EXTERNAL REVIEW DRAFT 3/30/11
&EPA
United States
Environmental Protection
ABBBCV
Roadmap for Incorporating Energy
Efficiency/Renewable Energy
Policies and Programs into State
Implementation Plans/Tribal
Implementation Plans
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EPA-456/D-11-001
Roadmap for Incorporating Energy Efficiency/Renewable Energy
Policies and Programs into State Implementation Plans/Tribal Implementation Plans
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Outreach and Information Division
Research Triangle Park, North Carolina
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Outreach and Information Division
Research Triangle Park, North Carolina
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ACKNOWLEDGMENTS
We would like to acknowledge substantial contributions from members of an inter-office
EPA team that included the Office of Atmospheric Programs, Air Quality Policy
Division/Office of Air Quality Planning and Standards, the Office of Policy Analysis,
Office of General Counsel and Regions 1 and 6.
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Table of Contents
SECTION 1.0: PURPOSE AND DOCUMENT ORGANIZATION 7
This Document Is Clarifying Existing Guidance And Is Not Regulation 10
Document Organization 11
SECTION 2.0: DECISION HUB TO DETERMINE PREFERRED PATHWAY(S) 13
Decision-Making Process 13
SECTION 3.0: FUTURE BASELINE PATHWAY 19
EGU Emissions Baseline Projection Options for State, Tribal and Local Agencies 19
Baseline Conditions To Be Met 20
Mandatory Policies That Are Not Traditionally, Federally Enforceable 20
SECTION 4.0: CONTROL STRATEGY PATHWAY 21
Control Strategy Option Is Traditionally, Federally Enforceable 22
Basic Steps For Quantifying Mandatory EE/RE Policies 22
SECTION 5.0: EMERGING/VOLUNTARY MEASURES PATHWAY 23
SECTION 6.0: WEIGHT OF EVIDENCE (WOE) PATHWAY 25
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Appendices
Appendix A: Glossary 31
Appendix B: Overview of the U.S. Electric System 36
Appendix C: Existing Energy Efficiency/Renewable Energy Guidance 42
Appendix D: Understanding State Renewable Energy and
Energy Efficiency Policies 51
Appendix E: Baseline Pathway 57
Appendix F: Control Strategy Pathway 65
Appendix G: Emerging/Voluntary Measures Pathway 89
Appendix H: Weight of Evidence (WOE) Pathway 92
Appendix I: EPA's Draft Methodology for Estimating Energy Impacts of
EE/RE Policies 95
Appendix J: State Examples and Opportunities 122
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Figure 1.1: Growth in State Energy Efficiency Expenditures 9
Figure 1.2: Growth in State RPS Policies 9
Figure 1.3: Organization of Manual 10
Figure 1.4: How to Use the Appendices 12
Figure 2.1: EE/RE SIP/TIP Pathway Flow Chart 15
Figure 2.2: Characteristics of Policies/Programs Suitable for Each Pathway 16
Figure 3.1: Manual Roadmap for Baseline Pathway 19
Figure 4.1: Manual Roadmap for Control Strategy Pathway 21
Figure 4.2: Four Criteria Control Strategy Pathway Must Address 22
Figure 5.1: Manual Roadmap for Emerging/Voluntary Measures Pathway 23
Figure 6.1: Manual Roadmap for WOE Pathway 25
Figure B.I: System Flow of Electricity 38
Figure B.2: NERC Interconnections 39
Figure B.3: Unit Dispatch in a Power System 40
Figure F.I: Capacity Factor Approach 78
Figure F.2: eGRID2010 Subregion Representational Map 80
Figure J.I: Steps for New Mexico Analysis 128
Figure J.2: Key Pieces of NESCAUM Multi-Pollutant Framework 131
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Table 2.1: Key Aspects of Three SIP EE/RE Pathways 17
Table D.I: Brief Overview of RE/EE Policies for Three States 55
Table E.2: EE/RE Policies State X Explicitly Included in Baseline Projections 63
Table F.I: Allocating Displaced Energy Using the Capacity Factor Approach 79
Table F.2: Egrid Non-Base load Emission Rates in 2007 81
Table F.3: Displaced Emissions Methodology Comparisons 82
Table 1.1: EMM Region Mapping and AEO2010-based Sales Growth Rates
by State 98
Table 1.2: Energy Efficiency Savings Estimated to be Embedded in AEO2010 101
Table 1.3: Measure Lifetime by State 102
Table 1.4: Levelized Cost of Saved Energy by State 107
Table 1.5: EPA Base Case Region Mapping for IPM 110
Table 1.6: Sectoral Shares of Savings 112
Table 1.7: RPS Requirements Used to Model Regional RPS Impacts for AEO2010 ..115
Table J.I: Hypothetical Example for Albuquerque-Bernalillo 129
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SECTION 1.0: PURPOSE AND DOCUMENT ORGANIZATION
The purpose of this roadmap is to clarify guidance1 EPA specifically issued in 2004 on
incorporating energy efficiency and renewable energy (EE/RE) policies and programs
into State Implementation Plans (SIPs), as well as related guidance EPA issued in that
year and in 2005. EE/RE policies and programs are cost effective strategies that state,
tribal or local agencies can utilize to help meet air quality goals, SIP and Tribal
Implementation Plans (TIP)3 requirements (i.e., emissions reductions needed to
demonstrate attainment and/or satisfy other Clean Air Act requirements).4
EPA recognizes that state, tribal or local agencies interested in incorporating these
policies and programs in SIPs/TIPs need more detailed information on how to achieve
that goal. EE/RE
programs can also be
part of a multi-pollutant ..... .t . , , , t t , , t ., , ..
. . . »What criteria should a state, local or tribal agency consider
emissions reduction when choosjng the best pathway for incorporating
strategy to help state,
tribal and local agencies
not just attain and
maintain compliance
with NAAQS, but also
to improve visibility
and reduce regional
haze, reduce air toxics
and greenhouse gases.
To that end, this
Questions Manual Addresses
measures/programs in SIPs/TIPs?
•What SIP/TIP criteria and other requirements should be satisfied
when incorporating EE/RE policies into SIPs/TIPs?
• For the control strategy pathway, what EE/RE quantification
requirements and general guidelines are available?
•What streamlined approaches are available for state, local and
tribal agencies to utilize when accounting for EE/RE policies in
SIPs/TIPs?
• Is some kind of discount factor necessary to reflect uncertainty,
not holding EE/RE measures to a higher standard than other
document provides a SIP/TIP measures?
roadmap for
understanding the requirements and other aspects of the four pathways available for
incorporating EE/RE policies and programs into SIPs/TIPs:
1. Projected emissions baseline for the future attainment year;
1 "Guidance on SIP Credits from Emission Reductions from Electric-Sector Energy Efficiency and
Renewable Energy Measures," USEPA, http://www.epa.gov/ttncaaal/tl/memoranda/ereseerem gd.pdf.
August 2004.
2 "Incorporating Emerging and Voluntary Measures in a State Implementation Plan (SIP)," USEPA,
http://www.epa.gov/ttncaaal/tl/memoranda/evm ievmg.pdf. September 2004 and "Guidance on
Incorporating Bundled Measures in a State Implementation Plan," USEPA,
http://www.epa.gov/ttn/caaa/tl/memoranda/10885guideibminsip.pdf. August 2005.
3 The 1990 CAA Amendments provide authority for Tribes to implement CAA programs and instructed
EPA to adopt regulations so that eligible Tribes may manage their own EPA-approved air pollution control
programs under the CAA. The 1998 Tribal Authority Rule (TAR) implements the provisions of section
301(d) of the CAA to authorize eligible Tribes to develop their own tribal programs. Under the TAR, a
Tribe may be approved by EPA to be eligible to be treated in the same manner as a State for one or more
CAA programs. Such a program may include, but is not limited to, a Tribal Implementation Plan (TIP).
As the TAR makes clear, tribal governments are not required to submit a TIP, nor are they subject to
deadlines mandated under the CAA. However, EPA must meet its obligations under the CAA.
4 The other requirements include: Reasonable Further Progress, Rate of Progress, and Reasonable
Available Control Technology/Reasonable Available Control Measures.
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2. SIP control strategy;
3. Emerging/voluntary measures; and
4. Weight-of-evidence (WOE) determination.
In doing so, the manual addresses several key policy issues, as described in the text box
above.
EPA believes it is important to recognize the emission benefits resulting from EE/RE
policies and programs in SIPs and TIPs. Therefore, EPA is encouraging state, tribal and
local agencies to incorporate EE/RE policies into SIPs/TIPs (or to account for them in
SIPs/TIPs) because these policies represent a real opportunity for state, tribal and local air
quality planners to take advantage of the emission benefits of the policies. Three reasons
are:
1) Over the past 10 years, states have increased their EE/RE investments by 209
percent, committing over $3 billion of ratepayer resources in 2009 to energy
efficiency programs.5 (See Figure 1.1 for ratepayer EE expenditures from 2000-
2009.) Also, as of 2009, thirty states (including Washington, DC) had adopted
renewable portfolio standard (RPS) which require their utilities to purchase
increasing amounts of their electricity supply from renewable resources, more
than double the number states in 2000 (see Figure 1.2).
2) EPA has issued revised National Ambient Air Quality Standards for ozone, SO2,
PM2.5 and NO2 that continue to drive the need to find greater emission reductions.
EPA is encouraging state, tribal and local agencies to incorporate EE/RE policies
and programs into SIPs/TIPs as they face a need to find greater pollutant
reductions from the electric power generation sector to meet these revised
standards. Moreover, the availability of EE permits the state, tribal and local
agencies to diversify the control measures being considered beyond the traditional
measures considered for point sources.
3) Improved precision and rigor for information related to the energy savings from
energy efficiency, what generation resources are displaced by EE/RE and their
resulting emissions benefits is more widely available so state, tribal and local
agencies do not have to start analyses from scratch.
5 "2010 State Energy Efficiency Scorecard," American Council for an Energy-Efficient Economy,
http://www.aceee.org/sites/default/files/publications/researchreports/el07.pdf. October 2010.
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Figure 1.1: Growth in State Energy Efficiency Expenditures
OCtO
/
^^
^,- — ^
2000 2003 2006 2007 2008 2009
1
Source: www.aceee.org/publications
Figure 1.2: Growth in
MA CT
(2OO3) (2OOO)
ME PA NJ
(2OOO) (20O1) (2OO1)
M N AZ N V Wl TX N M
(2002) (1999) (2001) (2OOO) (2OO2) (2OO2)
•1983 1991 199-4 1996 1997 1998 1999 2OOO 2OO1
IA MN AZ MN
WI NV
^^H Enactment (above timeline)
^^| Major Revisions (below timeline)
( ) Year of First Requirement
1 Source: www.cleanenerRvstates.orR/MeetinRs/RPS
-
State RPS Policies
CO
(2OO7)
HI
(2OO5)
MD DC
(2OO6) (2OO7)
NY DE
(2OO6) (2OO7)
CA Rl MT WA
(2003) (2007) (2008) (2O12)
2OO2 2O03 20O4 ZOOS 2OO6
NM CT NJ CT AZ
MN NM CO CA
NV PA NV CT
TX HI
NJ
Wl
Summit 09/WISER RPS
|
ll_
(2OO8)
NH Ml
(2OO8) (2O12)
NC MO
(2O1 O) (2O1 1 )
OR OH KS
(2011) (2009) (2011)
2OO7 2OO8 2OO9
CA DC HI
CO DE IL
CT MA ME
DE MD MN
MD NJ NV
ME NH OR
MN Rl
NJ
NM
PA
TX
Surnmit2009.pdf
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An EE/RE policy/program that is qualified under one of the four pathways described in
this manual may help air quality agencies to improve their collaboration with state public
service commissions and energy offices. If these energy-related offices understand that
the state is relying upon the emissions benefits from EE/RE for the SIP, then the offices
can work with the air agency at the planning stage to help design effective EE/RE
policies/programs. And, the energy office or public service commission has a role to
ensure that the emissions benefits are achieved.
This Document Is Clarifying Existing Guidance And Is Not Regulation
This document is being issued to clarify existing guidance and not create new guidance.
In addition, the Clean Air Act and implementing regulations at 40 CFR Part 51 contain
legally binding requirements. This manual does not substitute for those provisions or
regulations, nor is it a regulation itself. Thus, it does not impose binding, enforceable
requirements on any party, and may not be applicable in all situations.
This manual pertains only to the stationary source sector and does not does not apply to
mobile source emission reduction programs, including on-road and non-road vehicles.
Guidance on mobile source strategies can be found at:
http://www.epa.gov/otaq/stateresources/policy/pag transp.htm. For more information
about how to take credit for a voluntary mobile source emission reduction program, see
http://www.epa.gov/otaq/stateresources/policy/general/vmep-gud.pdf).
The EPA and state, tribal and local agency decision makers retain the discretion to adopt
approaches for approval of SIPs/TIPs that differ from this guidance where appropriate
and consistent with applicable
law. Any final decisions by
EPA regarding a particular SIP
will only be made based on the
statute and regulations within the
context of EPA notice-and-
comment rulemaking on a
submitted SIP revision.
Therefore, interested parties may
raise questions and objections
about the substance of this
guidance and appropriateness of
its application to a particular
situation. The EPA will, and
state, tribal and local agencies
should, consider whether or not
the recommendations in the
guidance are appropriate in a
particular situation. This
Figure 1.3: Organization of Manual
Decision Hub to Choose
Pathway
Section 2.0
Future Baseline Pathway
Section 3.0
Control Measure Pathway
Section 4.0
Emerging/Voluntary
Measures Pathway
Section 5.0
Weight of Evidence Pathway
Section 6.0
Information on All Three
Pathways
Appendices
guidance is a living document
and may be revised periodically
without public notice. However,
the EPA welcomes public comments on this document at any time and will consider
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those comments in any future revision of this guidance document. Finally, this document
does not prejudice any future final EPA decision regarding approval of any SIP.
This document is organized to provide a roadmap to show the options available for
incorporating EE/RE policies and programs into SIPs/TIPs once state, tribal and local air
quality planners understand the EE/RE policies and programs in their area. To achieve
that goal, the main body of the report is intentionally short. However, the Appendices
describe the mechanics and pathways state, tribal and local agencies interested in
SIPs/TIPs can account for EE/RE may take. References to outside sources are also
provided. (For links to sources external to EPA, note that EPA cannot attest to the
accuracy of non-EPA information provided by these third-party sites or any other linked
site. EPA is providing these links for your reference. In doing so, EPA does not endorse
any non-government websites, companies or applications.) Figure 1.3 provides the
organization of the manual. Figure 1.4 describes each appendix and its use.
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Figure 1.4: How to Use the Appendices
Four Pathways:
Projected emissions baseline for the future attainment year
SIP control strategy
Emerging/voluntary measures
Weight-of-evidence (WOE) determination
For
appendices
that apply
generally to
all four
options, see:
•Appendix A for glossary of energy and air quality terms
•Appendix B for information on how power distribution works in an area
•Appendix D for the fundamentals of EE/RE policies and some key
information to determine what policies and programs your area has
adopted and is implementing.
•Appendix F for an easy way to obtain a rough estimate of the emissions
benefits from EE/RE policies and programs.
•Appendix I for information on energy savings from EE/RE policies that
are "on the books"
• Appendix J for state examples of past or proposed incorporation of
EE/RE in SIPs
For the
baseline
option,
see:
•Appendix C.2 for information on existing EPA baseline guidance
•Appendix E for the requirements of the baseline pathway
For the
control
strategy
option, see:
•Appendix C.3 for information on existing EPA control strategy guidance
•Appendix F for the requirements of the control strategy pathway
For the
emerging/
voluntary
measures
option, see:
•Appendix C.4 for information on existing EPA voluntary/emerging measures
guidance
•Appendix G for the requirements of the voluntary/emerging measures pathway
For the WOE
option, see:
•Appendix C.5 for information on existing EPA WOE guidance
•Appendix H for the requirements of the WOE pathway
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SECTION 2.0: DECISION HUB TO DETERMINE PREFERRED
PATHWAY(S)
The intent of the decision hub section is to help state, tribal and local agencies navigate
through the many decisions each will encounter when deciding if and how to incorporate
EE/RE policies and programs in a SIP. EPA has identified the most important EE/RE
policy/program characteristics and questions state, tribal and local agencies should
consider when determining which pathway they can take to account for the emission
impacts of EE/RE policies and programs in a SIP. State, tribal and local agencies can
apply their unique situation and needs to the EE/RE SIP Pathway Flow Chart (Figure 2.1)
to help determine which pathway fits best for each applicable EE/RE policy and program.
For more information on specific requirements, documentation and quantification
methods refer to the appendix sections listed in Figure 2.1.
Decision-Making Process
The first task is to become familiar with the jurisdiction's EE/RE policies and programs,
the electric system, the level of magnitude of potential emission benefits and existing
EPA EE/RE SIP guidance. Certain terms are important to understand:
• Energy efficiency/renewable energy policies are regulations, statutes or state
public utility commission orders that require parties to acquire energy efficiency
and/or renewable energy or to commit to funding levels for programs aimed at
acquiring EE/RE.
• Energy efficiency program means a program designed to increase adoption of
energy efficient technologies and practices in particular end-use sectors through
education and outreach, codes and standards, financial incentives, and/or technical
assistance.
• Renewable energy program means a program designed to increase the
production and use of renewable energy sources through resource procurement
and development, education and outreach, financial incentives, and/or technical
assistance.
Once a state, tribal or local agency has reviewed existing and upcoming EE/RE policies
and programs in its jurisdiction, and the potential emissions benefits those policies and
programs may offer, the next task is to determine what SIP pathway(s) to pursue for each
EE/RE policy and program. There are some key questions to consider for each of the
jurisdiction's EE/RE policies and programs (see Figure 2.1). Are the jurisdiction's
policies and programs "on the books" (i.e., been adopted by a legislative or regulatory
body) and does the jurisdiction have any voluntary or emerging programs? Those terms
are defined as follows:
• A voluntary program is a "measure" or "strategy" that is not enforceable against
an individual source or entity.
• An emerging program is a "measure" or "strategy" that does not have the same
high level of certainty as traditional measures for quantification purposes.
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If a Jurisdiction wants to include EE/RE policies and programs in the voluntary/emerging
pathway:
On either side of the flowchart, if a jurisdiction has existing or upcoming voluntary
and/or emerging programs and wants SIP/TIP credit for the emission reductions, then it
should consider the emerging/voluntary measures pathway. Otherwise, the WOE
pathway would be the appropriate option.
If a Jurisdiction does not want to include EE/RE policies and programs in the
voluntary/emerging pathway:
On either side of the flowchart, if a jurisdiction is not including an EE/RE policy or
program in the voluntary and/or emerging pathway, then it can consider two or three of
the other pathways. Which of the three pathways a jurisdiction chooses depends upon
whether the EE/RE policy/program is:
• "On the books" (i.e., been adopted by a legislative or regulatory body) or
• "On the way" (i.e., planned for adoption by a legislative or regulatory body prior
to submittal of the SIP to EPA).
It also depends upon whether the state, tribal or local agency wants the EE/RE
policies/programs to be incorporated into the SIP/TIP such that they can be discretely,
traditionally enforceable by the federal government as a control strategy.
The flowchart provided in Figure 2.1 can be used to guide jurisdictions to ask these
questions for each of its EE/RE policies and programs. Going through this exercise will
help the jurisdiction consider how to group the EE/RE policies/programs into the
appropriate SIP pathway:
• For the "on the books" policies and programs that will not become traditionally,
federally enforceable as a control strategy, proceed to Section 3.0 and Appendix E
for more information on the baseline pathway. (Although Figure 2.1 does not
show it, a state, tribal or local agency could also pursue the WOE pathway for "on
the books" policies/programs if it decided against the baseline and control
strategy pathways.)
• For policies that are "on the way" regulations that will become traditionally,
federally enforceable as a control strategy, proceed to Section 4.0 and Appendix F
for more information on the control strategy pathway.
• For EE/RE programs that are emerging/voluntary, proceed to Section 5.0 and
Appendix G for more information on the emerging/voluntary measures pathway.
• For EE/RE policies/programs for which the area is not seeking SIP credit, proceed
to Section 6.0 and Appendix H for more information on the WOE pathway.
With each question in the flowchart process, there are tradeoffs. Table 2.1 describes key
characteristics of each pathway, including pros and cons. Figure 2.2 provides a summary
of key characteristics of the policies and programs that could be considered for each
pathway.
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Figure 2.1: EE/RE SIP/TIP Pathway Flow Chart
Learn About EPA EE/RE Guidance, Electric System and EE/RE Policies and Programs in the
Jurisdiction
See Appendices A, B and C
Does the
jurisdiction
have EE/RE
emerging or
voluntary
programs?
books" EE/RE
emerging or
voluntary
On the books"
EE/RE policies and
On the way"
EE/RE policies and
programs in the
jurisdiction
Repeat
process for
each
policy/
program
programs in the
jurisdiction
Does the area
want SIP/TIP
credit under
EPA's
emerging/
voluntary
measures
olicy"
Emerging/Voluntary
Measures Pathway
See Section 5,0
and Appendix G
Emerging/Voluntary
Measures Pathway
See Section S.O
and Appendix G
WOE Pathway
See Section 6.O
and Appendix H
Baseline Pathway
See Section 3.O
and Appendix D
Control Strategy
Pathway
See Section 4.0
and Appendix
Note: This flowchart is intended to accommodate most EE/RE policies/programs, but not necessarily all.
State, tribal and local agencies should consult with EPA regional offices on individual policies/programs
that the flowchart does not address.
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Figure 2.2: Characteristics of Policies/Programs Suitable for Each
Pathway
Future Baseline
Pathway
• "On the books"
policies and
programs
•Can be state
enforceable
• Not traditionally,
federally enforceable
but enforceable
through a Clean Air
Act SIP call
Control Strategy
Pathway
• "On the way" policies
and programs
• EE/RE policies and
programs for which
area wishes to seek
SIP credit
•Traditionally,
federally enforceable
Emerging/Voluntary
Measures Pathway
• Locally-based EE/RE
activities
•Voluntary EE/RE
policies and
programs are not
enforceable against a
source
• Emerging EE/RE
policies and
programs that are
not easy to quantify
• EE/RE policies and
programs for which
area wishes to seek
SIP credit
Weight-of-Evidence
Pathway
• Emerging/voluntary
measures
• "On the way" or "on
the books" EE/RE
policies and
programs
• Not federally
enforceable
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Table 2.1: Key Aspects of Three SIP EE/RE Pathways
Pathway Pros
Future
Baseline
Option
State, tribal and local agencies can
utilize EPA's EGU baseline
projections that incorporate "on
the books" EE/RE policies
EGU baseline projections using
energy models or similar methods
reflect EGU operations as a whole
system and account for a range of
power sector policies and
environmental constraints.
Cons
To the extent that a jurisdiction is relying
on EPA's baseline modeling runs, a con
can be that any revisions can be expensive
because the integrated planning model
(IPM) EPA uses is a proprietary model.
EGU baseline projections are best done
on a regional basis, rather than area by
area. Coordination is necessary with
other state, tribal and local agencies
within your region (perhaps through
regional planning organization).
Could be "enforced" by EPA through a
Clean Air Act SIP call in which the
Agency requests a SIP revision to make
up an emissions shortfall due to a state
failure to implement the policy as
envisioned in the baseline.
Circumstances Best
Suited For
• State, tribal and local
agencies that want to
include "On the books,"
EE/RE policies in their
SIP that have not been
accounted for elsewhere
in the SIP
Basic Steps to
Implement
Use available EPA
EGU baseline
projections or utilize a
dynamic model that
can project future
emissions, federal,
state, tribal and local
requirements, and
EE/RE policies within
power sector
Control
Strategy
Option
State, tribal and local agencies will
gain a better understanding of
which EGUs will displace
emissions as a result of future
EE/RE policies/programs.
State, tribal and local agencies will
have a tons-per-day (TPD) amount
of emissions for each EGU they
expect to reduce based on a
specified EE/RE policy and
program.
State, tribal and local agencies will
have emission reductions from a
control strategy to help them attain
More documentation is needed than the
future baseline and WOE approaches
because a jurisdiction would have to show
that the EE/RE policy/program was
permanent, enforceable, quantifiable, and
surplus
Quantification can be more resource
intensive because the state, tribal or local
agency would have to perform more of
the EGU analysis than the baseline
pathway in which EPA is providing more
support for EGU analysis
Best suited for state,
tribal and local agencies
that have EE/RE policies
that their area is required
to adopt before it submits
its SIP/TIP to EPA ("on
the way" policies) and
that will produce
emissions benefits in the
planning timeframe of
their SIP/TIP.
The state, tribal or
local agency must
demonstrate that
policies are permanent,
quantifiable, surplus
and enforceable
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Pathway Pros
Emerging/
Voluntary
Measures
Pathway
Areas can obtain SIP/TIP credit up
to six percent for EE/RE
policies/programs, or more if they
can make a clear convincing case
Recognizes that some EE/RE
policies/programs are not easy to
enforce or easily quantified
Cons
Potentially does not offer as much
potential SIP/TIP credit as the control
strategy pathway because it establishes
limitations and conditions that limit the
credit which emerging/voluntary
measures can receive
Quantification of emissions impacts may
be difficult for emerging/voluntary
measures
This option carries less impact than
including an EE/RE policy in the SIP/TIP
as part of the control strategy or in the
emissions baseline.
Circumstances Best
Suited For
• Emerging/voluntary
measures for which the
state, tribal or local
agency wishes to receive
SIP/TIP credit.
Basic Steps to
Implement
Develop description of
policies and perform
quantification of
emissions impact of
policies and programs.
Commit to monitor,
evaluate, and report at
least every three years
to the public and EPA
on the resulting
emissions effect of the
emission or pollutant
reduction measure
WOE
Option
Documentation for this pathway is
the least rigorous and requires the
least amount of effort.
A state, tribal or local agency can
include emission reductions from
any policy or program that may
impact a nonattainment area
without demonstrating how the
state, tribal or local agency will
meet the SIP/TIP control strategy
criteria.
EE/RE policies/
programs where a state,
tribal or local agency
wants to claim emissions
benefit that will affect
the area's future year air
quality design value, but
modeling the impact of
the policy/program is
either too resource
intensive or not possible.
State, tribal and local
agencies can use this
option only if they are
within a prescribed
margin of attaining the
applicable National
Ambient Air Quality
Standard (NAAQS).
• Develop basic
description of policies
and perform basic
quantification of
emissions impact of
policies and programs.
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SECTION 3.0: FUTURE BASELINE PATHWAY
A baseline forecast of future emissions in the attainment year is made when a jurisdiction
prepares a SIP/TIP or performs a SIP revision. The purpose of the baseline forecast is to
document expected conditions in the
absence of new measures or policies.
Because projected emission levels are
affected by demand for electric power
and new generation capacity,
jurisdictions can take steps
to understand the impacts of their
EE/RE policies and programs, and to
represent these impacts in baseline
emission forecasts. States, local, and
tribal agencies interested
in accounting for "on the books"
EE/RE policies in the baseline
pathway can conduct their own
analysis or start by using EPA's
existing methodology and results (see
Appendix E).
EGU Emissions Baseline Projection
Options for State, Tribal and Local
Agencies
Jurisdictions seeking to include existing EE/RE policies and programs in SIPs/TIPs
should consider adopting the future baseline pathway addressed here. By taking this
approach, the emission impacts from existing policies (i.e., policies already adopted by a
jurisdiction) are captured in the baseline, along with other "on the books" requirements,
conditions, and assumptions affecting the electric generating unit (EGU) sector baseline
forecast. A first step for jurisdictions is to identify the set of existing Federal and State
policies and programs that are included (and those not included) in the baseline electricity
demand forecast. State, local, and
Figure 3.1: Manual Roadmap for
Baseline Pathway
Baseline Pathway
For information on how power
distribution works in an area
See Appendix B
For an understanding of existing
baseline pathway guidance
See Appendix C.2
For potential revised ozone NAAQS, if
you want to use EPA's IPM Run
See Appendix E.2
For potential revised ozone NAAQS, if
you do not want to use EPA's IPM Run
See Appendix E.3
EE/RE SIP examples
See Appendix J
Baseline Pathway Conditions
State, local and tribal agencies can include a specific
EE/RE policy in the future SIP/TIP attainment year
emissions baseline if:
It has already been adopted by an appropriate
jurisdiction
AND
The effects of the policy have not already been
accounted for in the SIP/TIP - that is, you are not
double counting.
tribal agencies can then estimate
the impacts of previously-omitted
policies and programs, and use
these results to develop a revised
electricity demand forecast and/or
revised forecast of future
generation capacity. This updated
demand and supply forecast can
subsequently be used as a basis for
the EGU sector emissions forecast
over the period of interest. The
new future emissions baseline -
with a reflection of existing EE/RE policies and programs of interest - becomes the
starting point from which additional control strategy measures are assessed.
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Appendix E discusses the steps a state, tribal or local agency needs to take to pursue this
pathway, and process issues state, tribal and local agencies are likely to encounter such as
expected level of effort, other resources needed, and stakeholders that need to be
involved.
Agencies interested in leveraging EPA's energy modeling capability (using the IPM
model) to quantify EE/RE under the forthcoming ozone NAAQS can start by reviewing
Appendix E.2. States, local, and tribal agencies considering developing their own
quantification method can review Appendix E.4. Appendix J provides examples of how
other states have approached incorporating EE/RE policies into SIPs.
Baseline Conditions To Be Met
Certain conditions have to be met in order to include a policy in the future attainment
year baseline. For example, energy efficiency resource standards (EERS) that have been
adopted in law can be included in the baseline emissions forecast. However, if a state,
tribal or local agency is currently discussing whether to adopt such a policy, or has
proposed but not yet adopted one, it is not appropriate to include. Purely voluntary
policies are likewise ineligible.
In addition, EPA wants to ensure that the emissions reductions from EE/RE policies are
not counted twice. State, tribal and local agencies must clearly understand and account
for the EE/RE policies/programs in the baseline forecast before attempting to adjust this
forecast to account for additional EE/RE policies and programs.
Mandatory Policies That Are Not Traditionally, Federally Enforceable
It is also important to understand that EE/RE policies incorporated into the future
baseline are not traditionally, federally enforceable and that EPA may not bring an
enforcement action against an entity for failure to meet Clean Air Act requirements. If
the EE/RE policy or program is not implemented then the state may implement backup
policies to make up for the emissions shortfall. Alternatively, EPA may initiate a SIP call
under section 110 of the Clean Air Act in which EPA can request that the state revise the
SIP to make up the emissions shortfall brought about the area's failure to implement the
policy as envisioned in the baseline. Additionally, state utility regulators typically have
their own mechanisms to require compliance with state EE/RE policy requirements,
including financial incentives for exceeding state policy requirements and penalties for
non-compliance.
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SECTION 4.0: CONTROL STRATEGY PATHWAY
SIPs/TIPs must include strategies
containing control measures to provide
emissions reductions to enable
nonattainment and maintenance areas to
attain and meet certain SIP requirements.
The control strategy pathway would
provide state, tribal and local agencies the
opportunity to include EE/RE policies as
part of a control strategy. It is best suited
for a state, tribal and local agency that has
adopted EE/RE policies before it submits
its SIP to EPA ("on the way" policies) and
whose emissions benefits will be realized
coincident with the planning timeframe of
its SIP. The control strategy pathway offers
the most visible and direct benefit in the
SIP context and it is traditionally, federally
enforceable, which may make it more
desirable for some jurisdictions. In
addition, an EE/RE policy/program that is
qualified as a control strategy may help air
quality agencies to improve their
collaboration with state public service commissions and energy offices. If these energy-
related offices understand that the state, tribal or local agency is relying upon the
emissions benefits from EE/RE, that such benefits are required to be enforced, and that
gaps in achieving the environmental objectives of EE/RE would require the air quality
agency to be made up by other control strategies, then the offices can work with the air
agency at the planning stage to help design effective EE/RE policies/programs. And, the
energy office or public service commission has a role to ensure that the emissions
benefits are achieved.
This pathway involves more analysis and documentation than the baseline,
emerging/voluntary and WOE options. While both the control strategy and baseline
options involve significant quantification efforts, state, tribal and local agencies that
undertake the control strategy option also have to demonstrate that the emissions
reductions resulting from their mandatory EE/RE policies are surplus, enforceable and
permanent. This manual clarifies how those requirements can be satisfied. State, tribal
and local agencies meeting the requirements would have to provide more documentation
than would be necessary under the baseline, emerging/voluntary and WOE approaches.
Figure 4.1: Manual Roadmap for
Control Strategy Pathway
Control Strategy Pathway
4»
^
\
s
•^
/
For information on how power
distribution works in an area
See Appendix B
For an understanding of existing control
strategy pathway guidance
See Appendix C.3
For information on the control strategy
pathway
See Appendix F
EE/RE SIP examples
See Appendix J
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Figure 4.2: Four Criteria the Control Strategy Pathway
Must Address
Permanent
Evidence of regulation or legislation
mandating program for planning
period
Enforceable
Federal enforceability is key to EPA
being able to provide expanded SIP
credit for these programs
If the state failed to enforce the
program, EPA has the discretion to
enforce
Quantifiable
Quantification of benefits of EE/RE
programs
Surplus
No double counting of emissions
reductions
EPA requests a statement to that
effect from the state, local or tribal
government
Control Strategy
Option Is
Traditionally,
Federally Enforceable
Because the control
strategy option is
traditionally, federally
enforceable, process
issues could be greater.
The state, tribal or local
air quality office will
most likely need to
reach out to the state
Public Utility
Commission and others
to explain the
implications of making
the state, tribal or local
agency's mandatory EE/RE policies traditionally, federally enforceable and to discuss a
mechanism (in consultation with EPA Regional offices) for coordinating state
enforcement with federal enforcement activities.
Additional details about this pathway are included in Appendix F. Appendix F. 1 contains
information on the four criteria and how a state, tribal or local agency can satisfy them
(Figure 4.2 provides a brief description of the four criteria). With respect to quantifying
the benefits of mandatory EE/RE policies, the approach outlined in Appendices F.2 to F.4
recognizes that some state, tribal and local agencies (or groups of state, tribal and local
agencies) will possess the resources and capability to perform sophisticated modeling
analyses of the energy and air benefits of mandatory EE/RE policies, while others will
not. The appendices are organized by tiers of analysis from Tier One (advanced
quantification) to Tier Three (basic quantification). Appendix J provides examples of
initial state thinking about how to incorporate EE/RE policies into SIPs.
Basic Steps For Quantifying Mandatory EE/RE Policies
Overall, EPA's guidance on SIP credit spells out four steps to address when quantifying
mandatory EE/RE policies under the control strategies pathway:
1) STEP 1 Quantify the energy savings that an energy efficiency policy will
produce, or, for a renewable energy policy, the amount of energy generation that
will occur, between the base year and the area's attainment future baseline year.
2) STEP 2 - Quantify or estimate displaced EGU emissions from energy impacts of
an energy efficiency policy or renewable energy policy
3) STEP 3 - Determine the impact from the emission reduction on air quality in the
nonattainment area.
4) STEP 4 - Provide a mechanism to validate or evaluate the effectiveness of the
project or initiative.
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SECTION 5.0: EMERGING/VOLUNTARY MEASURES PATHWAY
A voluntary measure is a measure or
strategy that is not enforceable against an
individual source. An emerging measure
is a measure or strategy that does not have
the same high level of certainty as
traditional measures for quantification
purposes. A measure can be both
voluntary and emerging. In 2004 Agency
guidance EPA has recognized that many
areas of the country have implemented
most available traditional emission control
strategies and want to try new types of
pollutant reduction strategies to attain
NAAQS, including voluntary EE/RE
programs. The EPA supports and
encourages the testing of voluntary and
emerging pollutant reduction strategies.
This pathway is similar to the control
strategy pathway in that an EE/RE
program can receive emission reduction
SIP credit under this option. For
emerging/voluntary stationary measures,
the presumptive SIP credit limit is 6 percent of the total amount of emission reductions
required for the ROP, RFP, attainment, or maintenance demonstration purposes. These
measures must satisfy the four criteria for SIP measures:
• Permanent
• Quantifiable
• Surplus
• Enforceable
But the policy provides flexibility for emerging measures on the quantifiable criterion
and for voluntary measures it provides flexibility on the enforceable criterion.
The pathway is well suited for areas that have voluntary and/or emerging EE/RE
policies/programs are not easy to enforce and/or quantify but for which the area would
like SIP credit. The pathway does not offer as much potential SIP credit as the control
strategy pathway because it establishes limitations and conditions that limit the credit that
emerging/voluntary measures can receive. The pathway provides a mechanism that
allows state, tribal or local agencies to receive provisional emission reduction credit in
their SIP for new emission control and pollutant reduction strategies that have the
potential to generate additional emission reductions or air quality benefits. Provisionary
emission reductions or pollutant reduction strategies can become permanent when post-
implementation evaluations validate the amount of emission reductions achieved. The
Figure 5.1: Manual Roadmap for
Emerging/Voluntary Measures
Pathway
Voluntary/Emerging Measures Pathway
I
For information on how power
distribution works in an area
See Appendix B
For an understanding of existing
voluntary/emerging measures pathway
guidance
See Appendix C.4
For information on the
voluntary/emerging measures pathway
See Appendix G
EE/RE SIP examples
See Appendix J
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process issues and workload associated with this pathway are light to medium. They are
greater than the WOE pathway and less than the control strategy pathway.
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SECTION 6.0: WEIGHT OF EVIDENCE (WOE) PATHWAY
When state, tribal and local agencies prepare SIP demonstrations of attainment,
sometimes air quality modeling results can be inconclusive and predict that areas will not
attain aNAAQS based solely on
modeling. In those cases, EPA guidance
allows areas to submit weight-of-evidence
demonstrations to show that, despite
inconclusive modeling results, the area
will still attain based on other evidence.
Although WOE demonstrations can
include mandatory EE/RE
policies/programs, the WOE option is best
suited for a state, tribal or local agency
that has voluntary EE/RE programs that
demonstrate, through basic quantification,
that emissions reductions will occur
within the same planning timeframe as
that used for attainment. While the WOE
approach involves the least amount of
documentation and analysis, it also
provides the most uncertain potential
emissions reductions or air quality benefit
for the SIP. Process issues for this option
are likely to be light, including the level of effort expected, resources needed, and
stakeholders that need to be involved.
Weight of evidence demonstrations are described in guidance EPA has issued on their
use in SIP attainment demonstrations.6 Weight of evidence demonstrations are generally
a set of analyses of air quality, emissions, meteorological data, and modeling data that
State, tribal and local agencies can use to show that attainment of a NAAQS is likely,
despite modeled results which may not show attainment or may be close to the level of
the NAAQS. The greater the difference between the modeled design value and the level
of the standard, the more compelling the additional evidence produced by analyses must
be in order to conclude (based on the WOE results) that attainment is likely despite the
inconclusive modeled attainment test. EPA guidance includes guidelines for assessing
when corroborating analyses and/or weight of evidence determinations may be
appropriate.
Emissions reductions from mandatory EE/RE policies and voluntary programs proposed
for use in the WOE demonstration cannot be used elsewhere in the SIP. In other words,
no double counting is permitted. And the measures must be in place for the duration of
the SIP planning period. Appendix H describes the basics of the WOE approach in more
depth and provides information on WOE analyses and WOE examples.
Figure 6.1: Manual Roadmap for
WOE Pathway
Weight of Evidence Pathway
L>
For information on how power
distribution works in an area
See Appendix B
For an understanding of existing WOE
pathway guidance
See Appendix C.5
For information on the control strategy
pathway
See Appendix H
EE/RE SIP examples
See Appendix J
6 "Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals
for Ozone, PM2.5, and Regional Haze," http://www.epa.gov/scram001/guidance sip.htm. EPA -454/B-07-
002, April 2007.
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Appendices
Appendix A: Glossary 32
Appendix B: Overview of the U.S. Electric System 37
SECTION B.1: INTRODUCTION 37
SECTION B.2: ABOUT THE U.S. ELECTRIC SYSTEM 37
SECTION B.3: HOW THE ELECTRIC SYSTEM WORKS 38
SECTION B.4: THE LOCATION OF EMISSIONS REDUCTIONS RELATIVE TO THE SITING
OF CLEAN ENERGY RESOURCES 41
Appendix C: Existing Energy Efficiency/Renewable Energy Guidance 43
SECTION C.I: INTRODUCTION 43
SECTION C.2: EXISTING GUIDANCE ON BASELINE PATHWAY 43
SECTION C.3: EXISTING GUIDANCE ON CONTROL MEASURE PATHWAY 43
Quantifiable 44
Surplus 44
Enforceable 45
Permanent 46
SECTION C.4: EXISTING GUIDANCE ON EMERGING/VOLUNTARY MEASURES
PATHWAY 46
How A State Can Get SIP Approval For Emerging/Voluntary Measures 47
Four Criteria For SIP Emerging/Voluntary Measures 47
Quantifiable 47
Surplus 48
Enforceable 48
Permanent 49
Emission Reduction (SIP) Credit 49
Bundling Emerging/Voluntary Measures 49
SECTION C.5: EXISTING GUIDANCE ON WOE PATHWAY 50
Appendix D: Understanding State Renewable Energy and Energy Efficiency Policies 51
SECTION D.I: INTRODUCTION 51
SECTION D.2: OVERVIEW OF STATE RENEWABLE ENERGY POLICIES 51
SECTION D.3: OVERVIEW OF STATE ENERGY EFFICIENCY POLICIES 52
SECTION D.4: EXAMPLES OF STATE POLICIES 54
SECTION D.5: HOW STATE EE/RE PROGRAMS AND POLICIES ARE ADMINISTERED 55
SECTION D.6: WHERE TO GO FOR MORE INFORMATION 56
Appendix E: Baseline Pathway 57
SECTION E.I: BASICS OF FUTURE ATTAINMENT YEAR BASELINE APPROACHES 57
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Introduction To The Baseline Pathway For SIP/TIP Air Quality Modeling 57
EPA's Baseline Emission Forecast For EGUs 57
State, Tribal Or Local Developed Baseline Forecast 58
Tradeoffs Between Four SIP/TIP Pathways 58
Incorporating EE/RE Policies For The Baseline Pathway 59
SECTION E.2: STEPS FOR INCORPORATING "ON THE BOOKS" EE POLICIES 59
Step 1: Determine What Baseline Demand Forecast The State Or Region Will Use For EGU Projections
59
Energy Information Administration's (EIA) Demand Forecasts 59
Regional Transmission Organization Or Independent System Operator Demand Forecasts 60
Step 2: Determine What EE Policy Assumptions Are Already In EGU Baseline Demand Projections...60
Energy Information Administration's (EIA) EE Policy Assumptions 60
Regional Transmission Organization Or Independent System Operator EE Policy Assumptions 60
Step 3: Review State, Tribal And Local "On The Books" EE Policies To Determine If More Can Be
Included Into The EGU Baseline Demand Projections 61
Evaluating State, Tribal And Local EE/RE Policies Compared To Energy Information
Administration's (EIA) Assumptions 61
Evaluating State EE Policies Compared To Regional Forecast Assumptions 61
SECTION E.3: STEPS FOR INCORPORATING "ON THE BOOKS" RE POLICIES 61
Step 1: Determine What Renewable Energy Sources Are Already In Baseline Inventory And The
Relative Emission Factor For Each Type Of Renewable Energy Generated In The State Or Region 62
Step 2: Determine What RE Policy Assumptions Are Already In EGU Baseline Supply Projections 62
Energy Information Administration's (EIA) RE Policy Assumptions 62
Step 3: Review State, Tribal And Local "On The Books" RE Policies To Determine If More Can Be
Included Into The EGU Baseline Demand Projections 62
Documentation Requirements 62
Step 4: Perform Energy Modeling To Project EGU Baseline Emissions 63
Use IPM Modeling To Project Future Attainment Year Baseline For SIP/TIP Air Quality Modeling .63
SECTION E.4: FUTURE ATTAINMENT YEAR BASELINE USING OTHER APPROACHES
FOR SIP/TIP AIR QUALITY MODELING 63
Appendix F: Control Strategy Pathway 65
SECTION F.I: BASICS OF CONTROL STRATEGY PATHWAY 65
Description Of Pathway 65
Steps A State Needs To Take To Quantify Emissions Impacts 67
SECTION F.2: STEP 1: ESTIMATE THE ENERGY SAVINGS THAT AN ENERGY
EFFICIENCY POLICY WILL PRODUCE, OR, FOR A RENEWABLE ENERGY POLICY, THE
AMOUNT OF ENERGY GENERATION THAT WILL OCCUR 67
Introduction 67
Energy Savings From Energy Efficiency (EE) Policies 68
Renewable Energy Generated From Renewable Energy Policies 69
Taking Into Account The Future Attainment Year(S) Baseline Forecast When Developing EE/RE Policy
And/Or Program Energy Impacts For The Control Measure Pathway 69
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SECTION F.3: STEP 2: QUANTIFY OR ESTIMATE DISPLACED ECU EMISSIONS FROM
ENERGY IMPACTS OF AN ENERGY EFFICIENCY POLICY OR RENEWABLE ENERGY
POLICY 70
Introduction 70
Tier One Approach Using Dispatch And Capacity Expansion Models 71
Dispatch Models - Measuring Hourly Marginal Emission Rates 71
Capacity Expansion Models - Measuring Long Term Impacts of New Capacity 72
Tier Two Approach For "Stacking" EGUs And Quantifying Displaced EGU Emissions 73
Adjusted Historical Hourly Generation Dispatch Order 73
Tier Three Approach For Developing An EGU Dispatch Order And Estimating Displaced EGU
Emissions 76
Capacity Factor Approach 76
Tier Four Approach eGRID Subregion Emission Rates 80
"Non-Base load" eGRID Emission Rates 80
SECTION F.4: STEP 3: DETERMINE THE IMPACT FROM THE ESTIMATED EMISSION
REDUCTION ON AIR QUALITY IN THE NONATTAINMENT AREA 82
Determining The Geographic Area Where Emission Reductions Occur 83
Energy Efficiency 83
Renewable Energy 85
SECTION F.5: STEP 4: PROVIDE A MECHANISM TO VALIDATE OR EVALUATE THE
EFFECTIVENESS OF THE POLICY 85
SECTION F.6: OTHER CRITERIA FOR CONTROL MEASURE PATHWAY 86
Permanent Criterion 86
Enforceable Criterion 86
Surplus Criterion 87
Appendix G: Emerging/Voluntary Measures Pathway 89
SECTION G.I: BASICS OF EMERGING/VOLUNTARY MEASURES 89
Pathway Description 89
Tradeoffs Of Pathway 89
What Circumstances And Type Of State, Tribal And Local Agencies Is The Pathway Best Suited For ..90
Four Steps State, Tribal And Local Agencies Needs To Take To Implement The Pathway 90
Process Issues Including Expected Level Of Effort, Other Resources Needed, And Stakeholders Involved
90
SECTION G.2: VOLUNTARY/EMERGING MEASURES PATHWAY ANALYSIS AND
DOCUMENTATION 90
Permanent 90
Quantifiable 90
Surplus 91
Enforceable 91
Appendix H: Weight of Evidence Pathway 92
SECTION H.1: BASICS OF WOE 92
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Pathway Description 92
Tradeoffs Of Pathway 92
What Circumstances And Type Of States The Pathway Is Best Suited For 93
Four Steps State, Tribal And Local Agencies Needs To Take To Implement The Pathway 93
Process Issues Including Expected Level Of Effort, Other Resources Needed, And Stakeholders Involved
93
SECTION H.2: WOE EE/RE ANALYSIS AND DOCUMENTATION 93
Appendix I: EPA's Draft Methodology for Estimating Energy Impacts of EE/RE Policies 95
SECTION 1.1: INTRODUCTION 95
SECTION 1.2: OVERVIEW OF PROCESS 95
Step One: Understand EE/RE Policy Assumptions In Annual Energy Outlook 2010 Reference Case
Forecast (AEO 2010) 96
Step Two: Identify Key "On The Books" State EE/RE Policies Not Explicitly Included In AEO 2010
And Review Relevant Design Details 96
Step Three: Develop Analytical Methods To Estimate Incremental Impacts Of EE/RE Policies Relative
To AEO 2010 Reference Case Forecast 97
SECTION 1.3: OVERVIEW OF EPA'S DRAFT METHODOLOGY AND ANALYTICAL STEPS 97
EPA's Draft Methodology For Generating A Baseline (I.E., Business As Usual Or (BAU)) Forecast Of
State Electricity Sales To Represent AEO 2010 Regional Forecasts 98
EPA's Draft Methodology For Estimating Energy Savings Of EE State Policies Embedded In AEO
2010 99
EPA's Draft Methodology For Estimating Projected Energy Efficiency Savings From Energy Efficiency
Policies 102
Energy Efficiency Resource Standards 103
Rate-Payer Funded Commitments To EE Programs With An Established Public Benefits Fund Policy
106
RGGI-Funded EE programs 108
EPA's Draft Methodology For Generating State-Adjusted Forecast That Reflects Energy Savings
Incremental To AEO2010 109
SECTION 1.4: EPA'S DRAFT METHODOLOGY FOR ESTIMATING PROJECTED PEAK
DEMAND SAVINGS OF EE POLICIES 110
EPA's Draft Methodology For Generating Load Impact Curves Of EE Policies Ill
EPA's Draft Methodology For Estimating RE Sales From RPS Beyond What Is Captured In AEO2010
114
SECTION 1.5: EPA'S DRAFT METHODOLOGY FOR GENERATING STATE-ADJUSTED
FORECAST AND AGGREGATING IT TO FACILITATE MODELING REGIONAL RPS
IMPACTS 114
References 116
Appendix J: State Examples and Opportunities 121
SECTION J.I - STATES THAT ADDRESSED CLEAN ENERGY IN THEIR SIPS FOR THE 1997
OZONE NAAQS 121
Background 121
Summary 121
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State Examples 122
EE/RE In A Voluntary Control Measure Bundle 122
States Using EE/RE In A Weight Of Evidence Finding 123
SECTION J.2: STATES THAT ARE CONSIDERING INCORPORATING EE/RE PROGRAMS
AND POLICIES IN THEIR SIPS FOR THE REVISED OZONE NAAQS 123
State Of Connecticut 124
Background 124
Initiate Collaboration Among Key State Entities Responsible For Air And Energy Decisions 124
Understand And Identify EE/RE Policies And Programs To Be Included In The SIP 125
Understand Pathways Available For Incorporating EE/RE Programs And Policies Into SIPs 126
State Of New Mexico 126
Background 127
Initiate Collaboration Among Key State Entities Responsible For Air And Energy Decisions 127
Understand And Identify EE/RE Policies And Programs To Be Included In The SIP 127
Understand Pathways Available For Incorporating EE/RE Programs And Policies Into SIPs 127
State Of Maryland 129
Background 129
Understand And Identify EE/RE Policies And Programs To Be Included In The SIP 129
Understand Pathways Available For Incorporating EE/RE Programs And Policies Into SIPs 130
SECTION J.3: OPPORTUNITIES TO REDUCE ELECTRICITY CONSUMPTION AND NOX
EMISSIONS FROM EPA'S STORM WATER RULES 131
ATTACHMENT A: STATE OF CONNECTICUT EE/RE POLICIES AND PROGRAMS 133
RE Policies and Programs 133
EE Policies and Programs 134
Letter from USEPA Region 1 to State of Connecticut 136
ATTACHMENT B: STATE OF MARYLAND EE/RE POLICIES AND PROGRAMS 143
EmPower Maryland 143
Renewable Portfolio Standards 143
Regional Greenhouse Gas Initiative 144
Maryland Clean Car Program 145
ATTACHMENT C: STATE OF NEW MEXICO'S EE/RE POLICIES AND PROGRAMS 146
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Appendix A: Glossary
Allowances: Allowances represent the
amount of a pollutant that a source is
permitted to emit during a specified time
in the future under a cap and trade
program... Allowances are often
confused with credits earned in the
context of project-based or offset
programs, in which sources trade with
other facilities to attain compliance with
a conventional regulatory requirement.
Baseline period: The period of time
selected as representative of facility
operations before the energy efficiency
or renewable energy activity takes place.
Baseline: Conditions, including energy
consumption and related emissions,
which would have occurred without
implementation of the subject project or
program. Baseline conditions are
sometimes referred to as "business-as-
usual" conditions. Baselines are defined
as either project-specific baselines or
performance standard baselines.
Clean Air Act (CAA): The Clean Air
Act is the law that defines EPA's
responsibilities for protecting and
improving the nation's air quality and the
stratospheric ozone layer. The last
major change in the law occurred when
Congress enacted the Clean Air Act
Amendments of 1990. Legislation
passed since then has made several
minor changes.
Criteria Air Pollutant: The Clean Air
Act requires EPA to set National
Ambient Air Quality Standards for six
common air pollutants. These commonly
found air pollutants (also known as
"criteria pollutants") are found all over
the United States. They are particle
pollution (often referred to as particulate
matter), ground-level ozone, carbon
monoxide, sulfur oxides, nitrogen
oxides, and lead.
Demand: The time rate of energy flow.
Demand usually refers to electric power
measured in kW (equals kWh/h) but can
also refer to natural gas, usually as
Btu/hr, kBtu/ hr, or therms/day.
Discount rate: A measure of the time
value of money. The choice of discount
rate can have a large impact on the cost-
effectiveness results for energy
efficiency. As each cost-effectiveness
test compares the net present value of
costs and benefits for a given
stakeholder perspective, its computation
requires a discount rate assumption.
Electric generating unit(s) (EGU):
This is an entity that supplies electricity
to the electricity system relying on a
variety of fuels.
Electricity Dispatch models:
Electricity Dispatch models (also
commonly referred to as "production
cost" models) simulate the dynamic
operation of the electric system,
generally on a least-cost system
dispatch. In general, these models
optimize the dispatch of the system
based on the variable costs of each
resource and any operational constraints
that have been entered into the model.
These models are helpful in assessing
which existing plants are displaced.
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These models are also used in short-term
planning and regulatory support.
Emissions & Generation Resource
Integrated Database (eGRID): eGRID
is an EPA-maintained comprehensive
inventory of environmental attributes of
electric power systems, providing air
emissions data for the electric power
sector.
Energy efficiency (EE): Refers to
specific end-use programs, projects and
measures that achieve the same or better
level of performance as existing
technology or approaches through lower
energy consumption. These efforts
reduce overall electricity consumption
(reported in kilowatt or megawatt hours),
often without explicit consideration for
the timing of program-induced savings.
Such savings are generally achieved by
substituting technologically more
advanced equipment to produce the
same level of end-use services (e.g.
lighting, heating, motor drive) with less
electricity. Examples include high-
efficiency appliances, efficient lighting
programs, high-efficiency heating,
ventilating and air conditioning (HVAC)
systems or control modifications,
efficient building design, advanced
electric motor drives, and heat recovery
systems.
Energy efficiency measure:
Installation of equipment, installation of
subsystems or systems, or modification
of equipment, subsystems, systems, or
operations on the customer side of the
meter, in order to improve energy
efficiency.
Energy efficiency policy: Energy
efficiency policy means an enacted law
and/or regulation by a state, locality or
public utility commission order which
requires applicable entities to adopt
energy efficient technologies and/or
practices, or to undertake activities to
further such adoption in the marketplace.
It can include: (1) policies that establish
minimum efficiency requirements for
new homes and buildings (building
energy codes) or appliances (appliance
standards); (2) policies that establish
requirements on utilities (or other
program administrators) to deliver a
specified amount of energy savings by
developing energy efficiency programs
to increase market adoption of EE
technologies and practices (energy
efficiency resource standards); and (3)
policies that commit to specified funding
levels dedicated to implementing energy
efficiency programs (e.g., public benefits
funds). State and local governments
both have authority over energy
efficiency policies. EE policies are
generally enforced over a multi-year
period (e.g., through 2020) or until
changed or updated by revised
legislation or regulation (e.g., adopting a
revised building energy code). These
programs can be funded through
ratepayer surcharges, Federal funds (e.g.,
ARRA, SEP), proceeds from pollution
auctions such as the Regional
Greenhouse Gas Initiative (RGGI) or
any combination of the above.
Energy Efficiency Program: Energy
efficiency program means a program
designed to increase adoption of energy
efficient technologies and practices in
particular end-use sectors (or specific
market segments within a sector)
through education & outreach, financial
incentives, and/or technical assistance.
An individual EE program can be run by
a utility, state or local government,
and/or third parties. In most cases, EE
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program administrators (i.e., utilities,
state agencies, or 3rd parties) develop
and implement EE programs to meet
adopted EE policy objectives. State
Public Utilities Commissions (PUCs)
oversee and approve the EE programs
funded with rate-payer resources. EE
programs typically operate over a 1-3
year period.
Energy model: This refers to the
numerous models that are available for
simulating the electric power system.
They have strengths and weaknesses
relative to each other, as a general
matter, since they strike different
tradeoffs between the level of rigor and
ease of use.
Evaluation: The performance of studies
and activities aimed at determining the
effects of a program; any of a wide range
of assessment activities associated with
understanding or documenting program
performance, assessing program or
program-related markets and market
operations; any of a wide range of
evaluative efforts including assessing
program-induced changes in energy
efficiency markets, levels of demand or
energy savings, and program cost-
effectiveness.
Future attainment year baseline: A
baseline forecast of future emissions is
made when an area prepares a State
Implementation Plan (SIP)/Tribal
Implementation Plan. Future year
emission projections provide a basis for
considering control strategies for SIPs,
conducting attainment analyses, and
tracking progress towards meeting air
quality standards.
Heating, Ventilating, and Air
Conditioning (HVAC): This refers to
technology to provide for indoor
environmental comfort.
Integrated Planning Model (IPM):
The EPA uses IPM to analyze the
projected impact of environmental
policies on the electric power sector in
the 48 contiguous states and the District
of Columbia. EPA has used multiple
iterations of the IPM model in various
analyses of regulations and legislative
proposals.
Kilowatt-hour (KWh): A measure of
electricity defined as a unit of work or
energy, measured as 1 kilowatt
(l,000watts) of power expended for 1
hour. One kWh is equivalent to 3,412
Btu.
Load shapes: Representations such as
graphs, tables, and databases that
describe energy consumption rates as a
function of another variable such as time
or outdoor air temperature.
Marginal emission rates: The
emissions associated with the marginal
generating unit in each hour of the day.
Measurement and verification
(M&V): Data collection, monitoring,
and analysis associated with the
calculation of gross energy and demand
savings from individual sites or projects.
M&V can be a subset of program impact
evaluation.
Megawatt (MW): One million watts of
electricity.
Megawatt-hour (MWh): One thousand
kilowatt-hours or 1 million watt-hours.
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National Ambient Air Quality
Standards (NAAQS): The CAA, which
was last amended in 1990, requires EPA
to set NAAQS (40 CFR part 50) for
pollutants considered harmful to public
health and the environment. The CAA
established two types of national air
quality standards. Primary standards set
limits to protect public health, including
the health of "sensitive" populations
such as asthmatics, children, and the
elderly. Secondary standards set limits
to protect public welfare, including
protection against decreased visibility,
damage to animals, crops, vegetation,
and buildings.
Nitrogen Oxides (NOX): Nitrogen
oxide can refer to a binary compound of
oxygen and nitrogen, or a mixture of
such compounds.
"On the books" EE/RE Policies:
EE/RE policies that have been adopted
by a legislative or regulatory body.
"On the way" EE/RE Policies: EE/RE
policies that are planned for adoption by
a legislative or regulatory body prior to
the submittal of the SIP in question to
EPA.
Peak demand: The maximum level of
metered demand during a specified
period, such as a billing month or a peak
demand period.
Portfolio: Either (a) a collection of
similar programs addressing the same
market, technology, or mechanisms or
(b) the set of all programs conducted by
one organization.
Program: A group of projects, with
similar characteristics and installed in
similar applications.
Public Utilities Commission (PUC) or
Public Service Commission (PSC): A
PUC or PSC is a governing body that
regulates the rates and services of a
public utility. In some cases,
government bodies with the title "Public
Service Commission" may be civil
service oversight bodies, rather than
utilities regulators.
Renewable Energy (RE): Energy
resources are naturally replenishing but
flow-limited. They are virtually
inexhaustible in duration but limited in
the amount of energy that is available
per unit of time. Renewable energy
resources include biomass, hydro,
geothermal, solar, wind, ocean thermal,
wave action, and tidal action.
Renewable Energy Policy:
Regulations, statutes, or state public
utility commission orders that require
parties to acquire renewable energy or to
commit to funding levels for programs
aimed at acquiring RE.
Renewable Energy Program:
Renewable energy program means a
program designed to increase the
production and use of renewable energy
sources through resource development
and procurement, education & outreach,
financial incentives, and/or technical
assistance.
Renewable Portfolio Standard (RPS):
An RPS is a regulation that requires the
increased production of energy from
renewable energy sources, such as wind,
solar, biomass, and geothermal.
State Implementation Plans (SIPs): A
SIP is a plan developed by a state for
how that state will comply with the
requirements of the federal Clean Air
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Act, administered by the Environmental
Protection Agency. The SIP consists of
narrative, rules, technical
documentation, and agreements that an
individual state will use to clean up
polluted areas.
Traditional, Federal enforceability:
This refers to what occurs in the SIP
planning process when EPA approves a
SIP control strategy submitted to it for
review. When that occurs, it becomes
traditionally federally enforceable,
which provides EPA with authority to
ensure the SIP is implemented.
Tribal Implementation Plans (TIPs):
Although not required to do so, a tribe
with Treatment as State eligibility may
develop its own air quality control plan,
called a Tribal Implementation Plan
(TIP), for approval by EPA. A TIP
enacted by a tribal government and
approved by the EPA is legally binding
under both tribal and federal law and
may be enforced by the tribe, EPA, and
the public.
Voluntary EE/RE Programs:
Voluntary EE/RE programs are
programs adopted by state and local
governments or other parties to promote
EE/RE that may or may not result from
an EE/RE policy.
Voluntary/emerging measures
policy: In September 2004, EPA issued
guidance entitled: "Incorporating
Emerging and Voluntary Measures in a
State Implementation Plan (SIP)." The
guidance provides a policy for areas to
try new types of pollutant reduction
strategies such as EE/RE programs to
attain or maintain the NAAQS and meet
CAA requirements.
Watt (W): The unit of electrical power
equal to one ampere under a pressure of
one volt. A Watt is equal to 1/746 horse
power.
Weight-of-evidence (WOE): WOE
refers to the augmenting of a SIP
modeled attainment test with
supplemental analyses may yield a
conclusion differing from that indicated
by the modeled attainment test results
alone.
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Appendix B: Overview of the U.S.
Electric System
SECTION B.I: INTRODUCTION
Generating electricity from fossil fuels is the single largest source of anthropogenic
carbon dioxide (CO2) emissions in the United States, representing 40 percent of CO2
emissions in 2008.7 It is also the largest source of criteria air pollutants that affect air
quality and human health. For these and other reasons there has been growing interest in
understanding the impacts of state-level energy efficiency and renewable energy (EE/RE)
policies on emissions from power generation. Much of this interest has come from state
environmental regulators interested in including emission reductions from EE/RE
policies in their plans for improving and maintaining air quality.
For these stakeholders and others working to analyze the effects of clean energy on air
pollution emissions, there is a need to:
• Understand the electric system
• Understand how the system is likely to respond to the introduction of clean
energy resources
• Conduct analysis that credibly and accurately represents this interaction and
estimates reductions in air pollution
o
Appendix B is intended to address these needs . It highlights the basic workings of the
electric system and addresses important issues that arise in energy and emissions
planning, most notably the "control strategy pathway" for state implementation plan
(SIP)/Tribal Implementation Plan (TIP) quantification (see Appendix F). A key take-
away from this Appendix is that the operation of regional power systems is complex and
dynamic, so predicting how these systems will react to new resources - including energy
efficiency and renewable energy - is likewise a complex undertaking.
SECTION B.2: ABOUT THE U.S. ELECTRIC SYSTEM
The most common way to generate electricity is to burn fossil fuels to convert water into
steam, and to use the steam to spin a turbine that is connected to an electric generator.
Generators can also be turned by water - as is the case with hydroelectric power plants -
or by wind turbines. In all cases, the electricity generated at these facilities flows across
the transmission and distribution system to where it is needed to meet customer demand
in cities and rural areas.
7 "Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2008," April 2010, Table ES-2.
8 An additional resource for states interested in understanding the U.S. electric system is U.S. EPA's
guidance, Assessing the Multiple Benefits of Clean Energy: A Resource for States. See:
http://www.epa.gov/statelocalclinrate/resources/benefits.html
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The North American electric system is an interconnected network for generating,
transmitting, and delivering electricity to consumers. Over the past 100 years, the system
developed around a "central station" model that distributes power from large generating
stations (often located near a fuel source) to customers located in load centers that are
hundreds of miles away. The current electricity delivery system was designed and built
in the 1950s to move large quantities of power from generators to consumers at low cost.
Despite a recent trend towards more "distributed" power - in which small generation
facilities are located near loads - most electric power in the U.S. continues to be
generated at central-station facilities powered by coal, natural gas, nuclear, and
hydropower.
The North American electric system is divided into four distinct grids in the continental
United States and Canada: the Eastern, Western, Quebec, and Electric Reliability Council
of Texas (ERCOT), as depicted in Figure B.2, NERC Interconnections. The generators,
power lines, substations, and power distribution system are the responsibility of various
utility companies working together under regional oversight to keep each grid
operational. Each grid has only limited connections to the other three, but within them
electricity is imported and exported continuously among numerous smaller power control
areas (PCA).
PC As are managed by system operators, or transmission organizations, whose main
function is to maintain the reliability of the system in their areas (e.g., New England,
New York, California, etc.). They do this by keeping the electricity supplied by the
power plants in balance with that demanded by customers. This happens in real-time,
every day of the year. In other words, energy is simultaneously being generated and
consumed on each grid in the same quantity. There is very little ability to store
electricity, and it is difficult for the grid to accommodate large, rapid changes in use and
generation.
SECTION B.3: HOW THE ELECTRIC SYSTEM WORKS
Figure B. 1 depicts the flow of power from the generating station, or power plant, to the
transformer and transmission lines through a substation transformer (that reduces voltage)
to the distribution lines. It then flows through the pole transformer to the consumer's
service box. Electricity transmission typically refers to power flow between the
generating station and a substation, and electricity distribution most often refers to
delivery from the substation to consumers. The flow of electricity occurs in accordance
with the laws of physics—along "paths of least resistance," in much the same way that
water flows through a network of canals.
Over time in a given location, the consumer demand for power fluctuates significantly.
For instance, residential electricity demand typically peaks in the morning and evening
when residents are home and operating electricity-consuming products. In contrast,
commercial electricity demand typically peaks during the middle of the day while
industrial demand varies by individual firm and type of industry. System planners have
to account for these variations as well as other factors such as weather and the availability
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of individual power plants, all while keeping the system in balance. Fortunately, the
aggregate demand of the many jurisdictions across a single grid behaves in a relatively
predictable manner.
To meet consumer demand, the grid operators rely on a fleet of power plants with
different operational characteristics, fuels, and cost structures. Base load plants such as
Figure B.I: System Flow of Electricity
Color Key
Blue: Transmission
Green: Distribution
Black Generation
Transmission Linos
765. 500. 345. 230. and 138 kV
~ _t i'.:' MM HIQfl
C ;>VM " '
GenerstingStatwn Transmission
Generator Step Customer
Up Transformer 138kV or 230kV
Primary Customer
13kVend4kV
Secondary Customer
1?OV and 240V
and do not readily cycle up and
nuclear and most coal plants operate 24 hours a day
down. They are meant to start up and keep
running until maintenance is needed. Base load
units are also characterized by relatively high
capital costs and a ramp-up process that is slow,
expensive, and results in wear on the generating
units. As power demand increases over the
course of a day, intermediate and peaking plants
come on line. These plants have the physical
capability to quickly ramp up power production
to meet increasing demand and to rapidly cycle
down once that demand dissipates. These plants
are often engines or turbines that are fueled by oil
or natural gas (see Figure B.3).
The decision of which power plants to dispatch
and in what order is based in principle on economics, with the lowest-cost resources
dispatched first and the highest cost resources last. The last resources to be called upon
are referred to as the marginal units, which are typically the most expensive units to run.
In some cases in certain parts of the country, these plants can also be among the dirtiest
and least efficient of the power plant fleet.
Renewable energy and energy efficiency can affect the dispatch in different ways, though
both cause marginal units to run less frequently and result in fewer air emissions. In the
The Marginal Unit
1 The highest-cost unit dispatched at any point in
time is said to be "on the margin" and is known
as the "marginal unit." At peak times, for
example, high-cost combustion turbines and
gas/oil peaking units are frequently on the
margin. During off-peak times, plants with
lower operating costs (e.g., combined cycle gas
turbines and coal-fired steam units) can be on
the margin. In some regions the cost used to
determine merit order for dispatch is the
variable cost of running each plant (mainly fuel
cost), but in other regions the criterion for
dispatch is a bid price submitted by the owners
of the generators
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case of efficiency, energy consumption is lowered at the point of consumption resulting
in a reduction in demand on the electric system and a corresponding reduction in
emissions from the power plant fleet.
Figure B.2: NERC Interconnections
QUEBEC
INTERCONNECTION
WESTERN
INTERCONNECTION /
FRCC
EASTERN
INTERCONNECTION
ERCOT
INTERCONNECTION
In contrast, renewable energy sources reduce the output from the marginal unit by
producing electricity for the power. Thus, a wind farm producing electricity displaces the
need for electricity that would have otherwise been produced by that marginal unit.
Since wind power results in zero emissions, overall emissions from the power plant fleet
are reduced (absent a cap on emissions that determines overall pollution levels).
This theory of "economic dispatch" predicts that any new resource shifts upward all
resources above it in the dispatch order, reducing demand on the marginal unit (the most
expensive unit needed to meet demand). Actual plant dispatch, however, is frequently
more complicated than the representation in Figure B.3 for three main reasons:
• Transmission constraints may require system operators to dispatch certain units
that are more expensive than other available units.
• It is time consuming to start and stop many types of large generating units.
Limitations on unit "ramp-up rates" also force system operators to keep some
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units running during periods when they are not needed (in order to have the units
available when they are needed). These are referred to as load following, or
intermediate units, and are often running at a lower and less efficient rate while
not producing any power for input into the grid.
• System operators do not treat generating units as single entities in the dispatch
process. Instead, plant owners in competitive markets typically bid the power
from an individual generating unit into a smaller number of "blocks" that are
instead bid into the grid.
Because actual unit dispatch often looks very different from the ideal shown in Figure
B.3., environmental regulators and others should be aware of how these electric-system
realities are represented in control-measure estimates of emissions reductions.
Figure B.3: Unit Dispatch in a Power System
25,000
4 5
Day of the Week
SECTION B.4: THE LOCATION OF EMISSIONS REDUCTIONS RELATIVE
TO THE SITING OF CLEAN ENERGY RESOURCES
The goal of clean energy policies in the SIP planning context is typically to reduce
emissions within the state, tribal area or region where the policies are implemented. To
achieve this goal, all (or a portion of) the emissions reductions from EE/RE must occur in
a location that affects air quality in the implementing jurisdiction. The environmental
regulator can take steps to ensure that the analysis supporting such a policy accounts for
the interconnected and dynamic nature of the power system, and that it examines the
possibility that the benefits of clean energy policies may not be completely realized
within the jurisdiction of interest.
This can be illustrated by the example of a state with a renewable portfolio standard
requiring utilities to buy a fixed percentage of their electricity from renewable energy
facilities. If a local utility signs an energy-purchase contract with the nearest renewable
facility, the state may find it difficult to correlate wind power produced by that wind farm
to a corresponding reduction in electric output and emissions from specific fossil-fuel
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generators. The implementing state needs to ensure that the emission reductions occur at
an upwind or nearby facility that affects the implementing state's air quality.
For this reason, it is critically important to understand and accurately predict how the
regional power grid is likely to behave when assessing the emissions benefits from clean
energy resources.
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Appendix C: Existing Energy
Efficiency/Renewable Energy
Guidance
SECTION C.I: INTRODUCTION
The purpose of this appendix is to provide brief information on existing EPA guidance
that touches on EE/RE and SIPs. It is organized by pathway. EPA has issued five
guidance documents related to incorporating EE/RE programs in SIPs or one of the four
pathways:
• Guidance on State Implementation Plan (SIP) Credits for Emission Reductions
from Electric-Sector Energy Efficiency and Renewable Energy Measures, August
2004.
• Guidance on Incorporating Emerging and Voluntary Measures in a State
Implementation Plan (SIP), September 2004.
• Guidance on the Use of Models and Other Analyses for Demonstrating
Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze, April
2007.
• Incorporating Emerging and Voluntary Measures in a State Implementation Plan
(SIP), September 2004.
• Guidance on Incorporating Bundled Measures in a State Implementation Plan,
August 2005.
SECTION C.2: EXISTING GUIDANCE ON BASELINE PATHWAY
There are several guidance documents that provide recommendations on how to estimate
emissions for future years. Among point source emissions, there are two major subsets:
electric generating utilities (EGUs) and non-EGUs. The Clean Air Markets Division
(CAMD) of the U.S. EPA uses the Integrated Planning Model (IPM) to model emissions
trading programs and to predict future-year emissions from EGUs. More information on
IPM is available at (http://www.epa.gov/airmarkt/epa-ipm/). Additionally, IPM-based
emissions are posted by CAMD on EPA's website (http://www.epa.gov/airmarkets/epa-
ipm/iaqr.html). Other models may exist and could be used for estimation of future-year
emissions.
SECTION C.3: EXISTING GUIDANCE ON CONTROL MEASURE PATHWAY
EPA guidance spells out the criteria that energy efficiency/renewable energy (EE/RE)
measures need to address to be a SIP control measure:
• Quantifiable;
• Surplus;
• Enforceable; and
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• Permanent.
Quantifiable
The EE/RE measure guidance spells out four steps to address when trying to quantify
EE/RE measures:
• STEP1: Estimate the energy savings that an energy efficiency measure will
produce, or, for a renewable energy project, the amount of energy generation that
will occur.
• STEP 2 - Convert the energy impact in STEP 1 into an estimated emissions
reduction.
• STEP 3 - Determine the impact from the estimated emission reduction on air
quality in the nonattainment area.
• STEP 4 - Provide a mechanism to validate or evaluate the effectiveness of the
project or initiative.
The guidance also indicates that emission reductions generated by measures to reduce
emissions must be quantifiable and include procedures to evaluate and verify over time
the level of emission reductions actually achieved. The emission quantification and
evaluation methods in this guidance may be used to satisfy this criterion. However, since
there can be many types of energy efficiency or renewable programs covering many
different areas, alternative protocols may also be acceptable, and would be evaluated, as
necessary, on a case-by-case basis.
Surplus
The EE/RE measure guidance indicates that emission reductions are surplus as long as
they are not otherwise relied on to meet air quality attainment requirements in air quality
programs related to your SIP. In the event that the measures to reduce utility emissions
are relied on by you to meet air quality-related program requirements, they are no longer
surplus and may not be used as an additional reduction to meet SIP emission reduction
requirements, such as the attainment demonstration, RFP, or ROP. The surplus
requirement is especially important in areas subject to a cap and trade program.
If an energy efficiency program causes several EGUs that are part of a cap and trade
program to scale back the amount of electricity they generate and therefore reduce overall
emissions, it may be difficult to show that these reductions meet the "surplus" criteria for
crediting the measure. This is because the units are still allowed to emit up to the same
number of allowances in the program even though the amount of electricity they need to
generate has been reduced. The energy efficiency or renewable energy measure, in effect,
allow the EGUs to comply with the cap and trade program with a slightly higher average
emission rate and a theoretically lower allowance price. Therefore, the estimated
emission reductions from the energy efficiency or renewable energy measure would
typically not be surplus, and would essentially be double counted if we permitted the
allowances that were freed up by the measure to be used and also provided additional SIP
credit for the energy efficiency actions.
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The presence of a cap and trade program, however, does not necessarily prohibit the use
of energy efficiency and renewable energy measures by a State agency to achieve
additional SIP reductions. One acceptable way of achieving additional emission
reductions from energy efficiency and renewable energy measures in the presence of a
cap and trade program is through the retirement of allowances commensurate to the
emissions expected to be reduced by the energy efficiency measures. The retirement of
allowances provides some level of assurance that the energy efficiency measures will
achieve emission reductions that are surplus to the emissions reductions under the cap
and trade program. Another way is to clearly demonstrate that emissions decrease in the
area despite the cap and trade program and the ability for plants to sell more electricity to
other areas. This demonstration will likely entail a detailed analysis of electricity dispatch
and allowance markets to determine the specific impact of the measures on the system.
Enforceable
The EE/RE measures guidance indicates that EE/RE measures may be:
• Enforceable directly against a source;
• Enforceable against another party responsible for the energy efficiency or
renewable energy activity; or
• Included under our voluntary measures policy.9
EPA believes that most measures you may consider under the guidance would fall into
the second or third categories listed above. Energy efficiency and renewable energy are
unlike traditional control measures on stationary sources. There is typically a physical
distance between where the measure is implemented and the emission reductions, as well
as a geographic distribution to the emission reductions. Since electric generating units
are interconnected in the electric grid, a reduction in energy demand or generation from a
renewable resource will likely affect the operation and emissions of several fossil fired
units in the system. The energy efficiency or renewable energy measure itself may be
enforceable against the entities undertaking the activity even though they are not
responsible for the operation of the electric generators at which the emission reductions
are estimated for purposes of the SIP. For example, you could require certain entities to
purchase an amount of renewable energy. If you rely upon such requirements within the
SIP, then such measure could be enforceable against the entities required to purchase the
renewable electricity or to reduce energy consumption, even if those entities are not
responsible for the operation of the electricity generating units at which the emission
reductions are expected to occur.
If the reductions are "enforceable directly against the source", then they are considered
enforceable if:
• They are independently verifiable;
• Violations are defined;
9 "Incorporating Voluntary Stationary Source Emission Reduction
Programs into State Implementation Plans," USEPA/OAQPS, January 19, 2001,
http://www.epa.gov/ttn/oarpg/tl/memoranda/coverpol.pdf.
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• Those liable for violations can be identified;
• The state and EPA maintain the ability to apply penalties and secure appropriate
corrective actions where applicable;
• Citizens have access to all the emissions-related information obtained from the
source;
• Citizens can file suits against the source for violations; and
• They are practicably enforceable in accordance with EPA guidance on practicable
enforceability.
If the reductions are "enforceable against another party responsible for the energy
efficiency or renewable energy activity", then they are considered enforceable if:
• The activity or measure is independently verifiable;
• Violations are defined;
• Those liable for violations can be identified;
• The state and EPA maintain the ability to apply penalties and secure appropriate
corrective actions where applicable;
• Citizens have access to all the required activity information from the responsible
party;
• Citizens can file suits against the responsible party for violations; and
• The activity or measure is practicably enforceable in accordance with EPA
guidance on practicable enforceability.
Permanent
The EE/RE measure should be permanent throughout the term for which the credit
is granted unless it is replaced by another measure or the State demonstrates in a
SIP revision that the emission reductions from the measure are no longer needed to
meet applicable requirements.
SECTION C.4: EXISTING GUIDANCE ON EMERGING/VOLUNTARY
MEASURES PATHWAY
EPA guidance describes an emerging measure as a new emission reduction or pollutant
reduction measure that is more difficult to accurately quantify than traditional SIP
emission reduction measures. The difficulty in quantifying the emission or pollutant
reductions may be due to scientific, technological, or informational uncertainty. The
ability to quantify reductions from emerging measures may require development of a
protocol based on assumptions and/or modeling to estimate the reduction impacts of the
emerging measure. A voluntary measure is an action by a source that will reduce
emissions of a criteria pollutant or a precursor to a criteria pollutant that the State could
claim as an emission reduction in its SIP for purposes of demonstrating attainment or
maintenance of the NAAQS, RFP, or ROP, but that is not directly enforceable against a
source. EPA guidance also describes how States can identify individual voluntary and
emerging measures and "bundle" them in a single SIP submission.
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How A State Can Get SIP Approval For Emerging/Voluntary Measures
A State would submit a SIP to EPA which:
• Identifies and describes the measure;
• Contains projections of emission or pollutant reductions attributable to the
program, along with relevant technical support documentation, including, for
emerging measures, a full discussion of the relevant best available science
supporting the measure;
• Enforceably commits the State to implementation of those parts of the measure
for which the State or local government is responsible;
• Enforceably commits the State to monitor, evaluate, and report at least every three
years to the public and EPA on the resulting emissions effect of the emission or
pollutant reduction measure;
• Enforceably commits the State to remedy any SIP credit shortfall in a timely
manner, if the program does not achieve projected emission reductions;
• Meets all other requirements for SIP revisions under sections 110 and 172 of the
CAA; and
• Undergoes public notice and comment as any other SIP revision.
Four Criteria For SIP Emerging/Voluntary Measures
Quantifiable
Emissions and emission reductions attributed to the measure are quantifiable if someone
can reliably and replicably measure or determine them. Any uncertainty in the
quantification should be addressed by following the guidance contained in the Economic
Incentives Program (EIP)10 in section 5.2 (b). Voluntary measures should meet this
provision unless the measure is also an emerging measure.
For emerging measures, EPA allows flexibility for the quantification requirement. Some
areas want to try new types of emission control or pollution reduction strategies. Some of
these new strategies have a substantial chance to be as effective (and possibly more
effective) than current measures in reducing criteria pollutant levels. The EPA supports
and wishes to promote the testing of new emission and pollutant control strategies. This
policy provides a mechanism that allows States to receive provisional emission reduction
credit in their SIP for new emission control and pollutant reduction strategies that have
the potential to generate additional emission reductions or air quality benefits.
Provisionary emission reductions or pollutant reduction strategies can become permanent
when post-implementation evaluations validate the amount of emission reductions
achieved. "Provisionary" in this case means the State may use particular emission
reductions for RFP or other purposes before the quantification procedure has been fully
validated. Even though these emission reductions can be used to fulfill CAA emission
reduction requirements, if post implementation evaluations do not show that all the
projected emissions reductions have occurred, the State must reconcile the difference
10
"Improving Air Quality with Economic Incentive Programs," EPA- 452/R-01-001, January
2001.
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between the projected and actual emissions reductions. In order to encourage emerging
new programs with which EPA and the States do not have significant experience, but
which are technically and scientifically sound, the Agency believes it is appropriate to
allow quantification based on best available science or information where direct,
empirically verified data are not available. In these circumstances, the State should
quantify the pollution reduction based on the best knowledge currently available for the
measure being considered. The State should develop a protocol based on a carefully
considered determination of the activities that it is committing to undertake and the
activities' projected impact on pollution. The estimates may be based on modeling, on
extrapolated experience for similar types of projects or on another approach that is likely
to yield a reasonable estimate of pollution reduction.
Surplus
Emission reductions used to meet air quality attainment requirements are surplus as long
as they are not otherwise relied on in air quality-related programs relating to a SIP. For
voluntary and emerging measures, EPA believes these reductions should also be surplus
to adopted State air quality programs, even those programs that are not in the SIP, such as
a consent decree and Federal rules that focus on reducing criteria pollutants or their
precursors. For emission reductions used for attainment, RFP, ROP, maintenance or
general conformity, the emission reductions cannot already be assumed for the same
requirement, where the requirements are cumulative. An emission reduction may be used
for more than one of these requirements. For example, emission reductions used to meet
the RFP requirement may also be used for the attainment demonstration. However
emission reductions are not surplus if they have already been assumed in a program. In
other words, States cannot claim emission reductions that are already assumed in the
existing SIP, or that result from any other emission reduction or limitation of a criteria
pollutant or precursor that the State is required to have to attain or maintain a NAAQS or
satisfy other CAA requirements. In the event that emission reductions relied on from a
measure are subsequently required by a new air quality related program, such as those
listed above, those emission reductions would no longer be surplus for this purpose.
Enforceable
While we have already stated that voluntary measures are not enforceable against the
source, the State would be responsible for assuring that the emission reductions credited
in the SIP occur. The State would make an enforceable commitment to monitor, assess
and report on the emission reductions resulting from the voluntary measures and to
remedy any shortfalls from forecasted emission reductions in a timely manner as
discussed below.
Emission reductions and other required actions are enforceable against the source if for
each source:
• They are independently verifiable;
• Program violations are defined;
• Those liable can be identified;
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• For emerging measures, the State and the EPA maintain the ability to apply
penalties and secure appropriate corrective action where applicable;
• They are enforceable in accordance with other EPA guidance on practicable
enforceability;
• For voluntary measures, the EPA maintains the ability to apply penalties and
secure appropriate corrective action from the State where applicable and the State
maintains the secure appropriate corrective action with respect to portions of the
program that are directly enforceable against the source;
• Citizens have access to all the emissions-related information obtained from the
source; and
• For emerging measures, citizens can file suits against sources for violations.
Permanent
The voluntary/emerging measures guidance indicates that an emission reduction strategy
must continue throughout the term that the credit is granted unless it is replaced by
another measure (through a SIP revision) or the State demonstrates in a SIP revision that
the emission reductions from the measure are no longer needed to meet requirements that
apply to voluntary and emerging measures.
Emission Reduction (SIP) Credit
The EPA believes that it is appropriate to presumptively limit the amount of emission
reductions allowed for approval under this policy. Although EPA concludes that
emerging measures are consistent with the statute because all emerging measures will be
accompanied with an appropriate enforceable backstop commitment from the state as
described in this policy, EPA believes it is appropriate to limit these measures to a small
portion of the SIP given the untested nature of the control mechanisms. The presumptive
limit is 6 percent of the total amount of emission reductions required for the ROP, RFP,
attainment, or maintenance demonstration purposes. The limit applies to the total number
of emission reductions that can be claimed from any combination of voluntary and/or
emerging measures, including those measures that are both voluntary and emerging. The
limit is presumptive in that EPA believes it may approve measures into a SIP in excess of
the presumptive six percent where a clear and convincing justification is made by the
State as to why a higher limit should apply in their case. Any request for a higher limit
will be reviewed by EPA on a case-by-case basis. Any approval of emerging measures
under this policy will be conducted through full notice-and-comment rulemaking in the
context of a particular state SIP revision.
Bundling Emerging/Voluntary Measures
Emerging/voluntary measures can also be bundled together. The emissions reductions
for each measure in the bundle would be quantified and, after applying an appropriate
discount factor for uncertainty, the total reductions would be summed together in the SIP
submission. After SIP approval, each individual measure would be implemented
according to its schedule in the SIP. It is the performance of the entire bundle (the sum
of the emissions reductions from all the measures in the bundle) that is considered for SIP
evaluation purposes, not the effectiveness of any individual measure.
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SECTION C.5: EXISTING GUIDANCE ON WOE PATHWAY
The air quality modeling guidance issued in 2007 addresses the weight-of-evidence
approach for attainment demonstrations. The guidance indicates that States/Tribes
should always perform complementary analyses of air quality, emissions and
meteorological data, and consider modeling outputs other than the results of the
attainment test. Such analyses are instrumental in guiding the conduct of an air quality
modeling application. Sometimes, the results of corroboratory analyses may be used in a
weight of evidence determination to show that attainment is likely despite modeled results
which may be inconclusive. The further the attainment test is from being passed, the
more compelling contrary evidence produced by corroboratory analyses must be to draw
a conclusion differing from that implied by the modeled attainment test results. If a
conclusion differs from the outcome of the modeled test, then the need for subsequent
review (several years hence) with more complete data bases is increased. If the test is
failed by a wide margin (e.g., future design values outside the recommended range at an
individual site or multiple sites/locations), it is far less likely that the more qualitative
arguments made in a weight of evidence determination can be sufficiently convincing to
conclude that the NAAQS will be attained. Table 2.1 contains guidelines for assessing
when corroboratory analyses and/or weight of evidence determinations may be
appropriate.
In a weight of evidence (WOE) determination, States/Tribes should review results from
several diverse types of air quality analyses, including results from the modeled
attainment test. As a first step, States/Tribes should note whether or not the results from
each of these analyses support a conclusion that the proposed strategy will meet the air
quality goal. Secondly, States/Tribes should weigh each type of analysis according to its
credibility, as well as its ability to address the question being posed (i.e., is the strategy
adequate for meeting the NAAQS by a defined deadline?). The conclusions derived in the
two preceding steps are combined to make an overall assessment of whether meeting the
air quality goal is likely. This last step is a qualitative one. If it is concluded that a
strategy is inadequate to demonstrate attainment, a new strategy is selected for review,
and the process is repeated. States/Tribes should provide a written rationale documenting
how and why the conclusion is reached regarding the adequacy of the final selected
strategy. Results obtained with air quality models are an essential part of a weight of
evidence determination and should ordinarily be very influential in deciding whether the
NAAQS will be met.
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Appendix D: Understanding State
Renewable Energy and Energy
Efficiency Policies
SECTION D.I: INTRODUCTION
States have adopted and implemented a wide range of policies aimed at increasing the
quantity of energy efficiency and renewable energy resources. These policies have been
implemented for many reasons including energy security, resource diversity, economic
development, reducing exposure to volatile fuel prices, and improving air and water
quality and public health. This appendix provides a general description of common
energy efficiency and renewable energy policies, and provides some key questions for
state officials to consider when evaluating whether it makes sense for a state to account
for the future impacts of EE/RE policies in a SIP.
SECTION D.2: OVERVIEW OF STATE RENEWABLE ENERGY POLICIES
For purposes of this manual, the discussion of renewable energy policies will focus on
state Renewable Portfolio Standards (RPS). States may have other renewable energy
policies including surcharges on bills to be invested in renewable energy projects,
financial and tax incentives to allow businesses and residents to install renewable energy
projects on their sites, and tax incentives to lure renewable energy businesses to a state.
RPS are emphasized here as these policies, when implemented, impact the operation of
large numbers of power plants and potentially decrease emissions from that sector in a
particular state or power pool.
RPS are typically implemented and enforced by state energy officials or public service
commissions, and require that entities that sell electricity in that state to consumers to
procure a minimum amount of their electricity supply from renewable electricity sources.
RPSs are also enforced by these agencies, and must be updated and/or revised by
legislation or regulation.
For more information on RPSs and other state renewable energy policies, see EPA's
Guide to Action (Chapter 5) and other resources highlighted in section D.6 of this
appendix.
As of this writing, 37 states had implemented some form of a RPS.11 However, there are
significant differences between state policy designs, including:
http://www.dsireusa.org/
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• The quantity of renewable energy that utilities must buy procure as a percentage
of the total annual electricity demand;
• The definition of what energy sources qualify as renewable;
• The geographic location where the renewable energy facilities need to be located;
• Vintage restrictions or not, to determine the eligibility of facilities (e.g., hydro
facilities that existed prior to the RPS being enacted);
• Whether the renewable portfolio standard is voluntary;
• Penalties and the amount that utilities must pay if they do not meet the RPS
In order to consider a RPS as a control strategy, or to factor it into a baseline calculation,
the state needs to understand the details of its RPS, and its impacts on the operations and
emissions of fossil fuel fired power plants that affect its state. For instance, at its most
basic, a RPS may require the construction of renewable energy facilities such as wind
farms. Since technologies have not yet developed to store significant quantities of
electricity, when a wind plant is generating electricity, then a local fossil plant will be
backed off, producing emission benefits. If a state's RPS requires that renewable energy
be produced locally, then localized emission benefits will be easier to demonstrate. If a
state allows renewable energy to be imported from far away, the benefit becomes a bit
harder to prove.
In addition, the US Department of Energy's Annual Energy Outlook (AEO) factors state
RPS programs into its reference case energy demand forecasts. For example, the AEO
2010 includes state RPS policies which were in place as of September 2009. As a result,
state emission forecasts that use the IPM model will already have state RPS policies
reflected in the forecast. States using IPM would not need to do additional work to
include the RPS in their SIPs because that would result in double counting.
See Table D.I for a comparison of programs in three states. For example, the
Massachusetts has very aggressive RPS requirements. Its program requires that 15% of
the state's electricity demand come from Class I renewable resources (wind, solar, hydro,
landfill gas, etc.) by 2020, and increases 1% per year after that. Massachusetts has 2
classes of renewable resources, with RPS obligations for each. Class I are the newest
renewable energy facilities, while Class II are "vintage facilities" that were in operation
prior to 1997. Class II also includes waste energy facilities. In addition, much of the MA
RPS obligations are being met by imports from other states and power pools.12
SECTION D.3: OVERVIEW OF STATE ENERGY EFFICIENCY POLICIES
For purposes of this manual, energy efficiency policies refer to a range of laws,
regulations and programs aimed at reducing energy demand through the use of more
energy efficient equipment, technologies and practices. These programs can be funded
through ratepayer surcharges, Federal funds (e.g., ARRA, State Energy Programs,
proceeds from pollution auctions such as the Regional Greenhouse Gas Initiative (RGGI)
and/or any combination of the above). Examples include:
12 A power pool is an association of two or more interconnected electric systems having an agreement to
coordinate operations and planning for improved reliability and efficiencies.
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• Minimum efficiency requirements for new homes and buildings (building energy
codes) or appliances (appliance standards)
• Requirements for utilities (or other program administrators) to deliver a specified
amount of energy savings by developing energy efficiency programs to increase
market adoption of EE technologies and practices (i.e., energy efficiency resource
standards)
• Specified funding levels dedicated to implementing energy efficiency programs (e.g.,
public benefits funds, air pollution allowance auction revenue).
In addition to the EE policies described above, a number of important regulatory
mechanisms (e.g., utility incentive structures, innovative rate designs, smart grid
investments) can help achieve a state's overall energy efficiency goals. However, these
approaches are less relevant for the purposes of this guidance, either because the impacts
of these policies are accounted for in the policies already described above or because the
impacts of their impacts are especially difficult to quantify.
Federal, state, and local governments may have authority over energy efficiency policies.
For example, building energy code policies are typically developed at the federal level,
adopted by states, and enforced by localities. Almost all states have some form of
electric-sector energy efficiency programs. Most of them are funded through ratepayer
surcharges, block grants to the states from the Department of Energy (DOE) or with
proceeds from auctions such as RGGI. The money collected from these surcharges is
then reinvested, under the supervision of the Public Utility Commission, in a series of
programs approved by each state to achieve the stated policy goals of reducing energy
consumption. Examples of these types of programs include providing subsidies for more
energy efficient equipment, revision to building codes and standards, etc. These
programs may be administered by utility officials, independent third party energy
authorities, and/or state energy officials.
Similar to RPS discussed above, energy efficiency policies vary by state. Differences
include:
• Level of funding;
• Stability of funding year to year;
• Evaluation, Measurement and Verification (EM&V) techniques and energy
savings calculations;
• Energy savings goals for the programs;
• Degree of enforceability
In order to appropriately estimate the energy savings from these programs a state must
have infrastructure in place to support Evaluation, Measurement and Verification
(EM&V) efforts. A rigorous and credible EM&V program will provide environmental
regulators with a degree of certainty that savings claimed by the energy efficiency
policies are actually being achieved.
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For more information on state energy efficiency policies, see EPA's Guide to Action
(Chapter 4) and the other resources highlighted in section D.6 of this appendix.
For more information on state regulatory mechanisms, see the National Action Plan for
Energy Efficiency.
In order to consider energy efficiency policy as a control strategy, or to factor it into a
baseline calculation, the state needs to understand the details of its policy, and its impacts
on the operations and emissions of fossil fuel fired power plants that affect its state. At
its most basic, when users are using less electricity, then less electricity needs to be
generated and emissions are thus avoided. Energy efficiency programs result in emission
benefits since a power plant that otherwise might be dispatched is sitting idle or operating
at a lower output.
Once the state is comfortable with the estimates of energy savings, those savings then
need to be evaluated against the operational characteristics of the power pool in which
they are implemented. Often times, energy savings reported from energy efficiency
programs are given in a gross number of kilowatt hours per year, without respect to the
time of year or time of day in which those savings may have been realized. Given that
emissions associated with electricity generation are not evenly distributed over the course
of a day, a month or a year, some correlation needs to be demonstrated between the time
of day and year that an energy efficiency measure provides benefit. For instance, during
hot summer days many more power plants are running to meet increased electricity
demand. On those days, emissions are typically higher than a cool fall day due to the fact
that older, less efficient, and dirtier plants are called to meet the increased demand during
those periods.
So, in order to accurately characterize the emission benefit from an energy efficiency
program, the state needs to be able to tie the energy savings from that effort to the
emissions associated with the time that the effort is reducing demand from the electric
grid. This exercise is much more complex than is the case for an RPS due to the fact that
renewable energy sold into a power pool is tracked and metered every hour of the day;
whereas the benefits from efficiency are estimated using EM&V techniques (see
Appendix E for more details on appropriate quantification methodologies).
For more information on converting energy efficiency and renewable energy policy
impacts into emissions impacts, see Appendix E for the baseline pathway, Appendix F
for the control measure pathway, and Appendix G for the weight of evidence pathway.
SECTION D.4: EXAMPLES OF STATE POLICIES
Table D.I provides examples of three states' policies. The states featured are for
illustrative purposes only, but are intended to show the range of policies in place today.
The state of Connecticut has a mature set of programs that have been mandated by the
state legislature and are well funded. The state's primary EE program is a ratepayer
funded Public Benefit Program that, among other activities, provides resources to assist
homeowners and businesses to adopt a range of energy efficient technologies and
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practices. In 2009, Connecticut ranked 9* in the United States with respect to per capita
energy efficiency expenditures. The state's RPS program was started in 2000 and will
reach a maximum required percentage of 27 percent by 2020, among the highest in the
country.13
In 2007, North Carolina created its renewable energy and energy efficiency portfolio
standard (KEEPS). Under the KEEPS, public electric utilities in the state must obtain
renewable energy power and energy efficiency savings of 3% of prior-year electricity
sales in 2012, increasing to 12.5% in 2021. Energy efficiency is capped at 25% of the
2012-2018 targets and at 40% of the 2021 target. Under this program, individual utilities
now administer energy efficiency and renewable energy programs in North Carolina with
oversight and approval from the North Carolina Utilities Commission. Rate-regulated
utilities may recover the costs for renewable energy and energy efficiency programs
through a Demand Side Management/Energy Efficiency rate rider.14
Utilities in Mississippi offer few energy efficiency programs. Some do report energy
savings and one utility company offers loans for residential customers. Mississippi
currently has no RPS program.
Table D.I - Brief Overview of RE/EE Policies for Three States
EE/RE Policies Connecticut North Carolina Mississippi
Energy Efficiency Policies
How Long have EE policies
been in place?
Annual Funding for EE
Impact of EE Policies
Renewable Energy Policies
How long has RPS been in
place?
Impact of RPS
Compliance Mechanism
Yes
2000
$73. 4 million
3 54,000 Mwh saved
(2008)
Yes
1998
27% of electric
demand by 2020
Yes
Yes
2005
$64.3 million
15,000 Mwh
saved (2008)
Yes
2008
12. 5% of electric
demand by 2021
Yes
Yes
1980
$9.2 million
1 1,000 Mwh saved (2008)
No
N/A
N/A
N/A
SECTION D.5: HOW STATE EE/RE PROGRAMS AND POLICIES ARE
ADMINISTERED
As stated earlier, most EE and RE policies are implemented by state energy offices or
public utility/service commissions, and not administered through a state's environmental
office, though the benefits from these programs may have significant positive
environmental impacts. While a state environmental agency may not administer or
enforce these policies, their successful implementation may have significant
environmental impacts. For example, an RPS that requires utilities to purchase from
renewable energy facilities within its state or air shed may result in fossil fired units in
13 http://appsl.eere.energv.gov/states/maps/renewablejortfolio states.cfm
14 http://www.aceee.org/sector/state-policv/north-carolina
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the same area running less frequently resulting in significant air pollution benefits that are
not reflected in a typical DEP permitting program for power plants. So it is in the
interests of DEP staff to become acquainted with these policies and their potential
environmental benefits.
In all cases, it is important for state environmental regulators to familiarize themselves
with their counterparts in the PUCs and energy offices in their respective states.
EPA encourages States to focus the majority of its EE/RE in SIPs effort on EE/RE
policies, since these are what States can point to as being "on the books" and because
policies have more potential to provide meaningful impacts. Many of the specific EE/RE
programs a State runs in any particular year will be captured by accounting for the
policies that fund or require them. In attempting to account for individual EE/RE
program impacts in SIPs, States should be sure to demonstrate that these programs are
incremental to any EE/RE policies the State is also accounting for in its SIP. For
example, if a State is already accounting for the impacts of its EERS, it should not also
include incremental impacts for a residential CFL incentive program that the utilities in
the state develop to help meet the EERS.
SECTION D.6: WHERE TO GO FOR MORE INFORMATION
There are several places the reader can go for more information including:
• The Database of State Incentives for Renewables and Efficiency (DSIRE) is a
comprehensive source of information on state, local, utility and federal incentives
and policies that promote renewable energy and energy efficiency. Established in
1995 and funded by the U.S. Department of Energy, DSIRE is an ongoing project
of the N.C. Solar Center and the Interstate Renewable Energy Council.
http ://www. dsireusa. org/
» The American Council for an Energy Efficient Economy (ACEEE) is a national
nonprofit organization dedicated to advancing and deploying energy efficiency
technologies, policies, programs, and behavior. They provide up to date
information on energy efficiency programs and policies for all 50 states^
http://www.aceee.org/sector/state-policy
• EPA State Climate and Energy Program:
http://epa.gov/statelocalclimate/state/index.html
• Guide to Action: http://epa.gov/statelocalclimate/resources/action-guide.html
• National Action Plan for EE: http://www.epa.gov/cleanenergy/energy-
programs/suca/resources.html
• LBNL on RPS: http://eetd.lbl.gov/ea/ems/reports/lbnl-154e-revised.pdf
• LBNL or EE: http://eetd.lbl.gov/ea/ems/reports/lbnl-2258e.pdf
• The Regulatory Assistance Project: www.raponline.org
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Appendix E: Baseline Pathway
SECTION E.I: BASICS OF FUTURE ATTAINMENT YEAR BASELINE
APPROACHES
Introduction To The Baseline Pathway For SIP/TIP Air Quality Modeling
A baseline forecast of emissions in the future attainment year is made when a jurisdiction
prepares a SIP/TIP or performs a SIP/TIP revision. Because projected emission levels are
affected by demand for electric power and new generation capacity, jurisdictions can take
steps to understand the impacts of their EE/RE policies and programs, and to represent
these impacts in baseline emission forecasts.
The goal of developing a future emissions baseline projection is to account for as many
important variables as possible that affect future year emissions which will in turn affect
ambient air quality levels. Emission
levels (in addition to meteorology and
topography, transport and fate of
pollutants) are one of the most
important parameters in determining
resultant ambient air quality; however,
emissions and ambient concentrations
are not linearly related. Hence state,
tribal and local agencies need an Air
Quality Modeling (AQM) analysis for a
base year and a future attainment year
to assess the relationship between
emission levels and the resultant
ambient air quality. Similarly, emission
projections provide a basis for
developing control strategies for
SIPs/TIPs, conducting control policy future attainment year AQM attainment analyses,
and tracking progress towards meeting air quality standards.
Completed Action
•/
•/
S
•/
S
•/
Select a baseline demand forecast to
use for EGU projections
Assess new and existing generation
capacity of EGU' s in future year(s)
Determine what EE/RE policy
assumptions are already in EGU
baseline forecast
Select energy model or other approach
for projecting EGU emissions
Account for "on the books"
mandatory EE/RE policies in
modeling or other approach
Document results of modeling or other
approach
EPA's Baseline Emission Forecast For EGUs
EPA develops and periodically updates a power sector database, The National Electric
Energy Data System (NEEDS). NEEDS contains the unit level records of all existing
and planned/committed units in EPA power sector modeling applications. The NEEDS
database includes basic geographic, operating, air emissions, and other data on these
generating units.
EPA uses the Integrated Planning Model (IPM) to simulate the power sector behavior and
to analyze the impact of environmental regulations. A detailed documentation of the
latest publicly available versions of NEEDS and IPM are available at
http://www.epa.gov/airmarkets/progsregs/epa-ipm/BaseCasev410.html
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IPM is a multi-regional, dynamic, deterministic linear programming model of the U.S.
electric power sector. It provides forecasts of least cost capacity expansion, electricity
dispatch, and emission control strategies while meeting energy demand and
environmental, transmission, dispatch, and reliability constraints. IPM can be used to
evaluate the cost and emissions impacts of proposed policies to limit emissions of sulfur
dioxide (SO2), nitrogen oxides (NOx), carbon dioxide (CO2), mercury (Hg) and HC1
from the electric power sector. Other emissions (including PM2.5 and PM10) are also
calculated with a post-processing step. IPM's capabilities in power sector modeling
include on-the-books (for baseline) or proposed (policy/control strategy) environmental
constraints (Federal or State level rules, settlements and consent decrees) as well as
EE/RE policies. IPM outputs are streamlined to be used as direct inputs into AQM.
State, Tribal Or Local Developed Baseline Forecast
State, tribal or local agencies may develop SIP/TIP-credible baseline emissions
inventories for the EGU sector or may utilize emission projections developed by EPA. If
a state, tribal or local agency chooses to develop their own future baseline emission
projections, the methodology used for the projections and or emissions growth need to be
documented in detail. If the methodology is highly dependent upon a large number of
input decisions (including expert judgment) that could vary from one application of this
approach to another, then EPA will review those input decisions when it reviews a
SIP/TIP and will judge at that point whether the modeling is acceptable. This approach is
consistent with what EPA does for other emission inventory and projections compiled for
other source sectors. For instance, for those emission source sectors where an EPA
approved or recommended model exits, EPA does not give automatic approval of its use
in any SIP/TIP without consideration of the inputs. In the same way, EPA will ask for
the detailed documentation of inputs (in this case, expert judgment decisions made by the
submitter of SIP/TIP). EPA's review will consider the specific input assumptions and
EPA may request further information or verification of the assumptions presented. In
summary, whether a particular application of a state, tribal or local agency will be
approved in a SIP/TIP will depend on the review of actual inputs, application by a state,
and credibility of the predictions.
Tradeoffs Between Four SIP/TIP Pathways
If a state, tribal or local agency is deciding into which SIP/TIP pathway to incorporate its
EE/RE policies, it is important to understand inherent tradeoffs among the future baseline
attainment year, control measure, voluntary and emerging and weight of evidence
pathways.
1) For the baseline pathway, state, tribal and local agencies generally include EE/RE
policies that are currently "on the books" at the time the baseline forecast analysis
commences. This means the EE/RE policy must already be adopted in federal or
state regulation, a public utility commission order and/or law to reflect the level of
emissions in the future attainment year that will result if no additional control
strategies are implemented. .
2) Assumptions included in SIP/TIP baseline projections are not subject to the same
enforceability requirements as SIP/TIP control measures. For example, EE/RE
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policies explicitly incorporated into a baseline future attainment year must be "on
the books". If the EE/RE policy is not implemented, state, tribal or local agencies
must work with their Regional EPA Office to determine how to take corrective
action, such as a SIP/TIP revision. EPA does have the authority to issue a call for
a revised SIP/TIP to be submitted by a state, tribal or local agency, if baseline
assumptions are not corrected.
Incorporating EE/RE Policies For The Baseline Pathway
Accurately describing EE/RE policies is a critical step for completing an EGU baseline
forecast. The realized and future expected energy savings from EE polices directly
affects electricity demand growth rates and their emissions in EGU baseline projections.
Similarly, RE policies directly affect the electric power sector's future portfolio of power
supply that is dispatched to meet demand. Therefore, understanding the EE/RE policy
assumptions will help predict how electricity demand and supply will change emissions
in the future. For more information on EE/RE policies, see Appendix D
The next section illustrates the steps states should consider when incorporating "on the
books" EE and/or RE policies within the baseline.
SECTION E.2: STEPS FOR INCORPORATING "ON THE BOOKS" EE
POLICIES
This section illustrates the three steps states should consider when incorporating "on the
books" EE policies within the baseline. After these steps, state, tribal and local agencies
should be ready to proceed to the final fourth step that is described in section E.4 -
forecasting the impacts in the EGU sector.
State, tribal and local agencies have two options for each of the following steps: using the
information provided by the Energy Information Administration (EIA) or using
information from provided by regional grid operators, Regional Transmission
Organization or Independent System Operators.
Step 1: Determine What Baseline Demand Forecast The State Or Region Will Use
For EGU Projections
Energy Information Administration's (EIA) Demand Forecasts
The standard national baseline projection for the EGU sector comes from the Energy
Information Administration (EIA). EIA, the statistical arm of the Department of Energy,
publishes an Annual Energy Outlook15 (AEO) every year that forecasts the future 25
years of U.S. energy demand, supply and price. For example, EPA makes use of AEO
demand projections for its electric sector forecasting. EPA updates the modeling
platforms with the new AEO forecasts as they become available. Energy supply and
demand projections from the AEO are also used as growth indicators upon which growth
factors for fuel/combustion-related processes are based.
' Most recent version as of the release of this document is AEO 2010
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Projections included in the AEO forecast are generated from the National Energy
Modeling System (NEMS), which is a computer-based energy-economy modeling system
developed and maintained by DOE. It projects the production, imports, conversion,
consumption, and prices of energy, subject to assumptions on macroeconomic and
financial factors, world energy markets, resource availability and costs, behavioral and
technological choice criteria, cost and performance characteristics of energy
technologies, and demographics.
Regional Transmission Organization Or Independent System Operator Demand
Forecasts
If States prefer, they can use the EGU baseline projections provided by regional
transmission organizations or independent system operators. States should work closely
with their regional office if their demand forecast information comes from one of these
organizations to ensure all environmental regulations are accounted for in the analysis.
Step 2: Determine What EE Policy Assumptions Are Already In EGU Baseline
Demand Projections
Energy Information Administration's (EIA) EE Policy Assumptions
EIA's Annual Energy Outlook documentation includes description of the many
assumptions they make in conducting their modeling. For AEO 2010, EIA includes
several federal policies and regulations that are "on the books" as of September 2009.
The EE policies that are explicitly in the 2010 AEO baseline projections16 are the
following:
• Federal Appliance Standards17
10 Residential & 10 Commercial Appliance Categories
• Federal Funding for State Energy Program (SEP) and Energy Efficiency
Community Block Grant (EECBG), Weatherization Program, Green Schools and
Smart Grid Expenditures. (E.g., through the American Recovery and
Reinvestment Act (ARRA))18
• Building Codes19
All States adopt and enforce:
IECC 2006 Code by 2011 and IECC 2009 Code by 2018 ASHRAE 90.1 -2007 by
2018
Regional Transmission Organization Or Independent System Operator EE Policy
Assumptions
If a state is using demand forecasts from their regional transmission organizations or
independent system operators, they should ask if the following EE policies are explicitly
16 AEO 2010 information canbe found at: http://www.eia.doe.gov/oiaf/archive/aeolO/index.html
17U.S. Energy Information Administration (2010). Assumptions to the Annual Energy Outlook 2010: With
Projections to 2035, Appendix A. p. 170-185
18 U.S. Energy Information Administration (2010). Annual Energy Outlook 2010: With Projections to
2035. p. 8-10.
19 Ibid pg. 8
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modeled with their load forecast, implicitly embedded within load forecast (e.g.,
accounted for econometrically) or not reflected within the load forecast.
• Energy Efficiency policies or programs funded by utility rate payers
• Existing federal appliance and lighting efficiency standards that are already in
effect
• New federal appliance and lighting standards that are scheduled to take effect
over the forecast period
• State appliance or lighting efficiency standards (if applicable)
• State building energy codes
• Combined heat and power capacity additions
• Other distributed generation capacity additions
• Other applicable policies/programs
Step 3: Review State, Tribal And Local "On The Books" EE Policies To Determine
If More Can Be Included Into The EGU Baseline Demand Projections.
Evaluating State, Tribal And Local EE/RE Policies Compared To Energy
Information Administration's (EIA) Assumptions
If states are using AEO 2010 demand forecast assumptions, EPA has identified "on the
books" EE policies not already explicitly incorporated into Annual Energy Outlook 2010
and developed assumptions about estimating EE policies implicitly embedded within
EIA's load forecast (e.g., accounted for econometrically). EPA is providing an
approvable methodology and energy savings information for future years 2012, 2015 and
202020:
• Energy Efficiency Resource Standards
• Other commitments to ratepayer-funded EE Programs (e.g., public benefit funds,
IRP, "all cost-effective" EE requirement)
• RGGI Funded EE Programs
Evaluating State EE Policies Compared To Regional Forecast Assumptions
If a state, tribal or local agency does not use EIA's demand forecasts, the jurisdiction
should talk with their regional transmission organizations or independent system
operators to determine if additional "on the books" state EE policies can be incorporated
in their forecast.
SECTION E.3: STEPS FOR INCORPORATING "ON THE BOOKS" RE
POLICIES
This section illustrates the three steps states should consider when incorporating "on the
books" RE policies within the baseline. After these steps, state, tribal and local agencies
20 See appendix I for details on the methodology and energy savings/generation information for the policies
listed here.
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should be ready to proceed to the final fourth step - forecasting the impacts in the EGU
sector.
Step 1: Determine What Renewable Energy Sources Are Already In Baseline
Inventory And The Relative Emission Factor For Each Type Of Renewable Energy
Generated In The State Or Region
As a first step, States need to assess what type of renewable energy is already
incorporated into the energy supply mix (absent of any policy influence or past policy
influence).
Step 2: Determine What RE Policy Assumptions Are Already In EGU Baseline
Supply Projections
Energy Information Administration's (EIA) RE Policy Assumptions
For AEO 2010, EIA includes state renewable energy portfolio standards policies that are
"on the books" as of September 2009. EPA uses the same RPS assumptions as EIA. The
RE policies that are explicitly in the 2010 AEO baseline projections21 and EPA's EGU
projections are the following:
• Renewable Energy Portfolio Standards (RPS)22
30 States and D.C. Effective as of Sept. 2009
Step 3: Review State, Tribal And Local "On The Books" RE Policies To Determine
If More Can Be Included Into The EGU Baseline Demand Projections
States should examine if the information source for EGU supply projections includes all
state RE adopted policies. If states are using EIA's supply forecast assumptions, EPA
has identified "on the books" RE policies not already explicitly incorporated into Annual
Energy Outlook 2010. EPA is providing an approvable methodology and energy
information for future attainment years 2012, 2015 and 202023:
• Renewable Energy Portfolio Standards (RPS)
Five States effective after Sept. 2009 and before December 2010
Documentation Requirements
In all, EE/RE policies are only a few of the many assumptions incorporated into an EGU
baseline projection. Any EE/RE policies that are explicitly included in an EGU baseline
projection must be properly documented as shown below.
21 AEO 2010 information can be found at: http://www.eia.doe.gov/oiaf/archive/aeolO/index.html
22 See full list at: U.S. Energy Information Administration (2010). Annual Energy Outlook 2010: With
Projections to 2035. p. 14-17
23 See appendix I for details on the methodology and energy savings/generation information for the policies
listed here.
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Table E.2: EE/RE Policies State X Explicitly Included in Baseline Projections
Policy Year Policy
Name Enacted Requirements
Annual Energy Annual Energy For RE Policies:
Savings/ Savings/ Type of RE
Generation in Generation in the source and
Base Year Future Attainment corresponding
Year(s) Emission Rate
Step 4: Perform Energy Modeling To Project EGU Baseline Emissions
Use IPM Modeling To Project Future Attainment Year Baseline For SIP/TIP Air
Quality Modeling
EPA is providing technical information for incorporating EE/RE policies in EGU
baseline projections. IPM runs will be available for interested states to adopt as their
SIP/TIP EGU baseline projections. The EE/RE policies incorporated in EPA's baseline
modeling were determined based on EPA and State input. Appendix I has more
information on the methodology used to quantify the energy saved/generated from state
"on the books" policies as well as how that information is integrated into IPM model
runs.
SECTION E.4: FUTURE ATTAINMENT YEAR BASELINE USING OTHER
APPROACHES FOR SIP/TIP AIR QUALITY MODELING
In addition to or instead of IPM modeling offered by EPA, states can conduct their own
SIP/TIP baseline emissions growth/forecast for the electric power sector. (The
methodology and final product of such effort will be evaluated for SIP/TIP-credibility) If
a state prefers to forecast EGU emissions through /• v^
their own means, EPA has provided information on
types of dispatch models, energy models or capacity
expansion models available for use in Appendix F.
For long term projections (more than 5 years),
capacity expansion models can predict how the
electric system will evolve over time; includes what
capacity will be added through the construction of
new generating units and what units will be retired,
in response to changes in new regulations, demand x '
and prices. This method involves allowing the model to predict what will likely happen to
the resource mix based on costs of new technology, growth, existing fleet of generating
assets, environmental regulations (current and planned) and EE/RE policy assumptions.
We are providing:
• Estimates of energy savings
and generation for state "on
the books" EE/RE policies
in a format useful for State
and EPA to use for EGU
baseline future attainment
years - Refer to Appendix I
for more information
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Alternative methodologies are highly dependent upon a large number of input decisions
(including expert judgment) that could vary from one
application to another. EPA regional offices will
review those input decisions when it reviews a
SIP/TIP and will judge at that point whether the
modeling is acceptable. Whether or not an EPA
approved or recommended model exists, EPA cannot
give approval of a baseline model or approach used in
any SIP/TIP without consideration of the inputs. EPA
will ask for the detailed documentation of inputs (in
this case, expert judgment decisions or by the
submitter of SIP/TIP). EPA's review will consider the
specific input assumptions and may question some of
them. However, whether a particular application of an
alternative approach will be approved in a SIP/TIP will depend on the review of actual inputs,
application by a state, and credibility of the predictions.
Using EPA's ECU baseline run has
advantages:
• No cost run available to states
• EPA will work with states to
modify input parameters and
assumptions to reflect state's views
• EPA and States are collaborating to
capture specific "on the books"
EE/RE Policies
• IPM emission outputs are directly
compatible for Air Quality
Modeling
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Appendix F: Control Strategy
Pathway
SECTION F.I: BASICS OF CONTROL STRATEGY PATHWAY
Description Of Pathway
A control strategy is a policy, program,
or requirement used by a state, tribal or
local agency in a nonattainment or
maintenance area to reduce ambient air
pollution levels in order to satisfy Clean
Air Act requirements. States adopt
control strategies for the purposes of
attaining the National Ambient Air
Quality Standards (NAAQS),
demonstrating reasonable progress
towards attainment, and maintaining
the NAAQS.
After control strategies are adopted,
they are submitted to EPA for
incorporation into a State
Implementation Plan (SIP) or Tribal
Implementation Plan (TIP) for a
particular air pollutant. Taken together,
all of the control strategies in a SIP/TIP
must reduce emissions to levels that
achieve attainment, maintenance, or
reasonable further progress, depending
on the type of SIP/TIP.
This appendix addresses the tradeoffs,
level of effort, methods, and other key
requirements involved in incorporating
energy efficiency and renewable energy
(EE/RE) policies and programs in a
SIP. As with any SIP/TIP pathway, EPA recommends that state, tribal and local agencies
coordinate with their EPA regional office as soon as they decide to move forward
Tradeoffs Of Control Strategy Pathway
Including EE/RE policies and programs in a control strategy in a SIP can help
jurisdictions meet their air quality goals by accounting for emission reductions needed to
show attainment, progress, or maintenance. The control strategy pathway may be an
Completed Action
•/
•/
•/
S
•/
•/
Determine that the jurisdiction wants
the EE/RE policy and program to be
enforceable under the CAA. (See
enforcement criterion in Section F.6
for details)
Assess if the EGUs in the
nonattainment area are subject to a cap
and trade program for the applicable
pollutant. (See surplus criterion, in
section F.6 for details)
Estimate the magnitude of potential
emission reductions before
undertaking more comprehensive
analysis (See Tier 4 in Section F.3 for
details)
Follow the Quantification Steps 1-4.
• Estimate EE savings or generation
from EE/RE policy /program
• Quantify emissions of EGUs
displaced
• Determine emission impacts of
emission reductions in
nonattainment area
• Provide mechanism to evaluate
and verify results.
(See Sections F.2,F.3 and F.4 for
details)
Provide mechanism to ensure Federal
enforceability
Ensure EE/RE policies/programs are
permanent and surplus
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especially appealing option to state, tribal and local agencies that are having difficulty
reaching attainment and are seeking new and viable emissions reductions opportunities.
Several tradeoffs and issues should be considered when deciding whether including
EE/RE policies and programs in the control measure pathway is consistent with the
jurisdiction's circumstances and objectives,. This will enable a state, local and tribal
agency to evaluate the merits of following the control measure approach in the context of
the other three pathways for achieving similar objectives, as addressed elsewhere in this
document.
Key tradeoffs and considerations when deciding whether to pursue the control measure
pathway include:
• Transparency: Of the four pathways this option offers the most transparent and
direct approach to estimating the air quality impacts of EE/RE policies. State,
tribal and local agencies will gain a better understanding of which EGUs will
displace emissions as a result of future EE/RE policies/programs. State, tribal and
local agencies will have a tons-per-day (TPD) amount of emissions for each EGU
they expect to reduce based on a specified EE/RE policy and program. State,
tribal and local agencies will have emission reductions from a control strategy to
help them attain.
• Documentation: More documentation is needed than the future baseline and
WOE approaches because under the Clean Air Act a jurisdiction would have to
show that the EE/RE policy/program was permanent, enforceable, quantifiable,
and surplus. (Sections F.2 - F.4 offer steps for quantifying the emission reduction
impact from EE/RE measures, and section F.5 addresses the permanent,
enforceable, and surplus requirement.)
• Traditional, Federal Enforceability: EE/RE policies and programs that are
included as a control strategy must be enforceable against the implementing party.
State, tribal and local agencies need to consider their role and responsibility, as
well as the associated resources needed to enforce EE/RE policies included in a
control strategy.
• Coordination: Early coordination will help ensure that responsible agencies and
entities understand their roles and have sufficient time dedicated to incorporating
EE/RE policies and programs as a SIP control strategy. Developing strategies and
determining their efficacy for meeting and maintaining compliance with
applicable NAAQS requires a high level of coordination amongst multiple
government agencies
• Level of Analytical Rigor: Overall, quantification under this pathway can be
more resource intensive because the state, tribal or local agency would have to
perform more of the EGU analysis than the baseline pathway in which EPA is
providing more support for EGU analysis. The specific level of effort necessary
for quantifying the emission reduction impacts depends on the analytical approach
selected. Although more sophisticated techniques typically require a greater level
of effort, a discount factor is built into the framework such that the less
sophisticated the technique, the more that resulting emission reductions are
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discounted. Section F.3 of this appendix describes tiers of analysis that range
from more to less sophisticated.
• Coordination Across Relevant State Agencies: Another factor affecting level
of effort is the degree to which agencies responsible for SIP implementation
coordinate with entities responsible for overseeing and evaluating EE/RE policies
and programs (e.g., typically the state's public utility commission). The purpose
of these discussions is:
• For the Air Quality Planners to fully understand the elements of the EE/RE
policy or program (including extent, duration, and anticipated impact of the
policies/programs)
• To ensure that all parties understand the implications of including EE/RE in
the SIP, including the obligation to sustain the program consistent with
agreements in the SIP
• To help the respective agencies better understand the other's roles and
responsibilities. In many cases, formal agreements can be established
between state air agencies and PUCs to outline each entity's obligations for
implementing the state's EE/RE activities, quantifying their impact, and
including them in the SIP.
Steps A State Needs To Take To Quantify Emissions Impacts
The next sections outline four steps for quantifying EE/RE policy or programs as a
control measure strategy:
1. STEP 1: Estimate the energy savings that an energy efficiency policy or
program(s) will produce, or, for a renewable energy project, the amount of
energy generation that will occur.
2. STEP 2 - Quantify or estimate displaced EGU emissions from energy impacts
of an energy efficiency or renewable energy policy/program(s).
3. STEP 3 - Determine the impact from the emission reduction on air quality in
the nonattainment area.
4. STEP 4 - Provide a mechanism to validate or evaluate the effectiveness of the
project or initiative.
SECTION F.2: STEP 1: ESTIMATE THE ENERGY SAVINGS THAT AN
ENERGY EFFICIENCY POLICY WILL PRODUCE, OR, FOR A RENEWABLE
ENERGY POLICY, THE AMOUNT OF ENERGY GENERATION THAT WILL
OCCUR
Introduction
After states develop an EGU baseline emission projection for future attainment years, the
next decision a state will make is to determine which EE/RE policies and programs it
wants to incorporate in its SIP as a control measure. Thereafter, the state will need to
determine the specific ways that the EE/RE policies/programs will affect either electricity
demand or generation supply characteristics of the applicable EGUs for the State's
emissions analysis. This involves understanding the type and quality of the historical or
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predicted energy saving/generation information (at different time frames - annual, peak,
seasonal and/or hourly information).
Essentially this first step is to contact the energy experts in your jurisdiction to obtain
estimates of the KWh impacts from the EE/RE policy/program of interest. EPA
recommends starting with the Public Utility Commission staff and State Energy Offices.
If jurisdictions need further information, the Energy Information Administration, and
electric grid operators can also be sources. Electric grid operators could be a large utility
that controls the dispatch of resources. A regional transmission organization or an
independent service organization can be helpful resources. These organizations should
have the energy impacts information or, at a minimum, serve as the most useful sources
for developing the energy savings or generation estimates for particular EE/RE policies
or programs.
Energy Savings From Energy Efficiency (EE) Policies
Energy savings refers to the expected reduction in the amount of energy generated
by an existing utility system as a result of the specific energy efficiency policy and/or
program. Energy savings can reduce current energy demand, future demand, or both. For
EE, the purpose of this step is to determine the energy saving impacts of the specific EE
policy/program.
In some circumstances, quantifying emission reductions may rely on determining the
actual energy impact, in practice, of the EE policy/program. Therefore, for later
verification purposes, data on the amount of energy savings that an energy efficiency
policy and/or program delivers and the amount of renewable generation that takes place
may need to be collected and compared to original estimates.
For determining the amount of energy saved for EE policies and programs, although each
energy efficiency policy and/or program will have individual factors to be taken into
account, the general approach is as follows:
• Determine the baseline forecast of energy use for the activity subject to the energy
efficiency policy and/or program.24
• Determine the projected energy use after implementation of the EE policy and/or
program.
• Subtract A) from B). The result yields the projected energy savings due to the
energy efficiency policy and/or program.
When communicating with your state agency counterparts several factors should be
considered when estimating the prospective energy savings of an EE/RE policy and/or
program.25 These include:
• Program period: What year does the policy/program start? End?
24EPA(2010d).Chapter2
25 EPA (20lOd). page 42
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• Anticipated compliance or penetration rate: How many utilities will achieve the
target or standard called for? How many consumers will invest in new equipment
based on the initiative? How will this rate change over the time period?
• Annual degradation factor: How quickly will the performance of the measure
installed degrade or become less efficient?
• Transmission and distribution (T&D) loss: Is there an increase or decrease in
T&D losses that would require adjustment of the energy savings estimate?
Renewable Energy Generated From Renewable Energy Policies
Renewable energy policies and programs are designed to increase the amount of
renewable energy generation over time. For renewable energy and also for less
polluting sources of new energy, such as cogeneration and fuel cells this step is to
determines how much energy would be displaced by the RE policy and/or program.
In general, for renewable sources, the answer would be the total amount of energy
provided to the grid by the renewable energy source.
Performance data for renewable technologies are available from the National Renewable
Energy Laboratory (NREL), as well as universities and other organizations that promote
or conduct research on the applications of renewable energy. In addition, generation-
related data and RE potential information can be obtained from many sources, including:
• State energy offices
• Utility Integrated Resource Planning (IRP) filings,
• Public utility commissions,
• Independent system operators (ISOs),
• North American Electric Reliability Corporation (NERC),
• EPA's Emissions & Generation Resource Integrated Database (eGRID),
• DOE's Energy Information Administration (EIA),
• DOE's National Renewable Energy Laboratory (NREL).
Taking Into Account The Future Attainment Year(S) Baseline Forecast When
Developing EE/RE Policy And/Or Program Energy Impacts For The Control
Measure Pathway
The SIP baseline consists of the current inventory of emissions in the SIP plus any
assumptions regarding growth, or reduction in growth, and its affect on emissions. If a
state, tribal or local agency takes into account certain energy efficiency or renewable
energy policies and programs in developing its projected emissions baseline for the EGU
sector, the resulting projected baseline emissions may be lower than a scenario without
such activities. In this case, such activities are already accounted for in the SIP, as part of
the projected baseline emissions.
Importantly, to avoid double counting, additional emission reductions should not be
granted for those activities already considered in a State's projection of future baseline
emissions for EGUs. If a has jurisdiction applied certain energy efficiency or renewable
energy policies and/or programs in its projected EGU emissions baseline, it cannot
account for additional emission reductions for those same commitments in the SIP, since
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the effect of the EE/RE policy and/or program has already been accounted for in the
baseline. However, a state may seek emission reductions for EE/RE policies and
programs beyond those are already included in the baseline assumptions.
The next section recognizes that some states (or groups of states) have the resources and
capability to perform sophisticated modeling analyses of the energy and air benefits of
EE/RE programs, while others do not. The quantification steps envisioned below present
four tiers of analysis. Tier one is the ideal approach that hopefully many states can
follow. Tiers two and three are credible approaches that would provide less reliable
estimates and, therefore, could be "discounted." This section draws greatly from a
reference document for quantifying EE/RE programs: Assessing the Multiple Benefits of
Clean Energy, USEPA, February 2010.26 Jurisdictions can consult this resources for
more detail as they proceed through these steps,.
SECTION F.3: STEP 2: QUANTIFY OR ESTIMATE DISPLACED ECU
EMISSIONS FROM ENERGY IMPACTS OF AN ENERGY EFFICIENCY
POLICY OR RENEWABLE ENERGY POLICY.
Introduction
This section outlines four different approaches for quantifying displaced emissions. The
approaches outlined in this section are "tiered" by the rigor of each method. Tier One
and Tier Two approaches are the most rigorous. All quantification approaches provide a
methodology for quantifying displaced emissions and important assumptions that must be
documented. Where a tool is not specified, the methodology explains how to account for
the complex interactions applicable to the electrical grid.
Each approach requires different levels of EE savings information and RE generation
information to complete the emissions displacement analysis. Emission displacement
approaches using a dispatch model, capacity expansion model and adjusted historical
hourly generation stacking analysis can use hourly EE/RE saving and generation
information. If a state, tribal or local agency applies energy savings to the third and
fourth tiered approach then annual or seasonal savings information is needed.
Tier One - Dispatch or Capacity Expansion Model Approach This method outlines how
dynamic simulation models predict which EGUs will be displaced as a result of the
EE/RE policy and program. The dispatch and capacity expansion models account for the
complex interactions of the grid such as, transmission constraints, import/export
dynamics, estimate the amount of fossil fuel generation displaced, corresponding
displaced emissions at a scale fine enough to indicate if it is affecting an applicable
nonattainment area. This tier also covers States predicting future emission impacts using
a future capacity model.
Tier Two - Adjusted Historical Hourly Generation Stacking Approach This method
requires technical manipulation of actual historical generation, load and emission rates to
determine EGU dispatch order and marginal emissions rates. By applying this approach
' EPA (2010d) Assessing the Multiple Benefits of Clean Energy.
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State, tribal and local agencies will understand which EGUs are "baseload", load
following or EGUs used for peak demand in every hour of a historical year. Secondly,
jurisdictions would need to account for the complex nature of the electrical grid by
gathering information on electricity imports, exports and transmission constraints.
Tier Three - Capacity Factor Approach This method is based on the assumption that an
EGU's capacity factor is an indicator for the amount of generation subject to
displacement. This method does not approximate hourly EGU dispatch or predict which
EGU is on the margin every hour of the year. Rather, general assumptions are applied
about EGUs historical annual or seasonal generation within the region of interest. (A
discount factor may be applied for this approach)
The Tier Four - eGRID Subregion Emission Rates Approach This method entails a
simple calculation where a jurisdiction would multiply the amount of generation or
electricity sales displaced by the EE/RE policy/program by the "non-base load" emission
rate indicated for a specific pollutant in an eGRID subregion.27 The non-base load
emission rate for an eGRID subregion represents an average emission rate for the EGUs
that are likely to be displaced by an EE/RE policy and program. This method is
recommended to help determine if state, tribal or local agencies feel the magnitude of the
potential emission reductions justifies the additional effort entailed with carrying out a
more sophisticated analysis that could be used for SIP submission under the control
strategy pathway.
Tier One Approach Using Dispatch And Capacity Expansion Models
Dispatch Models - Measuring Hourly Marginal Emission Rates
An electric system dispatch model captures the impact of the portfolio of RE generation
or EE programs during each hour that the new portfolio of EE/RE resource(s) operates.
Dispatch models are designed to simulate energy transfers among different regions,
optimize system dispatch from generating units (multiple generation blocks from a single
unit within one hour), transmission constraints, forced outages and limitations on specific
power plants (e.g., ramp rates, start-up constraints minimum down time).
Dispatch models specifically replicate least-cost system dispatch, with the lowest cost
resources dispatched first and the highest cost last. Dispatch models determine which
generating units are displaced and when they are displaced based on economic and
operating constraints. Dispatch models determine which EGUs operate on the "margin"
in the electrical power system - typically the most expensive unit needed to meet demand
is the "marginal EGU" in a given time period. States can use hourly dispatch or energy
models to determine hourly marginal emission rates (Ibs/kWh), which can then be
aggregated by time period and applied to a portfolio of programs used to achieve the
EE/RE policy requirement. 28
27 Grid loss factors should be included in this calculation. Please refer to the eGRID Technical Support
Document for more information. Found at:
http://www.epa.gov/cleanenergv/documents/egridzips/eGRID2010TechnicalSupportDocument.pdf
28 EPA (2010d), pgs 69-70.
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There are important considerations when using dynamic simulation models such as
dispatch models. Since this method can be less transparent than other methods,
jurisdictions should work closely with the EPA regional office when determining
important input assumptions for any dispatch or energy model used to measure displaced
emissions.
The following information should accompany a state, tribal and local agency's SIP
submittal under this pathway for any quantification of emission reductions using a
dispatch or similar type of model.
Required documentation for dispatch model input assumptions:
• Type and amount of energy savings/generation information used - Specify if peak
(MW), annual (MWh), seasonal, and/or hourly load information was applied for
EE/RE policy
• Fuel prices assumed for all fuels and technologies
• Emission rates for each applicable EGU
Capacity Expansion Models - Measuring Long Term Impacts of New Capacity
Capacity expansion models are typically used for longer-term studies (e.g., five to 20
years), where the impacts are dominated by long-term investment and retirement
decisions. They are also typically used to evaluate large geographic areas.
Capacity expansion models predict how the electric system will evolve over time,
including what capacity will be added through the construction of new generating units
and what units will be retired, in response to changes in new regulations, demand and
prices. This method involves allowing the model to predict what will likely happen to the
resource mix based on costs of new technology, growth, existing fleet of generating
assets, environmental regulations (current and planned), and considering dispatch both
9Q
with and without the new clean energy resource.
The following information should accompany a state, tribal and local agency's SIP
submittal under this pathway for any quantification of emission reductions using a
Capacity Expansion Model or similar type of model.
Required documentation for Capacity Expansion Model input assumptions:
• Fuel price forecasts, EGU retirements, and EE/RE regulatory requirements (e.g.,
renewable portfolio standards).
• Plant type and emission rates of assumed new generation for all applicable future
years
• If model outputs were validated or calibrated against actual data or another
projection model.
EPA (2010d). Pages. 71-72.
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Tier Two Approach For "Stacking" EGUs And Quantifying Displaced ECU
Emissions
Adjusted Historical Hourly Generation Dispatch Order
This approach requires technical manipulation of actual historical generation, load and
emission rates to determine EGU dispatch order and marginal emissions rates. First, a
jurisdiction must obtain historical hourly generation (E.g., data from Continuous
Emission Monitoring (CEM)) from applicable EGUs to analyze the production of each
generating unit and how EGUs change throughout the day as loads changed. Then, states
should compare EGU generation and load information to identify 'base load' units
(EGUs that do not change generation based on changes in load requirements), following
load units (EGUs that increase and decrease production in response to changes in load)
and peaking units - (EGUs only operating at peak load times.)
Since individual units do not necessarily fall into one category all the time, it is important
to structure the analysis to capture these differences. One way to do this is to analyze the
dispatch order of the EGUs within different seasons or time periods (e.g., spring versus
summer and peak versus off-peak periods.) This analysis is the basis for how to calculate
weighted average marginal emission rates (the average of EGUs likely to be displaced by
EE/RE policies/programs) for any group of hours.
The following sections explain the five major steps for developing an hourly dispatch
order using actual historical data.
1) First, determine the relevant set of EGUs for the analysis. This involves
identifying the power control area(s) (PCA(s))30 in which the EE/RE
policies/programs are or will be located, (see Appendix B for more information
on how the electrical grid works)
2) Second, order the relevant set of EGUs to represent typical dispatch.
• Adjust dispatch order based on major energy transfers between the PCA and
other areas.
3) Third, quantify the displaced emissions from the applicable EGUs. (Also known
as, marginal emission rates)
4) Fourth, apply the EE/RE policy/program control measure to determine the
displaced emissions profile from applicable EGUs.
5) Fifth, analyze future emissions inventory to determine future EGU generation and
emission characteristics.
30 A Power Control Area (or balancing authority) is a portion of an integrated power grid for which a single
dispatcher has operational control of all electric generators. PCAs range in size from small municipal
utilities to large power pools such as PJM Interconnection.
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Step 1: Determine relevant set ofEGUsfor analysis
First identify the power control area(s) (PCA(s)) where the EE/RE policy are or will be
located. The PCA is an area where one operator is responsible for balancing generation
and load for the electrical facilities in the area.11 Larger PC As are operated by a single
operator of the transmission grid can be over a multi-state region, such as PJM
Interconnection or ISO New England. These regional operators (known either as
Regional Transmission Operators (RTOs) or Independent System Operators (ISOs)) are
regulated by the Federal Energy Regulatory Commission (FERC) to operate the dispatch
of the power system over the region, based on bids provided by the generators in the
region.
Once a jurisdiction identifies the area of analysis the next step is to understand if there are
any transmission constraints or congestion management zones within the PCA(s).
Transmission constraints can limit the flow of electricity from one area to another
because of physical constraints. These constraints can divide a PCA/RTO/ISO into
several distinct dispatch zones, called "congestion management zones".
Some congestion management zones can become so congested at certain times of the day
they can become "load pockets". In these areas, during constrained hours, higher-cost
generating units within the load pocket must operate rather than lower cost units outside
the pocket.31
Knowing if an EE/RE policy/program is located within the load pocket is important
because it would change the normal dispatch order of the EGUs in the analysis, by
forcing a higher-cost EGU to operate out of normal merit order. Thus, the load pocket
would be the primary area of analysis during the constrained hours, while the entire PCA
might be the primary area during other hours. It is particularly important to check for
transmission constraints in a displaced emissions analysis, because many new resources
are likely to be located in load pockets in response to reliability policies and market
signals.32
Once the area of analysis and related transmission constraints are clear, state, tribal and
local agencies can gather information on where EGUs are located within the defined
area(s) of analysis. The next step outlines how to develop a dispatch order using
historical hourly generation information.
31 Synapse 2005. Methods for Estimating Emissions Avoided by Renewable Energy and Energy Efficiency.
Page 7.
32 The process of checking for important transmission constraints involves reviewing ISO data and
communicating with system operators or other parties familiar with the control area in question. Important
transmission constraints are usually well known, and in many cases ISO rules or policies exist that address
them directly. Examples of such policies are ISO New England's RFP for demand response and generating
capacity in SW CT and the 80% installed capacity requirement in New York City.
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Step 2: Develop a Dispatch Order for Relevant Set ofEGUs using Historical Hourly
Information
First, a jurisdiction must obtain historical hourly generation (E.g., data from Continuous
Emission Monitoring (CEM)) from applicable EGUs to analyze the production of each
generating unit and how EGUs change throughout the day as load changes. EPA collects
data in hourly intervals from Continuous Emission Monitors (CEMS) for all large EGUs
subject to EPA's trading programs.33 Then, states, local and tribal agencies should
compare EGU generation and load information to identify 'base load' units (EGUs that
do not change generation based on changes in load requirements), following load units
(EGUs that increase and decrease production in response to changes in load) and peaking
units - (EGUs only operating at peak load times.)
Once the database is developed, identify load following units in each hour of the year.
Load following units are defined as units that increased output during an hour in which
system load increased or decreased output during an hour in which system load
decreased.
Step 2a: Account for energy imports and exports of the area of analysis.
The EGUs located in the area of analysis may import or export significant amounts of
energy. The first step in address electricity transfers is to determine whether there has
been significant movement in recent years between the area of analysis and other areas.
The following data sources are available for electricity import/export information.
• Data on total generation and export/import percentages will indicate whether it is
a net importer or exporter as well as the magnitude of transfers relative to total
generation.34
• Most system operators (RTO/ISO) release information annually about generation,
loads and interchange on their system.
• Reviewing long-term power purchase agreements that underlie exports and import
transfer information.
If the area of analysis is a net exporter or importer the next step is determine if the
transfer level follows a daily load pattern, a seasonal load pattern or is a consistent source
of energy throughout the year. Once typical energy transfers are characterized, the
dispatch order in the area of analysis should be adjusted to account for these transfers
within the relevant time frames.3
Step 3: Quantify the displaced emissions from the applicable EGUs
The amount of emission reductions that will occur from the EE/RE policy and program is
directly tied to the emission rate of the EGUs at which the energy is displaced.
33 This information can be found at EPA's Clean Air Markets Website:
http://camddataandmaps.epa.gov/gdm/index.cfm?fuseaction=emissions.prepackaged select
34 EPA (2010b) eGPJD 2010V1_0_STIE_USGC.
35 Synapse (2005)
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Use the hourly load-following emission rates to assess displacement from any type of
EE/RE policy and program based on the hours in which the respective EE/RE
policy/program is expected to reduce load requirements. These weighted average
emission rates of load following EGUs should reflect the group of EGUs that system
operators would use to meet marginal demand in that hour. Hourly emission rates can
reveal which hours of the day a set of EGUs in the area of analysis is emitting the most.
This allows for comparing emission rates at the set of baseload, load following and EGUs
that respond to peak demand.
Step 4: Apply energy savings and/or generation impacts of EE/RE policy/program to
displaced EG Us
Determine which EGUs within the dispatch order will be affected by evaluating how the
EE/RE policy reduces load or displaces generation of the area of analysis. Most
importantly identify if the EE/RE policy impacts peak hours and/or base load energy use.
It is possible for multiple EE/RE policies/programs affect both base load and peak hours
of a day. In that case, add the programs bottom up to obtain an aggregate level of energy
savings and generation on an hourly basis and apply their impacts to the predicted
displaced EGUs.36
Step 5: Future Generation and Displaced Emissions
If the projections for EE/RE policies and programs extend out more than 5 years then a
state should develop assumptions for how future generation will change over time. The
jurisdiction must examine each area of analysis and assign emission rates to new units
expected to come online or exclude planned retired plants in the jurisdiction's future
emission rates. There are multiple organizations that project how EGUs will meet future
demand and react to new environmental regulations. EPA recommends obtaining
projections future EGU information from EPA, EIA, or regional transmission
organizations.
It is also important to consider which new resources may be entering an area and whether
there are plans for transmission upgrades. Energy efficiency can avoid the need for new
or upgraded transmission lines. Depending upon the region, upgrades could encourage
further development of renewable energy, or may permit greater access by older, high-
emitting sources that may be more likely to run if the new transmission is built.
Tier Three Approach For Developing An EGU Dispatch Order And Estimating
Displaced EGU Emissions
Capacity Factor Approach
This approach is based on the assumption that an EGU's capacity factor is an indicator
for the amount of generation subj ect to displacement of an EE/RE policy/program. This
method does not approximate hourly EGU dispatch or predict which EGU is on the
margin for any hour of the year. Rather, general assumptions are made about EGUs
historical annual or seasonal generation within the region of interest. The effects of
36
Synapse (2005)
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EE/RE policies and programs are allocated to the EGUs in the region based on each
unit's capacity factor. For example, base load units are rarely subject to displacement
and, as a result, they have very high capacity factors (> 70 percent). Units with low
capacity factors (<20 percent) are load following or peaking units and are subject to
displacement.
The following sections explain the five major steps for a historical capacity factor
displacement analysis. Steps one, three and five require the same procedures as the tier
two approach and will not be repeated in this section.
1) First, determine the relevant set of EGUs for the analysis. This involves
O-y
identifying the power control area(s) (PCA(s)) in which the EE/RE
policies/programs are or will be located, (see Appendix B for more information
on how the electrical grid works)
2) Second, order the relevant set of EGUs to represent typical dispatch.
a. Allocate reduced generation based on historical capacity factors on a
seasonal basis
b. Adjust dispatch order based on major energy transfers between the PCA
and other areas.
3) Third, quantify the displaced emissions from the applicable EGUs. (Also known
as, marginal emission rates)
4) Fourth, apply the EE/RE policy/program control measure to determine the
displaced emissions profile from applicable EGUs.
5) Fifth, analyze future emissions inventory to determine future EGU generation and
emission characteristics.
Step 1: Determine relevant set of EGUs for area of analysis
See step one under the Tier Two Approach for details on the procedures for this step.
Step 2: Place relevant set of generating units in an order representing typical dispatch.
The historical capacity factor approach involves a simple rule that organizes EGUs within
a simplified dispatch order. The rule, summarized in Figure F.2, indicates that EGUs with
lower historical capacity factors will be displaced at a greater rate than units with higher
capacity factors.38
EGUs with the lowest capacity factors would be considered the marginal EGUs within
the dispatch order. For instance, EGUs with capacity factors 20 percent and below would
be completely displaced by EE/RE policies/programs.
37 A Power Control Area (or balancing authority) is a portion of an integrated power grid for which a single
dispatcher has operational control of all electric generators. PCAs range in size from small municipal
utilities to large power pools such as PJM Interconnection.
38 It is important to note that a unit may be "on", i.e. generating electricity for a given hour. But, it may
only be operating at partial load. (Also known as spinning reserve)
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In contrast, EGUs with the highest capacity factors would be considered "baseload"
EGUs. For instance, EGUs with capacity factors 70 percent and above would be
displaced by EE/RE policy/program at a lower rate and some not at all.
EGUs between these extremes would be considered "load following" and the EGUs
would be displaced linearly as capacity factor rises.
When ordering generating units into a d
and large amounts of import or
export of energy in the area of
analysis. EGUs can be taken off
line periodically for planned and
unplanned maintenance work,
and these outages influence
where the EGU is placed within
the dispatch order. However,
EGUs that are typically "base
load" plants should not jump to a
peaking unit because of
historical outages, however
lower prices in other fuels such
as natural gas may also influence
the dispatch order of traditional
base load coal plants.
Step 2a: Allocating reduced
generation based on historical
capacity factors on a seasonal basis
Seasonal capacity factors should be used, rather than annual, in allocating reduced
generation. If annual capacity factors are used, any seasonal patterns in plant utilization
would be lost. For example, many combustion turbines operate only during summer
daytime hours during a typical year. The use of annual capacity factors would allocate
displaced emissions to these units during other seasons of the year.
Step 2.b: Account for Energy imports and exports
See step three under the Tier Two Approach for details on the procedures for this step.
Step 3: Quantify the displaced emissions from the applicable EGUs
Develop an appropriate capacity factor rule to estimate displaced emissions by evaluating
how the EE/RE policy/program will displace the applicable EGUs. Historical seasonal
and annual emission rates are available in EPA's eGRID resource.
oad
\1 Capacity Factor Approach16
1 nri% _
.c
"^ Rfl%
5 -c.
ra cj
S "5.
O -&
£ a> dn% -
'E -=
=) S
»- zs
I
S n%
ff "^
\
\
\
\
\.
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Unit Capacity Factor
s
39
Step 4: Apply EE/RE policy impacts to determine EGU displacement
In some cases it helps to identify if the EE/RE policy/program targets peak hours and/or
base load energy use. For example, introducing more wind generation on the system
39
EPA (2010c) eGRID Version 1.0 Year 2007 Summary Tables
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EXTERNAL REVIEW DRAFT 3/30/11
could displace base load generation, in contrast, demand response programs would target
peak demand.
To apply the general rule outlined in Step 2 and 3, follow the steps below.
• First, calculate the amount of each unit's generation (MWhs) that could be
displaced.
• Second, take the total energy produced or saved and allocate reduced generation
to the applicable EGUs.
• Third, obtain the historical EGU emission rates to determine the amount of
emission reductions from the displaced generation, [multiply emission rate by
column [6] in this example]
Table F.I illustrates this process, evaluating an efficiency program projected to save
1,000 MWhs pear year. There are seven generating units in this hypothetical power
system, labeled A through G.
• Column [2] shows the percentage of each unit's production that could be
displaced by the efficiency program, based on the rule from Figure 7.
• Column [3] shows each unit's actual generation in the historical year being
used.
• Column [4] shows the amount of energy that could be displaced at each unit -
column [2] times column [3].
• Column [5] shows the percentage of the energy saved by the efficiency
program (1,000 MWs) allocated to each unit, and
• Column [6] shows the MWhs displaced at each generating unit.
Table F.I: Allocating Displaced Energy Using the Capacity Factor Approach40
[1]
Unit
A
B
C
D
E
F
G
Totals
[2] %
Displaceable
100%
82%
79%
48%
22%
0%
0%
[3] Historical
Gen. (MWh)
50,000
65,000
120,000
500,000
1.500,000
1.800,000
2.000,000
6.035,000
[4] MWhs
Displaceable
50,000
53.300
94.800
240,000
330,000
0
0
768.100
[5] % of Energy Saved
Allocated to Unit
7%
7%
12%
31%
43%
0%
0%
100%
[6] MWhs
Displaced
65
69
123
312
430
0
0
1,000
Step 5: Future Generation and Displaced Emissions.
See step five under the Tier Two approach for details.
40
Synapse (2005) page 17.
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Tier Four Approach eGRID Subregion Emission Rates
"Non-Base load" eGRID Emission Rates
The eGRID subregion non-baseload output emission rates are recommended to estimate
emission reductions from EE/RE policies and programs that reduce consumption of grid
supplied electricity. Non-baseload output emission rates are associated with the
emissions from plants that combust fuel and have capacity factors less than 80%. These
data are derived from plant level data and aggregated up to the eGRID subregion level.41
States can use this approach to estimate the relative magnitude of emission impacts from
a potential EE/RE policy or program by using the following equation.
Tons of emissions reduced from EE/RE policy and program = non-base load emission
rate (Ib/MWh) x (1/1-grid loss factor) x reduced consumption or supply in energy of EE
policy and program (MWh) x (20001bs/l short ton conversion for criteria pollutants)
Figure F.2: eGRID2010 Subregion Representational Map
Source: EPA(2010a)pageB-l
EPA( 2010a) eGRID Technical Support Document
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Table F.2: eGRID Non-Base load
Emission Rates in 200742
RGRIDsubregion
acronym
AKGD
AKMS
AZNM
CAMX
ERCT
FFtCC
HIMS
HIOA
MROE
URQW
HEWE
NWPP
NVCW
NVLI
NVU°
R=CE
R=CM
R=CW
RMPA
3PNG
SPSO
SRMV
SRMW
SRSO
SRTV
SRVC
U.S.
eGRID subregion name
A3CC Alaska Gnd
ASCC Miscellaneous
WECC Southwest
WECC California
ERCOT All
FRCC All
HICC Miscellaneous
HICC Oahu
MRO =3il
MR 0 West
NPCC Kew England
WECC Northwest
N=CC NYC.'rt'esicheEter
N=CC Long Island
N=CC Upsta:eNY
RFC Eas:
RFC Michigan
R=C Wes-
WECC Rockies
SPP North
SPP Sou-Ji
SERC Mississippi Valley
SERC Midwest
SERC Sou-Ji
SERC Tennessee Valley
SERC V'inginia,'Carolina
Ncm-Daseioaa ouqDiit
emission rates
Ozone
NOK season NO, SO;
;|j MWl-.l ii::. MVVh; . .;• MVVhi
2.7C36 2.7781 1.35S3
2C.5C7Q 20.7284 1 .7355
1.M35 -.3-86 3.4530
C.34S' 0.3213 3.1695
C.5254 0.544C 3.6738
1 .6-335 '.34E2 2.6173
8.4670 S.S413 2. 44 '2
3.4674 3.5661 5. £455
3.3246 3.1-42 3.639'
3.7435 3.83C4 6.2182
D.8070 0.7584 2.4570
1.86B7 '.9248 3.7530
C.9137 O.B93S 3.7154
1.425' -.3364 2.1349
1.42S7 '.2863 5.3505
2.1931 '.7953 9.7750
2.1978 '.7064 3,6509
3.2C24 2.2 -ac 11.6345
1.831' '.S6&2 1.639'
3.2662 2.94-2 5,6117
1.&&43 '.3406 1.5835
1.5C27 -.5747 1.12'6
2.4E32 '.52C7 8.9182
2.182B 1.7771 S.4630
2.9453 18351 7.27B7
2.0702 '.5S&9 7.9666
1.9542 1.6205 5.0676
EPA(2010c)
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Table F.3: Displaced Emissions Methodology Comparisons
TIER DISPLACED EXAMPLES ADVANTAGES DISADVANTAGES
EMISSIONS
METHODOLOGY
One
Two
Three
Four
Dispatch Model and
Energy Models
Hourly Marginal
Emissions Rates
Historical Capacity
Factors
Allocating Reduced
generation to plants
based on capacity
factors
Prosym
Promod
IPM
Ventyx Market
Analytics
OTC workbook
MARKAL
Use CEMS data
from CAMD
database. Create
CEMS-Base Load
Following Method
Use Simplified
capacity factor rule
Egrid non-baseload
emission rates
Green Power
Equivalency
Calculator (for RE
only)
Most credible way
to estimate impacts
of new resource on
power system.
Simulates energy
transfers between
regions,
transmission
constraints and
optimized dispatch
Credible in that it
captures actual
dispatch of fossil
fuel generators
following load.
Rule establishes
dispatch order
Uses capacity
factor as a proxy to
capture marginal
units emissions
Expensive, complex
and some models are
less transparent. All
dispatch models are
proprietary.
Does not account for
impacts on hydro or
energy transfers. Could
be labor intensive.
Oversimplification of
dispatch order, assumes
past historical
generation patterns will
persist in future.
Ignores all non emitting
generation (E.g., hydro)
Assumes one unit is
generating per hour of
day, not representative
system dispatch
SECTION F.4: STEP 3: DETERMINE THE IMPACT FROM THE ESTIMATED
EMISSION REDUCTION ON AIR QUALITY IN THE NONATTAINMENT
AREA
Displaced emissions should be attributed to each applicable EGU in order to determine
how those emissions reductions will improve the air quality in the nonattainment area. 43
Even if the EE/RE policy and program is clearly shown to occur in a nonattainment area,
unless a jurisdiction is able to determine where the displacement of electrical
generation will likely occur, it is problematic to assign the emission reductions to
the nonattainment area. For example, if the nonattainment area imports a
significant amount of electricity from locations outside and downwind of the area,
reduced demand from energy efficiency could result in less electricity being
imported, rather than reduced production (and consequently reduced emissions]
43 The current policy with respect to taking credit for emissions reductions outside nonattainment areas for
purposes of Reasonable Further Progress in ozone SIPs is as follows: RFP credit can be taken for VOC and
NOX emission reductions within 100 kilometers (km) and 200 km, respectively, outside the nonattainment
area under certain circumstances. This policy is currently under reconsideration. See "Reasonable Further
Progress Requirements for the 1997 8-Hour Ozone National Ambient Air Quality," 75 Federal Register
80420-80425, 80421, http://www.gpo.gov/fdsvs/pkg/FR-2010-12-22/pdf/2010-32139.pdf..
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within the nonattainment area, or in areas affecting its air quality. Conversely, if the
energy savings reduce emissions at upwind sources, then the measure may produce
some air quality benefits to the area. (For more details, see the section below on
determining the geographical area where emissions occur]
The state should use the appropriate air quality model to evaluate the extent to which
reductions will improve air quality in the nonattainment area from the selected EE/RE
policy as a control strategy.
Determining The Geographic Area Where Emission Reductions Occur
Determining the location of the emission reduction that occur at fossil fuel fired
generation is challenging because electricity from numerous generators is fed into an
electrical grid from which many different consumers at various locations will draw
power. There typically is no direct connection between a specific facility generating
electricity and the end user of that electricity. Understanding how the electric grid
operates in a jurisdictions area is the first important step in making educated
decisions about which units would be affected by a certain EE/RE policy and
program. The better you can estimate at which power plants a EE/RE policy or
program will likely affect generation and the better you can forecast the emission
rates at those power plants, the better the emission estimate you will have for the
SIP submission.
Energy Efficiency
Out of the many scenarios state, tribal and local may encounter, there are three common
scenarios jurisdictions may need to consider when determining which EGU(s) are
affected by the applicable EE policy and program. Amongst the three scenarios,
jurisdictions may encounter varying degrees of imported or exported electricity between
the area of analysis or Power Control Area (PC A). The first scenario explains where the
emission reductions may occur when very small amounts of electricity is imported or
exported into a PCA and the third scenario explains the circumstances around PC As with
large transfers of electricity imports and/or exports.
First Scenario: The EE policy and/or program directly reduce EGU generation within the
same power control area because both are located within the same power control area
(and nonattainment area) and there is minimal reliance on imported or exported
electricity. The Electric Reliability Council of Texas (ERCOT) is an example of this
scenario, where only 0.07% of energy was exported outside of the PCA and none was
imported.44 In addition, in 2007, HI, AK, MI, IA, and OR imported or exported less than
1% of electricity into or out of their respective states.
Second Scenario: The EE policy and/or program could directly reduce EGU generation
within the same PCA and nonattainment area because the EGUs within the respective
PCA export or import a small amount of electricity (e.g., less than 10%) to or from
another PCA located outside of the nonattainment area. In this case, it is very possible
that the EE/RE policy and/or program implemented in one nonattainment area could
44EPA(2010b)
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influence EGUs to operate less in the same nonattainment area. For example, the
following states exported less than 10% of electricity in 2007; IN, NE, AR, and TX. In
addition, the following states imported less than 10% of electricity in 2007; MI, IA, OR,
MO, KY, CO, GA, MS, VT and NY.11
Third Scenario: The EE policy and/or program may not directly reduce EGU generation
within the same PC A, and nonattainment area, because the EGUs within the respective
area either export or import a significant amount (e.g., over 40%)of electricity to or from
another power control area(s) located outside of the nonattainment area and State. In this
case, the EE/RE policy and/or program within one PCA would influence EGUs to operate
less in PCA(s) outside of where the policy/program is implemented. Determining if the
benefits are upwind from the nonattainment area of interest may be necessary. For
example, the following five states exported at least 40% of the electricity generated
within their state in 2007; WY, WV, ND, NH and MT.45 In addition, the following five
states imported at least 36% of electricity from outside the state in 2007; DC, ID, SD,
DE, andVA.11
EPA suggests that states seeking emission reductions from EE policy and programs
determine with the relevant PCA and congestion management zone (CM) in the
nonattainment area and understand seasonal or hourly differences during the timeframe
of interest. There are many cases in which the PCA will be a larger geographical area
compared to the nonattainment area. In that instance, it is important to investigate the
smaller areas within the electrical grid called, Congestion Management zones (CM) and
determine the amount of electricity imported and exported out of the CM. The state,
tribal or local agency should contact its EPA Regional Office to discuss a method by
which decreased demand can be apportioned among the EGUs in other PCA(s), CMs and
nonattainment areas.
For example, the EGUs located within a PCA containing a nonattainment area may
export a large percentage of their power production to a distant city outside the
nonattainment area. If that distant city adopted aggressive energy conservation measures
which resulted in a significant decrease in demand from the EGUs in the nonattainment
area, emission reductions for the nonattainment area may be appropriate but would
depend on:
• If a state or municipal policy in the distant city requires implementation of the
electricity demand program.
• If the demand reduction for EGUs in the nonattainment is permanent OR
temporary and subject to elimination due to short-term market forces (i.e.,
redirection of the power to another market)?
45EPA(2010b)
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Renewable Energy
Determining the location of the fossil fuel fired units that can operate less as renewable
energy becomes available can be a complex task, particularly when the renewable
resources are located outside the nonattainment area that seeks to use the reduction for
SIP purposes.
Step 1: Determine the location of the fossil fuel fired EGUs that have been able to reduce
their output as renewable energy resources were made available on past days. This
information should already exist at the ISO / RTO that oversees the electrical grid for the
area.
Step 2: Understanding how the grid has responded in the past as renewable resources
have come on-line to develop planning assumptions for how the grid will respond in the
future.
Step 3: Obtain and review the results from existing dispatch modeling conducted by the
grid operator of the PC A, ISO or RTO. The grid operators have the most pressing need
to accurately determine the impact that renewable energy resources will have on the
future operation of the electrical network.
In areas of the country where several states in close proximity to one another implement
RE policies and programs, it may be advantageous for these states to work together in
conjunction with their ISO / RTO and EPA Regional office to identify the overall impact
of the RE policy and programs on the electrical grid in the future. Ideally, such a process
will yield a technically valid solution that attributes the emission reductions from
decreased reliance on fossil fuel fired EGUs in an equitable manner between the states,
and also ensures that double counting of emission reductions does not occur.
EPA understands that conducting this type of analysis may be beyond the means of the
jurisdictions that implement these RE policies and programs. Accordingly, we encourage
any state, tribal and local that needs assistance with this to contact the relevant EPA
regional office for assistance. A list of EPA contacts is provided in section of this
document.
SECTION F.5: STEP 4: PROVIDE A MECHANISM TO VALIDATE OR
EVALUATE THE EFFECTIVENESS OF THE POLICY
The purpose of this step is to determine the type of monitoring, record keeping and
reporting needed to evaluate whether the expected energy impacts, emission reductions
and/or air quality improvements were achieved in practice. For energy efficiency
policies, if the state wants to incorporate energy efficiency policies as a control measure,
there should be an effort to evaluate, measure, and verify the impacts of energy
efficiency. For more information on this topic, see the National Action Plan for Energy
Efficiency Guide on EM&V.46
46
DOE (2006) National Action Plan for Energy Efficiency Report.
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For RE policies and programs, jurisdictions should have in place systems to track
whether energy providers are meeting the percentage targets for renewable energy in the
program. Typically, the state public utility commissions or state energy offices monitor
utility compliance or performance on a year-to-year basis.
SECTION F.6: OTHER CRITERIA FOR CONTROL MEASURE PATHWAY
In addition to the quantification of the emission reduction impact of the EE/RE policy
and program measures, jurisdictions must also determine whether the measure satisfies
the Clean Air Act requirements of permanent, enforceable, and surplus. Each of these
requirements is discussed below.
Permanent Criterion
The EE/RE policy and/or program control strategy should be permanent
throughout the term for which the emission reductions are granted unless it is
replaced by another measure or the State demonstrates in a SIP revision that the
emission reductions from the measure are no longer needed to meet applicable
requirements.
The state or responsible party must demonstrate that adequate personnel and program
resources are committed to implement and enforce the program. To demonstrate that this
requirement has been met, jurisdictions should provide:
• Evidence that funding has been (or will be) obligated to implement the activity;
• Evidence that all necessary approvals have been obtained from all appropriate
government entities; and
• Evidence of inclusion of the EE/RE program in a state regulation or statute.
o For RPS policies, the state needs to adopt regulation or legislation
mandating the program with a state commitment in the SIP to continued
implementation of the program
For energy efficiency policies and programs, the permanence of some programs, such as
purchase programs for energy efficient equipment and products, would need to be
addressed to ensure that:
• The purchased equipment/products would be replaced at the end of their useful
lives with comparably efficient equipment, or,
• That if there isn't a plan to replace the EE equipment/products, the loss of EE
savings is reflected in the SIP. However, a SIP commitment to continue support
and funding for the EE program in the future will provide some assurance that as
old equipment is replaced, it is replaced with comparable or more efficient
equipment.
Enforceable Criterion
Emission reductions used to meet SIP RFP or attainment needs must be enforceable
against a source, and the state and EPA must have the ability to apply penalties if deemed
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appropriate. Additionally, citizens must have access to the emissions related information
obtained from the sources, and must be able to file suits against the source for violations.
The state's renewable portfolio standards (RPS) and EE policies and programs must be
mandatory, created either by specific state legislation commission order or regulation. If
a state submits EE/RE programs for incorporation into its SIP, the programs also become
federally enforceable. Making state adopted EE/RE programs federally enforceable puts
them on par with more traditional air pollution control programs for which states have
sought SIP credit for in the past.
To ensure state overview and enforcement of these programs, EPA envisions the need for
an MOU between the state DEP and the DPUC or other state entity to delegate
enforcement of the program. From EPA's standpoint, it does not matter what part of
State government enforces the program - it could be the DEP or PUC - so long as the
state agency in question has authority from the legislature to administer and enforce the
program. 4? When EPA brings the program into the SIP, EPA has to have the option to
impose CAA-mandated penalties when the agency determines this is an appropriate
course of action. However, if the state "must" initiate enforcement, there is no need for
EPA to take enforcement action. Failure of the state to act would be appropriately
addressed in discussions with or an action against the State, not the entities in non-
compliance. Enforcement of the proposed EE/RE SIP policy and program elements
should be addressed in the State-EPA agreements on enforcement which delineate the
roles of each party and, on an annual basis, the sharing of enforcement responsibilities to
which the state and EPA agree, including who will pursue which cases under this
program.
Surplus Criterion
Jurisdictions cannot "double-count" emissions; Emission reductions associated with the
EE/RE program must not be relied upon in any other air quality program included in
jurisdictions SIP. . To demonstrate that this requirement has been met, jurisdictions
should provide:
• A statement that the appropriate agency has reviewed the control strategy and
confirms that it is not accounted for in other parts of the SIP; and
• A statement describing the potential areas of overlap, if any, and steps to ensure
that emission reductions are surplus and that there is no double-counting
If a cap and trade program is present, one method for demonstrating the surplus criterion
has been met is to retire allowances or otherwise ensure emissions will not increase
somewhere else within the cap.
47 The criteria described here that EPA would use to evaluate the enforceability of a SIP that incorporates
renewable energy incorporate by implication the requirement that the emissions data reflects the full
implications of renewables use on the grid. Recent studies document that at certain levels of wind
production (e.g., 20 percent), emissions factors on natural gas and coal facilities used to balance the grid are
significantly different from emissions factors for those units when used without wind on the grid. The
emissions data or emissions factors used in an enforcement case would have to reflect the actual emission
rates associated with actual wind power usage.
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References
DOE (2006). National Action Plan for Energy Efficiency. Available online at
http://www.epa.gov/cleanenergy/documents/suca/napee report.pdf
EPA (2010a). eGRID Technical Support Document. Available online at
EPA (2010b) eGRID Table in: eGRID2010Vl_0_STIE_USGC Available online at:
EPA (2010c) eGRID Version 1.0 Year 2007 Summary Tables. Available online at
EPA (2010d) Assessing the Multiple Benefits of Clean Energy. Available online at
http://www.epa.gov/statelocalclimate/resources/benefits.html
Synapse Energy Economics, Inc. (2005). Methods for Estimating Emissions Avoided by Renewable Energy
and Energy Efficiency. Available online at http://www.synapse-
energv.com/Downloads/SvnapseReport.2005-07.PQA-EPA.Displaced-Emissions-Renewables-and-
Efficiencv-EPA04-55.pdf
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Appendix G: Emerging/Voluntary
Measures Pathway
SECTION G.I: BASICS OF EMERGING/VOLUNTARY MEASURES
Pathway Description
In 2004 Agency guidance EPA has recognized that many areas of the country have
implemented most available traditional emission control strategies and are interested in
new types of pollutant reduction
strategies to attain and maintain
applicable NAAQS, including voluntary
EE/RE programs. The EPA supports
and encourages the testing of voluntary
and emerging pollutant reduction
strategies. A voluntary measure is a
measure or strategy that is not
enforceable against an individual
source. An emerging measure is a
measure or strategy that does not have
the same high level of certainty as
traditional measures for quantification
purposes. A measure can be both
voluntary and emerging.
Completed Action
•/
S
•/
S
•/
•/
Identify and describe the
emerging/voluntary EE/RE programs
to include
Calculate emissions reductions,
including description of quantification
technique
The State has to make an enforceable
commitment to implement those parts
of the measure for which the State or
local government is responsible
The State has to make an enforceable
commitment to monitor, evaluate, and
report at least every three years on
progress toward emission reductions
The State has to make an enforceable
commitment to remedy any SIP/TIP
credit shortfall if the program does not
achieve projected emission reductions
Certify EE/RE programs are
permanent and surplus
This pathway is similar to the control
strategy pathway in that an EE/RE
program can receive emission reduction
SIP/TIP credit under this option and
must satisfy the four criteria for SIP/TIP
measures:
• Permanent
• Quantifiable
• Surplus
• Enforceable
But the policy provides flexibility for emerging measures on the quantifiable criterion
and for voluntary measures it provides flexibility on the enforceable criterion.
Tradeoffs Of Pathway
The quantity of potential SIP/TIP credit for the emerging/voluntary measures pathway is
generally limited as compared to the control strategy pathway. The limitations and
conditions under which emerging/voluntary measures can receive credit are determined at
the beginning of the SIP/TIP process, and provisional pollutant reduction credit is
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provided under the assumption that the EE/RE measures will achieve the quantity of the
initially estimated emission reductions.
What Circumstances And Type Of State, Tribal And Local Agencies Is The
Pathway Best Suited For
The pathway is well suited for areas that have voluntary and/or emerging EE/RE
policies/programs that are not easy to enforce and/or quantify but for which the area
would like SIP/TIP credit.
Four Steps State, Tribal And Local Agencies Needs To Take To Implement The
Pathway
To implement this pathway, state, tribal and local agencies need to pursue four steps:
1) Identify and describe the voluntary EE/RE programs that it wishes to include as
emerging/voluntary measures.
2) Calculate expected emission reductions from the voluntary EE/RE programs and
document the technique.
3) Commit to implement the programs and to monitor, evaluate, and report at least
every three years on progress toward emission reductions.
4) Ensure that the EE/RE emission reductions included in the WOE demonstration
are not accounted for as part of the other two pathways to avoid double counting
and that they are permanent.
Process Issues Including Expected Level Of Effort, Other Resources Needed, And
Stakeholders Involved
The process issues and workload are greater than the WOE pathway and less than the
control strategy pathway. Quantification of emissions reductions associated with a state's
EE/RE programs and policies and their enforceability will require discussion and
verification on the emissions and energy savings data with staff in the state public utilities
commission, the regional transmission organization, or both.
SECTION G.2: VOLUNTARY/EMERGING MEASURES PATHWAY
ANALYSIS AND DOCUMENTATION
In order to adopt and implement emission reduction strategies to meet SIP/TIP CAA
requirements, such as RFP, ROP, attainment demonstrations, general conformity, and
maintenance, the reductions from control measures must be:
Permanent
The state or responsible party must demonstrate that adequate personnel and program
resources are committed to implement and enforce the program. The emission reductions
expected from the state's EE/RE programs should continue through the term for which
the credit is granted unless replaced by another measure, or the state demonstrates
through a SIP/TIP revision that the measure is no longer necessary.
Quantifiable
As noted in Appendix C, for emerging/voluntary stationary measures the presumptive
limit is 6 percent of the total amount of emission reductions required for the ROP, RFP,
attainment, or maintenance demonstration purposes. The limit applies to the total number
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of emission reductions that can be claimed from any combination of voluntary and/or
emerging measures, including those measures that are both voluntary and emerging. The
limit is presumptive in that EPA believes it may approve measures into a SIP/TIP in
excess of the presumptive six percent where a clear and convincing justification is made
by the state, tribal or local agency as to why a higher limit should apply in their case. Any
request for a higher limit will be reviewed by EPA on a case-by-case basis.
For emerging measures, EPA allows flexibility for the quantification requirement. Some
areas want to try new types of emission control or pollution reduction strategies. EPA's
policy provides a mechanism that allows the state, tribal or local agency to receive
provisional emission reduction credit in their SIP/TIP for new emission control and
pollutant reduction strategies that have the potential to generate additional emission
reductions or air quality benefits. In these circumstances, the state, tribal or local agency
should quantify the pollution reduction based on the best knowledge currently available
for the measure being considered. The state, tribal or local agency should develop a
protocol based on a carefully considered determination of the activities that it is
committing to undertake and the activities' projected impact on pollution. The estimates
may be based on modeling, on extrapolated experience for similar types of projects or on
another approach that is likely to yield a reasonable estimate of pollution reduction. EPA
recommends that state, tribal and local agencies consider the Tier Three or Four
techniques presented in Appendix F as a way to approach quantification, recognizing that
for emerging/voluntary programs is probably not warranted.
Surplus
The state, tribal or local agency needs to certify that the emission reductions being
claimed for credit under the emerging/voluntary measures policy are not also reflected in
the emissions baseline or included as part of a WOE demonstration.
Enforceable
As described in Appendix F, the emerging/voluntary measures policy provides some
flexibility on enforceability for voluntary by requiring the state, tribal or local agency to
assure that the emission reductions credited in the SIP/TIP occur. The state, tribal or
local agency would make an enforceable commitment to monitor, assess and report on
the emission reductions resulting from the voluntary measures and to remedy any
shortfalls from forecasted emission reductions in a timely manner. These commitments
would be needed from the state, tribal or local agency.
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Appendix H: Weight of Evidence
Pathway
SECTION H.1: BASICS OF WOE
Pathway Description
When state, tribal or local agencies conduct air quality modeling to assess the attainment
of a NAAQS, considering the efficacy of existing and future control measures, EPA
guidance encourages them to
perform complementary analyses of
air quality, emissions,
meteorological data, and other
modeling information to help
corroborate the conclusions of the
attainment demonstration.
Sometimes, the results of
corroboratory analyses may be used
in a weight of evidence
determination to show that
attainment is likely despite modeled
results which may not show attainment or may be close to the level of the NAAQS. The
further the predicted, modeled design value is from the standard, the more compelling the
contrary evidence produced by corroboratory analyses must be to draw a conclusion that
differs from that implied by the modeled attainment test results. If a conclusion differs
from the outcome of the modeling, then the need for subsequent review (several years
hence) with more complete data is increased. If the attainment test is failed by a wide
margin, it is far less likely that the more qualitative arguments made in a weight of
evidence determination can be sufficiently convincing to conclude that the NAAQS will
be attained.
In a WOE determination, states should review results from several diverse types of air
quality analyses, including results from the modeled attainment test. The diverse types of
analyses could include consideration of the impact of EE/RE programs, among other
factors. Weight of evidence demonstrations are generally described in guidance EPA has
issued on their use in SIP attainment demonstrations.
Completed Action
•/
•/
•/
•/
Identify the EE/RE programs and
policies to include
Ensure EE/RE programs and policies
will be in place for planning period
Calculate emissions reductions,
including description of quantification
technique
Ensure emissions reductions are not
double counted
48
Tradeoffs Of Pathway
Of the three options, this pathway involves the least documentation and analysis but it
does not provide a direct quantification of the potential air quality benefit for the SIP/TIP.
48
http://www.epa.gov/scramOOI/guidance sip.htm
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What Circumstances And Type Of States The Pathway Is Best Suited For
This option is best suited for a state that has mandatory policies and programs that are
difficult to quantify and/or model49 or voluntary EE/RE programs that it can demonstrate,
through basic quantification, will produce emissions reductions in the planning timeframe
for attainment.
Four Steps State, Tribal And Local Agencies Needs To Take To Implement The
Pathway
To implement this pathway, State, tribal and local agencies need to pursue four steps:
1) Identify the EE/RE programs and policies that it wishes to include in the WOE
demonstration.
2) Ensure that the EE/RE programs and policies will be in place for the duration of
the planning period in question, benefitting that area's ability to attain.
3) Perform a calculation of emission reductions expected from the policies and
programs and.
4) Ensure that the EE/RE emission reductions included in the WOE demonstration
are not accounted for as part of the other two pathways to avoid double counting.
Process Issues Including Expected Level Of Effort, Other Resources Needed, And
Stakeholders Involved
Process issues associated with this option are not significant. Quantification of emissions
reductions associated with a state's EE/RE programs and policies may require some
interaction with energy experts at the state level. But inclusion of EE/RE programs and
policies does not make them federally enforceable so coordination with the state energy
officials will not be necessary on that issue.
SECTION H.2: WOE EE/RE ANALYSIS AND DOCUMENTATION
States need to quantify the expected emissions reductions from the EE/RE programs and
policies included in the WOE demonstration that are expected to benefit air quality in the
nonattainment area in question. EPA has several tools available that can help states to
quantify the benefits of EE/RE policies that are described in Appendix E. In addition,
EPA is providing energy savings estimates for state-mandated EE policies that could be
used is a WOE demonstration (see Appendix G).
Documentation for this pathway is minimal in comparison to the other two pathways and
should include the following:
• Statement that program will be in effect for duration of planning period and that
its emissions reductions are not double counted.
• Brief description of a simplified technique (such as the Tier Four approach
described in Appendix F) for quantifying emissions reductions showing that the
49 There are many reasons why a state, tribal or local agency may not be able to quantify emissions
reductions or model a specific EE/RE policy. The state, tribal or local agency may lack sufficient resources
or the benefits may be too small to justify the effort.
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policies are likely to produce emission reductions in the attainment planning
timeframe for the nonattainment area in question.
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Appendix I: EPA's Draft Methodology for
Estimating Energy Impacts of EE/RE
Policies
SECTION 1.1: INTRODUCTION
To help state, tribal or local agencies examine the role for EE/RE policies and programs
in their SIPs/TIPs, EPA developed a draft methodology and estimated the electric-sector
impacts of existing energy efficiency and renewable energy (EE/RE) policies. EPA's
draft methods and analysis covers "on the books" EE/RE policies that are adopted in law
and codified in rule or order, but that are not reflected in the Energy Information
Administration's Annual Energy Outlook (AEO) 2010 electricity demand projections.
Electric sector impacts are provided for the following policies:
• Energy efficiency policies that require reductions in electricity consumption in
key end-use sectors (residential, commercial and industrial)
• Renewable Portfolio Standard (RPS) policies that increase renewable energy
generation or sales beyond what is already captured in AEO 2010
EPA anticipates that its methods and impact estimates may be useful to state, tribal or
local agencies preparing SIP/TIP submittals to meet the National Ambient Air Quality
Standards (NAAQS) for ozone and other pollutants.
This appendix describes the methodology EPA used to develop those energy savings
estimates, provides an overview of the information EPA is making available, and outlines
potential uses for the information. For more details on the projected impacts of state
EE/RE policies refer to: http://www.epa.gov/statelocalclimate/state/statepolicies.html.
SECTION 1.2: OVERVIEW OF PROCESS
EPA undertook the following process steps to determine which "on the books" EE/RE
policies are not explicitly accounted for in AEO 2010 reference case forecast.
• Step One: Understand Annual Energy Outlook 2010 Reference Case Forecast
(AEO 2010).
• Step Two: Identify key state EE/RE policies not explicitly included in AEO 2010
and collect relevant design details.
• Step Three: Develop analytical methods to estimate incremental50 impacts of
EE/RE policies relative to AEO 2010 reference case forecast.
50 Incremental impacts of EE/RE policies relative to AEO 2010 refers to the impacts not captured within
AEO 2010, taking into account any embedded impacts reflected in the forecast
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Step One: Understand EE/RE Policy Assumptions In Annual Energy Outlook 2010
Reference Case Forecast (AEO 2010)
To understand the EE/RE policy assumptions included in the AEO 2010 forecast, EPA
reviewed the Energy Information Administration's (EIA) documentation for the AEO
2010 reference case forecast and talked with EIA staff. EPA found that AEO 2010
explicitly includes the impacts of a number of existing EE/RE policies, including:
• Federal Appliance Standards51
10 Residential & 10 Commercial Appliance Categories
• Federal Funding
State Energy Program (SEP) and Energy Efficiency Community Block Grant
(EECBG), Weatherization Program, Green Schools and Smart Grid Expenditures.
(E.g., through the American Recovery and Reinvestment Act (ARRA))52
• Building Codes53
All States adopt and enforce:
IECC 2006 Code by 2011 and IECC 2009 Code by 2018 ASHRAE 90.1 -2007 by
2018
• Renewable Energy Portfolio Standards (RPS)54
30 States and D.C. Effective as of Sept. 2009
Step Two: Identify Key "On The Books" State EE/RE Policies Not Explicitly
Included In AEO 2010 And Review Relevant Design Details
Based on EPA's review described in Section 1.2.a, EPA identified four key "on the
books" state EE/RE polices not explicitly included in AEO 2010 reference case forecast.
EPA focused its analysis on EE/RE policies that are currently in regulation, statute or
state public utility commission order that require parties to acquire energy efficiency
and/or renewable energy or commit to funding levels for programs aimed at acquiring
EE. The EE/RE policies listed below are the set of "on the books" state EE/RE policies
EPA identified for this analysis.
State Energy Efficiency Policies:
• Energy Efficiency Resource Standards (EERS)
• Rate Payer-funded EE programs
• Regional Greenhouse Gas Initiative Funded EE programs
State Renewable Energy Policies:
51U.S. Energy Information Administration (2010). Assumptions to the Annual Energy Outlook 2010: With
Projections to 2035, Appendix A. p. 170-185
52 U.S. Energy Information Administration (2010). Annual Energy Outlook 2010: With Projections to
2035. p. 8-10.
53 Ibid pg. 8
54 See full list at: U.S. Energy Information Administration (2010). Annual Energy Outlook 2010: With
Projections to 2035. p. 14-17
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• Renewable Energy Portfolio Standards (RPS) Policies that were adopted or
updated between September 2009 and December 2010.
After identifying the applicable EE/RE policies, EPA scanned the 50 states to determine
which states have adopted the aforementioned state EE/RE policies as of December 31,
2010. Once EPA identified the applicable states, EPA reviewed the relevant design
details for each state EE/RE policy using publically available information, such as, state
legislation, state rules and regulations, commission orders and summary results from
ACEEE55, Lawrence Berkeley National Laboratory56 and Consortium for Energy
Efficiency57.
co
Step Three: Develop Analytical Methods To Estimate Incremental Impacts Of
EE/RE Policies Relative To AEO 2010 Reference Case Forecast
Once EPA understood the state-level policy characteristics, EPA developed analytical
methods to estimate the impacts of the "on the books" EE/RE policies. The analytical
methods EPA developed generated projected impacts of estimated annual energy savings
and generation for 2010-2020, peak impacts and hourly load impact curves for 2010,
2012, 2015 and 2020 for the four identified state EE/RE policies.
SECTION 1.3: OVERVIEW OF EPA'S DRAFT METHODOLOGY AND
ANALYTICAL STEPS
EPA applied the following key analytical steps to estimate the projected impacts of state
"on the books" EE/RE Policies.
Analytical Steps for annual energy savings of EE Policies:
• Step One: Generate a baseline (i.e., business as usual or (BAU)) forecast of state
electricity sales consistent with AEO 2010 regional forecasts, (see Section 1.3.a)
• Step Two: Estimate projected impacts of key state EE policies already embedded
in AEO 2010 forecast of electricity sales, (see Section I.3.b)
• Step Three: Estimate projected energy efficiency savings from key "on the
books" EE policies (see Section I.3.c)
o Energy Efficiency Resources Standards (EERS) (25 states)
o Rate-payer funding commitments to EE Programs
• Public Benefits Funds (3 states)
o Regional Greenhouse Gas Initiative (RGGI) allowance auction revenue for
EE Programs (3 states)
• Step Four: Generate state-adjusted energy forecast that reflects the energy
savings not captured in (i.e., incremental to) AEO 2010. (see Section 1.3.d)
Analytical Steps for peak demand savings of EE Policies
55 ACEEE (2010)
56 Ernest Orlando Lawrence Berkeley National Laboratory (LBNL) (2009)
57 Consortium for Energy Efficiency (CEE) (2010)
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• Step One: Estimate projected peak demand savings for the years 2010, 2012,
2015 and 2020. (see Section 1.4)
• Step Two: Generate load impact curves that represent typical hourly changes in
load from energy efficiency programs under consideration, (see Section 1.4.a)
Analytical Steps for RE Policies:
• Step One: Estimate renewable energy generation from RPS policies adopted or
revised between September 2009 and December 2010. (see Section 1.5)
• Step Two: Generate state-adjusted forecast and aggregate state-adjusted forecast
to facilitate modeling regional RPS impacts, (see Section 1.5.a)
EPA's Draft Methodology For Generating A Baseline (I.E., Business As Usual Or
(BAU)) Forecast Of State Electricity Sales To Represent AEO 2010 Regional
Forecasts
State-level baseline sales intended to represent the AEO2010 regional forecast59 were
developed using 2009 historical state sales data from the Energy Information
Administration (EIA)60 as the starting point, and then applying the electricity sales
growth rates from AEO2010. AEO2010-based 'annual average growth rates' (AAGR)
were calculated for each Electricity Market Module (EMM) region across the 2009-2035
forecast period. These regional growth rates were then applied to the 2009 historical
sales for each state lying predominantly within the EMM region61. The 2009-2035
AAGR was used to forecast sales for 2010-2035. shows the EMM region to which each
state was mapped and the AAGRs that were used to forecast its sales.
Table 1.1: EMM Region Mapping and AEO2010-Based
Sales Growth Rates by State
State
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Hawaii
Illinois
Indiana
Iowa
Maine
EMM Region
RA
SERC
CA
RA
NE
MAAC
FL
HI2
MAIN
ECAR
MAPP
NE
AAGR1
(2009-2035)
.4%
.0%
.0%
.4%
.3%
0.9%
.2%
.0%
.0%
.0%
.1%
.3%
59 Note ihatAEO2010 does not include state-level forecasts, so incremental impacts are calculated against
the Business-As-Usual Electricity Sales Forecast developed as described in Section 0.3.b.
60 EIA (20lOe), Table 2
61 EIA maps states to EMM regions for regional modeling of RPSs. This mapping was followed where
possible; states without precedent were assigned to EMM regions based on population distributions.
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State EMM Region AAGR1
(2009-2035)
Maryland
Massachusetts
Michigan
Minnesota
Montana
Nebraska
New Hampshire
New Jersey
New Mexico
New York
Ohio
Oregon
Pennsylvania
Rhode Island
Texas
Vermont
Washington
Wisconsin
MAAC
NE
ECAR
MAPP
NWP
MAPP
NE
MAAC
RA
NY
ECAR
NWP
MAAC
NE
ERCOT
NE
NWP
MAPP
0.9%
1.3%
1.0%
1.1%
1.1%
1.1%
1.3%
0.9%
1.4%
0.7%
1.0%
1.1%
0.9%
1.3%
0.9%
1.3%
1.1%
1.1%
EPA's Draft Methodology For Estimating Energy Savings Of EE State Policies
Embedded In AEO 2010.
AEO2010 does not explicitly include the impacts of state energy efficiency policies such
as EERSs, ratepayer-funded EE programs and RGGI-funded EE programs. However,
AEO2010 results could implicitly reflect these programs to the extent that forecast
parameters are calibrated to historical data and individual programs could have already
been in place for several past years. AEO2010 also accounts for future energy efficiency
improvements, which could be partly attributed to these key state EE policies. Some
portion of the savings from EE policies may therefore be embedded in the AEO2010
forecast and the AEO2010-based state-level BAU forecast. These embedded savings
were estimated for each state and subtracted from its total EE policy savings to estimate
the impacts that are incremental to AEO2010. Embedded savings were only applied for
years in which states see savings from EE policies and, to the extent possible, were only
calculated for entities that are required to implement the EE policies under consideration.
The methodology used to develop estimates of embedded savings for this analysis is a
variation of the method used in LBNL (2009), which, lacking better information, assumes
that the growth rates derived from the AEO forecast implicitly account for a continuation
of 50 percent of historical levels of savings. Embedded savings for each state were
quantified using the following three steps:
1) Step One: Estimating Historical Savings for Entities that Implement key state EE
policies
62
: EERS, Rate-payer funded EE programs and RGGI funded EE programs
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• Total first-year electricity savings from existing and new programs in 2006,
2007 and 2008 were obtained from ACEEE (2008, 2009b, 2010).63
• For states that have EERSs with a total sales basis, or have no EERSs but have
ratepayer- or RGGI-funded programs, savings for entities that implement the
EE policies were taken to be equal to the total incremental savings for each
historical year.
• For states that have EERSs with a basis other than total electricity sales,
savings for entities that implement the EE policies were estimated as follows:
• Utilities not affected by an EE policy in each state and their savings
for 2006, 2007 and 2008 were identified from EIA-861 utility-level
data (EIA 2007a, EIA 2008a, EIA 2009a).
• If the identified utilities had service areas in only one state, all their
savings were assumed to take place in that state
• If the identified utilities had service areas in multiple states and they
were either (a) affected by EE policies in all states, or (b) not affected
by EE policies in any state in which they had a service area, their
savings were apportioned to states in proportion to 2009 utility sales in
each state.
• If the identified utilities had service areas in multiple states and they
were affected by these policies in some but not all states in which they
had a service area, then all savings were assumed to take place in the
states in which they were affected by EE policies. Savings were
apportioned to these states in proportion to 2009 utility sales (EIA
2010e) in each state.
• Savings for entities that implement EE policies were estimated as the
total first-year electricity savings for the state minus any savings from
unaffected utilities that were apportioned to the state.
2) Step Two: Estimating the Weighted Average of Historical Savings as a Share of
Sales for 2006-2008
Historical savings from the previous step were divided by historical sales to
estimate a weighted average savings rate. Annual electricity sales data for 2006-
2008 for each state were obtained from EIA-861 state-level datasets (EIA 2007b,
EIA 2008b, EIA 2009b). The weighted average (m) of historical savings for
entities that implement EE policies as a share of state sales was calculated as:
m =
Where:
t goes from 2006 to 2008,
Xis the savings for entities that implement EE policies, and
7 is the annual electricity sales.
63 ACEEE estimates state-level EE savings using utility-level data from EIA-861 and information from a
state-by-state survey conducted by ACEEE.
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3)
Step Three: Estimating Embedded Savings for Each Future Year
The weighted average of historical savings as a share of sales for 2006-2008 (rri)
is multiplied by 50 percent to yield embedded savings as a share (n) of baseline
sales for each future year:
n = m * 50%
Table 1.2 presents the estimated embedded savings as shares of baseline sales.
Embedded savings were calculated as:
F(i) = n * B(i)
F(t-L+l)
Where:
F is the annual first-year embedded energy savings,
B is the baseline total sales, L is the measure lifetime, and
E is the cumulative embedded energy savings.
Table 1.2: Energy Efficiency Savings Estimated to be Embedded in AEO2010
State Savings Estimated to be Embedded
in AEO2010
(% of BAU Sales in Each Year)
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Hawaii
Illinois
Indiana
Iowa
Maine
Maryland
Massachusetts
Michigan
Minnesota
Montana
Nebraska
New Hampshire
New Jersey
New Mexico
New York
Ohio
0.14%
0.02%
0.48%
0.12%
0.54%
0.00%
0.06%
0.63%
0.00%
0.01%
0.34%
0.36%
0.02%
0.39%
0.00%
0.34%
0.18%
0.01%
0.33%
0.18%
0.05%
0.21%
0.01%
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State Savings Estimated to be Embedded
;„ Avmnin
Oregon
Pennsylvania
Rhode Island
Texas
Vermont
Washington
Wisconsin
0.34%
0.00%
0.47%
0.06%
0.91%
0.35%
0.31%
Developed by ICF International based on data from:
ACEEE (2008), Table 6; ACEEE (2009b), Table 6; ACEEE (2010),
Table 8
EIA (2007a), FileS; EIA (2008a), FileS; EIA (2009a), FileS; EIA
(2007b), Table 2; EIA (2008b), Table 2; EIA (2009b), Table 2; EIA
(2010e),Table2
EPA's Draft Methodology For Estimating Projected Energy Efficiency Savings
From Energy Efficiency Policies
State-level energy efficiency savings were estimated from EERSs, ratepayer-funded
programs, and RGGI-funded programs. Because these categories were not mutually
exclusive, double-counting of energy savings for states with EERSs was avoided by
treating EERS targets as overall goals that include savings from individual ratepayer-
funded and RGGI-funded programs. Qualifying individual programs were not identified
as being incremental to the EERS target, so each state for which savings are reported has
either EERS savings, or ratepayer- and/or RGGI-funded savings. To review EPA's
estimates of EE policies refer to:
http://www.epa.gov/statelocalclimate/state/statepolicies.html
First-year electricity savings expected to occur in each year, and cumulative savings from
EE measures implemented in the current year and past years, were estimated for each
energy efficiency policy category. Cumulative savings were calculated using state-
specific measure lifetimes (as available from ACEEE (2009a), see Table 1.3 below)
assuming no decay of savings during measure life. A default lifetime of 13 years was
used where state-specific assumptions were not available. No further first-year savings
were estimated beyond the requirements found in each state's policy period, and the
forecast reverts to the AEO2010, which includes improved technology and efficiency in
the long term.
Table 1.3: Measure Lifetime by State
State Measure Lifetime (Yrs)
Connecticut
Iowa
Massachusetts
Minnesota
Nevada
13
15
13
13
13
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State Measure Lifetime (Yrs)
New Jersey
New Mexico
New York
Oregon
Rhode Island
Texas
Vermont
Wisconsin
Default
14
9
15
12
11
13
13
12
13
Source:
ACEEE (2009a), Table 1
Energy Efficiency Resource Standards
An Energy Efficiency Resource Standard (EERS) is a policy mechanism that sets targets
for energy savings over a specified time frame from end-use energy efficiency programs
operated by utilities or other program administrators. State-level screening revealed that
states typically specify annual first-year or cumulative targets as percentages of
electricity sales or as absolute energy savings. They use different bases for specifying
EERS goals: some states specify goals based on sales from investor-owned utilities
(lOUs), while others have mandated targets based on total sales or some other subset of
total sales.
Energy savings for each state were estimated using formulas specific to the state's EERS,
as shown below. The appropriate sales basis for each state was identified and, if the basis
was not total sales, baseline forecasts of sales of affected utilities only were developed
using 2009 utility-level sales data from EIA64 and AEO20JO-based growth rates65. Full
achievement of EERS targets was assumed for all years in the compliance period for all
states, except for those with EERSs that have cost/rate caps. Savings were not estimated
for purely voluntary EERSs such as Virginia's EERS.
The general formulas used to estimate annual first-year and cumulative energy savings
for each year (t) were:
1) EERS with Annual First-Year Energy Efficiency Savings Targets Specified in
Percent Terms
= r(t)*Z(t-l)
A(t-L+l)
= C(t)-£(t)
Z(t)=5(t)-/(t)
Where:
r is the annual first-year percent savings target,
64EIA(2010c)
65 See
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A is the annual first-year energy savings,
L is the measure lifetime,
B is the baseline sales of utilities affected by these specific policies,
C is the cumulative energy savings,
E is the cumulative savings embedded in the AEO2010 forecast,
/is the cumulative savings incremental toAEO2010 forecast, and
Z is the adjusted sales after application of cumulative incremental savings.
2) EERS with Annual First- Year Energy Efficiency Savings Targets Specified in
Absolute Terms
C(t) = A(i) + A(i-\) + . . . + A(t-L+l)
= C(t)-£(t)
Where:
A is the annual first-year energy savings target,
L is the measure lifetime,
B is the baseline sales of utilities affected by these specific policies,
C is the cumulative energy savings,
E is the cumulative savings embedded in the AEO2010 forecast,
/is the cumulative savings incremental toAEO2010 forecast, and
Z is the adjusted sales after application of cumulative incremental savings
3) EERS with Cumulative Energy Efficiency Savings Targets Specified in Percent
Terms
If r(t) available,
= r(t)*5(t
= C(t)-E(t)
If r(t) not available,
Z(t) calculated by interpolation
C(t) = /(t) + £(t)
Where:
r is the cumulative percent savings target,
A is the annual first-year energy savings,
L is the measure lifetime,
B is the baseline sales of utilities affected by these specific policies,
C is the cumulative energy savings,
E is the cumulative savings embedded in the AEO2010 forecast,
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/is the cumulative savings incremental toAEO2010 forecast, and
Z is the adjusted sales after application of cumulative incremental savings
4) EERS with Cumulative Energy Efficiency Savings Targets Specified in Absolute
Terms
If C(t) available,
= C(t)-E(t)
If C(t) not available,
Z(t) calculated by interpolation
Where:
C is the cumulative energy savings target,
A is the annual first-year energy savings,
L is the measure lifetime,
B is the baseline sales of utilities affected by these specific policies,
E is the cumulative savings embedded in theAEO2010 forecast,
/is the cumulative savings incremental ioAEO2010 forecast, and
Z is the adjusted sales after application of cumulative incremental savings
Some special considerations that warranted adjustments to the general formulas were:
1) Combined EERS and RPS: Nevada and North Carolina have EERSs that are
combined with their RPSs. Savings from these combined policies were assumed
to be included mAEO2010.
2) Compliance Type and Cost/Rate Caps: Two states - Illinois and Texas - include
cost/rate caps in their EERS rules. Without a bottom-up economic analysis for all
possible programs and supply-side resources, it was not possible to evaluate the
impacts of these caps on the achievement of EERS targets. As an alternative,
savings for these states were estimated based on savings reported for previous
years and estimated for future years in utility filings66 and energy efficiency
studies67.
66 AEP TCC (2010), AEP TNC (2010), Ameren Illinois (2010), CenterPoint (2010), ComEd (2010), EPE
(2010), Entergy (2010), Oncor (2010), SWEPCO (2010), TNMP (2010), Xcel (2010)
67
Good Company Associates (2010)
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3) "All Cost-effective Energy Efficiency" Targets: Six states - Connecticut,
Massachusetts, New Mexico, Rhode Island, Vermont and Washington - require
utilities (or other EE program administrators) to implement all cost-effective
energy efficiency. In states with an "all cost-effective EE" target and available
numerical goals, the numerical goals were used (i.e., New Mexico). In states with
an "all cost effective EE" target without numerical goals through 2020, tailored
approaches based on utility plans68 and resource potential studies69 were applied
to estimate savings.
Rate-Payer Funded Commitments To EE Programs With An Established Public
Benefits Fund Policy
Energy efficiency savings were estimated for ratepayer-funded programs in states that
have established dedicated public benefits funds for such programs. Data for ratepayer-
funded programs are mainly available in terms of program expenditures, so savings were
calculated using estimates of energy savings per program dollar spent. For each state
with qualifying programs, information on annual program funding for 2010 was obtained
from state publications70 or utility surveys71, and funding for each future year in the time
period was projected as equal to the funding for 201072. Estimates of levelized costs of
saved energy (LCSE) were available for some states from ACEEE (2009a). The ACEEE
report presents costs of saved energy as reported by programs, except in cases where the
methods used by program administrators to estimate the LCSE were different from
ACEEE's standard approach. In such cases, ACEEE calculates LCSE as:
LCSE = (F* CRF)/A
CRF = (d *(l+d)L}l((l+d)L -1)
Where:
A is the annual first-year energy savings,
F is the annual program funding,
CRF is the Capital Recovery Factor,
L is the measure lifetime, and
d is the discount rate.
ACEEE uses a real discount rate of 5 percent to calculate the Capitol Recovery Factor
(CRF), and estimates that the average LCSE across the states included in the report is
$0.025/kWh. To apply ACEEE's LCSE estimates in a manner that is consistent with the
methodology by which they were calculated, this analysis also used a discount rate of 5
percent. The average LCSE of $0.025/kWh was used as the default LCSE where state-
68 CT Utilities (2010), MDPU (2010), National Grid (2008), EERMC (2010), VEIC (2009)
69 KEMA (2010), NWPCC(2010)
70 NHEU (2009), NJ BPU (2009)
71 CEE (2010)
72 In the case of New Jersey, total funding data for the NJ Clean Energy Program™ were available for
2010, 2011 and 2012. Though the share of total funding that is projected to be spent on energy efficiency
ranges from about 77 percent to 85 percent in these three years (NJ BPU 2008), a conservative assumption
was made that only 50 percent of total funding will be allocated to energy efficiency programs. Energy
efficiency funding for each future year in the time period was projected as equal to the funding for 2012.
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specific estimates were not available. No decay of savings during measure life was
assumed, so savings for each year during a measure's lifetime are equal to the lifetime
savings averaged over the measure lifetime.
Table 1.4: Levelized Cost of Saved Energy by State
State LCSE ($/kWh)
California
Connecticut
Iowa
Massachusetts
Minnesota
Nevada
New Jersey
New Mexico
New York
Oregon
Rhode Island
Texas
Vermont
Wisconsin
Default (Simple
Average)
$0.029
$0.028
$0.017
$0.031
$0.021
$0.019
$0.026
$0.033
$0.019
$0.016
$0.030
$0.017
$0.027
$0.033
$0.025
Note: LCSE is based on program administrator
costs, not on total resource costs.
Source: ACEEE (2009a), Table 1
Energy savings from ratepayer-funded programs in each year (t) were estimated using the
following formulas:
CRF = (d *(l+d)L)l((l+d)L -1)
A(t)73 = (F(t) * CRF)/LCSE(t)
C(t) = A(i) + A(i-\) + . . . + A(t-L+l)
Where:
CRF is the Capital Recovery Factor,
L is the measure lifetime,
d is the discount rate,
A is the annual first-year energy savings,
F is the annual program funding,
LCSE is the levelized cost of saved energy, and
C is the cumulative energy savings.
73 In the case of New Hampshire, lifetime savings estimates were available fromNHEU (2009) so they
were not estimated using this formula.
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Some special considerations and areas of improvement in the methodology are:
1) Ratepayer-funded energy savings for Montana are understated in this analysis
because funding data were available for only some of their utility programs.
More comprehensive data about Montana's program funding are needed to
improve the savings estimates for these states.
2) Additional information about forecasted funding will also assist in refining the
savings estimates for future program years.
RGGI-Funded EE programs
Savings from RGGI-funded energy efficiency programs were estimated for three states -
Delaware, New Hampshire and New Jersey. The other seven RGGI states have EERSs,
and RGGI-funded energy efficiency improvements count towards their EERS goals.
RGGI-funded savings were also estimated using state-level estimates of program funding
and costs of saved energy. Total RGGI proceeds available to each state in each year
during the policy period were estimated using forecasted allowance prices and CO2
emissions. 4 RGGI Signatory States have agreed that at least 25 percent of their shares of
RGGI auction proceeds will be allocated for a consumer benefit or a strategic energy
purpose,75 and to date states have allocated 52 percent of proceeds to improve energy
efficiency76. Proceeds are allocated according to state laws, and Delaware, New
Hampshire and New Jersey have explicitly adjustable allocations77 or have recently
diverted RGGI proceeds for purposes other than renewable energy, energy efficiency and
direct consumer assistance78.
In order to be conservative in projections of future EE funding from RGGI proceeds, an
assumption was made that 25 percent of each state's proceeds in each year are used to
fund energy efficiency programs. Based on information from ACEEE (2009a), an LCSE
of $0.026/kWh was used for New Jersey.
Consistent with the assumptions used to estimate savings from ratepayer-funded
programs, a default LCSE of $0.025/kWh was used for Delaware and New Hampshire,
and a discount rate of 5 percent was used for all states. No decay of savings during
measure life was assumed, so savings for each year during a measure's lifetime are equal
to the lifetime savings averaged over the measure lifetime.
Energy savings from RGGI-funded programs in each year (t) were estimated using the
following formulas:
CRF = (d *(l+d)L)l((l+d)L -1)
A(i) = (F(t) * CRF)/LCSE(i)
C(t) = A(i) + A(i-\) + ... + A(i-L+\)
74ICF(2010)
75 RGGI (2005)
76 RGGI (2011)
77 Delaware State Senate (2008)
78 Nashua Telegraph (2010)
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Where:
CRF is the Capital Recovery Factor,
L is the measure lifetime,
d is the discount rate,
A is the annual first-year energy savings,
F is the annual program funding,
LCSE is the levelized cost of saved energy, and
C is the cumulative energy savings.
Some special considerations and areas of improvement in the methodology are:
1) Two RGGI Signatory States, New York and Maryland, have EERSs in place
through 2015. RGGI-funded energy efficiency savings in these states would
count towards EERS goals until 2015, and then would continue as stand-alone
programs in years past 2015. Savings past 2015 were not estimated, however,
because there was no way to separate savings embedded in AEO2010 to isolate
the share tied specifically to programs funded by RGGI. Without quantified
embedded savings, incremental RGGI-savings could not be calculated.
2) The share of RGGI proceeds allocated to energy efficiency programs varies
across states. Detailed information on anticipated funding will help improve
estimates of future savings.
EPA's Draft Methodology For Generating State-Adjusted Forecast That Reflects
Energy Savings Incremental To AEO2010
Energy savings that are estimated as incremental to AEO2010 were estimated by
subtracting cumulative savings embedded mAEO20JO from total savings from EERSs,
ratepayer-funded programs and RGGI-funded programs:
7(t) = C(t)-£(t)
Where:
C is the cumulative energy savings,
E is the cumulative savings embedded in the AEO2010 forecast and
/is the cumulative savings incremental ioAEO2010 forecast.
The State-Adjusted Case Electricity Sales Forecast includes the impact of energy
efficiency savings that are incremental to the Reference Case (Business-As-Usual).
State-level adjusted sales (Z) are calculated as:
Z(t)=5(t)-/(t)
Where:
B is the baseline total sales and
/is the cumulative savings incremental ioAEO2010 forecast.
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SECTION 1.4: EPA'S DRAFT METHODOLOGY FOR ESTIMATING
PROJECTED PEAK DEMAND SAVINGS OF EE POLICIES
State-level peak savings were estimated as the hourly load impact of energy efficiency
programs during the state's peak hour.79 In the absence of state-specific information on
the timing of the peak, the peak hour for each state was assumed to be the same as the
Qf\
peak hour for the Integrated Planning Model (IPM) region in which it largely sits (based
on population) in EPA's Base Case.
Table 1.5 presents the state-to-region mapping that was used. Since the load shape data
used in EPA's Base Case were available for 2007, the peak hour for each year of interest
was also shifted based on the first day of the year in the same manner as in Step 3 above.
For each state, the peak hour for each year was then identified on the load impact curve
for that year, and the corresponding hourly impact was taken to be the peak savings.
Table 1.5: EPA Base Case Region Mapping for IPM
State IPM Region
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Hawaii
Illinois
Indiana
Iowa
Maine
Maryland
Massachusetts
Michigan
Minnesota
Montana
Nebraska
New Hampshire
New Jersey
New Mexico
New York
AZNM
ENTG
CA-S
RMPA
NENG
MACE
FRCC
HAWI
COMD
RFCO
MRO
NENG
MACS
NENG
MECS
MRO
NWPE
MRO
NENG
MACE
AZNM
NYC
It was assumed that EE programs do not shift the peak, and a dynamic analysis of peak demand was not
performed.
80 "Model region" refers to the geographic regions defined for the "EPA Base Case using IPM® v.4.10," a
projection of electricity sector activity that takes into account only those Federal and state air emission
laws and regulations whose provisions were either in effect or enacted and clearly delineated at the time
the base case was finalized in August 2010. The peak hour is taken from load shapes used in EPA's Base
Case using IPM®, which are compiled by aggregating EIA-714 data to the model region level.
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State IPM Region
Ohio
Oregon
Pennsylvania
Rhode Island
Texas
Vermont
Washington
Wisconsin
RFCO
PNW
MACE
NENG
ERCT
NENG
PNW
WUMS
Developed by ICF International based on:
US EPA (2010), Introduction
EPA's Draft Methodology For Generating Load Impact Curves Of EE Policies
The approach for developing load impact curves was based on previous work performed
by ICF International for EPA in 2009. Through this project, ICF developed regional
sectoral load impact shapes to represent typical hourly load impacts from energy
efficiency programs. Residential sector and commercial sector impact shapes were
estimated for each of the nine Census Divisions and industrial sector impact shapes were
estimated for each of the four Census Regions. The shapes of the impacts were based on
region- and sector-specific energy efficiency program mixes that were developed
independently by ICF. These program mixes were not intended to represent any
particular set of programs in place, but were generic, driven by considerations including
cost-effectiveness to the consumer, which varied mainly due to regional building
population and climate. To see the results of EPA's draft estimates refer to
http://www.epa.gov/statelocalclimate/state/statepolicies.html
The regional sectoral energy efficiency load impact shapes previously developed were
scaled based on state sectoral savings shares and total incremental savings in order to
develop load impact curves for this analysis. The implicit assumption was that the
energy efficiency measures being modeled in aggregate mirror the bundled measures
underlying the original load shapes. Load impact curves for each state were developed
for 2010, 2012, 2015 and 2020 using the following steps.
1) Estimating Sectoral Shares of Energy Efficiency Savings
a. The average (0) of national sectoral savings81 (X) as a share of national
sectoral sales 2 (7) for 2007-2009 was calculated for the residential (r),
commercial (c) and industrial (i) sectors.
b. Sectoral sales (7) in 2009 as a share (P) of total residential, commercial
and industrial sales in 2009 were calculated for each state (s).
EIA 2008a, EIA 2009a, EIA 2010c
EIA 2008b, EIA 2009b, EIA 2010e
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PT,S - Yr,s,20Q9/(
PC,S =
Pi,s = ^c,s,
c. Sectoral shares of energy efficiency savings (Q) in each state were
calculated as:
QT.S = (PT,s * Or,n)/(Pr,S * Or,n + Pc,s * Oc,n + Pj,s * OU)
QC,s = (Pc,s * Oc,n)/(Pr,s * Or,n + Pc,s * Oc,n + Pi>s * 0U)
*
*
*
Savings shares for each state are presented in Table 1.6.
Table 1.6: Sectoral Shares of Savings
State Share of Savings (%)
Residential Commercial
Industrial
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Hawaii
Illinois
Indiana
Iowa
Maine
Maryland
Massachusetts
Michigan
Minnesota
Montana
Nebraska
New Hampshire
New Jersey
New Mexico
New York
Ohio
Oregon
Pennsylvania
Rhode Island
50.6%
51.2%
40.4%
42.1%
47.4%
46.6%
55.1%
40.2%
41.4%
46.2%
43.7%
47.1%
47.0%
45.9%
41.7%
43.8%
43.3%
44.0%
47.5%
40.7%
38.0%
38.6%
45.8%
50.5%
46.9%
43.1%
43.3%
33.0%
52.0%
46.2%
47.7%
43.0%
42.0%
42.6%
44.9%
32.1%
35.6%
42.0%
49.7%
40.0%
45.9%
42.3%
41.4%
40.6%
45.5%
55.0%
48.7%
57.6%
38.6%
38.9%
39.3%
51.7%
6.1%
15.8%
7.6%
11.7%
4.9%
10.5%
2.9%
17.2%
13.8%
21.7%
20.6%
10.9%
3.3%
14.0%
12.4%
13.9%
15.4%
15.4%
7.0%
4.3%
13.3%
3.8%
15.7%
10.7%
13.7%
5.2%
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State Share of Savings (%)
Residential Commercial
Industrial
Texas
Vermont
Washington
Wisconsin
46.8%
47.0%
49.8%
42.1%
40.8%
42.1%
38.9%
42.2%
12.4%
10.9%
11.3%
15.6%
Developed by ICF International based on data from:
EIA (2008a), File3; EIA (2009a), File3; EIA (2010c),
File3
EIA (2008b), Table 2; EIA (2009b), Table 2; EIA (2010e),
Table 2
2) Scaling Based on Sectoral Savings Shares for Each State
a. The regional residential and commercial hourly EE impact shapes for
Census Region and the industrial shape for the Census Division in which
the state lies were selected.
b. The selected regional sectoral load impact shapes were scaled using the
appropriate sectoral shares of energy efficiency savings (Q) estimated in
Step (1) to develop scaled sectoral 8760 hourly load impacts for each
state.
c. The scaled residential, commercial and industrial 8760-hour load impacts
were summed by hour to get the total hourly load impact shape of energy
savings for the state (this is still normalized to base 1).
3) Shifting Based on First Day of the Year and Accounting for Leap Years
a. The original load impact shapes were developed for a year that began on a
Sunday.
b. The first day of each year of interest was identified, and the load impact
shapes were reconciled by determining the least number of days between
that day and Sunday.
e.g. 2010 begins on a Friday, and Friday is two days before Sunday
2020 begins on a Wednesday, and Wednesday is three days after Sunday
c. For each year of interest, the total hourly load impact shape for the state
was shifted ahead or behind by the least number of days to ensure that the
first day of the load impact shape corresponded with the first day of the
year.
d. Two years of interest, 2012 and 2020, are leap years. The last day of each
of these years was not included in the analysis to ensure consistency
across years.
4) Scaling based on Total Incremental Savings for Each State
a. For each year, the shifted and scaled hourly load impacts were scaled once
more by multiplying them with the total cumulative incremental savings
estimated for that year. The resulting 8760 hourly load impacts sum to the
total cumulative incremental savings and represent the load impact shape
for the year.
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EPA's Draft Methodology For Estimating RE Sales From RPS Beyond What Is
Captured In AEO2010
The AEO2010 Reference Case incorporates RPSs or substantively similar laws in place at
the time of forecast development. Six states' RPSs83 were included in this analysis
because they were known to have been excluded from AEO2010 or revised since the time
ofAEO2010 forecast development.
RPS targets as a percent of total sales were available for each year in the policy period for
California, Colorado, Delaware and Massachusetts. These were applied to the State-
Adjusted Case Electricity Sales forecasts for the respective states to estimate required
renewable energy sales. In the case of Hawaii, where RPS targets were only available for
2010, 2015, 2020 and 2030, sales in intervening years were estimated by interpolation.
Since New York's RPS allows existing renewables to count toward the goal, the state's
renewable sales in 2015 were estimated using available data on 2004 renewable sales84
o c
and the incremental sales needed to meet the 30 percent target . Sales in intervening
years were estimated by interpolation. For all states, RPS requirements were frozen in
percent terms for the years after the RPS policy period.
SECTION 1.5: EPA'S DRAFT METHODOLOGY FOR GENERATING STATE-
ADJUSTED FORECAST AND AGGREGATING IT TO FACILITATE
MODELING REGIONAL RPS IMPACTS
Since the AEO2010 forecast is developed based on regional inputs, mandatory RPS
targets from the various states are aggregated to the regional level in order to represent
them in NEMS. The amount of renewable generation required in each state is estimated
based on the state's RPS targets, compliance schedules, and projected sales growth.
Though some states could be split across two or more regions, each state's required
renewable generation is assigned to a single NERC region based on EIA expert judgment
of factors such as predominant load locations and locations of RPS-eligible renewable
resources. Required renewable generation for all assigned states is then summed to the
NERC region level and used to determine regional renewable generation shares of total
sales. Hawaii's RPS, which sets the state's renewable mandate at 20 percent by 2020, is
not modeled in AEO2010 because NEMS provides electricity market projections for the
continental US only.
Table 1.7 presents some of the state-level RPS targets used by EIA to facilitate aggregate
regional modeling of impacts; adjustments made for regional modeling may cause
discrepancies between these targets and the actual RPS policies. Targets are presented
only for the six states for which incremental RPS requirements were estimated, as
described in the next section.
83 California, Colorado, Delaware, Hawaii, Massachusetts, New York
84 NY PSC (2004)
85 NY PSC (2009)
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Table 1.7: RPS Requirements Used to Model Regional RPS Impacts for AEO2010
State State RP S Targets (1000 GWh)
••
California
Colorado
Delaware
Hawaii1
Massachusetts
New York
2010
39.06
1.70
0.49
NA
1.34
24.98
2012
43.03
3.54
0.79
NA
1.92
26.64
2015
48.24
5.49
1.24
NA
2.76
28.59
2020
58.78
7.88
1.91
NA
4.29
29.40
Note:
AEO2010 provides a forecast for the continental U.S. only, so
impacts of Hawaii's RPS are not included mAEO2010.
Source:
EIA (201 Of) (included with permission)
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Delaware State Senate, 144th General Assembly (2008). Senate Bill No. 263: An Act to Amend
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NJ BPU (2009). New Jersey's Board of Public Utilities and New Jersey's Clean Energy Program
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590-E7E1-473B-A648-450A39E80F48%7D>
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Vermont Energy Investment Corporation (VEIC) (2009). Efficiency Vermont: Annual Plan 2010-
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Appendix J: State Examples and
Opportunities
SECTION J.I - STATES THAT ADDRESSED CLEAN ENERGY IN THEIR SIPS FOR
THE 1997 OZONE NAAQS
Background
Leading up to the ozone State Implementation Plan (SIP) revisions due in 2007, several
states pursuing additional emissions reductions took steps to factor their clean energy
initiatives into air quality plans. These jurisdictions established multi-stakeholder
working groups to analyze the emissions benefits of efficiency and renewables (EE/RE),
and to specify the policy mechanisms involved with this new approach. Key drivers for
these efforts included impending regulatory deadlines and significant financial assistance
provided under DOE's "Clean Energy/Air Quality Integration Initiative." The Initiative
was active from 2005-2007 and focused on four states: Illinois, Texas, Louisiana, and
New Jersey. Two other jurisdictions - Connecticut and the metropolitan Washington,
D.C. region - independently took steps to quantify their emissions reductions.
Summary
State experience to-date has produced mixed results, both in terms of estimated air
quality impacts and policy outcomes. In all cases, states found that analyzing the effects
of EE/RE on air quality is time and resource intensive, and that available
modeling/quantitative tools do not always produce the level of certainty that state and
federal air agencies desire. Furthermore, experience shows that many different parties -
e.g., DEPs, SEOs, EE/RE administrators, EPA regional offices, OAQPS, technical
consultants, etc - need to be engaged over extended periods of time for states to achieve
their goals.
In terms of policy outcomes, the following jurisdictions were successful in including
clean energy in their air quality plans:
1. DC Region (via the MWCOG) - voluntary control measures in 1 hour and 8 hour
ozone SIPs
2. TX and Shreveport, LA - voluntary control measure in 8 hour ozone early-action
compact SIP revision
3. CT - weight of evidence in 8 hour ozone SIP
NJ and IL also convened working groups to evaluate clean energy/air quality
opportunities, but ultimately decided not to include EE/RE resources in their plans.
One question that cannot be conclusively answered from state experience is whether the
relevant EE/RE projects are "additional." This is because the SIP is intended to capture
all pollution mitigation activities, regardless of whether the actions were originated
within the SIP process. As a result, state agencies are not required to specify whether
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clean energy projects would have happened anyway. A secondary issue revolves around
whether reduced electric demand would create emission reductions in the presence of a
cap and trade program.
State Examples
This section highlights examples of states that have taken steps to include clean energy in
their SIPs. In all cases, the states took the following general approach to quantifying the
impacts of clean energy on air quality:
• Determining the amount, type, and location of electric generation that would be
displaced by EE/RE measures being pursued in the jurisdiction
• Estimating the annual and summer ozone season NOx emission rates from power
plants serving the state/region
• Determining the impact on annual and ozone-season NOx emissions
• Resolving policy barriers to incorporating reductions into state air quality plans
EE/RE In A Voluntary Control Measure Bundle
Texas: A stakeholder group in Texas was established to explore the impact of recent
clean energy legislation - Senate Bill 5 (SB5) and Senate Bill 7 (SB7) - on air quality,
and assess how the impacts could be incorporated into its ozone SIP. Key stakeholders
included the TX Commission on Environmental Quality (TCEQ), Texas State Energy
Conservation Office (SECO), and federal agencies, with analytic support from Texas
A&M Energy Systems Lab. The clean energy measures evaluated included requirements
for utilities to offset 10% of load growth through EE, clean vehicle incentives, and a
requirement for new buildings to meet the state's new energy performance standards,
including better weather-stripping, more efficient air conditioners, and stricter insulation
guidelines. With EPA regulatory approval in 2007, the state included EE/RE in the SIP
as a voluntary control measure.
TX ozone transport SIP, search for "efficiency":
http://www.tceq.state.tx.us/assets/public/implementation/air/sip/transport/041608SIP ADOPTION.pdf
(html page with above link: http://www.tceq.state.tx.us/implementation/air/sip/sipplans.html)
DC Region: In 2004, Montgomery County, MD led a multi-county buying group to
purchase wind power and undertook a first-of-its-kind analysis to estimate its effect on
air quality. The reductions were ultimately included in the Maryland SIP, which was
approved by EPA in 2005. Building on this success, Metropolitan Washington Council
of Governments developed a regional air quality plan for the eight-hour ozone standard
for the DC Region non-attainment area that also included clean energy provisions. This
2007 MWCOG air quality plan increased municipal RE purchases fourfold from 2004 to
2009 - with commitments to purchase 123 million kWh of renewable energy certificates
annually - and included the installation of LED traffic lights in place of conventional
incandescent lights. The plan was adopted by Virginia, Maryland, and the District of
Columbia and the respective ozone SIPs were approved by the EPA regions in 2007.
DC Region 8 hour ozone SIP, see p. 126:
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http://www.mwcog.org/uploads/pub-documents/9FhcXg20070525084306.pdf (html page with above
link: http://www.mwcog.org/environment/air/SIP/default.asp)
Shreveport, LA: As part of its SIP revisions for the purpose of attaining and maintaining
the 8-hour ozone standard, the Louisiana Department of Environmental Quality (DEQ)
submitted an Early Action Compact SIP for the Shreveport area to EPA in 2004. The SIP
included the emission reductions expected to be achieved from performance contracting
at 33 municipal buildings in Shreveport. The performance contract was estimated to have
saved 9,121 MWh of electricity per year with NOx emission reductions of 0.041 tons per
ozone season-day. The city arrived at this figure after employing several different
methods to determine the emissions avoided through its programs. EPA Region 6
published approval of this SIP revision in August, 2005.
Shreveport Early Action Compact, seep. 3:
http://www.deq.louisiana.gOv/portal/Portals/0/AirQualitvAssessment/Planning/SIP/Progress%20Report%2
06-30-04.pdf (html page with above link:
http://www.deq.louisiana.gov/portal/Default.aspx?tabid=2311)
States Using EE/RE In A Weight Of Evidence Finding
Connecticut: In Connecticut, the Department of Environmental Protection (DEP) - a
member of the Ozone Transport Commission - wanted to know if the EE programs
managed by Connecticut Light and Power and the United Illuminating Company could
reduce electricity consumption and NOx emissions on "high electricity demand days."
The DEP worked with other OTC states to analyze the mix of power plants used to meet
peak demand and determined that many had the highest emission rates in the region. The
OTC team also found that peakload electricity demand on the hottest days was growing
two to three times faster than baseload demand. With this information, CT DEP
established a team of technical experts to analyze the effect that EE/RE projects -
including high efficiency air conditioners, compact fluorescent lighting, and solar
photovoltaic energy - were having on NOx emissions at critical/peak times. The results
were included as "weight of evidence" in the 8-hour ozone SIP and submitted to the EPA
region in June 2007.
CT 8 hour ozone SIP, see page 31:
http://www.ct.gov/dep/lib/dep/air/regulations/proposed and reports/section 8.pdf (html page with
above link: http://www.ct.gov/dep/cwp/view.asp?a=2684&q=385886&depNav 010=1619)
SECTION J.2: STATES THAT ARE CONSIDERING INCORPORATING EE/RE
PROGRAMS AND POLICIES IN THEIR SIPS FOR THE REVISED OZONE
NAAQS
There are several states now exploring opportunities for incorporating EE/RE into their
forthcoming ozone SIPs. Three of these states are featured in this appendix:
• Connecticut
• New Mexico
• Maryland
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The three states are at the early stages of the SIP process and their efforts have involved
(or will need to involve) at least three activities that include:
• Initiating collaboration with key state entities responsible for air and energy
decisions
• Understanding and identifying EE/RE policies and programs to be included in the
SIP, as well as estimating the magnitude of potential air emissions benefits
• Understanding pathways available for incorporating EE/RE programs and
policies into SIPs
State Of Connecticut
Connecticut's experience is used in this section to illustrate one state's approach to
addressing these steps. Background information is provided in Attachment A on the
state's EE/RE policies and programs. Other states can use this experience to inform their
own efforts to incorporate EE/RE into SIPs.
Background
On January 6, 2010, EPA proposed a rule to strengthen the primary and secondary
NAAQS for ground level ozone. This effort proposed a tightening of the ozone NAAQS
down to a level within the range of 60 - 70 parts per billion (ppb). Such a standard
would require additional stringent control measures on ozone precursor emissions of
VOC and NOx.
Since EPA issued the first ozone NAAQS in the 1970s, Connecticut has developed and
implemented many VOC and NOx air pollution control strategies applicable to both
stationary and mobile sources in order to protect the public health of its citizens. During
this time, Connecticut implemented the most cost effective emission control programs.
As EPA continues to strengthen the ozone NAAQS, it becomes more challenging to
identify and implement highly cost effective emission control strategies. In light of this
challenge, early in 2010 the Connecticut Department of Environmental Protection (DEP)
expressed an interest to EPA New England in exploring the use of emission reductions
associated with the state's EE and RE programs in the state's air quality planning
documents, such as the State Implementation Plan (SIP) for air quality, in the same
manner as emission reductions from more traditional air pollution control regulations
might be used. As noted earlier in this document, Connecticut cited emission reductions
from these programs within its WOE submittal made within its attainment demonstration
for EPA's 1997 8-hour ozone standard. Given the demonstrated ability of EE and RE
programs towards meeting air quality goals, DEP intends to rely more heavily on the
benefits of these programs in future attainment demonstrations, such that the impact from
the state's EE/RE programs will be directly factored into the future year modeling effort.
DEP is also considering the incorporation of some EE/RE components into the SIP as
control measures.
Initiate Collaboration Among Key State Entities Responsible For Air And Energy
Decisions
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To help ensure that the appropriate state entities are involved in joint air and energy
decisions, Connecticut has taken concrete actions to foster collaboration across agencies.
These partnerships assist in addressing the complex policy and analytic questions that cut
across traditional agency responsibilities for improving air quality and expanding the use
of clean energy. Examples of such questions include: how to identify the appropriate
SIP pathway, what method to use to estimate the energy impacts from EE/RE, and how to
quantify the resulting air quality improvement.
Over the past several years, the DEP has established formal lines of communication with
the Connecticut Department of Public Utility Control (DPUC). For example, the DEP is
a member of the state's Energy Conservation Management Board (ECMB), the Clean
Energy Fund, and the Connecticut Energy Advisory Board. These ties are important,
because the DPUC is primarily responsible for oversight of Connecticut's EE and RE
programs, including implementation, monitoring and enforcement. Each of these
programs is discussed separately below. In addition, the state continues to engage with
USEPA on the key state-federal issues that will arise if Connecticut formally moves
ahead to incorporate EE/RE into its SIP.
Understand And Identify EE/RE Policies And Programs To Be Included In The SIP
Connecticut has several existing laws requiring electric utilities to meet minimum
percentages of the state's energy needs with zero-emissions energy efficiency and
renewable energy. On the renewable energy side, a "renewable portfolio standard" (RPS)
policy requires that electricity distribution companies (Connecticut Light and Power
Company and United Illuminating Company) obtain a minimum percentage of their retail
load from renewable energy. The policy became law in 2005 with a minimum
requirement of 4.5% in that year, increasing to 27% of the state's retail electricity load by
2020. To ensure compliance, CTDPUC conducts evaluations compliance of the RPS
each year through an administrative docket process. It imposes fines or other corrective
actions if compliance is not shown.
On the efficiency side, Connecticut has over twenty years of experience with EE
programs. The Connecticut Energy Efficiency Fund (CEEF) is capitalized by a surcharge
of $0.003 per kilowatt-hour (3 mills per kWh) on utility customers' electric bills. Each of
the two utilities administers and implements efficiency programs with monies from its
ratepayer fund, in accordance with a comprehensive plan approved by the Connecticut
Department of Public Utility Control (DPUC). Additional sources of funding for the
CEEF in 2009 included the Regional Greenhouse Gas Initiative (RGGI), the Forward
Capacity Market (FCM), Class III Renewable Credits, and the American Recovery and
Reinvestment Act (ARRA).
The two utilities are authorized to implement the following types of energy efficiency
programs:
• Conservation and load-management programs, including programs that benefit
low-income individuals
• Research, development, and commercialization of products or processes that are
more energy-efficient than those generally available
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• Development of markets for such products and processes
• Support for energy-use assessment, real-time monitoring systems, engineering
studies and services related to new construction or major building renovation
• Indoor air-quality programs relating to energy conservation
• Joint fuel-conservation initiatives programs targeted at reducing consumption of
more than one fuel resource
• Public education regarding conservation.
To ensure that savings impacts are "real," the CTDPUC conducts an annual review and
evaluation of the EE programs implemented by the state's electricity suppliers.
Connecticut agencies are currently in the process of determining which of the above
activities are suitable for incorporation into the SIP. Connecticut is also reviewing its
options for quantifying the emission reduction impact from these measures.
Understand Pathways Available For Incorporating EE/RE Programs And Policies
Into SIPs
Connecticut's past experience using clean energy in an air-planning context (via its
attainment demonstration for EPA's 1997 8-hour ozone standard) provides a head start in
defining and addressing important analytic and policy challenges. To address current air
quality challenges, CTDEP and its partners are now working to identify the state's
options for:
• Including EE/RE policies and programs in future attainment demonstrations
• Factoring the impact of EE/RE programs directly into future year modeling
efforts
• Adopting EE/RE in the SIP as a control measure.
As the state proceeds, examples of key issues that the State of Connecticut will need to
address should it pursue the control strategy pathway are included in the USEPA, Region
1 letter to the state (Attachment B). These issues include what energy-impacts data to use,
how to gauge the impact that EE programs have during high electricity demand days
(days typically correlated with high ozone episodes), and how to calculate air quality
impacts at the appropriate level of detail. This letter outlines the state's strategy moving
forward and raises several outstanding questions for the state to answer. While
uncertainties remain, Connecticut's letter can be used to inform the work of other states
and jurisdictions interested in taking a similar approach.
State Of New Mexico
The State of New Mexico Department of the Environment and the City of Albuquerque
have expressed an early interest in possibly incorporating New Mexico's EE/RE policies
and programs into a potential, future SIP for the forthcoming, revised ozone NAAQS.
Currently, there are no ozone nonattainment areas in New Mexico and it is uncertain
whether the state will have any under the revised ozone NAAQS. Depending on ozone
area designations and the level of the standard, the state could possibly have three to
seven new nonattainment areas.
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Background
The USEPA has held preliminary meetings with the state to help EPA and state air staff
and managers both better understand and identify New Mexico's EE/RE policies and
programs and estimate the magnitude of potential air emissions benefits from those
policies and programs. The state and EPA have also discussed the need for interaction
between state air staff and state energy officials. The USEPA has also explored with the
state the pathways available for incorporating EE/RE programs and policies and
programs into SIPs.
Initiate Collaboration Among Key State Entities Responsible For Air And Energy
Decisions
New Mexico is a state with a very predominant urban area (Albuquerque-Bernalillo
County), with which cooperation is very important. Especially since, for New Mexico the
home-rule status of the City of Albuquerque-Bernalillo County is responsible for its own
SIP revision. The State and Albuquerque-Bernalillo may choose to act together in any
ozone SIP technical analyses, so that the entire State can be analyzed as one for purposes
of electric sector EE/RE policies and programs. With Albuquerque-Bernalillo
constituting such a large percentage of the State's total population, this cooperative
treatment might benefit both entities.
Understand And Identify EE/RE Policies And Programs To Be Included In The SIP
The state of New Mexico has three primary EE/RE policies:
• The Renewable Energy Act requires investor-owned electric utilities to produce
or buy increasing amounts of renewable energy, starting at 5 percent by 2011 and
increasing to 20 percent by 2020.
• The Efficient Use of Energy Act requires that public utilities, distribution
cooperative utilities and municipal utilities include cost-effective energy
efficiency and load management investments in their energy resource portfolios.
In 2008, the statute was amended to include a State Energy Efficiency Resource
Standard (EERS) in which public utilities must acquire all cost-effective and
achievable energy efficiency and load management resources available in their
service territories.
• The Energy Efficiency and Renewable Energy Bond Act authorizes up to $20
million in bonds to finance energy efficiency and renewable energy improvements
in state government and school buildings.
Attachment C provides more detail on New Mexico's EE/RE policies.
Understand Pathways Available For Incorporating EE/RE Programs And Policies
Into SIPs
With respect to potential EE/RE SIP demonstrations for a State such as New Mexico,
it is unclear what the State and Albuquerque will choose to do with regard to electric
sector EE/RE policies and programs in an ozone SIP revision.
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Below are two control measure examples that could apply to a state like New Mexico. It
should be noted that no New Mexico counties are currently designated ozone
nonattainment, so these examples are provided for illustrative purposes only.
The first example is a general control measure approach. Figure J. 1 conceptually
illustrates the steps that would apply genetically, while Table J. 1 provides an example for
Albuquerque-B ernali 11 o.
Figure J.I: Steps for New Mexico Analysis
For each such control
Identify each non-NEMS, enforceable measure and NAA, apportion Determine which power control
control measure causing electric \ the kwh reductions \ areas or EGUs will be included in
sector EE/RE kwh reductions for the geographically across the the attainment demonstration
attainment year (1) State to specific power for each NAA
control areas or EGUs (2)
For each NAA, input the NOx
Calculate the NOx emissions emissions reduction for each control
reduction for each power control measure into the photochemical
area/EGU for each NAA due to each model and calculate the ambient
control measure (3) ozone improvement in the future
attainment year
(1) A total kwh estimate is first made for each measure. The State and City may choose to calculate a seasonal ozone day
kwh reduction. Note that these EE/REe measures can occur in a different geographic area of the State hut still decrease
emissions from EGUs in the nonattainment area.
(2) EPA can provide guidance on suggested techniques, which may be based on electricity dispatch models.
(3) For each control measure, individual power control area or EGU NOx emission factors would be multiplied by the
kwh reduced at each power control area (PCA)/EGU.
The second example in Table J. 1 illustrates a more specific, hypothetical accounting of
EE/RE NOx reductions for Albuquerque-Bernalillo County alone. In this example, four
separate EE/RE measures are quantified to determine their impacts on reducing NOx
emissions in the state and ultimately ambient ozone in the nonattainment area. Some of
these measures are ones adopted by New Mexico and highlighted in Attachment C to this
appendix. Not all of these NOx emissions reductions would occur within Albuquerque-
Bernalillo County. Also note in this example it is assumed that seven EGUs are impacted
by these various measures, but NOx emissions from only EGUs 1-5 are determined to
impact ozone levels in Albuquerque-Bernalillo.
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Table J.I: Hypothetical Example for Albuquerque-Bernalillo
EE/RE Measure (1) Resulting Electricity Reductions NOx Reduction at PCA/EGU (2)
(tons/ozone season day)
LED retrofits for traffic lights (in
NAA)
State Renewable Energy Tax
Credit (Corporate) (in NAA)
Building Tax Credit (in NAA)
State Renewable Energy
Production Tax Credit
(Corporate) in County A (outside
NAA)
1 million kwh
2 million kwh
1 million kwh
10 million kwh
ECU 1: 0.1, ECU 2: 0.2, ECU
3:0.05
ECU 1: 0.2, ECU 2: 0.05, ECU
3: 0.2, ECU 4: 0.3
ECU 2: 0.05, ECU 4: 0.25
ECU 4:2.0, ECU 5:1.0, ECU 6:
2.0, ECU 7:1. 5
(1) In concert with the State, EE/RE control measures can include not only those that actually occur in
Albuquerque-Bernalillo but also those that occur in outlying areas but that cause a reduction in emissions
from EGUs that impact Albuquerque-Bernalillo
(2) In this example only EGUs 1-5 affect ozone concentrations in the Albuquerque-Bernalillo NAA.
Therefore, emissions reductions from only EGUs 1-5 would be input into the photochemical model to
assess the ambient ozone reductions due to the electric sector EE/RE measures.
State Of Maryland
Background
Under a revised, more stringent ozone standard, almost all of Maryland will likely
measure air quality that results in being designated nonattainment, which will pose
challenges as the state seeks additional reductions in ozone precursors. In addition,
Maryland also recently adopted legislation that requires the state to develop a climate
action plan to reduce greenhouse gas emissions 25 percent by the year 2020.
Coordinated multi-pollutant planning and the implementation of synergistic strategies
will be necessary to successfully meet these two challenges. .
Understand And Identify EE/RE Policies And Programs To Be Included In The SIP
Maryland currently has several pieces of legislation intended to provide a substantial start
toward these goals (see Attachment B for a greater description):
• The Healthy Air Act which required coal-fired power plants in Maryland to
reduce NOx by 75%, SO2 by 85%, and mercury by 90%, and
• Participation in the Regional Greenhouse Gas Initiative to reduce CO2 emissions.
• The EmPOWER Maryland Energy Efficiency Act of 2008 is designed to reduce
per capita electricity use by Maryland consumers by 15 percent in 2015.
• The accelerated RPS standard 20% of electricity from renewable resources by
2022.
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Understand Pathways Available For Incorporating EE/RE Programs And Policies
Into SIPs
Maryland anticipates that a significant weight of evidence demonstration will be
necessary in the next round of ozone SIPs to supplement conventional photochemical
modeling. At this time, Maryland believes that emission reductions for energy efficiency
may be a key element needed to show attainment.
To separate the emission reductions that should be attributed to energy efficiency
policies/programs compared to programs that control emissions through specific caps,
Maryland has contracted with NESCAUM to run an integrated framework of models.
The NE-MARKAL (New England MARKet ALlocation model), initiative, which began
through a collaboration between NESCAUM and the U.S. EPA Office of Research and
Development in 2003, has resulted in the development of a least-cost optimized linear
programming (LP) model which is tailored specifically to the energy infrastructure of
several Northeast states.86 NE-MARKAL is a data-rich analytical framework for
examining energy policy options and their resultant impact on energy services in the
region. The model serves as the centerpiece of the integrated policy analysis framework
developed at NESCAUM which aids in developing a comprehensive understanding of
technology, economic, environmental and public health consequences of air quality
protection initiatives.
How the NE-MARKAL model works:
• The NE-MARKAL model can accept Maryland-specific inputs for spending on
planned energy efficiency programs and combine them with the mandated caps
for NOx, SO2, mercury and CO2 and the Maryland clean car program.
• Emissions outputs from NE-MARKAL can then be inputted into the Community
Multiscale Air Quality (CMAQ) model to estimate the NOx air quality benefits
from the caps as well as from the energy efficiency programs and displaced fossil
fuel use due to the RPS standards.
• Financial outputs from NE-MARKAL can be imported into the Regional
Economic Models, Inc (REMI) model to estimate economic benefits from these
programs such as gross state product, jobs and disposable income.
• Finally, the outputs can be input into the Benefits Mapping and Analysis Program
(BENMAP) model to estimate health benefits from all the programs (see Figure
1.1).
The results of combined strategy runs from the economic energy model NE-MARKAL
and CMAQ can be compared to results obtained from conventional strategy runs of
CMAQ alone to assess the benefits of adding energy efficiency benefits versus the
benefits estimated for the implementation of caps alone.
Working with NESCAUM, Maryland has completed Phase I which including:
86 http://www.nescaum.org/topics/ne-markal-model
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• A Maryland specific calibration of the NE-MARKAL model
• An independent assessment for the impacts of RGGI and Maryland Clean Cars
This type of scenario analysis serves to identify the magnitude of climate, air quality and
energy impacts relative to the other strategies under examination.
In Phase II, Maryland proposes to identify interactions between the strategies that may
lead to climate, air quality and energy outcomes that differ from an analysis that
examines only one strategy at a time.
Figure J.2: Key Pieces of NESCAUM Multi-Pollutant Framework
NE-MARKAL
Energy Model
CMAQ Air Quality Model
Future
State Mandatory EE/RE
Policies
Expenditures
12-StateREMI
Economic Model
SECTION J.3: OPPORTUNITIES TO REDUCE ELECTRICITY CONSUMPTION AND
NOX EMISSIONS FROM EPA'S STORM WATER RULES
EPA's Office of Water (OW) is proposing new storm water mitigation regulations in late
2011. After OW takes public comments, they plan to finalize these regulations in 2012.
Compliance measures for these new regulations are expected to rely heavily on best
practices for "green infrastructure," a series of actions and technologies that encourage
natural processes to accommodate and minimize storm water runoff. (See examples
below) These kinds of measures can directly result in reducing electricity consumption
and NOx emissions in the following ways:
• Reduce municipal electricity demand due to less frequent pumping, (easiest to
quantify and attribute to NOx emission reductions);
• Obviating construction of conventional, artificial storm water channeling,
processing, and controlled discharge systems;
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Reduction in electricity demand for cooling in buildings near green infrastructure
implementation areas; and
Reduction in photochemical
generation potential due to cooling of
urban core.
A recent report for the Philadelphia
metropolitan area is an excellent resource that
can help locals and states interested in
8"7
pursuing NOx SIP reductions in this way.
Green Infrastructure
Measure Examples
• Increasing vegetated surfaces in
developed areas,
• Swales,
• Water gardens,
• Holding ponds,
• Permeable pavements,
EPA stands ready to work with any interested
state or local agency in investigating the potential for NOx reductions due to storm water
compliance activities.
87 "A Triple Bottom Line Assessment of Traditional and Green Infrastructure Options for Controlling CSO
Events in Philadelphia Watersheds, Stratus Consulting,"
http://www.michigan.gov/documents/dnr/TBL.AssessmentGreenVsTraditionalStormwaterMgt 293337 7.
rjdf,2009.
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ATTACHMENT A: STATE OF CONNECTICUT EE/RE POLICIES AND PROGRAMS
RE Policies and Programs
Connecticut's renewable portfolio standard (RPS) is a mandatory program implemented
pursuant to state legislation. The RPS program began in 1998 as part of the electric
deregulation initiative, and requires that electricity suppliers obtain a minimum
percentage of their retail load from renewable sources. The minimum percent
requirement was 4.5 % in 2005, and it increases each year until 2020, at which point 27%
of the state's retail electricity load must come from renewables sources. CTDPUC
evaluates each electricity supplier's compliance with the RPS requirement each year
through an administrative docket process, and imposes fines or other corrective actions if
compliance is not shown. To date, Connecticut's electricity suppliers have been able to
meet their obligations every year but one, and the DPUC imposed substantial monetary
fines for each MWh shortfall in meeting the required RPS. Under CT's RPS program,
there is a requirement for a quarterly truing up and an annual report. The CT DPUC
requires EDCs to look back to see if the RPS minimum percentage requirement was met.
If it has not been met, then the DPUC requires the LDC to pay a fee or essentially a fine.
In 2006, 15 companies distributed or supplied electricity to CT customers. Eight of the
15 entities did not "serve" any load in that year. Of the seven companies that did, four
met the Class I percentage requirement, while three did not. As a consequence, the three
companies paid fees totaling $3.5 million.
Given the established track record and the enforcement of the program at the state level,
Connecticut is exploring ways to rely on the emission reductions from its RPS program in
the next SIP necessary to meet EPA's reconsidered ozone standard, which is expected to
be announced in July, 2011. Utilizing RPS in air quality plans is complicated by the fact
that electricity suppliers may demonstrate compliance with the RPS through the purchase
of renewable energy credits (RECs) from out of state renewable energy generators,
whereas the federal Clean Air Act requires that reductions relied on for RFP or
attainment must come from within the nonattainment area. Connecticut intends to work
with the region's Independent System Operator, the ISO-New England, to analyze which
electric generating units (EGUs) are likely to ramp down as more "must-take" renewable
energy resources are made available. A key aspect of this analysis will be predicting the
location of future renewable energy resources in New England, and identifying the fossil-
fuel fired units that either shut-down or operate less due to the increased electricity
produced from renewable resources.
Under CT's RPS program the renewable power generally can come from the New
England or NY power pools, although the statutory region includes New England states,
NY, PA, NJ, MD, DE. All of these states have RPS programs except VT.
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EE Policies and Programs
Connecticut has over twenty years of experience with EE programs. Even before the
restructuring of the electric power industry that occurred in 1998, electric utilities in
Fairfield County used EE programs to supplement energy generation and to help mitigate
transmission constraints. These early successes were then developed into statewide
programs when, in 1998, the state's legislature established the Connecticut Energy
Efficiency Fund and created the ECMB. These programs are funded primarily by
ratepayers but are supplemented with funds from other sources such as proceeds from the
auction of allowances in the Regional Greenhouse Gas Initiative program. The CEEF is
funded by a surcharge of $0.003 per kilowatt-hour (3 mills per kWh) on Connecticut
Light and Power (CL&P) and United Illuminating (UI) customers' electric bills. Each of
the two utilities administers and implements efficiency programs with monies from its
ratepayer fund, in accordance with a comprehensive plan approved by the Connecticut
Department of Public Utility Control (DPUC). The utilities develop their plans with
advice and assistance from the state's Energy Conservation Management Board (ECMB).
Additional sources of funding for the CEEF in 2009 included the Regional Greenhouse
Gas Initiative (RGGI), the Forward Capacity Market (FCM), Class III Renewable
Credits, and the American Recovery and Reinvestment Act (ARRA).
As with the state's RPS program, the DPUC conducts an annual review and evaluation of
the EE programs implemented by the state's electricity suppliers. Connecticut is
evaluating whether some of these programs may be suitable for incorporating into its SIP.
Connecticut is also reviewing options for quantifying the emission reduction impact from
these measures. With regard to quantification, the state may use as a starting point the
somewhat conservative estimate of energy savings bid into and accepted by the ISO-New
England's Forward Capacity Market. Additionally, the state is exploring how to gauge
the impact that its EE programs have during high electricity demand days, as these days
typically correlate well with high ozone episodes. Energy Efficiency Policy
Connecticut's original electric-industry restructuring legislation (Public Act 98-28) was
enacted in April 1998 and created the Connecticut Energy Efficiency Fund (CEEF). The
mission of the CEEF is to advance the efficient use of energy, to reduce air pollution and
negative environmental impacts, and to promote economic development and energy
security.
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Take EE
Measure
How Does Connecticut Quantify Energy (kWh)
Savings from Energy Efficiency?
Average Program Example
Define Method
Add and
Subtract
Secondary
Benefits
Determine
Confidence of
Installation
Determine %
of Time Units
are Operating
Determine
Coincidence with
Peak (Summer
and Winter)
Savings
(kWh)
C&I
Standard
Lighting
Replaced lighting
(kWoM-kWnew)
+
Occupancy Sensors
0.3 'x flights on
sensor x
wattage/light)
+ Un-needed
Additional
Cooling
- Additional
Heating
Needed
41.67%2
£(Hours of
Operation per
Operating
Unit)
A) Occupancy
Coincidence
Factor.
-Winter=0.13*
-Summer=0.15*
B) Lighting
Coincidence
Factor.
-Winter=0.55*
-Summer=0.70*
1 D. Maniccia B. Von Neida, and A. Tweed. An analysis of the energy and cost savings potential of occupancy sensors for commercial lighting systems Illuminatin;
Engineering Society of North America 2000 Annual Conference: Proceedings. IESNA: New York, NY. Pp. 433-459
2 R.A. Rundquist et al., Calculating Lighting and HVAC Interactions. ASHRAE Journal, November 1993
* Average winter coincidence factor of each sector calculated by the above
kWh Savings =>Emissions Averted
Emissions saved=
(ISO Emissions
Factor) x (2008
MWh-2009MWh)
X
1.511bs/MWh
X
0.521bs/MWh=
X
8901bs/MWh
Emissions Facials are fiom New England Averages of the ISO New England 2008 New England Electric Generator Air Emissions
Report.
Connecticut Values from the above report are: SO,.= 0 42bs/MWh; NCt^O 47Ibs/MWh; CO,=740Ibs/MWh
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Letter from USEPA Region 1 to State of Connecticut
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
REGION 1
5 POST OFFICE SQUARE. SUITE 100
BOSTON. MA 02109-3912
September 30, 2010
Anne Gobin, Chief
Bureau of Air Management
Connecticut Dept. of Environmental Protection
79 Elm Street
Hartford, Connecticut 06106-5127
Dear Ms. Gobin:
As you know, on January 6, 2010 EPA proposed to tighten the national ambient air
quality standard (NAAQS) for ground level ozone. This letter is intended to convey to
you our preliminary suggestions for how Connecticut could pursue expanded emission
reduction credit from your state's energy efficiency and renewable energy programs
within the SIP Connecticut will need to develop to meet this forthcoming standard.
Members of our respective staffs have met a number of times over the past several
months to discuss the various aspects of Connecticut's energy efficiency (EE) and
renewable energy (RE) legislation, and the merits of incorporating these programs into
your SIP. Through these discussions, it has become clear that establishing linkages
between Connecticut's EE/RE programs and your state's more established criteria
pollutant air quality management planning process is desirable, appropriate and
technically feasible. Therefore, we are providing you with our preliminary
recommendations for the technical support materials we think should be assembled to
document emission reductions from the fossil fuel fired electrical generating units in
Connecticut due to implementation of these programs. Although the focus of our
discussions has been on NOx emission reductions from EGUs and ozone SIPs, we
believe this methodology can be used to determine emission reductions from other
pollutants for SIPs as well.
In addition to our collaborative effort with Connecticut, you should also be aware that a
larger effort is underway within EPA nationally to provide clarifying guidance on the
incorporation of EE/RE measures in SIPs. As that develops, we will provide additional
feedback as necessary.
In 2004, EPA published the following two documents that .contain guidance for states
seeking to incorporate emission reductions from EE/RE programs into their SIPs:
• "Guidance on SIP Credits from Emission Reductions from Electric-Sector Energy
Efficiency and Renewable Energy Measures," and.
• "Incorporating Emerging and Voluntary Measures in a SIP."
Toll Free. 1.888-372-7341
Intefriet Address (URL) • http.//www.epa.gov/region1
Recycled/Recyclable • Printed wjth VegBiable Oil Based Inks on Recycled Paper (Minimum 30% Postconsumer)
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Pursuant to this guidance, energy efficiency and renewable energy programs were
generally considered emerging measures. The guidance stated that, "Voluntary and
emerging measures are limited to 6 percent of the total amount of emission reductions
required for the rate-of-progress, reasonable further progress, attainment, or maintenance
demonstration purposes." However, measures that can be shown to meet the federal
Clean Air Act's requirements for approvable SIP measures are not subject to this
limitation. Given Connecticut's considerable track record in implementing its
legislatively mandated EE and RE programs, we believe that your state can pursue SIP
credit from these programs as traditional measures such that they would not be subject to
the 6 percent limitation. The Enclosure offers suggestions for how to document the
emission reductions from these programs.
The incorporation of expanded emission reduction credit from Connecticut's energy
efficiency and renewable energy programs represents a new and important aspect of your
state's overall air quality management program, and we look forward to continuing to
work with your staff to bring this to fruition. It is clear that the formal lines of
communication that your agency has forged with your state's Department of Public
Utility Control have been beneficial to Connecticut in this endeavor, and we encourage
you to maintain this relationship in the future.
Please thank Rick Rodrigue, Paul Bodner, and Paul Farrell of you staff for the
considerable amount of time, energy, and leadership that they are providing to meet this
objective.
. Sincerely, /
David B. Conroy, Chief/
Air Programs Branch
cc: Rick Rodrigue, CT-DEP
Paul Bodner, CT-DEP
Paul Farrell, CT-DEP
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ENCLOSURE
Energy Efficiency (EE) and Renewable Energy (RE) in Connecticut's Ozone State
Implementation Plan (SIP)
In order to meet federal Clean Air Act (CAA) requirements, emission control measures
must be shown to be quantifiable, surplus, enforceable, and permanent. Each of these
criteria are discussed below along with our suggestions for the information that
Connecticut could gather to illustrate how its EE and RE programs meet these criteria.
Quantifiable: Pollution control measures submitted for inclusion within a SIP must be
quantifiable and amenable to verification over time so that the level of emission reduction
claimed can be tracked to see if it has actually been achieved.
Quantification of RE measures: Section 16-245(a) of the Connecticut General Statutes
established a renewable portfolio standard mandate that requires electricity suppliers
providing services to the state ensure that a portion of the electricity they make available
is generated by renewable resources. The portion of electricity that must come from
renewable resources is 14% for 2010, and this percent requirement increases each year
through 2020. Connecticut's legislation also requires a quarterly truing up and an annual
report that compels EGUs to confirm whether or not the RPS minimum percentage
requirement was met.
The Connecticut Department of Public Utility Control (DPUC), in implementing this
legislation, allows the renewable energy used to meet Connecticut's RPS requirements to
come from within the state, within the ISO-New England control area, or from an
adjacent power control area. This large geographic area from which Connecticut's
electricity suppliers may seek renewable energy resources complicates the analysis of the
NOx emissions that are avoided due to fossil fuel fired electrical generating units (EGUs)
running less as renewable suppliers become available. However, we believe sufficient
data exist that will allow Connecticut to gauge the impact of its RPS legislation on NOx
emissions from the production of electricity in the area.
One method Connecticut could explore is analysis of the location and NOx emitting
characteristics of the fossil fuel fired EGUs that have been able to reduce their output as
renewable energy resources were made available on past days. The output based NOx
emission rates for these units (e.g., units of Ibs. NOx per megawatt-hour) can then be
multiplied by the actual number of megawatt-hours of renewable electricity procured by
the state's electricity suppliers. This method can provide an approximation of the NOx
emissions avoided as a result of Connecticut's RPS program. Given the
interconnectedness of the region's electricity grid, and the existence of RPS programs in
neighboring states, it may be advantageous for Connecticut to approach ISO-New
England, the regional transmission organization (RTO) that oversees operation of New
England's electric power system, for assistance in performing this analysis.
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A second quantification approach could entail review of dispatch modeling prepared by
other entities such as ISO-New England, or if resources allow dispatch modeling tailored
to this specific project, to provide an indication of how the dispatch of EGUs in the future
will be affected by implementation of Connecticut's RPS program.
Quantification ofEE measures: Over the past several years much work has been
performed in the area of measurement and verification of the impact that energy
efficiency programs have on electricity demand, and linkage of these savings to
reductions in air pollutant emissions. For example, Connecticut's energy efficiency
program requires documentation of estimated energy savings from the state's ratepayer
funded EE program before and after energy efficiency programs are implemented.
More recently, ISO-New England took the significant step of allowing electricity savings
from energy efficiency, distributed generation, load management, and load response to be
bid into its forward capacity market (FCM). Market participants earn payments for the
qualifying resources successfully bid into the market. The inclusion of energy efficiency
in the FCM, which includes payments made by ISO-New England for the electricity
savings represented by these measures, provides additional evidence that the calculated
EE savings are real and also provides an additional accountability mechanism to ensure
that they occur. We suggest that Connecticut DEP explore use of the amount of
electricity savings bid in to the FCM by the state's electricity suppliers as a starting point
in determining the amount of NOx emissions avoided from the state's EE programs. This
could be supplemented with other readily available approximations of the electricity
savings from energy efficiency measures such as those documented in the ISO-New
England Regional System Plan, or in Connecticut's Integrated Resource Plan. As a side
note, we also encourage Connecticut DEP to monitor the distributed generation resources
in the state to ensure that these resources' participation in this market have a positive
impact on air quality.
In addition to the above, an understanding of how the regional photochemical urban
airshed modeling that will be used to support Connecticut's SIP treats state RPS
standards is imperative to avoid double counting the impact of these measures on future
year emissions from the EGU sector. EPA headquarters is currently looking into
technical analyses it may be able to perform that will help shed light on this issue. EPA
and CT-DEP should continue to work collaboratively on this effort as EPA's analysis is
developed and refined.
Surplus: Emission reductions are considered surplus as long as they aren't otherwise
used to meet attainment requirements in the SIP. Accordingly, Connecticut should
ensure that it has a good understanding of the assumptions, made in the electricity sector
future year baseline modeling done to support its next ozone SIP. One manner of
accounting for the NOx emission reductions from Connecticut's energy efficiency and
renewable portfolio standards programs would be to ensure that the future baseline
assumptions for the electricity sector in the state's modeled attainment demonstration
accurately reflect the impact of the state's programs. Alternatively, Connecticut could
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take steps to ensure that the future year baseline modeling does not incorporate the
impact from its EE/RE programs, and then determine their impact separately akin to how
traditional control measure reductions are determined.
EPA recently proposed a rule to address air pollution transported from one state to
another in the Eastern U.S. The proposed rule includes annual and ozone season NOx
budgets for Connecticut. If this rule is finalized as it was proposed, NOx emissions from
EGUs in Connecticut will be subject to emissions caps and will be allocated allowances
to use as a means of demonstrating compliance with their obligations under the rule
developed to implement this program. Connecticut should ensure that emission
reductions which accrue from the implementation of its energy efficiency programs do
not simply result in the freeing up of allowances that EGUs in the state can use or sell to
other entities in need of allowances to cover their air emitting activity. One method for
accomplishing that would be for the state to set aside allowances for EE/RE and then
retire them as these measures come to fruition, but there may be other viable approaches
that address this concern.
Enforceable: Emission reductions used to meet SIP RFP or attainment needs must be
enforceable against a source, and the state and EPA must have the ability to apply
penalties if deemed appropriated. Additionally, citizens must have access to the
emissions related information obtained from the sources, and must be able to file suits
against the source for violations.
In Connecticut's case, the state's renewable portfolio standards and energy efficiency
programs are mandatory programs created by specific state legislation that is primarily
implemented by the state's Department of Public Utility Control (DPUC). As we have
discussed over the past several months, submittal of these programs for incorporation into
the Connecticut State Implementation plan (SIP) will enable these programs to also
become federally enforceable. This federal enforceability is key to EPA being able to
provide expanded SIP credit for these programs. In the coming months, we envision that
Connecticut DEP and EPA staff will be able to work out the details of the specific
legislation and/or rules that should be submitted to EPA, as well as the development of
any formal agreements between CT-DEP and CT-DPUC regarding overview and
enforcement of these programs.
Permanent: The emission reductions expected from the state's EE/RE programs should
continue through the term for which the credit is granted unless replaced by another
measure, or the state demonstrates through a SIP revision that the measure is no longer
necessary. With regard to Connecticut's renewable ponfolio standards program, given
that the state has adopted legislation for this program and has an established track record
of oversight and enforcement for it, we believe the "permanent" criterion could be
addressed by the state committing in the SIP to continued implementation of the program.
With regard to Connecticut's energy efficiency programs, the permanence of some
programs, such as purchase programs for energy efficient equipment and products, would
need to be addressed in that there is no guarantee that the purchased equipment/products,
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take steps to ensure that the future year baseline modeling does not incorporate the
impact from its EE/RE programs, and then determine their impact separately akin to how
traditional control measure reductions are determined.
EPA recently proposed a rule to address air pollution transported from one state to
another in the Eastern U.S. The proposed rule includes annual and ozone season NOx
budgets for Connecticut. If this rule is finalized as it was proposed, NOx emissions from
EGUs in Connecticut will be subject to emissions caps and will be allocated allowances
to use as a means of demonstrating compliance with their obligations under the rule
developed to implement this program. Connecticut should ensure that emission
reductions which accrue from the implementation of its energy efficiency programs do
not simply result in the freeing up of allowances that EGUs in the state can use or sell to
other entities in need of allowances to cover their air emitting activity. One method for
accomplishing that would be for the state to set aside allowances for EE/RE and then
retire them as these measures come to fruition, but there may be other viable approaches
that address this concern.
Enforceable: Emission reductions used to meet SIP RFP or attainment needs must be
enforceable against a source, and the state and EPA must have the ability to apply
penalties if deemed appropriated. Additionally, citizens must have access to the
emissions related information obtained from the sources, and must be able to file suits
against the source for violations.
In Connecticut's case, the state's renewable portfolio standards and energy efficiency
programs are mandatory programs created by specific state legislation that is primarily
implemented by the state's Department of Public Utility Control (DPUC). As we have
discussed over the past several months, submittal of these programs for incorporation into
the Connecticut State Implementation plan (SIP) will enable these programs to also
become federally enforceable. This federal enforceability is key to EPA being able to
provide expanded SIP credit for these programs. In the coming months, we envision that
Connecticut DEP and EPA staff will be able to work out the details of the specific
legislation and/or rules that should be submitted to EPA, as well as the development of
any formal agreements between CT-DEP and CT-DPUC regarding overview and
enforcement of these programs.
Permanent: The emission reductions expected from the state's EE/RE programs should
continue through the term for which the credit is granted unless replaced by another
measure, or the state demonstrates through a SIP revision that the measure is no longer
necessary. With regard to Connecticut's renewable ponfolio standards program, given
that the state has adopted legislation for this program and has an established track record
of oversight and enforcement for it, we believe the "permanent" criterion could be
addressed by the state committing in the SIP to continued implementation of the program.
With regard to Connecticut's energy efficiency programs, the permanence of some
programs, such as purchase programs for energy efficient equipment and products, would
need to be addressed in that there is no guarantee that the purchased equipment/products,
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would be replaced at the end of their useful lives with comparably efficient equipment.
However, we believe the permanence of energy efficiency measures can be adequately
demonstrated and will continue to work with staff from Connecticut DEP to address it.
For example, from a broad perspective it seems reasonable to conclude that as
technological innovations in this industry continue, future equipment replacements will
likely take the form of comparable or improved equipment from an EE perspective.
Additionally, Connecticut's ten plus years of experience with funding and
implementation of its EE programs coupled with a SIP commitment to continue doing so
should help address the permanence criterion.
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ATTACHMENT B: STATE OF MARYLAND EE/RE POLICIES AND
PROGRAMS
EmPower Maryland
EmPOWER Maryland, enacted in 2007, requires utilities and the MEA to reduce per
capita peak demand and per capita electricity consumption in the state 15% by 2015. The
utilities are in the process of implementing residential, commercial, and industrial sector
programs to achieve the goal, and the MEA is implementing complementary programs,
including:
• EmPOWER Maryland State Agency Loan Program (SALP): a loan program for
state agencies to expand the use of energy performance contracts to make state
buildings more efficient;
• EmPOWER Maryland Empowering Finance Initiative: a loan program targeted at
helping residential consumers afford clean energy improvements
• EmPOWER Maryland Appliance and Lighting Rebate Programs: rebate programs
to incentivize the purchase of energy efficient appliances and light bulbs
• EmPOWER Maryland Industrial and Commercial Programs: various programs
targeting the industrial and commercial sector, including a loan program to help
finance the cost of energy efficiency projects in commercial and industrial
facilities and a program to provide Maryland industries access to informational
resources, workshops, technical support and energy assessment opportunities
• EmPOWER Maryland Residential Initiatives: various programs, including a grant
program in coordination with DHCD to conduct energy efficiency retrofits in
apartment units to reduce energy bills for low and moderate income families
These EmPOWER Maryland programs incorporate several of the other policies
recommended in the Maryland Climate Action Plan, including:
• RCI-2: Demand-Side Management Energy Efficiency Programs (captured by the
utilities' peak demand programs)
• RCI-3: Low Cost Loans for Energy Efficiency (captured by EmPower Maryland
SALP, EmPowering Finance and Industrial and Commercial Programs, described
above)
• RCI-7: More Stringent Appliance/Equipment Efficiency Standards (captured by
the EmPOWER Maryland Program Appliance and Lighting Rebate Programs,
described above. MEA also continues to advocate for legislation for stronger
standards.)
• RCI-11: Promotion and Incentives for Energy-Efficient Lighting (captured by the
EmPOWER Maryland Program Appliance and Lighting Rebate Programs)
Renewable Portfolio Standards
The goal of Maryland's RPS is for the state to obtain 20% of its electricity from
renewable resources by 2022, with intermediate targets of 7.5% by 2011 and 18% by
2020. To help Maryland reach these ambitious targets, MEA has focused on advocating
for policies to promote renewable energy and on running programs to stimulate the
renewable energy market.
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This past year, MEA advocated for legislation, passed by the Maryland General
Assembly, to amend the RPS to accelerate the solar RPS requirement in the near term
(2011-2017), resulting in more incentives for solar development. MEA also advocated for
legislation, passed by the Maryland General Assembly, to reauthorize the Maryland
renewable energy production tax credit, offering up to $2.5 million to eligible taxpayers
for the production of renewable electricity.
Through its residential renewables grant program, MEA awarded hundreds of grants
(ranging from $1,000-10,000) to homeowners and businesses to offset the cost of
installing wind, geothermal and solar PV systems. Demand has increased from 200
systems a year to 200 systems a month, even with significantly reduced incentives.
MEA also developed and implemented Project Sunburst, a program offering rebates of up
to $1,000 per KW of solar PV capacity installed on public buildings. The program will
incentivize the building of about 10 MW of solar in Maryland over the next year, more
than doubling current capacity in the state.
In addition, leading by example, MEA and DGS partnered with the University System to
launch the Generating Clean Horizons Initiative, which resulted in Power Purchase
Agreements with 3 new, utility scale renewable developments (65 MW of onshore wind
and 17 MW of thin film solar).
To promote all different types of renewables, MEA has a program manager dedicated to
biomass, biofuels and electric vehicles; a program manager dedicated to wind; and two
program managers dedicated to solar. These program managers focus on providing
support for the development and adoption of their respective technologies.
Finally, MEA administered the renewable energy production tax credit. Over the past
three years, more than $5 million in these credits have been claimed.
As demonstrated above, MEA's efforts to help the state reach the RPS goal incorporate
several of the other policies recommended in the Maryland Climate Action Plan,
including:
• ES-1: Promotion of Renewable Resources
• ES-2: Technology-focused Initiatives for Electricity Supply
• ES-5: Clean Distributed Generation
Regional Greenhouse Gas Initiative
The Regional Greenhouse Gas Initiative is a market-based carbon dioxide (CO2) cap and
trade program designed to reduce CO2 emissions from fossil fuel-fired power plants.
The program will be implemented by the participating states in January 2009. As there
are no technological controls available to reduce CO2 emissions, the program provides
for the sale of a determined quantity of CO2 allowances. Electric generators will be
required to purchase one CC>2 allowance for every ton of CC>2 emitted. The proceeds will
be used to fund energy efficiency programs, resulting in reduced CO2 emissions achieved
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through reduced electrical demand. These regulations will apply to fossil fuel-fired
generating units over 25 megawatts.
Regional reduction targets have been agreed upon as a two-phase regional emissions cap:
• 2009 through 2015: Hold regional emissions constant at current levels (about 150
million tons carbon dioxide), with a built-in review of the RGGI program no later
than 2015.
• 2015 - 2020: Reduce emissions by 10% below current levels
Maryland Clean Car Program
The Maryland Clean Cars Program required adoption of the California clean car program
for implementation beginning in MD in model year 2011. The implementing regulations
were originally adopted in 2007 and updated in both 2009 and 2010. The following
legislation passed in 2010 created incentives for the purchase of advanced technology
vehicles that are required by the Clean Car Program:
• HB 469 (SB281) Motor Vehicle Excise Tax - Tax Credit for Electric Vehicles -
provides credit against the motor vehicle excise tax for qualified vehicles.
• HB 674 (SB) High Occupancy Vehicle (HOV) Lanes - Use by Plug-In Vehicles
- allows qualified vehicles access to HOV lanes without the required minimum
occupancy.
The Maryland Clean Cars Act of 2007 required MDE to adopt regulations implementing
the California Clean Car Program. Maryland's implementing regulations adopted,
through incorporation by reference, the applicable California regulations. The California
program is a dynamic, changing program in which many of the relevant California
regulations are continuously updated. To retain the California program, Maryland must
remain consistent with their regulations, hence when California updates its regulations,
Maryland has to update our regulations. The Maryland regulations were updated in 2009
and 2010.
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ATTACHMENT C: STATE OF NEW MEXICO'S EE/RE POLICIES AND
PROGRAMS
New Mexico has three primary EE/RE policies. First, the state has a renewable portfolio
standard. In March 2007 the state added new requirements to the state's Renewable
Portfolio Standard, which formerly required utilities to get 10 percent of their electricity
needs by 2011 from renewables. Under the new law, regulated electric utilities must
have renewables meet 15 percent of their electricity needs by 2015 and 20 percent by
2020. Rural electric cooperatives must have renewable energy for 5 percent of their
electricity needs by 2015, increasing to 10 percent by 2020. Renewable energy can come
from new hydropower facilities, from fuel cells that are not fossil-fueled, and from
biomass, solar, wind, and geothermal resources.
Second, the state requires that lOU's must offer a voluntary renewable energy program to
their customers. In addition to and within the total portfolio percentage requirements,
utilities must design their public utility procurement plans to achieve a fully diversified
renewable energy portfolio no later than January 1, 2011, as follows:
A diversity requirement for lOU's as % of total RPS requirement:
• No less than 20% Wind
• No less than 20% Solar
• No less than 10% Other technologies
• No less than 7.5% Distributed Generation (2011-2014) and 3% Distributed
Generation by 2015
Third, enacted in 2005, New Mexico's Efficient Use of Energy Act (Section 62-17-1
NMSA 1978) requires that public utilities, distribution cooperative utilities and municipal
utilities include cost-effective energy efficiency and load management investments in
their energy resource portfolios and that any regulatory disincentives that may exist to
public utility investments in cost-effective energy efficiency and load management are
eliminated.
In 2008, the statute was amended to include a State Energy Efficiency Resource Standard
(EERS). Under this amendment public utilities providing electricity and natural gas
service to New Mexico customers shall, subject to commission approval, acquire all cost-
effective and achievable energy efficiency and load management resources available in
their service territories. This requirement, however, for public utilities providing
electricity service, shall not be less than savings of five percent of 2005 total retail
kilowatt-hour sales to New Mexico customers in calendar year 2014 and ten percent of
2005 total retail kilowatt-hour sales to New Mexico customers in 2020 as a result of
energy efficiency and load management programs implemented starting in 2007.
Energy Efficiency and Renewable Energy Bond Act (Sections 6-2ID-1 through 6-21D-
10 NMSA 1978)
Energy Efficiency and Renewable Energy Bond Act (Sections 6-2ID-1 through 6-21D-
10 NMSA 1978) authorizes up to $20 million in bonds to finance energy efficiency and
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renewable energy improvements in state government and school buildings. State agencies
or school districts may request an energy assessment from the New Mexico Energy,
Minerals and Natural Resources Department to identify specific energy saving measures.
Combined heat and power and waste heat recovery systems are eligible for funding.
Bonds are to be paid back by realized energy savings.
The state also has an array of financial to support these programs. The governor has also
signed a number of Executive Orders in support of energy efficiency and renewable
energy in state government and to create a climate action plan.
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