and innovative demand

side EE programs that seek to alter consumer and building occupant behavior may pose quantification and verification challenges. Still other types of measures, s uch as state energy

efficient appliance standards and building codes, have not typically been subject to similar evaluation of energy savings results. These types of approaches may have substantial impacts, but may require additional documentation of EM&V methods in accordance with EPA guidance, including development of appropriate quantification, monitoring, and verification protocols if they do not currently exist

.

A

. Quantification, Monitoring, and Verification for End

- Use Energy Efficiency

1

. Introduct ion

For rate

- based state plans, a key element of the plan is a demonstration of how the state, and related entities with enforceable obligations under the plan, will measure and verify energy savings to be achieved the through the implementation of end

- u se energy efficiency measures incorporated in the plan. 50 In the context of demand

- side energy efficiency programs currently overseen by state PUCs, this function is typically addressed through an evaluation, measurement,
and verification plan (EM&V plan)

. This section discusses current state and utility EM&V

50 In this section we use the term “end

- use energy efficiency measure” or “energy efficiency measure” to refer to an end

- use energy efficiency requirement (such as an EERS), and energy efficiency progra m, or individual installed energy efficiency measure, such as installation of an energy

- efficient air conditioner through an energy efficiency program.37

practice for end

- use energy efficiency programs and discusses considerations related to acceptable EM&V plan s and evaluation approaches for a state plan under CAA section 111(d).

2

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

From the time that demand

- side energy efficiency (EE) emerged as an important energy strategy in the 1970s, 51 efforts to evaluate the impacts of EE actions have been cri tical to their success, credibility, and expansion

. Starting with measurement and verification (M&V) of individual projects, these efforts have evolved to the point where there is now a mature and rigorous evaluation, measurement, and verification (EM&V) i ndustry

. This industry includes many professional firms, protocols and guidelines, training and certification programs, regulatory oversight, and established conferences with a rich library of published reports and publically available data and analyses.

State agencies responsible for planning, implementing, and evaluating demand

- side energy efficiency programs and policies utilize EE savings values, as follows: 52

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

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

 Evaluated savings: values reported by an independent third

- party evaluator after the efficiency activities and an impact evaluation have been completed.

Both claimed and evaluated energy savings involve real

- time and/or retrospective assessments of the performance and implementation of an energy efficien cy program or a portfolio of programs

. Important impacts for evaluation include energy and demand savings and

non

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

51 National Energy Program Fact Sheet on the President's Program, April 20, 1977. 52 State and Local Energ y Efficiency Action Network. 2012. Energy Efficiency Program Impact Evaluation Guide

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

.38

development, energy security, transmission and dist ribution benefits, and water savings). Impact evaluations also support cost

- effectiveness analyses aimed at determining the value of energy efficiency programs to utility customers and identifying relative program costs and benefits of energy efficiency co mpared to other energy resources, including both demand

- and supply

- side options

.
Regardless of how the energy savings of an energy efficiency measure are determined, all energy savings values are estimates of savings and not directly measured

. Savings a re determined by comparing energy use after an energy efficiency project or measure is installed (the reporting period) with what is assumed to be the energy use in the absence of the project or

measure (the “counterfactual” scenario, or baseline). Savings therefore depend critically on baseline assumptions, which are necessarily estimated with varying degrees of accuracy

. Figure
1

- 1 illustrates this concept.

Figure 1. Energy Use Before, During, and After an Energy Efficiency Project is I nstalled 53

53 Ibid.39

3. Cur rent EM&V Practices in States
3.1 EM&V for Demand

- Side Energy Efficiency Programs Overseen by State PUCs
Current practice with EM&V for demand

- side energy efficiency programs in the U.S. is primarily defined by state utility commission (PUC) 54 requiremen ts for customer

- funded efficiency programs

. T he level of PUC oversight varies from state to state, but this oversight process has generated the majority of the industry guidance and protocols for documenting energy savings from energy efficiency programs. Typically, impact evaluation reports are prepared based on the requirements established by PUCs and submitted (usually annually) for PUC review, approval, and use in resource planning and performance assessment. According to a recent survey, most states (7 9 percent ) rely on independent consultants and contractors to conduct evaluations, while some states ( 21 percent ) use utility and/or government agency staff. 55

The range of EM&V budgets varies significantly between states, typically from two percent to si x percent of total energy efficiency program expenditures. 56 The average EM&V budget in 2011 was about 3.6 percent of program expenditures

. Reasons for this disparity may include the fact that as states expand energy efficiency programs, they may implement more complex programs, which require additional EM&V. 57 EM&V effort in states also typically increases as the magnitude of program expenditures and energy savings impacts increase , and as states and utilities gain experience in implementing energy efficienc y programs

.

States at the low end of this EM&V expenditure range typically rely heavily on deemed savings approaches, which are a common and relatively low

- cost strategy for documenting energy savings

. Deemed savings are measure

- specific stipulated values based on historical and

54 In some states these government entities are referred to as a public service commission (PSCs) or board of public utilities (BPU), as well as other names. 55 Kushler, M.; Nowak, S.; Witte, P. , A National Survey of State Policies and Practices for the Evaluation of Ratepayer

- Funded Energy Efficiency Programs, American Council for an Energy

- Efficient Economy (ACEEE) (February 2012), Report Number U122 Available at http://www .aceee.org/ research

- report/u122

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

. 57 Expansion of energy efficiency program s may also lead to a reduction in EM&V costs per unit of energy savings, as programs achieve economies of scale and experience in conducting EM&V activities.40

verified data (in some cases using the results of prior EM&V studies). Unlike other EM&V approaches, with deemed savings there are no

– or very limited

– meas urement activities

. I nstead, only the quantity of energy efficiency measu res implemented is verified (e.g., number of motors installed correctly, number of energy

- efficient air conditioners that were purchased using a program rebate ) . The verified installed energy efficiency measures are then multipl ied by the estimated (or dee med) energy savings per measure to derive energy savings for each measure
and energy savings for the total number of measures installed through an energy efficiency

program

. The use of deemed energy savings is only considered appropriate for efficiency act ions
with well

- known characteristics

. A variant of this approach is the deemed savings calculation
, which involves the use of one or more agreed

- upon (stipulated) engineering algorithms used to generate energy and/or demand savings associated w ith energy e fficiency measure s . These calculations may include predetermined assumptions for one or more parameters in the algorithm, but typically require users to input data associated with the actual installed measure into the algorithm. 58

The d eemed savings val ues , themselves, are typically centrally located in a “Technical Reference Manual” (TRM)

. The content and format of these TRMs vary, but in most cases consist s of a database of standardized, state

- or region

- specific algorithms (deemed calculations)
and as sociated energy savings estimates (deemed savings values) for energy efficiency measures

. TRM s also include various data assumptions, sample calculation s , and other inputs that the state

uses to develop energy savings values for the range of energy efficie ncy programs in place . The
benefits to energy efficiency program administrators of using a TRM include reduce d EM&V
costs and greater certainty regarding projected
, claimed , and evaluated energy savings values (see definitions above) . There are about 20 st ates currently using TRM databases

. 59

58 Examples of equipment types that are commonly evaluated using deemed savings values and calculations include energy

- efficient washing machines, computer equipment, and refrigerators, and lighting retrofit projects with well

understood operating hours. For deemed savings calculations, evaluators collect information about the actual installed measures

-- such as hours of usage, wattage, and/or equipment capacity

-- and combine this with predetermined assumptions in the algorithm. 59 State and Local Energy Efficiency Action Network, Scoping Study to Evaluate Feasibility of National Dat abases for EM&V Documents and Measure Savings , prepared by Jayaweera, T.; Haeri, H.; Lee, A.; Bergen, S.; Kan, C.; Velonis, A.; Gurin, C.; Visser, M.; Grant, A.; Buckman, A.; The Cadmus Group Inc. (June 2011), available at http://www.eere.energy. gov/seea ction/pdfs/emvscoping__databasefeasibility.pdf.41

It should be noted that TRM values for individual energy efficiency measures are not always formally vetted in a regulatory process, although this is a good practice. 60 A recent survey of TRMs found that deemed energy savings values for comparable energy efficiency

measures vary across states and regions

. 61 T he reasons for these variations include the use of
different calculation methodologies, technical assumptions, and input variables. Some of these
differences are ex pected based on relevant differences in weather and baseline assumptions ( e.g., existing building stock and common practices vary from one state to another )

. However, other
differences are related to out

- of

- date input assumptions and calculation errors

. In the context of state plans, this variation, and in particular data quality issues with some TRMs, raises
consideration of whether complete reliance on existing TRM resources for state plans is prudent and appropriate , including how such reliance could or should be circumscribed

.
In addition to the use of deemed savings, states on the higher end of the EM&V expenditure range rely to a greater extent on a variety of direct measurement approaches for
document ing energy savings

. Rather than mandating which EM&V methods must be used in a particular situation, PUCs typically allow utilities and other program administrators to select from a range of appropriate EM&V approaches that are consistent with standard practice in the energy efficiency industry

. EM&V a nalyses and calculations are then carried out, in most cases by an independent, third

- party evaluator
, through a process that is unbiased, uses technically rigorous methods , effective peer review, and is subject to public review and comment. In addition, e nergy savings are frequently certified by the PUC as compliant with requirements
defined in a pre

- approved EM&V plan.

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

60 State and Local Energy Efficiency Action Network, Energy Efficiency Program Impact Evaluation Guide
, prepared by Steven R. Schiller, Schiller Consulting, Inc. (2012), available at http://www.seeaction.energy.gov

. 61 Ibid.42

 U se of one or more of the industry

- standard EM&V protocols or guidelines (listed below) , as well as the use of deemed savings values for well

- understood energy efficiency programs and measures

 Consideration of local fac tors , such as climate
, building type, and occupan cy

.

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

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

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

Despite this well

- defined and generally accepted set of industry best practices, many
states with energy efficiency pr ograms use different input values and assumptions (e.g., net versus gross savings, run

- time of equipment, measure lifetime) in applying these practices

. This
can result in significant differences in claimed energy savings values for similar energy
efficien cy measures between states, even when the same measure type is installed under otherwise identical circumstances. In response to a growing awareness of th is lack of cross

- state comparability, policy makers, regulatory agencies, and other stakeholders are i ncreasingly advocating for the use of common evaluation approaches across jurisdictions . Several national and regional EM&V efforts have emerged to promote collaboration and information sharing
across states. These initiatives include the Northeast Energy Efficiency Partnership’s (NEEP)
EM&V Forum , which is active in New England, New York, and the Mid

- Atlantic
, and the Pacific Northwest’s Regional Technical Forum (RTF). Both efforts aim to promot e multi

- state coordination in EM&V practices , mak e EM&V result s more transparent and public ly available
, and support the adoption of similar definitions, methods
, and input assumptions. 62

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

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

.43

a. U.S. DOE Uniform Methods Project (UMP) Protocols 63
b. International Performance Measurement and V erification Protocol (IPMVP) 64

c. Federal Energy Management Program ( FEMP ) M&V Guidelines 65
d. American Society of Heating, Refrigerating and Air

- Conditioning Engineers ( ASHRAE )
Guideline 14
, Measurement of Energy and Demand Savings 66

e. California Evaluation Protocol s 67
f. ISO New England (ISO

- NE) Manual for Measurement & Verification of Demand
Resources 68

g. PJM Energy Efficiency Measurement and Verification Manual 69
h. State and Local Energy Efficiency Action Network, Energy Efficiency Program Impact
Evaluation Guide 70
i. U.S. DOE Superior Energy Performance Measurement and Verification Protocol for Industry 71

63 U.S. Department of Energy (DOE), Uniform Methods Project (April 2013) , available at: http://energy.gov/eere/about

- us/initiatives

- and

- projects/uniform

- methods

- project

- determining

- energy

- efficiency

program

- savings

. 64 Efficiency Valuation Organization (EVO), International Performance Measurement and Verification Protocol (2012), avail able at: http://www.evo

- world.org/

. 65 FEMP, M&V Guidelines: Measurement and Verification for Federal Energy Projects, Version 3.0 (April 2008), available at: https://www1.eere.energy.gov/femp/pdfs/mv_guidelines.pdf

. 66 American Society of Heating, Refrigerating and Air

- Conditioning Engineers (ASHRAE), Guideline 14: Measurement of Energy and Demand Savings (June 2002) , available at: https://gaia.lbl.gov/people/ryin/public/Ashrae_guideline14

- 2002_Measurement%20of%20Energy%20and%20Demand%20Saving%20.pdf

. 67 California Public Utilities Commissions (CPUC), California Energy Efficiency Evaluation Protocols: Technical, Methodological, and Reporting Requirements for Evaluation Professionals (2006), available at: http://www.calmac.org/events/EvaluatorsProtocols_Final_AdoptedviaRuling_06

- 19

- 2006.pdf

. 68 ISO

- New England (ISO

- NE), Measurement and Verification of Demand Reduction Value from Demand Resources (2013), avail able at http://www.iso

- ne.com/rules_proceds/isone_mnls/MMVDR/index.html

. 69 PJM, Manual 18B: Energy Efficiency Measurement & Verification (2010) , available at http://www.pjm.com/~/media/documents/manuals/m18b.ashx

. 70 U.S. DOE State and Local Energy Efficiency Action Network (SEE Action), Energy Efficiency Program Impact Evaluation Guide (December 201 2), available at: http://www1.eere.energy.gov/seeaction/pdfs/emv_ee_program_impact_guide.pdf

. 71 U.S. DOE, Superior Energy Performance Measurement and Verif ication Protocol for Industry (2012), available at: http://superiorenergyperformance.energy.gov/pdfs/sep_mv_protocol.pdf

.44

While many states are currently relying upon these protocols and guidelines, other states and regional organizations ( e.g., ISOs and RTOs ) take the additional step of specify ing accuracy and uncertainty requirements for energy savings estimates. For example, ISO

- NE requires that energy efficiency bids into its Forward Capacity Market (FCM) ensure that impact evaluations
achieve ±10 percent statistical precision at the 80% conf idence interval (see below for more on FCMs).

Regardless of the evaluation approach followed, the majority of state PUCs and energy efficiency program administrators aim to strike a balance between the transaction costs of EM&V activities (i.e., expens e, time, staff effort) and the resulting reliability, validity, and
usefulness of the estimated energy savings results. The appropriate balance between EM&V costs and the rigor of EM&V

– and the related certainty of energy savings estimates

– is often
dete rmined based on the type of program (including program purpose and goals), level of program expenditure s , and magnitude of anticipated energy savings.

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

orward c apacity m arkets (FCMs) that pay suppliers to ensure sufficient electric generating capacity is available to meet future peak electricity demand

. In operating these markets, ISO New England (ISO

- NE) and PJM both allow demand

- side energy efficiency programs and other demand

- side resources to compete directly with electric gene rators to meet the region al capacity needs

. One requirement for utilities and other energy efficiency program administrators seeking to bid into the market is to submit an e valuation p lan

. ISO acceptance of

t his evaluation p lan “ qualifies ” energy efficienc y programs and projects as prospective market

resources . The evaluation plan specifies the amount of energy and demand savings to be
delivered over the contract period (typically three years into the future), and documents how the requirements of the ISO’s M&V s tandards m anual will be satisfied

.
Based on experience to

- date, states bidding their energy efficiency programs into both the
ISO

- NE and PJM forward capacity markets are typically subjected to EM&V requirements that45

go beyond the evaluation already conducted for the purpose of meeting PUC requirements . This is because, while PUCs typically require evaluation protocols and procedures for documenting
the cost

- effectiveness of annual energy (MWh) savings, FCMs require the measurement and
verification o f capacity (MW) savings during specific peak demand hours. In addition to the evaluation of energy savings, a separate set of measurement techniques and data collection protocols are required to document peak demand reduction impacts. Furthermore, attainin g the
level of statistical precision and confidence described above typically requires additional sampling 72 than is required by PUCs. One consideration is whether EM&V requirements in ISO capacity markets include components that would facilitate better est imation of avoided CO 2 emissions related to energy efficiency programs include in state plans.

For the states located i n ISO

- NE and PJM, the common evaluation requirements for FCM participation have create d an impetus for regional collaboration on EM&V pr actices . New England and Mid

- Atlantic states continue to work together to establish consistent evaluation protocols through the creation of a n “EM&V Forum,” which is convened by the Northeast Energy Efficiency Partnerships (NEEP) and supports common evalua tion methods, reporting metrics, and cost sharing on research studies. 73 The Forum also serve s as a venue for information exchange to address common EM&V challenges encountered with FCM participation

.

3 .3 EM&V for Programs and Policies Not Typically Over seen by PUCs
In contrast to energy efficiency programs overseen by PUCs, EM&V is less common for other types of energy efficiency requirements or programs , especially for minimum energy efficiency requirements that do not involve the expenditure of electr icity ratepayer dollars

. Examples include building energy codes, appliance efficiency standards, various energy efficiency financing programs, behavioral change programs, and market transformation programs that target both the suppliers of energy

- efficient products and increasing consumer demand for those products

. While these approaches often have substantial impacts in reducing

72 With additional sampling requirements, energy efficiency program evaluators are typically required to measure a larger percentage of the energy efficiency measures installed within the total population of all measures installed through an energy efficiency program. 73 More information about the EM&V Forum is available through Northeast Energy Efficiency Partnerships, at https://neep.org/emv

- forum/index

.46

energy use, they may also face EM&V challenges. In some cases, appropriate evaluation protocols and approaches have not been deve loped for some programs and measures

. In cases where appropriate EM&V methods do exist, there may also be less experience applying them

. 74

4

. Considerations for EM&V of End

- Use Energy Efficiency Programs and Measures in State Plans
A key consideratio n for state plans is the process and requirements for EM&V of RE and
demand

- side EE measures that result in electricity generation or savings. As described in the

p reamble, at section VII.F.4 , the EPA intends to develop guidance on acceptable methods that

c an be incorporated in an EM&V plan included as part of an approvable state plan. C ritical
features of such EM&V guidance, including scope, applicability, and minimum criteria
, are discussed in this section

. 4.1 Accuracy of Energy Savings Estimates

T o document and verify that avoided CO 2 emissions from energy efficiency programs and measures are real and persistent, impact evaluation must be rigorous and transparent. Impact assessment should also consider the appropriate balance between certainty of r esults and the EM&V costs to achieve a specified level of certainty. Because energy savings data are estimates , their use as part of the basis for determining the avoided CO 2 emissions result ing from energy efficiency programs and measures in a state plan will depend upon the level of accuracy of this information. Therefore, evaluation results should be reported as “expected values”

— that is, energy savings values are expected to be correct within an associated range of certainty. Key
considerations for EM&V of energy efficiency programs and measures in state plans are similar
to those faced in the design of any program evaluation approach: (1) the level of certainty that is required given a program’s objectives and requirements, and (2) how achievement of th at necessary level of certainty is balanced with the amount of effort (e.g., resources, time, money) used to obtain that level of certainty

.

74 Examples of such EM&V methods are described in the PNNL report, “Building Energy Codes Program: National Benefits Assessment: 1992

- 2040.”; and in Meyers et al, “Energy and Economic Impacts of U.S. Federal Energy and Water Conservation Standards Adopted From 1987 through 2012” LBNL

- 6217E.47

4.2 EM&V Technical Considerations for State Plans Using energy efficiency requirements, programs, and measure s as an emission reduction approach in state plans requires consideration of several evaluation

- related technical
considerations

. The following sections describe these considerations.

4.2.1 Qualifying Demand

- Side Energy Efficiency Actions
States are cur rently implementi ng a wide range of demand

- side energy efficiency requirements, programs, and measures

. However, EM&V of some of these programs and measures are associated with greater levels of measurement precision and certainty than others, based in par t on the EM&V procedures currently in place

. For example, energy efficiency programs subject to PUC oversight and review are frequently evaluated using rigorous evaluation procedures that are based upon several decades of research and experience

. These

ene rgy efficiency programs are subject to a quasi

- judicial, public, and transparent review process, which can lead to adoption of EM&V protocols that convey a relatively high level of certainty for EM&V results

.

In contrast, other energy efficiency requirem ents and measures, some of which may result in very significant and cost

- effective energy savings (e.g., building energy codes, local tax credits, EE loan programs, etc.), are not subject to PUC oversight and typically have comparably fewer EM&V requiremen ts. There are also some newer EE program designs (e.g., certain
behavior

- based programs and some market transformation programs 75 ) for which rigorous EM&V methodologies or a track record of energy savings persistence do not yet exist

. 76

75 Behavior

- based energy efficiency programs aim to affect consumer energy

- use behaviors in order to achieve energy and/or peak demand savings. Techniques to measure the impacts of these program designs are emerging and currently under development. Market transformation programs are characterized by strategic intervention in a market to address market barriers and market failures to accelerate market adoptio n of energy

- efficient technologies and practices, and create lasting market change. While market transformation approaches can have very high energy savings impact s, by creating sustained deployment of energy

- efficient technologies and practices, evaluatio n of these strategies is challenging due to the involvement of numerous market players and the multi

- year timeframe for achieving energy savings. 76 We note that EM&V approaches and protocols for behavior

- based end

- use energy efficiency programs do exist, b ut they have not been widely applied. For examples, see State and Local Energy Efficiency Action Network (SEE Action), Evaluation, Measurement, and Verification (EM&V) of Residential Behavior

- Based Energy Efficiency Programs: Issues and Recommendations (20 12), Prepared by A. Todd, E. Stuart, S. Schiller, and C. Goldman,48

As discussed in the preamble, w hile the EPA does not intend to limit the types of RE and
demand

- side EE measures and programs that can be included in a state plan

– provided that supporting EM&V is rigorous, complete, and consistent with EPA requirements and guidance

– the l evel and type of documentation required by EPA in an approvable state plan may depend on
whether EM&V practices for that type of program or measure are well established. One option
for organiz ing these variations in EM&V practices is with a qualitative hie rarchy, as follows:

 EM&V procedures and protocols well established

– for example, rebate and direct install programs for appliances , HVAC, and lighting equipment

 EM&V procedures and protocols moderately well established

– for example, building codes and s tandards

 EM&V procedures and protocols less well established

– for example, building disclosure and labeling programs

Table 2 provides an illustrative characterization of the relative level of EM&V uncertainty for different types of energy efficiency prog rams and measures under this approach

. This information is illustrative and generalized. In particular, there are numerous exceptions to the categorization of the relative uncertainty of EM&V results for different types of programs
and measures listed in T able 2

.

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

.49

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

Common Energy Efficiency Programs and Polic i es 77

EM&V Procedures and Protocols Well Established EM&V Procedures and Protocols Moderately Well Established EM&V Procedures and Protocols Less Well Established

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

o lighting

o heating, ventilation, and air conditioning (HVAC)

o refrigeration

o motors

 Cons umer

- direct and mid

stream rebates for ENERGY STAR

- certified lighting, appliances (including residential refrigerator recycling), and HVAC equipment

 Building commissioning and retro

- commissioning

 Incentives for certified energy

- efficient residential

new c onstruction, such as ENERGY STAR Homes

 Combined heat and power (CHP) installations/retrofits

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

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

 Product

- specific upstream market transformation programs directed at manufacturers

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

 Targeted training programs

 Building labeling and disclosure programs

 Targeted consumer behavior programs

77 This table is intended as a generalized description, based upon numerous conversations with professional energy efficiency program evaluators. It should be noted that there are states with building energy codes, behavior pr ograms, and market transformation programs that are well documented and subject to rigorous EM&V. In addition, such characterizations will change over time, as EM&V approaches for new and innovative programs and measures become standard practice.50

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

- defined list of well

- understood program types for which evaluation is straightforward and energy savings results are subject to a relatively low level of uncertainty. 78 Other programs and measures with less well developed EM&V approaches would require greater documentation in state plans of EM&V methods that will be appli e d

. This proposed approach is intended to maximize state flexibility and accommodate the full range of state energy efficiency programs, while simultaneously maintaining EM&V rigor and transparency. As discussed in the preamble, at section VIII.F.4 , EPA is also taking comment on
the option of limit ing the eligible types of ene rgy efficiency programs and measures that could be included in a state plan to a pre

- defined list of well

- understood program types for which evaluation is straightforward and energy savings results are subject to a relatively low level of uncertainty.

4.2 .2 Avoided Transmission and Distribution (T&D) Losses from End

- Use Energy Efficiency Measures
In general, the difference between the amount of electricity input to the transmission system by an EGU and the amount ultimately delivered to an end

- user constitutes transmission
and distribution (T&D) line losses. 79 According to EIA data, nationally, annual electricity
transmission and distribution losses are equivalent to about seven percent of the electricity that is input to the transmission system in the United States

. For every unit of energy use avoided at the
end

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

78 This in cludes energy efficiency programs and measures for which there is significant experience with EM&V, a robust set of existing EM&V studies and reports, and relatively straightforward EM&V approaches. 79 The T&D system includes all the power lines and related equipment used to deliver electricity from an electric generating plant to an end

- use site. Along the way, some of the supplied by the generator is lost due to the resistance of the wires and equipment that the electricity passes through, as well as react ive power losses in alternating current systems due to inductance and capacitance. Most of this lost energy is converted to heat. The magnitude of losses in the T&D system depends on the physical characteristics of the system in question, as well as how it is operated.51

delivered to consumers through the T&D system. 80 Many state PUCs are aware of this
additi onal benefit of demand

- side energy efficiency programs, and actively credit program energy savings results to account for program contributions to avoided line losses, albeit using a range of measurement approaches and calculations

. A consideration for EM& V requirements and guidance for state plans is whether to account for avoided T&D losses, and how to do so in a
consistent manner across states.

4.2.3 Reported Energy Savings Values
Energy savings results for energy efficiency programs are often express ed in terms of annual MWh of savings per year. However, for an assessment of the associated avoided CO 2 emissions impacts, it may be useful to utilize time

- differentiated (i.e., hourly, seasonal) energy savings data. 81 Information about the timing of energ y savings has direct implications for estimating the avoided CO 2 emissions that result from an efficiency program or portfolio of

programs

. T he temporal energy savings profile that results from the application of energy

efficient technologies and practices to different end

- uses can vary significantly

. For example, air conditioner programs save energy primarily on hot summer days, whereas a refrigerator program saves energy every hour of the year

. Time

- differentiated information related to electricity

genera tion is useful in estimating avoided CO 2 emissions. In particular time

- differentiated data is necessary to estimate the marginal avoided CO 2 emissions related to electric generation, as
discussed above in section IV.C.3

.
In practice, state PUCs around the country have substantially different requirements and recommendations for evaluating and reporting time

- differentiated energy savings

. Some energy efficiency program administrators report annual energy savings impacts, where savings are typically based on either tracking data (i.e., data used to estimate savings for planning purposes) or evaluated (i.e., ex

- post) savings data. Other programs supplement reporting of annual energy savings with data on the timing of energy savings, which can be used to identi fy the marginal EGU or cohort of marginal EGUs that would have provided generation in the absence of the

80 U.S. EPA, Assessing the Multiple Benefits of Clean Energy: A Resource for States (February 2010), available at: http://epa.gov/statelocalclimate/d ocuments/pdf/epa_assessing_benefits_ch3.pdf 81 This is often referred to as the “load shape” of energy savings achieved through an energy efficiency measure.52

energy savings. This supplemental data can be used to more accurately estimate avoided CO 2 emissions that result from program energy savings. Due to im proved evaluation software and data availability, it is increasingly common for energy efficiency program EM&V plans to include calculation of estimated seasonal or even hourly energy savings as part of the program evaluation process

. A consideration for E M&V requirements and guidance for state plans is the
extent to which time

- differentiated data on energy savings from energy efficiency programs is available, and whether states can readily acquire such data and information for use in implementing their sta te plans.

A related consideration is metrics reported for electricity savings

. The primary metric required to understand the avoided CO 2 emissions impacts of energy efficiency programs and measures is annual MWh of energy saved

. In addition, a secondary metric is MW demand
reduction impacts, which may be desirable because it is helpful in identifying the marginal EGU or cohort of EGUs, in particular units on the build margin

. This information is necessary to estimate the marginal avoided CO 2 em issions related to electric generation, when reporting on
avoided CO 2 emissions achieved through energy efficiency programs and measures during a plan reporting period, as discussed above in section IV.C.3 . Identifying EGUs on the build margin
, based on es timates of MW demand savings that will be achieved through the implementation of energy efficiency programs and measures included in a state plan
, may also be useful in projecting emission performance by affected EGUs that will be achieved under the state plan.

4.2.4 Savings Definitions: Net and Gross Savings
As described above, state PUCs typically specify whether energy efficiency program administrators are required to report either gross or net energy savings , or both

. Gross savings are the change in energy use (MWh) and demand (MW) that results directly from program

related actions taken by program participants, regardless of why they participated in a program. Net savings refer to the change in energy use and demand that is directly attributable to a particular energy efficiency program. 82 Reporting of net savings helps a PUC ensure that energy

82 Calculations of net energy savings involve excluding energy efficiency measures undertaken by "free riders" (i.e., EE program participants who receive a program rebate even though they would have taken the efficiency action anyway), or adjusting energy savings estimates to account for these effects. Free riders increase program costs53

efficiency program budgets are being used to promote technologies and practices that are not otherwise being adopted in the market place

. A consideration for EM &V requirements and guidance for energy efficiency requirements and programs included in state plans is whether required reporting of energy savings should be specified on either a gross or net basis , or both, to promote national consistency in measuring t he impact of energy efficiency measures across state plans. 83

4.2.5 “ Measure Life ” and Persistence of Savings
Measure life and p ersistence of energy savings describe the ongoing effects of an installed energy efficiency measure, including the retention o f the measure ( i.e. , is it still in place) and the performance degradation of that measure, which reduces a measure’s achieved energy savings over time

. Typically, program administrators estimate the impact of energy efficiency programs in terms of first

- y ear savings (in MWh), plus the cumulative MWh savings realized from that program (or measure) over an assumed “measure lifetime”. Depending on the mix of energy efficiency measures and their assumed measure lives, these energy

- savings benefits may extend f

rom 10 to 15 years, or more into the future from the point of measure installation. In practice, evaluators determine measure lifetimes on the basis of engineering judgment, manufacturer specifications, and some empirical field studies

. These values are
fr equently entered into PUC

- managed state technical databases for ongoing and repeated use in
evaluation studies

. For state plans, a key consideration for EM&V is whether measure life and persistence values for energy efficiency measures documented by states are accurate, up

- to

- date, and consistent with those utilized in other states (after accounting for appropriate non

- energy factors, such as weather and building occupancy type).

without produc ing additional energy savings impacts beyond what would have occurred in the absence of the EE program. Free ridership may also be addressed in the setting of baselines that are used to calculate energy savings. Estimates of net energy savings may also inv olve an assessment of "free drivers" (sometimes referred to as "spillover effects"). These are individuals who do not directly participate in an EE program, but who undertake efficiency actions in response to program activity (e.g., marketing/advertising, greater availability of energy

efficient equipment in a marketplace as the result of EE programs). Accurate estimation of free ridership and spillover effects is complex, especially in areas of the country with robust energy efficiency markets with multipl e
non

- program influences competing for customers’ attention. 83 If both gross and net savings were required to be reported, this would increase the transparency of reported energy savings estimates, but only one savings value would be used to evaluate the e ffect of energy efficiency programs and measures on CO 2 emissions from affected EGUs.54

5

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

r esources used to establish such guidance, including consideration of existing state and utility protocols, as well as existing international, national, and regional consensus standards or protocols , as described in this section

.

As summarized in the pre amble, and discussed in more depth in this section, utilities and states have conducted ongoing evaluation of end

- use energy efficiency and renewable energy measures and programs for several decades. These evaluations, which include quantification,
monitor ing and verification of results, generally rely upon a well

- defined set of industry

- standard practices and procedures. As a result, existing state and utility EM&V requirements and processes generally provide a solid foundation for minimum EM&V requirement s that can be
utilized by the EPA in the development of EM&V requirements and guidance for state plans. However, measurement approaches vary by state based on multiple factors, including the measure and program type being evaluated, the level and nature of regulatory oversight, the degree of state and utility experience with these measures and programs, and the overall magnitude of program impacts. Due to this variation in state EM&V approaches, as well as the specific objectives of a state plan under CAA s ection 111(d), harmonization of state EM&V approaches, or inclusion of supplemental EM&V actions and procedures, may be warranted in an approvable state plan.

As discussed previously, current state EM&V practices involve aligning the level of
EM&V effort (i.e., rigor, reliability, validity, and uncertainty of energy savings estimates) with
the appropriate level of certainty of evaluation results , while taking into consideration the magnitude of energy efficiency program impacts

. This approach is consistent with the objective of achieving environmental results, ensur ing minimum levels of cross

- state consistency, and supporting and encourag ing the use of energy efficiency requirements, programs, and measures55

in state plans

. To advance these objectives, the EP A could take several possible approaches for documenting energy efficiency savings from measures in state plans.

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

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

– such as a required minimum level of precision and accuracy (see discussion of ISO forward capacity markets above)

– for all energy efficiency programs and measures

 Establishing specifi c EM&V requirements for certain types of widely used energy efficiency programs and measures

– such as those addressed by DOE’s Uniform Methods Project (UMP)

– while establishing a generalized EM&V approach that states can apply to programs that are relati vely new, innovative, or untested

 Establishing a set of generalized, process

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

At one end of this spectrum, establishing program

- specific EM&V requirements and an associated level of rigor for EM&V provide s certainty to states in terms of required energy

s avings documentation, and do es so in a manner that ensures a consistent level of EM&V rigor across all state plans

. However , this approach may require significant effort by the EPA to establish such requirements, and could potentially duplicate state effor ts currently under way to harmonize EM&V practices

. This approach may also limit the variety of valid EM&V approaches applied at the state level, and by extension the types of energy efficiency programs and measures that could be included in a state plan

. It could also inhibit the development of innovative EM&V approaches that improve the accuracy of energy savings estimates. At the other end of the spectrum, if only generalized, process

- oriented EM&V requirements and guidance are established, then a state has maximum flexibility, but also faces somewhat greater uncertainty about whether the EM&V approach included in a state plan will be approved by the
EPA. This could increase the transaction costs incurred by states during the development of their56

plans, a nd could possibly delay the full implementation of energy efficiency progr ams incorporated in state plans.

Alternatively, a middle

- ground approach involves a combination of specific EM&V
criteria for common energy efficiency program and measure types, alo ng with generalized guidance for emerging program designs and measures

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

In addition, one option for supplementing either approach described above is to prescribe who can conduct EM&V activities and prepare e nergy savings documentation
, and to specify
their needed qualifications. This approach is analogous to professional certification requirements in the accounting and engineering fields, in which a minimum level of credibility, rigor, and accountability is i mparted to the services provided by qualified individuals and firms

. Criteria for eligible evaluators might include a demonstration of independence from those implementing or administering the energy efficiency programs and measures ( i.e. , identification a nd mitigation of potential conflicts of interest) and required minimum levels of training, experience, or
certification

. This approach recognizes that the qualifications, integrity, and independence of those conducting EM&V of energy efficiency programs an d measures, and preparing energy savings estimates
, is critical to assuring best

- practice EM&V

. However, such requirements alone may not ensure sufficient evaluation rigor.

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

 Relying on existing EM&V infrastructure and protocols, most of which have been established for utility

- customer funded energy efficiency programs overseen by state
PUCs

 Establishing new protocols and procedures57

Relying on existing approaches has the benefit of utilizing existing resources that can be relatively quickly ramped up for use in state plans. However, existing state and utility EM&V infrastructure and protocols may not be applicable to the full range of energy efficiency programs and measures that a state may want to include in its plan. In addition, because existing state and utility EM&V infrastructure and protocols were established to support the goals of state energy ef ficiency programs, in current form they may not adequately support the level of EM&V required for state plans under CAA section 111(d). In particular, this may include the form and precision of energy savings data and reporting necessary to evaluate avoide d CO 2 emissions that result from energy efficiency programs and measure included in state plans.

5.2 EPA Review of EM&V Plans as Part of the State Plan Review Process
As discussed in the preamble, at section VIII.F.4 , the EPA is proposing that a state plan must include an EM&V plan, which is subject to approval by EPA, as part of plan review and approval. Under this approach, the EPA would review these EM&V plans as part of its review of
submitted state plans. One option is that an approvable EM&V plan could rely primarily on

state

- or utility

- level EM&V plan review and approval processes, consistent with established EPA requirements and guidance for EM&V, with open public involvement and state lead

- agency approval

. Using existing state EM&V plan review processes may better ensure that energy savings estimates are transparent, peer review ed , and address stakeholder input. Using state processes also minimizes duplication of state and the EPA requirements, and balances the need for EM&V credibility and rig or with an interest in encouraging the deployment of cost

- effective energy efficiency programs and measures through incorporation in state plans.

5.3 General Quality Standards for EM&V Rigor and Accuracy
Since existing state EM&V process vary, EM&V gu idance established by EPA may need to identify and establish minimum criteria for EM&V rigor, accuracy and reliability, and quality
control

. R equirements could be (a) a single set of requirements that apply to all energy efficiency programs and measures in all states or (b) a variable or flexible set of requirements with increasing levels of EM&V effort and rigor depending on the relative degree of uncertainty of energy savings from the energy efficiency programs and measures in a state plan

. For example,58

w ell understood energy efficiency measures with a higher degree of energy savings certainty might require a lower level of EM&V effort, while measures with greater complexity or uncertainty of energy savings effects would require greater EM&V effort. 84

Fo r s imple, well

- understood and straightforward energy efficiency programs and measures, such as lighting retrofits , EPA guidance might specify only verification that measures were installed and the use of deemed energy savings values ( i.e., lower EM&V effor t level)

. In contrast, EPA guidance might specify more detailed EM&V (i.e., a higher level of EM&V effort)
for less well

- understood or more complex energy efficiency programs and measures, such as behavior programs and market transformation programs

.

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

6

. EM&V Documentation in a 111(d) State Implementation Plan
EM&V documentation will be an important component of state plans that incor porate energy efficiency programs and measures , because transparency and reproducibility increase overall confidence in reported energy savings results . A crucial component of EPA’s proposed approach for evaluating energy efficiency programs and measures i ncluded in a state plan is a requirement that state plans that include enforceable energy efficiency and renewable energy measures must include an EM&V plan for these measures. These EM&V plan s would specif y how achieved energy savings will be retrospectiv ely evaluated at appropriate increments during

84 For the purposes of this discussion, lower, medium, and high levels of “EM&V effort” are intentionally indeterminate. One possibility is that “lower EM&V effort” could refer to greater reliance on deemed savings values, smaller sample sizes for measured savings, fewer direct measurements, and proportionately greater reliance

on ex

- ante estimates. “Medium” and “high” levels of EM&V effort could require incrementally more effort in each of these areas. Other interpretations of this concept are possible.59

the plan period. Decisions about the level of EM&V documentation that is necessary in a state plan must consider tradeoffs between provision of more information and greater transparency,
and the level of EM&V effort required

. Excessive documentation requirements may not add value in terms of transparency, but may discourag e the inclusion of cost

- effective energy efficiency options in state plans. However, two basic criteria for EM&V documentation should be appl ied in state plans:

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

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

6.1 Illustrative Example of an EM&V Plan for End

- Use Energy Efficiency Programs Measures in a State Plan
The following is an example of a possible outline of the types of information that might be included in an EM&V plan for energy efficiency programs and measures included in a state plan. An EM&V plan would specify how EM&V activities will be conducted and reported for relevant energy efficiency programs and measures during a state plan performance period. An EM&V plan could apply to utility energy efficiency programs that are incorporated into a state plan on a stand

- alone basis, and might also apply to such programs when used to meet mandatory energy efficie ncy requirements, such as an EERS, that are incorporated into a state plan.

Who Will Document Savings a nd When

 Name of the organization that will prepare evaluated energy savings reports

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

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

 Name of the state or regional government entity, or non

- governmental entity, which will review and certify the evaluated savings60

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

Documentation Procedures

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

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

 Description of the r ange of uncertainty for energy savings estima tes indicated in evaluated energy savings reports, including sources of uncertainty

 Description of a ssumptions concerning availability of data and data collection methods

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

o Inclusion of estimates of avoided electricity transmissions and distribution losses

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

o Sources of uncertainty

B

. Quantification, Monitoring, and Ver ification for Renewable Energy Measures

For rate

- based state plans, a key element of the plan is a demonstration of how the state, and related entities with enforceable obligations under the plan, will measure and verify electric generation that is achiev ed through the implementation of renewable energy measures incorporated in the plan. 85 This section discusses current state and utility quantification, monitoring, and verification practices for renewable energy measures
, and discusses
considerations relat ed to possible acceptable quantification, monitoring and verification approaches for a state plan under CAA section 111(d).

States and utilities use a variety of policy instruments to increase the production and use of renewable energy

. The principal mech anisms include : renewable portfolio standards (RPSs),

85 In this section we use the term “renewable energy measure” to refer to a renewable energy requirement (such as an RPS), a renewable energy deployment program, or individua l installed renewable energy measures, such as installation of a solar photovoltaic system through a renewable energy deployment program.61

feed

- in tariffs (FITs), tax incentives (e.g., property tax exemptions; production

- based tax incentives; etc.), financial assistance programs (e.g., grants, loans, and other direct financial
assistance b ased on generating capacity or investment level ), and other policies (R&D support; manufacturing incentives; workforce training; net metering; etc.). Experience to date indicates that RPSs have led to the vast majority of the increase in renewable energy g enerating capacity and generation resulting from state policies. However, FITs and production

- based tax incentives have been among the most important incentives used by states and utilities to help achieve RPS requirements, as well as to spur additional pr oduction and use of renewable energy. Further, these types of programs rely on measurable electric generation as the basis for compliance or incentive payments. As a result, the following discussion focuses on quantification, monitoring,
and verification m echanisms related to these state policies

. Other types of programs (e.g., certain grant and rebate programs) may not currently quantify electric generation output from funded renewable energy projects. However, if such programs were modified to require the collection of
such data , m any of the quantification, monitoring, and verification considerations discussed in
this section would also generally apply.

1

. Renewable Portfolio Standards
A RPS is designed to increase the amount of renewable energy a distri bution utility or
load

- serving entity provides to retail electricity customers. 86 . This increased customer demand in turn increases the production of renewable energy to meet demand. To achieve compliance with a RPS, an increasing share of a distribution ut ility’s electricity retail sales is required to be produced or acquired from renewable energy resources and delivered to customers. To verify compliance, RPSs have been complemented by tracking systems for renewable energy generation and use. These trackin g systems account for the growing amount of renewable energy

86 In states that have restructured their electricity sectors and introduced retail competition, entities other than a utility may supply electricity to a retail customer. These entities use a regulated distribution utility’s network to deliver electricity to a retail consumer. These entities either generate their own electricity or contract for supply from wholesale elect ricity market participants. In this section, we use the term “distribution utility” to refer broadly to both local distribution companies (LDCs) and other load

- serving entities that supply electricity to retail customers.62

that is produced for obligated retail sellers as well as large and small retail energy consumers that purchase renewable energy on a voluntary basis

. 87

The point of regulation for state RPSs is t ypically investor

- owned electric distribution
utilities , because most RPS apply to entities under t he jurisdiction of state PUCs. I n a number of states, municipally

- owned utilities and electric cooperatives are exempt from state RPS , have lower RPS require ments, or are required to develop their own renewable energy procurement targets. Additionally, some states have created separate renewable energy requirements for each
of their affected distribution utilities.

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

There are several pathways that affected distributed utilities typically have to meet state RPS requirements , including building and operating renewable energy generating capacity, purchasing electricity from renewable energy generators, and purchasing the attributes from renewable energy generation

. Many state RPSs take this latter approach. Rather than requiring each distribution utility to generate electricity from its own renewable energy facilities or purchase electricity from a renewable facility owned by others, many states require distribution utilities to acq uire renewable energy certificates (RECs) that represent the attributes of the unit of renewable electricity produced. 88

By allowing REC trading, many states have created markets for RECs based on specific state RPS requirements. Renewable energy generato rs can sell RECs as another product bundled with the underlying power they produce or sell RECs separately to different customers. Once the

87 “Voluntary” renewable energy pur chases, as used here, refers to renewable energy purchases in addition to the renewable energy required by RPSs. 88 RECs are contractual instruments that convey ownership of the attributes of a unit of energy generated, but do not represent the energy itsel f. The attributes conveyed with RECs include information about the generator, such as: type of resource (e.g., wind), plant

- level air emissions (if any), geographic location, nameplate capacity (MW), commercial operation date, ownership, and the eligibilit y for RPS compliance or voluntary market certification.63

RECs are separated from the power generated, the power has no attributes associated with it and is considered generi c or “null” power. 89

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

 Eligible renewable energy resources . While most RPS

- el igible resources in most states
will result in avoided CO 2 emissions from fossil fuel

- fired EGUs, some RPS

- eligible

resources in some states are responsible for greenhouse gas (GHG) emissions or do not meet common definitions of renewable energy (e.g., was te coal, coal

- bed methane, and fuel cell operation using fossil

- fuel feedstocks).

 Existing and new resources . RPS

- eligible resources can include facilities that began operation prior to the enactment of the RPS and, more importantly, prior to the proposal of the emission guidelines by EPA. 90

 Scope of coverage

. In some states a RPS applies to all retail sales in a state, but in others only a subset of retail sales (e.g., only investor

- owned utility retail sales) are subject to a
RPS.

 Credit multipliers . Som e states provide additional incentives for specific eligible resources in the form of bonus credit toward compliance in their RPS accounting framework. For example, these states may favor certain resources (e.g., distributed solar PV), or locally

- important resources or technologies. The MWh produced or renewable energy certificates (RECs) related to MWh production from such facilities may be counted twice or three times toward compliance with a RPS in such states. However, these credit multipliers and bonus es are not an accurate representation of the amount of

89 These distinctions are typically made as part of utility disclosure to customers about the energy resource mix and emissions of the electricity used by a customer that was supplied from by the dist ribution utility. “Generic power” or “null power” refers to energy that has no generation attributes or descriptive information ( i.e. , the remaining system mix of power, after assignment of specified power to different utility customers, through power purc hase contracts or purchase of generation attributes through RECs). For electricity labeling, disclosure to customers, or other market claims, generic or null power is typically assigned the attributes of the remaining system mix of power, after the assignm ent of attributes as described above. 90 In the preamble, the EPA is proposing that, for an existing state requirement, program or measure, a state may apply toward its required emission performance level the emission reductions that existing state programs and measures achieve during the plan period due to actions taken after the date on which the emission guidelines are proposed (i.e., from June 2014 onward).64

renewable energy generation that is attributable to a RPS. For the purpose of quantifying the amount of renewable energy produced as a result of a RPS included as a measure in a state plan, only the ac tual renewable energy generation used to comply with an RPS is
relevant.

 Banking

. Some states permit the carryover of renewable energy produced in one year to satisfy RPS requirements in a subsequent year. Accounting for year

- to

- year carryover should be ad dressed in a state plan, in order to determine the renewable energy generation that occurred in a respective reporting year or compliance period

.

 Alternative compliance payments (ACP)

. Many states allow a compliance alternative which requires obligated en tities to pay a predetermined fee to the state for each MWh of RPS shortfall. Although these ACP payments may be directed to programs to promote the deployment of renewable energy technologies, these payments are not equivalent to renewable energy generati on and should not be accounted as such.

 Interstate issues

. While treatment of interstate emission effects is discussed in detail in
section VII , for quantification, monitoring, and verification of renewable energy generation under a RPS it is important to note that most states allow use of eligible renewable energy resources located in other states to satisfy the state RPS requirements. 91

Considerations related to the quantification, monitoring, and verification of renewable energy generation used to meet a RPSs depends on the design and implementation of the RPS

. Distribution utilities subject to a RPS may meet their RPS obligations by building and operating their own renewable energy generating facilities, entering into bilateral contracts with other parti es to purchase renewable energy, and participating in the REC market

. Each compliance method has specific implications for the quantification, monitoring, and verification of renewable energy generation used to meet RPS obligations. Implications under thes e different pathways are discussed below.

91 This may also include international renewable energy resources, such as Canadian hydroelectric a nd wind energy resources, which may be used to comply with some state RPSs.65

Build renewable generating facilities In many states, u tilities with RPS obligations may build, own, and operate their own renewable energy generating facilities

. This pathway is often used by vertically integr ated utilities subject to a RPS. For large renewable energy generating facilities, production is measured through a revenue

- grade utility meter as it enters the grid at the point of
interconnection

. This meter is subject to the same verification standards as for any other generator participating in the wholesale market.

Some utilities with RPS obligations also build, own, and operate smaller distributed renewable energy generating facilities

. Smaller generators, such as residential rooftop solar PV systems of less than 10 kW capacity, often don’t have discrete metering of their total generation

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

.

Bilateral contract model Under the bilateral contract model, distribution utilities with RPS obligations contract with renewable energy generators for supply

. These contracts typically specify a delivery amount in MWh over a specified contract period. These supply contracts may be short

- or long

- term, may specify g eneration from certain renewable energy EGUs, and may be solicited through an RFP or entered into through negotiation

. Quantification of renewable energy generation (in MWh) is accomplished through the use of a revenue

- grade meter that measures the flow of electricity from the generator into the transmission grid

. A contract may also stipulate an adjustment to the metered MWh generation data to account for transmission losses that occur between the point of injection of electricity to the transmission grid and the point of receipt at a utility transmission or distribution system

. A renewable energy supply contract also generally addresses the ownership of the RECs related to the renewable energy generation

. Under such a

92 Metered data for these PV systems may only track net electricity supply to or from the grid, representing either surplus generation that is not used to serve on

- site electricity load or additional net electricity supplied from the grid if the system does not meet a building’s total electricity load.66

contract, purchase of the RECs should accompany the purchase of the electricity, in order for the utility to satisfy its RPS obligations through the contract. 93

State RPS compliance processes may provide for PUC review of supply contracts, including inspection of meters and verification of e lectricity delivery from the generator to the utility distribution network through a specified contract path (e.g., through evidence of transmission rights held or scheduled). The purchasing utility also reports their purchase and delivery of RPS

- compliant renewable energy pursuant to the contract to the state agency responsible for RPS enforcement, typically the state PUC or state energy office. Verification is accomplished by audit of electricity supply contracts along with REC tracking system reports of RECs held by the utility and submitted for retirement by the tracking system administrator. Some state RPS require that electricity from qualifying renewable energy sources be produced within the state or a specified grid region, or if outside the state or specified grid region, that electricity be delivered to the state or grid region. In such cases, the verification of electricity delivery is typically done by the REC tracking system administrator before issuing RECs for the imported energy. Verification can be provided, for example, by demonstration of scheduled delivery through the ISO or RTO serving the state or region, through demonstration that the seller holds transmission rights for delivery or possession of NERC tags for the energy. 94 Bilateral c ont racts also typically require certification by the seller that attributes related to the sold electricity have not been and will not be otherwise sold, retired, claimed, represented as part of energy sold elsewhere, or used to satisfy obligations in another jurisdiction.

93 This ensures that multiple parties are not using the same MWh of renewable energy generation to comply with their RPS obligations. 94 A NERC Tag, sometimes referred to as an E Tag, is an electronic tag that is used to track wholesale electricity transactions that involve the transfer of electricity across or through control areas. NERC Tags allow transmission system operators to track electricity transactions in real time in order to assess any potential reliability implications of scheduled power transactions. NERC Tags define the physical path of an electricity transaction from the point of generation to the point of receipt, and also define the financial path, including all parties to a transaction. All wholesale electricity transactions that will result in the transfer of electricity from one control area to another, or that involve transfers through a control area, must be accompani ed by a NERC Tag. Based on a real

- time assessment of NERC Tags, system operators can curtail transfers if reliability issues would arise as a result of the transfer. NERC tags are issued through an electronic system in accordance with specifications establ ished by the North American Electric Reliability Corporation (NERC).67

REC model Under the REC model, renewable energy generators register their EGU with a renewable energy tracking system, which have been established by several regional groupings of states, as
well as a few individual states. 95 The registrat ion process collects data about the generator’s attributes: type of resource (e.g., wind), plant

- level emissions, geographic location, nameplate capacity (MW), commercial operation date, ownership, and the eligibility for RPS compliance or voluntary marke t certification. After the generator is registered, revenue

- meter data is transmitted to the tracking system

. Meter accuracy is verified for renewable energy generators in the same manner as for any other generator participating in wholesale electricity ma rkets.

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

. The renewable energy generator can then sell the renewable electricity as a bundle (both the commodity electricity and the associated REC) or unbundle the RECs from the electricity and sell the two products separately

. Other market participants, such as brokers, REC marketers, and load

- serving entities also maintain accounts with the tracking system so that REC electronic transactions can be
recorded within the tracking system platform

. The system tracks each REC through these transactions and ultimately “retires” the REC when the final purchaser designates it for
retirement

. Retirement could result from the REC being used to satisfy a state RPS, or as a result
of a volun tary buyer retiring the REC to demonstrate that they had purchased and used renewable energy to meet their electricity demand.

95 Currently, nine regional renewable energy certificate (REC) tracking systems operate in different regions of North America, including: Texas Renewable Energy Credit Program, run by the Electric Reliability Council of Texas (ERCOT), NEPOOL Generation Information System (GIS), PJM Generation Attribute Tracking System (PJM

- GATS), Western Renewable Energy Generation Information System (WREGIS), Midwest Renewable Energy Tracking System (M

- RE TS), North American Renewables Registry (NARR), Michigan Renewable Energy Certification System (MIRECS), Nevada Tracks Renewable Energy Credits (NVTREC), and North Carolina Renewable Energy Tracking System (NC

- RETS). For more information see http://apps3.eere.energy.gov/greenpower/markets/certificates.shtml?page=3

.68

Because the tracking system follows the REC from the point of issuance to retirement, including all interim transactions, it min imizes the opportunity for renewable energy to be
double

- counted across, for example, two different state RPSs, or between two voluntary purchasers

. In recent years, the various tracking systems have developed interchange standards so that RECs generated w ithin one tracking system can be transferred to and used within another tracking system. 96 Note that not every potential interchange possibility is currently supported, and that many states have additional eligibility restrictions within their RPS that may limit the
use of RECs related to electric generation from distant locations

. These include requirements in
some state RPS s for the seller to hold firm transmission rights for delivery of the accompanying electricity from the renewable energy generator int o the respective ISO/RTO system or grid system in which a state is located

.
Small distributed generators Smaller distributed generators, such as residential rooftop solar PV systems of less than 10 kW capacity, often don’t have discrete metering of their total generation

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

. Where such projects are third

party owned and operated, the project developer will own the RECs and factor their revenue
value into thei r pricing offered to the site host for electricity supply

. Note also that many utility

sponsored renewable energy incentive programs stipulate that all RECs resulting from the project must be transferred from the generation owner to the utility as a condit ion of participation in the incentive program

. These RECs can then be used by the utility to meet its RPS obligations, or can be sold to other parties.

96 Additional linkages between tracking systems are being established. More information can be found at htt p://www.narecs.com/resources/registries/69

State agency role In many states, the PUC or its equivalent is responsible for establishing the det ailed rules and procedures that obligated parties must follow to comply with a RPS

. The PUC is usually responsible for receipt and review of obligated parties’ periodic compliance reports, imposing compliance penalties as needed, and for evaluating the imp acts of the program on energy costs, generation diversity, and market operations

. The list of eligible resources and MWh requirements are often set through state legislation, but these decisions may also be delegated to the PUC for study and promulgation t hrough regulations of commission orders.

In some states the energy office may be responsible for certifying the eligibility of specific generators to participate in the RPS and for making siting determinations

. In New York, for example, the New York State Energy Research and Development Authority (NYSERDA) is responsible for the centralized procurement of the renewable energy needed to meet the RPS for
all of the state’s investor

- owned utilities

.

2

. Feed

- in Tariffs

Feed

- in tariffs (FITs) are offered by some individual electric distribution utilities and

some states for renewable energy systems that meet eligibility criteria

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

p ublished pricing formula for a specified period of time

. FITs typically have caps on the amount of renewable energy that will be purchased by a utility (in MWh of energy or MW of capacity). FITs may also include customer impact caps for the tariff as a who le (in total dollars spent or in specified retail rate impacts allowable), and may also have limits on the size of any participating renewable energy generator from which the utility will purchase electricity through the FIT

. FITs may also have pricing for mula s that are differentiated by resource or that change through time as specified benchmarks are achieved (e.g., MW of renewable energy generating capacity subject to the FIT, amount of electricity purchased through a FIT as a percentage of utility sales, or retail

97 There are several states that offer FITs, including California, Hawaii, Maine, Oregon, Rhode Island, South Carolina, Vermont and Washington, as well as numerous electric utilities.70

rate impact level reached)

. Typically, the tariff treats all similarly

- situated generators in a
consistent manner.

Quantification of renewable energy generation output under a FIT is accomplished through the use of a revenue

- grade meter to meas ure the generator’s injection of electricity into the grid

. The utility’s tariff will typically specify the minimum performance characteristics and/or certifications that a meter must meet in order to be used on its system

. Utilities retain the right to in spect and test the calibration of meters connected to their systems

. As the utility will be paying the generator each month based on the meter reading, it is in the utility’s interest to ensure that the meter is reading precisely and accurately through tim e.

Both the utility and the state will need to consider the ownership of the environmental attributes arising from the renewable energy generation purchased by a utility through a FIT, and whether the renewable energy can be counted toward RPS compliance

. If renewable energy generation purchased by a utility through a FIT may be counted toward RPS compliance, then it should not be counted separately as another renewable energy program in a state plan.

State agency role FITs are usually authorized by state statutes that specify w hich utilities must offer a FIT, eligibility criteria (e.g., renewable energy resource type, location, project MW generating capacity limits), and sometimes overall program targets ( e.g., total installed MW of generating capacity su bject to the FIT ). State statutes may also specify whether the utilities offering a FIT
will receive the RECs related to purchased electricity generation output for use in complying with a state RPS, and whether customers receiving FIT payments may also re ceive incentives
under other utility and state progr ams. Typically state statutes leave implementation details to the
PUC ( or other utility governing body , if applicable, for municipal and cooperative utilities) , but may provide guidance on what to conside r in setting FIT payment levels. Based on this statutory authority, PUCs develop detailed rules governing implementation, which can include payment levels and contract length. PUCs may direct the affected utilities to develop standard contracts
with all th e terms and conditions spelled out, and these standard contracts must be approved by
the PUC

. As with state RPS , the PUC is responsible for receipt and review of the utility’s71

periodic status reports, approving changes to a tariff if needed, and evalu ating the impacts of the
tariff on retail prices, generation diversity, and electricity system operations

.

Several FITs are offered by distribution utilities not overseen by PUCs , such as municipal utilities and rural electric cooperatives . T hese utilities ha ve a variety of governance structures ( e.g. , municipal government, coop erative board of directors ). The utility governing bodies in these situations will be responsible for receipt and review of the utility’s status reports, taking
corrective action if nee ded, and evaluating the impacts of the tariff

.

3

. State Tax Incentives
Several states offer a variety of tax incentives to promote the production and use of renewable energy

. These currently include sales tax exemptions for certain kinds of equipment (e. g., PV panels)
, property tax abatement for improvements to a building or facility related to the asset value of the renewable energy generati ng system, and income tax credits for the installation of renewable energy systems based on capacity or investment level. Several states provide a renewable energy production tax credit based on the amount of renewable energy generated

. This ap proach is useful because it results in a measureable quantity of renewable

energy electricity generation

.

With a production

- based tax incentive, the renewable energy generator might claim a tax credit for each MWh of qualifying renewable energy generation within the state

. One design consideration for a production

- based tax incentive that affects quantification of renewable ene rgy generation output is whether the electricity must be sold to a third party as opposed to being used by the site host

. In the former case, a revenue

- grade utility meter would be present at the point of interconnection to the electricity grid, which prov ides measurement of MWh generation output for tax compliance purposes

. Site

- host use might necessitate the installation of an additional meter within the project site to permit reliable measurement of the renewable energy generator’s output

.
State agency role Currently, existing state tax policies are primarily under the authority of the state revenue agency. The state revenue agency might have the primary responsibility for establishing the rules72

for production

- based tax incentives, although it may seek advice from state energy agencies regarding the technical aspects of renewable energy generator operation and the behavior of energy markets

. The renewable energy generator might claim the tax incentive through the state tax collection process and report M Wh generation to claim the tax credit. The revenue agency could receive tax filings from the owner and operators of renewable energy generators and be responsible for determining whether the taxpayer’s claim for tax incentives is supported by the MWh gener ation evidence

. Assuming the state revenue authority retains its ability to audit the taxpayer’s return, it could verify claimed MWh generation.

As with FITs, the renewable energy generation resulting from production

- based tax incentives might be used for RPS compliance

. If that were to become the case, then it should not be counted separately in a state plan from MWh generation used to comply with a state RPS.

4

. Options for Quantification, Monitoring, and Verification of Renewable Energy Measures in State Plans
As summarized in the preamble, and discussed in more depth in this section, utilities and states have conducted ongoing evaluation of renewable energy measures and programs for several decades. These evaluations, which include quantificatio n, monitoring and verification of results, generally rely upon a set of standard practices and procedures. In addition, states have designed and implemented REC tracking systems to facilitate compliance with state RPS. This resource provides the ability to track the location and attributes of renewable energy generators, and the electric generation from these generators, as well as the parties that use RECs for compliance with state RPS. As a result, existing state and utili ty requirements and processes for quantification, monitoring, and verification of renewable energy programs and measures generally provide a so lid foundation for minimum requirements and guidance for EM&V for RE

measures in state plans that are esta blished by the EPA.

The programs discus sed above (RPS, FIT
, and performance

- based tax incentives) all require quantification, monitoring, and verification of electricity generation from renewable energy generators, as well as provisions of other key information
, to determine eligibility and73

tra ck program activity or compliance with regulatory requirements (if applicable)

. Quantification of electricity generation is typically through the use of revenue

- quality meters
, 98 or engineering estimates for small distributed generators. These data are esse ntial to program management, verification of compliance or payments, budget contro l, and tracking progress toward goals. For example, PUCs overseeing compliance with state RPS receive compliance informa tion from each obligated utility, including retail sal es, compliance status based on MWh of electricity generated by eligible utility

- owned renewable energy sources, or electricity or RECs purchased from eligible renewable energy generators, which may also consider application of multipliers or
alternative co mpliance payments

. 99 PUCs overseeing utility FIT and state agencies overseeing performance

- based tax incentive s managers receive reports containing MWh of electric generation from qualified electric generators that receive d payments under either a FIT or ta x i ncentive . These data are essential for normal program management and accountability.

Current state data requirements under RPS, FIT, and production

- based tax incentives are tailored to the objectives of these programs and facilitating effective regulat ory oversight. Typically, avoiding CO 2 emissions, while considered a relevant co

- benefit, is not a primary objective of these regulations and programs. As a result, additional information and reporting may be necessary to accurately quantify the avoided CO 2 emissions associated with the renewable energy generated through an RPS, FIT, or production

- based tax incentive that is included in a state plan

.

The following types of information will increase the accuracy and verifiability of avoided
CO 2 emission es timates related to renewable energy requirements, programs, and measures included in a state plan. For example, information on the location of the renewable energy generation (e.g., in

- by state or within a specified grid region ) of the renewable energy gen eration used for compliance with state requirements and programs would be helpful in determining
avoided CO 2 emissions. Information about the location of electric generators that supplied

98 “Revenue

- quality meter” ref ers to a meter used for billing purposes in wholesale electricity markets, which typically need to meet ISO or RTO precision requirements or other specifications. 99 Compliance status will also consider the application of credit multipliers or alternative c ompliance payments, if relevant under an RPS.74

electricity generation that was imported to a state or grid region, will also be important. Time

differentiated information related to electricity generation is also useful in estimating avoided
CO 2 emissions. In particular time

- differentiated data is necessary to estimate the marginal
avoided CO 2 emissions related to elec tric generation. Such time

- differentiated data could be based on metering or engineering estimates for a technology type that indicate the typical generation profile for the renewable energy resource. This could include time differentiation on an hourly, d aily, or seasonal basis. If RECs can be b anked and used or RPS compliance at a later time than the year in which the electricity generation related to the REC occurred, information about the quan tity and vintage of RECs from prior year(s) generation that i s used for RPS compliance will also be useful.75

VI

. Reporting and Recordkeeping for End

- Use Energy Efficiency and Renewable Energy Programs and Measures
As discussed in the preamble, in section VIII.F.5, repo rting and recordkeeping for end

use energy efficiency and renewable energy requirements and programs will be an important component of certain types of sate plans. If a state plan incorporates renewable energy and
demand

- side energy efficiency requirements and programs under a rate

- based approach or implements a mass

- based portfolio approach with such measures, reporting and recordkeeping requirements for an approvable plan would differ from those applicable to an affected EGU. For example, these requiremen ts may include compliance reporting by an electric distribution utility subject to an end

- use energy efficiency resource standard (EERS) or renewable portfolio standard (RPS). They may also include reporting by a vertically integrated utility implementing an approved integrated resource plan. In the latter instance, the utility may also be the owner and operator of affected EGUs, but additional reporting of quantified effects of renewable energy and
demand

- side energy efficiency measures under the utility p lan would be necessary to demonstrate emissions performance under the state plan. In other instances, a state agency or entity or a private or public third

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

In the preamble, the EPA seeks comment on appropriate reporting and recordkeeping requirements f

or entities implementing end

- use energy efficiency and renewable energy programs included as enforceable measures in a state plan, or for entities subject to requirements
, such as an EERS or RPS , tha t are included as an enforceable state plan measure. This section provides examples of current reporting and recordkeeping under state energy efficiency requirements and programs, such as EERS, RPS, and utility and state deployment programs for energy effi ciency and renewable energy. The section then examines the suitability of these reporting and recordkeeping practices as potential approaches in an approvable state plan.76

A

. Reporting for End

- Use Energy Efficiency Programs and Measures
Reporting requi rements and time frames (i.e. how often reports are required) for entities implementing energy efficiency programs and measures are key considerations for state plans

. In

a state

- regulatory context with PUC oversight, impact reports are the mechanism by wh ich utilities and other program administrators document energy (MWh) and demand (MW) savings

. These reports serve as basis for PUC review of total achieved energy savings relative to program goals or regulatory requirements, as well as for determining fina ncial performance incentives for utilities, where they exist

.
In most states, impact reporting is initially conducted at the level of efficiency “programs” (each consisting of numerous “project” installations or efficiency measures occurring at individua l homes, commercial buildings, or industrial facilities)

. Program level data are then aggregated to the “portfolio” level to capture the full impact of energy efficiency investments occurring under a PUC’s jurisdiction for the timeframe of interest.

Impa cts reports are typically submitted annually, but in some cases program administrators also provide interim (e.g., quarterly) reports

. This added step can help inform progress towards goals, as well as provide for corrections in cases where evaluated (ex

- p ost) energy savings are not achieving projected or claimed (ex

- ante) savings levels

.
The information provided below presents a range of common reporting elements and common practices implemented by state PUCs

. These reporting elements and practices

– whi ch raise important considerations for the reporting of energy

- efficiency impacts in state plans

– include:

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

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

o Short description of the policies or programs implemented

o Implementation schedules and timeframes

 Energy

- savings impacts reported to PUCs in annual reports:77 o Incremental annual and lifetime MWh savings for reporting (in the case of an

energy efficiency program) or compliance years ( in the case of utility compliance
with a multi

- year Energy Efficiency Resource Standard)

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

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

 EM&V process followed:

o Date and location of on

- site facility visits and field observations

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

o Information about evaluators:

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

 Certification that evaluators were selected through a public bid process,
and are third

- parties unaffiliated with efficiency program administrators or the state government

 EM&V methods used:

o Deemed savings values

- name, date, and public location of technical reference manual (TRM) 100 used for deemed savings values

o Direct measurement approaches

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

 Other documentation:

o Data about the quantity of measures/projects on which the full program

- level energy savings impacts are based (i.e., information de scribing the sample size and sampling procedures used)

o Whether net or gross energy savings 101 are estimated, definitions used for gross and net savings, and the basis for gross to net calculations, if applicable

100 A technical reference manual (TRM) is a document consisting of predetermined savings values, assumptions, methods, and calculation approaches for conducting EM&V of state demand

- side energy efficiency program s. Most states with robust efficiency programs rely on a TRM.78 o Avoided transmission and distribution (T&D) im pacts assumptions, if applied

The energy savings EM&V reporting elements listed above vary from state to state in terms of type and level of documentation, and reports are provided in different formats from state to state. This significant variation amon g states in reporting contents and format raises several considerations for states utilizing demand

- side energy efficiency programs in state plans

. One is whether the reporting processes, timeframes, and documentation required by state PUCs,
described abov e, are sufficient and appropriate in the context of state plans

. Another consideration is whether lead state agencies that oversee energy efficiency programs should be required to certify reported energy efficiency savings impacts on behalf of the state, p otentially including certification that the values are appropriate and conservative, and meet their approval

. A final consideration is whether and how energy savings impact reports are made available for public input and comment prior to finalization, reco gnizing that impact reports in many states exist but are not easily located or widely accessible by the public, nor are they provided in
consistent formats from state to state.

B

. Reporting for Renewable Energy Programs and Measures

1

. Typical Reportin g and Compliance Requirements under State RPS
Each state has different reporting and compliance requirements for its RPS, but all states with mandatory RPS require obligated entities to provide compliance reports to the state PUC or equivalent state over sight agency. Compliance obligations are typically specified in authorizing legislation, regulations, or PUC orders. Compliance is typically on an annual basis, and includes a list of required reporting elements. Some states also require distribution utili ties to provide an implementation plan describing how they will comply with the state RPS rules in the future

.
Data requirements for reporting may vary based on the design and implementation of a RPS. However, for nearly all state RPS requirements, annua l compliance report data is based on

101 Gross savings are the change in energy use and/or energy demand that results directly from program

- related actions taken by program participants, regardless of why they participated in the pro gram. Net savings refer to the change in energy use and/or energy demand that is directly attributable to a particular energy efficiency program.79

measurable electric generation results and verified through tracking system data. 102 In some states, compliance reports may also include state

- level projections of renewable energy generation resulting from current or pro posed state RPS policies.

The most common form of tracking system for RPS compliance is a regional or state REC tracking system or registry. These systems track RECs for both the compliance and voluntary markets. RECs are typically provided with a unique identification number and may be certified by a third

- party verifier. Annual compliance reports containing REC data typically include the number of RECs the utility or load

- serving entity procured and retired, what renewable energy generators supplied the RECs, and how much the utility spent on procuring the
RECs.

2

. Typical Reporting for Renewable Energy Deployment Programs 103
Renewable energy depl o yment progr ams involve the provision of a payment or credit for a renewable energy project, or for a quant ified amount of electricity generation , in the case of performance

- based incentives. Qualification of eligible projects and payment for qualifying electric generation (or related attributes) require reporting of electric generation and other project
for ea ch specific program. Program administrators use this information to track program progress and report to PUCs or other oversight entities. The summary below addresses typical reporting required for utility

- administered programs, as well as programs adminis tered by non

- profit entities and state agencies and authorities.

Reporting for utility administered renewable energy incentive programs Some utilities offer incentives to electricity consumers to accelerate the deployment of renewable energy technologies, such as rebates, feed

- in tariffs, and net metering programs. As mentioned previously, it is easier to quantify the renewable electricity generation resulting from some programs than it is for others. Utilities administering FITs, for example, will track t he

102 Some state RPS require electric utilities to procure a specified amount of renewable energy generating capac ity, rather than supply a specified number of MWh or percentage of electricity supply from renewable energy generation to retail customers. 103 In this section, “deployment programs” refers to incentive programs and market transformation programs designed to accelerate the market deployment of renewable energy technologies.80

number of customer cont racts, resource type, capacity of ea ch contracted project, MWh generated
, and utility expenditures for that generation under the tariff . In contrast, utilities administering a rebate or loan program are more likely to track the nu mber of customer participants, the type and size of the projects, the cost of the projects
, and the amount of rebates paid or loans provided. Measuring the electric generation output of these projects may not necessary to evaluate program status.

Net

- met ering is a renewable energy incentive program that is based on performance
, but where the total output of the net

- metered device is often unknown. Utilities reporti ng on net

metering programs track the number of participating customers, the type and size o f net

- metered systems, a nd overall net

- metered capacity. However, the gross amount of electricity generated may not be known if a single bi

- directional meter is used. Such meters only record net electricity
withdrawn from the grid or net electricity produc tion supplied to the grid during an identified time period . Utilities and the customers where the renewable energy generating system is located

may not necessarily know the total electric generation from the renewable energy system
, u nless
two meters are i nstalled

– one to measure total output from the customer

- sited system, and another to measure the total electricity purchased from the utility.

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

.81

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

. 104 IRPs document how a utility will meet forecasted annual peak and energy demand over a defined period of time through a combination of supply

- side and demand

- side resources. IRPs are typically mandated through state legislation or PUC orders and may incl ude renewable energy generation planning, particularly as it relates to compliance with in

- state requirements. IRPs are typically submitted on an annual basis to a state utility commission and/or other state entity, and address a multi

- year period (e.g., 1 0 years is a typical period for an IRP). IRPs are a good resource for tracking and forecasting utility renewable energy developments within a state. Though they may not include renewable energy production data, data included in IRPs may help states project renewable energy generation trends in subsequent years, and are a good resource for the development of state plans.

Reporting for renewable energy incentive programs administered by non

- profit or state entities State renewable ener gy financial incentive s ar e typically administered by a PUC, state revenue agency, other state agency (e.g., state energy office), or a private non

- profit or for

- profit entity contracted by a state agency. These programs may include an administrative process for

pre

- qualificati on, which in some instances may be competitive (e.g., performance

- based contracts) or available on a first

- come, first

- serve basis (e.g., capped production tax incentive)

. Applications to incentive programs are good sources of data, and program admini strat ors usually compile data from approved applications to track program status. Additional reporting data is also typically required to receive the incentive. For example, a production

- based tax incentive is
calculated based on the amount of electricity gener ated by a renewable energy installation, which may be tracked and verified through utility or third

- party metering protocols. These reports
, which are currently used for internal reporting for budgetary control and performance evaluation,
and to track othe r performance metrics for regular public program reporting, could form much of the basis for reporting under state plans for such measures.

104 IRPs are typically required in states with vertically integrated electric utilities, but are less common in states that have deregulated their electricity sectors and introduced competit ion for the supply of electricity to retail customers.82

3

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

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

- qua lity meters, and verified through tracking system data. 105 Other requirements and programs that provide performance

- based payments and incentives, such as FITs , net metering, and performance

- based tax incentives, also require reporting of metered generation output

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

In addition to the reporting states currently require for renewable energy requirements
and programs, supplemental reporting information or adjustments may be necessary for state plans to demonstrate the avoided CO 2 emissions associated with these requirements, programs,
and measures. States may need to require additional reporting detail, such as the location of renewable energy generating units that supplied output used to comply with a state RPS. Additional rep orting detail about when renewable energy was generated may also be valuable for estimating the avoided CO 2 emissions from renewable energy generation, especially if a marginal avoided emission rate approach is used. This includes r eporting of the typical generating profile of a renewable energy generating unit
, group of units, or renewable energy resource type

. 107 For distributed renewable energy resources, reporting of the MW capacity of generating systems that are installed as a result of state requirement s or programs during a reporting period would also be useful for estimating avoided CO 2 emissions. These distributed

105 Small distributed renewable energy systems, such as those below 10 kW in capacity, are often allowed to use engineering estimates to determine annual output. 106 Some of these programs, such as net met ering, may also require supplemental reporting in order to track total generation that avoids CO 2 emissions. In many instances, net metering programs only track the net electricity supplied to a customer or supplied to the grid by the renewable energy syst em, rather than total generation output. 107 This might include information about the seasonal or daily generating profile of the generating unit or renewable energy resource type.83

resources, since they are located “behind” the utility meter at a customer location, have a similar effect in reducing the demand for elect ricity supplied from the grid as end

- use energy efficiency

measures.

Example reporting requirements that provide sufficient data for estimating the avoided
CO 2 emissions from renewable energy requirements and programs might include the following:

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

 MW capacity of “behind

- the

- meter” distributed renewable energy generating systems added during a reporting period as the result of a sta te program

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

 For REC data, information including the following genera tor attributes: type of resource (e.g., wind), plant

- level emissions, geographic location, nameplate capacity (MW), commercial operation date, ownership, and the eligibility for RPS compliance or voluntary market certification84

VII

. Trea tment of Interstate Emission Effects
Programs and measures in a state plan, such as RE and demand

- side EE measures, may affect the emission performance of the interconnected electricity system beyond a state border. In addition, many state measures allow f or actions in neighboring states to meet the in

- state requirement, or explicitly address CO 2 emissions in neighboring states. For example, many state renewable portfolio standards allow for generation by qualifying renewable energy sources in
other states to count toward meeting the state portfolio requirement. Some states also apply CO 2 emission requirements related to the generation of power purchased by regulated utilities, including power imported from out of state.

As discussed in the preamble to th e proposal, in section VIII.F.6, the EPA recognizes the complexity of accounting for interstate effects associated with measures in a state plan in a consistent manner, to minimize the likelihood of double counting. The EPA also realizes that
interstate effe cts on CO 2 emissions from affected EGUs could be attributed in different ways in the context of an approvable state plan. This section discusses in more detail the options and
alternatives for treatment of interstate CO 2 emission effects presented in the p reamble. The se options and alternatives could be applied to both projections of plan performance and demonstration of achieved emission performance under a plan. These options and alternatives may not be mutually exclusive

– in some instances states could apply different approaches, without introducing the potential for double counting of emission effects. One option presented
could lead to double counting of emission effects, and we highlight these aspects of this option in
the discussion below.

In genera l, the options and alternatives address different possible state plan scenarios, and consider the range of interstate approaches that states are currently using to implement electricity sector policies, such as multi

- state emission budget trading programs and regional renewable energy certificate markets for state RPSs. The options and alternatives reflect possible accounting approaches for interstate emission effects under CAA section 111(d) that could potentially align with these current state programs an d measures that we anticipate states may want to include in a state plan.85

A. Background
Electricity flows across state lines. Often electricity load centers (i.e., areas of high electricity demand) in one state are supplied in part by generating units i n another state. As a result, some states are net exporters or importers of electricity on an annual basis. Reducing electricity load through improved end

- use energy efficiency (e.g., through state energy efficiency programs) or deploying new renewable ene rgy electric generating capacity (e.g., through a state RPS) therefore can result in CO 2 emission effects that are realized outside the state that implements the regulation or program that produces the effects. Reducing electricity demand or increasing ava ilable electric generating capacity also often impacts the economic dispatch curve and locational economics that are used to dispatch EGUs on a regional basis. As a result, state
end

- use energy efficiency and renewable energy regulations and programs often have regional effects on electricity generation and avoided CO 2 emissions. In addition, many state regulations explicitly address CO 2 emissions in neighboring states, or allow for actions in neighboring states
to meet an in

- state regulatory requirement. F or example, many state RPS allow for generation in other states to count toward meeting a utility portfolio requirement

.

End

- use energy efficiency actions reduce electricity load, and ultimately impact electric generation. In some instances improving end

- use energy efficiency will reduce electric generation nearby a load center (e.g., in the case of a load pocket with limited access to electricity transmission capacity). I n such cases, it may be feasible to directly link in

- state end

use energy efficiency programs and measures to avoided CO 2 emissions from specific in

- state EGUs. More often, reduction of electricity load will impact EGU dispatch across a regional generation control area, based on factors such as power plant economics and electricity

transm ission capability, and could also impact flows between control areas. 108 In these cases,
state end

- use energy efficiency programs and measures will affect electricity generation in the state that reduces load, as well as in neighboring states.

108 Often these dispatch economics differ by location, based on electricity dem and, transmission constraints, and generation economics of individual power plants necessary for meeting demand (e.g., in competitive wholesale markets, these factors are represented through locational marginal prices (LMPs), which determine dispatch).86

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

The approach to implementing an RPS may differ in vertically integrated, cost

- of

- service states where the distribution utility also owns electric generating c apacity and dispatches generation resources within its service territory. In such cases, the RPS may require a utility to increase its renewable energy generating capacity, rather than supplying a percentage of the electricity it delivers to retail custome rs from renewable energy sources to meet load. A number of state RPS also include “carve

- outs” or “set

- asides” where a portion of the renewable energy supplied to retail customers must come from renewable energy generating capacity located inside
the state . Most of these carve

- outs are for distributed solar photovoltaic generating capacity, which are located at the point of customer end

- use (e.g., rooftop mounted solar PV on residential homes and commercial buildings). 109 Distributed solar PV capacity often p rovides benefits to the electric distribution system by improving distribution system reliability and avoiding the need for distribution system capacity upgrades. This type of distributed renewable energy generation has
effects similar to end

- use energy ef ficiency, as it reduces the customer electricity load that must

109 A number of RPS also have carve

- outs for other renewable energy resources, typically those where there is a significant renewable energy resource located in the state. An example is carve

- outs for offshore wind energy in coastal states.87

be met through large EGUs connected to the grid. 110 Regardless of the approach taken, state RPS regulations typically have impacts on EGU dispatch, and related avoided CO 2 emissions, beyond
the state border.

B

. Summary of Possible Approaches for Treatment of Interstate Emission Effects
As discussed in the preamble, the EPA is proposing a set of approaches for addressing interstate emission effects that result from the implementation of state pl ans that incorporate end

use energy efficiency and renewable energy programs

. The preamble also solicits comment on
additional alternatives. The proposed approaches in the preamble include:

 For EE programs and measures:

o A state may take into account in it s plan only those CO 2 emission reductions occurring in the state that result from demand

- side energy efficiency programs and measures implemented in the state.

o States participating in multi

- state plans would have the flexibility to distribute the
CO 2 emiss ion reductions among states in the multi

- state area.

o States could jointly demonstrate CO 2 emission performance by affected EGUs through a multi

- state plan in a contiguous electric grid region, in which case attribution among states of emission reductions f rom demand

- side energy efficiency measures would not be necessary.

 For RE programs and measures:

o Consistent with existing state RPS policies, a state could take into account all of the
CO 2 emision reductions from renewable energy programs and measures impl emented by the state, whether they occur in the state and/or in other states.

o States participating in multi

- state plans would have the flexibility to distribute the
CO 2 emission reductions among states in the multi

- state area.

o States could jointly demonstr ate CO 2 emission performance by affected EGUs through a multi

- state plan in a contiguous electric grid region, in which case

110 Distributed solar PV is also typically peak coincident, meaning it provides its greatest electric generation output at times of peak system electricity demand. At many times of the day and year, solar PV systems supply electricity back to the grid, when PV system output exc eeds building electricity demand.88 attribution among states of emission reductions from renewable energy measures would not be necessary

This section surveys the ran ge of potential approaches that could be applied for individual state plans, as well as approaches that could be applied on a regional basis. Th e surveyed approaches include th ose proposed, as well as alternatives. These basic approaches, including variant s of some approaches, include:

 State may only claim the impact of a measure in reducing in

- state EGU CO 2 emissions For plan measures such as end

- use energy efficiency and renewable energy regulations and programs, estimating the avoided CO 2 emissions from in

- state versus out

- of

- state EGUs could be addressed through modeling, other analytical tools, or proxy metrics (e.g., net import factor).

 State that implements the measure claims the emissions reduction benefit Under this approach, the state that impleme nts the measure (e.g., end

- use energy efficiency and renewable energy regulations or programs, or an emission limit that
addresses out

- of

- state generation) claims the avoided CO 2 emissions, regardless of where they occur.

 Cooperative multi

- state accounting Multiple states are allowed to mutually agree to how they will distribute avoided CO 2 emissions from state plan measures (e.g., end

- use energy efficiency and renewable energy regulations or programs, or an emission limit that addresses out

- of

- state
gen eration) across their respective EGU fleets. Avoided CO 2 emissions are distributed among states by agreed formula they derive

– an accounting “credit” in one state for

out

- of

- state avoided CO 2 emissions is complemented by an accounting “debit” in
the ot her state where the avoided CO 2 emissions occurred (i.e., through an increase in reported CO 2 emissions or CO 2 emission rate).

 Tradable regional EE/RE credit market
This is a variant of the multi

- state accounting approach, which could be applicable where multiple states in a region are implementing rate

- based state plans. Under this approach,
state end

- use energy efficiency and renewable energy regulations and programs that meet89

EM&V guidelines or requirements are allowed to generate credits, based on MWh of energy savings or renewable energy generation. These credits, which are denoted in
avoided tons of CO 2 or avoided MWh, could be used by affected EGUs toward demonstration of compliance with state rate

- based CO 2 emission limits within a designated region . EE/RE credit issuance could be on a project and/or program basis. State accounting for interstate emission effects would be addressed through the credit market and determined based on credits held by affected EGUs.

 Regional demonstration by states of EGU emission performance States are allowed to regionally demonstrate emission performance by affected EGUs. Stets jointly demonstrate emission performance for affected EGUs, in terms of total CO 2 emissions (under a mass

- based multi

- state plan) or weighted average CO 2 emission rate (under a rate

- based multi

- state plan).

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

Table 3 includes illustrative examples of the a pplication of some of the different approaches for addressing interstate emission effects summarized above. The table explains how these approaches might be applied in different state plan contexts. The illustrative examples consider the range of approache s states are currently using to implement electricity sector policies, all of which interstate effects, such as multi

- state emission budget trading programs, regional renewable energy certificate markets used for state RPS compliance, and end

- use energy ef ficiency programs.90

Table 3. Applied Examples of Intersate E missio n E ffects Attribution A pproaches

1

. State May Claim the Impact of a Measure on CO 2 Emissions from Affected EGUs Within its Borders
Under this approach, the effect of a state meas ure could be applied to help demonstrate emission performance by affected EGUs in the state if it has the effect of avoiding CO 2 emissions from those in

- state EGUs. This could be done regardless of whether the action taken to implement the state measure oc curs within or outside the state. For example, renewable energy generation that occurs outside the state as a result of a state renewable portfolio standard obligation would still be a valid state plan action, provided the out

- of

- state renewable energy

gen eration has the effect of avoiding CO 2 emissions from affected EGUs inside the state. As another example, for a state that is a net importer of electricity, improvements in demand

- side EE and related reductions in electricity demand may reduce the need for generation from both
affected in

- state and out

- of

- state EGUs. These electricity demand reductions could be applied to help demonstrate emission performance by affected EGUs in the state if the reduction in electricity demand has the effect of avoiding CO 2 emissions from those in

- state EGUs.91

Estimating the effect of RE and demand

- side EE measures on in

- state versus out

- of

- state EGU CO 2 emissions could be addressed through modeling, other analytical tools, or proxy metrics such as a net import factor.

Mod eling could be used to assess the interstate effects of state measures on EGU CO 2 emissions, both for projections of emission performance under the plan and ex post demonstration of performance achieved. Under this approach, both projected plan performance and performance achieved is assessed on a state

- by

- state basis

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

- by

- state basis within the region. To the extent that a state’s EE/RE measures were projected to avoid CO 2 emissions from its own in

- state EGUs , these effects could be applied to meet the required level of CO 2 emission performance for affected EGUs in the state plan. (See section IV.C of this TSD for a full discussion of using a dispatch modeling approach to projected avoided CO 2 emissions that will be achieved through a plan.)

Ex post demonstrati on of plan performance
To assess the state

- by

- state avoided CO 2 emissions that result from the implementation of a plan, a dispatch model would also be applied to a grid region, on a retrospective “look

- back” basis. This modeling would assess the avoided C O 2 emissions resulting from reported MWh of energy savings and MWh of reported renewable energy generation, as a result of implementation of EE/RE measures in the plan. Under a rate

- based plan approach, modeled estimates of avoided
CO 2 emissions, based on reported EE savings and RE generation, could be applied through an administrative adjustment by the state program administrator or through the issuance of tradable EE/RE credits within the state. For ex post demonstration under a mass

- based plan approach, performance would be determined based on reported stack CO 2 emissions from affected EGUs

— no further analysis would be necessary. (See section IV.C of this TSD for a full discussion of using a modeling look

- back approach to estimate avoided CO 2 emissions.)92

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

- state affected EGUs. For example, in a state that imports 30% of electricity on average during a year, energy savings from EE measures might be multiplied by a factor of 0.70. 111 Avoided CO 2 emissions might then be calculated by multiplying this adjusted energy savings number by th e average or marginal CO 2 emission rate for affected EGUs in the state. This type of approach could be employed in both projections of plan performance and ex post demonstrations of performance. However, this method would be subject to uncertainty, as elec tricity net imports may vary significantly on an annual basis, due to changes in system dispatch. (See section IV.C of this TSD for a discussion of dispatch dynamics that affect avoided CO 2 emissions.)

This approach would avoid double counting of emission effects of state measures among states. However, it could reduce incentives for states to employ measures that have a system

wide, regional effect in reducing EGU CO 2 emissions. In effect, because an adjustment factor would be applied to energy savings un der this approach, a net importer state would need to achieve greater energy savings through end

- use energy efficiency requirements and programs to
achieve a ton of avoided CO 2 emissions under its plan than a state that is not a net importer.

2

. State tha t Implements the Measure Claims the Emission Effects
Under this approach, the state that implements the measure (e.g., an EERS or RPS, or an emission limit that addresses the attributes of purchased electricity from out

- of

- state generation)
claims the avoi ded CO 2 emissions, regardless of where they occur.

If the avoided CO 2 emissions from state plan measures at the regional level are greater than avoided emissions from affected EGUs within the state, these interstate effects would need
to be accounted for and applied to affected EGUs within the state

. This could be achieved through an administrative adjustment by the state, or through a tradable credit system that is
limited to affected EGUs in the state.

111 In this instance, it would be assumed that 30% of the reduction in electricity load resulted in avoided CO 2 emissions from out

- of

- state EGUs that serve electricity load in the importing state.93

Under an administrative adjustment approach, out

- of

- state avoided emissions would be applied to the in

- state EGU fleet by the state program administrator when determining average
fleet CO 2 emission rate or tonnage CO 2 emissions. Under a tradable credit approach, credits
would be issued for all avoided CO 2 emissions resulting from applicable state plan measures, without regard to where the avoided emissions occurred. Since the tradable credit system would be limited to affected EGUs in the state, use of the credits by affected EGUs when demonstrating complia nce with a rate

- based emission limits would functionally apply the avoided CO 2 emissions to the state that was responsible for the measure.

This approach provides a clear policy signal and incentives that reward state actions that
reduce EGU CO 2 emissions on a system

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

- based approach to achieving CO 2 emissions reductions from affected EGUs, without raising the prospect of double counting of emission effects among state.

3

. Cooperative Multi

- State Accounting of Interstate Emission Effects Under this approach, multiple states would be allowed to mutually agree on how they
will distribute avoided CO 2 e missions from RE and demand

- side EE measures across their respective EGU fleets. Avoided CO 2 emissions would be distributed among states according to a formula that they specify. Based on this agreed formula, each state would adjust its demonstrated
emissi on performance by affected EGUs accordingly. In effect, a “credit” for out

- of

- state emission effects in one state would be complemented by a “debit” for such effects in another

state.

This approach provides states with discretion about how to attribute i nterstate effects, based on their situations and policy preferences in a grid region. Importantly, this approach also avoids the potential for double counting of interstate emission effects among states. However,94

this approach is premised on regional colla boration among all states in a grid region. Not all states in a grid region may be willing to cooperate in implementing such an accounting approach.

4

. Tradable Regional EE/RE Credit Market
Under this approach, RE and demand

- side EE actions that meet app licable quantification, monitoring, and verification requirements would be issued tradable credits that could be applied by affected EGUs to their reported CO 2 emission rates when demonstrating compliance with an emission limitation in a state plan. 112 A cre dit issued in one state could be used by an affected EGU in another state toward meeting its respective rate limit. 113

A regional credit market would be premised on agreement among states that credits issued throughout a region could be used in multiple sta tes. The distribution among different states of usage of the credits would be determined by economic factors such as credit prices and EGU marginal emissions abatement costs. In effect, accounting of interstate effects would be allocated among states based on prices in the credit market.

This approach is applicable if multiple states are implementing rate

- based state plans. Where states were implementing a mix of rate

- based and mass

- based state plans in a shared grid region, this approach would lead to do uble counting of emission effects among plans, unless this
market

- based EE/RE credit approach was also coupled with a cooperative accounting agreement among states. In this latter instance, for states implementing a mass

- based approach, where
credits for a voided CO 2 emissions are transferred to affected EGUs located in another state for compliance purposes, the state from which credits were transferred would adjust its reported CO 2 mass emission from affected EGUs when demonstrating achievement of the requi red CO 2 emission performance level by affected EGUs identified in the state plan. 114

112 These credits might be de noted in avoided CO 2 emissions or MWh of electricity savings or electricity generation, as described above in Section VI.E.3., incorporating RE and demand

- side EE measures under a rate

- based approach. Depending on a state’s circumstances and its plan appro ach, these tradable credits might represent a new instrument created for use under a state plan, or a state might use an existing instrument, such as RECs. 113 Credits could be issued on a program or project basis. The types of measures for which credits cou ld be issued and the basis for issuing credits would be an enforceable element of a state plan. 114 Note that in this example, state reporting of overall achieved CO 2 emission performance by affected EGUs under a state plan is distinct from demonstration of compliance by affected EGUs subject to a mass

- based CO 295

5

. Regional Demonstration by States of Emission P erformance
Under this approach, multiple states would demonstrate CO 2 emission performance by affected EGUs on a regional basis. 115 This could allow states in a contiguous grid region to implement a portfolio of RE and demand

- side EE measures without the need for state

- by

- state attribution of avoided CO 2 emissions. Instead, states would assess the impact of state measures in

av oiding CO 2 emissions from the fleet of affected EGUs in the multi

- state region.

This approach creates incentives for the implementation of system

- based approaches that collaboratively reduce EGU CO 2 emissions on a regional basis, while also avoiding the n eed to attribute interstate emission effects among states. However, regional collaboration will require more time for the development of multi

- state plans. This approach is also premised on the willingness of all states in a grid region to participate in t he development and implementation of
a multi

- state plan. Some states in a grid region may be unwilling to collaborate regionally.

6

. Assessment of Interstate Effects by the EPA in the Course of State P lan R eview
Under this approach, the EPA would evaluat e interstate effects on a regional basis during the plan review process. 116 The EPA would assess the emissions performance of affected EGUs on a regional basis, considering the measures contained in the group of state plans for a respective grid region. Unde r this approach, the EPA might conduct a n analysis that considers all of the state program measures together on a combined basis and evaluates projected emissions performance achieved by affected EGUs in the region.

To the extent that all affected EGUs i n a region are projected to achieve the required level of performance represented in individual state plans, or are projected to achieve an aggregate

emission limit. For EGU compliance, no adjustment would be made to CO 2 emissions reported by affected EGUs subject to the mass

- based emission limit, even though emissions from these affected EGUs may have been reduced as a result of EE/RE regulations and programs implemented in a neighboring state. In this case, the state would adjust the overall CO 2 emissions from the affected fleet to account for the “export” of avoided CO 2 emission credits, in order to demonstrate the overall level of CO 2 emission performance that is assumed to have been achieved by the affected EGU fleet under the plan. 115 This approach could be applied for CO 2 emission performance on either a rate or mass basis. 116 For example, this assessment could be for a multi

- state region that generally aligns with a contiguous grid region.96

regional level of performance consistent with the level of required performance included in all state plan s in the region, instances of double counting of interstate effects among states are less important

. T he EPA could indicate as part of plan approval that it will review actual emission performance achieved by affected EGUs during the plan period on a regio nal basis.97

VIII

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

I. Overview of State Climate and Energy P olicies a nd Programs that Reduce Power S ector CO 2 E missions
Across the nation, many states and regions have shown strong leadership in creating and implementing policies, programs, and measures that reduce CO 2 emissions from the power sector, while achieving other economic, environmental, and energy benefits. These policies and programs can serve as a strong foundation as states develop plans to meet state goals for affected electric generating units (EGUs) under the proposed emission guidelines.
This document pr ovides a survey of many of these activities. Policies and programs range from market

- based programs and CO 2 emission performance standards that require CO 2 emission reductions from EGUs, to others, such as renewable portfolio standards (RPS) and energy ef ficiency resource standards (EERS), that reduce CO 2 emissions by altering the mix of energy supply and reducing energy demand. States have developed their policies and programs with stakeholder input and tailored them to their own circumstances and priorit ies. Their leadership and experiences provided the EPA with important information about best practices to build upon in the proposed rule.
States vary in their regulatory structures, electricity generation and usage patterns, while geography affects facto rs such as the availability of fuels, transmission networks, and seasonal energy demand. States have tailored their climate and energy policies and programs accordingly. For example, in some states, utilities are vertically integrated, meaning that the one company is responsible for electricity generation, transmission, and distribution over a given service territory. State public utility regulators have authority over these utilities. In other states, where the electric power industry has been restructur ed, ownership of electric generation assets has been decoupled from transmission and distribution assets, and retail customers have their choice of electricity suppliers. In states where restructuring is active (see Figure 1 ), state public utility regulators do not have authority to regulate the companies responsible for electricity generation, only the electricity distribution utilities. States rely upon and have access to different fuel types and have a variety of EGU types within state borders. States are part of regional electricity grids that usually do not align with state borders. Electricity is imported and exported by utilities across states throughout each regional grid.98

Figure 1 : Status of Electricity Restructuring by State

Source: “Status of Restructuring by State”, U.S. Energy Information Administration, accessed March 19, 2014, htt p://www.eia.gov/electricity/policies/restructuring/restructure_elect.html

. States also have different economic considerations, drivers, and approaches when implementing climate change, energy efficiency, and renewable energy policies, programs, and

measu res. State actions may be motivated by state environmental, energy and/or economic concerns. For example, t en states have passed legislation requiring GHG emission reductions and are using a combination of emission limits, performance standards, energy e fficiency and renewable energy measures to achieve these requirements. 117 Other state measures are motivated by public utility commission (PUC) requirements to achieve all cost

- effective end

- use energy efficiency improvements or by renewable energy generatio n requirements. Policies, programs, and measures vary from state to state in their implementation levels and administration. Some are administered by state agencies and others by utilities, with varying mechanisms for ensuring compliance with applicable r equirements.
This appendix is not exhaustive and is only intended to provide background information about strategies states have used to achieve CO 2 emission reductions in the power sector, advance end

- use energy efficiency, and increase the use of renew able energy resources. For example, states may also consider measures that states have used to support other low

- or zero

emitting generating technologies beyond what is addressed here. State policies and programs

117 States include California, Connecticut, Hawaii, Maine, Maryland, Massachusetts, Minnesota, New Jersey, Oregon, and Washington. Targets are typically defined on a 1990 base year, aiming to achieve reductions of between 0 and 10 percent by 2020, although Maryland and Minnesota have chosen targets of 25 percent below 2006 levels by 2020, and 15 percent below 2005 levels by 2015 respectively.99

included in this appendix are not necess arily approvable in the context of a CAA section 111(d) state plan. In order to be approvable, state requirements, programs, and measures included in a state plan must meet criteria laid out in the proposed emission guidelines.

II. Existing State and U tili ty Policies, Programs, and Measures that A ffect EGU CO 2 E missions
Some state and utility policies, programs, and measures directly target EGU CO 2 emissions by creating specific limits or standards for CO 2 emissions in the power sector. Other policies and pr ograms, such as those that advance deployment of end

- use energy efficiency and renewable energy, are designed to reduce energy demand or promote an increase of supply from low

- or non

- GHG emitting generating sources, which reduces CO 2 emissions from fossil fuel

fired EGUs. Many states that are aggressively pursuing climate change mitigation look to end

use energy efficiency and renewable energy first, recognizing the potential for low

- cost GHG emissions reductions and the economic, reliability, and fuel di versity benefits these resources provide.
For example, according to California, “the integrated nature of the grid means that policies which displace the need for fossil generation can often cut emissions from covered sources more deeply, and more cost

- ef fectively than can engineering changes at the plants alone, though these source

- level control efforts are a vital starting point.” 118 In working to meet its statewide goal of reducing GHG emissions to 1990 levels by 2020 and 80 percent below 1990 levels by 2 050, the California calls its energy efficiency standards “the bedrock upon which climate policies are built” and uses renewable energy to fill any remaining energy needs.” 119 Compared to the costs of other climate policies, California finds that “energy ef ficiency provides substantial emissions reductions and should be an essential element of the BSER CO 2 reduction target.” 120 As another example, Connecticut has a law that requires the state to reduce GHG emissions to 10 percent below 1990 emissions levels b y 2020 and 80 percent from 2001 levels by 2050. 121 Connecticut considers energy efficiency investments, expanded renewable energy generation, and participation in the Regional Greenhouse Gas Initiative (RGGI) among its top ten strategies to reduce GHG emiss ions when considering cost

- effectiveness and GHG emission reduction potential. 122

118 Mary Nichols (Chai rman of California Air Resources Board), letter to EPA Administrator Gina McCarthy, December 27, 2013. 119 Ibid. 120 Ibid. 121 Environment Northeast, Connecticut House Bill No. 5600: An Act Concerning Connecticut Global Warming Solutions , accessed March 19, 201 4, http://www.env

ne.org/public/resources/pdf/CT_Global_Warming_Bill_Summary.pdf

. 122 States’ Section 111(d) Implementation Group Input to EPA on Carbon Pollution Sta ndards for Existing Power Plants, Joint comments from 15 states on Carbon Pollution Standards for Existing Power Plants sent to USEPA Administrator McCarthy on December 16, 2013. Signatories include: Mary D. Nichols, Chairman of California Air Resources Bo ard, Robert B. Weisenmiller, California Energy Commission, Michael R. Peevey, Chair of California Public Utilities Commission, Larry Wolk, MD, MSPH, Executive Director and Chief Medical Offices of Colorado Department of Public Health and Environment, Dan E sty, Commissioner of Connecticut Department of Environmental Protection, Collin O’Mara, Secretary of Delaware Department of Natural Resources and100

Beyond these specific policies and programs, some states implement utility planning requirements that can affect emissions both directly and indirectly. This section describe s a range of existing state actions that fall into all of these categories.

a. Actions That Directly Reduce EGU CO 2 Emissions
Existing state actions that directly reduce EGU CO 2 emissions tend to fall in one of two categories: market

- based emission limits o r emission performance standards.

i. Market

- based Emission Limits
Description
An emissions budget trading program is a market

- based tool for reducing pollution. The basic approach, which involves the allocation and trade of a limited number of environme ntal permits, has been used across environmental media, including air pollution control, clean water regulation, and land

- use applications.
As shown in Figure 2 below, ten states have implemented emissions budget trading programs addressing CO 2 and othe r GHG emissions. These include California’s emission budget trading program and the nine northeast and mid

- Atlantic states participating in the Regional Greenhouse Gas Initiative (RGGI), consisting of Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New York, Rhode Island, and Vermont. 123 , 124

Environmental Control, Dallas Winslow, Chairman of Delaware Public Service Commission, Douglas Scott, Chair of Illinois Commerce Commission, David Littell, Commissioner of Maine Public Utilities Commission, Robert M. Summers, Secretary of Maryland Department of the Environment, Kelly Speakes

- Backman, Commissioner of Maryland Public Service Commission, Ken Kimmell, Commissioner of Massachusetts Department of Environmental Protection, Mark Sylvia, Commissioner of Massachusetts Department of Energy resources, John Linc Stine, Commissioner of Minnesota Pollution Control Agency, Mike Rothman, Commissioner of Minnesota Department of Commerce, Thomas S. Burack, Commissioner of New Hampshire Department of Environmental Service, Joseph Martens, Commissioner of New York State Department of Environmental Conservation, Audrey Zibelman, Chief of New York State Public Commission , Dick Pederson, Director Oregon department of Environmental Quality, Janet Coit, Director of Rhode Island Department of Environmental Management, Marion Gold, Commissioner of Rhode Island Office of Energy resources, Deborah Markowitz, Secretary of Vermont Agency of Natural Resources, James Volz, Chairman of Vermont Public Service Board, Maia Bellon, Director of Washington State Department of Ecology. Letter hereafter referred to as “State environmental agency leaders from CA, CO, DE, IL, ME, MD, MA, MN, NH , NY, OR, RI, VT, WA, Open Letter to the EPA Administrator Gina McCarthy on Emission Standards Under Clean Air Act Section 111(d), December 16, 2013.” 123 “RGGI Homepage”, Regional Greenhouse Gas Initiative, accessed March 19, 2014, at http://www.rggi.org/

. 124 “Cap and Trade Program”, California Air Resources Board, accessed March 19, 2014 http://www.arb.ca.gov/cc/capandtrade/capandtrade.htm

.101

Figure 2 : States with Active Greenhouse Gas Emission Budget Trading Programs

Policy Mechanics
Design
An emissions budget trading program establishes an aggregate limi t on pollution through an emissions cap that specifies the total allowable emissions over a specified time period for all of the emission sources subject to the program. To comply with the emission limitation, each emission source must surrender emission a llowances equal to its reported emissions at the end of each compliance period.
Allowances may be traded among both regulated and non

- regulated parties, creating a market for emission allowances. In turn, the allowance market establishes a price signal f or emissions (a market price for emitting a unit of pollution), which triggers broad economic incentives for reducing emissions across the covered sector(s) and encourages innovation in developing emission control strategies and new pollution control techn ologies.
There are several key design elements that may vary from program to program:

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

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

 Initial emissio n budget (i.e., the aggregate emission limitation for covered emission sources) and emissions reduction schedule102

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

o Multi

- year compliance periods

o Allowance banking

o Offset s (e.g., project

- based emissions reductions occurring outside the capped sector/sources)

 Additional provisions to mitigate price volatility and overall costs

o Auction reserve price

o Cost containment reserve of allowances provided for sale at set price thre sholds; o nce the allowance price hits a threshold, an extra supply of allowances are made available

.
T a b l e 1 summarizes some of the key design elements of the RGGI and California programs.

Table 1 : Comparison of RGGI and California Emissions Budget Trading Programs Element RGGI California Applicability  All fossil fuel

- fired EGUs with a capacity

of 25 MW or greater. 125  All facilities in covered sectors emitting at least 25,000 metric tons CO 2

- equivalent (CO 2 e) or greater. 126 Scope  Facilities in electric power sector. 127  Facilities in electric power and large industrial sectors (plus fuel distributors in 2015) 128
Emissions budget  Recently reduced 45 percent to 91 million

tons of CO 2 in 2014. Begi nning in 2015, the budget will decline 2.5 percent per year to 2020. 129  Set at 2 percent below expected 2012 emissions, declining by 2 percent in 2014 and 3 percent annually from 2015 to 2020. 130

Compliance period  EGUs must demonstrate compliance

every three years and hold allowances equal to 50 percent of reported CO 2 emissions at the end of the first two years of every three

- year compliance period. 131  Facilities must demonstrate compliance every three years. On an annual basis, facilities must also hold allo wances and offsets covering 30 percent of the previous year’s emissions. 132

125 RGGI, Overview of RGGI CO 2 Budget Trading Program (Regional Greenhouse Gas Initiative, 2007), accessed on March 19, 2014, http://www.rggi.org/docs/program_summary_10_07.pdf

. 126 CARB, Cap and Trade Regulatio n Instructional Guidance, Chapter 2: Is My Company Subject to the Cap

- and

Trade Regulation (California Air Resources Board, 2012), accessed on March 19, 2014, http://www.arb.ca.gov/cc/ capandtrade/guidance/chapter2.pdf

. 127 “Regulated Sources”, Regional Greenhouse Gas Initiative Inc., accessed on May 14, 2014, http://www.rggi.org/design/overview/regulated_sources

. 128 CARB, Overview of ARB Emissions Trading Program (California Air Resources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf

. 129 RGGI Inc., “ RGGI States Make Major Cuts to Greenhouse Gas Emissions from Power Plants,” Regional Greenhouse Gas Initiative Press Release (January 13, 2014), accessed on March 19, 2014, ht tp://www.rggi.org/docs/PressReleases/PR011314_AuctionNotice23.pdf

. 130 CARB, Overview of ARB Emissions Trading Program (California Air Resources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf

. 131 “Compliance” Regional Greenhouse Gas Initiative Inc., accessed on May 30, 2014 http://www.rggi.org/market/tracking/compliance

. 132 CARB, Overview of ARB Emissions Trading Program (California Air Resources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf

.103

Allowance allocation method  Each state distributes allowances from its

established budget in an amount and manner determined by its applicable statutes and regulations. Approximate ly 90 percent of CO 2 allowances are distributed through auction. 133  Allowances are both allocated and auctioned off according to provisions established by the program. More information is available from CARB (see footnote).

. 134

Cost containment provisions  A Cost Containment Reserve (CCR) of

CO 2 allowances provides a fixed additional supply of allowances that are only available if the auction price exceeds a set threshold ($4 in 2014 rising to $10 in 2017 and 2.5 percent per year thereafter). 135 An additional five million allowances became available March 2014 when market price exceeded the current price trigger of $4 per ton. 136

 Trigger price increases until 2020 when 10 million allowances become available if price per ton exceeds $10.75 137  A strategic reserve i s included, providing an Allowance Price Containment Reserve of one percent of allowances for 2013

- 2014, four percent of allowances for 2015

- 2017, and seven percent of allowances for 2018

- 2020. Shares of allowances held in the reserve will be released at three price trigger points; $40, $45, and $50 per ton and rise by 5 percent per year including inflation. 138

Banking  Allows unlimited allowance banking. 139  Allows unlimited allowance banking. 140 Offsets  EGUs subject to RGGI are allowed to use

offsets within th e RGGI region to meet 3.3 percent of their c ompliance obligation. 141

, 142  Facilities may use domestic offsets for up to 8 percent of their compliance obligation. 143 A framework has been established to include international offsets but these are currently

133 “2013 Allowance Allocation”, Regional Greenhouse Gas Initiative, Inc., accessed on March 19, 2014, http://rggi.org/design/overview/allowance

- allocation/2013

- allocation

. 134 CARB, Overview of ARB Emissions Trading Program (California Air Resourc es Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf

. 135 “The RGGI CO 2 Cap” Regional Greenhouse Gas Initiative Inc., accessed on May 30 , 2014 http://www.rggi.org/design/overview/cap

. 136 RGGI , “CO 2 Allowances Sold at $4.00 at 23 rd RGGI Auction,” Regional Greenhouse Gas Initiative Press Release (March 7, 2014), accessed on March 19, 2014, http://www.rggi.org/docs/Auctions/23/PR030714_Auction 23.pdf

. 137 RGGI, Summary of RGGI Model Rule Changes (Regional Greenhouse Gas Initiative, Inc., 2013), A ccessed on March 19, 2014, http://www.rggi.org/doc s/ProgramReview/_FinalProgramReviewMaterials/Model_Rule_Summary.pdf

. 138 “California Cap on Greenhouse Gas Emissions and Market

- Based Compliance Mechanisms to Allow for the Use of Compliance Instruments Issued by Linked Jurisdictions,” California Code of Re gulations, Title 17, §95800

- 96023, accessed on May 30, 2014, http://www.arb.ca.gov/cc/capandtrade/ctlinkqc.pdf

. 139 RGGI, Overview of RGGI CO 2 Budget Trading Program (Regional Greenhouse Gas In itiative, 2007), accessed on March 19, 2014, http://www.rggi.org/docs/program_summary_10_07.pdf

. 140 CARB Proposed Regulation to Implement the California Cap

- and

- Trade Program (California Air R esources Board, 2010), accessed on March 19, 2014, http://www.arb.ca.gov/regact/2010/capandtrade10/capisor.pdf

. 141 “CO 2 Offsets” Regional Greenhouse Gas Initiative, Inc., accessed on March 19, 2014, http://www.rggi.org/market/offsets

. 142 Eligible offsets under RGGI include: landfill methane capture and destruction, sulfur hexafluoride (SF 6 ) reduction from power transmission, U.S. forest projects (reforestation, improved forest management, and avoided conversion) or afforestation (in CT and NY only), end use energy efficiency, and agricultural manure management. “Offset Categories” R G G I , I n c egional Greenhouse Gas Initiative, Inc ., A ccessed on May 30, 2014. http://www.rggi.org/market/offsets/categories

. 143 CARB, Overview of ARB Emissions Trading Program (California Air Resources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf

.104 not all owed in the program. 144

Authority
State and regional GHG emission budget trading programs are authorized through individual state legislation and implemented through state regulations. For example, California implemented its emission budget trading progr am under the authority of its 2006 Global Warming Solutions Act, which requires the state to reduce its 2020 GHG emissions to 1990 levels. 145 Each RGGI state has separate authorizing legislation, and in some cases their legislation specifically directs the use of auction proceeds. For example, Maine authorized its participation in RGGI through Statute 580

- A, Title 38 Chapter 3B: Regional Greenhouse Gas Initiative. This statute also requires that 100 percent of auction proceeds go towards carbon reduction and energy conservation efforts. 146 RGGI is implemented through individual state CO 2 budget trading program regulations. 147
The state regulatory authority issues individual authorizations to emit a specific quantity of emissions (“allowances”), which represent o ne (metric or short) ton of a pollutant, in an amount no greater than the established emission budget.
Obligated Parties
Obligated parties in emission budget trading programs are generally the covered emission sources. It is the emission sources that are responsible for surrendering emission allowances equal to their reported emissions at the end of each compliance period. For example, as stated above, RGGI covers fossil fuel

- fired EGUs 25 megawatts or larger in size. 148 The California emission budget tradi ng program covers electricity generators, importers of electricity and industrial facilities with annual emissions that exceed 25,000 metric tons CO 2

- equivalent. Starting in 2015, the California program will also cover distributors of transportation, natur al gas, and other fuels with emissions greater than 25,000 metric tons CO 2

- equivalent. 149

Offsets are initially limited to forestry, urban forestry, livestock methane capture and destruction, and destruction of ozone depleting substan ces. However, rice cultivation and coal mine methane are proposed for inclusion in the program. See: CARB

– Potential New Compliance Offset Projects: http://www.arb.ca.gov/cc/capandtrade /offsets/offsets.htm for more information. 144 Ibid. 145 Assembly Bill 32, California Global Warming Solutions Act of 2006, Division 25.5 (September 27, 2006), accessed March 19, 2014, http://www.leginfo.ca.gov/pub/05

- 06/bill/asm/ab_0001

- 0050/ab_32_bill_20060927_chaptered.pdf

. 146 Maine revised statutes, Title 38, Chapter 3

- B, section 580

- B, the Regional Greenhouse Gas Initiative Act of 2007, accessed on M arch 19, 2014, http://www.mainelegislature.org/legis/statutes/38/title38sec580

- B.html

. 147 RGGI, “State Statutes and Regulations,” http://www.rggi.org/design/regulations. 148 “Regulated Sources”, Regional Greenhouse Gas Initiative Inc., accessed on May 14, 2014, http://www.rggi.org/design/overview/regulated_sources

. 149 CARB, Overview of ARB Emissions Trading Pro gram (California Air Resources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf

.105

Measurement and Verification
Emission budget trading programs include requirements for emission monitoring and reporting by affected emission sources, holding and tra nsfer of allowances, and surrender of allowances (and offset allowances or credits) in an amount equal to reported emissions. Allowance surrender in an amount equal to reported emissions is often referred to, generally, as the program “compliance obligati on”.
For example, EGUs subject to the RGGI program must report CO 2 emissions quarterly pursuant to state regulations, which are generally consistent with EPA regulations for reporting of CO 2 emissions from EGUs under 40 CFR 75. 150 Emissions are reported qu arterly to EPA, using the Emissions Collection and Monitoring Plan System (ECMPS), and data is transferred to the RGGI CO 2 Allowance Tracking System (RGGI COATS). GHG emissions reporting for affected sources under the California program is addressed throug h the California mandatory GHG reporting regulations, using a modified version of the reporting platform administered through the EPA Greenhouse Gas Reporting Program. 151 Affected emission sources must report emissions annually and provide third party verifi cation of reported emissions.
Penalties for Non

- compliance
Failure to submit allowances in an amount equal to reported emissions result in automatic emission penalties in the form of additional allowance submission requirements (e.g., three

- to

one submis sion requirements to account for any shortfall in RGGI, and a four

- to

- one submission requirement for any shortfall under the California program). States may also apply other administrative fines and penalties, pursuant to their implementing regulations.

I mplementation Status
The RGGI program was established in 2009. From 2009 through 2012, the nine current RGGI participating states invested auction proceeds of more than $700 million in programs that lower costs for energy consumers and reduce CO 2 emission s, including approximately $460 million in energy efficiency programs. 152 The participating RGGI states estimate that those investments are providing benefits of more than $1.8 billion in lifetime energy savings to energy consumers in the region. 153

150 RGGI, Overview of RGGI CO 2 Budget Trading Program (Regional Greenhouse Gas Initiative, 2007), accessed on March 19, 2014, http://www.rggi.org/docs/program_summary_10_07.pdf

. 151 CARB, Overview of ARB Emissions Trading Program (California Air R esources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf

. 152 RGGI Inc., Regional Investment of RGGI CO 2 Allowance Proceeds, 2012 (Reg ional Greenhouse Gas Initiative Inc., 2014), accessed on March 19, 2014, http://www.rggi.org/docs/Documents/2012

- Investment

- Report.pdf
, Programs include residential, commercial, a nd industrial programs. Of the $707 million in auction proceeds invested by RGGI participating states through 2012, 65 percent supported end

- use energy efficiency programs. 153 Ibid.106

Figure 3 : Historical GDP and Greenhouse Gas Emissions in the RGGI Region

Between 2005, when agreement to implement RGGI was first announced, and 2012, power sector CO 2 emissions in the RGGI participating states fell by more than 40 per cent while GDP in the region grew (see F i g u r e 3 ). 154 The RGGI program, which began in 2009, was not a primary driver for these emission reductions in RGGI states, but the lower emissions led participating states to a djust the multi

- state CO 2 emission limit. 155 In January 2014, the RGGI participating states lowered the overall allowable CO 2 emission level in 2014 by 45 percent,

154 Regional Greenhouse Gas Initiative, Open Letter to Gina McCarthy on Emiss ion Standards under Clean Air Act Section 111(d), December 2, 2013, accessed on March 19, 2014, http://www.rggi.org/docs/RGGI_States_111d_Letter_Comments.pdf

. By contrast, total U. S. power sector CO 2 emissions fell by 16 percent during the same period of time. See 2014 U.S. Greenhouse Gas Inventory for more detail: U.S. EPA, Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990

- 2012 (U.S. Environmental Protection Agency, 2014), accessed May 14, 2014, http://www.epa.gov/climatechange/ghgemissions/usinventoryreport.html

. 155 Environment Northeast, RGGI Emissions Trends (Environment Northeast, 2011), a ccessed on March 19, 2014, http://www.env

- ne.org/public/resources/pdf/ENE_RGGI_Emissions_Report_110502_FINAL.pdf

. The first three

- year control period under RGGI, establishing CO 2 emission limits for EGUs, began on January 1, 2009. Low gas prices, increased renewables, decreased electric demand and weather are considered four primary drivers of the reductions through 2010, as reported by Environment Northeast in May 2011.107

setting a multi

- state CO 2 emission limit for affected EGUs of 91 million short tons of CO 2 i n 2014 and 78 million short tons of CO 2 in 2020, more than 50 percent below 2008 levels. 156

The California economy

- wide market

- based GHG emission budget trading program, which addresses GHG emissions from multiple sectors, was implemented in 2012 with emis sion limits beginning in 2013. 157
, 158 While California’s emission budget trading program, like its state emission limit, is multi

- sector in scope, the state projects that the emission trading program and related complementary measures will reduce power sector GHG emissions to less than 80 million metric tons of CO 2 - equivalent by 2025, a 25 percent reduction from 2005 power sector emission levels. 159 Prior to the implementation of the emission trading program, California reports that it reduced power sector CO 2 emissions by 16 percent from 2005 to a 2010

- 2012 averaging period, a reduction of 16 million metric tons of CO 2

- equivalent. 160

ii. CO 2 Emission Performance Standards
Description

CO 2 emission performance standards can apply either directly to EGUs or to the local distribution company (LDC) that sells electricity to the customers. (For more information about electricity is generated and distributed, see Chapter 2 of the Regulatory Impact Analysis).
As of March 2014, four states

- California, New York, Oregon and Washington

- have enacted mandatory GHG emission standards that impose enforceable emission limits on new and/or expanded electric generating units. 161 Three states

- California, Oregon and Washington

- have enacted mandatory GHG emission performance st andards that set an emission rate for

156 RGGI Inc., “RGGI States Make Major Cuts to Greenhouse Gas Emissions from Power Plants,” Regional Greenhouse Gas Initiative Press Release (January 13, 2014), accessed on March 19, 2014, http://www.rggi.org/docs/PressReleases/PR011314_AuctionNotice23.pdf

. 157 “Cap

- and

- Trade Program,” California Air Resources Board, accessed March 19, 2014, http://www .arb.ca.gov/cc/capandtrade/capandtrade.htm

. 158 The California program was developed in coordination with U.S. state and Canadian province WCI partners. 159 State environmental agency leaders from CA, CO, DE, IL, ME, MD, MA, MN, NH, NY, OR, RI, VT, WA, Open L etter to the EPA Administrator Gina McCarthy on Emission Standards under Clean Air Act Section 111(d), December 16, 2013, accessed on March 19, 2014, http://www.georgetownclimate.org/sites/default/files/EPA_Submission_from_States

- FinalCompl.pdf

. Preliminary California Air Resources Board analyses, based in part on CARB 2008 to 2012 Emissions for Mandatory GHG reporting Summary (2013), cited in this l etter. 160 Ibid. 161 California Energy Commission, California SB 1368, Chapter 598: Emission Performance Standards, September 29, 2006, accessed March 19, 2014, http://www.energy.ca.gov/emission_standard s/

. New York Department of Environmental Conservation, Part 251: CO2 Performance Standards for Major Electric Generating Facilities, June 12, 2012, accessed March 19, 2014, http://www.dec.ny.gov /regs/83094.html#83097 .; Oregon Department of Energy, Oregon’s Carbon Dioxide Emission Standards for New Energy Facilities (Oregon Department of Energy, 2010) http://www.oregon. gov/energy/Siting/docs/Reports/CO2Standard.pdf ; Washington State Legislature, Chapter 80.70 RCW: Carbon Dioxide Mitigation, Accessed on March 19, 2014, http://apps.leg.wa.gov/rcw/de fault.aspx?cite=80.70&full=true108

electricity purchased by electric utilities. 162 In addition to these states, Illinois and Montana have policies to incentivize or require new coal plants to capture at least 50 percent of their CO 2 emissions (see F i g u r e 4 )

. 163
Figure 4 : States with Greenhouse Gas Performance Standards

Policy Mechanics
Design
States have implemented three different types of CO 2 performance standards that affect EGUs and/or LDCs differently. The first requires power plant emissions per electricity generated to be less than or equivalent to an established standard and is directly applicable to EGUs. The second type places conditions on the emissions attributes of elec tricity procured by electric utilities. It consists of standards that are applicable to LDCs that provide electricity to retail customers. A third type requires that new coal

- fired power plants must capture and store a specific percentage of CO 2 emissions . Table 2 provides state examples for each of the types of CO 2 performance standards.

162 Ibid. 163 Illinois General Assembly, Public Act 095

- 1027, SB1987, Clean Coal Portfolio Standard Law, January 12, 2009, accessed March 19, 2014 http:/ /ilga.gov/legislation/publicacts/95/PDF/095

- 1027.pdf ; Montana State Legislature, H.B.0025.05, An Act Generally Revising the Electric Utility Industry and Customer Choice Laws, May 14, 2007, accessed March 19, 2014, http://leg.mt.gov/bills/2007/billpdf/HB0025.pdf

.109

Authority
In some states, programs are regulated through the Public Utilities Commission (California, Oregon). New York’s program is regulated through the Department of Environmental Conservation. Washington’s program is regulated through two different sets of entities depending on the ownership of the utilities. The Washington Utilities and Transportation Commission regulate investor owned utilities, and the utility' s governing board, Washington Department of Ecology, and the State Auditor oversees consumer owned utilities.
Obligated Parties
The emission performance standard can apply either directly to EGUs or to the local distribution company (LDC) that sells elec tricity to the customer.
Measurement and Verification
Obligated parties must measure and report on electricity generation and CO 2 emissions on a regular basis to verify their compliance with the standard. The reporting requirements and timing varies from state to state and are typically set by the agency that oversees the program as described under authority above.

Table 2 provides an overview of different CO 2 performance standards, while Table 3 provides exampl es regarding measurement and verification requirements across California, New York, Oregon, and Washington

.
Table 2 : Examples of State CO 2 Performance Standards

164 New York Department of Environmental Conservation, Part 251: CO2 Performance Standards for Major Electric Generating Facilities, June 12, 2012, accessed March 19, 2014, http://www.dec.ny.gov/regs/83094.html#83097

. 165 Oregon Department of Energy, Oregon’s Carbon Dioxide Emission Standards for New Energy Facilities (Oregon Department of Energy, 2010) http://www.oregon.gov/energy/Siting/docs/Reports/CO2Standard.pdf

. What It Does State Examples Requires power plant emissions per electr icity generated to be less than or equivalent to the established standard; Applies to EGUs  New York (Part 251, 2012)

- New or expanded baseload plants (25 MW and larger) must meet an emission rate of either 925 lb CO 2 /MWh (output based) or 120 lbs CO 2 /MMBT U (input based). Non

- baseload plants (25 MW and larger) must meet an emission rate of either 1450 lbs CO 2 /MWh (output based) or 160 lbs CO 2 /MMBTU (input based). 164

 Oregon (HB 3283; 1997, 2007)

- New natural gas

- fired power plants (baseload and

non

- baseload ) must meet an emission rate of 675 lb CO 2 /MWh. Cogeneration and offsets may be used to comply with the emission standard. 165

 Washington (RCW 80

- 70

- 010; 2004)

- New EGUs 25 MW and larger must have an110 166 Washington State Legislature, Chapter 80.70 RCW: Carbon Dioxide Mitigation, Accessed on March 19, 2014, http://apps.leg.wa.gov/rcw/default.aspx?cite=80.70&full=true

. 167 California Energy Commission, California SB 1368, Chapter 598: Emission Performance Standards, September 29, 2006, accessed March 19, 2014, http://www.energy.ca.gov/emission_standards/

. 168 U.S. EPA, eGRID 2010 data files (U.S. Environmental Protection Agency, 2014), accessed on March 19, 2014, http://www.epa.gov/cleanenergy/energy

- resources/egrid/index.html#

. 169 Oregon Department of Energy, Oregon’s Carbon Dioxide Emission Standards for New Energy Facilities (Oregon Department of Energy, 2010) http://www.oregon.gov/energy/Siting/docs/Reports/CO2Standard.pdf

. 170 Washington State Legislature, Chapter 80.70 RCW: Carbon Dioxide Mitigation, Accessed on March 19, 2014, http://apps.leg.wa.gov/rcw/default.aspx?cite=80.70&full=true

. 171 Illinois General Assembly, Public Act 095

- 1027, SB1987, Clean Coal Portfolio Standard Law, January 12, 2009, accessed March 19, 2014 http://ilga.gov/legislation/publicacts/95/PDF/095

- 1027.pdf

. 172 Montana State Legislature, H.B.0025.05, An Act Generally Revising the Electric Utility Industry and Customer Choice Laws, May 14, 200 7, accessed March 19, 2014, http://leg.mt.gov/bills/2007/billpdf/HB0025.pdf

. 173 Regulatory Assistance Project, Emissions Performance Standards in Selected States (Regulatory Assistance Project, 2 010), accessed on May 30, 2014, http://www.raponline.org/search/related/relation/project

- document/id/10 approved CO 2 mitigation plan that results in mitigation o f 20 percent of the total CO 2 emissions over the life of the facility. Includes modifications to existing EGUs that result in an increase in CO 2 emissions of 15 percent or more. The CO 2 mitigation plan may include one or more of a list of eligible measur es (includes indirect measures, such as EE/RE and offsets). 166
Places conditions on the emissions attributes of electricity procured by electric utilities; Applies to LDCs  California (SB 1368; 2006)

- Electric utilities may only enter into long

- term power purchase agreements for baseload power if the electric generator supplying the power has a CO 2 emission rate that does not exceed that of a natural gas combined cycle plant. The California Energy Commission promulgated regulations establishing an emission rate of 1,100 lb CO 2 /MWh. 167 By comparison, the average emissions rate of gas plants in the U.S. is 945 lb CO 2 /MWh, while the average emissions rate of pulverized coal plants is 2,154 lb CO 2 /MWh. 168

 Oregon (HB 101; 2009) and Washington (SB 6001; 2007)

- Elect ric utilities may only enter into long

- term power purchase agreements for baseload power if the electric generator supplying the power has a CO 2 emission rate of 1,100 lb CO 2 /MWh or less. 169 170 Requires that new coal

- fired power plants must capture and store a specific percentage of CO 2 emissions  Illinois (SB 1987; 2009) Illinois utilities and retailers must purchase at least 5 percent of their electricity from Clean Coal Facilities in 2015 and beyond. To be designated a Clean Coal Facility, new coal

- fired pow er plants must capture and store 50 percent of carbon emissions from 2009

- 2015, 70 percent for 2016

- 2017, and 90 percent after 2017. 171

 Montana (HB 25; 2007). The Public Service Commission may not approve new plants constructed after January 2007 that are pr imarily coal

- fired unless at least 50 percent of the plant’s CO 2 emissions are captured and stored. 172 These requirements apply to formerly restructured utilities in the state. Northwest Energy is the only utility subject to this requirement, which serves a bout two

- thirds of Montana. 173111

Table 3 : Examples of Measurement and Verification Requirements for CO 2 Performance Standards State Measurement and Verification Details California  The California PUC is responsible for approving any long term financial commitment by an electric utility and must adopt rules to enforce these requirements as well as verification procedures. 174 New York  CO 2 emission regulations require recordkeeping, monitoring and reporting consistent with existing st ate and federal regulations.

 Each applicable emissions source must install Continuous Emissions Monitoring Systems (CEMS) subject to Federal CO 2 reporting requirements for 40 CFR part 75, successfully complete certification tests, and record, report, and quality assure the data from the CEMS.

 The owner or operator must report the CO 2 mass emissions data and heat input data on a semi

- annual basis to the Department of Environmental Conservation.

 On a quarterly basis, the owner or operator must report all o f the data and information required in either 40 CFR part 60 or subpart H of 40 CFR part 75. 175 Washington  Mitigation projects must be approved by the appropriate council, department, or authority, and made a condition of the proposed and final site certifi cation agreement or order of approval.

 Direct investment projects are approved if they provide reasonable certainty that the performance requirements of the projects will be achieved and that they were implemented after July 1, 2004.

 For facilities under the jurisdiction of a council, the implementation of a carbon dioxide mitigation project, other than purchase of carbon credits, is monitored by an independent entity for conformance with the performance requirements of the carbon dioxide mitigation plan. The independent entity shares the project monitoring results with the council.

 For facilities under jurisdiction of the department or authority, the implementation of a carbon dioxide mitigation project, other than a purchase of carbon credits, is monit ored by the department or authority issuing the order of approval. 176 Oregon  It is up to the Council during the certificate application phase to determine the gross CO 2 emissions over a 30 year lifetime of the proposed facility to determine whether it meets the CO 2 performance standard.

 During the operation phase of approved facilities, there are CO 2 reporting requirements to the Oregon Department of Environmental Quality and US EPA.

 New facilities must pass a 100 hour test in their first year of operation to show they meet the performance standards. 177

174 “SB 1368 Emission Performance Standards,” California Energy Comm ission, Accessed March 19, 2014, http://www.energy.ca.gov/emission_standards/

. 175 New York Department of Environmental Conservation, Part 251: CO 2 Performance Standards for Major Electric Generating Facilities, June 12, 2012, Accessed March 19, 2014, http://www.dec.ny.gov/regs/83094.html#83097

. 176 Washington State Legislature, Chapter 80.70 RCW: Carbon Dioxide Mitigation, Accessed on March 19, 2014, http://apps.leg.wa.gov/rcw/default.aspx?cite=80.70&full=true 177 Oregon Department of Energy, Oregon’s Carbon Dioxide Emission Standards for New Energy Facilities (Oregon D epartment of Energy, 2010) Accessed on March 19, 2014 http://www.oregon.gov/energy/Siting/docs/Reports/CO2Standard.pdf

.112

Penalties for Noncompliance
For policies that affect target new electric generating units, utilities must prove any proposed units are in compliance at the time of permitting. In Oregon, if facilities do not meet the performance standard in their first year of operation during a 100 hour test 178 , they must purchase offsets to account for any excess emissions. 179
Implementation Status
Since enacting the performance standard, California’s carbon emissions rat es have fallen from approximately 1,245 lbs CO 2 e/MWh for fossil generation (considering both in

- state and imported power) and 875 lbs CO 2 e/MWh for all power in 2005 to an average of approximately 1,090 lbs CO 2 e/MWh and 775 lbs CO 2 e/MWh in the three years b efore 2012. 180

b. Energy Efficiency Policies, Programs and Measures

Demand

- side energy efficiency policies and programs reduce utilization of EGUs and avoid greenhouse gas emissions associated with electricity generation . These electricity demand reductions can be achieved through enabling policies that incentivize investment in demand

- side energy efficiency improvements by overcoming market barriers that otherwise prevent these investments, such as lack of information on energy efficient options, high trans action costs, split

incentives, lack of product availability, and perceptions of organizational risks. Reducing electricity demand also reduces the associated transmission and distribution losses that occur across the grid between the sites of electricity generation and the end use.

Demand

- side energy efficiency is considered a central part of climate change mitigation in states that currently have mandatory GHG targets, accounting for roughly 35 percent to 70 percent of expected reductions of state's pow er sector emissions. 181 For example, California expects to achieve reductions of 21.9 MMTCO 2 e in 2020 from energy efficiency programs targeting electricity reductions. Taking into account expected reductions of 21.3 MMTCO 2 e expected from California's RPS and 2.1 MMTCO 2 e from the million solar roofs program, energy efficiency makes up 48 percent of power sector reductions based on California's Climate Change Scoping Plan. 182 Another state, Washington, expects to reduce 9.7 MMTCO 2 e from energy efficiency measures in 2020. Taking into account expected reductions of 4.1 MMTCO 2 e from

178 During the first year of operation new power plants tes t their equipment to ensure compliance with standards for commercial equipment. Initial CO 2 performance requirements can be validated during this test. 179 Oregon Department of Energy, Oregon’s Carbon Dioxide Emission Standards for New Energy Facilities
, Acc essed on March 19, 2014, http://www.oregon.gov/energy/Siting/docs/Reports/CO2Standard.pdf

. 180 State environmental agency leaders from CA, CO, DE, IL, ME, MD, MA, MN, NH, NY, OR, RI, VT, WA, Open Letter to EPA Administrator Gina McCarthy on Emission Standards Under Clean Air Act Section 111(d), December 16, 2013, accessed on March 19, 2014, http://www.georgetownclimate.org/sites/default/files/EPA_Submission_from_States

- FinalCompl.pdf

. 181 These reduction target ranges are based on a review of state GHG reduction laws in California, Connecticut, Hawaii, Maine, Maryland, Massach usetts, Minnesota, New Jersey, Oregon, and Washington. 182 California Air Resources Board, Climate Change Scoping Plan, accessed March 19, 2014, http://www.arb.ca .gov/cc/scopingplan/document/adopted_scoping_plan.pdf

.113

Washington's RPS, energy efficiency makes up 70 percent of expected emission reductions from stationary energy within the state. 183
States have employed a variety of strategies to increas e investment in demand

- side energy efficiency technologies and practices, including (1) energy efficiency resource standards, (2) demand

- side energy efficiency programs, (3) building energy codes, (4) appliance standards and (5) tax credits. Each of these strategies is described below.

i. Energy Efficiency Resource Standards
Description
Energy Efficiency Resource Standards (EERS) set multiyear targets for energy savings that utilities or third

- party program administrators typically meet through customer energy efficiency programs but also through other approaches, such as peak demand reductions, building codes and combined heat and power (CHP). An EERS can apply to retail distributors of either electricity or natural gas, or both, depending on the state. To date, 23 states have mandatory EE requirements in place, two states have voluntary targets, and two more states allow EE to be used to meet part of a mandatory RPS, for a total of at least 2 7 states with some type of EE requirement or goal. 184 , 185

Poli cy Mechanics
Design
EERS design and implementation details vary by state, and may be expressed as a percentage reduction in annual retail electricity sales, as a percentage reduction in retail electricity sales growth, or as a specific electricity saving s amount over a long

- term period. A typical EERS sets multiyear targets for energy savings that drive investment in EE programs implemented by utilities or third party administrators. Over the compliance period, an EERS reduces electricity demand by a ta rget amount that utilities must meet. As a result, an EERS indirectly affects utility CO 2 emissions by reducing the use of fossil

- fuel

- fired EGUs.

183 Washington Department of Ecology, Growing Washington’s Economy in a Carbon

- Constrained World, Accessed March 19, 2014, https://fortress.wa.gov/ecy/publications/publications/0801025.pdf

. 184 "State Energy Efficiency Resource Standards (EERS)," (American Council for an Energy

- Efficient Economy, April 2014), Accessed on May 23, 2014, http://www.aceee.org/files/pdf/policy

- brief/eers

- 04

- 2014.pdf

. 185 Delaware and Florida were not included in the totals. Delaware has enacted legislation to create an EERS, but final regulations have not yet been promulgated (Database of State Incentives for Renewables & Efficiency, Accessed on May 29, 2014, http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=DE17R ). Florida has en acted an EERS, but program funding to date is considered to be “...far below what is necessary to meet targets” ("State Energy Efficiency Resource Standards (EERS)," American Council for an Energy

- Efficient Economy, April 2014, Accessed on May 23, 2014, http://www.aceee.org/files/pdf/policy

- brief/eers

- 04

- 2014.pdf ).114

Authority
Most state EERS policies are established through legislation. However, there are several inst ances in which they have been established by PUC orders under broader statutory authority, such as by setting quantitative targets consistent with the achievement of ‘all cost

- effective energy efficiency. 186
Obligated Parties
Retail electricity suppliers , which are utilities that sell electricity to customers for end

- use purposes, are the obligated parties under an EERS.
Measurement and Verification
PUCs generally oversee EERS. Retail electricity suppliers comply with EERS requirements by developing a portfolio of end

- use energy efficiency programs that encourage electric utility customers to invest in more energy efficient technologies and practices as described below. Transmission and distribution infrastructure improvements may also count towards EE RS programs in some states. 187 PUCs typically rely on independent program evaluators to perform evaluation, measurement and verification (EM&V) activities that estimate the incremental annual and cumulative energy savings attributable to the programs. 188 The se estimates are typically the basis for compliance reports submitted by retail electricity suppliers. See Table 4 for examples of penalties for program noncompliance. For more information about measurement and verification of energy efficiency policies or programs, see earlier in the State Plan Considerations Technical Support Document.

186 Ernest Orlando Lawrence Berkeley National Laboratory, Benefits and Costs of Aggressive Energy Efficiency Programs and th e Impacts of Alternative Sources of Funding: Case Study of Massachusetts , accessed on May 14, 2014, http://emp.lbl.gov/sites/all/files/REPORT%20lbnl

- 3833e.pdf

. An important policy driv er for EE programs in six states is a statutory requirement for utilities to acquire "all cost

- effective energy efficiency". This policy typically requires utilities and other program administrators to pursue energy efficiency up to the point at which it is no longer cost effective, as defined by cost

- benefit tests and procedures REQUIRED by state PUCs. States with all

cost effective energy efficiency policies include: CA, CT, MA, RI, VT, WA. For MA, this goals has translated into achieving annual electr ic energy savings equivalent to a 2.4% reduction in retail sales from energy efficiency programs in 2012. 187 For example, Ohio allows transmission and distribution infrastructure improvements to count towards their EERS. Database of State Incentives for Ren ewables & Efficiency, Accessed on May 29, 2014, http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=OH16R&re=0&ee=0

. 188 Evaluation, measurement, and v erification (EM&V) refers to set of techniques and approaches used to estimate the quantity of energy savings from an EE program or policy. Since energy savings cannot be directly measured, efficiency program impacts are estimated by taking the difference between: (a) actual energy consumption after efficiency measures are installed, and (b) the energy consumption that would have occurred during the same period had the efficiency measures not been installed (i.e., the baseline).115

Table 4 : Examples of Penalties for Noncompliance State Direct Financial Penalties Pennsylvania Failure to achieve the requisite reductions in el ectricity consumption and peak demand

during Phase 1 results in one

- time fines from $1 million to $20 million. Failure to file a plan with the public utilities commission is also punishable by a fine of $100,000 per day. Costs associated with any such fine s may not be passed on to ratepayers. 189 Ohio Failure to comply with energy efficiency or peak demand reduction requirements results

in the state public utilities commission assessing a forfeiture upon the utility, to be credited to the Advanced Energy Fund . The amount of the forfeiture is either: an amount, per day per under

- compliance or non

- compliance, not greater than $10,000 per violation; or an amount equal to the then existing market value of one renewable energy credit (REC) 190 per megawatt hour of und er

- compliance or noncompliance. 191 Illinois For both natural gas and electric utilities, failure to submit an energy reduction plan will

result in a fine of $100,000 per day until the plan is filed. This penalty is deposited in the Energy Efficiency Trust Fund and may not be recovered by rate payers. 192

Penalties for Noncompliance
If the obligated parties do not demonstrate compliance with the EERS, they may face financial penalties. The existence and amount of penalties varies across the states. Tabl e 4 provides examples of financial penalties in three states, Pennsylvania, Ohio and Illinois.
Implementation Status
As of April 2014
, 23 states had an active EERS in place, while at least two have EE targets or goals that are voluntary at this time (see Figure 5 ) . In addition, two states have renewable portfolio standard that allow the option for energy efficiency to meet requirements. 193

189 “Energy Efficiency and Co nservation Requirements for Utilities: Pennsylvania” Database of State Incentives for Renewables & Efficiency, accessed on March 19, 2014, http://www.dsireusa.org/ incentives/incentive.cfm?Incentive_Code=PA14R&re=0&ee=0

. 190 RECs represent the non

- energy attributes, including all the environmental attributes, of electricity generation from renewable energy sources. RECs are typically issued in single MWh increments. See the section on Renewable Portfolio Standards for more detail. 191 “Energy Efficiency and Conservation Requirements for Utilities: Ohio” Database of State Incentives for Renewables & Efficiency, accessed on March 19, 2014, http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=OH16R&re=0&ee=0

. 192 “Energy Efficiency and Conservation Requirements for Utilities: Illinois” Database of State Incentives for Rene wables & Efficiency, accessed on March 19, 2014, http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=IL19R&re=0&ee=0

. 193 See footnotes 184 and 185

.116

Figure 5 : Status of Energy Efficiency Resource Stan dards by State

Most states are meeting or on track to meet their incremental savings goals, which typically range from an annual reduction in electricity of about 0.25

- 2.5 percent. 194 In 2011, across the 50 states, incremental savings were equivalent t o 0.62 percent of retail electricity sales. 195 For those states with EERS policies in place for more than two years as of 2011, thirteen of twenty states are achieving 100 percent or more of their goals, three states are achieving over 90 percent of their go als, and only three states are realizing savings below 80 percent of their goals. 196

ii. Demand

- side Energy Efficiency Programs
Description

Demand

- side energy efficiency programs are programs designed to advance energy efficiency improvements within a stat e or utility service area. They are typically implemented to help meet state policies, standards or objectives, such as energy efficiency resource standards

194 Ibid. 195 “The 2013 State Energy Efficiency Scorecard”, American Council for an Energy

- Efficient Economy, Accessed on March 19, 2014, http://www.aceee.org/research

- report/e13k

. 196 Michael Sciortino, Seth Nowak, Patti White, Dan York, and Martin Kushler. “Energy Efficiency Resource Standards: A Progress Report on State Experience.” American Council for an Energy Ef ficient Economy (2011).117

(EERS), ‘all cost effective’ energy efficiency goals, integrated resource planning, and other dema nd

- side management program and budget processes.
Policy Mechanics
Design

Demand

- side energy efficiency programs include financial incentives to use energy efficient products, make energy efficiency upgrades to improve the performance of residential,

co mmercial, and industrial buildings, and provide technical assistance and information programs to address market and information barriers. Funding for these programs typically comes from charges added to customer utility bills and from revenues raised thro ugh emission allowance auctions, such as under RGGI. The RGGI auction proceeds go to a variety of sources with the authority to run demand

- side energy efficiency programs, including those also funded via independent trusts, DOE’s Weatherization Assistance Program (WAP), and state

- run energy efficiency grant programs for municipalities. 197
States are also funding energy efficiency programs using revenues from “forward capacity markets” operated by regional electricity operators. Forward capacity markets allow energy suppliers to bid against each other for the amount of capacity they can supply into the electricity market in a future year. Demand

- side management programs have been allowed to bid into these markets as an energy source, demonstrating that energy efficiency programs can compete with more traditional forms of electricity supply in meeting the needs of the power grid.
Authority

Demand

- side programs that are a part of EERS programs are typically established through legislation or PUC authority. Oth er demand

- side management programs can arise as a result of utility planning processes and state and local government efforts to ensure all cost

effective energy efficiency and other policy goals are met.
Obligated Parties
Energy efficiency programs can be administered by investor

- owned, municipal or cooperative utilities; third party administrators; or state and local government agencies.
Measurement and Verification
PUCs generally oversee demand

- side energy efficiency programs. Program administr ators typically rely on independent evaluators to perform evaluation, measurement and verification (EM&V) activities that estimate the incremental annual and cumulative energy savings attributable to the programs. These estimates are typically the basis f or annual

197 RGGI, “Regional Investment of RGGI CO2 Allowance Proceeds, 2012”, Regional Greenhouse Gas Initiative (February 2014), accessed on March 19, 2014, http://ww w.rggi.org/docs/Documents/2012

- Investment

- Report.pdf

.118

performance reports submitted by retail electricity suppliers or third party administrators to the PUCs. In the case of state and local government agency run programs that are not overseen by the PUC, energy savings are typically estimated to ass ure proper use of grants or other funds. For more information about the evaluation, measurement and verification of energy efficiency policies and programs, see earlier in the State Plan Considerations Technical Support Document.
Penalties for Noncomplia nce As discussed above, some states with an EERS levy direct fines for missing energy efficiency targets or failure to submit an energy efficiency plan. For some programs under PUC oversight, failure to reach certain performance levels may result in an in ability to receive an incentive payment or recover all incurred costs. Demand

- side programs funded by RGGI proceeds or grants typically do not have penalties for noncompliance. However, state agencies play a role in evaluating these programs and deciding w hether funding should continue to flow to them.
Implementation Status

Well

- established state demand

- side energy efficiency programs have demonstrated their ability to reduce electricity demand. 198 For example, data reported to the U.S. Energy Information Administration (EIA) show that in 2012 California avoided 35,482 GWh of electricity consumption through its demand

- side efficiency programs, while Illinois avoided 3,084 GWh and Maryland avoided 1,528 GWh, . 199 These reductions are equivalent to 13.7 percent , 2.1 percent, and 2.5 percent of total 2012 retail electricity sales in those states, respectively. 200 According to data and analyses from sources including Lawrence Berkeley National Lab (LBNL), the U.S. Department of Energy’s Energy Information Administr ation, and the American Council for an Energy Efficient Economy (ACEEE), as well as the EPA’s own analysis, 12 leading states have either achieved

– or have established requirements that will lead them to achieve

- annual incremental savings rates of at le ast 1.5 percent of the electricity consumption that would otherwise have occurred. 201

In 2011 , utilities in 48 states implement ed demand

- side energy efficiency programs. 202 State demand

- side energy efficiency programs are estimated to have reduced CO 2 emissio ns by 75 million metric tons in 2011, or 3.5 percent of national power sector emissions. 203 204

198 “The Future of Utility Customer

- Funded Energy Efficiency Programs in the United States”, Lawrence Berkeley National Laboratory, Accessed on March 19, 2014, http://emp.lbl.gov/publications/future

- utility

- customer

- funded

energy

- efficiency

- programs

- united

- states

- projected

- spend

. 199 “Electric Power Sales, Revenue, and Energy Efficiency Form EIA

- 861 Detailed Data Files”, Energy Information Administration, Accessed on March 19, 2014, http://www.eia.gov/electricity/data/eia861/

. 200 “Electricity: Detailed State Data”, Energ y Information Administration, Accessed on March 19, 2014, http://www.eia.gov/electricity/data/state/

. 201 See the Greenhouse Gas Abatement Measures TSD for more information. 202 “The 2013 State Energy E fficiency Scorecard”, American Council for an Energy

- Efficient Economy, Accessed on March 19, 2014, http://www.aceee.org/research

- report/e13k. 203 The Edison Foundation: Innovation, Electricity Efficiency, Summary of Customer

- Funded Electric Efficiency Savi ngs, Expenditures, and Budgets (2011

- 2012) , March 2013, Accessed on March 19, 2014,119

iii. Building Energy Codes
Description
Building energy codes establish minimum efficiency requirements for new and renovated residential and commercial buildings. Thes e measures are intended to eliminate inefficient technologies with minimal impact on up

- front project costs. This can reduce the need for energy generation capacity and new infrastructure while reducing energy bills. Energy codes lock in future energy sav ings during the building design and construction phase, rather than through a renovation.
Policy Mechanics
Design

Codes specify “thermal resistance” improvements to the building shell and windows, minimum air leakage, and minimum efficiency for heating and cooling equipment.
Mandatory building energy codes establish minimum efficiency requirements for residential and commercial construction. The International Energy Conservation Code (IECC) is the prevailing model code for the residential sector. ASH RAE 90.1

- 2010 is the model commercial code.
By locking in efficiency measures at the time of construction, codes are intended to capture energy savings that are more cost

- effective than retrofit opportunities available after a building has been construc ted. Energy code requirements are also intended to overcome market barriers to efficient construction in both the commercial and residential sectors, such as the complexity of advanced codes, lack of local

- level implementation resources, and a shortage of empirical data on the costs and benefits of codes.
Authority
Model building codes are typically developed at the national or international level, adopted at the state and/or local level, and implemented and enforced locally.
Obligated Parties

Loc al parties, such as developers and property owners requiring building permits, are the most common obligated parties.

http://www.edisonfoundation.net/iei/Documents/FINAL_IEE% 20Whitepaper_2012_US%20Energy%20Efficiency. pdf

. 204 EPA, Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990

- 2011 Executive Summary , (Environment Protection Agency, 2013), accessed on March 19, 2014. http://www.epa.gov/climatechange/Downloads/ghgemissions/US

- GHG

- Inventory

- 2013

- ES.pdf

.120

Measurement and Verification
Program implementation steps, including builder training, compliance assurance, and enforcement, are typica lly the responsibility of state and local governments. These steps, however, are often not fully or uniformly implemented for numerous reasons, including an emphasis on health and safety issues over the proper functioning of mechanical equipment, a lack of trained staff to review building plans and conduct onsite inspections, and limited funding to carry out key implementation activities. As a result, most jurisdictions do not have the capacity to analyze code compliance and to identify the measures and str ategies that should be targeted for improved implementation. For more information about measurement and verification of energy efficiency, see earlier in the State Plan Considerations Technical Support Document.
Penalties for Noncompliance
In order to ge t building permits approved, the relevant developer or property owners must show they are in compliance with standards. Since permitting is done at the local level, the use of penalties and the ability to enforce standards vary significantly by region. DOE has been working with states and localities to improve compliance practice
Implementation Status
To date, 28 states have adopted IECC 2009 while four states have gone further by adopting the IECC 2012. In the commercial sector, 33 states have adopted AS HRAE 90.1

- 2007 and five states have adopted ASHRAE 90.1

- 2010. Currently, 11 states have outdated or no state

wide residential energy code, and 9 states have outdated or no state

- wide energy codes for commercial construction. 205 The current status of state re sidential and commercial energy codes are shown below in F i g u r e 6 a n d F i g u r e 7 , r e s p e c t i v e l y

. The State of Oregon, which has adopted residential and commercial codes based on the IECC 2009, estimated total savings in 2009 from building energy codes of 1.17 GWh and 2.3 GWh in the residential and commercial sectors, respectively. 206 This was equivalent to more than 7 percent of total retail electricity sales in Oregon in 2009. 207

205 “Code Status”, Online Code Environment & Advocacy Network, Accessed on March 19, 2014, http://energycodesocean.org/code

- status

. 206 Oregon Department of Energy, 2011

- 2013 State of Oregon Energy Plan , Accessed on March 19, 2014, http://www.oregon.gov/energy/docs/reports/legislature/2011/energy_plan_2011

- 13.pdf

. 207 “State Electricity Profiles: Oregon Electricity Profile 2012”, Energy Information Administration, Accessed on March 19, 2014, http://www.eia.gov/electricity/state/oregon/

.121

Figure 6 : Residential State Energy Code Status

Figure 7 : Commercial State Energy Code Status122

iv. Appliance and Equipment Efficiency Standards
Description
State appliance standards establish minimum e nergy

- efficiency levels for those appliances and other energy

- consuming products that are not already covered by the federal government. These standards typically prohibit the sale of less efficient models within a state. States are finding that appliance standards offer a cost

- effective strategy for improving energy efficiency and lowering energy costs for businesses and consumers, though these standards are superseded when Federal standards are enacted for new product categories,.
While state appliance s tandards can be useful in testing and exploring the effectiveness of standards for new products, states cannot preempt or supersede existing Federal standards. States may apply to DOE for a waiver to implement more stringent standards. This is sometimes g ranted if a certain period of time has passed since the federal standard has been updated.
Policy Mechanics
Design
When states implement appliance and equipment standards, they are establishing a minimum efficiency for products, such as refrigerators or air conditioners, thereby reducing the energy associated with using the product. Standards prohibit the production and sale of products less efficient than the minimum requirements, encouraging manufacturers to focus on how to incorporate energy

- efficient technologies into their products at the least cost and hastening the development of innovations that bring improved performance.
Authority
State energy offices, which typically administer the federal state energy program funds, have generally acted as t he administrative lead for standards implementation. In contrast, inspection and enforcement of appliance standards regulations has typically involved self

policing. Industry competition is such that competitive manufacturers usually report violations.

Ob ligated Parties
Manufacturers of products being sold in a given state are typically obligated to ensure their appliances meet the appropriate energy efficiency standards.
Measurement and Verification
Evaluating the benefits and costs of the standards is important during the standards

setting process. Once enacted, however, little field evaluation is performed. For more information about measurement and verification of energy efficiency, see earlier in the State Plan Considerations Technical Support Docum ent.123

Penalties for Noncompliance
Appliances and equipment found in violation of the minimum energy performance standards are not allowed to be sold or manufactured in the state.
Implementation Status
Currently, fifteen states and the District of Columb ia have enacted appliance efficiency standards. However, most of these standards have been superseded by federal standards. Still, nine states (AZ, CA, CT, MD, NV, NY, OR, RI, WA) and the District of Columbia have either enacted standards for equipment not covered federally or obtained waivers to enact tougher appliance standards where the federal regulations have become outdated. California currently leads all states in active state standards, covering 13 products, including consumer audio and video produc ts, pool pumps and hot tubs, vending machines, televisions, battery chargers, and various lighting applications. 208

v. Incentives and Finance Mechanisms for Energy Efficiency
Description
States offer a diverse portfolio of financing and incentive approaches that are designed to address specific financing challenges and barriers and incentivize specific markets and customer groups to invest in energy efficiency. These programs include revolving loan funds, energy performance contracting, tax incentives, rebat es, grants, and other incentives.
Policy Mechanics
Design
Revolving loan funds provide low

- interest loans for energy efficiency improvements. The funds are designed to be self

- supporting. States create a pool of capital that “revolves” over a multi

- year period, as payments from borrowers are returned to the capital pool and are subsequently lent to other borrowers. Revolving loan funds can be created from several sources, including public benefits funds (PBFs), 209 utility program funds, general state r evenues, or federal funding sources. Revolving funds can grow in size over time, depending on repayment interest rates and program administrative costs.

208 “Appliance Efficiency Regulations: California”, Database of State Incentives for Renewables & Efficiency, Accessed on March 19, 2014, http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=CA48R&re=0&ee=0

. 209 Public benefit funds (PBFs) are dedicated funds used for supporting research and development of energy efficiency and renewable energ y projects. Funds are normally collected either through a small charge for every electric customer or through specified contributions from utilities.124

Energy performance contracting allows the public sector to contract with private energy service compa nies (ESCOs) to provide building owners with energy

- related efficiency improvements that are guaranteed to save more than they cost over the course of the contracting period. ESCOs provide energy auditing, engineering design, general contracting, and insta llation services, and help arrange project financing. 210 The contracts are privately funded and do not involve state funding or financial incentives.
State tax incentives for energy efficiency are available as personal or corporate income tax credits, tax e xemptions (e.g., sales tax exemptions on energy

- efficient appliances), and tax deductions (e.g., for construction programs). Tax incentives aim to spur private sector innovation to develop more energy efficient technologies and practices and increase consu mer choice of energy

- efficient products. 211
Rebates (also known as “buy

- downs”) are used to promote demand

- side energy efficiency reductions by providing direct incentives to customers who purchase or make upgrades to approved efficient appliances or retro fit their homes (e.g., a utility may refund part of the cost for a homeowner to improve attic insulation or purchase a high

- efficiency furnace). Funding for rebates may come from PBFs, direct grants, or utility program funds.
Grants from the federal gove rnment, state government, regional agency, or private source may be used to start or finance energy efficiency programs. A grant may be used to provide funding for a specific construction project (e.g., retrofit of a school), finance a rebate program, init iate a revolving fund, conduct a behavior change campaign (e.g., educate public about the benefits of off

- peak energy use), or any other type of program that meets the specific grant requirements.
Authority
Financial mechanisms and incentives for energy efficiency are run by utilities and state and local governments. Utilities primarily offer rebates, grants, and loans. Personal, corporate, sales, and property tax incentives are mainly offered by state and local governments. 212
Implementation Status

Fin ancial mechanisms and incentives for energy efficiency exist in all 50 states, with the most prevalent financial mechanisms and incentives for energy efficiency are rebates and loan programs. There are 43 tax incentives and over one

- thousand rebate, grant, and loan programs. 213 In the first 3 years of Alaska’s Home Energy Rebate Program, the State provided an estimated

210 EPA, Integrating State and Local Environmental and Energy Goals: Energy Performance Contracting. Fact S heet (EPA, September 2004). 211 Elizabeth Brown, Harvey Sachs, Patrick Quinlan, and Daniel Williams. “Tax Credits for Energy Efficiency and Green Buildings: Opportunities for State Action.” American Council for an Energy Efficient Economy (2002). 212 “Financi al Incentives for Energy Efficiency” Database of State Incentives for Renewables & Efficiency, accessed on March 19, 2014, http://www.dsireusa.org/summarytables/finee.cfm

. 213 Ibid.1 25

$110 million to help finance energy efficiency retrofits for 16,500 homeowners. Retrofitted housed are currently saving an estimated 1.6 trill ion BTUs of energy annually, or 5 percent of the Alaska’s total annual energy demand for residential space heating. 214

c. Renewable Energy Policies and Programs
States have adopted a range of requirements and programs to advance the deployment of renewable en ergy technologies, including renewable portfolio standards, performance

- based incentives and public benefit funds. 215 These renewable energy policies and programs reduce GHG emissions by increasing the use of renewable energy and altering the mix of energy s upply.

i. Renewable Portfolio Standards
Description
A renewable portfolio standard (RPS), also known as a renewable electricity standard (RES), is a mandatory requirement for retail electricity suppliers to supply a minimum percentage or amount of their re tail electricity load with electricity generated from eligible sources of renewable energy. 216 An RPS indirectly affects EGU CO 2 emissions by reducing the utilization of fossil

- fuel

- fired EGUs. As of June 2013, 29 states and Washington, DC have adopted a ma ndatory RPS (see Figure 8), although designs vary (e.g., applicability, targets and timetables, geographic and resource eligibility, alternative compliance payments) and an additional nine have voluntary renewable goals. 217

214 Scott Goldsmith, Sohrab Pathan, and Nathan Wiltse, Snapshot: The Home Energy Rebate Program , (Cold Climate Housing Research Center, May 2012), Accessed on March 19, 2014, http://cchrc.org/docs/snapshots/HERP_snapshot.pdf

. 215 Feed

- in tariffs, a performance

- based incentive, offer long

- term purchase agreements to renewable energy electricity generators. Public benefit funds are typically created b y levying a small fee as a part of retail electricity rates and are used to support rebate, loan, and other programs that support renewable energy deployment. For more information, see Database of State Incentives for Renewables and Efficiency , available a t http://www.dsireusa.org/

. 216 In some state Renewable Portfolio Standards (alternatively called “Alternative and Renewable Energy Portfolio Standards”), selected non

- renewable sources such as coal bed methane or gasif ication are eligible for credit. 217 Database of State Incentives for Renewables and Efficiency, March 2013, accessed on May 23, 2014, http://ww.dsireusa.org ; Alaska House Bill 306, Signed by Governor Sean Parnell June 1 6, 2010, http://www.legis.state.ak.us/basis/get_bill_text.asp?hsid=HB0306Z&session=26

.126

Figure 8 : States with Renewable Portfolio Standards

Policy Mechanics
Design
RPS requirements typically start at modest levels and ramp up over a period of several years. An RPS relies on market mechanisms to increase electricity generation from eligible

source s of renewable energy.
Retail electricity suppliers can comply with RPS requirements through several mechanisms, which vary by state, including:

 Ownership of a qualifying renewable energy facility and its electric generation output,

 Purchasing electric ity bundled with renewable energy certificates (RECs) 218 from a qualifying renewable energy facility, and

218 RECs represent the non

- energy attributes, including all the environmental attributes, of electricity generation from renewable energy sources. RECs are typically issued in single MWh increments.127

 Purchasing RECs separately from electricity generators. Unlike bundled renewable energy, which is dependent on physical delivery via the power grid, r enewable energy certificates (RECs) can be traded between any two parties, regardless of their location. However, state RPS rules typically condition the use of RECs based on either location of the associated generation facility or whether it sells power i nto the state or to the regional grid.
Authority
Most state RPS are established through legislation and administered by state PUCs.
Obligated Parties
RPS applicability varies by state. All state RPS apply to investor

- owned utilities, while some state RPS obligate municipal utilities, rural cooperatives, and/or other retail providers, often depending on a minimum number of customers served.
Measurement and Verification
Some state RPS include an alternative compliance payment (ACP) option, where a re tail electricity supplier may purchase compliance credits from the state at a known price, which acts as a de facto price cap, if it has not procured sufficient electricity from renewable energy sources or RECs to meet the RPS compliance requirement. Stat e PUCs typically require annual compliance reports from retail electricity suppliers subject to a RPS. Most states use regional tracking systems (e.g., Western Renewable Energy Generation Information System, PJM Generation Attribute Tracking System) to iss ue, track, and retire RECs for RPS compliance purposes. 219 For more information about measurement and verification of renewable energy, see earlier in the State Plan Considerations Technical Support Document.
Penalties for Noncompliance

States have develo ped a range of compliance enforcement and flexibility mechanisms. As of 2007, despite the fact that several states had not achieved the RPS targets, only Connecticut and Texas had levied fines. A $5.6 million penalty was incurred in Connecticut in 2006. In 2003 and 2005, two competitive electricity service providers in Texas were penalized a total of $4,000 and $28,000 respectively. Flexible enforcement and opportunities to “make

- up” shortfalls in subsequent years or ACPs that are recycled to support other renewable and efficiency measures have helped other states avoid penalties for noncompliance. 220

219 For a summary of REC tracking systems, see: U.S. Department of Energy Renewable Energy Certificates (RECs) National REC Tracking Sy stems. http://apps3.eere.energy.gov/greenpower/markets/certificates.shtml?page=3 220 Ryan Wiser and Galen Barbose, Renewables Portfolio Standards in the United States

– A Status Report with Data Through 2007, (Lawrence Berkeley National Laboratory, 2008)
, Accessed March 19, 2014 http://emp.lbl.gov/sites/all/files/REPORT%20lbnl

- 154e

- revised.pdf

.128

Implementation Status
States with RPS policies have demonstrated higher levels of renewable energy capacity development. From 1998

- 2012, 67 percent ( 46 GW ) of all non

- hydro renewable capacity additions occurred in states with active or impending RPS requirements, although other factors may contribute to the growth in renewable capacity. 221

ii. Performance

- Based Incentives and Finance Mechanisms for Renewable Ene rgy Description
States offer a diverse portfolio of financing, performance based incentive and state utility ratemaking approaches that are designed to address specific financial challenges and barriers and help specific markets and customer groups prod uce clean energy.
Policy Mechanics
Design
States support the advancement of clean generation technologies through performance

based incentives, including feed

- in tariffs and other payments, or tax incentives. Performance

based incentives are paid base d on the actual energy production of a system. Feed

- in tariffs establish temporarily elevated price per kWh in order to encourage renewable energy innovation using high cost technologies. Tax incentives are used to lower financial barriers to renewable

ene rgy production.
A major source of funding for renewable energy activities comes from PBFs, but states also fund these activities through alternative sources including direct grants, rebates and generation incentives provided by utilities.

State tax inc entives for renewable energy and Combined Heat and Power (CHP) take the form of personal or corporate income tax credits and tax exemptions. State tax incentives for renewable energy are a common policy tool, mainly using credits on personal or corporate i ncome tax and exemptions from sales tax, excise tax, and property tax.
Authority
Financial mechanisms and incentives for renewables are run by utilities, non

- profits, and state and local government. Personal, corporate, sales, and property tax incentive s are mainly offered by state and local government. 222

221 Ibid. 222 “Financial Incentives for Renewable Energy”, Database of State Incentives for Renewable Energy, accessed March 19, 2014, http://www.dsireusa.org/summarytables/finre.cfm

.129

Implementation Status
Financial mechanisms and incentives for renewable energy of some form exist in most states. According to the Database of State Incentives for Renewable Energy (DSIRE), there are over 200 tax incentives. In addition, nearly a hundred performance based incentives are offered from state and local governments, as well as utilities and non

- profits. 223
There are currently 18 states that have state

- wide performance

- based policies, and in several other states utilities have adopted programs based on performance

- based incentives, including feed

- in tariffs, standard offer payments, and payments in exchange for RECs. 224 In many cases, however, PBI is limited to customer

- sited projects or limite d by size eligibility.
Financial incentives, working in concert with a strong RPS and net metering policies, have contributed to the rapid growth in solar power deployment in New Jersey. The state’s RPS includes a minimum carve

- out for solar sources, and allows solar energy generators to earn Solar Renewable Energy Certificates (SRECs) that can then be sold to electricity suppliers trying to meet the minimum solar production and/or purchase requirement. As a result of these interdependent policies, solar p hotovoltaic facilities are increasing, with installations more than doubling from 2010 through 2011. 225 New Jersey ranks second only to California in terms of total installed capacity. 226

d. Utility Planning Approaches and Requirements
Description
Some publi c utility commissions require utilities to conduct portfolio management or integrated resource planning (IRP) to ensure the supply of least cost and stable electric service to customers over the long term. Portfolio management refers to energy resource pl anning that incorporates a variety of energy resources, including supply

- side (e.g., traditional and renewable energy sources) and demand

- side (e.g., energy efficiency) options. The term "portfolio management" typically describes resource planning and proc urement in states that have restructured their electric industry and may be required for default service providers (the backup electric service provider in areas open to competition). IRP is generally used by vertically integrated utilities and is a long

- range planning process to meet forecasted demand for energy within a defined geographic area through a combination of supply

- side resources and demand

side resources and considering a broad range of perspectives. The goal of an IRP is to identify

223 Ibid. 224 Ibid. 225 Solar

- New Jersey.org, “Why has New Jersey become a Leader in Solar in the U.S.?” Solar

- New Jersey.org , August 15, 2012, Accessed March 19, 2014, http://www.solar

- new

- jersey.org/2012/08/15/why

- has

- new

- jersey

become

- a

- leader

- in

- solar

- in

- the

- us/

. 226 “Open PV State Rankings”, National Renewable Energy Laboratory, Accessed March 19, 2014, https://op enpv.nrel.gov/rankings

.130

the mix o f resources that will minimize future energy system costs while ensuring safe and reliable operation of the system.
In addition to energy resource planning, two states have policies or requirements for utilities to specifically factor pollution reduction requirements into their planning. In Colorado, the Clean Air Clean Jobs Act (CACJA), signed into law on April 19, 2010, required utilities to submit a plan to the PUC showing how they would meet EPA standards for a variety of pollutants. 227 The law was pa ssed because the state was out of compliance with the national Ambient Air Quality Standard for Ozone, and the EPA threatened to propose more stringent standards for the state.
In 2001, Minnesota enacted Minnesota Statute 216B.1692, which encourages util ities to make voluntary emission reductions and provides them with a mechanism to recover the costs through customer rate increases outside of the normal rate review cycle. 228
Policy Mechanics
Design

 Portfolio Management and IRP

- Portfolio management e mphasizes diversity in fuels, technologies, and power supply contract durations. Portfolio management includes energy efficiency and renewable generation as key strategic components. Portfolio management typically involves a multi

- step process of forecasti ng, resource identification, scenario analysis, and resource procurement.
Several states and vertically integrated utilities rely on an IRP process for long

- term planning. Since these utilities own generation assets, t hey use their IRPs to evaluate a broa d range of options for meeting electricity demand over a 20

- or 30

- year time frame. The IRP considers new supply

- side options (including renewable resources) and demand

side options, and purchased power (including transmission considerations). A broad

ra nge of plans are considered, reflecting a range of objectives and capturing key uncertainties. Plans are evaluated against established criteria (e.g., costs, rate impacts, emissions, diversity, etc.) and are ranked. The IRPs detail fuel and electricity pri ce information, customer demand forecasts, existing plant performance, other plant additions in the region, and legislative decisions. The following examples show how various states have designed their programs:

o Montana is a deregulated state that has est ablished least cost planning rules and policy guidelines for default electricity suppliers. These rules and guidelines

227 RAP, Addressing the Effects of Environmental Regulations: Market Factors, Integrated Analyses, and Administrative Processes (Regulatory Assistance Project, 2013), Accessed March 19, 2014, www.raponline.org/document/download/id/6455

. 228 Minnesota PUC, Report To The Legislature On Emissions Reduction Projects Under Minnesota Statutes 216B.1692 (Minnesota Public Utilities Commission, 2008), Accessed March 19, 2014, http://www.puc.state.mn.us/portal/groups/public/documents/pdf_files/000661.pdf

.131 target long

- term electricity supply and are slightly different for vertically integrated utilities and restructured utilities. Vertically integrated utilities are required to submit electric supply resource plans every two years with the aim of providing a balanced, environmentally responsible electricity portfolio. Meanwhile, restructured utilities must file updates to their portfolio acti on plans every three years. 229 These plans must include supply

- side and demand

- side resources, and they must address the need to supply power in a way that minimizes the environmental cost by estimating the cost to the environment of alternatives. In additio n, utilities must account for the costs of complying with existing and future environmental regulations. When considering various resource options, Montana requires a competitive solicitation process, allowing resource operators and developers to submit th eir proposals to the default electricity supplier for consideration. Montana also requires the portfolio management plans to be subject to an advisory committee review and a public review. 230

o Oregon electric utilities submit IRPs every two years, covering a 20

- year timeframe. The goal of these plans is to consider the acquisition of resources at least cost while keeping the public interest in mind. Potential risk factors must be considered, including price volatility, weather, and the cost of meeting existin g and future federal environmental regulations. Quantifiable environmental externalities are included, as are less quantifiable developments such as changes in market structure and the establishment of a renewable portfolio standard. As for energy efficien cy requirements during the planning process, Oregon determines these on a utility

- by

- utility basis. 231

 Multi

- Pollutant Utility Planning

– Two states, Minnesota and Colorado, have worked collaboratively with their investor

- owned utilities to develop multi

- p ollutant emission reduction plans on a utility

- wide basis. This multi

- pollutant, collaborative approach enables utilities to determine the least cost way to meet long

- term and comprehensive energy and environmental goals.

o The Colorado CACJA requires inves tor

- owned utilities (IOUs) with coal plants to submit a multi

- pollutant plan to the PUC to meet the EPA standards for NO x , SO 2 , particulates, mercury, and CO 2 . Utilities were not required to adopt a specific plan set by the state, but had to meet with Colo rado Department of Public Health and

229 Wilson, Rachel and Bruce Biewald, Best Practices in Electric Utility Integrated Resour ce Planning (Regulatory Assistance Project, 2013), Accessed March 19, 2014, http://www.raponline.org/document/download/id/6608

. 230 U.S. EPA, Clean Energy

- Environment Guide to Action (U.S. Envi ronmental Protection Agency, 2006), Accessed March 19, 2014, http://epa.gov/statelocalclimate/resources/action

- guide.html

. 231 Ibid.132 Environment (CDPHE) and PUC approval. Xcel Energy’s plan was submitted and approved in 2010. 232

o The Minnesota Emission Reductions Rider allows utilities to submit plans for projects that reduce emissions and go beyond fe deral requirements outside of a general rate case. It allows them to recover the costs of those actions as an incentive. 233 The specific design and process of the projects vary by utility, but typically involve installing additional pollution control equip ment at coal

- fired power plants, or repowering them with natural gas.
Authority
State utility commissioners oversee utilities’ and default service providers’ procurement practices in their states. Typically, the commissions solicit comments and input as they develop portfolio management practices from a wide variety of stakeholders. The utility regulator may also play a role in reviewing and approving utilities’ planning procedures, selection criteria, and/or their competition solicitation processes.

Ob ligated Parties
Vertically integrated utilities are often obligated under integrated resource planning, while in restructured markets, the default utility service provider may be obligated to conduct portfolio management.

For multi

- pollutant planning, Co lorado IOUs, Xcel Energy and Black Hills Energy were required to file plans with the Department of Public Health and Environment and the PUC in order to be compliant with the CACJA. Plans needed to meet the National Ambient Air Quality Standards for a numb er of air pollutants.

As the Minnesota multi

- pollutant legislation is voluntary for state utilities, there is neither compliance nor reporting requirements.
Measurement and Verification
Regulatory oversight aims to ensure utilities are following through with their plans. Regulators often require utilities to submit portfolio management plans and progress reports at regular intervals. These plans and reports describe in detail the assumptions used, the opportunities assessed, and the decisions made when d eveloping resource portfolios. Regulators then carefully review these plans and either approve them or reject them and recommend

232 RAP, Addressing the Effects of Environmental Reg ulations: Market Factors, Integrated Analyses, and Administrative Processes (Regulatory Assistance Project, 2013), Accessed March 19, 2014, www.raponline.org/document/download/id/6455

. 233 Minn esota Office of Revisor of Statutes, 2013 Minnesota Statutes, §216B, 1692 Emissions Reduction Rider, 2013, Accessed March 19, 2014, https://www.revisor.mn.gov/statutes/?id=216B.1692

.133

changes needed for approval. California, for example, requires utilities to submit biennial IRPs and quarterly reports on their plans.
Penalties for Noncompliance
There are no penalties for noncompliance, however there is usually significant interaction with the regulator during the planning and implementation process as is described above.
Implementation Status
Currently mor e than half of the states have integrated resource or other long

- term planning requirements, 234 while Minnesota and Colorado have multi

- pollutant planning policies or requirements (see Figure 9 ).
In Montana, for exa mple, the 2011 Electric Supply Resource Plan for NorthWestern Energy calls for:

 Shortening the length of power supply contracts from seven years to a more competitive, staged process of between three to five years.

 Diversifying Montana’s resource mix with the recent addition of a 150 MW gas

- fired power plant.

 Improving the integration of intermittent power sources into the power supply as new wind turbines play a larger role in the state’s resource mix.

 Meet state RPS requirements.

 Acquire cost

- effective d emand side management resources, targeting 6 MW of additional energy conservation per year.

 Monitor market, regulatory, and technology changes to better manage risks and opportunities. 235

234 Wilson, Rachel and Bruce Biewald
, Best Practices in Electric Utility Integrated Resource Planning (Regulatory Assistance Project, 2013), Accessed March 19, 2014, http://www.raponline.org/document/dow nload/id/6608

. 235 NorthWestern Energy, Electric Supply Resource Plan (NorthWestern Energy, 2011), accessed March 19, 2014, https://www.northwesternenergy.com/our

- company/tariffs

- and

- rates/montana

- tariffs

- and

- rates/electric

- supply

resource

- procurement

- plan

.134

Figure 9 : States with Integrated Resource Pl anning or Similar Processes

In Oregon, PacifiCorp has filed its 2013 integrated resource plan. Key highlights from the report include:

 Demand

- side energy efficiency efforts are expected to meet 67 percent of electricity load growth from 2013 to 2022

 Market analyses for integrating wind resources into the grid, and pursuing opportunities for combined heat and power resources.

 Goals to obtain 1,425

- 1,876 GWh of energy efficiency resources by 2015 and 2,034

- 3,180 GWh by 2017.

 Permitting and development e fforts to convert a unit of the Naughton power plant from coal to gas. 236

To meet Colorado’s multi

- pollutant planning requirement, Xcel Energy submitted a plan that was approved by the Colorado PUC on December 9, 2010. Implementation of the plan will reduce NO x levels 88% and CO 2 levels 28% relative to 2008 levels by 2018. 237 Black Hills Energy has also filed its electric resource plan (ERP). This plan includes the retirement of a coal

fired power plant and two older natural gas

- fired gas units, as well as a proposal to build a 40

236 PacifiCorp, Integrated Resource Plan (PacifiCorp, 2013), Accessed March 19, 2014, http://www.pacificorp.com/content/dam/pacificorp/doc/Energy_Sources/Integrated_Resource_Plan/2013IRP/Pacifi Corp

- 2013IRP_Vol1

- Main_4

- 30

- 13.pdf

. 237 Xcel Energy, Xcel Energy

- Emissions Reduction Plan , (Xcel Energy, 2011), accessed March 19, 2014, https://www.xcelenergy.com/staticfiles/xe/Corporate/Environment/10

- 12

- 303_CACJ

- 6E_FS.pdf

.135

MW natural gas turbine. It plans to add 100 MW of capacity by 2017, Black Hills Energy will use competitive bidding to meet the remaining 60 MW. 238
In Minnesota, projects currently implemented under the multi

- pollutant legislation in clude the Minnesota Power’s Arrowhead Regional Emissions Abatement (AREA) Project, Minnesota Power’s Boswell 3 Emissions Reduction Plan, Xcel Energy’s Mercury Reduction Plan, and Xcel Energy’s Metropolitan Emissions Reduction Proposal (MERP). MERP, authori zed in 2002, has shown a 93% reduction in SO 2 , 91% reduction in NO x , 81% reduction in mercury, 55% reduction in particulates, and 21% reduction in CO 2 from 2007

- 2009. 239

238 Black Hills Energy, “Black Hills Energy Files Plan for Ongoing Reliable, Cost

- effective Energy for Years to Come in Colorado” accessed on March 19, 2014, http://www.blackhillsenergy.com/node/34671#.UzHkuIXYhIt

. 239 Xcel Energy, “Minnesota Metro Emissions Reduction Project

– Environmental Benefits,” accessed March 19, 2014, https://www.xcelenergy.com/Environment/Doing_Our_Part/Clean_Air_Projects/MN_MERP

.136 List of Acronyms

ACEEE

- American Council for an Energy Efficient E conomy ACP

- Alternative Compliance Payment BSER

– Best System of Emission Reduction CACJA

- Clean Air Clean Jobs Act CCR

– Cost Containment Reserve CHP

– Combined Heat and Power CEMS

– Continuous Emissions Monitoring System CO 2 – Carbon Dioxide CO 2 e

– Car

bon Dioxide Equivalent CDPHE

– Colorado Department of Public Health and Environment DOE

– Department of Energy DSIRE

- Database of State Incentives for Renewable Energy EERS

– Energy Efficiency Resource Standard EGU

– Electricity Generating Unit EIA

– Ener gy Information Administration EM&V

– Evaluation, Measurement, and Verification EPA

– Environmental Protection Agency ERP

– Electric Resource Plan ESCO

– Energy Service Company GDP

– Gross Domestic Product GHG

– Greenhouse Gas GW

– Gigawatt (1 GW = 1,000 MW ) GWh

– Gigawatt

- hour (1 GWh = 1,000 MWh) IECC

- International Energy Conservation Code IOU

– Investor

- Owned Utility IRP

– Integrated Resource Planning kWh

– Kilowatt

- hour LBNL

– Lawrence Berkeley National Laboratory LDC

– Local Distribution Company MERP

- Metropolitan Reduction Proposal MMBTU

– Million British Thermal Units MW

– Megawatt MWh

– Megawatt

- hour (1 MWh = 1,000 kWh) NOx

– Nitrogen Oxides PBF

– Public Benefit Funds PBI

– Performance

- based Incentives RGGI

– Regional Greenhouse Gas Initiative REC

– Renewable Energy Certificate RES

– Renewable Energy Standard RPS

– Renewable Portfolio Standard PUC

– Public Utility Commission SO 2 – Sulfur Dioxide VEIC

– Vermont Energy Investment Corporation WAP

– Weatherization Assistance ProgramTechnical Support Document (TSD) for Carbon Pollution Emission Guidelines for Ex isting Stationary Sources: Electric Utility Generating Units
Docket ID No. EPA-HQ-OAR-2013-0602



# State Plan Considerations

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

June 20142 Table of Contents

I. Introduction .................................................................................................................. ......3 II. Description of State Plan Pathways .................................................................................5 A. Direct Emission Limits .............................................................................................7 B. Portfolio Approach ....................................................................................................8 III. Enforceability Considerations under Different State Plan Scenarios .........................13 A. Parties Regulated by the Stat e other than Affected EGUs ......................................14 B. Private or Public Third-Party Entity not Regulated by the State ............................16 C. State Agency, Authority, or Entity ..........................................................................17 D. Multi-State Approaches ..........................................................................................18 IV. Incorporating End-Use Energy Efficien cy and Renewable Energy Programs and Measures under a Rate-Based Approach ......................................................................20 A. Concept of Adjusting EGU CO 2 Emission Rates based on the Effects of End-Use Energy Efficiency and Renewable Energy .............................................................20 B. Approaches for Adjusting EGU CO 2 Emission Rates ............................................21 C. Methods and Tools for Quantifying Avoided CO 2 Emissions from End-Use Energy Efficiency and Renewable Energy .........................................................................24 V. Quantification, Monitoring, and Verifica tion of End-Use Energy Efficiency and Renewable Energy Programs and Measures .................................................................34 A. Quantification, Monitoring, and Verifi cation for End-Use Energy Efficiency .....36 B. Quantification, Monitoring, and Verifi cation for Renewable Energy Measures ...60 VI. Reporting and Recordkeeping for End- Use Energy Efficiency and Renewable Energy Programs and Measures ....................................................................................75 A. Reporting for End-Use Energy Effi ciency Programs and Measures .....................76 B. Reporting for Renewable En ergy Programs and Measures ...................................78 VII. Treatment of Interstate Emission Effects ......................................................................84 A. Background ............................................................................................................85 B. Summary of Possible Approaches for Tr eatment of Interstate Emission Effects..87 VIII. Appendix ...................................................................................................................... .....973 I. Introduction
As discussed in the preamble, in section VIII.F, the EPA is proposing to give states broad discretion to develop state plan s that best suit their circum stances and policy objectives. In developing its plan, a state will need to make a number of deci sions that will require careful consideration, in order to ensure that its plan both meets a st ate’s policy objectives and is approvable by EPA. The preamble, in section VIII. F, identified several key decision points and
factors that states should consider when developing their plans. In this section of the preamble,
the EPA also raised a number of considerations for how it will apply the proposed general plan approvability criteria to differe nt types of state plan appro aches. This includes a number of
considerations related to appropriate approaches, methods, a nd materials that are submitted for state plan components in an appr ovable plan, under different types of state plans. This technical support document (TSD) explains and discusses th ese considerations in depth, and elaborates options proposed in the preamble where releva nt. Topics addressed in this TSD include:

 Description of stat e plan pathways

o Provided as context for the discussion of applied cons iderations that follows

 Enforceability considerations under different plan scenarios

o Summary of potential enforceable m echanisms under different state plan
scenarios

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

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

o Methods for estimating avoided CO 2 emissions that result from EE/RE requirements and programs, for use in projecting emission performance under a state plan and in ex post adjustment of CO 2 emission rates during plan implementation

 Quantification, monitoring, and verificati on of EE/RE requirements and programs

o Survey of quantification, monitoring, and verifica tion under existing state and utility EE/RE requirements and programs4 o Discussion of possible approaches for minimum requirements or guidance for quantification, monitoring, and verification for EE/RE requirements and programs included in state plans, building off exis ting state processes and infrastructure

o Discussion of areas where supplementa l information would be useful for estimating avoided CO 2 emissions from EE/RE requirements and programs

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

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

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

o Discussion of areas where supplementa l information would be useful for estimating avoided CO 2 emissions from EE/RE requirements and programs

 Treatment of interstate emission effects

o Further elaboration of proposed approach es and alternatives discussed in the preamble

It should be noted that the preamble discu sses, and solicits comment on, legal issues concerning whether CAA section 111( d) authorizes some of the type s of state plans described in this TSD and whether it authorizes state plans to include some of these types of measures. This TSD does not further discuss those legal issues, but solely for the purpose of describing all of the available types of state plans and measures, assu mes that all of them are authorized under CAA section 111(d).5 II. Description of State Plan Pathways
As discussed in the preamble, the EPA is proposing a state plan approach that could accommodate a diverse set of state requirement s, programs, and measures, through two basic approaches – direct emission limits and a por tfolio approach. These two basic approaches provide four distinct state plan “pathways” under CAA section 111(d). These pathways include:

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

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

 A state-driven portfolio approach

 A utility-driven portfolio approach

Under this flexible approach, a state plan could include a combin ation of measures that reduce
CO 2 emissions at affected EGUs through the appli cation of emission limits as well as measures
that involve actions within the in terconnected electricity system that reduce utilization at affected EGUs and thereby avoid EGU CO 2 emissions. Examples of thes e latter measures include, among others, end-use energy efficiency resource standa rds and renewable energy portfolio standards, as well as certain components of ut ility integrated resource plans. A state could either rely solely
on CO 2 emission limits that are enforceable against affected EGUs or, alternatively, rely on a portfolio approach, which would include those li mits as well as other enforceable measures. Table 1 provides practical examples of possibl e state plan approaches under each of these pathways, which are discusse d in more detail below.

This section elaborates the different plan a pproaches that are discussed in section VIII.B of the preamble, to provide context for the app lied considerations that are discussed throughout the remainder of the TSD. In particular, some of these considerations apply to different types of state plan approaches. For example, section III of this TSD addresses enforceable legal mechanisms that might apply under different types of state plans, such as utility- and state-driven portfolio approaches, which would apply enforceable obligations to different entities. Section IV of this TSD applies to state plans that implement rate-based CO 2 emission limits for affected EGUs that also provide for the adjustment of CO 2 emission rates based on the effect of6 enforceable end-use energy efficiency and rene wable energy requirements and programs that are incorporated in a plan. Section V of this TSD addresses quantification, monitoring, and verification of end-use energy efficiency and renewable energy programs and measures.
Considerations addressed in this section woul d apply to states implementing a rate-based emission limit approach that provides for adjustment of CO 2 emission rates based on the effect of end-use energy efficiency and renewable energy, as well as states implemen ting utility- or statedriven portfolio approaches that incorporate end-use energy efficiency and renewable energy requirements and programs. Likewi se, section VI of this TSD addresses considerations for reporting and recordkeeping for end-use energy e fficiency and renewable energy requirements and programs, which would apply fo r these types of state plans.

Table 1. Different Illustrative Plan Approaches7 A. Direct Emission Limits
The first basic state plan approach is CO 2 emission limits that apply directly to affected EGUs, and includes two pathways: 1.) rate-based CO 2 emission limits applied to affected EGUs; and 2.) mass-based CO 2 emission limits applied to affected EGUs. For both types of emission limits, end-use energy efficiency and rene wable energy measures that avoid EGU CO 2 emissions could be a major component of a state’s overal l strategy for cost-effect ively reducing EGU CO 2 emissions.

1. Rate-Based CO 2 Emission Limits Applied to Affected EGUs
Rate-based emission limits would apply a lb CO 2 /MWh emission limit to affected EGUs. Depending on a state’s approach, compliance flexibility could be provided through different mechanisms, such as averaging among affected sour ces, or the use of tradable credits for avoided
CO 2 emissions resulting from end-use energy e fficiency and renewable energy measures as discussed below. In the case of the latter appr oach, such credits could be used by an affected EGU to adjust its CO 2 emission rate when demonstrating co mpliance with a rate-based emission
limit. 1 Rate-based emission limits could be implem ented on a state-by-state basis, or through multi-state averaging or trading. Rate-based em ission limits might also be a component of a portfolio approach (described below), where the emission rate limit would not assure full achievement of the required level of emission pe rformance specified for affected EGUs in the state plan, in which case the emission limit would be supplemented with other enforceable

measures.

Rate-based emissions limits could incorpor ate end-use energy efficiency and renewable energy measures that avoid EGU CO 2 emissions, through an administrative adjustment by the state or tradable crediting system. 2 These adjustment credits could be used by an affected EGU to

1 Section IV of this TSD discusses possi ble approaches for such adjustments. 2 Under a tradable credit system, a state would issue adjustment credits based on avoided CO 2 emissions achieved through end-use energy efficiency and renewable ener gy measures. EGUs could then apply these tradable adjustment credits when demonstrating compliance with a rate-based CO 2 emission limit. These tradable credits might be issued to affected EGUs for free or through purchase. Alternatively, end- use energy efficiency and renewable energy actions undertaken by private parties (including EGU owners and operators) might be eligible for the issuance of adjustment credits. Un der an administrative adjustment appr oach, a state program administrator might administratively adjust an affected EGU’s CO 2 emission rate based on avoided CO 2 emissions achieved8 comply with the rate-based emission limit, by adjusting the unit’s reported CO 2 emission rate. 3 Under this approach, end-use energy efficiency and renewable energy m easures that avoid EGU
CO 2 emissions would be enforceable components of a state plan. These actions would need to be enforceable components of a state plan to pr ovide assurance that a sufficient amount of adjustment credits will be available to facili tate EGU compliance with the emission rate limit, and that end-use energy efficiency and renewabl e energy measures that generate adjustment credits are properly quantified, monitored, and verified. 4

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

Mass-based emission limits would a pply either an individual limit on CO 2 tons emitted
from an affected EGU or establish a finite CO 2 emissions budget for a group of affected EGUs. The latter approach is typically implem ented through a tradable allowance system.

With mass-based emission limits, end-use en ergy efficiency measures that avoid EGU
CO 2 emissions could be a major component of a state’s overall strate gy for cost-effectively reducing EGU CO 2 emissions, but would be complementary to the enforceable state plan ( i.e. , not included as enforceable measures in a state plan ). These actions could be used to help a state cost-effectively achieve the CO 2 emissions limits, or to ach ieve other policy goals, but CO 2 emissions performance would be assured throug h the enforceable limit on mass emissions from
affected EGUs.

B. Portfolio Approach
The second basic state plan approach uses a portfolio of actions, in which a state plan includes multiple programs and measures that are designed to achieve either a rate-based or mass-based emissions performance goal for aff ected EGUs. This approach includes two

through state end-use energy efficiency and renewable energy deployment programs or utility compliance with energy efficiency resource standards or renewable energy portfolio standards. These adjustments might be apportioned to affected EGUs based on a predetermined metr ic. Affected EGUs would then begin with an adjusted CO 2 emission rate when considering additional actions necessary for compliance with the rate-based CO 2 emission limit. 3 Section IV of this TSD discusses po ssible approaches for such adjustments. 4 Section V of this TSD addresses considerations for quantification, monitoring, and verification of end-use energy efficiency and renewable energy measures.9 pathways: 1.) a state-driven portfolio approach ; and 2.) a utility-driven portfolio approach. A portfolio approach would include emission limits for affected EGUs along with other enforceable end-use energy efficiency and renewabl e energy measures that avoid EGU CO 2 emissions. A portfolio approach could be state-driven or u tility-driven, depending on the utility regulatory
structure in a state.

In general, a portfolio approach is disti nguished from an emission limit approach by the
fact that achievement of the full level of required emission performance for affected EGUs specified in the plan is not ensu red through the application of dire ct emission limits that apply to
affected EGUs.

A portfolio approach would include both direct emission limits that apply to affected
EGUs and other indirect m easures that avoid EGU CO 2 emissions. Under a portfolio approach, end-use energy efficiency and renewabl e energy measures that avoid EGU CO 2 emissions would be enforceable components of a state plan. Th is would be necessary because the emission limit applied directly to affected E GUs would not assure full achieve ment of the required level of emission performance specified in the state plan. 5

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

1. State-Driven Portfolio Approach
A state-driven portfolio appro ach – rather than a utility-dri ven approach – is more likely to be adopted in a state with a restructured electricity sector. In these states, rate-regulated

5 Under a portfolio approach, either a rate-based or mass-based emission limit might be applied. Such plans might also include application of a direct em ission limit to a subset of affected EGUs. Both scenarios would necessitate inclusion of supplemental measures, such as end-use energy efficiency and renewable ener gy, or other measures that directly apply to affected EGUs (e.g., repowering or re tirement of one or more high -emitting EGUs), in order to achieve the required level of emission performance for affected EGUs specified in the state plan.10 electric utilities have typically divested electric generation assets and there is often also retail competition where non-utility entities can s upply retail customers with electricity. 6 Electric
distribution utilities in these states typically purchase electri city from competitive wholesale markets. As a result, utilities in these states typically do not engage in a utility integrated resource planning (IRP) process. IRP processes, which are a natural fit for implementing a portfolio approach, are much more common in states with regulated vertically integrated utilities that own and operate elec tric generating assets.

In restructured states, policies for increas ing end-use energy effi ciency and renewable energy are often established through regulations that apply to electr ic distribution utilities, such as end-use energy efficiency resource standard s and renewable portfolio standards. Many of
these states have also establis hed independent non-profit entities to administer end-use energy efficiency and renewable energy deployment programs funded through re gulated electricity

rates.

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

2. Utility-Driven Portfolio Approach
A state with vertically integrated, state-regulate d electric utilities is more likely to adopt a utility-driven portfolio approac h. In such states, private util ities own and operate electric generation, transmission, and distribution system s necessary to supply retail customers with electricity. 7 These utilities are overseen by state public utility commissions that approve utility capital investments and oversee utility operations , and allow utilities to recover approved

6 In some restructured states, the holding company that owns the distribution utility may also own generating assets which are operated on a competitive basis. In these instance s, there typically are legal provisions in place that mandate the independent management and operation of generation and distribution assets. 7 In some instances these regulated utilities may supplemen t electric generation with purchases through wholesale electricity markets and may also sell surplus generation in these wholesale markets on a competitive basis.11 investments and operating costs, al ong with a specified financial ra te of return, through regulated retail electricity rates. State utility commissions of ten require regulated uti lities to engage in an integrated resource planning (IRP) process, which s eeks to identify the least-cost set of resources available to provide electricity to retail cust omers over a multi-year period, and often includes
evaluation of measures such as end-use en ergy efficiency, demand-side management, and renewable energy. 8 Once an IRP is approved by a state publ ic utility commission, a utility’s cost recovery and rate of return is often linked to identified measures and metrics in the IRP. 9

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

A utility plan under this approach might re ly heavily on end-use energy efficiency and renewable energy actions, but also might focus on direct actions at affected EGUs, such as repowering to fire a lower-carbon fuel or reti rement of high-emitting units. Such plans might
also include direct emission limits on affected EGUs, or implementation of an environmental dispatch approach that incorporates CO 2 emission rate into the disp atch protocol used by the utility to schedule electric generation. 10

Under a utility-driven portfolio approach, the entire suite of obliga tions under the plan would be enforceable against the utility company, which would also be an owner and operator of
affected EGUs. If there are other affected EGUs in the state that are not owned and operated by a

8 Depending on the state, an IRP process may also asse ss factors such as fuel diversity and environmental performance, among others, when identifying th e least-cost mix of resources for a utility. 9 In some cases, an IRP prescribes or authorizes specific actions. In others, an IRP serv es as a guide for the utility and the public utility commission when evaluating acquisitio n or implementation of specific utility resources or programs. In such cases, the specific resource or program is approved thro ugh a PUC order that authorizes or requires actions and identifies performance obligations. Th ese orders may or may not be fully consistent with provisions in an IRP. 10 Vertically integrated utilities, even if they operate w ithin the footprint of a competitive wholesale electricity market, may self-schedule generation assets.12 vertically integrated utility, a state plan might need to include other measures that address CO 2 emission performance by these affected EGUs.

A similar approach could be taken by munici pally owned utilities or utility cooperatives, which often also engage in an IRP process. Ho wever, state public util ity commissions (PUCs) often do not regulate these utilities. As a result, implementatio n of a portfolio approach by these entities would introduce practical enforceab ility considerations under a state plan.13 III. Enforceability Considerations under Different State Plan Scenarios
As discussed in the preamble of the propos al, in section VIII.F.1, a state plan must
include enforceable measures. To ensure that it s plan is enforceable, a state will need to:

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

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

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

As discussed in the preamble, responsible enti ties in an approvable state plan may include an owner or operator of an affect ed EGU, other entities with res ponsibilities assigned by a state, or the state itself. Other entities might include an en tity that is regulated by the state, such as an electric distribution utility, or a private or publ ic third-party entity. St ate responsibility might include obligations that are assume d directly by a state agency, aut hority, or other state entity to carry out aspects of a state plan.

While this approach provides states with br oad discretion to devel op plans that best suit their circumstances and policy ob jectives, assigning re sponsibility to other parties regulated by the state, private or public third-party entitie s, or state entities raises enforceability
considerations. This section disc usses how the general enforceability approach discussed in the preamble, and described above, might apply in practice under different state plan approaches.

This section describes possibl e scenarios of responsible en tities and legal mechanisms and approaches that might be used to address enforceability considerations under different types of state plans. These scenarios we re developed to capture the range of entities that are currently implementing end-use energy efficiency and renewa ble energy deployment programs in states, or are subject to states requirements such as e nd-use energy efficiency resource standards (EERS) or renewable portfolio standards (RPS). For each of these examples, this section describes current legal relationships between these entiti es and the state, and discusses possible legal14 instruments that might provide the state with the authority to ensure that obligations in a state plan are met and to address failure to meet t hose obligations. The mechanisms discussed take different forms, but would specify the three el ements described above: obligations, compliance demonstration, and enforcement mechanisms. Th is section also discusses enforceability
considerations in cases where states act jointly through a multi-state plan.

A. Parties Regulated by the State other than Affected EGUs
One likely state plan scenario involves incl usion of enforceable obligations for stateregulated entities other than affected EGUs. An exam ple of a state-regulated entity that is not an owner or operator of affected EGUs may be an electric distribution utility. 11 These entities are typically regulated by a state public utility commission. An example of an enforceable state plan measure that might apply to an electric distribution utility is a compliance obligation under a state end-use energy efficiency resource standard (EERS) or renewable portfolio standard (RPS), or implementation of incentive programs for th e deployment of end-use energy efficiency and renewable energy technologies.

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

11 Electric distribution utilities are also often referred to as local distribution companies (L DCs). Here we refer to an electric distribution utility as an entity that owns and operates an electric distribution network but is not the owner and operator of EGUs. As discussed further, vertically integrated utilities own and operate electric distribution networks as well as EGUs.15 1. Electric Distribution Utility with Obligatio ns to Meet an EERS or RPS Pursuant to State Regulations

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

2. Vertically Integrated Electric Utility with Obligations under a State-Approved Integrated Resource Plan
A utility integrated resource plan (IRP) may include a number of direct and indirect
actions that affect EGU CO 2 emissions, and may also include compliance with EERS and RPS regulations. Broadly, IRPs may prescribe or auth orize actions for which utilities can recover capital investments and operating costs th rough regulated retail electricity rates. 13 This creates strong financial incentives for implementing an action, but may not mandate an action.

For a state plan under this scenario, an enfo rceability consideration is whether an IRP, and related public utility commission orders, must include additional requirements to implement certain actions, beyond denial of rate recovery or a change to utility tariffs if a utility fails to

12 We note that some direct emission limits for CO 2 emissions include somewhat similar provisions. For example, both the RGGI state CO 2 emission budget trading programs and the California GHG emission budget trading program include cost containment prov isions where more emission allowances are made available to affected sources at certain allowance price thre sholds. In both these instances, such relevant characteristics of the state regulations would need to be take n into account when projecting the CO 2 emission performance that will be achieved by affected EGUs under the state plan. 13 In some cases, an IRP prescribes or authorizes specific actions. In others, an IRP serv es as a guide for the utility and the public utility commission when evaluating acquisitio n or implementation of specific utility resources or programs. In such cases, the specific resource or program is approved thro ugh a PUC order that authorizes or requires actions and identifies performance obligations. Th ese orders may or may not be fully consistent with provisions in an IRP.16 meet specified obligations in th e IRP. If so, this may require state legislation to provide additional authority to state public utility comm issions in some states, or confer additional authority to other agencies (e.g., a state environmental agency).

B. Private or Public Third-Party Entity not Regulated by the State
Another state plan scenario involves pub lic or private third-party entities with enforceable obligations under a state plan. A private or public third-party enti ty could be a utility entity that is not regulated by a state public utility commission, su ch as a municipal utility or a utility cooperative. 14 It could also be a private non-profit en tity established to administer end-use energy efficiency and renewable energy deployment programs. 15 In most cases, since they often expend electricity ratepayer funds, such non-prof it entities are created by state legislation and overseen by state public utility commissions or state-regulated private utilities.

An appropriate legal instrument or agreemen t applicable to such entities included in a state plan might include legal arrangements si milar to those currently used to establish independent entities that expend electricity ratepa yer dollars in multiple st ates. For entities not subject to state oversight, such a m echanism might also include mechanisms where an entity voluntarily submits to the authority of a state, pu rsuant to state statutor y or regulatory authority specified in a state plan. Such agreements might be attached to a funding source. For example, the entity would voluntarily submit to such auth ority as a condition of receiving certain funds, such as state appropriated funds or funds coll ected through state-regula ted electricity rates. Alternatively, a municipal utility or utility cooperative might volunt arily submit to state authority as a condition of the state agreeing to let the entit y implement a portfolio a pproach, in lieu of the application of certain direct CO 2 emission limits for affected E GUs owned and operated by such entities through a state regulation. In some cases, new state statut ory authority might be enacted to support a state plan, specifying enforceable oblig ations for these private or public third-party entities under the plan.

14 Here, “not regulated” refers to regu lation of electricity rates by a state public utility commission. To the extent that such entities are owners and operators of affected E GUs, these EGUs may be subject to state environmental and other regulations. In some cases these utility entities are also subject to state EERS and RPS regulations, as specified under state law. 15 Examples include the Energy Trust of Oregon, the Dela ware Sustainable Energy U tility, and Efficiency Vermont.17 An additional consideration is whether such legal instruments or agreements, if related to a renewable energy or end-use en ergy efficiency deployment pr ogram, should specify a stable budget authority and funding source through each pl an performance period. Such authority and funding might be necessary to ensu re that suitable funds are made available to achieve the level of energy savings or renewable energy deploymen t projected in the state plan, which may be necessary to achieve the level of emission performance by affected EGUs that is projected will be achieved through implementation of the plan.

C. State Agency, Authority, or Entity
This state plan scenario involves a state entity with an enforceable obligation in a state plan. For example, state authorities in some states implement renewable energy and end-use energy efficiency deployment programs. 16 In this scenario, the requirement for the state entity
would be an enforceable co mponent of the state plan.

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

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

An additional consideration is whether such legal arrangements, if related to a renewable energy or end-use energy effi ciency deployment program, shoul d also specify a stable budget

16 A prominent example is the New York State Energy Research and Development Authority (NYSERDA), which administers energy efficiency and renewable energy deployment programs. 17 We note that under the CAA, measures included in an approved 111(d) stat e plan would be federally enforceable by EPA, and that citizens would also have the ability to file citizen suits to compel enforcement of state plan obligations, under CAA Section 304 (42 U.S. Code Section 7604).18 authority and funding source through the plan performance period, or other provisions, to ensure that programs are implemented as projected under the state plan.

D. Multi-State Approaches
As discussed in the preamble, in section VIII.F.1, multi-state approaches introduce crosscutting enforceability considerations.

For these multi-state approaches, states w ould demonstrate emission performance from affected EGUs in aggregate jointly with partner states. For states participating in a multi-state approach, the individual state pe rformance goals in the emission guidelines would be replaced with an equivalent multi-state performance goal. For example, states taking a rate-based approach would demonstrate that all affected E GUs subject to the multi-state plan achieve a weighted average CO 2 emission rate that is c onsistent, in aggregate, w ith an aggregation of the state-specific rate-based CO 2 emission performance goals estab lished in the emission guidelines that apply to each of the part icipating states. If states were taking a mass-based approach, participating states would demonstrate that all a ffected EGUs subject to the multi-state plan emit a total tonnage of CO 2 emissions consistent with a transl ated multi-state mass-based goal. This multi-state mass-based goal would be based on transl ation of an aggregation of the state-specific
rate-based CO 2 emission performance goals established in the emission guidelines that apply to each of the partic ipating states.

1. Multi-State Emission Budget or Ra te-Based Emission Trading Programs
The Regional Greenhouse Gas Initiative (RGGI) is an example of a multi-state approach to regulation of CO 2 emissions. Through this initiative, ni ne states are currently implementing
coordinated CO 2 emission budget trading programs. Th e program works as a coordinated regional whole through a shared emission and allowance tracking system and allowance auction process, but is implemented in accordance w ith materially consistent stand-alone state regulations and individual statutory authority. Thes e regulations recognize CO 2 allowances issued by other participating states for use by a ffected EGUs when complying with each state’s emission limitation, but contain all the necessa ry components to administer the program19 requirements on an individual state basis. 18 As a result, while the initiative is implemented regionally, each CO 2 emission budget trading program regulati on is enforceable against affected
EGUs at the state level and func tions as a discrete program.

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

2. Multi-State Portfolio Approaches
A multi-state portfolio approach could introduce novel enforceab ility considerations. If it were based on interdependent em ission reduction strategies among states that are not tied to emission limits that directly apply to affected EGUs, the emission performance of affected EGUs in one participating state may be dependent, in pa rt, on actions taken in ot her participating states. If a state (or states) failed to implement comm itments under the multi-state plan, this raises the question of whether the EPA shoul d address non-performance of one or more participating states in the context of failure to achieve the requi red level of multi-state emission performance under the plan, or instead enforce actions at the individu al state level for those st ates that are failing to meet commitments under the multi-state plan.

18 The emission limitation consists of a requirement to submit CO 2 allowances equal to reported CO 2 emissions during a compliance period. While states have individual emission budgets, representing the total number of allowances issued for a given year that are available for allocation, there are no individual state emission limits. The CO 2 emission constraint is regional, based on the sum of state CO 2 emission budgets. 19 Enforceability would be contingent , in part, on states having comparable enforcement mechanisms.20 IV. Incorporating End-Use Energy Efficiency a nd Renewable Energy Programs and Measures under a Rate-Based Approach
A. Concept of Adjusting EGU CO 2 Emission Rates based on the Effects of End-Use Energy Efficiency and Renewable Energy
As discussed in the preamble, in section VIII.F.3, the EPA is proposing that RE and demand-side EE requirements, programs, and measur es may be incorporated into a rate-based plan approach. 20 Measures that avoid CO 2 emissions from affected EGUs, such as quantified and verified end-use energy savings and renewable energy generation, co uld be used to adjust the
CO 2 emission rate of an affected EGU when de monstrating compliance with a rate-based CO 2 emission limit. Alternatively, a state could use the effect of such measures as a basis for administratively adjusting the average CO 2 emission rate of affected EGUs when demonstrating achievement of the required emission ra te performance level in a state plan.

Under this approach, affected EGUs could comply with a rate-based CO 2 emission limit through actions at the EGU, 21 as well as through the use of credits 22 for actions that occur
elsewhere in the interconnected electricity system that avoid CO 2 emissions from affected EGUs. If a state is implementing a portf olio approach, then the state c ould administratively adjust the average CO 2 emission rate of affected EGUs thr ough a similar process when demonstrating achievement of the required emission rate performance level in the state plan.

This section explores in depth the mechanic s and implications of the different possible approaches for adjusting CO 2 emission rates that are summari zed in the preamble. Aspects of this discussion may apply to both retrospective demonstration of CO 2 emission performance achieved by affected EGUs under an appr oved state plan and projections of CO 2 emission performance by affected EGUs included in a submitted state plan.

20 The EPA is also proposing that RE and demand-side EE measures could be used under a mass-based portfolio approach in an approvable state plan. Ho wever, the focus of this section is limited to application of such measures under a rate-based approach. 21 This could include an individual affected EGU or group of affected EGUs if a rate -based averaging or trading approach is used. 22 These credits could be tradable, or represent non-tradable credits administratively apportioned to affected EGUs. This latter approach effectively represents an administrative adjustment applied by the state.21 B. Approaches for Adjusting EGU CO 2 Emission Rates
As discussed in the preamble, credits or adjustment to an EGU CO 2 emission rate, based on the effect of RE and demand-side EE program s and measures, might represent avoided MWh of electric generation or avoided tons of CO 2 emissions. 23 If adjustment or credits represent avoided MWh, they would be added to the denominator of the lb CO 2 /MWh emission rate when determining an adjusted lb CO 2 /MWh emission rate. If adjustment or credits represent avoided
CO 2 emissions, they would be subtracted from th e numerator when determining an adjusted lb
CO 2 /MWh emission rate. The approach chosen coul d affect the amount of credit or adjustment provided for RE and demand-side EE programs and measures. Thes e implications are discussed
below.

1. Adjustment of CO 2 Emission Rate based on Avoided MWh
One approach is to adjust an EGU’s CO 2 emission rate based on avoided MWh of generation from an EGU, or cohort of EGUs, resulting from RE and demand-side EE programs
and measures. 24 A MWh crediting or adjustment appro ach implicitly assumes that the avoided
CO 2 emissions come directly from the particular affected EGU (or group of EGUs) to which the adjustment or credits are applie d. It assumes, in effect, that an additional emission-free MWh is being generated by that respective EGU, and th at the RE or demand-side EE measure reduces
CO 2 emissions from that indivi dual EGU or group of EGUs. 25 In practice, the average or marginal CO 2 emission rate in the power pool or iden tified region – representing the avoided
CO 2 emissions from the generating sources being displaced by a MWh of energy savings or a MWh of renewable energy generation – could diff er significantly from the calculated avoided
CO 2 emissions derived by adjusting the MWh output of an affected EGU. The following examples highlight these concepts.

23 The preamble solicits comment on the ap propriateness of these different appr oaches, which are further elaborated in this section. 24 It should be noted that this was the process used by EPA for incorporating end-use energy efficiency, renewable energy, and nuclear energy when calculating state CO 2 emission performance goals for affected EGUs. As discussed in the preamble, states may have flexibility to use a diff erent approach when demonstr ating the effect of these measures in a rate-based state plan. 25 As a result, the assumed avoided CO 2 emissions from an individual MWh of energy savings or generation from renewable energy will differ based on the reported CO 2 emission rate of the individual EGU to which the MWh is applied as an adjustment to its MWh output.22 Example 1 : Assume an EGU with a stack emission rate of 1,500 lb CO 2 /MWh generates 1,000 MWh. Also assume that 1,000 emission-free MW h credits for the effect of demand-side EE measures are added to the denominator when calculating the EGU’s adjusted CO 2 emission rate. The adjusted CO 2 emission rate is 1,500,000 lb CO 2 divided by 2,000 MWh, which equals a
CO 2 emission rate of 750 lb CO 2 /MWh. In this example, each MW h credit represents 750 lb of
avoided CO 2 emissions.

Example 2 : The same calculation applied to an affected EGU with a 2,000 lb CO 2 /MWh rate would yield a different result. In this in stance the adjusted emission rate is 2,000,000 lb CO 2 divided by 2,000 MWh, which equals a CO 2 emission rate of 1,000 lb CO 2 /MWh. In this example, each MWh credit represents 1,000 lb of avoided CO 2 emissions.

2. Adjustment of CO 2 Emission Rate based on Avoided CO 2 Emissions
An alternative approach is to provide an adjustment to the CO 2 emission rate of an EGU, or cohort of EGUs, based on the estimated CO 2 emissions that are avoided in the power pool or identified region as a result of RE and demand- side EE programs and measures. This approach acknowledges that the avoided CO 2 emissions may come from the electric power pool or other identified region as a whole, rather than an individual EGU. The avoided CO 2 emissions are determined based on the MWh saved or generated, multiplied by a CO 2 emission rate for the power pool or region.

This CO 2 emission rate could be based on the aver age or marginal emission rate in the power pool, region, or state. A marg inal avoided emission rate repr esents the generation that is displaced at the margin for every MWh saved or generated through an RE or demand-side EE program or measure. An average avoided emision ra te is based on either all fossil generation in a region or total generation. This approach assu mes that every MWh saved or generated equally displaces generation from every gene rator in a power pool or region.

Another approach that has been suggeste d by some stakeholders is crediting or adjustment based on the level of the rate-based emission limit for affected EGUs (or the overall rate-based level of emission pe rformance for affected EGUs specified in a state plan). For23 example, under this approach, if th e emission rate limit were 1,500 lb CO 2 /MWh, one MWh of energy savings or renewable energy generati on would result in a credit or adjustment representing 1,500 lb of CO 2 that could be subtracted from the numerator of an EGU’s CO 2 emission rate. This approach assumes that affected EGUs jointly emit CO 2 from the stack on an average basis at this required compliance leve l (i.e., consistent with a “closed” averaging system), and that a MWh saved or generated avoids CO 2 emissions from affected EGUs at this average compliance level. 26

3. Other Considerations

Some of the CO 2 emissions avoided through RE and demand-side EE measures may be from non-affected EGUs. This may result because affected EGUs are only a subset of the fossil fuel-fired EGU fleet, which also includes (or will include) existing non-aff ected fossil fuel-fired EGUs, such as simple-cycle combustion turbines used to meet peak demand, as well as new fossil fuel-fired EGUs subject to emission stan dards under CAA section 111(b). Furthermore, as the fleet capital stock slowly tu rns over, affected EGUs under s ection 111(d) will comprise a slowly shrinking subset of the total fossil fuel -fired EGU fleet. These dynamics may need to be addressed in a state plan wh en crediting or adjusting CO 2 emission rates of affected EGUs based
on the effects of RE and demand-side EE measures . The approaches described in more detail later in this section may be able make these di stinctions between affected and non-affected fossil
fuel-fired EGUs.

26 This outcome might be expected in a closed averaging system, without the use of crediting or adjustment for the avoided emission effects of RE and demand-side EE meas ures. In this instance an EGU that emitted above the compliance rate would need to average its performance with (or submit tradable credits obtained from) an EGU that performed below the required rate. On balance, all EGUs subject to the emission rate limit would perform at or below the compliance rate.24 C. Methods and Tools for Quantifying Avoided CO 2 Emissions from End-Use Energy Efficiency and Renewable Energy

1. Introduction
There are a number of approach es for quantifying the avoided CO 2 emissions resulting from end-use energy efficiency and renewabl e energy (EE/RE) programs, requirements and

measures 27 in the electric sector. These approaches ra nge from the application of basic avoided emission rates to using sophisti cated electric sector models. 28 Annual average avoided emission rates have often been used for rough approximations of CO 2 emissions avoided from reduced electric energy use. 29 An annual average avoided emission rate assumes that EE/RE programs and measures reduce electric generation from all generating types on a proportional basis consistent with the generation mix in a region. A marginal emission rate represents the emission rate of an electric generating unit (EGU) or c ohort of EGUs likely to be displaced by EE/RE measures (i.e., a marginal avoided emissions rate ), based on the last unit( s) to come online to meet electricity load and the firs t unit(s) to be brought offline when electricity load is reduced.

The primary question underlying estimating CO 2 emissions reductions from EE/RE measures is the determination of which electric generators will be displaced (i.e. , cease generation or reduce generation output) in the presence of incremental EE/RE. This section briefly describes a range of avoided emission rates approach es, their underlying assumptions,
and considerations associated with the use of different avoided emission rate approaches.

2. Average Emission Rate Approach
An average emission rate (typi cally expressed in tons of CO 2 /MWh) is usually understood to mean the average of all genera tors’ emissions rates, weighted by annual generation. The rate (r avg ) is calculated as:

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

.25 ݎ

௔௩௚ ൌ ∑ ݁ ௜ ௜ ∑ ݃ ௜

௜ Where:

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

. Because the average emission rate puts the sum of all generation in the denominator (as MWh), including nuclear, hydroelectric, and renewable generating resources, the rate fundamentally assumes that EE/RE reduces all generating types by an equal proportion, regardless of their type or contribution to the margin. 30 EGUs are generally dispatched on an economic merit order, where the least-cost EGUs (on a variable cost basis) are dispatched first, and higher cost resources are dispatched later. Since nuclear, hyd ro, wind, and solar resour ces operate at a very low cost, 31 they are generally dispatch ed before most fossil units. 32 Under current and historical operating conditions, there are few circumstances in which non-fossil resources reduce output in the presence of lower demand. As a result, in st ates with a moderate contribution of non-emitting resources to total generation, the average emission rate may be lower than could reasonably be expected for reductions from EE/RE programs and measures. 33 Conversely, in states that have significant baseload fossil generation and few non-emitting resources, a state-average emission rate may reflect an emission rate that is too high. This may occur by incorporating emissions
from coal-fired EGUs that are le ss likely to reduce generation with a reduction in electricity load, compared with other lower-emitting fossil fuel-fired EGUs.

30 In other words, a two-percent reduction in energy use would cause all EGUs in the system to reduce generation output by two percent, including coal, gas, nuclear, hydro, and renewable generating resources. 31 For representative variable costs for new EGU, see supp orting documentation for the Electricity Market Module of the Annual Energy Outlook (AEO) 2013, table 8.2., “Cost and performance characteristics of new central station electricity generating technologies”. Geothermal, wind, and solar generating resources are assumed to have a variable operating cost of $0/MWh. Hydroelectric generating resources have an assumed variable operating cost of $2.60/MWh and incur no fuel cost, while nuclear generating resources have an assumed variable operating cost of $2.10/MWh (exclusive of fuel costs). In contrast, gas and coal units are assumed to have variable operating costs from $3-$7/MWh (exclusive of fuel costs. 32 The exception is rare curtailment events for renewable re sources when more energy is produced than required, and due to operational constraints, where wi nd turbines are stalled to maintain system energy balance. Renewable energy generators, such as wind and solar, are sometimes referred to as “non-dispatchable” resources, since the renewable energy resource is intermittent and these generators ca nnot be called upon to run when the renewable energy resource is unavailable. However, here we refer to econ omic dispatch of these resources at times when the renewable energy resource is available. In these instances, these generators are often one of the first resources to be called upon, due to their low variable operating costs. 33 Counting hydroelectric, nuclear, and renewable resources in the denominator would render the emissions rate too low, and thus the avoided emissions smaller than actually realized.26 3. Marginal Emission Rate Approach
A marginal emission rate represents the emi ssion rate of the EGU or cohort of EGUs likely to be displaced by EE/RE ( i.e., an avoided emission rate). A marginal unit is the highestcost unit dispatched at any point in time. 34 Under most circumstances, and at any given time, the marginal unit is the last unit to be brought online to meet electr icity demand and the first unit to be brought offline when electricity load is re duced. Due to constraints on generating unit ramp

rates 35 and transmission availability, it is not unc ommon for multiple units to be dispatched incrementally simultaneously, thus creating a cohor t of marginal units. Marginal unit(s) change on a moment-to-moment basis, determined by load requirements and the va riable cost of each unit available to generate anothe r unit of power. A marginal un it can either be a unit brought online to meet load or may be an EGU that is al ready operating, but that is dispatched at a greater level of output to meet load.

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

ݎ

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

௜ െ ∑ ݃ ாாோா,௜,௧ ௜

Where:

e ref and e EERE = emissions (tCO 2 ) from EGUs i in hour t in the reference case ( ref ) and the change case ( EERE ), respectively; and g ref and g EERE = generation (MWh) from EGUs i in hour t in the reference case ( ref ) and the change case ( EERE ), respectively.

34 See EPA’s Roadmap for Incorporating EE/RE Policies and Programs in State Implementa tion Plans: Appendix B, available at http://www.epa.gov/statelocalclimate/docum ents/pdf/overview_paper_4-28-2011.pdf 35 Ramp rate refers to the ability of an EGU to respond to increasing load, based on its ability to increase output. Ramp rates are typically determined by technology type, with some technologies, such as combustion turbines, able to more quickly increase output in response to increasing load.27 The magnitude of the EE/RE program and the EE/RE load impact shape 36 is a key element in determining marginal emissions reducti ons. In order to obtain a valid estimate of the emission reduction effect of an EE/RE program , an annual marginal avoided emission rate
should be calculated that refl ects the EE/RE program’s load impact shape and magnitude. This annual marginal avoided emission rate may then be applied to other EE/RE programs with similar load impact shapes and magnitudes. The ma rginal emission rate is highly time sensitive, as are the impacts of EE/RE programs and measures . For example, the EGU that is on the margin and is most likely to be displaced from EE/RE in each hour of the year. In addition, different EE/RE programs may have very different load impact shapes, reducing energy requirements in different hours of the year. The interaction between the pattern of EGUs on the margin and the load impact shape of EE/RE programs and meas ures results in a specific marginal avoided emission rate. Applying an annual marginal avoide d emission rate calculated based on the impact of one specific set of EE/RE programs and meas ures to another set of EE/RE programs and measures that is substantively different in tim ing or magnitude of energy savings or generation (i.e ., with a different load impact shape and magnitude) may result in erroneous results ( i.e. the assumption that the wrong EGUs are displaced). 37

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

36 The load impact shape of an EE/RE pr ogram or measure is the hourly (or, if necessary, daily or seasonal) pattern of either energy savings from an EE program or measure, or generation from an RE generator that is supplied to the grid. 37 For example, an EE program focused on measures that re duce peak electricity demand, such as more efficient air conditioning, or a solar RE program, may result in significant reductions in electricity use from the grid during peak demand hours, and little electricity use reduction during ov ernight “trough” hours. In contrast, an industrial EE program may result in a relatively constant electricity load reduction over most hours. An EE program focused on peak reduction measures may reduce generating output from primarily peaking units, while an EE program targeting EE measures with a more constant load impact shape may significantly reduce baseload generation during overnight trough hours.28 4. Methods and Tools for Estimating Avoided CO 2 Emission Rates and Avoided CO 2 Emissions

4.1. Calculation Tool Method
The EPA has developed a user- friendly tool to estimate th e emission reduction impacts of EE/RE requirements, programs and measures. Th e “AVoided Emissions and geneRation Tool” (AVERT) 38 was developed to help air quali ty planners quantify NOx and SO 2 emission impacts, as specified in EPA’s Roadmap for Inco rporating EE/RE Programs in NAAQS SIPs. 39 AVERT can also be used to quantify the displaced CO 2 emissions of EE/RE measures within the
continental United States.

The AVERT method uses historical hourly emi ssions rates based on recent the EPA data on fossil fuel-fired EGUs’ hourly generation an d emissions reported through EPA’s Acid Rain Program. 40 This method couples historical hourly gene ration and emissions w ith the hourly load reduction profiles of EE/RE programs and measures to determine hourly emissions reductions on the margin. AVERT can be used to estimate EE/RE -related emissions reductions in a current or near-future year. However, AVERT estimates for cu rrent or future years are based on historical behavior rather than projected economic behavior. As a result, AVERT does not use projections of future fuel or electricity market prices that affected EGU dispatch, and is therefore not an appropriate tool for l onger-term projections.

Users of AVERT can analyze how the different load profiles of a variety of EE programs and measures, as well as wind and solar technolog ies, affect the magnit ude and location of CO 2 emissions at the county, state, and regional le vel. AVERT has a flexible framework with a simple user interface designed speci fically to meet the needs of state air quality planners and
other interested stakeholders.

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

available at http://epa.gov/airquality/eere/pdfs/appendixI.pdf ), for details about how this approach can be used in the different NAAQS SIP pathways. 40 http://ampd.epa.gov/ampd/.29 AVERT may be used to derive marginal emi ssion reductions from hi storical generation and emissions data, which can be used to derive a marginal avoided CO 2 emission rate. However, AVERT does not quantify average emi ssions rates. AVERT approximates historical dispatch behavior using a statis tical algorithm. It does not repres ent transmission constraints, or significant changes in grid structures or fu ture economic conditions. To estimate a recent historical marginal CO 2 emissions reduction from existing EE /RE programs or measures, a user would input the MWh related to results from EE/RE programs or measures (representing either MWh of electricity savings or MWh of generation) in a representative historical baseline year as a positive increment to electricity load, and r ecord the emissions incrementally added in the
tool. 41 The calculated marginal CO 2 emission rate is the incremental CO 2 emissions added by AVERT, based on historical EGU dispatch pattern s, divided by the incremental MWh of EE/RE savings or generation input to AVERT as an increas e in electricity load. This approach reflects the marginal impact of EE/RE measures based on historical recorded pa tterns of emissions and generation. 42

4.2. Electricity Sector Modeling Method
Quantification of avoided CO 2 emissions from EE/RE requirements, programs, and measures can be achieved through retrospective modeling approaches. Models can be used to
calculate avoided CO 2 emissions by comparing actual realized EGU CO 2 emissions to projected
EGU CO 2 emissions that would have occurred in a hi storical reference case that does not include implementation of the EE/RE that is being eval uated. The appropriate choice of model depends on the look-back period. For short look-back periods of one to thre e years, an electricity system simulation dispatch model can determine the marg inal generation contribu tion to emissions in a

41 Because AVERT represents a historical baseline year, EE and RE programs that o ccurred in a past year are already recorded by the statistics of AVERT. To estimate the emissions impact s of historic EE/RE programs, a user would increase the load by the EE/RE increment to estimate what generation and emissions would have been in the reference case look-back year. 42 AVERT reflects fuel and emission control technologies to the extent they have influenced dispatch during the base year chosen. However, AVERT cannot change disp atch based on future economic or regulatory conditions, such as expected fuel prices, emissi on allowance prices, or specific emissions limits. AVERT should not be used for this type of analysis. When used to review historical da ta, AVERT will capture the impact of historical fuel prices and other impacts on the variable cost of production, but cannot capture specific emission limits.30 historical reference case ( i.e. absent incremental EE/RE programs). 43 Over the short term, simulation dispatch models properly account for E GU economic dispatch considerations, such as fuel and emission allowance prices, and operational constraints, such as ramp rates, outages, and heat rate curves. Look-back periods beyond three to five years would benefit from use of a utility-scale capacity expansion and dispatch planning model to understand the change in build out of new generating capacity, as well as tran smission and distribution infrastructure, and its impact on generation between th e historical reference case an d actual realized historical

outcome.

Electricity System Simulation Dispatch Models Quantifying the CO 2 emissions reductions achiev ed by EE/RE measures through modeling of a near-term look-back period requires a counterfactua l historical reference case model run, which examines how the electric syst em would have operated in the absence of the
EE/RE emission reduction measures under considerat ion. The emissions projected in this model run may be compared against actual realized em issions during the historical period. The lookback model should be calibrated by running the sa me model with the EE/RE measures in place and comparing the outcome of that model agai nst realized generation and emissions at an appropriate spatial scale. 44

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

43 “Reference case” here refers to the case in which a dditional incremental carbon emi ssions reduction mechanisms are not employed, in this case resulting from EE/RE programs and measures. 44 Generally, simulation models will not capture exact output of individual EGUs relative to reality due to a variety of factors, including outages and other non-economic cons iderations not reflected in the model. Therefore, a comparison at an individual EGU scale may not be meanin gful, but aggregate emissions at a state or regional scale should be expected to be comparable.31 Simulation dispatch models may be most rele vant as part of ex-post plan reporting, for estimating the avoided CO 2 emissions from affected EGUs that occurred as a result of EE/RE measures included in a plan, during a specified plan reporting period.

Utility-Scale Capacity Expansion and Dispatch Planning Models Quantifying the CO 2 emissions reductions achiev ed by EE/RE measures through modeling over a longer-term look- back period requires a counterfact ual historical reference case model run, which examines how the electric syst em would have operated and have been built out, in the absence of the EE/RE measures under consideration. Th e critical difference between this type modeling approach and the use of a si mulation dispatch model is the assessment of changes made at the “build margin” – i.e. , new additions to generating capacity that may have been avoided or compelled, or retirements of ex isting units that may not have occurred in the reference case. The emissions projected in this model run may be compared against actual realized emissions during the historical period. The look-back model should be calibrated by running the same model with the EE/RE measures in place and co mparing the outcome of that model run against actual realized generation and emissions at an appropriate spatial scale.

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

Capacity expansion and dispatch planning mode ls may be more relevant than simulation dispatch models for projecting the emission perf ormance that will be achieved by affected EGUs under a plan. As discussed below, these models are able to assess both the “operating” and “build” margins that impact EGU CO 2 emissions as the result of EE/RE measures.32 5. Considerations Associated with us e of an Avoided Emissions Rate
Operational versus Build Margin Avoided emission rates approaches that do not include a capacity expansion model all assume that EE/RE measures only impact the operational margin – i.e., they impact moment-tomoment operations of EGUs in the existing grid. While this is true, deployment of EE/RE over a period of years may have impacts beyond the oper ational margin. Deployment of significant
EE/RE measures over time often im pacts decisions to build new fo ssil generating capacity, retire existing aging generating capacit y, and make different decision s about transmission expansion.
These different decisions about what infrastructure to build or retire are known as the “build margin,” and may ultimately have a greater impact on long-term emissions outcomes than the operational margin.

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

The use of an avoided emissions rate calcu lated based on the operational margin alone may fail to represent the impact of EE/RE meas ures that occur at th e build margin. This differentiation is particularly important in re gions where the pursuit of EE/RE measures may result in the retirement of high-emitting, non-eco nomic generating assets. The use of a capacity expansion and dispatch planning model would he lp accurately assess avoided emissions due to changes at both the build and operational margins.33 Quantifying In-State versus Out-of-State Emissions Reductions The electric system is not confined by state boundaries, and emissions displaced by EE/RE measures may occur over a wide geographic area, 45 including outside of the state that implemented the EE/RE measures. Without the us e of a simulation dispatch model (or, under some circumstances, use of a tool such as AVERT) 46 it can be challenging to attribute emissions reductions that occur within the implementing stat e versus emissions reduc tions that occur across state boundaries. If a state sought to recognize the effect of EE/RE measures and quantified emissions reductions using an approach that did not account for avoided emissions at an appropriate spatial scale, it may inappropriately account for emi ssions reductions that occur in other states, or conclude that all emissions reductions occur within the state’s boundaries. 47 In interconnected areas in which some states pur sue mass-based emissions reductions approaches through their state plans while othe r states pursue rate-based appro aches that include adjustment or crediting for avoided CO 2 emissions from implementati on of EE/RE measures, avoiding double-counting of emission effects among states will be an important consideration when quantifying the avoided emissions resulting from EE/RE measures. These considerations are
discussed below in sec tion VII of this TSD.

45 See California Energy Commission, Emissions Reductions from Renewabl e Energy and Energy Efficiency in California Air Quality Management Districts (2011), available at ( http://ucciee.org/downloads/CAEmissionsReductions.pdf ). 46 AVERT captures the magnitude of in-state versus out-of -state emissions reductions, but may not be an accurate assessment tool for edge-cases – i.e. states that fall near the boundaries of the AVERT regions – because AVERT does not capture inter-regional transmission. 47 In the simplest case, a state without any fossil generating capacity that implements EE/RE measures would cause emissions reductions in neighboring states, and none within its own borders. Similarly, a state with significant, predominantly baseload fossil generation may also cause little in-state emissions reductions from implementation of EE/RE measures because those emissions reductions may occur at marginal generators locat ed outside of the state. Conversely, a state with significant marginal fossil genera ting capacity might realize reductions in emissions from EE/RE measures implemented in other states. These complica tions may arise regardless of if a state is a net importer or net exporter of energy. The key differentiation is if the state’s EGUs are generally on the margin relative to interconnected EGUs in neighboring states.34 V. Quantification, Monitoring, and Verifi cation of End-Use Energy Efficiency and Renewable Energy Programs and Measures
As discussed in the preamble, in section VII. F.4, a key consideration for state plans is the process and requirements for quantifying, monito ring, and verifying the effect of renewable energy and demand-side energy efficiency measures that result in electricity generation or savings. 48 In the preamble, the EPA proposes that a st ate plan that includes enforceable RE and
demand-side EE measures must include an eval uation, measurement, and verification (EM&V) plan that explains how the effect of these measures will be determined in the course of plan implementation. An EM&V plan will specify the analytic methods, assumptions, and data sources that the state will employ during the st ate plan performance periods to determine the energy generation and energy savings related to RE and demand-side EE measures. As discussed in the preamble, an EM&V plan would be subj ect to EPA approval as part of a state plan. In the preamble, the EPA also discusses its intent to develop guidance for acce ptable EM&V methods that could be incorporated in an approvable EM&V plan included as part of an approvable state plan. The EPA seeks comment in the preamble on the critical features of such guidance, including scope, applicability, and minimum requir ements, as well as the appropriate basis for
and technical resources used to establish such guidance, including ex isting state and utility protocols and existing internationa l, national, and regiona l consensus standards or protocols. This
section further elaborates these considerations discussed in the preamble, with individual subsections addressing RE and demand- side EE programs and measures.

The appropriate type of EM&V for RE a nd demand-side EE program s and measures will depend on the state plan approach. For states im plementing a mass-based portfolio approach, the effect of renewable energy and demand-side en ergy efficiency requirements, programs, and measures in helping to achi eve the required level of CO 2 emission performance under a state

48 In particular, this consideration applies to states impl ementing a rate-based emission limit approach that provides for adjustment of CO 2 emission rates based on the effect of end-use energy efficiency and renewable energy, as well as states implementing utility- or state-driven portfolio ap proaches that incorporate end-use energy efficiency and renewable energy requirements and programs.35 plan will be directly evident in reductions in the monitored CO 2 emissions from affected EGUs. 49 In effect, the overall impact of thes e measures could be tracked through CO 2 emission monitoring, reporting, and record-kee ping requirements applied to affected EGUs. However, for states implementing a rate-based plan appro ach, an approvable plan will need to include quantification, monitori ng, and reporting requirements related to RE and demand-side EE requirements, programs, and measures incorporated in a state plan.

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

This section of the TSD disc usses current state and util ity evaluation, monitoring, and verification approaches for end-use energy e fficiency and renewable energy programs and
mandates. This section also discu sses the potential suitability of these approaches in the context of an approvable state plan, and whether harm onization of state approaches, or supplemental actions and procedures, might be warranted in an approvable state plan. In particular, this section
discusses considerations related to the es tablishment of requirements and guidance for quantification, monitorin g, and verification of end-use energy efficiency and renewable energy measures for an approvable state plan. It also discusses the possible a ppropriate basis for and resources used to establish such requirem ents and guidance. This discussion includes consideration of existing state and utility protocol s, as well as any international, national, and regional consensus standards or protocols.

This section also discusses the types of e nd-use energy efficiency and renewable energy measures and programs for which EM&V of re sults is relatively straightforward. Such

49 There could be exceptions, for ex ample where a state plan includes acknowledgement of avoided CO 2 emissions that occur outside state borders as a re sult of state plan measures. See section VII of this TSD for further discussion of the treatment of interstate effects.36 approaches might be subject to streamlined review of EM&V prot ocols included in an approvable plan, provided that such protocols are applied in accordance with EPA requirements and guidance. For example, many utilities have implemented a similar core set of end-use energy efficiency and renewable energy measures and progr ams for utility customers. For these types of measures and programs, a substantial base of experience has been established nationally for quantification, monitoring, and verification of measure and program outcomes.

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

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

1. Introduction
For rate-based state plans, a key element of the plan is a demonstration of how the state, and related entities with enforceable obligations under the plan, will measure and verify energy savings to be achieved the through the implementa tion of end-use energy efficiency measures incorporated in the plan. 50 In the context of demand-side energy efficiency programs currently overseen by state PUCs, this func tion is typically addressed th rough an evaluation, measurement, and verification plan (EM&V plan). This sec tion discusses current state and utility EM&V

50 In this section we use the term “end-use energy efficien cy measure” or “energy efficiency measure” to refer to an end-use energy efficiency requirement (such as an EERS), and energy efficiency progra m, or individual installed energy efficiency measure, such as installation of an energy-efficient air conditioner through an energy efficiency program.37 practice for end-use energy efficiency program s and discusses considerations related to acceptable EM&V plans and evaluation approaches for a state plan under CAA section 111(d).

2. Background on Evaluation, Monitorin g, and Verification (EM&V) of Energy Efficiency Measures
From the time that demand-side energy effici ency (EE) emerged as an important energy strategy in the 1970s, 51 efforts to evaluate the impacts of EE actions have been critical to their success, credibility, and expansion. Starting w ith measurement and verification (M&V) of individual projects, these effort s have evolved to the point wh ere there is now a mature and rigorous evaluation, measurement, and verifica tion (EM&V) industry. This industry includes many professional firms, protocols and guide lines, training and certification programs, regulatory oversight, and estab lished conferences with a rich library of published reports and publically available data and analyses.

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

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

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

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

Both claimed and evaluated energy savings involve real-time a nd/or retrospective assessments of the performance and implementa tion of an energy efficiency program or a portfolio of programs. Important impacts for evaluation include energy and demand savings and non-energy benefits (e.g., avoided emissions, hea lth benefits, job creation and local economic

51 National Energy Program Fact Sheet on the President's Program, April 20, 1977. 52 State and Local Energy Effi ciency Action Network. 2012. Energy Efficiency Program Impact Evaluation Guide

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

.38 development, energy security, tr ansmission and distribution benef its, and water savings). Impact evaluations also support cost-eff ectiveness analyses aimed at de termining the value of energy efficiency programs to utility customers and identifying relative program costs and benefits of energy efficiency compared to other energy re sources, including both demand- and supply-side options.

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

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

53 Ibid.39 3. Current EM&V Practices in States
3.1 EM&V for Demand-Side Energy Effici ency Programs Overseen by State PUCs
Current practice with EM&V for demand-side energy efficiency programs in the U.S. is primarily defined by state utility commission (PUC) 54 requirements for customer-funded efficiency programs. The level of PUC oversight va ries from state to state, but this oversight process has generated the majo rity of the industry guidance and protocols for documenting energy savings from energy efficiency program s. Typically, impact evaluation reports are prepared based on the requirements established by PUCs and submitted (usually annually) for PUC review, approval, and use in resource planning and performan ce assessment. According to a recent survey, most states (79 percent) rely on independent c onsultants and contractors to conduct evaluations, while some states (21 percen t) use utility and/or government agency staff. 55

The range of EM&V budgets varies significa ntly between states, typically from two percent to six percent of total en ergy efficiency program expenditures. 56 The average EM&V budget in 2011 was about 3.6 percent of program e xpenditures. Reasons for this disparity may include the fact that as states expand energy efficiency programs, they may implement more complex programs, which require additional EM&V. 57 EM&V effort in states also typically increases as the magnitude of program expenditu res and energy savings impacts increase, and as states and utilities gain e xperience in implementing energy efficiency programs.

States at the low end of this EM&V e xpenditure range typically rely heavily on deemed savings approaches, which are a common and relativ ely low-cost strategy for documenting energy savings. Deemed savings are measure-sp ecific stipulated values based on historical and

54 In some states these government entities are referred to as a public service commission (PSCs) or board of public utilities (BPU), as well as other names. 55 Kushler, M.; Nowak, S.; Witte, P. , A National Survey of State Policies and Practices for the Evaluation of Ratepayer-Funded Energy Efficiency Programs, American Council for an Energy-Efficient Economy (ACEEE) (February 2012), Report Numb er U122 Available at http://www.aceee.org/ re search-report/u122. 56 Wallace, P.; Forster, H.J. (2012). State of the Efficiency Program In dustry Budgets, Expenditures, and Impacts 2011. Consortium for Energy Efficiency. www.cee1.org/files/2011 CEE Annual Industry Report.pdf

. 57 Expansion of energy efficiency programs may also lead to a reduction in EM&V costs per unit of energy savings, as programs achieve economies of scale and experience in conducting EM&V activities.40 verified data (in some cases using the result s of prior EM&V studies ). Unlike other EM&V approaches, with deemed savings there are no – or very limited – measurement activities. Instead, only the quantity of energy efficiency meas ures implemented is veri fied (e.g., number of motors installed correctly, number of energy-effi cient air conditioners that were purchased using a program rebate). The verified installed energy efficiency measures are then multiplied by the estimated (or deemed) energy savings per measure to derive energy savings for each measure and energy savings for the total number of meas ures installed through an energy efficiency program. The use of deemed energy savings is only considered appropriate for efficiency actions
with well-known characteristics. A variant of this approach is the deemed savings calculation
, which involves the use of one or more agreed-u pon (stipulated) engineeri ng algorithms used to generate energy and/or demand savings associated with energy efficiency measures. These calculations may include predetermined assump tions for one or more parameters in the algorithm, but typically require us ers to input data associated w ith the actual installed measure into the algorithm. 58

The deemed savings values, themselves, are typically centrally located in a “Technical Reference Manual” (TRM). The content and form at of these TRMs vary, but in most cases consists of a database of standardized, state- or region-specific algorith ms (deemed calculations) and associated energy savings estimates (deemed sa vings values) for energy efficiency measures. TRMs also include various data assumptions, sample calculations, and other inputs that the state uses to develop energy savings values for the rang e of energy efficiency programs in place. The benefits to energy efficiency program administ rators of using a TRM include reduced EM&V costs and greater certainty rega rding projected, claimed, and ev aluated energy savings values (see definitions above). Ther e are about 20 states curre ntly using TRM databases. 59

58 Examples of equipment types that are commonly evaluate d using deemed savings valu es and calculations include energy-efficient washing machines, com puter equipment, and refrigerators, an d lighting retrofit projects with wellunderstood operating hours. For deemed savings calculati ons, evaluators collect information about the actual installed measures -- such as hours of usage, watta ge, and/or equipment capacity -- and combine this with predetermined assumptions in the algorithm. 59 State and Local Energy E fficiency Action Network, Scoping Study to Evaluate Feasibility of National Databases for EM&V Documents and Measure Savings , prepared by Jayaweera, T.; Haeri, H.; Lee, A.; Bergen, S.; Kan, C.; Velonis, A.; Gurin, C.; Visser, M.; Grant, A.; Buckman, A.; The Cadmus Group Inc. (June 2011), available at http://www.eere. energy. gov/seeaction/pdfs/emvsc oping__databasefeasibility.pdf.41 It should be noted that TRM values for i ndividual energy efficiency measures are not always formally vetted in a regulatory process, although this is a good practice. 60 A recent survey of TRMs found that deemed energy savings values for comparable energy efficiency measures vary across states and regions. 61 The reasons for these vari ations include the use of different calculation methodologies, technical assumptions, and input variables. Some of these differences are expected based on relevant differences in weather and baseline assumptions (e.g., existing building stock and common practices vary from one state to another). However, other
differences are related to out-of- date input assumptions and calcula tion errors. In the context of state plans, this variation, and in particular data quality issues with some TRMs, raises consideration of whether comple te reliance on existing TRM resour ces for state plans is prudent and appropriate, including how such relian ce could or should be circumscribed.

In addition to the use of deemed savings , states on the higher end of the EM&V expenditure range rely to a grea ter extent on a variety of dir ect measurement approaches for documenting energy savings. Rather than mandati ng which EM&V methods must be used in a particular situation, PUCs typica lly allow utilities and other progr am administrators to select from a range of appropriate EM&V approaches that are consistent with standard practice in the energy efficiency industry. EM&V analyses and cal culations are then carri ed out, in most cases by an independent, third-party ev aluator, through a pro cess that is unbiase d, uses technically rigorous methods, effective peer review, and is subject to public review and comment. In addition, energy savings are frequently certified by the PUC as compliant with requirements defined in a pre-approved EM&V plan.

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

60 State and Local Energy E fficiency Action Network, Energy Efficiency Program Impact Evaluation Guide
, prepared by Steven R. Schiller, Schille r Consulting, Inc. (2012), available at http://www.seeaction.energy.gov

. 61 Ibid.42  Use of one or more of the industry-standa rd EM&V protocols or guidelines (listed below), as well as the use of deemed savings values for well-understood energy efficiency programs and measures

 Consideration of local fact ors, such as climate, bu ilding type, and occupancy.

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

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

 Provision of interim and annual re porting of achieved energy savings.

Despite this well-defined and generally accep ted set of industry best practices, many states with energy efficiency programs use diffe rent input values and assumptions (e.g., net versus gross savings, run-time of equipment, meas ure lifetime) in applying these practices. This can result in significant differences in claime d energy savings values for similar energy efficiency measures between states, even when the same measure type is installed under
otherwise identical circumstances. In response to a growing awarene ss of this lack of cross-state comparability, policy makers, regulatory agencies, and other stakeholders are increasingly advocating for the use of common evaluation appr oaches across jurisdictions. Several national and regional EM&V efforts have emerged to promote collaboration and information sharing across states. These initiatives include the Northeast Energy Efficiency Partnership’s (NEEP) EM&V Forum, which is active in New Engla nd, New York, and the Mid-Atlantic, and the Pacific Northwest’s Regional Technical Forum (RTF ). Both efforts aim to promote multi-state coordination in EM&V practices, make EM&V resu lts more transparent and publicly available, and support the adoption of similar defi nitions, methods, and input assumptions. 62

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

62 For a list of EM&V resources, including more info rmation about these regional EM&V collaboratives, see http://www1.eere.e nergy.gov/seeaction/evaluation.html

.43 a. U.S. DOE Uniform Methods Project (UMP) Protocols 63
b. International Performance Measuremen t and Verification Protocol (IPMVP) 64

c. Federal Energy Management Program (FEMP) M&V Guidelines 65
d. American Society of Heating, Refrigerat ing and Air-Conditioning Engineers (ASHRAE) Guideline 14, Measurement of Energy and Demand Savings 66

e. California Evaluation Protocols 67
f. ISO New England (ISO-NE) Manual for M easurement & Verification of Demand
Resources 68

g. PJM Energy Efficiency Measurement and Verification Manual 69
h. State and Local Energy Efficiency Action Ne twork, Energy Efficiency Program Impact
Evaluation Guide 70
i. U.S. DOE Superior Energy Performance M easurement and Verification Protocol for Industry 71

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

. 64 Efficiency Valuation Organization (EVO), International Performance Measurement and Verification Protocol (2012), available at: http://www.evo-world.org/

. 65 FEMP, M&V Guidelines: Measurement and Verification for Federal Energy Projects, Version 3.0 (April 2008), available at: https://www1.eere.energy.gov/ femp/pdfs/mv_guidelines.pdf

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

. 67 California Public Utilities Commissions (CPUC), California Energy Efficiency Evaluation Protocols: Technical, Methodological, and Reporting Requirements for Evaluation Professionals (2006), available at: http://www.calmac.org/events/EvaluatorsProto cols_Final_AdoptedviaRuling_06-19-2006.pdf. 68 ISO-New England (ISO-NE), Measurement and Verification of Demand Reduction Value from Demand Resources (2013), available at http://www.iso-ne.com/rules_proceds/isone_mnls/MMVDR/index.html. 69 PJM, Manual 18B: Energy Efficiency Measurement & Verification (2010) , available at http://www.pjm.com/~/media/documents/manuals/m18b.ashx

. 70 U.S. DOE State and Local Energy Effi ciency Action Network (SEE Action), Energy Efficiency Program Impact Evaluation Guide (December 2012), available at: http://www1.eere.energy.gov/seeaction/pdfs /emv_ee_program_impact_guide.pdf. 71 U.S. DOE, Superior Energy Performance Measurement and Verification Protocol for Industry (2012), available at: http://superiorenergyperformance. energy.gov/pdfs/sep_mv_protocol.pdf.44 While many states are currently relying upon these protocols and guide lines, other states and regional organizations (e.g., ISOs and RTOs) take the additional step of specifying accuracy and uncertainty requirements for energy savings estimates. For example, ISO-NE requires that energy efficiency bids into its Forward Capacity Market (FCM) ensure that impact evaluations achieve ±10 percent statistical precision at the 80% confidence interval (see below for more on FCMs).

Regardless of the evaluation approach follo wed, the majority of state PUCs and energy efficiency program administrators aim to stri ke a balance between the transaction costs of EM&V activities (i.e., expense, time, staff e ffort) and the resulting re liability, validity, and usefulness of the estimated energy savings re sults. The appropriate balance between EM&V costs and the rigor of EM&V – and the related ce rtainty of energy savings estimates – is often determined based on the type of program (i ncluding program purpose and goals), level of program expenditures, and magnitude of anticipated energy savings.

3.2 EM&V for Energy Efficiency Measures used in ISO Forward Capacity Markets
Two Independent System Operators (ISOs) resp onsible for operating regional electricity grids and overseeing wholesale electricity mark ets in certain regions of the country have established forward capacity markets (FCMs) that pay suppliers to ensu re sufficient electric generating capacity is available to meet futu re peak electricity demand. In operating these markets, ISO New England (ISO-NE) and PJM both allow demand-side energy efficiency programs and other demand-side res ources to compete directly with electric generators to meet the regional capacity needs. One re quirement for utilities and other energy efficiency program administrators seeking to bid into the market is to submit an evaluation plan. ISO acceptance of this evaluation pl an “qualifies” energy efficiency programs and pr ojects as prospective market resources. The evaluation plan specifies the amount of energy and demand savings to be delivered over the contract peri od (typically three years into th e future), and documents how the requirements of the ISO’s M&V standards manual will be satisfied.

Based on experience to-date, st ates bidding their energy effici ency programs into both the ISO-NE and PJM forward capacity markets are ty pically subjected to EM&V requirements that45 go beyond the evaluation already conducted for the purpose of meeting PUC requirements. This is because, while PUCs typically require eval uation protocols and procedures for documenting the cost-effectiveness of annual energy (MWh ) savings, FCMs require the measurement and verification of capacity (MW) sa vings during specific peak de mand hours. In addition to the evaluation of energy savings, a separate set of measurement technique s and data collection protocols are required to document peak demand reduction impacts. Furthermore, attaining the level of statistical precision and confidence de scribed above typically requires additional sampling 72 than is required by PUCs. One considerat ion is whether EM&V requirements in ISO capacity markets include components that woul d facilitate better estimation of avoided CO 2 emissions related to energy efficiency programs include in state plans.

For the states located in ISO-NE and PJM, the common evaluation requirements for FCM participation have created an impetus for regional collaboration on EM&V practices. New England and Mid-Atlantic states continue to work together to establish consistent evaluation protocols through the creation of an “EM&V Forum,” which is convened by the Northeast Energy Efficiency Partnerships (NEEP) and supports common evaluation methods, reporting metrics, and cost sharing on research studies. 73 The Forum also serves as a venue for information exchange to address common EM&V challenge s encountered with FCM participation.

3 .3 EM&V for Programs and Policies Not Typically Overseen by PUCs
In contrast to energy efficiency program s overseen by PUCs, EM&V is less common for other types of energy efficiency requirements or programs, especially for minimum energy efficiency requirements that do not involve the expenditure of electric ity ratepayer dollars. Examples include building energy codes, appl iance efficiency standards, various energy efficiency financing programs , behavioral change programs, and market transformation programs that target both the suppliers of energy-efficient pr oducts and increasing consumer demand for those products. While these approaches often have substantial impacts in reducing

72 With additional sampling requirements, energy efficiency program evaluators are typically required to measure a larger percentage of the energy efficien cy measures installed within the total population of all measures installed through an energy efficiency program. 73 More information about the EM&V Forum is available through Northeast Energy Efficiency Partnerships, at https://neep.org/emv-forum/index

.46 energy use, they may also face EM&V challe nges. In some cases, appropriate evaluation protocols and approaches have not been develo ped for some programs and measures. In cases where appropriate EM&V methods do exist, ther e may also be less experience applying them. 74

4. Considerations for EM&V of End-Use En ergy Efficiency Programs and Measures in State Plans
A key consideration for state plans is the pr ocess and requirements for EM&V of RE and demand-side EE measures that result in electricity generation or savings. As described in the preamble, at section VII.F.4, the EPA intends to develop guidance on acceptable methods that can be incorporated in an EM&V plan included as part of an approvabl e state plan. Critical features of such EM&V guidance, including sc ope, applicability, and minimum criteria, are
discussed in this section.
4.1 Accuracy of Energy Savings Estimates
To document and verify that avoided CO 2 emissions from energy efficiency programs and measures are real and persistent, impact eval uation must be rigorous a nd transparent. Impact
assessment should also consider the appropriate balance between certainty of results and the EM&V costs to achieve a specified level of certainty. Because energy savings data are estimates , their use as part of the basis for determining the avoided CO 2 emissions resulting from energy efficiency programs and measures in a state pl an will depend upon the leve l of accuracy of this information. Therefore, evaluation results shoul d be reported as “expected values”—that is, energy savings values are expected to be correct within an associated range of certainty. Key considerations for EM&V of energy efficiency pr ograms and measures in state plans are similar to those faced in the design of any program evalua tion approach: (1) the level of certainty that is required given a program’s objectives and requir ements, and (2) how achievement of that necessary level of certainty is balanced with the amount of effo rt (e.g., resources, time, money)
used to obtain that level of certainty.

74 Examples of such EM&V methods are described in the PNNL report, “Building Energy Codes Program: National Benefits Assessment: 1992-2040.”; and in Meyers et al, “Energy and Economic Impacts of U.S. Federal Energy and Water Conservation Standards Adopted From 1987 through 2012” LBNL-6217E.47 4.2 EM&V Technical Considerations for State Plans Using energy efficiency requi rements, programs, and measures as an emission reduction approach in state plans requires considera tion of several evaluation-related technical considerations. The following sections describe these considerations.

4.2.1 Qualifying Demand-Side Energy Efficiency Actions States are currently implementing a wide range of demand-side energy efficiency requirements, programs, and measures. However, EM&V of some of these programs and measures are associated with gr eater levels of measurement preci sion and certainty than others, based in part on the EM&V procedures currently in place. For example, energy efficiency programs subject to PUC oversi ght and review are frequently evaluated using rigorous evaluation procedures that are based upon severa l decades of research and experience. These energy efficiency programs are subject to a qu asi-judicial, public, a nd transparent review process, which can lead to adoption of EM&V protocols that convey a relatively high level of certainty for EM&V results.

In contrast, other energy effi ciency requirements and measures, some of which may result in very significant and cost-effective energy sa vings (e.g., building energy codes, local tax credits, EE loan programs, etc.), are not subject to PUC oversight and typically have comparably fewer EM&V requirements. There are also some newer EE program designs (e.g., certain behavior-based programs and some market transformation programs 75 ) for which rigorous EM&V methodologies or a track record of en ergy savings persistence do not yet exist. 76

75 Behavior-based energy efficiency programs aim to affect cons umer energy-use behaviors in order to achieve energy and/or peak demand savings. Techniques to measure the impacts of th ese program designs are emerging and currently under development. Market transformation programs are characterized by strategic intervention in a market to address market barriers and market failures to accelerate market adoption of energy-efficient technologies and practices, and create lasting market change. While market transformation approaches can have very high energy savings impacts, by creating sustained deployment of energy-efficient technologies and practices, evaluation of these strategies is challenging due to the involvement of numerous market players and the multi-year timeframe for achieving energy savings. 76 We note that EM&V approaches and protocols for behavior-based end-use energy efficiency programs do exist, but they have not been widely applied. For examples, see State and Local Energy Efficiency Action Network (SEE Action), Evaluation, Measurement, and Verification (EM&V) of Residential Behavior-Based Energy Efficiency Programs: Issues and Recommendations (2012), Prepared by A. Todd, E. Stuart, S. Schiller, and C. Goldman,48 As discussed in the preamble, wh ile the EPA does not intend to limit the types of RE and demand-side EE measures and programs that can be included in a state plan – provided that supporting EM&V is rigorous, complete, and cons istent with EPA requirements and guidance – the level and type of documentation required by EPA in an approvable state plan may depend on whether EM&V practices for that type of progr am or measure are well established. One option for organizing these variations in EM&V practices is with a qua litative hierarchy, as follows:

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

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

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

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

Lawrence Berkeley National Laboratory. Available at http://www1.eere.ene rgy.gov/seeaction/pdfs/emv_beha viorbased_eeprograms.pdf

.49 Table 2. Illustrative Characterization of EM&V Procedures and Protocols for Common Energy Efficiency Programs and Policies 77

EM&V Procedures and Protocols Well Established EM&V Procedures and Protocols Moderately Well Established EM&V Procedures and Protocols Less Well Established

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

o lighting

o heating, ventilation, and air conditioning (HVAC)

o refrigeration

o motors

 Consumer-direct and midstream rebates for ENERGY STAR-certified lighting, appliances (including residential refrigerator recycling), and HVAC equipment

 Building commissioning and retro-commissioning

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

 Combined heat and power (CHP) installations/retrofits

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

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

 Product-specific upstream market transformation programs directed at manufacturers

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

 Targeted training programs

 Building labeling and disclosure programs

 Targeted consumer behavior programs

77 This table is intended as a generalized description, based upon numerous conversations with professional energy efficiency program evaluators. It sh ould be noted that there are states with building energy codes, behavior programs, and market transformation programs that are well documented and subject to rigorous EM&V. In addition, such characterizations will change over time, as EM&V approaches for new and innovative programs and measures become standard practice.50 As discussed in the preamble, at section VIII.F.4, EPA is proposing to allow a wide (or unlimited) set of energy efficiency program and measure types in state plans, as long as the energy savings are adequately documented according to rigorous EM&V methods and appropriate state regulatory ove rsight. Recognizing these variati ons in EM&V procedures and protocols, one option for EM&V requirements and guidance for state plans is to streamline review of EM&V plans for a pre-defined li st of well-understood program types for which evaluation is straightforward and energy savings results are subject to a relatively low level of uncertainty. 78 Other programs and measures with le ss well developed EM&V approaches would require greater documentation in state plans of EM&V methods that will be applied. This proposed approach is intended to maximize stat e flexibility and accommoda te the full range of state energy efficiency programs, while si multaneously maintaining EM&V rigor and transparency. As discussed in the preamble, at section VIII.F.4, EPA is also taking comment on the option of limiting the eligible types of energy efficiency programs and measures that could be included in a state plan to a pre-define d list of well-understood program types for which evaluation is straightforward and energy savings results are subject to a relatively low level of uncertainty.

4.2.2 Avoided Transmission and Distributi on (T&D) Losses from End-Use Energy Efficiency Measures
In general, the difference between the amount of electricity input to the transmission system by an EGU and the amount ultimately deli vered to an end-user constitutes transmission and distribution (T&D) line losses. 79 According to EIA data, na tionally, annual electricity
transmission and distribution losses are equivalent to about seven percent of the electricity that is input to the transmission system in the United States. For every unit of energy use avoided at the end-use site, energy efficiency also avoids the losses that would ot herwise occur as electricity is

78 This includes energy effi ciency programs and measures for which th ere is significant experience with EM&V, a robust set of existing EM&V studies and reports, and relatively straightforward EM&V approaches. 79 The T&D system includes all the power lines and related equipment used to deliver electricity from an electric generating plant to an end-use site. Along the way, some of the supplied by the generator is lost due to the resistance of the wires and equipment that the elect ricity passes through, as well as reactive power losses in alternating current systems due to inductance and capacitance. Most of this lost energy is converted to heat. The magnitude of losses in the T&D system depends on the physical characteristics of the system in questio n, as well as how it is operated.51 delivered to consumers through the T&D system. 80 Many state PUCs are aware of this
additional benefit of demand-side energy efficiency progr ams, and actively credit program energy savings results to account fo r program contributions to avoide d line losses, albeit using a range of measurement approaches and calculati ons. A consideration for EM&V requirements and guidance for state plans is whether to accoun t for avoided T&D losses, and how to do so in a
consistent manner across states.

4.2.3 Reported Energy Savings Values
Energy savings results for energy efficiency programs are often expressed in terms of annual MWh of savings per year. However, for an assessment of the associated avoided CO 2 emissions impacts, it may be useful to utilize time-differentiated (i.e ., hourly, seasonal) energy savings data. 81 Information about the timing of ener gy savings has direct implications for estimating the avoided CO 2 emissions that result from an e fficiency program or portfolio of programs. The temporal energy savings profile that results from the application of energyefficient technologies and practices to different end-uses can vary significantly. Fo r example, air conditioner programs save energy primarily on hot summer days, whereas a refrigerator program saves energy every hour of the year. Time-diffe rentiated information related to electricity generation is useful in estimating avoided CO 2 emissions. In particular tim e-differentiated data is necessary to estimate the marginal avoided CO 2 emissions related to electric generation, as
discussed above in section IV.C.3.

In practice, state PUCs around the country have substantiall y different requirements and recommendations for evaluating and reporting time- differentiated energy savings. Some energy efficiency program administrators report annua l energy savings impacts, where savings are typically based on either tracking data (i.e., data used to es timate savings for planning purposes) or evaluated (i.e., ex-post) sa vings data. Other programs supplement reporting of annual energy savings with data on the timing of energy savings, which can be used to identify the marginal EGU or cohort of marginal EGUs that would ha ve provided generation in the absence of the

80 U.S. EPA, Assessing the Multiple Benefits of Clean Energy: A Resource for States (February 2010), available at: http://epa.gov/statelocalclimate/documents/pdf/epa_assessing_benefits_ch3.pdf 81 This is often referred to as the “load shape” of energy savings achieved through an energy efficien cy measure.52 energy savings. This supplemental data can be used to more accurately estimate avoided CO 2 emissions that result from program energy savi ngs. Due to improved evaluation software and data availability, it is increasingly common fo r energy efficiency program EM&V plans to
include calculation of estimated seasonal or even hourly energy savings as part of the program evaluation process. A consideration for EM&V re quirements and guidance for state plans is the
extent to which time-differentiated data on en ergy savings from energy efficiency programs is available, and whether states can readily acq uire such data and information for use in implementing their state plans.

A related consideration is metr ics reported for electricity savings. The primary metric required to understand the avoided CO 2 emissions impacts of energy efficiency programs and measures is annual MWh of energy saved. In addition, a secondary metric is MW demand reduction impacts, which may be desirable because it is helpful in identifying the marginal EGU or cohort of EGUs, in particular units on the bui ld margin. This information is necessary to estimate the marginal avoided CO 2 emissions related to electr ic generation, when reporting on
avoided CO 2 emissions achieved through energy efficien cy programs and measures during a plan reporting period, as discussed above in secti on IV.C.3. Identifying EGUs on the build margin, based on estimates of MW demand savings that will be achieved through the implementation of energy efficiency programs and measures included in a state plan, may also be useful in projecting emission performance by affected EGUs that will be achieve d under the state plan.

4.2.4 Savings Definitions: Net and Gross Savings
As described above, state PUCs typically specify whether energy efficiency program administrators are required to report either gross or net ener gy savings, or both. Gross savings are the change in energy use (MWh) and dema nd (MW) that results directly from programrelated actions taken by program pa rticipants, regardless of why th ey participated in a program. Net savings refer to the change in energy use a nd demand that is direct ly attributable to a particular energy efficiency program. 82 Reporting of net savings help s a PUC ensure that energy

82 Calculations of net energy savings involve excluding ener gy efficiency measur es undertaken by "free riders" (i.e., EE program participants who receive a program rebate ev en though they would have taken the efficiency action anyway), or adjusting energy savings estimates to account for these e ffects. Free riders increase program costs53 efficiency program budgets are being used to pr omote technologies and practices that are not otherwise being adopted in the marketplace. A consideration for EM&V requirements and guidance for energy efficiency requirements and programs included in state plans is whether required reporting of energy savings should be specified on either a gross or net basis, or both, to promote national consistency in measuring the imp act of energy efficiency measures across state plans. 83

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

without producing additional energy savings impacts beyond what would have occurred in the absence of the EE program. Free ridership may also be addressed in the setting of baselines that are used to calculate energy savings. Estimates of net energy savings may also involve an asse ssment of "free drivers" (s ometimes referred to as "spillover effects"). These are individuals who do not directly participate in an EE program, but who undertake efficiency actions in response to program activity (e.g., marketing/advertising, greater availability of energyefficient equipment in a marketplace as the result of EE programs). Accura te estimation of free ridership and spillover effects is complex, especially in areas of the c ountry with robust energy efficiency markets with multiple non-program influences compe ting for customers’ attention. 83 If both gross and net savings were required to be reported , this would increase the transp arency of reported energy savings estimates, but only one savings value would be used to evaluate the effect of en ergy efficiency programs and measures on CO 2 emissions from affected EGUs.54 5. Options for EM&V Requirements and Guidance for State Plans
As EPA develops guidance on acceptable evaluati on methods that can be incorporated in an EM&V plan included as part of an approvabl e state plan, the agency (as discussed in the preamble at section VIII.F.4) is seeking comme nt on the appropriate basis for and technical resources used to establish such guidance, incl uding consideration of ex isting state and utility protocols, as well as existing international, national, and re gional consensus standards or protocols, as described in this section.

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

As discussed previously, current state EM&V practices involve aligning the level of EM&V effort (i.e., rigor, reliability, validity, and uncertainty of energy savings estimates) with the appropriate level of certain ty of evaluation results, while taking into consideration the magnitude of energy efficiency program impacts. This approach is consis tent with the objective of achieving environmental results, ensuring mi nimum levels of cross-state consistency, and supporting and encouraging the use of energy efficiency requireme nts, programs, and measures55 in state plans. To advance thes e objectives, the EPA could take several possible approaches for documenting energy efficiency savings from measures in state plans.

Options for EM&V requirements and guidance for state plans that incorporate energy efficiency requirements, progr ams, and measures include:

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

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

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

At one end of this spectrum, establishing program-specific EM&V requirements and an associated level of rigor for EM&V provides ce rtainty to states in terms of required energy savings documentation, and does so in a manner that ensures a consistent level of EM&V rigor across all state plans. However, this approach may require significant effort by the EPA to establish such requirements, and could potentially duplicate state efforts currently under way to harmonize EM&V practices. This approach ma y also limit the variety of valid EM&V approaches applied at the state level, and by extension the types of energy efficiency programs
and measures that could be included in a state plan. It could also inhibit the development of innovative EM&V approaches that improve the accuracy of energy savings estimates. At the other end of the spectrum, if only generali zed, process-oriented EM&V requirements and guidance are established, then a state has maximu m flexibility, but also faces somewhat greater uncertainty about whether the EM&V approach in cluded in a state plan will be approved by the
EPA. This could increase the transaction costs in curred by states during the development of their56 plans, and could possibly delay the full im plementation of energy efficiency programs incorporated in state plans.

Alternatively, a middle-ground approach invol ves a combination of specific EM&V criteria for common energy efficiency program and measure types, along with generalized guidance for emerging program designs and measur es. Such an approach would provide some level of certainty regarding accep table EM&V approaches in stat e plans, while maintaining a certain degree of flexibility for states to dete rmine an appropriate mix of EM&V approaches, given the types of energy efficiency progr ams and measures included in their plan.

In addition, one option for supplementing either approach described above is to prescribe
who can conduct EM&V activitie s and prepare energy savings documentation, and to specify their needed qualific ations. This approach is analogous to professional certification requirements in the accounting and engineering fields, in wh ich a minimum level of credibility, rigor, and accountability is imparted to the services provid ed by qualified individuals and firms. Criteria for eligible evaluators might incl ude a demonstration of independe nce from those implementing or administering the energy efficiency programs and measures ( i.e. , identification and mitigation of potential conflicts of intere st) and required minimum levels of training, experience, or certification. This approach rec ognizes that the qualifications , integrity, and independence of those conducting EM&V of energy efficiency programs and measures, and preparing energy savings estimates, is critical to assuring best-practi ce EM&V. However, such requirements alone may not ensure sufficient evaluation rigor.

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

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

 Establishing new protocols and procedures57 Relying on existing approaches has the benefit of utilizing existing resources that can be relatively quickly ramped up for use in state pl ans. However, existing state and utility EM&V infrastructure and protocols ma y not be applicable to the fu ll range of energy efficiency programs and measures that a state may want to include in its plan. In addition, because existing state and utility EM&V infrastructure and protocol s were established to su pport the goals of state energy efficiency programs, in current form they may not adequately sup port the level of EM&V required for state plans under CAA section 111(d). In particular, this may include the form and precision of energy savings data and repor ting necessary to ev aluate avoided CO 2 emissions that result from energy efficiency programs and measure included in state plans.

5.2 EPA Review of EM&V Plans as Pa rt of the State Plan Review Process
As discussed in the preamble, at section VIII.F.4, the EPA is proposing that a state plan must include an EM&V plan, which is subject to approval by EPA, as part of plan review and approval. Under this approach, th e EPA would review these EM&V pl ans as part of its review of submitted state plans. One option is that an approvable EM&V plan could rely primarily on state- or utility-level EM&V pl an review and approval processes, consistent with established EPA requirements and guidance for EM&V, with open public involvement and state lead-agency approval. Using existing state EM&V plan revi ew processes may better ensure that energy savings estimates are transparent, peer review ed, and address stakehol der input. Using state processes also minimizes duplica tion of state and the EPA require ments, and balances the need for EM&V credibility and rigor with an interest in encouraging the deployment of cost-effective energy efficiency programs and measures th rough incorporation in state plans.

5.3 General Quality Standards for EM&V Rigor and Accuracy
Since existing state EM&V process vary, EM&V guidance established by EPA may need to identify and establish minimum criteria for EM &V rigor, accuracy and reliability, and quality control. Requirements could be (a) a single set of requirements that apply to all energy efficiency programs and measures in all states or (b) a va riable or flexible set of requirements with increasing levels of EM&V effort and rigor de pending on the relative degr ee of uncertainty of energy savings from the energy efficiency program s and measures in a state plan. For example,58 well understood energy efficiency measures with a higher degree of energy savings certainty might require a lower level of EM&V effort, while measures with greater complexity or uncertainty of energy savings effects would require greater EM&V effort. 84

For simple, well-understood and straight forward energy efficiency programs and measures, such as lighting retrofits, EPA guidan ce might specify only verification that measures were installed and the use of deemed energy savi ngs values (i.e., lower EM&V effort level). In contrast, EPA guidance might specify more detailed EM&V (i.e., a higher level of EM&V effort) for less well-understood or more complex energy efficiency programs and measures, such as behavior programs and mark et transformation programs.

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

6. EM&V Documentation in a 111( d) State Implementation Plan
EM&V documentation will be an important co mponent of state plans that incorporate energy efficiency programs and measures, beca use transparency and reproducibility increase overall confidence in reported energy savings results. A crucial component of EPA’s proposed approach for evaluating energy efficiency program s and measures included in a state plan is a requirement that state plans that include enfo rceable energy efficiency and renewable energy measures must include an EM&V plan for th ese measures. These EM&V plans would specify how achieved energy savings will be retrospectivel y evaluated at appropriate increments during

84 For the purposes of this discussion, lower, medium, and high levels of “EM&V effort” are intentionally indeterminate. One possibility is that “lower EM&V effo rt” could refer to greater reliance on deemed savings values, smaller sample sizes for measured savings, fewer direct measurements, and pro portionately greater reliance on ex-ante estimates. “Medium” and “hig h” levels of EM&V effort could require incrementally more effort in each of these areas. Other interpretations of this concept are possible.59 the plan period. Decisions about the level of EM&V documentation that is necessary in a state plan must consider tradeoffs between provision of more inform ation and greater transparency, and the level of EM&V effort required. Exce ssive documentation requirements may not add value in terms of transparency, but may disc ourage the inclusion of cost-effective energy efficiency options in state plans. However, two basic criteria for EM&V documentation should be applied in state plans:

 Energy savings documentation should be provid ed at a level of detail that allows for recalculation of program en ergy savings totals; and

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

6.1 Illustrative Example of an EM&V Plan for End-Use Energy Efficiency Programs Measures in a State Plan
The following is an example of a possible outl ine of the types of in formation that might be included in an EM&V plan for energy effici ency programs and measures included in a state plan. An EM&V plan would specify how EM&V activities will be conducted and reported for relevant energy efficiency programs and measur es during a state plan performance period. An EM&V plan could apply to utilit y energy efficiency programs that are incorporated into a state plan on a stand-alone basis, a nd might also apply to such programs when used to meet mandatory energy efficiency requirements, such as an EERS, that are incorporated into a state plan.

Who Will Document Savings and When

 Name of the organization that will pr epare evaluated energy savings reports

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

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

 Name of the state or regional government entity, or non-governmental entity, which will review and certify the evaluated savings60  How evaluated energy savings reports will be made publicly available and what the primary use of the reports will be

Documentation Procedures

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

 Name of impact evaluation protocols, guida nce documents, and other methods that will be followed in preparing eval uated energy savings reports

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

 Description of assumptions c oncerning availability of data and data collection methods

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

o Inclusion of estimates of avoided electr icity transmissions a nd distribution losses

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

o Sources of uncertainty

B. Quantification, Monitoring, and Veri fication for Renewable Energy Measures
For rate-based state plans, a key element of the plan is a demonstration of how the state, and related entities with enforceable obligations under the plan, will measure and verify electric generation that is achieved through the impl ementation of renewable energy measures incorporated in the plan. 85 This section discusses current state and utility quantification, monitoring, and verification practices for renewable energy measures, and discusses
considerations relate d to possible acceptabl e quantification, monito ring and verification approaches for a state plan under CAA section 111(d).

States and utilities use a variet y of policy instruments to in crease the production and use of renewable energy. The principal mechanisms include: renewable portfolio standards (RPSs),

85 In this section we use the term “ren ewable energy measure” to refer to a renewable energy requirement (such as an RPS), a renewable energy deployment program, or individual installed renewable energy measures, such as installation of a solar photovoltaic system through a renewable energy deployment program.61 feed-in tariffs (FITs), tax incentives (e.g., pr operty tax exemptions; production-based tax incentives; etc.), financial a ssistance programs (e.g., grants, loan s, and other direct financial assistance based on generating cap acity or investment level), and other policies (R&D support; manufacturing incentives; workforc e training; net metering; etc.). Experience to date indicates that RPSs have led to the vast majority of th e increase in renewable en ergy generating capacity and generation resulting from st ate policies. However, FITs and production-based tax incentives have been among the most important incentives used by states and utilities to help achieve RPS requirements, as well as to spur additional production and use of rene wable energy. Further, these types of programs rely on m easurable electric generation as the basis for compliance or incentive payments. As a result, the following discussion focuses on qua ntification, monitoring,
and verification mechanisms related to these stat e policies. Other types of programs (e.g., certain grant and rebate programs) may not currently quantify electric generation output from funded renewable energy projects. However, if such programs were modifi ed to require the collection of such data, many of the quantification, monitoring , and verification considerations discussed in this section would also generally apply.

1. Renewable Portfolio Standards
A RPS is designed to increase the amount of renewable energy a distribution utility or load-serving entity provides to retail electricity customers. 86 . This increased customer demand in turn increases the production of renewable energy to meet demand. To achieve compliance with a RPS, an increasing share of a distribution utility’s el ectricity retail sales is required to be produced or acquired from renewa ble energy resources and delivered to customers. To verify compliance, RPSs have been complemented by tracking systems for renewable energy generation and use. These tracking systems account for the growing amount of renewable energy

86 In states that have restructured their electricity sectors and introduced retail competition, entities other than a utility may supply electricity to a retail customer. These entities use a regulated distribution utility’s network to deliver electricity to a retail consumer. These entities either generate their own electricity or contract for supply from wholesale electricity market participants. In this section, we use the term “distribution utility” to refer broadly to both local distribution companies (LDCs) and other load-servi ng entities that supply electricity to retail customers.62 that is produced for obligated retail sellers as well as large and small retail energy consumers that purchase renewable energy on a voluntary basis. 87

The point of regulation for state RPSs is ty pically investor-owned electric distribution utilities, because most RPS apply to entities under the jurisdiction of stat e PUCs. In a number of states, municipally-owned utilitie s and electric cooperatives are exempt from state RPS, have lower RPS requirements, or are required to de velop their own renewable energy procurement targets. Additionally, some states have created separate renewable energy requirements for each
of their affected di stribution utilities.

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

There are several pathways that affected distri buted utilities typically have to meet state RPS requirements, including building and opera ting renewable energy generating capacity, purchasing electricity from renewable energy ge nerators, and purchasing the attributes from renewable energy generation. Many st ate RPSs take this latter a pproach. Rather than requiring each distribution utility to generate electricity from its own renewable energy facilities or purchase electricity from a renewable facility owned by others, many stat es require distribution utilities to acquire renewable ener gy certificates (RECs) that represent the attributes of the unit of renewable electricity produced. 88

By allowing REC trading, many states have created markets for RECs based on specific state RPS requirements. Renewable energy genera tors can sell RECs as another product bundled with the underlying power they pr oduce or sell RECs separately to different customers. Once the

87 “Voluntary” renewable energy purchases, as used here, re fers to renewable energy purchases in addition to the renewable energy required by RPSs. 88 RECs are contractual instruments that convey ownership of the attributes of a unit of energy generated, but do not represent the energy itself. The attri butes conveyed with RECs include information about the generator, such as: type of resource (e.g., wind), plant-level air emissions (if any), geographic location, nameplate capacity (MW), commercial operation date, ownership, and the eligibility for RPS compliance or voluntary market certification.63 RECs are separated from the power generated, the power has no attributes associated with it and is considered generic or “null” power. 89

There are a number of key aspects of RPS design and implementation that affect the quantification, monitorin g, and verification of renewable ener gy generation used to meet a RPS:

 Eligible renewable energy resources . While most RPS-eligible resources in most states
will result in avoided CO 2 emissions from fossil fuel-fired EGUs, some RPS-eligible resources in some states are responsible for greenhouse gas (GHG) emissions or do not
meet common definitions of renewable ener gy (e.g., waste coal, coal-bed methane, and fuel cell operation using fo ssil-fuel feedstocks).

 Existing and new resources . RPS-eligible resources can in clude facilities that began operation prior to the enactment of the RPS and, more importantly, prior to the proposal of the emission guidelines by EPA. 90

 Scope of coverage . In some states a RPS applies to all re tail sales in a state, but in others only a subset of retail sales (e.g., only investor-o wned utility retail sale s) are subject to a
RPS.

 Credit multipliers . Some states provide additional incentives for specific eligible
resources in the form of bonus credit to ward compliance in their RPS accounting framework. For example, these states may fa vor certain resources (e.g., distributed solar PV), or locally-important resources or t echnologies. The MWh produced or renewable energy certificates (RECs) related to MWh production from such facilities may be
counted twice or three times toward compliance with a RPS in such states. However, these credit multipliers and bonuses are not an accurate representation of the amount of

89 These distinctions are typically made as part of utility disclosure to customers about the energy resource mix and emissions of the electricity used by a customer that was supplied from by the distribution utility. “Generic power” or “null power” refers to energy that has no generation attributes or descriptive information ( i.e. , the remaining system mix of power, after assignment of specified power to diff erent utility customers, through power purchase contracts or purchase of generation attributes through RECs). For electricity labeling, disclosure to customers, or other market claims, generic or null power is typically assigned the attr ibutes of the remaining syst em mix of power, after the assignment of attributes as described above. 90 In the preamble, the EPA is proposing that, for an existing state requiremen t, program or measure, a state may apply toward its required emission performance level the emission reductions that existing state programs and measures achieve during the plan peri od due to actions taken after the date on which the emission guidelines are proposed (i.e., from June 2014 onward).64 renewable energy generation that is attributable to a RPS. For the purpose of quantifying the amount of renewable energy produced as a result of a RPS included as a measure in a state plan, only the actual renewable energy generation used to comply with an RPS is
relevant.

 Banking . Some states permit the carryover of re newable energy produced in one year to satisfy RPS requirements in a subsequent year. Accounting for y ear-to-year carryover should be addressed in a st ate plan, in order to determine the renewable energy generation that occurred in a respectiv e reporting year or compliance period.

 Alternative compliance payments (ACP) . Many states allow a compliance alternative which requires obligated entitie s to pay a predetermined fee to the state for each MWh of RPS shortfall. Although these ACP payments ma y be directed to programs to promote the deployment of renewable energy technologies, these payments are not equivalent to renewable energy generation and sh ould not be accounted as such.

 Interstate issues . While treatment of interstate emission effects is discussed in detail in section VII, for quantification, monitori ng, and verification of renewable energy generation under a RPS it is important to note that most states allow use of eligible renewable energy resources loca ted in other states to sati sfy the state RPS requirements. 91

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

91 This may also include international renewable energy re sources, such as Canadian hydroelectric and wind energy resources, which may be used to comply with some state RPSs.65 Build renewable generating facilities In many states, utilities with RPS obliga tions may build, own, and operate their own renewable energy generating facili ties. This pathway is often used by vertically integrated utilities subject to a RPS. For large renewa ble energy generating f acilities, production is measured through a revenue-grade utility mete r as it enters the grid at the point of interconnection. This meter is subject to the same verification standa rds as for any other generator participating in the wholesale market.

Some utilities with RPS obligations also build, own, and operate smaller distributed renewable energy generating faciliti es. Smaller generators, such as residential rooftop solar PV systems of less than 10 kW capacity, often don’ t have discrete metering of their total generation. 92 State RPS requirements may permit these distributed generators to qualify for use in meeting utility RPS obligations based on an engineering estimate of their renewable energy generation output , provided the distributed genera tors are registered with a REC tracking system and the generation output is verified accord ing to tracking system and RPS rules.

Bilateral contract model Under the bilateral contract model, distribut ion utilities with RPS obligations contract with renewable energy generators for supply. Thes e contracts typically sp ecify a delivery amount in MWh over a specified contract period. These s upply contracts may be short- or long-term, may specify generation from certain renewabl e energy EGUs, and may be solicited through an RFP or entered into through negotiation. Quan tification of renewabl e energy generation (in MWh) is accomplished through the use of a reve nue-grade meter that measures the flow of electricity from the generator into the transm ission grid. A contract may also stipulate an adjustment to the metered MWh generation data to account for transmission losses that occur between the point of injection of electricity to the transmission gr id and the point of receipt at a utility transmission or distribut ion system. A renewable energy s upply contract also generally addresses the ownership of the RECs related to the renewable energy generation. Under such a

92 Metered data for these PV systems may only track net electricity supply to or from the grid, representing either surplus generation that is not used to serve on-site electricity load or additional net electricity supplied from the grid if the system does not meet a building’s total electricity load.66 contract, purchase of the RECs should accompany th e purchase of the electricity, in order for the utility to satisfy its RPS ob ligations through the contract. 93

State RPS compliance processes may provide for PUC review of supply contracts, including inspection of meters a nd verification of electricity deliv ery from the generator to the utility distribution network th rough a specified contract pa th (e.g., through evidence of transmission rights held or scheduled). The pur chasing utility also re ports their purchase and delivery of RPS-compliant renewable energy purs uant to the contract to the state agency responsible for RPS enforcement, typically the state PUC or stat e energy office. Verification is accomplished by audit of electricity supply contra cts along with REC tracking system reports of RECs held by the utility and submitted for retirement by the tracking system administrator. Some state RPS require that electricity from qualifyi ng renewable energy sources be produced within the state or a specified grid region, or if outside the state or specified grid region, that electricity be delivered to the state or grid region. In such cases, the verifi cation of electricity delivery is typically done by the REC tracking system admini strator before issuing RECs for the imported energy. Verification can be provided, for exampl e, by demonstration of scheduled delivery through the ISO or RTO serving th e state or region, through demons tration that the seller holds transmission rights for delivery or po ssession of NERC tags for the energy. 94 Bilateral contracts also typically require certification by the seller that attributes related to the sold electricity have not been and will not be otherwise sold, retire d, claimed, represented as part of energy sold elsewhere, or used to satisfy obligations in another jurisdiction.

93 This ensures that multiple parties are not using the sa me MWh of renewable energy generation to comply with their RPS obligations. 94 A NERC Tag, sometimes referred to as an E Tag, is an el ectronic tag that is used to track wholesale electricity transactions that involve the transfer of electricity across or through cont rol areas. NERC Tags allow transmission system operators to track electricity tr ansactions in real time in order to assess any potential reliability implications of scheduled power transactions. NERC Tags define the physical path of an electricity transaction from the point of generation to the point of receipt, and also define the fi nancial path, including all parties to a transaction. All wholesale electricity transactions that will result in the transfer of electricity from one contro l area to another, or that involve transfers through a co ntrol area, must be accompanied by a NERC Tag. Based on a real-time assessment of NERC Tags, system operators can curtail transfers if reliabi lity issues would arise as a result of the transfer. NERC tags are issued through an electronic system in accordan ce with specifications established by the North American Electric Reliability Corporation (NERC).67 REC model Under the REC model, renewable energy genera tors register their EGU with a renewable energy tracking system, which have been establis hed by several regional groupings of states, as
well as a few individual states. 95 The registration process coll ects data about the generator’s attributes: type of resource (e.g., wind), plant-level emissions, geographic location, nameplate capacity (MW), commercial operatio n date, ownership, and the elig ibility for RPS compliance or voluntary market certification. Af ter the generator is register ed, revenue-meter data is transmitted to the tracking system. Meter accuracy is verified for renewable energy generators in the same manner as for any other generator par ticipating in wholesale electricity markets.

Each MWh of renewable energy generation reported to the tracking system by a registered generator results in the issuance of a REC, with its own unique serial number and information about the generator, location, resour ce type, and the month in which the MWh was generated, and the month or quarter in which the certificate was issue d. The renewable energy generator can then sell the rene wable electricity as a bundle (bot h the commodity electricity and the associated REC) or unbundle the RECs from the electricity and sell the two products separately. Other market participants, such as brokers, REC marketers, and load-serving entities also maintain accounts with the tracking system so that REC electronic transactions can be recorded within the tracking system platform. The system tracks each REC through these transactions and ultimately “retires” the REC when the final purchaser designates it for
retirement. Retirement could result from the REC bei ng used to satisfy a state RPS, or as a result of a voluntary buyer retiring the REC to demons trate that they had purchased and used renewable energy to meet their electricity demand.

95 Currently, nine regional renewable energy certificate (REC) tracking systems operate in different regions of North America, including: Texas Re newable Energy Credit Program, run by the Electric Reliability Council of Texas (ERCOT), NEPOOL Generation Information System (GIS), PJM Generation Attribute Tracking System (PJM-GATS), Western Renewable Energy Generation Information System (WREGIS), Midwest Renewable Energy Tracking System (M-RETS), North American Renewabl es Registry (NARR), Mich igan Renewable Energy Certification System (MIRECS), Nevada Tracks Renewable Energy Credits (NVTREC), and North Carolina Renewable Energy Tracking System (NC-RETS). For more information see http://apps3.eere.energy.gov/greenpower/markets/certificates.shtml?page=3

.68 Because the tracking system follows the REC from the point of issuance to retirement, including all interim transactions, it minimi zes the opportunity for renewable energy to be double-counted across, for example, two diffe rent state RPSs, or between two voluntary purchasers. In recent years, the various tracki ng systems have developed interchange standards so that RECs generated within one tracking system can be transferred to and used within another tracking system. 96 Note that not every potential interc hange possibility is currently supported, and that many states have additional eligibility restrictions within their RPS that may limit the use of RECs related to electric generation from distant locations. These include requirements in
some state RPSs for the seller to hold firm tr ansmission rights for deliv ery of the accompanying electricity from the renewable energy generato r into the respective ISO/RTO system or grid system in which a state is located.

Small distributed generators Smaller distributed generators, such as reside ntial rooftop solar PV systems of less than 10 kW capacity, often don’t have discrete me tering of their total generation. State RPS requirements may permit these distributed genera tors to qualify for use in meeting utility RPS obligations based on an engine ering estimate of their renewa ble energy generation output , provided the distributed generators are registered with a REC tr acking system and the generation output is verified according to tracking system and RPS rules. Where such projects are thirdparty owned and operated, the project developer will own the RECs and factor their revenue value into their pricing offered to the site host for electricit y supply. Note also that many utilitysponsored renewable energy incentive programs stipul ate that all RECs resulting from the project must be transferred from the generation owner to the utility as a condition of participation in the incentive program. These RECs can then be used by the utility to meet its RPS obligations, or can be sold to other parties.

96 Additional linkages between tracking systems are bein g established. More information can be found at http://www.narecs.com/res ources/registries/69 State agency role In many states, the PUC or its equivalent is responsible for establis hing the detailed rules and procedures that obligated pa rties must follow to comply with a RPS. The PUC is usually responsible for receipt and review of obligated parties’ periodic compliance reports, imposing compliance penalties as needed, and for evaluati ng the impacts of the program on energy costs, generation diversity, and market operations. The list of eligible resources and MWh requirements are often set through state legisla tion, but these decisions may also be delegated to the PUC for study and promulgation through regu lations of commission orders.

In some states the energy office may be re sponsible for certifyi ng the eligibility of specific generators to participate in the RPS a nd for making siting determinations. In New York, for example, the New York State Energy Resear ch and Development Authority (NYSERDA) is responsible for the centralized pr ocurement of the renewable ener gy needed to meet the RPS for
all of the state’s invest or-owned utilities.

2. Feed-in Tariffs
Feed-in tariffs (FITs) are o ffered by some individual elect ric distribution utilities and some states for renewable energy syst ems that meet eligibility criteria. 97 Under a FIT, the utility offers to purchase specific kinds of electricity (e .g., solar) from sellers at posted prices or under a published pricing formula for a specified period of time. FITs typically have caps on the amount of renewable energy that will be purchased by a utility (in MWh of energy or MW of capacity). FITs may also include customer impact caps for th e tariff as a whole (in total dollars spent or in specified retail rate impacts allowable), and may al so have limits on the size of any participating renewable energy generator from which the utility will purchase electricity through the FIT. FITs may also have pricing formulas that are differe ntiated by resource or that change through time as specified benchmarks are achieved (e.g., MW of re newable energy generating capacity subject to the FIT, amount of electricity purch ased through a FIT as a percentage of utility sales, or retail

97 There are several states that offer FITs, including Ca lifornia, Hawaii, Maine, Oregon, Rhode Island, South Carolina, Vermont and Washington, as well as numerous electric utilities.70 rate impact level reached). Typi cally, the tariff treats all simila rly-situated generators in a
consistent manner.

Quantification of renewable energy genera tion output under a FIT is accomplished through the use of a revenue-grade meter to measure the generator’s injection of electricity into the grid. The utility’s tariff will typically sp ecify the minimum performance characteristics
and/or certifications that a meter must meet in order to be used on its system. Utilities retain the right to inspect and test the calibration of meters c onnected to their systems. As the utility will be paying the generator each month based on the meter reading, it is in the utility’s interest to ensure that the meter is reading pr ecisely and accurately through time.

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

State agency role FITs are usually authorized by state statutes th at specify which utilities must offer a FIT, eligibility criteria (e.g., renewa ble energy resource type, lo cation, project MW generating capacity limits), and sometimes overall program targets (e.g., to tal installed MW of generating capacity subject to the FIT). State statutes may al so specify whether the utilities offering a FIT will receive the RECs related to purchased elect ricity generation output for use in complying with a state RPS, and whether customers recei ving FIT payments may also receive incentives under other utility and stat e programs. Typically state statutes leave implementation details to the PUC (or other utility governing bod y, if applicable, for municipal and cooperative utilities), but may provide guidance on what to consider in se tting FIT payment levels. Based on this statutory authority, PUCs develop detailed rules govern ing implementation, which can include payment levels and contract length. PUCs may direct the affected utilities to de velop standard contracts with all the terms and conditions spelled out, a nd these standard contr acts must be approved by the PUC. As with state RPS, the PUC is respon sible for receipt and review of the utility’s71 periodic status reports, approving changes to a tariff if needed, a nd evaluating the impacts of the tariff on retail prices, generation diversit y, and electricity system operations.

Several FITs are offered by distribution utilit ies not overseen by PUCs, such as municipal
utilities and rural electr ic cooperatives. These utilities have a variety of governance structures ( e.g. , municipal government, cooperative board of di rectors). The utility governing bodies in these situations will be responsible for receipt an d review of the utility’s status reports, taking corrective action if needed, and ev aluating the impacts of the tariff.

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

With a production-based tax incentive, the re newable energy generator might claim a tax credit for each MWh of qualifying renewable en ergy generation within the state. One design consideration for a production-based tax incentive that affects quantification of renewable energy generation output is whether the electricity must be sold to a third party as opposed to being used by the site host. In the former case, a revenue-grade utility meter would be present at the point of interconnection to the electricity grid, which provides measurement of MWh generation output for tax compliance purposes. Site-host use might necessitate the installation of an additional meter within the project site to permit reliable measurement of the renewable energy generator’s output.

State agency role Currently, existing state tax policies are pr imarily under the authority of the state revenue agency. The state revenue agency might have the primary responsibility for establishing the rules72 for production-based tax incentive s, although it may seek advice from state energy agencies regarding the technical aspects of renewable energy generator operation and the behavior of energy markets. The renewable energy generator mi ght claim the tax incentive through the state tax collection process and report MWh generation to claim the tax credit. The revenue agency could receive tax filings from th e owner and operators of renewable energy generators and be responsible for determining whethe r the taxpayer’s claim for tax incentives is supported by the MWh generation evidence. Assuming the state revenue authority re tains its ability to audit the taxpayer’s return, it could veri fy claimed MWh generation.

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

4. Options for Quantification, Monitoring, and Verification of Renewable Energy Measures in State Plans
As summarized in the preamble, and discussed in more depth in this section, utilities and states have conducted ongoing evaluation of re newable energy measures and programs for several decades. These evaluations, which includ e quantification, monitori ng and verification of results, generally rely upon a set of standard practices and procedur es. In addition, states have designed and implemented REC tracking systems to facilitate compliance w ith state RPS. This resource provides the ability to track the locati on and attributes of renewable energy generators, and the electric generation from these generators , as well as the partie s that use RECs for compliance with state RPS. As a result, existing state and utility requirements and processes for quantification, monitori ng, and verification of renewable energy programs and measures generally provide a solid founda tion for minimum requirements and guidance for EM&V for RE measures in state plans that are established by the EPA.

The programs discussed above (RPS, FIT, a nd performance-based tax incentives) all require quantification, monitori ng, and verification of electrici ty generation from renewable energy generators, as well as provisions of othe r key information, to determine eligibility and73 track program activity or compliance with regulatory requirements (if applicable). Quantification of electricity generation is typically through the use of revenue-quality meters, 98 or engineering estimates for small distributed generators. Thes e data are essential to program management, verification of compliance or payments, budget c ontrol, and tracking progress toward goals. For example, PUCs overseeing compliance with st ate RPS receive compliance information from each obligated utility, including retail sales, compliance status based on MWh of electricity generated by eligible utility-owned renewable energy sources, or electricity or RECs purchased from eligible renewable energy generators, which may also consider application of multipliers or alternative compliance payments. 99 PUCs overseeing utility FIT and state agencies overseeing performance-based tax incentives managers receive reports containing MWh of electric generation from qualified electric generators that rece ived payments under either a FIT or tax
incentive. These data are essential for nor mal program management and accountability.

Current state data requirements under RPS, FIT, and production-based tax incentives are tailored to the objectives of these programs and facilitating effectiv e regulatory oversight. Typically, avoiding CO 2 emissions, while considered a releva nt co-benefit, is not a primary objective of these regulations and programs. As a result, additional information and reporting may be necessary to accurately quantify the avoided CO 2 emissions associated with the renewable energy generated through an RPS, FI T, or production-based tax incentive that is included in a state plan.

The following types of information will increase the accuracy and verifiability of avoided
CO 2 emission estimates related to renewable en ergy requirements, programs, and measures included in a state plan. For example, inform ation on the location of the renewable energy generation (e.g., in-by state or within a specified grid region) of the re newable energy generation used for compliance with state requirements and programs would be helpful in determining
avoided CO 2 emissions. Information about the location of electric generators that supplied

98 “Revenue-quality meter” refers to a meter used for billing purposes in wholesale electricity markets, which typically need to meet ISO or RTO precisi on requirements or other specifications. 99 Compliance status will also consider the application of credit multipliers or alternative compliance payments, if relevant under an RPS.74 electricity generation that was imported to a stat e or grid region, will also be important. Timedifferentiated information related to electricity generation is also useful in estimating avoided
CO 2 emissions. In particular time-differentiated data is necessary to estimate the marginal
avoided CO 2 emissions related to electric generation. Such time-differentiated data could be based on metering or engineering estimates fo r a technology type that indicate the typical generation profile for the renewable energy reso urce. This could include time differentiation on an hourly, daily, or seasonal basis. If RECs can be banked and used or RPS compliance at a later time than the year in which the electricity generation related to the REC occurred, information about the quantity and vintage of RECs from prior year(s) generation that is used for RPS compliance will also be useful.75 VI. Reporting and Recordkeeping for E nd-Use Energy Efficiency and Renewable Energy Programs and Measures
As discussed in the preamble, in section VIII.F.5, reporting and recordkeeping for enduse energy efficiency and renewable energy re quirements and programs will be an important component of certain types of sa te plans. If a state plan inco rporates renewable energy and demand-side energy efficiency requirements a nd programs under a rate-based approach or implements a mass-based portfolio approach with such measures, reporting and recordkeeping requirements for an approvable plan would differ from those applicab le to an affected EGU. For example, these requirements may include complian ce reporting by an electr ic distribution utility subject to an end-use energy efficiency resour ce standard (EERS) or renewable portfolio standard (RPS). They may also include reporting by a vertically integrated utility implementing an approved integrated resource plan. In the latter instance, the utility may also be the owner and operator of affected EGUs, but a dditional reporting of quantified effects of renewable energy and demand-side energy efficiency measures under the utility plan would be necessary to demonstrate emissions performance under the state plan. In other instances, a state agency or entity or a private or public third-party entity may be implementing programs and measures that support the deployment of clean ener gy technologies that are incorpor ated in a state plan. In each of these instances, reporting of program complian ce or program outcomes is a necessary part of an approvable plan to demonstr ate performance under the plan.

In the preamble, the EPA seeks comment on appropriate reporting and recordkeeping requirements for entities implementing end-us e energy efficiency and renewable energy programs included as enforceable measures in a stat e plan, or for entities subject to requirements, such as an EERS or RPS, that are included as an enforceable state plan measure. This section provides examples of current reporting and r ecordkeeping under state energy efficiency requirements and programs, such as EERS, RPS, and utility and state deployment programs for energy efficiency and renewable energy. The sect ion then examines the suitability of these reporting and recordkeeping practices as potenti al approaches in an approvable state plan.76 A. Reporting for End-Use Energy Efficiency Programs and Measures
Reporting requirements and time frames (i.e. how often reports are required) for entities implementing energy efficiency programs and measures are key considerations for state plans. In a state-regulatory context with PUC oversight , impact reports are the mechanism by which utilities and other program ad ministrators document energy (MWh) and demand (MW) savings. These reports serve as basis for PUC review of total achieved energy savi ngs relative to program goals or regulatory requirements, as well as for determining financial performance incentives for utilities, where they exist.

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

Impacts reports are typically submitted annually, but in some cases program administrators also provide interim (e.g., quarter ly) reports. This added step can help inform progress towards goals, as well as provide for co rrections in cases wher e evaluated (ex-post) energy savings are not achieving projected or claimed (ex-ante) savings levels.

The information provided below presents a range of common re porting elements and common practices implemented by state PUCs. Thes e reporting elements and practices – which raise important considerations for the reporting of energy-effici ency impacts in state plans –
include:

 State EM&V guidelines, protoc ols, and/or framework ut ilized, where applicable

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

o Short description of the polic ies or programs implemented

o Implementation schedules and timeframes

 Energy-savings impacts reported to PUCs in annual reports:77 o Incremental annual and lifetime MWh savi ngs for reporting (in the case of an energy efficiency program) or compliance ye ars ( in the case of utility compliance with a multi-year Energy Efficiency Resource Standard)

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

 Verification documentation, which shows that in stallation of energy efficiency measures occurred, and the installed measures ar e capable of genera ting energy savings

 EM&V process followed:

o Date and location of on-site facili ty visits and field observations

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

o Information about evaluators:

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

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

 EM&V methods used:

o Deemed savings values - name, date, a nd public location of technical reference manual (TRM) 100 used for deemed savings values

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

 Other documentation:

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

o Whether net or gross energy savings 101 are estimated, definitions used for gross and net savings, and the basis for gro ss to net calculations, if applicable

100 A technical reference manual (TRM) is a document consisting of predetermined savings values, assumptions, methods, and calculation approaches for conducting EM&V of state demand-side energy efficiency programs. Most states with robust efficiency programs rely on a TRM.78 o Avoided transmission and distribution (T &D) impacts assumptions, if applied

The energy savings EM&V reporting elements li sted above vary from state to state in terms of type and level of documentation, and report s are provided in different formats from state to state. This significant vari ation among states in reporting cont ents and format raises several
considerations for states utiliz ing demand-side energy efficiency programs in state plans. One is whether the reporting processes, timeframes, and documentation required by state PUCs, described above, are sufficient and appropriate in the contex t of state plans. Another consideration is whether lead state agencies that oversee energy efficiency programs should be required to certify reported energy efficiency savi ngs impacts on behalf of the state, potentially including certification that the values are appropriate and conser vative, and meet their approval.
A final consideration is whethe r and how energy savings impact reports are made available for public input and comment prior to finalization, recognizing that im pact reports in many states exist but are not easily located or widely acce ssible by the public, nor are they provided in
consistent formats from state to state.

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

Data requirements for reporting may vary ba sed on the design and implementation of a RPS. However, for nearly all state RPS require ments, annual compliance report data is based on

101 Gross savings are the change in energy use and/or energy demand that results directly from program-related actions taken by program participants, regardless of why they participated in the program. Net savings refer to the change in energy use and/or energy demand that is directly attributable to a particular energy efficiency program.79 measurable electric generation results a nd verified through tracking system data. 102 In some states, compliance reports may also include st ate-level projections of renewable energy generation resulting from current or proposed state RPS policies.

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

2. Typical Reporting for Renewa ble Energy Deployment Programs 103
Renewable energy deployment pr ograms involve the provision of a payment or credit for a renewable energy project, or for a quantified am ount of electricity gene ration, in the case of performance-based incentives. Qu alification of eligible projects and payment for qualifying electric generation (or related a ttributes) require reporting of elect ric generation and other project for each specific program. Program administrators use this information to track program progress and report to PUCs or other ove rsight entities. The summary be low addresses typical reporting required for utility-administered programs, as well as programs administered by non-profit entities and state agenci es and authorities.

Reporting for utility administered re newable energy incentive programs
Some utilities offer incentives to electricity consumers to accelerate the deployment of renewable energy technologies, such as rebates, feed-in tariffs, and net metering programs. As mentioned previously, it is easie r to quantify the renewable electri city generation resulting from some programs than it is for others. Utilities ad ministering FITs, for example, will track the

102 Some state RPS require electric utilities to procure a sp ecified amount of renewable energy generating capacity, rather than supply a specified number of MWh or percentage of electricity supply from renewable energy generation to retail customers. 103 In this section, “deployment programs” refers to incentive programs and market transformation programs designed to accelerate the market deploy ment of renewable energy technologies.80 number of customer contracts, resource type , capacity of each cont racted project, MWh generated, and utility ex penditures for that generation under the tariff. In contrast, utilities administering a rebate or loan program are more likely to track the number of customer participants, the type and size of the projects, the cost of the pr ojects, and the amount of rebates paid or loans provided. Measuri ng the electric generation output of these projects may not necessary to evaluate program status.

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

Many of these renewable energy deployment programs are developed as part of requirements by PUCs, and therefore utilities mu st provide reporting on a routine basis to the PUC about program expenditures and outcomes (typi cally quarterly or an nually). These records should be readily accessible to states for es timating the impacts of their renewable energy deployment programs included in a state plan. Ho wever, some utility incentive programs are administered by distribution util ities that are not regulated by a state PUC (e.g., municipal and cooperative electric utilities). In these instances program reporting data may not be readily available to a state, unless sepa rately required by a state if such programs are included in a state plan.81 Renewable energy deployment programs may be designe d and implemented under the auspices of a utility inte grated resource plan (IRP). 104 IRPs document how a utility will meet forecasted annual peak and energy demand over a defined period of time through a combination of supply-side and demand-side resources. IRPs are ty pically mandated thr ough state legislation or PUC orders and may include renewable energy generation planning, particularly as it relates to compliance with in-state requirements. IRPs are typically submitted on an annual basis to a state utility commission and/or other state entity, and address a multi-year period (e.g., 10 years is a typical period for an IRP). IRPs are a good resource for tracking and forecasting utility renewable energy developments within a state. Though they may not include renewable energy production data, data included in IRPs may help states project rene wable energy generation trends in subsequent years, and are a good re source for the developmen t of state plans.

Reporting for renewable energy incentive progr ams administered by non-profit or state entities State renewable energy financial incentives ar e typically administered by a PUC, state revenue agency, other state agency (e.g., state en ergy office), or a private non-profit or for-profit entity contracted by a state agency. These progr ams may include an administrative process for pre-qualification, which in some instances may be competitive (e.g., performance-based contracts) or available on a first-come, first- serve basis (e.g., capped pr oduction tax incentive). Applications to incentive programs are good sources of data, and program administrators usually compile data from approved applications to trac k program status. Additional reporting data is also typically required to receiv e the incentive. For example, a production-based tax incentive is calculated based on the amount of electricity ge nerated by a renewable energy installation, which may be tracked and verified through utility or third-party metering protocols. These reports, which are currently used for internal reporting for budgetary control and performance evaluation, and to track other performance metrics for regul ar public program reporting, could form much of the basis for reporting under state plans for such measures.

104 IRPs are typically required in states with vertically inte grated electric utilities, but are less common in states that have deregulated their electricity sectors and introduced comp etition for the supply of electricity to retail customers.82 3. Considerations for Reporting Requirem ents for Renewable Energy Measures in State Plans
State renewable energy requirements, such as RPS and FITs, and incentive programs typically include robust reporting requirements. For nearly all state RPS requirements, annual compliance report data is based on measureable electric generation, using revenue-quality meters, and verified through tracking system data. 105 Other requirements and programs that provide performance-based payments and in centives, such as FITs, net metering, and performance-based tax incentives, also requi re reporting of metered generation output. 106 State and utility incentive programs where payment of incentives is not based on electric generation may not currently be sufficient for repor ting under a state plan . Additional reporting requirements may be necessary if these programs ar e included as enforceable measures in a state plan.

In addition to the reporting states curren tly require for renewable energy requirements and programs, supplemental reporting information or adjustments may be necessary for state plans to demonstrate the avoided CO 2 emissions associated with these requirements, programs, and measures. States may need to require additi onal reporting detail, su ch as the location of renewable energy generating units that supplied output used to comply with a state RPS. Additional reporting detail about when renewable en ergy was generated may also be valuable for estimating the avoided CO 2 emissions from renewable energy generation, especially if a marginal avoided emission rate approach is used. This includes re porting of the typical generating profile of a renewable energy genera ting unit, group of units, or renewable energy resource type. 107 For distributed renewable energy resour ces, reporting of the MW capacity of generating systems that are installed as a resu lt of state requirements or programs during a reporting period would also be us eful for estimating avoided CO 2 emissions. These distributed

105 Small distributed renewable energy systems, such as th ose below 10 kW in capacity, are often allowed to use engineering estimates to determine annual output. 106 Some of these programs, such as net metering, may also require supplemental reporting in order to track total generation that avoids CO 2 emissions. In many instances, net metering programs only track the net electricity supplied to a customer or supplied to the grid by the renewable energy system, rather than total generation output. 107 This might include information about the seasonal or daily generating profile of the generating unit or renewable energy resource type.83 resources, since they are located “behind” the ut ility meter at a customer location, have a similar effect in reducing the demand for electricity supp lied from the grid as en d-use energy efficiency

measures.

Example reporting requirements that provide sufficient data for estimating the avoided
CO 2 emissions from renewable energy requirement s and programs might include the following:

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

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

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

 For REC data, information including the following generator attributes: type of resource (e.g., wind), plant-level emissions, geogra phic location, nameplate capacity (MW), commercial operation date, ownership, and the eligibility for RPS compliance or voluntary market certification84 VII. Treatment of Interstate Emission Effects
Programs and measures in a state plan, such as RE and demand-side EE measures, may affect the emission performance of the interconnect ed electricity system beyond a state border. In addition, many state measures allow for actions in neighboring states to meet the in-state requirement, or explicitly address CO 2 emissions in neighboring stat es. For example, many state renewable portfolio standards allow for gene ration by qualifying renewable energy sources in other states to count toward meeting the state po rtfolio requirement. Some states also apply CO 2 emission requirements related to the generati on of power purchased by regulated utilities, including power imported from out of state.

As discussed in the preamble to the proposal , in section VIII.F.6, the EPA recognizes the complexity of accounting for interstate effects as sociated with measures in a state plan in a consistent manner, to minimize the likelihood of double counting. The EPA also realizes that
interstate effects on CO 2 emissions from affected EGUs could be attributed in different ways in the context of an approvable state plan. This se ction discusses in more detail the options and
alternatives for treatment of interstate CO 2 emission effects presented in the preamble. These options and alternatives coul d be applied to both projecti ons of plan performance and demonstration of achieved emission performance under a plan. These opti ons and alternatives may not be mutually exclusive – in some inst ances states could appl y different approaches, without introducing the potential for double counti ng of emission effects. One option presented could lead to double counting of em ission effects, and we highlight these aspects of this option in
the discussion below.

In general, the options and alte rnatives address different possi ble state plan scenarios, and consider the range of interstate approaches that states are currently using to implement electricity sector policies, such as multi-state emissi on budget trading programs and regional renewable energy certificate markets for state RPSs. Th e options and alternatives reflect possible accounting approaches for interstate emission effects under CAA section 111(d) that could potentially align with these curr ent state programs and measures that we anticipate states may want to include in a state plan.85 A. Background
Electricity flows across state lines. Often electricity load centers (i.e., areas of high electricity demand) in one state are supplied in part by generating units in another state. As a result, some states are net exporters or importe rs of electricity on an annual basis. Reducing electricity load through improved e nd-use energy efficiency (e.g., th rough state energy efficiency programs) or deploying new re newable energy electric generati ng capacity (e.g., through a state RPS) therefore can result in CO 2 emission effects that are real ized outside the state that implements the regulation or program that produ ces the effects. Reducin g electricity demand or increasing available electric generating capacity also often impacts the economic dispatch curve and locational economics that are used to dispatch EGUs on a regional basis. As a result, state end-use energy efficiency and renewable energy regulations and program s often have regional effects on electricity ge neration and avoided CO 2 emissions. In addition, many state regulations explicitly address CO 2 emissions in neighboring states, or al low for actions in neighboring states to meet an in-state regulatory requirement. For example, many state RPS allow for generation in
other states to count toward meeti ng a utility portfolio requirement.

End-use energy efficiency actions reduce electricity load, and ultimately impact electric generation. In some instances improving end- use energy efficiency will reduce electric generation nearby a load center (e.g., in the case of a load pocket with limited access to electricity transmission capacity). In such cases, it may be feasible to directly link in-state enduse energy efficiency programs and measures to avoided CO 2 emissions from specific in-state EGUs. More often, reduction of electricity load will impact EGU dispatch across a regional generation control area, based on factors such as power plant economics and electricity transmission capability, and could also impact flows between control areas. 108 In these cases, state end-use energy efficiency programs and measur es will affect electric ity generation in the state that reduces load, as well as in neighboring states.

108 Often these dispatch economics differ by location, base d on electricity demand, transmission constraints, and generation economics of individual pow er plants necessary for meeting de mand (e.g., in competitive wholesale markets, these factors are represente d through locational marginal prices (LMPs), which determine dispatch).86 State RPS regulations also impact electricit y generation at a regiona l level. Over time,
state RPSs result in the introducti on of new, incremental renewabl e energy generating capacity to regional generation control areas, which affects E GU dispatch at the regional level. State RPSs are typically applied to electric distribution utilities as a percen tage of sales (e.g., a specified percentage of delivered electricity must come from qualifying renewable energy sources). Many state RPSs do not require the qualifying renewa ble energy electric generation to take place within the state, or even be de livered into the state, but instea d require that the renewable energy be supplied within (or delivered into) the ISO/RTO in which th e state resides. Often, utility compliance with state RPS is through the submi ssion of renewable energy credits (RECs), which represent the attributes of renewable energy gene ration but not the actual electricity generated. As a result, in many cases the intent of the state policy is often to affect the characteristics of the regional electric generation mix, rather than the state generation mix.

The approach to implementing an RPS may diffe r in vertically integrated, cost-of-service
states where the distribution ut ility also owns electric gene rating capacity and dispatches generation resources within its se rvice territory. In such cases, th e RPS may require a utility to increase its renewable energy generating capacity , rather than supplying a percentage of the electricity it delivers to retail customers from renewable energy sources to meet load. A number
of state RPS also include “carve-outs” or “set -asides” where a portion of the renewable energy supplied to retail customers must come from re newable energy generating capacity located inside
the state. Most of these carve-outs are for di stributed solar photovolta ic generating capacity, which are located at the point of customer end-use (e.g., rooftop mounted solar PV on residential homes and commercial buildings). 109 Distributed solar PV capacity of ten provides benefits to the electric distribution system by improving distributi on system reliability and avoiding the need for distribution system capacity upgrades. This type of distributed renewa ble energy generation has effects similar to end-use energy efficiency, as it reduces the customer electricity load that must

109 A number of RPS also have carve-outs for other renewa ble energy resources, typically those where there is a significant renewable energy resource lo cated in the state. An example is car ve-outs for offshore wind energy in coastal states.87 be met through large EGUs connected to the grid. 110 Regardless of the approach taken, state RPS regulations typically have impacts on EGU dispatch, and related avoided CO 2 emissions, beyond
the state border.

B. Summary of Possible Approaches for Trea tment of Interstate Emission Effects
As discussed in the preamble, the EPA is pr oposing a set of approaches for addressinginterstate emission effects that result from the implementation of state plans that incorporate enduse energy efficiency and renewable energy pr ograms. The preamble also solicits comment on additional alternatives. The proposed a pproaches in the preamble include:

 For EE programs and measures:

o A state may take into account in its plan only those CO 2 emission reductions occurring in the state that result from demand-side ener gy efficiency programs and measures implemented in the state.

o States participating in multi-state plans w ould have the flexibility to distribute the
CO 2 emission reductions among states in the multi-state area.

o States could jointly demonstrate CO 2 emission performance by affected EGUs through a multi-state plan in a contiguous electric grid region, in which case attribution among states of emission reductions from dema nd-side energy efficiency measures would not be necessary.

 For RE programs and measures:

o Consistent with existing state RPS policies, a state could take into account all of the
CO 2 emision reductions from renewable en ergy programs and measures implemented by the state, whether they occur in the state and/or in other states.

o States participating in multi-state plans w ould have the flexibility to distribute the
CO 2 emission reductions among states in the multi-state area.

o States could jointly demonstrate CO 2 emission performance by affected EGUs through a multi-state plan in a contiguous electric grid region, in which case

110 Distributed solar PV is also typically peak coincident, meaning it provides its greatest electric generation output at times of peak system electricity demand. At many time s of the day and year, solar PV systems supply electricity back to the grid, when PV system out put exceeds building electricity demand.88 attribution among states of emission reductions from renewable energy measures would not be necessary

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

 State may only claim the impact of a measure in reducing in-state EGU CO 2 emissions For plan measures such as end-use energy e fficiency and renewable energy regulations and programs, estimating the avoided CO 2 emissions from in-state versus out-of-state EGUs could be addressed through modeling, othe r analytical tools, or proxy metrics (e.g., net import factor).

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

 Cooperative multi-state accounting Multiple states are allowed to mutually ag ree to how they will distribute avoided CO 2 emissions from state plan measures (e.g., end-use energy efficien cy and renewable energy regulations or programs, or an em ission limit that addresses out-of-state generation) across their resp ective EGU fleets. Avoided CO 2 emissions are distributed among states by agreed formula they derive – an accounting “credit” in one state for
out-of-state avoided CO 2 emissions is complemented by an accounting “debit” in
the other state where the avoided CO 2 emissions occurred (i.e., through an increase in reported CO 2 emissions or CO 2 emission rate).

 Tradable regional EE/RE credit market
This is a variant of the multi-state accounti ng approach, which could be applicable where multiple states in a region are implementing ra te-based state plans. Under this approach, state end-use energy efficiency and renewable energy regulations and programs that meet89 EM&V guidelines or requirements are allowe d to generate credits, based on MWh of energy savings or renewable energy generati on. These credits, which are denoted in
avoided tons of CO 2 or avoided MWh, could be used by affected EGUs toward demonstration of compliance with state rate-based CO 2 emission limits within a designated region. EE/RE credit issuance coul d be on a project and/or program basis. State accounting for interstate emission eff ects would be addresse d through the credit market and determined based on credits held by affected EGUs.

 Regional demonstration by states of EGU emission performance States are allowed to regionally demonstrat e emission performance by affected EGUs. Stets jointly demonstrate emission performan ce for affected EGUs, in terms of total CO 2 emissions (under a mass-based multi-state plan) or weighted average CO 2 emission rate (under a rate-based multi-state plan).

 The EPA jointly assesses regional performance achieved in aggregate by all individual state plans in a grid region
The EPA assesses interstate e ffects on a regional basis duri ng the plan review process. The EPA requires states to agree to an interstate attribution process only if necessary (i.e., if regional performance falls short of the a ggregated identified pe rformance levels for affected EGUs in individual state plans). Alte rnatively, the EPA requires plan revisions if regional performance falls short of the aggr egated regional performance level (i.e., the aggregated identified performance levels for a ffected EGUs in indi vidual state plans).

Table 3 includes illustrative ex amples of the application of some of the different approaches for addressing interstate emission e ffects summarized above. The table explains how these approaches might be applied in different state plan contexts. The illustrative examples consider the range of approaches states are cu rrently using to implement electricity sector policies, all of which in terstate effects, such as multi-state emission budget trading programs, regional renewable energy certificate markets us ed for state RPS compliance, and end-use energy efficiency programs.90 Table 3. Applied Examples of Intersate Emission Effects A ttribution Approaches

1. State May Claim the Im pact of a Measure on CO 2 Emissions from Affected EGUs Within its Borders
Under this approach, the effect of a state m easure could be applied to help demonstrate emission performance by affected EGUs in the state if it has the effect of avoiding CO 2 emissions from those in-state EGUs. This could be done regardless of whether the action taken to implement the state measure occurs within or ou tside the state. For example, renewable energy generation that occurs outside the state as a result of a state renewable portfolio standard obligation would still be a valid state plan action, provided th e out-of-state renewable energy generation has the e ffect of avoiding CO 2 emissions from affected EGUs inside the state. As another example, for a state that is a net impor ter of electricity, improvements in demand-side EE and related reductions in electricity demand may reduce the need for generation from both
affected in-state and out-of-state EGUs. These el ectricity demand reductions could be applied to help demonstrate emission performance by aff ected EGUs in the state if the reduction in electricity demand has the effect of avoiding CO 2 emissions from those in-state EGUs.91 Estimating the effect of RE and demand-side EE measures on in-state versus out-of-state
EGU CO 2 emissions could be addressed through m odeling, other analytical tools, or proxy metrics such as a net import factor.

Modeling could be used to assess the inters tate effects of state measures on EGU CO 2 emissions, both for projections of emissi on performance under the plan and ex post demonstration of performance achieved. Under th is approach, both projected plan performance and performance achieved is asse ssed on a state-by-state basis.

Ex ante projections of plan performance To project the effect of EE/RE measures under a state plan, a dispatch model would be applied to a grid region to estimate the marginal or average avoided CO 2 emissions impact of the plan measures on a state-by-state basis within the region. To the extent that a state’s EE/RE measures were projected to avoid CO 2 emissions from its own in-state EGUs, these effects could be applied to meet the required level of CO 2 emission performance for affected EGUs in the state plan. (See section IV.C of this TSD for a full di scussion of using a dispatch modeling approach to projected avoided CO 2 emissions that will be achieved through a plan.)

Ex post demonstration of plan performance To assess the state-by-state avoided CO 2 emissions that result from the implementation of a plan, a dispatch model would also be applied to a grid region, on a retrospective “look-back” basis. This modeling woul d assess the avoided CO 2 emissions resulting from reported MWh of energy savings and MWh of reported renewable en ergy generation, as a result of implementation of EE/RE measures in the plan. Under a rate-based plan approac h, modeled estimates of avoided
CO 2 emissions, based on reported EE savings and RE generation, could be applied through an administrative adjustment by the state program admi nistrator or through the issuance of tradable EE/RE credits within the state. For ex post de monstration under a mass-based plan approach, performance would be determined based on reported stack CO 2 emissions from affected EGUs— no further analysis would be necessary. (See sect ion IV.C of this TSD for a full discussion of using a modeling look-back appr oach to estimate avoided CO 2 emissions.)92 Use of simplified proxy metrics to apportion effects among states Simplified metrics, such as a net electricity im port or export factor, might also be applied to assess the impact of state actions in avoiding CO 2 emissions from in-state affected EGUs. For example, in a state that imports 30% of electricity on average dur ing a year, energy savings from EE measures might be multiplied by a factor of 0.70. 111 Avoided CO 2 emissions might then be calculated by multiplying this adjusted energy savings number by the average or marginal CO 2 emission rate for affected EGUs in the state. Th is type of approach could be employed in both projections of plan performance and ex post de monstrations of performance. However, this method would be subject to uncertainty, as elect ricity net imports may vary significantly on an annual basis, due to changes in system dispatc h. (See section IV.C of th is TSD for a discussion of dispatch dynamics that affect avoided CO 2 emissions.)

This approach would avoid double counting of emission effects of state measures among states. However, it could reduce incentives for st ates to employ measures that have a systemwide, regional effect in reducing EGU CO 2 emissions. In effect, because an adjustment factor would be applied to energy savi ngs under this approach, a net importer state would need to achieve greater energy savings through end-use en ergy efficiency requirements and programs to
achieve a ton of avoided CO 2 emissions under its plan than a st ate that is not a net importer.

2. State that Implements the Measure Claims the Emission Effects
Under this approach, the state that implement s the measure (e.g., an EERS or RPS, or an
emission limit that addresses the at tributes of purchased electricity from out-of-state generation)
claims the avoided CO 2 emissions, regardless of where they occur.

If the avoided CO 2 emissions from state plan measures at the regional level are greater
than avoided emissions from affected EGUs within the state, these interstate effects would need to be accounted for and applied to affected EGUs within the state. This could be achieved through an administrative adjustment by the state, or through a tradable credit system that is
limited to affected EGUs in the state.

111 In this instance, it would be assumed that 30% of the reduction in electricity load resulted in avoided CO 2 emissions from out-of-state EGUs that serv e electricity load in the importing state.93 Under an administrative adjust ment approach, out-of-state avoided emissions would be applied to the in-state EGU fleet by the state program administrator when determining average
fleet CO 2 emission rate or tonnage CO 2 emissions. Under a tradable credit approach, credits
would be issued for all avoided CO 2 emissions resulting from applicable state plan measures, without regard to where the avoided emissions occurred. Since the tradab le credit system would be limited to affected EGUs in the state, use of the credits by affected EGUs when demonstrating compliance with a rate-based emission lim its would functionally apply the avoided CO 2 emissions to the state that was responsible for the measure.

This approach provides a clear policy signal and incentives that reward state actions that
reduce EGU CO 2 emissions on a system-wide, regional ba sis. However, this approach, absent cooperative accounting among states in a grid region, as described below, will likely lead to double counting of emission impacts among states , which could reduce the overall emissions reductions achieved through state plans on a national basis under CAA section 111(d). We also note below that other approaches could also provide incentives for a regional, system-based approach to achieving CO 2 emissions reductions from aff ected EGUs, without raising the prospect of double counting of emission effects among state.

3. Cooperative Multi-State Accounting of Interstate Emission Effects
Under this approach, multiple states would be allowed to mutually agree on how they
will distribute avoided CO 2 emissions from RE and demand-side EE measures across their respective EGU fleets. Avoided CO 2 emissions would be distributed among states according to a formula that they specify. Based on this agreed fo rmula, each state would adjust its demonstrated emission performance by affected EGUs accordingl y. In effect, a “credit” for out-of-state emission effects in one state would be compleme nted by a “debit” for such effects in another

state.

This approach provides states with discretion about how to attribute interstate effects, based on their situations and policy preferences in a grid region. Importantly, this approach also avoids the potential for double c ounting of interstate emission effects among states. However,94 this approach is premised on regional collabor ation among all states in a grid region. Not all states in a grid region may be willing to coopera te in implementing such an accounting approach.

4. Tradable Regional EE/RE Credit Market
Under this approach, RE and demand-side EE ac tions that meet appl icable quantification, monitoring, and verification requirem ents would be issued tradable credits that could be applied by affected EGUs to their reported CO 2 emission rates when demonstrating compliance with an emission limitation in a state plan. 112 A credit issued in one state could be used by an affected EGU in another state toward meeting its respective rate limit. 113

A regional credit market would be premis ed on agreement among states that credits issued throughout a region could be used in multiple states. The distribution among different states of usage of the credits would be determin ed by economic factors such as credit prices and EGU marginal emissions abatement costs. In eff ect, accounting of interstate effects would be allocated among states based on prices in the credit market.

This approach is applicable if multiple stat es are implementing rate-based state plans. Where states were implementing a mix of rate-based and mass-based state plans in a shared grid region, this approach would lead to double counting of emission e ffects among plans, unless this market-based EE/RE credit approach was also coupled with a cooperative accounting agreement among states. In this latter instance, for st ates implementing a mass-based approach, where
credits for avoided CO 2 emissions are transferred to affected EGUs located in another state for compliance purposes, the state from which credits were transferred would adjust its reported CO 2 mass emission from affected EGUs when de monstrating achievement of the required CO 2 emission performance level by affected EGUs identified in the state plan. 114

112 These credits might be denoted in avoided CO 2 emissions or MWh of electricity savings or electricity generation, as described above in Section VI.E.3., incorporating RE and demand-side EE measures under a rate-based approach. Depending on a state’s circumstances an d its plan approach, these tradable credits might represent a new instrument created for use under a state plan, or a state mi ght use an existing instrument, such as RECs. 113 Credits could be issued on a program or project basis. The types of measures for which credits could be issued and the basis for issuing credits would be an enforceable element of a state plan. 114 Note that in this example, state reporting of overall achieved CO 2 emission performance by affected EGUs under a state plan is distinct from demonstration of compliance by affected EGUs subject to a mass-based CO 295 5. Regional Demonstration by St ates of Emission Performance
Under this approach, multiple states would demonstrate CO 2 emission performance by affected EGUs on a regional basis. 115 This could allow states in a contiguous grid region to implement a portfolio of RE and demand-side EE measures without the need for state-by-state
attribution of avoided CO 2 emissions. Instead, states would asse ss the impact of state measures in avoiding CO 2 emissions from the fleet of affected EGUs in the multi-state region.

This approach creates incentives for the impl ementation of system-based approaches that collaboratively reduce EGU CO 2 emissions on a regional basis, wh ile also avoiding the need to
attribute interstate emission e ffects among states. However, regi onal collaboration will require more time for the development of multi-state pl ans. This approach is also premised on the willingness of all states in a grid region to par ticipate in the development and implementation of a multi-state plan. Some states in a grid regi on may be unwilling to collaborate regionally.

6. Assessment of Interstate Effects by the EPA in the Course of State Plan Review
Under this approach, the EPA would evaluate interstate effects on a regional basis during the plan review process. 116 The EPA would assess the emissions performance of affected EGUs on a regional basis, consideri ng the measures contained in the group of state plans for a respective grid region. Under this approach, the EP A might conduct an analys is that considers all of the state program measures together on a co mbined basis and evaluates projected emissions performance achieved by affected EGUs in the region.

To the extent that all affected EGUs in a re gion are projected to ach ieve the required level of performance represented in i ndividual state plans, or are proj ected to achieve an aggregate

emission limit. For EGU compliance, no adjustment would be made to CO 2 emissions reported by affected EGUs subject to the mass-based emission limit, even though emissions from these a ffected EGUs may have been reduced as a result of EE/RE regulations and programs implemented in a neighboring state. In this case, the state would adjust the overall CO 2 emissions from the affected fleet to account for the “export” of avoided CO 2 emission credits, in order to demonstrate the overall level of CO 2 emission performance that is assume d to have been achieved by the affected EGU fleet under the plan. 115 This approach could be applied for CO 2 emission performance on e ither a rate or mass basis. 116 For example, this assessment could be for a multi-state region that generally aligns with a contiguous grid region.96 regional level of performance consistent with th e level of required perf ormance included in all state plans in the region, instan ces of double counting of interstate effects among states are less important. The EPA could indicate as part of plan approval that it wi ll review actual emission performance achieved by affected EGUs duri ng the plan period on a regional basis.97 VIII. Appendix
Survey of Existing State Policies and Programs that Reduce Power Sector CO 2 Emissions

I. Overview of State Climate and Energy Po licies and Programs that Reduce Power Sector CO 2 Emissions
Across the nation, many states and regions have shown strong leader ship in creating and implementing policies, programs, and measures that reduce CO 2 emissions from the power sector, while achieving other economic, environmen tal, and energy benefits. These policies and programs can serve as a strong founda tion as states develop plans to meet state goals for affected electric generating units (EGUs) under the proposed emission guidelines.
This document provides a surv ey of many of these activities. Policies and programs range from market-based programs and CO 2 emission performance sta ndards that require CO 2 emission reductions from EGUs, to others, such as renewable portfolio standards (RPS) and energy efficiency resource standards (EERS), that reduce CO 2 emissions by altering the mix of energy supply and reducing energy demand. States have developed their policies and programs with stakeholder input and tail ored them to their own circum stances and priorities. Their leadership and experiences provided the EPA with important information about best practices to build upon in the proposed rule.
States vary in their regulatory structures, electricity generation a nd usage patterns, while geography affects factors such as the availability of fuels, tr ansmission networks, and seasonal energy demand. States have tailored their clim ate and energy policies and programs accordingly. For example, in some states, util ities are vertically integrated, meaning that the one company is responsible for electricity generation, transm ission, and distributi on over a given service territory. State public utili ty regulators have authority over th ese utilities. In other states, where the electric power industry has be en restructured, ownership of electric generation assets has been decoupled from transmission and distribution assets, and retail customers have their choice of electricity suppliers. In states where restruct uring is active (see Figure 1), state public utility regulators do not have authority to regulate the companies respons ible for electricity generation, only the electricity distribution utilities. States rely upon and have access to different fuel types and have a variety of EGU types within state borders . States are part of regional electricity grids that usually do not align with state borders. Electricity is imported and exported by utilities across states throughout each regional grid.98 Figure 1: Status of Electric ity Restructuring by State

Source: “Status of Restructuring by State”, U. S. Energy Information Administration, accessed March 19, 2014, http://www.eia.gov/electricity/policies/ restructuring/restructure_elect.html

.
States also have different economic consid erations, drivers, and approaches when implementing climate change, energy efficienc y, and renewable energy policies, programs, and measures. State actions may be motivated by state environmental, energy and/or economic concerns. For example, ten states have passe d legislation requiring GHG emission reductions and are using a combination of emission limits, performance standards, energy efficiency and renewable energy measures to achieve these requirements. 117 Other state measures are motivated by public utility commission (PUC) requirements to achieve all cost-effective end-use energy efficiency improvements or by renewable energy generation requirements. Policies, programs, and measures vary from state to state in thei r implementation levels and administration. Some are administered by state agencies and others by utilities, with varying mechanisms for ensuring compliance with applicable requirements.
This appendix is not exhaustive and is only intended to provide background information about strategies states have used to achieve CO 2 emission reductions in the power sector, advance end-use energy efficiency, and increase the use of renewable energy resources. For example, states may also consider measures that states have used to support other low- or zeroemitting generating technologies beyond what is addressed here. State policies and programs

117 States include California, Connecticut, Hawaii, Main e, Maryland, Massachusetts, Minnesota, New Jersey, Oregon, and Washington. Targets are typically defined on a 1990 base year, aiming to achieve reductions of between 0 and 10 percent by 2020, although Maryland and Minnesota have chosen targets of 25 percent below 2006 levels by 2020, and 15 percent below 2005 levels by 2015 respectively.99 included in this appendix are not necessarily approvabl e in the context of a CAA section 111(d) state plan. In order to be a pprovable, state requirements, progr ams, and measures included in a state plan must meet criteria laid out in the proposed emission guidelines.

II. Existing State and Utility Policies, Pr ograms, and Measures that Affect EGU CO 2 Emissions
Some state and utility polic ies, programs, and measures directly target EGU CO 2 emissions by creating specific limits or standards for CO 2 emissions in the power sector. Other policies and programs, such as those that adva nce deployment of end-use energy efficiency and renewable energy, are designed to reduce energy demand or promote an increase of supply from low- or non-GHG emitting generatin g sources, which reduces CO 2 emissions from fossil fuelfired EGUs. Many states that are aggressively pursuing climate change mitigation look to enduse energy efficiency and renewable energy fi rst, recognizing the pot ential for low-cost GHG emissions reductions and the econom ic, reliability, and fuel divers ity benefits these resources provide.
For example, according to California, “the in tegrated nature of the grid means that policies which displace the need for fossil gene ration can often cut emissions from covered sources more deeply, and more cost-effectively th an can engineering change s at the plants alone, though these source-level control efforts are a vital starting point.” 118 In working to meet its statewide goal of reducing GHG emissions to 1990 levels by 2020 and 80 percent below 1990 levels by 2050, the California calls its energy efficiency standards “the bedrock upon which climate policies are built” and uses renewable energy to fill any remaining energy needs.” 119 Compared to the costs of other climate policies, California finds that “en ergy efficiency provides substantial emissions reductions and should be an essential elem ent of the BSER CO 2 reduction target.” 120 As another example, Connecticut has a law that requires th e state to reduce GHG emissions to 10 percent below 1990 emissions le vels by 2020 and 80 percent from 2001 levels by 2050. 121 Connecticut considers energy efficiency investments, expanded renewable energy generation, and participation in the Regional Greenhouse Gas In itiative (RGGI) among its top ten strategies to reduce GHG emissions when considering cost-effec tiveness and GHG emission reduction potential. 122

118 Mary Nichols (Chairman of California Air Resources Board), letter to EPA Administrator Gina McCarthy, December 27, 2013. 119 Ibid. 120 Ibid. 121 Environment Northeast, Connecticut House Bill No. 5600: An Act Concerning Connecticut Global Warming Solutions , accessed March 19, 2014, http://www.envne.org/public/resour ces/pdf/CT_Global_Warming_Bill_Summary.pdf

. 122 States’ Section 111(d) Implementation Group Input to EPA on Carbon Pollution Standards for Existing Power Plants, Joint comments from 15 states on Carbon Pollutio n Standards for Existing Powe r Plants sent to USEPA Administrator McCarthy on December 16, 2013. Signatories include: Mary D. Nichols, Chairman of California Air Resources Board, Robert B. Weisenmiller, California En ergy Commission, Michael R. Peevey, Chair of California Public Utilities Commission, Larry Wolk, MD, MSPH, Execu tive Director and Chief Me dical Offices of Colorado Department of Public Health and Environment, Dan Esty, Commissioner of Connecticut Department of Environmental Protection, Collin O’Mara, Secretary of Delaware Department of Natural Resources and100 Beyond these specific policies and programs, some states implement utility planning requirements that can affect emi ssions both directly and indirectl y. This section describes a range of existing state actions that fall into all of these categories.

a. Actions That Directly Reduce EGU CO 2 Emissions
Existing state actions that directly reduce EGU CO 2 emissions tend to fall in one of two categories: market-based emission limits or emission performance standards.

i. Market-based Emission Limits
Description
An emissions budget trading program is a ma rket-based tool for reducing pollution. The basic approach, which involves th e allocation and trade of a limited number of environmental permits, has been used across environmental media, including air pollution control, clean water regulation, and land-use applications.
As shown in Figure 2 below, ten states have implemented emissions budget trading programs addressing CO 2 and other GHG emissions. These in clude California’s emission budget trading program and the nine northeast and mid- Atlantic states partic ipating in the Regional Greenhouse Gas Initiative (RGGI), consisting of Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, Ne w York, Rhode Island, and Vermont. 123,124

Environmental Control, Dallas Winslow, Chairman of Dela ware Public Service Commission, Douglas Scott, Chair of Illinois Commerce Commission, Da vid Littell, Commissioner of Maine Public Utilities Commission, Robert M. Summers, Secretary of Maryland De partment of the Environment, Kelly Speakes-Backman, Commissioner of Maryland Public Service Commission, Ken Kimmell, Commissioner of Massachusetts Department of Environmental Protection, Mark Sylvia, Commissioner of Massachusetts Department of Energy resources, John Linc Stine, Commissioner of Minnesota Pollution Control Agency, Mike Rothman, Commissioner of Minnesota Department of Commerce, Thomas S. Burack, Commissioner of New Hampshire Department of Environmental Service, Joseph Martens, Commissioner of New York State Department of Environmental Conservation, Audrey Zibelman, Chief of New York State Public Commission, Dick Pederson, Director Oregon department of Environmental Quality, Janet Coit, Director of Rhode Island Department of Environmental Management, Marion Gold, Commissioner of Rhode Island Office of Energy resources, Deborah Markowitz, Secretary of Vermont Agency of Natural Resources, James Volz, Chairman of Ve rmont Public Service Board, Maia Bellon, Director of Washington State Department of Ecology. Letter hereafter referred to as “State enviro nmental agency leaders from CA, CO, DE, IL, ME, MD, MA, MN, NH, NY, OR, RI, VT, WA, Open Letter to the EPA Administrator Gina McCarthy on Emission Standards Under Clean Air Act Section 111(d), December 16, 2013.” 123 “RGGI Homepage”, Regional Greenhouse Gas Initiative, accessed March 19, 2014, at http://www.rggi.org/

. 124 “Cap and Trade Program”, California Air Resources Board, accessed March 19, 2014 http://www.arb.ca.gov/cc/capandtrade/capandtrade.htm

.101 Figure 2: States with Active Greenhous e Gas Emission Budget Trading Programs

Policy Mechanics
Design
An emissions budget trading program establis hes an aggregate limit on pollution through an emissions cap that specifies the total allowable emissions over a specified time period for all of the emission sources subject to the program. To comply with the emission limitation, each emission source must surrender emission allowances equal to its reported em issions at the end of each compliance period.
Allowances may be traded among both regu lated and non-regulated parties, creating a market for emission allowances. In turn, the a llowance market establishes a price signal for emissions (a market price for emitting a unit of pollution), which triggers broad economic incentives for reducing emissions across the co vered sector(s) and encourages innovation in developing emission control strategies and new pollution control technologies.
There are several key design elements that may vary from program to program:

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

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

 Initial emission budget (i.e., the aggregate em ission limitation for covered emission sources) and emissions reduction schedule102  Flexibility provisions, in addi tion to ability to trade emi ssion allowances, including:

o Multi-year compliance periods

o Allowance banking

o Offsets (e.g., project-based emissions re ductions occurring outside the capped sector/sources)

 Additional provisions to mitigate pr ice volatility and overall costs

o Auction reserve price

o Cost containment reserve of allowances provi ded for sale at set price thresholds; once the allowance price hits a threshold, an extra supply of allowances are made available.
Table 1 summarizes some of the key design el ements of the RGGI and California programs.
Table 1: Comparison of RGGI and Califor nia Emissions Budget Trading Programs Element RGGI California Applicability  All fossil fuel-fired EGUs with a capacity of 25 MW or greater. 125  All facilities in covered sectors emitting at least 25,000 metric tons CO 2- equivalent (CO 2 e) or greater. 126 Scope  Facilities in electric power sector. 127  Facilities in electric power and large industrial sectors (plus fuel distributors in 2015) 128 Emissions budget  Recently reduced 45 percent to 91 million tons of CO 2 in 2014. Beginning in 2015, the budget will decline 2.5 percent per year to 2020. 129  Set at 2 percent below expected 2012 emissions, declining by 2 percent in 2014 and 3 percent annually from 2015 to 2020. 130

Compliance period  EGUs must demonstrate compliance every three years and hold allowances equal to 50 percent of reported CO 2 emissions at the end of the first two years of every three-year compliance period. 131  Facilities must demonstrate compliance every three years. On an annual basis, facilities must also hold allowances and offsets covering 30 percent of the previous year’s emissions. 132

125 RGGI, Overview of RGGI CO 2 Budget Trading Program (Regional Greenhouse Ga s Initiative, 2007), accessed on March 19, 2014, http://www.rggi.org/docs/program_summary_10_07.pdf. 126 CARB, Cap and Trade Regulation Instructional Guidance, Chapter 2: Is My Company Subject to the Cap-andTrade Regulation (California Air Resources Board, 2012), accessed on March 19, 2014, http://www.arb.ca.gov/cc/capandtrade/guidance/chapter2.pdf. 127 “Regulated Sources”, Regional Greenhouse Gas Initiative Inc., accesse d on May 14, 2014, http://www.rggi.org/design/ov erview/regulated_sources

. 128 CARB, Overview of ARB Emissions Trading Program (California Air Resources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf. 129 RGGI Inc., “RGGI States Make Major Cuts to Gree nhouse Gas Emissions from Power Plants,” Regional Greenhouse Gas Initiative Pre ss Release (January 13, 2014) , accessed on March 19, 2014, http://www.rggi.org/docs/PressReleas es/PR011314_AuctionNotice23.pdf. 130 CARB, Overview of ARB Emissions Trading Program (California Air Resources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf. 131 “Compliance” Regional Greenhouse Gas Initiative Inc., accessed on May 30, 2014 http://www.rggi.org/market/tracking/compliance

. 132 CARB, Overview of ARB Emissions Trading Program (California Air Resources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf.103 Allowance allocation method  Each state distributes allowances from its established budget in an amount and manner determined by its applicable statutes and regulations. Approximately 90 percent of CO 2 allowances are distributed through auction. 133  Allowances are both a llocated and auctioned off according to provisions established by the program. More information is available from CARB (see footnote). . 134

Cost containment provisions  A Cost Containment Reserve (CCR) of CO 2 allowances provides a fixed additional supply of allowances that are only available if the auction price exceeds a set threshold ($4 in 2014 rising to $10 in 2017 and 2.5 percent per year thereafter). 135 An additional five million allowances became available March 2014 when market price exceeded the current price trigger of $4 per ton. 136

 Trigger price increases until 2020 when 10 million allowances become available if price per ton exceeds $10.75 137  A strategic reserve is included, providing an Allowance Price Containment Reserve of one percent of allowances for 2013-2014, four percent of allowances for 2015-2017, and seven percent of allowances for 2018-2020. Shares of allowances held in the reserve will be released at three price trigger points; $40, $45, and $50 per ton and rise by 5 percent per year including inflation. 138

Banking  Allows unlimited allowance banking. 139  Allows unlimited allowance banking. 140 Offsets  EGUs subject to RGGI are allowed to use offsets within the RGGI region to meet 3.3 percent of their compliance obligation. 141

, 142  Facilities may use domestic offsets for up to 8 percent of their compliance obligation. 143 A framework has been established to include international offsets but these are currently

133 “2013 Allowance Allocation”, Regional Greenhouse Gas Initiative, Inc., accesse d on March 19, 2014, http://rggi.org/design/overview/allowance-allocation/2013-allocation

. 134 CARB, Overview of ARB Emissions Trading Program (California Air Resources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf. 135 “The RGGI CO 2 Cap” Regional Greenhouse Gas In itiative Inc., accessed on May 30, 2014 http://www.rggi.org/d esign/overview/cap

. 136 RGGI, “CO 2 Allowances Sold at $4.00 at 23 rd RGGI Auction,” Regional Greenhouse Gas Initiative Press Release (March 7, 2014), acce ssed on March 19, 2014, http://www.rggi.org/docs/Auctions/23/PR030714_Auction23.pdf

. 137 RGGI, Summary of RGGI Model Rule Changes (Regional Greenhouse Gas Initiative, Inc., 2013), Accessed on March 19, 2014, http://www.rggi.org/docs/ProgramRe view/_FinalProgramReviewMaterials/Model_Rule_Summary.pdf

. 138 “California Cap on Greenhouse Gas Emissions and Market-Based Compliance Mechanisms to Allow for the Use of Compliance Instruments Issued by Linked Jurisdicti ons,” California Code of Regulations, Title 17, §95800- 96023, accessed on May 30, 2014, http://www.arb.ca.gov/cc /capandtrade/ctlinkqc.pdf

. 139 RGGI, Overview of RGGI CO 2 Budget Trading Program (Regional Greenhouse Ga s Initiative, 2007), accessed on March 19, 2014, http://www.rggi.org/docs/program_summary_10_07.pdf. 140 CARB Proposed Regulation to Implement the California Cap-and-Trade Program (California Air Resources Board, 2010), accessed on March 19, 2014, http://www.arb.ca.gov/regact/20 10/capandtrade10/capisor.pdf. 141 “CO 2 Offsets” Regional Greenhouse Gas Initia tive, Inc., accessed on March 19, 2014, http://www.rggi.org/market/offsets

. 142 Eligible offsets under RGGI include: landfill methan e capture and destruction, sulfur hexafluoride (SF 6 ) reduction from power transmission, U.S. forest projects (reforestation, improved forest management, and avoided conversion) or afforestation (in CT and NY only), end use energy efficiency, and agricultural manure management. “Offset Categories” RGGI, Incegional Greenhouse Gas Initiative, Inc., Accessed on May 30, 2014. http://www.rggi.org/marke t/offsets/categories

. 143 CARB, Overview of ARB Emissions Trading Program (California Air Resources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf.104 not allowed in the program. 144

Authority
State and regional GHG emission budget trad ing programs are authorized through individual state legislation and implemented th rough state regulations. For example, California implemented its emission budget trading progr am under the authority of its 2006 Global Warming Solutions Act, which requires the state to reduce its 2020 GHG emissions to 1990 levels. 145 Each RGGI state has separate authoriz ing legislation, and in some cases their legislation specifically directs the use of aucti on proceeds. For example, Maine authorized its participation in RGGI through Statute 580-A, Title 38 Chapter 3B: Regional Greenhouse Gas Initiative. This statute also requires that 100 percent of auction proceeds go towards carbon reduction and energy conservation efforts. 146 RGGI is implemented through individual state CO 2 budget trading program regulations. 147
The state regulatory authority issues individu al authorizations to emit a specific quantity of emissions (“allowances”), which represent one (metric or short) ton of a pollutant, in an amount no greater than the established emission budget.
Obligated Parties
Obligated parties in emission budget trading pr ograms are generally the covered emission sources. It is the emission sources that are responsible for surrende ring emission allowances equal to their reported emissions at the end of each compliance period. For example, as stated above, RGGI covers fossil fuel-fired E GUs 25 megawatts or larger in size. 148 The California emission budget trading program covers electricity generators, importers of electricity and industrial facilities with annual emissions that exceed 25,000 metric tons CO 2- equivalent. Starting in 2015, the California program will also cover distributors of transportation, natural gas, and other fuels with emissions greater than 2 5,000 metric tons CO 2- equivalent. 149

Offsets are initially limited to forestry, urban forestry, liv estock methane capture and destruction, and destruction of ozone depleting substances. However, rice cultivation and coal mine methane are proposed for inclusion in the program. See: CARB – Potential New Compliance Offset Projects: http://www.arb.ca.gov/cc/capa ndtrade/offsets/offsets.htm for more information. 144 Ibid. 145 Assembly Bill 32, California Global Warming Solutions Act of 2006, Division 25.5 (September 27, 2006), accessed March 19, 2014, http://www.leginfo.ca.gov/pub/05-06/bill/asm/ab_0001- 0050/ab_32_bill_20060927_chaptered.pdf. 146 Maine revised statutes, Title 38, Chapter 3-B, sectio n 580-B, the Regional Greenhouse Gas Initiative Act of 2007, accessed on March 19, 2014, http://www.mainelegislature.org/legis/statutes/38/title38sec580-B.html. 147 RGGI, “State Statutes and Regulations,” http://www.rggi.org/ design/regulations. 148 “Regulated Sources”, Regional Greenhouse Gas Initiative Inc., accesse d on May 14, 2014, http://www.rggi.org/design/ov erview/regulated_sources

. 149 CARB, Overview of ARB Emissions Trading Program (California Air Resources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2011/cap_trade_overview.pdf

.105 Measurement and Verification
Emission budget trading programs include requirements for emission monitoring and reporting by affected emission so urces, holding and transfer of allowances, and surrender of allowances (and offset allowances or credits) in an amount equal to reported emissions. Allowance surrender in an amount equal to reporte d emissions is often referred to, generally, as the program “compliance obligation”.
For example, EGUs subject to the RGGI program must report CO 2 emissions quarterly pursuant to state regulations, which are generall y consistent with EPA regulations for reporting of CO 2 emissions from EGUs under 40 CFR 75. 150 Emissions are reported quarterly to EPA, using the Emissions Collection a nd Monitoring Plan System (ECMPS) , and data is transferred to the RGGI CO 2 Allowance Tracking System (RGGI COATS). GHG emissions reporting for affected sources under the California program is addressed through the California mandatory GHG reporting regulations, using a modified vers ion of the reporting platform administered through the EPA Greenhouse Gas Reporting Program. 151 Affected emission sources must report emissions annually and provide third pa rty verification of reported emissions.
Penalties for Non-compliance

Failure to submit allowances in an amount e qual to reported emissions result in automatic emission penalties in the form of additional a llowance submission requirements (e.g., three-toone submission requirements to account for any s hortfall in RGGI, and a four-to-one submission requirement for any shortfall under the Califor nia program). States may also apply other administrative fines and penalties, purs uant to their implementing regulations.
Implementation Status
The RGGI program was established in 2009. From 2009 through 2012, the nine current RGGI participating states invest ed auction proceeds of more than $700 million in programs that lower costs for energy consumers and reduce CO 2 emissions, including approximately $460 million in energy efficiency programs. 152 The participating RGGI states estimate that those investments are providing benefits of more than $1.8 billion in lifetime energy savings to energy consumers in the region. 153

150 RGGI, Overview of RGGI CO 2 Budget Trading Program (Regional Greenhouse Ga s Initiative, 2007), accessed on March 19, 2014, http://www.rggi.org/docs/program_summary_10_07.pdf. 151 CARB, Overview of ARB Emissions Trading Program (California Air Resources Board, 2011) accessed on March 19, 2014, http://www.arb.ca.gov/newsrel/2 011/cap_trade_overview.pdf. 152 RGGI Inc., Regional Investment of RGGI CO 2 Allowance Proceeds, 2012 (Regional Greenhouse Gas Initiative Inc., 2014), accessed on March 19, 2014, http://www.rggi.org/docs/Documents/2012-Investment-Report.pdf
, Programs include residential, commercial, and industrial pr ograms. Of the $707 million in auction proceeds invested by RGGI participating states through 2012, 65 percent supported end-use energy efficiency programs. 153 Ibid.106 Figure 3: Historical GDP and Greenhouse Gas Emissions in the RGGI Region

Between 2005, when agreement to implement RGGI was first announced, and 2012, power sector CO 2 emissions in the RGGI participating states fell by more than 40 percent while GDP in the region grew (see Figure 3). 154 The RGGI program, which began in 2009, was not a primary driver for these emission reductions in RGGI states, but the lower emissions led participating states to adjust the multi-state CO 2 emission limit. 155 In January 2014, the RGGI participating states lowered the overall allowable CO 2 emission level in 2014 by 45 percent,

154 Regional Greenhouse Gas Initiative, Open Letter to Gi na McCarthy on Emission St andards under Clean Air Act Section 111(d), December 2, 2 013, accessed on March 19, 2014, http://www.rggi.org/docs/RGGI_Sta tes_111d_Letter_Comments.pdf

. By contrast, total U.S. power sector CO 2 emissions fell by 16 percent during the same period of time. See 2014 U.S. Greenhouse Gas Inventory for more detail: U.S. EPA, Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2012 (U.S. Environmental Protection Agency, 2014), accessed May 14, 2014, http://www.epa.gov/climatechange/ghgemissions/usinventoryreport.html. 155 Environment Northeast, RGGI Emissions Trends (Environment Northeast, 2011), accessed on March 19, 2014, http://www.env-ne.org/public/r esources/pdf/ENE_RGGI_Emi ssions_Report_110502_FINAL.pdf

. The first three-year control period under RGGI, establishing CO 2 emission limits for EGUs, began on January 1, 2009. Low gas prices, increased renewables, decreased el ectric demand and weather are considered four primary drivers of the reductions through 2010, as reported by Environment Northeast in May 2011.107 setting a multi-state CO 2 emission limit for affected EGUs of 91 million short tons of CO 2 in 2014 and 78 million short tons of CO 2 in 2020, more than 50 percent below 2008 levels. 156

The California economy-wide market-based GHG emission budget trading program, which addresses GHG emissions from multiple s ectors, was implemented in 2012 with emission limits beginning in 2013. 157,158 While California’s emission budget trading program, like its state emission limit, is multi-sector in scope, the stat e projects that the emi ssion trading program and related complementary measures will reduce power sector GHG emissions to less than 80 million metric tons of CO 2 -equivalent by 2025, a 25 percent reduction from 2005 power sector emission levels. 159 Prior to the implementation of th e emission trading program, California reports that it reduced power sector CO 2 emissions by 16 percent from 2005 to a 2010-2012 averaging period, a reduction of 16 million metric tons of CO 2- equivalent. 160

ii. CO 2 Emission Performance Standards
Description

CO 2 emission performance standards can apply ei ther directly to EGUs or to the local distribution company (LDC) that se lls electricity to the customers. (For more information about electricity is generated and di stributed, see Chapter 2 of the Regulatory Impact Analysis).
As of March 2014, four states - California , New York, Oregon and Washington - have enacted mandatory GHG emission standards that impose enforceable emission limits on new and/or expanded electric generating units. 161 Three states - Californi a, Oregon and Washington - have enacted mandatory GHG emission performan ce standards that set an emission rate for

156 RGGI Inc., “RGGI States Make Major Cuts to Gree nhouse Gas Emissions from Power Plants,” Regional Greenhouse Gas Initiative Pre ss Release (January 13, 2014) , accessed on March 19, 2014, http://www.rggi.org/docs/PressReleas es/PR011314_AuctionNotice23.pdf. 157 “Cap-and-Trade Program,” California Air Resources Board, accessed March 19, 2014, http://www.arb.ca.gov/cc/capandtrade/capandtrade.htm

. 158 The California program was developed in coordination with U.S. state and Canadian province WCI partners. 159 State environmental agency leader s from CA, CO, DE, IL, ME, MD, MA, MN, NH, NY, OR, RI, VT, WA, Open Letter to the EPA Administrator Gina McCarthy on Emission Standards under Clean Air Act Section 111(d), December 16, 2013, accesse d on March 19, 2014, http://www.georgetownclimate.org/sites/default/f iles/EPA_Submission_from_States-FinalCompl.pdf

. Preliminary California Air Resources Board analyses, based in part on CARB 2008 to 2012 Emissions for Mandatory GHG reporting Summary (2013), cited in this letter. 160 Ibid. 161 California Energy Commission, California SB 1368, Chapter 598: Emission Performance Standards, September 29, 2006, accessed March 19, 2014, http://www.energy.ca.gov/emission_standards/. New York Department of Environmental Conservation, Part 251: CO2 Performance Standards for Major Electric Generating Facilities, June 12, 2012, accessed March 19, 2014, http://www.dec.ny.gov/regs/83094.html#83097 .; Oregon Department of Energy, Oregon’s Carbon Dioxide Emission Standards fo r New Energy Facilities (Orego n Department of Energy, 2010) http://www.oregon.gov/energy/Sitin g/docs/Reports/CO2Standard.pdf ; Washington State Legislature, Chapter 80.70 RCW: Carbon Dioxide Mitigation, Accessed on March 19, 2014, http://apps.leg.wa.gov/rcw/default.aspx?cite=80.70&full=true108 electricity purchased by electric utilities. 162 In addition to these states, Illinois and Montana have policies to incentivize or require new coal plants to capture at least 50 percent of their CO 2 emissions (see Figure 4). 163
Figure 4: States with Greenhouse Gas Performance Standards

Policy Mechanics
Design
States have implemented three different types of CO 2 performance standards that affect EGUs and/or LDCs differently. The first re quires power plant emissions per electricity generated to be less than or equi valent to an established standard and is directly applicable to EGUs. The second type places conditions on the emi ssions attributes of electricity procured by electric utilities. It consists of standards that are applicable to LDCs that provide electricity to retail customers. A third type requires that new coal-fired power plants must capture and store a specific percentage of CO 2 emissions. Table 2 provides state ex amples for each of the types of CO 2 performance standards.

162 Ibid. 163 Illinois General Assembly, Public Act 095-1027, SB1987, Clean Coal Portfolio Standard Law, January 12, 2009, accessed March 19, 2014 http://ilga.gov/legislation/publicacts/95/PDF/095-1027.pdf ; Montana State Legislature, H.B.0025.05, An Act Generally Revising the Electric Utility Industry and Customer Choice Laws, May 14, 2007, accessed March 19, 2014, http://leg.mt.gov/bills/20 07/billpdf/HB0025.pdf

.109 Authority
In some states, programs are regulated through the Public Utilities Commission (California, Oregon). New York’s program is regulated through the Department of Environmental Conservation. Wash ington’s program is regulated through two different sets of entities depending on the ownership of the utilitie s. The Washington Utilities and Transportation Commission regulate investor ow ned utilities, and the utility's governing board, Washington Department of Ecology, and the State Audito r oversees consumer owned utilities.
Obligated Parties
The emission performance standard can apply ei ther directly to EGUs or to the local distribution company (LDC) that se lls electricity to the customer.
Measurement and Verification
Obligated parties must measure and report on electricity generation and CO 2 emissions on a regular basis to verify their compliance w ith the standard. The reporting requirements and timing varies from state to state and are typically set by the agency that oversees the program as described under authority above.

Table 2 provides an overview of different CO 2 performance standards, while Table 3 provides examples regarding measurement and ve rification requirements across California, New York, Oregon, and Washington.
Table 2: Examples of State CO 2 Performance Standards

164 New York Department of Environmental Conservation, Part 251: CO2 Performance Standards for Major Electric Generating Facilities, June 12 , 2012, accessed March 19, 2014, http://www.dec.ny.gov/regs/83094.html#83097. 165 Oregon Department of Energy, Oregon’s Carbon Dioxide Emission Standards for New Energy Facilities (Oregon Department of Energy, 2010) http://www.oregon.gov/energy/Siti ng/docs/Reports/CO2Standard.pdf

.

What It Does State Examples Requires power plant emissions per electricity generated to be less than or equivalent to the established standard; Applies to EGUs  New York (Part 251, 2012) - New or expanded baseload plants (25 MW and larger) must meet an emission rate of either 925 lb CO 2 /MWh (output based) or 120 lbs CO 2 /MMBTU (input based). Non-baseload plants (25 MW and larger) must meet an emission rate of either 1450 lbs CO 2 /MWh (output based) or 160 lbs CO 2 /MMBTU (input based). 164

 Oregon (HB 3283; 1997, 2007) - New natural gas-fired power plants (baseload and non-baseload) must meet an emission rate of 675 lb CO 2 /MWh. Cogeneration and offsets may be used to comply with the emission standard. 165

 Washington (RCW 80-70-010; 2004) - New EGUs 25 MW and larger must have an110 166 Washington State Legislature, Chapter 80.70 RCW: Ca rbon Dioxide Mitig ation, Accessed on March 19, 2014, http://apps.leg.wa.gov/rcw/default.aspx?cite=80.70&full=true

. 167 California Energy Commission, California SB 1368, Chapter 598: Emission Performance Standards, September 29, 2006, accessed March 19, 2014, http://www.energy.ca.gov/emission_standards/. 168 U.S. EPA, eGRID 2010 data files (U.S. Environmental Protection Agen cy, 2014), accessed on March 19, 2014, http://www.epa.gov/cleanenergy/en ergy-resources/egrid/index.html#

. 169 Oregon Department of Energy, Oregon’s Carbon Dioxide Emission Standards for New Energy Facilities (Oregon Department of Energy, 2010) http://www.oregon.gov/energy/Siti ng/docs/Reports/CO2Standard.pdf

. 170 Washington State Legislature, Chapter 80.70 RCW: Ca rbon Dioxide Mitig ation, Accessed on March 19, 2014, http://apps.leg.wa.gov/rcw/default.aspx?cite=80.70&full=true

. 171 Illinois General Assembly, Public Act 095-1027, SB1987, Clean Coal Portfolio Standard Law, January 12, 2009, accessed March 19, 2014 http://ilga.gov/legislation/publicacts/95/PDF/095-1027.pdf

. 172 Montana State Legislature, H.B.0025.05, An Act Genera lly Revising the Electric Utility Industry and Customer Choice Laws, May 14, 2007, accessed March 19, 2014, http://leg.mt.gov/bills/20 07/billpdf/HB0025.pdf

. 173 Regulatory Assistance Project, Emissions Performance Standards in Selected States (Regulatory Assistance Project, 2010), accessed on May 30, 2014, http://www.raponline.org/search/related/relation/project-document/id/10 approved CO 2 mitigation plan that results in mitigation of 20 percent of the total CO 2 emissions over the life of the facility. Includes modifications to existing EGUs that result in an increase in CO 2 emissions of 15 percent or more. The CO 2 mitigation plan may include one or more of a list of eligible measures (includes indirect measures, such as EE/RE and offsets). 166
Places conditions on the emissions attributes of electricity procured by electric utilities; Applies to LDCs  California (SB 1368; 2006) - Electric utilities may only enter into long-term power purchase agreements for baseload power if the electric generator supplying the power has a CO 2 emission rate that does not exceed that of a natural gas combined cycle plant. The California Energy Commission promulgated regulations establishing an emission rate of 1,100 lb CO 2 /MWh. 167 By comparison, the average em issions rate of gas plants in the U.S. is 945 lb CO 2 /MWh, while the average emissions rate of pulverized coal plants is 2,154 lb CO 2 /MWh. 168

 Oregon (HB 101; 2009) and Washington (SB 6001; 2007) - Electric utilities may only enter into long-term power purchase agreem ents for baseload power if the electric generator supplying the power has a CO 2 emission rate of 1,100 lb CO 2 /MWh or less. 169170 Requires that new coal-fired power plants must capture and store a specific percentage of CO 2 emissions  Illinois (SB 1987; 2009) Illinois utilities and retailers must purchase at least 5 percent of their electricity from Clean Coal Facilities in 2015 and beyond. To be designated a Clean Coal Facility, new coal-fired power plan ts must capture and store 50 percent of carbon emissions from 2009-2015, 70 percent for 2016-2017, and 90 percent after 2017. 171

 Montana (HB 25; 2007). The Public Service Commission may not approve new plants constructed after January 2007 that are primar ily coal-fired unless at least 50 percent of the plant’s CO 2 emissions are captured and stored. 172 These requirements apply to formerly restructured utilities in the state. Northwest Energy is the only utility subject to this requirement, which serves about two-thirds of Montana. 173111 Table 3: Examples of Measurement a nd Verification Requirements for CO 2 Performance Standards State Measurement and Verification Details California  The California PUC is responsible for approving any long term financial commitment by an electric utility and must adopt rules to enforce these requirements as well as verification procedures. 174 New York  CO 2 emission regulations require recordkeeping, monitoring and reporting consistent with existing state and federal regulations.

 Each applicable emissions source must install Continuous Emissions Monitoring Systems (CEMS) subject to Federal CO 2 reporting requirements for 40 CFR part 75, successfully complete certifica tion tests, and record, report , and quality assure the data from the CEMS.

 The owner or operator must report the CO 2 mass emissions data and heat input data on a semi-annual basis to the Department of Environmental Conservation.

 On a quarterly basis, the owner or operator must report all of the data and information required in either 40 CFR part 60 or subpart H of 40 CFR part 75. 175 Washington  Mitigation projects must be approved by the appropriate council, department, or authority, and made a condition of the proposed and final site certification agreement or order of approval.

 Direct investment projects ar e approved if they provide reasonable certainty that the performance requirements of the projects will be achieved and that they were implemented after July 1, 2004.

 For facilities under the jurisdiction of a council, the implementation of a carbon dioxide mitigation project, other than purchase of carbon credits, is monitored by an independent entity for conformance with the performance requirements of the carbon dioxide mitigation plan. The independent entity shares the project monitoring results with the council.

 For facilities under jurisdiction of the department or authority, the implementation of a carbon dioxide mitigation project, other than a purchase of carbon credits, is monitored by the department or authority issuing the order of approval. 176 Oregon  It is up to the Council during the certificate application phase to determine the gross CO 2 emissions over a 30 year lifetime of the proposed facility to determine whether it meets the CO 2 performance standard.

 During the operation phase of approved facilities, there are CO 2 reporting requirements to the Oregon Department of Environmental Quality and US EPA.

 New facilities must pass a 100 hour test in their first year of operation to show they meet the performance standards. 177

174 “SB 1368 Emission Performance Standards,” California Energy Commission, Accessed March 19, 2014, http://www.energy.ca. gov/emission_standards/

. 175 New York Department of Environmental Conservation, Part 251: CO 2 Performance Standards for Major Electric Generating Facilities, June 12, 2012, Accessed March 19, 2014, http://www.dec.ny.gov/regs/83094.html#83097. 176 Washington State Legislature, Chapter 80.70 RCW: Ca rbon Dioxide Mitig ation, Accessed on March 19, 2014, http://apps.leg.wa.gov/rcw/default.aspx?cite=80.70&full=true 177 Oregon Department of Energy, Oregon’s Carbon Dioxide Emission Standards for New Energy Facilities (Oregon Department of Energy, 20 10) Accessed on March 19, 2014 http://www.oregon.gov/energy/Siti ng/docs/Reports/CO2Standard.pdf

.112 Penalties for Noncompliance
For policies that affect target new electric generating units, utilities must prove any proposed units are in compliance at the time of permitting. In Oregon, if facilities do not meet the performance standard in their firs t year of operation during a 100 hour test 178 , they must purchase offsets to account for any excess emissions. 179
Implementation Status
Since enacting the performance standard, Califor nia’s carbon emissions rates have fallen from approximately 1,245 lbs CO 2 e/MWh for fossil generation (c onsidering both in-state and imported power) and 875 lbs CO 2 e/MWh for all power in 2005 to an average of approximately 1,090 lbs CO 2 e/MWh and 775 lbs CO 2 e/MWh in the three years before 2012. 180

b. Energy Efficiency Policies, Programs and Measures
Demand-side energy efficiency policies and programs reduce utilization of EGUs and avoid greenhouse gas emissions associated with electricity generation. These electricity demand reductions can be achieved through enabling policies that incentivize inve stment in demand-side energy efficiency improvements by overcoming ma rket barriers that otherwise prevent these investments, such as lack of information on ener gy efficient options, high transaction costs, splitincentives, lack of product availability, and perceptions of organizational risks. Reducing electricity demand also reduces the associated transmission and distribution losses that occur across the grid between the sites of el ectricity generation and the end use.
Demand-side energy efficiency is considered a central part of climate change mitigation in states that currently have mandatory GHG targets, accounting for roughly 35 percent to 70 percent of expected reductions of state's power sector emissions. 181 For example, California expects to achieve reductions of 21.9 MMTCO 2 e in 2020 from energy efficiency programs targeting electricity reductions. Taking in to account expected reductions of 21.3 MMTCO 2 e expected from California's RPS and 2.1 MMTCO 2 e from the million solar roofs program, energy efficiency makes up 48 percent of power sector reductions based on California's Climate Change Scoping Plan. 182 Another state, Washington, expects to reduce 9.7 MMTCO 2 e from energy efficiency measures in 2020. Taking into account expected reductions of 4.1 MMTCO 2 e from

178 During the first year of operation new power plants test their equipment to ensure compliance with standards for commercial equipment. Initial CO 2 performance requirements can be validated during this test. 179 Oregon Department of Energy, Oregon’s Carbon Dioxide Emission Standards for New Energy Facilities
, Accessed on March 19, 2014, http://www.oregon.gov/energy/Siting/docs/Reports/CO2Standard.pdf

. 180 State environmental agency leader s from CA, CO, DE, IL, ME, MD, MA, MN, NH, NY, OR, RI, VT, WA, Open Letter to EPA Administrator Gina McCarthy on Emission Standards Under Clean Air Act Section 111(d), December 16, 2013, accessed on March 19, 2014, http://www.georgetownclimate.org/sites/default/f iles/EPA_Submission_from_States-FinalCompl.pdf

. 181 These reduction target ranges are based on a review of state GHG reduction laws in California, Connecticut, Hawaii, Maine, Maryland, Massachusetts, Minne sota, New Jersey, Oregon, and Washington. 182 California Air Resources Board, Climate Change Scoping Plan, accessed March 19, 2014, http://www.arb.ca.gov/cc/ scopingplan/document/adopted_scoping_plan.pdf

.113 Washington's RPS, energy efficiency makes up 70 percent of expected emission reductions from stationary energy within the state. 183
States have employed a variet y of strategies to increase investment in demand-side energy efficiency technologies and practices, incl uding (1) energy efficiency resource standards, (2) demand-side energy efficiency programs, (3) building energy codes, (4) appliance standards and (5) tax credits. Each of these strategies is described below.

i. Energy Efficiency Resource Standards
Description
Energy Efficiency Resource Standards (EERS) set multiyear targets for energy savings that utilities or thir d-party program administrators typi cally meet through customer energy efficiency programs but also through other approaches, such as peak demand reductions, building codes and combined heat and power (CHP). An EERS can apply to retail distributors of either electricity or natural gas, or both, de pending on the state. To date, 23 states have mandatory EE requirements in place, two states have voluntary targets, and two more states allow EE to be used to meet part of a mandatory RPS, for a total of at least 27 states with some type of EE requirement or goal. 184,185
Policy Mechanics
Design
EERS design and implementation details vary by state, and may be expressed as a percentage reduction in annual reta il electricity sales, as a pe rcentage reduction in retail electricity sales growth, or as a specific electricity savings amount over a long-term period. A typical EERS sets multiyear targets for energy savings that drive investment in EE programs implemented by utilities or third party admini strators. Over the compliance period, an EERS reduces electricity demand by a target amount that utilities must meet. As a result, an EERS indirectly affects utility CO 2 emissions by reducing the use of fossil-fuel-fired EGUs.

183 Washington Department of Ecology, Growing Washington’s Economy in a Carbon-Constrained World, Accessed March 19, 2014, https://fortress.wa.gov/ecy/publications/publications/0801025.pdf

. 184 "State Energy Efficiency Resour ce Standards (EERS)," (American Council for an Energy-Efficient Economy, April 2014), Accessed on May 23, 2014, http://www.aceee.org/files/pdf/policy

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. 185 Delaware and Florida were not included in the totals. Delaware has enacted legislation to create an EERS, but final regulations have not yet been promulgated (Datab ase of State Incentives for Renewables & Efficiency, Accessed on May 29, 2014, http://www.dsireusa.org/incentives/ incentive.cfm?Incentive_Code=DE17R ). Florida has enacted an EERS, but program funding to date is cons idered to be “...far below what is necessary to meet targets” ("State Energy Efficiency Resource Standard s (EERS)," American Council for an Energy-Efficient Economy, April 2014, Accessed on May 23, 2014, http://www.aceee.org/files/pdf/policy

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‐ 2014.pdf ).114 Authority
Most state EERS policies are established through legislation. However, there are several instances in which they have been established by PUC orders under broader statutory authority, such as by setting quantitative targets consistent with the achievement of ‘all cost-effective energy efficiency. 186
Obligated Parties
Retail electricity suppliers, whic h are utilities that sell electricity to customers for end-use purposes, are the obligated parties under an EERS.
Measurement and Verification
PUCs generally oversee EERS. Retail el ectricity suppliers comply with EERS requirements by developing a portfolio of end-us e energy efficiency programs that encourage electric utility customers to i nvest in more energy efficien t technologies and practices as described below. Transmission and distributi on infrastructure improvements may also count towards EERS programs in some states. 187 PUCs typically rely on independent program evaluators to perform evaluation, measurement a nd verification (EM&V) activities that estimate the incremental annual and cumulative ener gy savings attributable to the programs. 188 These estimates are typically the basis for compliance reports submitted by retail electricity suppliers. See Table 4 for examples of penalties for progr am noncompliance. For more information about measurement and verification of energy efficiency policies or programs, see earlier in the State Plan Considerations Tec hnical Support Document.

186 Ernest Orlando Lawrence Be rkeley National Laboratory, Benefits and Costs of Aggressive Energy Efficiency Programs and the Impacts of Alternative Sources of Funding: Case Study of Massachusetts , accessed on May 14, 2014, http://emp.lbl.gov/sites/all/f iles/REPORT%20lbnl-3833e.pdf .An important policy driver for EE programs in six states is a statutory requirement for utilities to acqui re "all cost-effective energy efficiency". This policy typically requires utilities and other program administrators to pursue energy efficiency up to the point at which it is no longer cost effective, as defined by cost-benefit tests and procedures REQUIRED by state PUCs. States with allcost effective energy efficiency policie s include: CA, CT, MA, RI, VT, WA. For MA, this goals has translated into achieving annual electric energy savings equivalent to a 2.4% reduction in retail sales from energy efficiency programs in 2012. 187 For example, Ohio allows transmission and distributio n infrastructure improvements to count towards their EERS. Database of State Incentives for Renewa bles & Efficiency, Accessed on May 29, 2014, http://www.dsireusa.org/incentives/incentiv e.cfm?Incentive_Code=OH16R&re=0&ee=0

. 188 Evaluation, measurement, and verification (EM&V) refers to set of techniques and approaches used to estimate the quantity of energy savings from an EE program or po licy. Since energy savings cannot be directly measured, efficiency program impacts are estima ted by taking the difference between: (a) actual energy consumption after efficiency measures are installed, and (b) the energy consumption that would have occurred during the same period had the efficiency measures not be en installed (i.e., the baseline).115 Table 4: Examples of Pe nalties for Noncompliance State Direct Financial Penalties Pennsylvania Failure to achieve the requisite reductions in electricity consumption and peak demand during Phase 1 results in one-time fines from $1 million to $20 million. Failure to file a plan with the public utilities commission is also punishable by a fine of $100,000 per day. Costs associated with any such fines may not be passed on to ratepayers. 189 Ohio Failure to comply with energy efficiency or peak demand reduction requirements results in the state public utilities commission assessing a forfeiture upon the utility, to be credited to the Advanced Energy Fund. The amount of the forfeiture is either: an amount, per day per under-compliance or non-compliance, not greater than $10,000 per violation; or an amount equal to the then existing market value of one renewable energy credit (REC) 190 per megawatt hour of under-compliance or noncompliance. 191 Illinois For both natural gas and electric utilities, fa ilure to submit an energy reduction plan will result in a fine of $100,000 per day until the plan is filed. This penalty is deposited in the Energy Efficiency Trust Fund and may not be recovered by rate payers. 192

Penalties for Noncompliance
If the obligated parties do not demonstrat e compliance with the EERS, they may face financial penalties. The existen ce and amount of penalties varies across the states. Table 4 provides examples of financial penalties in three states, Penns ylvania, Ohio and Illinois.
Implementation Status
As of April 2014, 23 states had an active EER S in place, while at least two have EE targets or goals that are volunt ary at this time (see Figure 5) . In addition, two states have renewable portfolio standard that allow the optio n for energy efficiency to meet requirements. 193

189 “Energy Efficiency and Conservation Requirements for Ut ilities: Pennsylvania” Database of State Incentives for Renewables & Efficiency, accessed on March 19, 2014, http://www.dsireusa.org/incentives/incentiv e.cfm?Incentive_Code=PA14R&re=0&ee=0

. 190 RECs represent the non-energy attributes, including a ll the environmental attributes, of electricity generation from renewable energy sources. RECs are typically issued in single MWh increments. See the section on Renewable Portfolio Standards for more detail. 191 “Energy Efficiency and Conservation Requirements fo r Utilities: Ohio” Database of State Incentives for Renewables & Efficiency, accessed on March 19, 2014, http://www.dsireusa.org/incentives/incentiv e.cfm?Incentive_Code=OH16R&re=0&ee=0

. 192 “Energy Efficiency and Conservation Requirements for Utilities: Illinois” Database of State Incentives for Renewables & Efficiency, accessed on March 19, 2014, http://www.dsireusa.org/incentives/incentiv e.cfm?Incentive_Code=IL19R&re=0&ee=0

. 193 See footnotes 184 and 185.116 Figure 5: Status of Energy Efficiency Resource Standards by State

Most states are meeting or on track to m eet their incremental savings goals, which typically range from an annual reduction in electricity of about 0.25 - 2.5 percent. 194 In 2011, across the 50 states, incremental savings were eq uivalent to 0.62 percent of retail electricity sales. 195 For those states with EERS po licies in place for more than two years as of 2011, thirteen of twenty states are achieving 100 percent or more of their goals, three states are achieving over 90 percent of their goals, and only three states ar e realizing savings belo w 80 percent of their goals. 196

ii. Demand-side Energy Efficiency Programs
Description
Demand-side energy efficiency programs are programs designed to advance energy efficiency improvements within a state or utility service area. They are typically implemented to help meet state policies, standa rds or objectives, such as energy efficiency resource standards

194 Ibid. 195 “The 2013 State Energy Efficiency Scorecard”, Ameri can Council for an Energy-Efficient Economy, Accessed on March 19, 2014, http://www.aceee.org/re search-report/e13k

. 196 Michael Sciortino, Seth Nowak, Patti White, Dan York, and Martin Kushler. “Energy Efficiency Resource Standards: A Progress Repo rt on State Experience.” American Council for an Energy Efficient Economy (2011).117 (EERS), ‘all cost effective’ energy efficiency goals, integrated resource planning, and other demand-side management program and budget processes.
Policy Mechanics
Design
Demand-side energy efficiency programs incl ude financial incentives to use energy efficient products, make energy efficiency upgrades to improve the performance of residential, commercial, and industrial buildings, and provide technical assistance and information programs to address market and information barriers. Funding for these programs typically comes from charges added to customer utili ty bills and from revenues raised through emission allowance auctions, such as under RGGI. The RGGI auction proceeds go to a variety of sources with the authority to run demand-side energy efficiency programs, in cluding those also funded via independent trusts, DOE’s Weatherization Assi stance Program (WAP), and state-run energy efficiency grant progr ams for municipalities. 197
States are also funding ener gy efficiency programs using revenues from “forward capacity markets” operated by regional electri city operators. Forward capacity markets allow energy suppliers to bid against each other for th e amount of capacity they can supply into the electricity market in a future year. Demand-side management programs have been allowed to bid into these markets as an energy source, dem onstrating that energy efficiency programs can compete with more tradi tional forms of electricity supply in meeting the ne eds of the power grid.
Authority
Demand-side programs that are a part of EERS programs are typically established through legislation or PUC authority. Other dema nd-side management programs can arise as a result of utility planning proce sses and state and local governmentefforts to ensure all costeffective energy efficiency and other policy goals are met.
Obligated Parties
Energy efficiency programs can be admini stered by investor-o wned, municipal or cooperative utilities; third pa rty administrators; or state and local government agencies.
Measurement and Verification
PUCs generally oversee demand-side en ergy efficiency programs. Program administrators typically rely on independent ev aluators to perform evaluation, measurement and verification (EM&V) activities that estimate the incremental annual and cumulative energy savings attributable to the programs. Thes e estimates are typically the basis for annual

197 RGGI, “Regional Investment of RGGI CO2 Allowance Proceeds, 2012”, Regional Greenhouse Gas Initiative (February 2014), acce ssed on March 19, 2014, http://www.rggi.org/docs/Documents/2012

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.118 performance reports submitted by retail electricity s uppliers or third party administrators to the PUCs. In the case of state and local government agency run programs that are not overseen by the PUC, energy savings are typically estimated to assure proper use of grants or other funds. For more information about the evaluation, meas urement and verification of energy efficiency policies and programs, see earlier in the State Pl an Considerations Technical Support Document.
Penalties for Noncompliance
As discussed above, some states with an EERS levy direct fines for missing energy efficiency targets or failure to submit an en ergy efficiency plan. For some programs under PUC oversight, failure to reach certain performance leve ls may result in an inability to receive an incentive payment or recove r all incurred costs. Demand-side programs funded by RGGI proceeds or grants typically do not have penal ties for noncompliance. However, state agencies play a role in evaluating these programs and d eciding whether funding should continue to flow to them.
Implementation Status
Well-established state demand-side energy effi ciency programs have demonstrated their ability to reduce electricity demand. 198 For example, data reported to the U.S. Energy Information Administration (E IA) show that in 2012 Calif ornia avoided 35,482 GWh of electricity consumption through its demand-side efficiency programs, while Illinois avoided 3,084 GWh and Maryland avoided 1,528 GWh, . 199 These reductions are equivalent to 13.7 percent, 2.1 percent, and 2.5 per cent of total 2012 re tail electricity sales in those states, respectively. 200 According to data and analyses fr om sources including Lawrence Berkeley National Lab (LBNL), the U.S. Department of Energy’s Energy Information Administration, and the American Council for an Energy Efficient Economy (ACEEE), as well as the EPA’s own analysis, 12 leading states have either achieved – or have established requirements that will lead them to achieve - annual incremental savings ra tes of at least 1.5 per cent of the electricity consumption that would otherwise have occurred. 201
In 2011, utilities in 48 states implemented demand-side energy efficiency programs. 202 State demand-side energy efficiency pr ograms are estimated to have reduced CO 2 emissions by 75 million metric tons in 2011, or 3.5 percen t of national power sector emissions. 203204

198 “The Future of Utility Customer-Funded Energy Efficiency Programs in th e United States”, Lawrence Berkeley National Laboratory, Accessed on March 19, 2014, http://emp.lbl.gov/publications/future-utility-customer-fundedenergy-efficiency-programs-un ited-states-projected-spend

. 199 “Electric Power Sales, Revenue, and Energy Efficiency Form EIA-861 Detailed Data Files”, Energy Information Administration, Accessed on March 19, 2014, http://www.eia.gov/electricity/data/eia861/

. 200 “Electricity: Detailed State Dat a”, Energy Information Administration, Accessed on March 19, 2014, http://www.eia.gov/electricity/data/state/

. 201 See the Greenhouse Gas Abatement M easures TSD for more information. 202 “The 2013 State Energy Efficiency Scorecard”, Ameri can Council for an Energy-E fficient Economy, Accessed on March 19, 2014, http://www.aceee.org/re search-report/e13k. 203 The Edison Foundation: Innova tion, Electricity Efficiency, Summary of Customer-Funded Electric Efficiency Savings, Expenditures, and Budgets (2011-2012) , March 2013, Accessed on March 19, 2014,119 iii. Building Energy Codes
Description
Building energy codes establish minimum effi ciency requirements for new and renovated residential and commercial buildings. These measures are intended to eliminate inefficient technologies with minimal impact on up-front project costs. This can reduce the need for energy generation capacity and new infrastructure wh ile reducing energy bills. Energy codes lock in future energy savings during the building desi gn and construction phase, rather than through a renovation.
Policy Mechanics
Design

Codes specify “thermal resistance” improveme nts to the building shell and windows, minimum air leakage, and minimum efficien cy for heating and cooling equipment.
Mandatory building energy codes establis h minimum efficiency requirements for residential and commercial construction. The In ternational Energy Conservation Code (IECC) is the prevailing model code for the reside ntial sector. ASHRAE 90.1-2010 is the model commercial code.
By locking in efficiency measures at the time of construction, codes are intended to capture energy savings that are more cost-effec tive than retrofit opportuni ties available after a building has been constructed. Energy code requir ements are also intended to overcome market barriers to efficient construction in both the co mmercial and residential sectors, such as the complexity of advanced codes, lack of local-l evel implementation resources, and a shortage of empirical data on the costs and benefits of codes.
Authority
Model building codes are typically developed at the national or international level, adopted at the state and/or local level, and implemented and enforced locally.
Obligated Parties
Local parties, such as developers and prope rty owners requiring building permits, are the most common obligated parties.

http://www.edisonfoundation.net/iei/D ocuments/FINAL_IEE%20Whitepaper_ 2012_US%20Energy%20Efficiency. pdf

. 204 EPA, Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011 Executive Summary , (Environment Protection Agency, 2013), accessed on March 19, 2014. http://www.epa.gov/climatechange/Downloads/ghgemissions/US-GHG-Inventory-2013-ES.pdf

.120 Measurement and Verification
Program implementation steps, including bu ilder training, complia nce assurance, and enforcement, are typically the responsibility of state and local governments. These steps, however, are often not fully or uniformly im plemented for numerous reasons, including an emphasis on health and safety issues over the pr oper functioning of mechanical equipment, a lack of trained staff to review building plan s and conduct onsite inspect ions, and limited funding to carry out key implementation activities. As a result, most jurisdictions do not have the capacity to analyze code compliance and to identi fy the measures and strategies that should be targeted for improved implementation. For more information about measurement and verification of energy efficiency, see earlier in the State Plan Considerations Technical Support Document.
Penalties for Noncompliance
In order to get building permits approved, the relevant developer or property owners must show they are in compliance with standards. Sinc e permitting is done at the local level, the use of penalties and the ability to enforce standard s vary significantly by region. DOE has been working with states and localitie s to improve compliance practice
Implementation Status
To date, 28 states have adopted IECC 2009 while four states have gone further by adopting the IECC 2012. In the commercial sect or, 33 states have adopted ASHRAE 90.1-2007 and five states have adopted ASHRAE 90.1-2010. Cu rrently, 11 states have outdated or no statewide residential energy code, a nd 9 states have outdated or no state-wide energy codes for commercial construction. 205 The current status of state residential and commercial energy codes are shown below in Figure 6 and Figure 7, resp ectively. The State of Oregon, which has adopted residential and commercial codes based on the IECC 2009, estimated total savings in 2009 from building energy codes of 1.17 GWh and 2.3 GWh in the residential and commercial sectors, respectively. 206 This was equivalent to more than 7 pe rcent of total retail electricity sales in Oregon in 2009. 207

205 “Code Status”, Online Code Environment & Ad vocacy Network, Accesse d on March 19, 2014, http://energycodeso cean.org/code-status

. 206 Oregon Department of Energy, 2011-2013 State of Oregon Energy Plan , Accessed on March 19, 2014, http://www.oregon.gov/energy/docs/reports/legislature/2011/energy_plan_2011-13.pdf

. 207 “State Electricity Profiles: Oregon Electricity Profile 2012”, Energy Information Administration, Accessed on March 19, 2014, http://www.eia.gov/electricity/state/oregon/

.121 Figure 6: Residential State Energy Code Status

Figure 7: Commercial State Energy Code Status122 iv. Appliance and Equipment Efficiency Standards
Description
State appliance standards establish mini mum energy-efficiency levels for those appliances and other energy-consuming products that are not already covered by the federal government. These standards typically prohibit the sa le of less efficient mo dels within a state. States are finding that appliance standards o ffer a cost-effective strategy for improving energy efficiency and lowering energy costs for busines ses and consumers, though these standards are superseded when Federal standards ar e enacted for new product categories,.
While state appliance standards can be useful in testing and explori ng the effectiveness of standards for new products, states cannot preempt or supersede existing Fede ral standards. States may apply to DOE for a waiver to implement mo re stringent standards. This is sometimes granted if a certain period of time has passe d since the federal standard has been updated.
Policy Mechanics
Design
When states implement appliance and equi pment standards, they are establishing a minimum efficiency for products, such as refrige rators or air conditione rs, thereby reducing the energy associated with using the product. Standa rds prohibit the production and sale of products less efficient than the minimum requirements, encouraging manufacturers to focus on how to incorporate energy-efficient technol ogies into their produ cts at the least cost and hastening the development of innovations that bring improved performance.
Authority
State energy offices, which typically administ er the federal state energy program funds, have generally acted as the administrative l ead for standards implementation. In contrast, inspection and enforcement of appliance standa rds regulations has typically involved selfpolicing. Industry competition is such that co mpetitive manufacturers usually report violations.
Obligated Parties
Manufacturers of products being sold in a give n state are typically obligated to ensure their appliances meet the appropria te energy efficiency standards.
Measurement and Verification
Evaluating the benefits and costs of the st andards is important during the standardssetting process. Once enacted, however, little field evaluation is performed. For more information about measurement and verification of energy efficiency, see earli er in the State Plan Considerations Technical Support Document.123 Penalties for Noncompliance
Appliances and equipment found in viola tion of the minimum energy performance standards are not allowed to be sold or manufactured in the state.
Implementation Status
Currently, fifteen states and th e District of Columbia have enacted appliance efficiency standards. However, most of these standards have been superseded by federal standards. Still, nine states (AZ, CA, CT, MD, NV, NY, OR, RI, WA) and the Distri ct of Columbia have either enacted standards for equipment not covered fe derally or obtained waivers to enact tougher appliance standards where the federal regulati ons have become outdated. California currently leads all states in active stat e standards, covering 13 products , including consumer audio and video products, pool pumps and hot tubs, vending machines, televisions, battery chargers, and various lighting applications. 208

v. Incentives and Finance Mechanisms for Energy Efficiency
Description
States offer a diverse portfolio of financing and incentive approaches that are designed to address specific financing challenges and barriers and incentivize specific markets and customer groups to invest in energy efficiency. Thes e programs include revolving loan funds, energy performance contracting, tax incentives, rebates, grants, and other incentives.
Policy Mechanics
Design
Revolving loan funds provide low-interest lo ans for energy efficiency improvements. The funds are designed to be self-supporting. States create a pool of capital that “revolves” over a multi-year period, as payments from borrowe rs are returned to the capital pool and are subsequently lent to other borro wers. Revolving loan funds can be created from several sources, including public bene fits funds (PBFs), 209 utility program funds, ge neral state revenues, or federal funding sources. Revolving funds can gr ow in size over time, depending on repayment interest rates and program administrative costs.

208 “Appliance Efficiency Regulations: California”, Databa se of State Incentives for Renewables & Efficiency, Accessed on March 19, 2014, http://www.dsireusa.org/incentives/incentiv e.cfm?Incentive_Code=CA48R&re=0&ee=0

. 209 Public benefit funds (PBFs) are dedicated funds used for supporting research and development of energy efficiency and renewable ener gy projects. Funds are norma lly collected either throug h a small charge for every electric customer or through specified contributions from utilities.124 Energy performance contracting allows the public sector to contract with private energy service companies (ESCOs) to provide buildi ng owners with energy-related efficiency improvements that are guaranteed to save more th an they cost over the co urse of the contracting period. ESCOs provide energy auditing, engineeri ng design, general contr acting, and installation services, and help arrange project financing. 210 The contracts are priv ately funded and do not involve state funding or financial incentives.
State tax incentives for energy efficiency ar e available as personal or corporate income tax credits, tax exemptions (e.g., sales tax exem ptions on energy-efficient appliances), and tax deductions (e.g., for construction programs). Tax in centives aim to spur private sector innovation to develop more energy effici ent technologies and practices a nd increase consumer choice of energy-efficient products. 211
Rebates (also known as “buy-downs”) are used to promote demand-side energy efficiency reductions by providi ng direct incentives to cust omers who purchase or make upgrades to approved efficient appliances or re trofit their homes (e.g., a utility may refund part of the cost for a homeowner to improve attic in sulation or purchase a high-efficiency furnace). Funding for rebates may come from PBFs, di rect grants, or utili ty program funds.
Grants from the federal government, state government, regional agency, or private source may be used to start or finance energy effici ency programs. A grant may be used to provide funding for a specific construction project (e.g., retrofit of a school ), finance a rebate program, initiate a revolving fund, conduct a behavior change campaign (e.g., educate public about the benefits of off-peak energy use), or any other type of program that meets the specific grant requirements.
Authority

Financial mechanisms and incentives for ener gy efficiency are run by utilities and state and local governments. Utilities primarily offer re bates, grants, and loans. Personal, corporate, sales, and property tax incen tives are mainly offered by state and local governments. 212
Implementation Status
Financial mechanisms and incentives for energy e fficiency exist in all 50 states, with the most prevalent financial mechanisms and incenti ves for energy efficiency are rebates and loan programs. There are 43 tax incentives and over on e-thousand rebate, grant, and loan programs. 213 In the first 3 years of Alaska’s Home Energy Rebate Program, the Stat e provided an estimated

210 EPA, Integrating State and Local Environmental and Energy Goals: Energy Performance Contracting. Fact Sheet (EPA, September 2004). 211 Elizabeth Brown, Harvey Sachs, Patrick Quinlan, and Daniel Williams. “Tax Credits for Energy Efficiency and Green Buildings: Opportunities for State Action.” American Council for an Energy Efficient Economy (2002). 212 “Financial Incentives for Energy E fficiency” Database of State Incentives for Renewables & Efficiency, accessed on March 19, 2014, http://www.dsireusa.org/su mmarytables/finee.cfm

. 213 Ibid.125 $110 million to help finance energy efficiency retrofits for 16,500 homeowners. Retrofitted housed are currently saving an estimated 1.6 trillion BTUs of energy annually, or 5 percent of the Alaska’s total annual energy demand for residential space heating. 214

c. Renewable Energy Policies and Programs
States have adopted a range of requirement s and programs to advance the deployment of renewable energy technologies, including renewa ble portfolio standards, performance-based incentives and public benefit funds. 215 These renewable energy policies and programs reduce GHG emissions by increasing the use of renewable energy and altering the mix of energy supply.

i. Renewable Portfolio Standards
Description
A renewable portfolio standard (RPS), also known as a renewable electricity standard (RES), is a mandatory requirement for retail electricity suppliers to supply a minimum percentage or amount of their re tail electricity load with elec tricity generated from eligible sources of renewable energy. 216 An RPS indirectly affects EGU CO 2 emissions by reducing the utilization of fossil-fuel-fired EGUs. As of June 2013, 29 states and Washington, DC have adopted a mandatory RPS (see Figure 8), although designs vary (e.g., applicability, targets and timetables, geographic and resource eligibil ity, alternative complia nce payments) and an additional nine have voluntary renewable goals. 217

214 Scott Goldsmith, Sohrab Pathan, and Nathan Wiltse, Snapshot: The Home Energy Rebate Program , (Cold Climate Housing Research Center, May 2012), Accessed on March 19, 2014, http://cchrc.org/docs/snapshots/HERP_snapshot.pdf

. 215 Feed-in tariffs, a performance-based incentive, offe r long-term purchase agreements to renewable energy electricity generators. Public benefit fu nds are typically created by levying a small fee as a part of retail electricity rates and are used to support rebate, loan, and other programs that support renewable energy deployment. For more information, see Database of State Incentives for Renewables and Efficiency , available at http://www.dsireusa.org/

. 216 In some state Renewable Portfolio Standards (alterna tively called “Alternative and Renewable Energy Portfolio Standards”), selected non-renewable so urces such as coal bed methane or ga sification are eligible for credit. 217 Database of State Incentives for Renewables an d Efficiency, March 2013, accessed on May 23, 2014, http://ww.dsireusa.org ; Alaska House Bill 306, Signed by Governor Sean Parnell June 16, 2010, http://www.legis.state.ak.us/basis/get _bill_text.asp?hsid=HB0306Z&session=26

.126 Figure 8: States with Renewable Portfolio Standards

Policy Mechanics
Design
RPS requirements typically start at modest le vels and ramp up over a period of several years. An RPS relies on market mechanisms to increase electricity generation from eligible sources of renewable energy.
Retail electricity suppliers can comply with RPS requirements through several mechanisms, which vary by state, including:

 Ownership of a qualifying renewable energy fac ility and its electric generation output,

 Purchasing electricity bundled with renewable energy certificates (RECs) 218 from a qualifying renewable energy facility, and

218 RECs represent the non-energy attributes, including a ll the environmental attributes, of electricity generation from renewable energy sources. RECs are typically issued in single MWh increments. 

### Renewable Portfolio Standards

Mandatory -

Voluntary - 29

9

Last updated 8/8/2013127  Purchasing RECs separately from electrici ty generators. Unlike bundled renewable energy, which is dependent on physical deliver y via the power grid, renewable energy certificates (RECs) can be traded between a ny two parties, regardless of their location. However, state RPS rules typi cally condition the use of RECs based on either location of the associated generation facility or whether it sells power into the state or to the regional grid.
Authority
Most state RPS are established through legi slation and administered by state PUCs.
Obligated Parties
RPS applicability varies by stat e. All state RPS apply to in vestor-owned utilities, while some state RPS obligate municipa l utilities, rural coope ratives, and/or other retail providers, often depending on a minimum numb er of customers served.
Measurement and Verification
Some state RPS include an alternative comp liance payment (ACP) option, where a retail electricity supplier may purchase compliance credits from the state at a known price, which acts as a de facto price cap, if it has not procured su fficient electricity from renewable energy sources or RECs to meet the RPS compliance requireme nt. State PUCs typi cally require annual compliance reports from retail electricity suppliers subject to a RPS. Most states use regional tracking systems (e.g., Western Renewable Ener gy Generation Information System, PJM Generation Attribute Tracking System) to issu e, track, and retire RECs for RPS compliance purposes. 219 For more information about measuremen t and verification of renewable energy, see earlier in the State Plan Consider ations Technical Support Document.
Penalties for Noncompliance
States have developed a range of compliance enforcement and flexibility mechanisms. As of 2007, despite the fact that se veral states had not achieved th e RPS targets, only Connecticut and Texas had levied fines. A $5.6 million penalt y was incurred in Connecticut in 2006. In 2003 and 2005, two competitive electricity service provide rs in Texas were pena lized a total of $4,000 and $28,000 respectively. Flexible enforcement a nd opportunities to “mak e-up” shortfalls in subsequent years or ACPs that are recycled to support other rene wable and efficiency measures have helped other states a void penalties for noncompliance. 220

219 For a summary of REC tracking systems, see: U.S. Department of Energy Renewable Energy Certificates (RECs) National REC Tracking Systems. http://apps3.eere.energy.gov/greenpower /markets/certificates.shtml?page=3 220 Ryan Wiser and Galen Barbose, Renewables Portfolio Standards in the United States – A Status Report with Data Through 2007, (Lawrence Berkeley National Laboratory, 2008)
, Accessed March 19, 2014 http://emp.lbl.gov/sites/all/files /REPORT%20lbnl-154e-revised.pdf

.128 Implementation Status
States with RPS policies have demonstrated higher levels of renewable energy capacity development. From 1998-2012, 67 percent ( 46 GW) of all non-hydro renewable capacity additions occurred in states with active or impending RPS requirements, although other factors may contribute to the grow th in renewable capacity. 221

ii. Performance-Based Incentives and Fina nce Mechanisms for Renewable Energy
Description
States offer a diverse portfolio of financi ng, performance based incen tive and state utility ratemaking approaches that are designed to addr ess specific financial challenges and barriers and help specific markets and cust omer groups produce clean energy.
Policy Mechanics
Design
States support the advancem ent of clean generation tec hnologies through performancebased incentives, including feed-in tariffs and ot her payments, or tax incentives. Performancebased incentives are paid base d on the actual energy production of a system. Feed-in tariffs establish temporarily elevated pr ice per kWh in order to encour age renewable energy innovation using high cost technologies. Tax incentives are used to lower financial barriers to renewable energy production.
A major source of funding for renewable ener gy activities comes from PBFs, but states also fund these activities through alternative so urces including direct grants, rebates and generation incentives pr ovided by utilities.
State tax incentives for renewable energy a nd Combined Heat and Power (CHP) take the form of personal or corporate income tax cred its and tax exemptions. State tax incentives for renewable energy are a common policy tool, main ly using credits on personal or corporate income tax and exemptions from sale s tax, excise tax, and property tax.
Authority

Financial mechanisms and incentives for rene wables are run by util ities, non-profits, and state and local government. Personal, corporate, sa les, and property tax incentives are mainly offered by state and local government. 222

221 Ibid. 222 “Financial Incentives for Renewable Energy”, Databa se of State Incentives for Renewable Energy, accessed March 19, 2014, http://www.dsireusa.org/summarytables/finre.cfm

.129 Implementation Status

Financial mechanisms and incentives for rene wable energy of some form exist in most states. According to the Database of State Incentives for Renewa ble Energy (DSIRE), there are over 200 tax incentives. In addition, nearly a hun dred performance based incentives are offered from state and local governments, as well as utilities and non-profits. 223
There are currently 18 states that have stat e-wide performance-based policies, and in several other states utilities have adopted programs based on performance-based incentives, including feed-in tariffs, standard offer paym ents, and payments in exchange for RECs. 224 In many cases, however, PBI is limited to customer-s ited projects or limited by size eligibility.
Financial incentives, working in concert with a strong R PS and net metering policies, have contributed to the rapid growth in solar power deployment in New Jersey. The state’s RPS includes a minimum carve-out for solar sources, a nd allows solar energy ge nerators to earn Solar Renewable Energy Certificates (SRECs) that can th en be sold to electric ity suppliers trying to meet the minimum solar production and/or pur chase requirement. As a result of these interdependent policies, solar pho tovoltaic facilities ar e increasing, with inst allations more than doubling from 2010 through 2011. 225 New Jersey ranks second only to California in terms of total installed capacity. 226

d. Utility Planning Approaches and Requirements
Description
Some public utility commissions require util ities to conduct portfolio management or integrated resource planning (IRP) to ensure the supply of least cost and stable electric service to customers over the long term. Portfolio manage ment refers to energy resource planning that incorporates a variety of energy resources, incl uding supply-side (e.g., traditional and renewable energy sources) and demand-side (e.g., energy e fficiency) options. The term "portfolio management" typically describes resource pla nning and procurement in states that have restructured their electric indus try and may be required for defau lt service providers (the backup electric service provider in areas open to comp etition). IRP is generally used by vertically integrated utilities and is a long-range planni ng process to meet forecasted demand for energy within a defined geographic ar ea through a combination of suppl y-side resources and demandside resources and considering a broad range of perspectives. The goal of an IRP is to identify

223 Ibid. 224 Ibid. 225 Solar-New Jersey.org, “Why has New Jersey become a Leader in Solar in the U.S.?” Solar-New Jersey.org
, August 15, 2012, Accessed March 19, 2014, http://www.solar-new-jersey.org/ 2012/08/15/why-has-new-jerseybecome-a-leader-in-solar-in-the-us/

. 226 “Open PV State Rankings”, National Renewable Energy Laboratory, Accessed March 19, 2014, https://openpv.nrel.gov/rankings

.130 the mix of resources that will minimize future energy system costs while ensuring safe and reliable operation of the system.
In addition to energy resource planning, two st ates have policies or requirements for utilities to specifically factor pollution reduction requirements in to their planning. In Colorado, the Clean Air Clean Jobs Act (CACJA), signed into law on April 19, 2010, required utilities to submit a plan to the PUC showing how they would meet EPA standa rds for a variety of pollutants. 227 The law was passed because the state wa s out of compliance with the national Ambient Air Quality Standard for Ozone, and the EPA threatened to propose more stringent standards for the state.
In 2001, Minnesota enacted Minnesota Statut e 216B.1692, which encourages utilities to make voluntary emission reductions and provides them with a mechanism to recover the costs through customer rate increases outside of the normal rate review cycle. 228
Policy Mechanics
Design

 Portfolio Management and IRP - Portfolio ma nagement emphasizes diversity in fuels, technologies, and power supply contract durations. Portfolio management includes energy efficiency and renewable generation as key strategic components. Portfolio management typically involves a multi-step process of forecasting, resource identification, scenario analysis , and resource procurement.
Several states and vertically integrated u tilities rely on an IRP process for long-term planning. Since these utilities own generation assets, they use their IRPs to evaluate a broad range of options for mee ting electricity demand over a 20- or 30-year time frame. The IRP considers new supply-side options (including renewable resources) and demandside options, and purchased power (includi ng transmission considerations). A broad range of plans are considered, reflecti ng a range of objectives and capturing key uncertainties. Plans are evaluated against esta blished criteria (e.g., costs, rate impacts, emissions, diversity, etc.) and are ranked. Th e IRPs detail fuel and electricity price information, customer demand forecasts, ex isting plant performance, other plant additions in the region, and legislative d ecisions. The following examples show how various states have designed their programs:

o Montana is a deregulated state that has established least cost planning rules and policy guidelines for default electricit y suppliers. These rules and guidelines

227 RAP, Addressing the Effects of Environmental Regulations: Market Factors, Integrated Analyses, and Administrative Processes (Regulatory Assistance Project, 2013), Accessed March 19, 2014, www.raponline.org/document/download/id/6455

. 228 Minnesota PUC, Report To The Legislature On Emissions Reduction Projects Under Minnesota Statutes 216B.1692 (Minnesota Public Utilities Commission, 2008), Accessed March 19, 2014, http://www.puc.state.mn.us/portal/group s/public/documents/pdf_files/000661.pdf.131 target long-term electricity supply and are slightly different for vertically integrated utilities and restructured utilitie s. Vertically integr ated utilities are required to submit electric supply resource plans every two year s with the aim of providing a balanced, environmentally responsible electricity portfolio. Meanwhile, restructured utilities must f ile updates to their po rtfolio action plans every three years. 229 These plans must include supply-side and demand-side resources, and they must address the need to supply power in a way that minimizes the environmental cost by estim ating the cost to the environment of alternatives. In addition, u tilities must account for the costs of complying with existing and future environmental regulat ions. When considering various resource options, Montana requires a competitive solicitation process, allowing resource operators and developers to submit thei r proposals to the default electricity supplier for consideration. M ontana also requires the por tfolio management plans to be subject to an advisory co mmittee review and a public review. 230

o Oregon electric utilities submit IRPs every two years, covering a 20-year timeframe. The goal of these plans is to consider the acquisiti on of resources at least cost while keeping the public interest in mind. Potential risk factors must be considered, including price volatility, weat her, and the cost of meeting existing and future federal environmental re gulations. Quantifiable environmental externalities are included, as are less qua ntifiable developments such as changes in market structure and the establishmen t of a renewable portfolio standard. As for energy efficiency requirements during the planning process, Oregon determines these on a utility-by-utility basis. 231

 Multi-Pollutant Utility Planning – Two states, Minnesota and Colorado, have worked collaboratively with their investor-owned u tilities to develop multi-pollutant emission reduction plans on a utility-wide basis. This multi-pollutant, collaborative approach enables utilities to determine the least cost way to meet long-term and comprehensive energy and environmental goals.

o The Colorado CACJA requires investor-owned utilities (IOUs) with coal plants to submit a multi-pollutant plan to the PUC to meet the EPA standards for NO x , SO 2 , particulates, mercury, and CO 2 . Utilities were not required to adopt a specific plan set by the state, but had to meet with Co lorado Department of Public Health and

229 Wilson, Rachel an d Bruce Biewald, Best Practices in Electric Utility Integrated Resource Planning (Regulatory Assistance Project, 2013), Accessed March 19, 2014, http://www.raponline.org/document/download/id/6608

. 230 U.S. EPA, Clean Energy-Environment Guide to Action (U.S. Environmental Protection Agency, 2006), Accessed March 19, 2014, http://epa.gov/statelocalclimate/resources/action-guide.html. 231 Ibid.132 Environment (CDPHE) and PUC approval. Xcel Energy’s plan was submitted and approved in 2010. 232

o The Minnesota Emission Reductions Rider allows utilities to submit plans for projects that reduce emissions and go beyond federal requirements outside of a general rate case. It allows them to recover the costs of those actions as an incentive. 233 The specific design and process of the projects vary by utility, but typically involve installing additional po llution control equipment at coal-fired power plants, or repowering them with natural gas.
Authority
State utility commissioners oversee utilities’ and default service providers’ procurement practices in their states. Typi cally, the commissions solicit comments and input as they develop portfolio management practices from a wide vari ety of stakeholders. Th e utility regulator may also play a role in reviewing and approving uti lities’ planning procedur es, selection criteria, and/or their competition solicitation processes.
Obligated Parties
Vertically integrated utili ties are often obligated under in tegrated resource planning, while in restructured markets, the default util ity service provider may be obligated to conduct portfolio management.
For multi-pollutant planning, Colorado IOUs, Xcel Energy and Black Hills Energy were required to file plans with the Department of Public Health and Envi ronment and the PUC in order to be compliant with the CACJA. Plans ne eded to meet the National Ambient Air Quality Standards for a number of air pollutants.
As the Minnesota multi-pollutant legislation is vo luntary for state utilities, there is neither compliance nor reporting requirements.
Measurement and Verification
Regulatory oversight aims to ensure utilit ies are following through with their plans. Regulators often require utilitie s to submit portfolio management plans and progress reports at regular intervals. These plans and reports de scribe in detail the assumptions used, the opportunities assessed, and the decisions made wh en developing resource portfolios. Regulators then carefully review these plans and either approve them or reject them and recommend

232 RAP, Addressing the Effects of Environmental Regulations: Market Factors, Integrated Analyses, and Administrative Processes (Regulatory Assistance Project, 2013), Accessed March 19, 2014, www.raponline.org/document/download/id/6455

. 233 Minnesota Office of Revisor of Statutes, 2013 Minnesota Statutes, §216B, 1692 Emissions Reduction Rider, 2013, Accessed March 19, 2014, https://www.revisor.mn.gov/statutes/?id=216B.1692

.133 changes needed for approval. California, for exam ple, requires utilities to submit biennial IRPs and quarterly reports on their plans.
Penalties for Noncompliance
There are no penalties for nonc ompliance, however there is usually significant interaction with the regulator during the planning and implementation process as is described above.
Implementation Status
Currently more than half of the states ha ve integrated resource or other long-term planning requirements, 234 while Minnesota and Colorado have multi-pollutant planning policies or requirements (see Figure 9).
In Montana, for example, the 2011 Electri c Supply Resource Plan for NorthWestern Energy calls for:

 Shortening the length of power supply contracts from seven years to a more competitive, staged process of between three to five years.

 Diversifying Montana’s resource mix with the recent addition of a 150 MW gas-fired power plant.

 Improving the integration of intermittent power sources into the power supply as new wind turbines play a larger ro le in the state’s resource mix.

 Meet state RPS requirements.

 Acquire cost-effective demand side management resources, targeting 6 MW of additional energy conservation per year.

 Monitor market, regulator y, and technology changes to better manage risks and opportunities. 235

234 Wilson, Rachel an d Bruce Biewald, Best Practices in Electric Utility Integrated Resource Planning (Regulatory Assistance Project, 2013), Accessed March 19, 2014, http://www.raponline.org/document/download/id/6608

. 235 NorthWestern Energy, Electric Supply Resource Plan (NorthWestern Energy, 2011), accessed March 19, 2014, https://www.northwesternenergy.com/our-company/tariffs-a nd-rates/montana-tariffs-and-rates/electric-supplyresource-procurement-plan

.134 Figure 9: States with Integrated Reso urce Planning or Similar Processes

In Oregon, PacifiCorp has filed its 2013 inte grated resource plan. Key highlights from the report include:

 Demand-side energy efficiency efforts are expect ed to meet 67 percent of electricity load growth from 2013 to 2022

 Market analyses for integrat ing wind resources into the grid, and pursuing opportunities for combined heat and power resources.

 Goals to obtain 1,425-1,876 GWh of energy efficiency resources by 2015 and 2,034- 3,180 GWh by 2017.

 Permitting and development efforts to conve rt a unit of the Naughton power plant from coal to gas. 236
To meet Colorado’s multi-pollutant planning requirement, Xcel Energy submitted a plan that was approved by the Colorado PUC on December 9, 2010. Implementation of the plan will reduce NO x levels 88% and CO 2 levels 28% relative to 2008 levels by 2018. 237 Black Hills Energy has also filed its electric resource plan (ERP). This plan includes the retirement of a coalfired power plant and two older natural gas-fired gas units, as well as a proposal to build a 40

236 PacifiCorp, Integrated Resource Plan (PacifiCorp, 2013), Accessed March 19, 2014, http://www.pacificorp.com/content/dam/pacificorp/doc/Ene rgy_Sources/Integrated_Resource_Plan/2013IRP/Pacifi Corp-2013IRP_Vol1-Main_4-30-13.pdf. 237 Xcel Energy, Xcel Energy-Emissions Reduction Plan , (Xcel Energy, 2011), accessed March 19, 2014, https://www.xcelenergy.com/staticfiles/xe/Corporate/Environment/10-12-303_CACJ-6E_FS.pdf

.135 MW natural gas turbine. It plans to add 100 MW of capacity by 2017, Black Hills Energy will use competitive bidding to meet the remaining 60 MW. 238
In Minnesota, projects currently implemen ted under the multi-po llutant legislation include the Minnesota Power’s Arrowhead Regi onal Emissions Abatement (AREA) Project, Minnesota Power’s Boswell 3 Emissions Reduc tion Plan, Xcel Energy’s Mercury Reduction Plan, and Xcel Energy’s Metropolitan Emissions Reduc tion Proposal (MERP). MERP, authorized in 2002, has shown a 93% reduction in SO 2 , 91% reduction in NO x , 81% reduction in mercury, 55% reduction in partic ulates, and 21% reduction in CO 2 from 2007-2009. 239

238 Black Hills Energy, “Black Hills Energy Files Plan fo r Ongoing Reliable, Cost-effective Energy for Years to Come in Colorado” accessed on March 19, 2014, http://www.black hillsenergy.com/node /34671#.UzH kuIXYhIt

. 239 Xcel Energy, “Minnesota Metro Emissions Reduction Project – Environmental Benefits,” accessed March 19, 2014, https://www.xcelenergy.com/Environment/Doi ng_Our_Part/Clean_Air_Projects/MN_MERP

.136 List of Acronyms
ACEEE - American Council for an Energy Efficient Economy ACP - Alternative Compliance Payment BSER – Best System of Emission Reduction CACJA - Clean Air Clean Jobs Act CCR – Cost Containment Reserve CHP – Combined Heat and Power CEMS – Continuous Emissi ons Monitoring System CO 2 – Carbon Dioxide CO 2 e – Carbon Dioxide Equivalent CDPHE – Colorado Department of Public Health and Environment DOE – Department of Energy DSIRE - Database of State Ince ntives for Renewable Energy EERS – Energy Efficiency Resource Standard EGU – Electricity Generating Unit EIA – Energy Information Administration EM&V – Evaluation, Measurement, and Verification EPA – Environmental Protection Agency ERP – Electric Resource Plan ESCO – Energy Service Company GDP – Gross Domestic Product GHG – Greenhouse Gas GW – Gigawatt (1 GW = 1,000 MW) GWh – Gigawatt-hour (1 GWh = 1,000 MWh) IECC - International Energy Conservation Code IOU – Investor-Owned Utility IRP – Integrated Resource Planning kWh – Kilowatt-hour LBNL – Lawrence Berkeley National Laboratory LDC – Local Distribution Company MERP - Metropolitan Reduction Proposal MMBTU – Million British Thermal Units MW – Megawatt MWh – Megawatt-hour (1 MWh = 1,000 kWh) NOx – Nitrogen Oxides PBF – Public Benefit Funds PBI – Performance-based Incentives RGGI – Regional Greenhouse Gas Initiative REC – Renewable Energy Certificate RES – Renewable Energy Standard RPS – Renewable Portfolio Standard PUC – Public Utility Commission SO 2 – Sulfur Dioxide VEIC – Vermont Energy Investment Corporation WAP – Weatherization Assistance Program