DRAFT DELIBERATIVE 11 April 2014



### 1 GHG Abatement Measures Technical Support Document Chapter 4: Cleaner Generation Sources

4.1. Introduction

Renewable energy is a cost-effective approach for reducing carbon dioxide (CO 2 

### ) emissions from fossil fuel-fired electric generating units (EGUs) thr ough the substitution of electricity generated from renewable resources, referred to in this document as renewable energy (RE). The portfolio of available RE sources encompasses a wide variety of technol ogies from utility-scale RE plants to smaller-scale distributed generation sited at residential, commercial, or industrial facilities. RE technologies are fueled by the sun, wind, water, organic matter, and othe r resources regularly replenished by physical and biological cycles. To integrate the rapidly increasing a nd evolving portfolio of RE into the Best System of Emission Reductions (BSER), the EPA has developed a best practices scenario that builds upon current state policy encouraging increased production of RE taking into account renewable potential in particular regions of the country.

Additionally, the EPA believes that the planne d expansion of new nuclear generating capacity and the preservation of existing nuclear generating capacity represent a cost-effective means to reduce
CO 2 

### emissions at fossil fuel-fired EGUs by provid ing carbon-free generation that can replace generation at those EGUs. Increasing the amount of nuclear capacity relative to the amount that would otherwise be available to operate is a technically viable a nd economically efficient approach for reducing CO 2 

### emissions from affected fossil fuel-fired EGUs.

This TSD is intended to support discussion of cleaner generation sources (RE and nuclear) as a component of BSER in the preamble (most extens ively in these sections: Building Blocks for Setting State Goals and Considerations, State Goals, State Plans, and Impacts of the Proposed Rule) and its representation within the RIA. Results from this chap ter feed into the technical support document (TSD) on state goal setting. Cleaner generation is also addr essed in TSDs on Survey of Existing State Actions, 

### State Plan Considerations
, 

### Projecting EGU CO 2 

### Emission Performance , and 

### Legal Memorandum

. 4.2. “Best Practices” RE Targets

To estimate the potential RE available for inclusion as part of BSER the EPA developed a “best practices” RE generation scenario. The best practices scenario is derived from state experience with policies that drive investment in RE and the genera tion that results from those efforts. The EPA focused on state-level RE policy for several reasons. Every state in the union is producing electricity from renewable resources, and some states have achieved significant levels of renewable generation, surpassingDRAFT DELIBERATIVE 11 April 2014



### 2 a quarter of in-state generation. State-level RE re quirements have been implemented in 29 states plus Washington, DC, representing all regions of the country. Eight states have voluntary goals. 1 

### These statelevel goals and requirements have b een developed and implemented with technical assistance from statelevel regulatory agencies and utility commissions su ch that they reflect expert assessments of RE technical and economic potential that can be cost-e ffectively developed for that state’s electricity

consumers. The best practices scenario focuses on RE require ments established through Renewable Portfolio Standards (RPS), which provide specific quantifiabl e RE generation requirements over time. The EPA used these RPS-mandated quantities as the basis for deri ving regional targets that could be applied to states as part of BSER, using the RPS-based targ ets as a reasonable benchmark of regionally costeffective RE generation which states could grow towa rds over time. While EPA’s best practices scenario is derived from RPS data, states may also consider a broad variety of other RE policies to increase generation, such as performance-based incentives, fi nancial assistance programs, regulatory changes to facilitate the development of renewable sources and their interconnection to the grid and “lead by example” strategies integrating RE generation into state properties. 2 

### Because the EPA did not quantify potential that could be tapped through any of those policy approaches, the agen cy believes that the RE targets derived from RPS mandates represent a conservative estimate of cost-effective generation that could actually be developed by states. While future RPS requirements will necessitate mo re RE generation and capacity beyond current levels, the EPA does not expect the anticipated rate of growth required to meet those requirements to exceed the historical rate of RE deployment. Fu ll compliance with current RPS requirements through 2035 would necessitate the deployment of approximate ly 3 to 5 GW of new renewable capacity per year through 2020 and 2 to 3 GW through 2035. Averag e deployment of RPS-supported renewable capacity from 2007-2012 has exceeded 6 GW per year. 3 

### In addition, recent improvements in RPS compliance rates
indicate to the EPA the reasonableness of current RPS growth trajectories. Weighted average compliance rates among all states have improved in each of th e past three reported years (2008 - 2011) from 92.1 percent to 95.2 percent despite a 40 percent increase in RPS obligations during this period. 4 

### As the

1 Map: Renewable Portfolio Standard Policies, www.dsireusa.org, March 2013, can be located at: http://www.dsireusa.org/summarymaps/. 2 See State Plan Considerations TSD for a discussion of how states can incorpor ate such RE policies into their state plans for this rule. 3 Barbose, Galen, “Renewables Portfolio Standards in th e United States: A Status Update,” Lawrence Berkeley National Lab, November 2013. 4 http://emp.lbl.gov/rps, retrieved March 2014. The RPS comp liance measure cited is inclusive of credit multipliers and banked RECs utilized for compliance, but excludes alternative compliance payments, borrowed RECs, deferredDRAFT DELIBERATIVE 11 April 2014



### 3 Lawrence Berkeley National Laboratory (LBNL) RP S Status Update found, in the period 1998-2012, 67% of all non-hydro U.S. RE capacity additions, totaling roughly 46,000 MW, was built in states with RPS requirements. 5



### This scenario provides an estimate of an ach ievable level of total RE generation within states. It does not represent an EPA forecast of bus iness-as-usual impacts of state policies or an EPA estimate of the full potential of RE availabl e to the power system; rather, it is intended to represent a feasible development scenario that enables reductions of CO 2 

### emissions from fossil fuel-fired EGUs in all states and that is ge nerally consistent with ongoing trends in RE development. The scenario uses a level of perf ormance that has already been demonstrated or required by policies of leading states, while consid ering each state’s unique existing level of RE performance and allowing appropriate time for each state to increase from their current level of performance to the identified be st practice level. In the c ontext of this rulemaking, RE “performance” and RE targets are measured as the share of total generation represented by nonhydro renewables, as expl ained further below.

The following steps were taken to establish the inputs for developmen t of the best practice scenario
for each state:
4.2.1 Determine current level of performance

4.2.2 Determine best practice level of performance

4.2.3 Determine start year for state efforts

4.2.4 Determine pace at which states improve from start year to best practice level of performance

4.2.5 Calculate RE targets for interim and final state goals

4.2.1 Determine current level of performance

obligations, and excess compliance. This estimate does not represent official compliance statistics, which vary in methodology by state. 5 Barbose, Galen, “Renewables Portfolio Standards in th e United States: A Status Update,” Lawrence Berkeley National Lab, November 2013. Slide 8.DRAFT DELIBERATIVE 11 April 2014



### 4 The type and extent of current RE capacity varies significantly across states, and is influenced by the renewable resources available, the economics of the power sector to date in different regions, and the state policies that affect renewable sources specifi cally and energy production generally. The extent of that generation has also changed rapidly in the p ast few years, and states with RE policies have significantly increased their renewable capacity. To ch aracterize the current level of RE use, we have used the most current state-level data on ge neration: 2012 net generation data by state. 6



### Definitions of qualifying RE vary across state RPS requirements. For the sake of comparing RPS requirements in order to derive RE targets for each region, the EPA adopted a broad interpretation of RE generation to include any non-fossil renewable fuel type, with the exception of generation from existing hydroelectric power facilities. Large existing hydroele ctric facilities provide a large percentage of RE generation in a few states, and inclusion of this gene ration in current and projected levels of performance would distort the best practices scenario by presuming future development potential of large hydroelectric capacity in other states. These types of facilities have not been the focus of most RPS policies, and many RPS policies specifically exclude their use in complian ce. No states are expected to significantly increase generation from existing large hydropower f acilities nor develop any new large facilities. 7 

### The analysis of potential informing regional RE targets does not e xplicitly account for the potential of building new smaller hydroelectric facilities as a source under RPS policies; however, generation from such facilities would not be excluded from compliance with a state’s goal under this rule.

The most recent 2012 performance data is shown in Table 4-1. Consistent with the design of a number RPS policies, RE “performance” is measured here 

### as the share of total generation represented by non-hydro RE.

Table 4-1. 2012 RE Performance by State

State Non-Hydro RE Generation Total Generation Performance Level Alabama 2,776,554 152,878,688 2% Alaska 39,958 6,946,419 1% Arizona 1,697,652 110,904,994 2% Arkansas 1,660,370 65,005,678 3% California 29,966,846 199,518,567 15% Colorado 6,192,082 52,556,701 12%

6 U.S. EIA state level data available at http://www.eia.gov/electricity/data/state/. 7 U.S. EIA, Annual Energy Outlook 2014, p. 121, available at http://www.eia.gov/forecasts/a rchive/aeo13/index.cfm..DRAFT DELIBERATIVE 11 April 2014



### 5 Connecticut 666,525 36,117,544 2% Delaware 131,051 8,633,694 2% District of Columbia 8 

### - 71,787 0% Florida 4,523,798 221,096,136 2% Georgia 3,278,536 122,306,364 3% Hawaii 924,815 10,469,269 9% Idaho 2,514,502 15,499,089 16% Illinois 8,372,660 197,565,363 4% Indiana 3,546,367 114,695,729 3% Iowa 14,183,424 56,675,404 25% Kansas 5,252,653 44,424,691 12% Kentucky 332,879 89,949,689 0% Louisiana 2,430,042 103,407,706 2% Maine 4,098,795 14,428,596 28% Maryland 898,152 37,809,744 2% Massachusetts 1,843,419 36,198,121 5% Michigan 3,785,439 108,166,078 3% Minnesota 9,453,871 52,193,624 18% Mississippi 1,509,190 54,584,295 3% Missouri 1,298,579 91,804,321 1% Montana 1,261,752 27,804,784 5% Nebraska 1,346,762 34,217,293 4% Nevada 2,968,630 35,173,263 8% New Hampshire 1,381,285 19,264,435 7% New Jersey 1,280,715 65,263,408 2% New Mexico 2,573,851 36,635,909 7% New York 5,192,427 135,768,251 4% North Carolina 2,703,919 116,681,763 2% North Dakota 5,280,052 36,125,159 15% Ohio 1,738,622 129,745,731 1% Oklahoma 8,520,724 77,896,588 11% Oregon 7,207,229 60,932,715 12% Pennsylvania 4,459,118 223,419,715 2% Rhode Island 101,895 8,309,036 1% South Carolina 2,143,473 96,755,682 2% South Dakota 2,914,666 12,034,206 24% Tennessee 836,458 77,724,264 1%

8 The District of Columbia has no utility-scale RE generatio n, but the District does have distributed RE resources contributing to the electrical grid. It can also be noted th at the non-RE generation reported closed in 2012, so the District of Columbia no longer has any utility-scale generation.DRAFT DELIBERATIVE 11 April 2014



### 6 Texas 34,016,697 429,812,510 8% Utah 1,099,724 39,402,961 3% Vermont 465,169 6,569,670 7% Virginia 2,358,444 70,739,235 3% Washington 8,214,350 116,835,474 7% West Virginia 1,296,563 73,413,405 2% Wisconsin 3,223,178 63,742,910 5% Wyoming 4,369,107 49,588,606 9%

4.2.2 Determine best practice level of performance

Achievable RE potential exists at significant and co mparable levels in all regions of the country. While varied regional characteristics (e.g., the extent of renewable resources available, cost of competing sources of power, and level of past RE developmen t) affect estimates of achievable potential, ongoing improvements in technologies and practices, and con tinually improving strategies for RE development are increasing the extent of economically utilized renewa ble resources across all regions of the United States. RE has been capturing a growing percentage of new capac ity additions in the past few years. In 2012, RE accounted for more than 56% of all new electrical cap acity installations in the U.S. – a major increase from 2004 when renewable installations captu red only 2% of new capacity additions. 9 

### The economics of the fastest growing RE technologies – on-shore wind and solar photovoltaics (PV) – are improving. In 2012, cumulative installed wind capacity increased by nearly 28% and cumulative installed solar PV capacity grew more than 83% from the previous year. 10 

### In the United States, installed wind electricity capacity increased more than 23 fold between 2000 and 2012. 11 

### Solar electricity generating capacity grew by a factor of over 21 between 2000 and 2012 and curr ently accounts for 0.3% of annual U.S. electricity generation. 12 

### The National Renewable Energy Laboratory (N REL) has also found that the continental U.S. has solar potential that exceeds high solar gene rating countries like Germany, which now has the capacity to generate over 6% of their electricity from solar. 13 

### Looking forward, the U.S. Department of Energy has found that 46 states would have substan tial wind development by 2030 under a scenario in

9 U.S. Department of Energy. 2012 Renewable Energy Data Book. DOE/GO-102013-4291.October 2013. p. 3. 10 U.S. Department of Energy. 2012 Renewable Energy Data Book. DOE/GO-102013-4291.October 2013. p. 18. 11 Ibid. p. 53. 12 Ibid. p. 63. 13 NREL. Photovoltaic Solar Resource: The United States, Spain and Germany. 2009. Available at: http://www.nrel.gov/gis/imag es/us_germany_spain/pvmap_usgermanyspai n%20poster-01.jpg. Also IEA. PVPS Snapshot of Global PV 1992-2013. Report IEA- PVPS T1-24:2014, March 31, 2014. http://www.ieapvps.org/fileadmin/dam/public/report/statistics/PVPS_report_-_A_Snapshot_of_Global_PV_-_1992-2013_- _final_3.pdf.DRAFT DELIBERATIVE 11 April 2014



### 7 which 20% of national generation is provided by wind . The distribution of that deployment is shown in Figure 4.1. 14



### The best practices scenario is also based upon an analysis of renewable portfolio standards, a policy that facilitates the quantification of RE targets. By only examining the impact of one type of policy, the analysis is inherently conservative, as many other policy options are also available to states in
addition to RPS.

Figure 4.1. 

### DOE Projected Installed Wind Capacity by State under 20% National Generation
Scenario

4.2.2.1. Quantification of Effective RE Levels from State-Level RPS Requirements

In order to apply the various RPS policies to the development of a best practice level of performance, the EPA used publicly-available qua ntitative information about mandatory state RPS requirements from the Database for State Incentiv es for Renewables and Efficiency (DSIRE). 15 

### This

14 U.S. Department of Energy. 20% Wind Energy by 2030: Increasing Wind Energy’s Contribution to U.S. Electricity Supply – Executive Summary. December 2008. http://www.nrel.gov/ docs/fy09osti/42864.pdf. 15 Database of State Incentives for Renewables & E fficiency (DSIRE) is a very comprehensive source of information on incentives and policies that support renewabl es and energy efficiency in the United States. DSIRE is currently operated by the N.C. Solar Ce nter at N.C. State University, with support from the Interstate Renewable Energy Council, Inc. DSIRE is funded by the U.S. Department of Energy. http://www.dsireusa.org/.DRAFT DELIBERATIVE 11 April 2014



### 8 information enabled the EPA to determine the effectiv e RE levels in 2020 for states with mandatory RPS requirements. 16



### DSIRE provides regularly-updated RPS Data Spreadsheets that detail state RPS requirements by year, resources, and other key component parts. 17 

### The RPS compliance schedules are broken down into the specific annual percentages requirements for th e years 2000 to 2030. Many states have multiple compliance requirements, including the main per centage requirements for eligible resources and additional resource-specific percentage requirements that states are increasingly using to promote the development of a particular set of resources or t echnologies (e.g., solar PV). DSIRE called each of these sets of resource requirements “tiers” and applied a sta ndardized approach to them, “in order to compare RPS policies on equal footing.” 18 

### The benefit of this approach is that state resource requirements become additive and facilitate a process of selection and excl usion. The EPA added together each state’s tiers, as standardized by DSIRE, to determine states’ effectiv e RE levels for 2020, but excluded tiers, other than main tiers, that include energy efficiency or any fossil fuel.

In addition, six states have established more th an one set of RPS requirements for in-state utilities, including “secondary” and “tertiary” RPS requ irements for smaller utilities, municipal utilities, or cooperative utilities. The EPA only included the prim ary RPS requirements to simplify the analysis of primary and secondary RPS requirements in determin ing states’ effective RE levels for 2020. By only considering primary requirements, there is additi onal inherent conservatism in the RPS estimates, as additional state-level RPS obligations are not included in the calculated targets.

16 EPA did not include targets that were capacity-based. 17 DSIRE. RPS Data Spreadsheet. April 2013 version. http://www.dsireusa.org/rpsdata/index.cfm. 18 DSIRE. DSIRE RPS Field Definitions. April 2011. http://www.dsireusa.org/rpsdata/RPSFiel dDefinitionsApril2011.pdf. p. 1.DRAFT DELIBERATIVE 11 April 2014



### 9 Figure 4.2 RPS Data Structure 19



### The RPS compliance schedules in six states impl ement maximum requirements prior to 2020; their effective RE levels for 2020 are set to those maximum levels. In fact, most states maintain their percentage requirements indefinitely.

TABLE 4.2 . Effective RE Levels Derived from RPS Requirements

RPS States Primary Target Target Year 2020 Effective RE Levels Exclusions

AZ 15% 2025 10% CA 33% 2020 33% CO 30% 2020 30% Secondary RPS requirement CT 23% 2020 23% Class 3 includes non-RE DC 20% 2023 20% DE 25% 2027 19% HI 40% 2030 25% IL 25% 2025 16% Secondary RPS requirement KS 20% 2020 20%

19 DSIRE. RPS Data Spread sheet. April 2013 version.DRAFT DELIBERATIVE 11 April 2014



### 10 MA 33% 2030 22% MD 20% 2022 18% ME 40% 2017 40% MI 10% 2015 10% MN 30% 2020 30% Secondary RPS requirement MO 15% 2021 10% MT 15% 2015 15% NC 13% 2021 10% Secondary RPS requirement NH 25% 2025 20% NJ 24% 2021 22% NM 20% 2020 20% Secondary RPS requirement NV 25% 2025 22% NY 29% 2015 29% OH 13% 2024 9%

OR 25% 2025 20% Secondary & tertiary RPS requirements PA 8% 2021 8% Class 2 includes non-RE RI 16% 2019 16% WA 15% 2020 15% WI 10% 2015 10%

4.2.2.2. Development of Regional RE Generation Targets from State-level Effective RE Levels

To take into account the varied availability of different renewable resources across regions of the United States, the EPA uses the state-level effective RE levels derived from R PS requirements to quantify regional RE targets consistent with states’ best prac tice in RE development. This methodology helps us to quantify RE potential in states which do not have an RPS policy from which the renewable resource potential can be inferred. Specifically, the scenario es timates each region’s RE potential by assuming all states in each region can achieve by 2030 the average of the 2020 requirements of RPS states in that region.

The regions assigned to states to quantify their RE generation target are based upon North American Electric Reliability Corporation (NERC) regions and Regional Transmission Organizations (RTOs) and are the same as the regions used in th e modeling of the “regional” compliance scenarios as outlined in the proposal RIA (see Figure 4-3). 20 

### States within each region exhibit similar profiles of RE potential or have similar levels of renewable resource s. The regional similarities can be inferred from the

20 For more information on the structure of these regions, please refer to the Regulatory Impact An alysis Chapter 3.DRAFT DELIBERATIVE 11 April 2014



### 11 state-level technical potential reported in an NREL GIS-based analysis. 21 

### The results show clear trends for the regions used to create the best practices scenario, with portfolios of particular technologies showing clear dominance in specific regions. North Central and South Central regions have strong on-shore wind resource potential. The East Central and Southeast regions show moderate to strong resources in both biopower and rooftop PV potential. The West has uni que potential in geothermal (hydrothermal) power and concentrating solar power. The Northeast h as strong resources in off-shore wind and moderate biopower and solar resources available. It should be noted that high technical potential in a particular renewable resource is not necessarily needed to reach th e generation levels called fo r in this proposal. For example, Maine produced 28% of its electricity generation in 2012 from biopower and onshore wind, while it is estimated in this report to have moderate technical potential for biopower and low levels of onshore wind capacity.

Figure 4.3. Regions for Development of Best Practices RPS Scenario

21 NREL. U.S. Renewable Energy Technical Potentials: A GIS-Based Analysis. NREL/TP-A20-51946. July 2012. http://www.nrel.gov/do cs/fy12osti/51946.pdf.DRAFT DELIBERATIVE 11 April 2014



### 12 Table 4.3. List of States Included in Regions for Development of RE Best Practices Scenario 22



### Region States

East Central Delaware, District of Columbia , Maryland, New Jersey, Ohio, Pennsylvania,
Virginia, West Virginia
North Central Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri, North Dakota, South
Dakota, Wisconsin

Northeast Connecticut, Maine, Massachu setts, New Hampshire, New York, Rhode
Island, Vermont

South Central Arkansas, Kansas, Louisiana, Nebraska, Oklahoma, Texas
Southeast Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South
Carolina, Tennessee

West Arizona, California, Colorado, Id aho, Montana, Nevada, New Mexico,
Oregon, Utah, Washington, Wyoming

The EPA compiled the state-level effective RE le vels derived above, organized them by region, and determined an average percent generation target for that region. This average did not include any values for states in which there is no binding RPS requirement. This average regional RE generation target offers a basis for the determination of state- level RE targets for informing state goals, as described below. Given their unique locations, Alaska and Hawa ii are not grouped with other states into these regions. As a conservative approach to estimating cost-effective RE generation potential in Alaska and Hawaii, the EPA developed RE generation targets for each of those states based on the lowest values for the six regions evaluated here, equivalent to the regional target for the Southeast region.

22 Alaska and Hawaii are not grouped with other states into regions.DRAFT DELIBERATIVE 11 April 2014



### 13 Table 4.4. Regional RE Generation Targets

Region Regional RE Generation Targets
Alaska 10%
East Central 16%
Hawaii 10%
Northeast 25% 

### North Central 15% 

### South Central 20%
South 

### east 10%
West 21%

4.2.3 Determine start year for state efforts

The best practice scenario assumes that RE ge neration will begin increasing in 2017, the year following the initial state plan submission deadline 23 

### , and continues through 2029, by which time the EPA assumes the regions can achieve the identified regional RE target level of performance. The EPA has set each state’s level of performance prior to the start year of the scenario (2017) to be equal to its current level of performance (as shown a bove using 2012 generation data). This approach assumes neither improvement nor decline in performance between 2012 and 2017.

4.2.4 Determine pace at which states improve from st art year to best practice level of performance

In order to account for the time needed to plan and construct the required additional amounts of renewable capacity, the best practices scenario assum es an increasing trend over time of annual levels of RE generation that can carry the start year perfo rmance level of each region (in 2017, assumed to be equivalent to its 2012 observed perform ance level) to that region’s RE generation target by 2029. This 2017-2029 trend yields an annual growth factor th at is unique to each region and based upon each region’s current renewable ge neration level and its RE targ et level identified above.

23 See Preamble Section 8.E – Process for State Plan Submittal and Review for further discussion of timing requirements for state plan submittals.DRAFT DELIBERATIVE 11 April 2014



### 14 To derive the annual growth factor, the EPA de termined the amount of additional renewable generation (in megawatt-hours) that would be required beyond each region’s historic (2012) generation to reach that region’s RE target. The EPA then determ ined the constant rate at which each region would need to increase its generation each year to reach the regional RPS target, if these rates are applied in the period 2017-2029. The constant rate of annual RE generation increase calculated from this approach is called the growth factor in this context. Due to thei r unique location, the EPA used a different method to calculate growth factors for Alaska and Hawaii, cal culating an annual growth factor based on the
difference between both states’ historical 2005 and 20 12 RE generation. Growth factors for each region are provided in Table 4.5.

Table 4.5. Regional Annual RE Growth Factors

Region Growth Factor 

### Alaska 8% East Central 17% Hawaii 8% North Central 6% Northeast 10% South Central 8% Southeast 13% West 6%

Then, for all states in a given region, that regi on’s annual growth factor was applied to each state’s historic (2012) RE generation level to calculate a new level of RE generation for that state in the initial year (2017). This calculation is then repeated for each year in the 2017-2029 time period. If, as the growth factor is applied annually, a state reaches an RE generation level that equals or exceeds the regional RE percent generation target, their RE gene ration target is made equal to the RE percent generation target and is no longer gr own over the remainder of the time period. If a state’s RE generation in 2012 has already exceeded the regional RE target, their annual RE generation levels are held to the regional RE target for all years in the 2017-2029 time pe riod. For all other states, the annual growth factor is applied through 2029. These annua l RE generation estimates represent the realization of the best practice scenario for each state. These RE generation levels are provided in absolute and percentage (share of total generation) term s in Table 4.6 and Table 4.7.

This approach imposes the same regional RE target in percentage (share of total generation) terms to all states in a given region; therefore, the abso lute megawatt-hour target will be smaller for statesDRAFT DELIBERATIVE 11 April 2014



### 15 starting with a lower absolute amount of RE genera tion and larger for a state starting with a higher absolute amount of RE generation.

This approach applies the calculated growth f actors and regional RE targets to state-level generation, whereas the state-level RPS requirement s upon which they are based are not necessarily applied in practice to generation that is produced with in the relevant state. However, the EPA notes that state-level RPS policies are often established with th e aim of developing in-sta te renewables generation. 24 

### This intention is evident in RPS policies that in clude minimum requirements for specific types of renewable resources whose development is desired in that state. Regional analysis by NREL has also shown that many states in the west are satisfy ing RPS requirements with in-state generation. 25 

### Furthermore, the regional RE target is not applied di rectly as an immediate requirement of each state but is instead used to calculate a regional growth factor that is then applied to each state’s pre-existing RE generation, such that historic RE performance acts as a limiting factor on the extent to which a state is assumed to reach the regional target. Over the pr ogram period, several states do not reach the RE percentage target in the best practices scenario, su ch as Kentucky in the Southeast and Nevada in the West. Thus, this approach is designed to respect ea ch state’s ability to improve toward the RE targets developed above.

Table 4.6. State Best Practice RE Ge neration Levels (Thousand Megawatt-hours)

State Historic RE Best Practice RE Generatio n Levels (thousand MWh)

2012 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029

AK 40 43 47 50 54 58 63 68 73 79 85 92 100 107

AL 2,777 3,150 3,573 4,053 4,597 5,214 5,915 6,709 7,611 8,633 9,793 11,108 12,600 14,293

AR 1,660 1,799 1,949 2,112 2,288 2,479 2,686 2,911 3,154 3,417 3,702 4,011 4,346 4,709

AZ 1,698 1,807 1,924 2,048 2,181 2,322 2,472 2,632 2,802 2,983 3,175 3,381 3,599 3,832

CA 29,967 31,903 33,965 36,160 38,497 40,984 41,151 41,151 41,151 41,151 41,151 41,151 41,151 41,151

CO 6,192 6,592 7,018 7,472 7,955 8,469 9,016 9,598 10,219 10,840 10,840 10,840 10,840 10,840

CT 667 750 845 951 1,071 1,206 1,358 1,529 1,721 1,938 2,182 2,457 2,766 3,114

DE 131 154 180 211 248 291 341 399 468 549 644 755 886 1,038 FL

24 Wiser, Ryan H., and Galen L. Barbose. 2008. Renewable Portfolio Standards in the United States: A Status Report with Data Through 2007 . LBNL-154E. Berkeley, CA : Lawrence Berkeley National Laboratory, p. 7. 25 Hurlbut, David, Joyce McLaren, and Rachel Gelman. Beyond Renewable Portfolio Standards: An Assessment of Regional Supply and Demand Conditions Affecting the Futu re of Renewable Energy in the West. NREL/TP-6A20- 57830. Golden, CO: NREL, August 2013.DRAFT DELIBERATIVE 11 April 2014



### 16 4,524 5,131 5,821 6,603 7,490 8,496 9,637 10,931 12,400 14,066 15,955 18,098 20,529 22,110DRAFT DELIBERATIVE 11 April 2014



### 17 GA 3,279 3,719 4,219 4,785 5,428 6,157 6,984 7,922 8,987 10,194 11,563 12,231 12,231 12,231

HI 925 998 1,047 1,047 1,047 1,047 1,047 1,047 1,047 1,047 1,047 1,047 1,047 1,047

IA 14,183 8,566 8,566 8,566 8,566 8,566 8,566 8,566 8,566 8,566 8,566 8,566 8,566 8,566

ID 2,515 2,677 2,850 3,034 3,197 3,197 3,197 3,197 3,197 3,197 3,197 3,197 3,197 3,197

IL 8,373 8,873 9,404 9,967 10,563 11,195 11,864 12,574 13,326 14,123 14,968 15,863 16,812 17,818

IN 3,546 3,758 3,983 4,222 4,474 4,742 5,025 5,326 5,645 5,982 6,340 6,719 7,121 7,547

KS 5,253 5,691 6,166 6,681 7,239 7,843 8,498 8,885 8,885 8,885 8,885 8,885 8,885 8,885

KY 333 378 428 486 551 625 709 804 912 1,035 1,174 1,332 1,511 1,714

LA 2,430 2,633 2,853 3,091 3,349 3,629 3,931 4,260 4,615 5,001 5,418 5,870 6,361 6,892

MA 1,843 2,076 2,337 2,631 2,962 3,335 3,755 4,228 4,761 5,360 6,035 6,795 7,650 8,613

MD 898 1,053 1,235 1,448 1,698 1,991 2,335 2,738 3,210 3,764 4,414 5,176 5,982 5,982

ME 4,099 3,612 3,612 3,612 3,612 3,612 3,612 3,612 3,612 3,612 3,612 3,612 3,612 3,612

MI 3,785 4,012 4,252 4,506 4,776 5,061 5,364 5,685 6,025 6,385 6,767 7,172 7,601 8,056

MN 9,454 7,889 7,889 7,889 7,889 7,889 7,889 7,889 7,889 7,889 7,889 7,889 7,889 7,889

MO 1,299 1,376 1,459 1,546 1,638 1,736 1,840 1,950 2,067 2,190 2,322 2,460 2,608 2,764

MS 1,509 1,712 1,942 2,203 2,499 2,834 3,215 3,647 4,137 4,692 5,323 5,458 5,458 5,458

MT 1,262 1,343 1,430 1,523 1,621 1,726 1,837 1,956 2,082 2,217 2,360 2,513 2,675 2,848

NC 2,704 3,067 3,479 3,946 4,477 5,078 5,760 6,534 7,412 8,407 9,536 10,817 11,668 11,668

ND 5,280 5,460 5,460 5,460 5,460 5,460 5,460 5,460 5,460 5,460 5,460 5,460 5,460 5,460

NE 1,347 1,459 1,581 1,713 1,856 2,011 2,179 2,361 2,558 2,771 3,003 3,254 3,525 3,819

NH 1,381 1,555 1,751 1,971 2,220 2,499 2,814 3,168 3,567 4,016 4,522 4,822 4,822 4,822

NJ 1,281 1,502 1,761 2,065 2,421 2,839 3,329 3,904 4,577 5,367 6,294 7,380 8,654 10,147

NM 2,574 2,740 2,917 3,106 3,306 3,520 3,748 3,990 4,248 4,522 4,814 5,125 5,457 5,809

NV 2,969 3,160 3,365 3,582 3,814 4,060 4,322 4,602 4,899 5,216 5,553 5,912 6,294 6,700

NY 5,192 5,846 6,582 7,411 8,344 9,395 10,578 11,910 13,409 15,098 16,999 19,139 21,549 24,262

OH 1,739 2,039 2,391 2,803 3,287 3,854 4,519 5,299 6,214 7,287 8,544 10,019 11,748 13,776

OK 8,521 9,232 10,003 10,838 11,743 12,723 13,785 14,936 15,579 15,579 15,579 15,579 15,579 15,579

OR 7,207 7,673 8,169 8,697 9,259 9,857 10,494 11,172 11,894 12,567 12,567 12,567 12,567 12,567

PA 4,459 5,229 6,131 7,189 8,430 9,885 11,591 13,592 15,938 18,688 21,914 25,696 30,131 35,331

RI 102 115 129 145 164 184 208 234 263 296 334 376 423 476

SC 2,143 2,431 2,758 3,128 3,549 4,025 4,566 5,180 5,875 6,665 7,560 8,575 9,676 9,676

SD 2,915 1,819 1,819 1,819 1,819 1,819 1,819 1,819 1,819 1,819 1,819 1,819 1,819 1,819

TN 836 949 1,076 1,221 1,385 1,571 1,782 2,021 2,293 2,601 2,950 3,346 3,796 4,306

TX 34,017 36,857 39,934 43,268 46,880 50,794 55,034 59,629 64,607 70,001 75,845 82,177 85,963 85,963DRAFT DELIBERATIVE 11 April 2014



### 18 UT 1,100 1,171 1,246 1,327 1,413 1,504 1,601 1,705 1,815 1,932 2,057 2,190 2,331 2,482

VA 2,358 2,765 3,243 3,802 4,459 5,228 6,131 7,189 8,429 9,884 11,192 11,192 11,192 11,192

VT 465 524 590 664 748 842 948 1,067 1,201 1,353 1,523 1,645 1,645 1,645

WA 8,214 8,745 9,310 9,912 10,552 11,234 11,960 12,733 13,556 14,432 15,365 16,358 17,415 18,540

WI 3,223 3,416 3,620 3,837 4,066 4,310 4,567 4,841 5,130 5,437 5,762 6,107 6,472 6,859

WV 1,297 1,520 1,783 2,090 2,451 2,874 3,370 3,952 4,634 5,434 6,372 7,471 8,761 10,273

WY 4,369 4,651 4,952 5,272 5,613 5,975 6,362 6,773 7,210 7,676 8,172 8,700 9,263 9,861



### Table 4.7. State Best Practice RE Gene ration Levels (% of Total Generation)

State Historic RE Best Practice RE Generation Levels

2012 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029

AK 0.6% 0.6% 0.7% 0.7% 0.8% 0.8% 0.9% 1.0% 1.1% 1.1% 1.2% 1.3% 1.4% 1.5%
AL 2% 2.1% 2.3% 2.7% 3.0% 3.4% 3.9% 4. 4% 5.0% 5.6% 6.4% 7.3% 8.2% 9.3%
AR 3% 2.8% 3.0% 3.2% 3.5% 3.8% 4.1% 4. 5% 4.9% 5.3% 5.7% 6.2% 6.7% 7.2%
AZ 2% 1.6% 1.7% 1.8% 2.0% 2.1% 2.2% 2. 4% 2.5% 2.7% 2.9% 3.0% 3.2% 3.5% CA 15% 16.0% 17.0% 18.1% 19.3% 20.5% 20.6% 20.6% 20.6% 20.6% 20.6% 20.6% 20.6% 20.6% CO 12% 12.5% 13.4% 14.2% 15.1% 16.1% 17.2% 18.3% 19.4% 20.6% 20.6% 20.6% 20.6% 20.6% CT 2% 2.1% 2.3% 2.6% 3.0% 3.3% 3.8% 4. 2% 4.8% 5.4% 6.0% 6.8% 7.7% 8.6%
DE 2% 1.8% 2.1% 2.4% 2.9% 3.4% 3.9% 4. 6% 5.4% 6.4% 7.5% 8.7% 10.3% 12.0%
FL 2% 2.3% 2.6% 3.0% 3.4% 3.8% 4.4% 4. 9% 5.6% 6.4% 7.2% 8.2% 9.3% 10.0% GA 3% 3.0% 3.4% 3.9% 4.4% 5.0% 5.7% 6.5% 7.3% 8.3% 9.5% 10.0% 10.0% 10.0%
HI 9% 9.5% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0%
IA 25% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1%
ID 16% 17.3% 18.4% 19.6% 20.6% 20.6% 20.6% 20.6% 20.6% 20.6% 20.6% 20.6% 20.6% 20.6%
IL 4% 4.5% 4.8% 5.0% 5.3% 5.7% 6.0% 6. 4% 6.7% 7.1% 7.6% 8.0% 8.5% 9.0%
IN 3% 3.3% 3.5% 3.7% 3.9% 4.1% 4.4% 4. 6% 4.9% 5.2% 5.5% 5.9% 6.2% 6.6% KS 12% 12.8% 13.9% 15.0% 16.3% 17.7% 19.1% 20.0% 20.0% 20.0% 20.0% 20.0% 20.0% 20.0%
KY 0% 0.4% 0.5% 0.5% 0.6% 0.7% 0.8% 0. 9% 1.0% 1.2% 1.3% 1.5% 1.7% 1.9%
LA 2% 2.5% 2.8% 3.0% 3.2% 3.5% 3.8% 4. 1% 4.5% 4.8% 5.2% 5.7% 6.2% 6.7%
MA 5% 5.7% 6.5% 7.3% 8.2% 9.2% 10.4% 11.7% 13.2% 14.8% 16.7% 18.8% 21.1% 23.8%
MD 2% 2.8% 3.3% 3.8% 4.5% 5.3% 6.2% 7.2% 8.5% 10.0% 11.7% 13.7% 15.8% 15.8%
ME 28% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0% 25.0%
MI 3% 3.7% 3.9% 4.2% 4.4% 4.7% 5.0% 5. 3% 5.6% 5.9% 6.3% 6.6% 7.0% 7.4%
MN 18% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% MO 1% 1.5% 1.6% 1.7% 1.8% 1.9% 2.0% 2. 1% 2.3% 2.4% 2.5% 2.7% 2.8% 3.0% MS 3% 3.1% 3.6% 4.0% 4.6% 5.2% 5.9% 6.7% 7.6% 8.6% 9.8% 10.0% 10.0% 10.0%
MT 5% 4.8% 5.1% 5.5% 5.8% 6.2% 6.6% 7. 0% 7.5% 8.0% 8.5% 9.0% 9.6% 10.2% NC 2% 2.6% 3.0% 3.4% 3.8% 4.4% 4.9% 5. 6% 6.4% 7.2% 8.2% 9.3% 10.0% 10.0%DRAFT DELIBERATIVE 11 April 2014



### 19 ND 15% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1%
NE 4% 4.3% 4.6% 5.0% 5.4% 5.9% 6.4% 6. 9% 7.5% 8.1% 8.8% 9.5% 10.3% 11.2%
NH 7% 8.1% 9.1% 10.2% 11.5% 13.0% 14.6% 16.4% 18.5% 20.8% 23.5% 25.0% 25.0% 25.0%
NJ 2% 2.3% 2.7% 3.2% 3.7% 4.4% 5.1% 6.0% 7.0% 8.2% 9.6% 11.3% 13.3% 15.5%
NM 7% 7.5% 8.0% 8.5% 9.0% 9.6% 10.2% 10.9% 11.6% 12.3% 13.1% 14.0% 14.9% 15.9%
NV 8% 9.0% 9.6% 10.2% 10.8% 11.5% 12.3% 13.1% 13.9% 14.8% 15.8% 16.8% 17.9% 19.0%
NY 4% 4.3% 4.8% 5.5% 6.1% 6.9% 7.8% 8.8% 9.9% 11.1% 12.5% 14.1% 15.9% 17.9% OH 1% 1.6% 1.8% 2.2% 2.5% 3.0% 3.5% 4. 1% 4.8% 5.6% 6.6% 7.7% 9.1% 10.6% OK 11% 11.9% 12.8% 13.9% 15.1% 16.3% 17.7% 19.2% 20.0% 20.0% 20.0% 20.0% 20.0% 20.0% OR 12% 12.6% 13.4% 14.3% 15.2% 16.2% 17.2% 18.3% 19.5% 20.6% 20.6% 20.6% 20.6% 20.6%
PA 2% 2.3% 2.7% 3.2% 3.8% 4.4% 5.2% 6.1% 7.1% 8.4% 9.8% 11.5% 13.5% 15.8%
RI 1% 1.4% 1.6% 1.8% 2.0% 2.2% 2.5% 2. 8% 3.2% 3.6% 4.0% 4.5% 5.1% 5.7% SC 2% 2.5% 2.9% 3.2% 3.7% 4.2% 4.7% 5. 4% 6.1% 6.9% 7.8% 8.9% 10.0% 10.0% SD 24% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1% 15.1%
TN 1% 1.2% 1.4% 1.6% 1.8% 2.0% 2.3% 2. 6% 2.9% 3.3% 3.8% 4.3% 4.9% 5.5%
TX 8% 8.6% 9.3% 10.1% 10.9% 11.8% 12.8% 13.9% 15.0% 16.3% 17.6% 19.1% 20.0% 20.0%
UT 3% 3.0% 3.2% 3.4% 3.6% 3.8% 4.1% 4. 3% 4.6% 4.9% 5.2% 5.6% 5.9% 6.3% VA 3% 3.9% 4.6% 5.4% 6.3% 7.4% 8.7% 10.2% 11.9% 14.0% 15.8% 15.8% 15.8% 15.8%
VT 7% 8.0% 9.0% 10.1% 11.4% 12.8% 14.4% 16.2% 18.3% 20.6% 23.2% 25.0% 25.0% 25.0% WA 7% 7.5% 8.0% 8.5% 9.0% 9.6% 10.2% 10.9% 11.6% 12.4% 13.2% 14.0% 14.9% 15.9%
WI 5% 5.4% 5.7% 6.0% 6.4% 6.8% 7.2% 7. 6% 8.0% 8.5% 9.0% 9.6% 10.2% 10.8%
WV 2% 2.1% 2.4% 2.8% 3.3% 3.9% 4.6% 5.4% 6.3% 7.4% 8.7% 10.2% 11.9% 14.0%
WY 9% 9.4% 10.0% 10.6% 11.3% 12.0% 12.8% 13.7% 14.5% 15.5% 16.5% 17.5% 18.7% 19.9%



### 4.2.5. Calculate RE targets for interim and final state goals

The agency then translated the annual RE best practice performance levels for each state into state-level interim and final RE targets for informing this rule’s quantification of state goals. Separate interim and final RE targets were calculated for the proposed state goals and the alternate state goals in this proposed rulemaking. For the proposed state goals , the interim RE target for each state was calculated as the average of that state’s RE best practice pe rformance level from 2020-2029, and the final target is equivalent to that state’s RE best practice performance level in the year 2029. For the alternate state goals, the interim RE target for each state was calculated as the average of that state’s RE best practice performance level from 2020-2024, and the final target is equivalent to that state’s RE best practice performance level in the year 2024. State-level RE ta rgets, expressed in absolute (megawatt-hour) terms and as a percentage level of each state’s RE generati on as a share of its total generation, along with 2012 RE levels for each state, are provided in Table 4.8. Fo r an explanation of how these state-level RE targets informed the calculations of state goals in this rule, please refer to the Goal Computation TSD.DRAFT DELIBERATIVE 11 April 2014



### 20 Table 4.8. Proposed and Alternate State Goals for RE Generation as a Percenta ge of Total Generation,
with 2012 Historical RE Generation

State 2012 Proposed Goals Alternate Goals

Interim Level Final Level Interim Level Final Level

Alabama 2% 6% 9% 4% 5%

Alaska 1% 1% 2% 1% 1%



### Arizona 2% 3% 3% 2% 3%

Arkansas 3% 5% 7% 4% 5%

California 15% 20% 21% 20% 21%

Colorado 12% 19% 21% 17% 19%

Connecticut 2% 5% 9% 4% 5%

Delaware 2% 7% 12% 4% 5%

Florida 2% 6% 10% 4% 6%
Georgia 3% 8% 10% 6% 7%

Hawaii 9% 10% 10% 10% 10%



### Idaho 16% 21% 21% 21% 21%

Illinois 4% 7% 9% 6% 7%

Indiana 3% 5% 7% 4% 5%

Iowa 25% 15% 15% 15% 15%

Kansas 12% 19% 20% 19% 20%
Kentucky 0% 1% 2% 1% 1%

Louisiana 2% 5% 7% 4% 4%

Maine 28% 25% 25% 25% 25%
Maryland 2% 10% 16% 6% 8%

Massachusetts 5% 15% 24% 11% 13%DRAFT DELIBERATIVE 11 April 2014



### 21 State 2012 Proposed Goals Alternate Goals

Interim Level Final Level Interim Level Final Level
Michigan 3% 6% 7% 5% 6%

Minnesota 18% 15% 15% 15% 15%
Mississippi 3% 8% 10% 6% 8%

Missouri 1% 2% 3% 2% 2%

Montana 5% 8% 10% 7% 7%

Nebraska 4% 8% 11% 6% 7%

Nevada 8% 15% 19% 12% 14%
New Hampshire 7% 19% 25% 15% 19%
New Jersey 2% 8% 16% 5% 7%

New Mexico 7% 12% 16% 10% 12%

New York 4% 11% 18% 8% 10%

North Carolina 2% 7% 10% 5% 6%

North Dakota 15% 15% 15% 15% 15%

Ohio 1% 6% 11% 4% 5%

Oklahoma 11% 19% 20% 18% 20%
Oregon 12% 19% 21% 17% 20%
Pennsylvania 2% 9% 16% 5% 7%

Rhode Island 1% 4% 6% 3% 3%

South Carolina 2% 7% 10% 5% 6%

South Dakota 24% 15% 15% 15% 15%

Tennessee 1% 3% 6% 2% 3%

Texas 8% 16% 20% 13% 15%

Utah 3% 5% 6% 4% 5%DRAFT DELIBERATIVE 11 April 2014



### 22 State 2012 Proposed Goals Alternate Goals

Interim Level Final Level Interim Level Final Level
Virginia 3% 12% 16% 9% 12%
Washington 7% 12% 16% 10% 12%
West Virginia 2% 8% 14% 5% 6%

Wisconsin 5% 8% 11% 7% 8%
Wyoming 9% 15% 20% 13% 15%

Table 4.9. Proposed and Alternate State Goals fo r RE Generation in Megawatt-hours, with 2012
Historical RE Generation

State 2012 Proposed Goals Alternate Goals Interim Level Final Level Interim Level Final Level

Alabama 2,776,554 8,647,278 14,292,801 6,009,218 7,610,632
Alaska 39,958 78,090 107,370 63,422 73,413
Arizona 1,697,652 2,937,707 3,831,642 2,481,537 2,801,621

Arkansas 1,660,370 3,370,253 4,708,823 2,703,555 3,153,509

California 29,966,846 40,868,634 41,150,704 40,586,564 41,150,704

Colorado 6,192,082 9,945,536 10,839,820 9,051,252 10,218,740

Connecticut 666,525 1,934,220 3,114,375 1,376,991 1,721,274

Delaware 131,051 561,909 1,038,351 349,356 468,394

Florida 4,523,798 13,971,137 22,109,614 9,790,728 12,399,889 Georgia 3,278,536 9,392,695 12,230,636 7,095,644 8,986,583
Hawaii 924,815 1,046,927 1,046,927 1,046,927 1,046,927DRAFT DELIBERATIVE 11 April 2014



### 23 Idaho 2,514,502 3,196,687 3,196,687 3,196,687 3,196,687
Illinois 8,372,660 13,910,775 17,818,004 11,904,488 13,326,217
Indiana 3,546,367 5,892,120 7,547,086 5,042,327 5,644,522
Iowa 14,183,424 8,565,921 8,565,921 8,565,921 8,565,921
Kansas 5,252,653 8,577,482 8,884,938 8,270,026 8,884,938 Kentucky 332,879 1,036,717 1,713,556 720,442 912,434

Louisiana 2,430,042 4,932,549 6,891,619 3,956,800 4,615,333

Maine 4,098,795 3,611,728 3,611,728 3,611,728 3,611,728 Maryland 898,152 3,728,926 5,982,069 2,394,301 3,210,129

Massachusetts 1,843,419 5,349,504 8,613,477 3,808,366 4,760,555

Michigan 3,785,439 6,289,326 8,055,859 5,382,246 6,025,037

Minnesota 9,453,871 7,888,544 7,888,544 7,888,544 7,888,544

Mississippi 1,509,190 4,272,197 5,458,430 3,266,297 4,136,743

Missouri 1,298,579 2,157,527 2,763,528 1,846,357 2,066,863
Montana 1,261,752 2,183,403 2,847,804 1,844,362 2,082,259

Nebraska 1,346,762 2,733,684 3,819,427 2,192,912 2,557,879

Nevada 2,968,630 5,137,075 6,700,268 4,339,384 4,899,105

New Hampshire 1,381,285 3,727,303 4,822,223 2,853,632 3,567,113

New Jersey 1,280,715 5,491,354 10,147,466 3,414,138 4,577,463

New Mexico 2,573,851 4,453,928 5,809,243 3,762,317 4,247,605DRAFT DELIBERATIVE 11 April 2014



### 24 New York 5,192,427 15,068,148 24,261,905 10,727,168 13,409,233
North Carolina 2,703,919 8,135,750 11,668,176 5,852,016 7,411,538

North Dakota 5,280,052 5,459,957 5,459,957 5,459,957 5,459,957

Ohio 1,738,622 7,454,735 13,775,594 4,634,830 6,214,090

Oklahoma 8,520,724 14,666,348 15,579,318 13,753,378 15,579,318

Oregon 7,207,229 11,551,256 12,567,372 10,535,140 11,894,029

Pennsylvania 4,459,118 19,119,477 35,330,855 11,887,147 15,937,543

Rhode Island 101,895 295,694 476,110 210,507 263,140
South Carolina 2,143,473 6,534,613 9,675,568 4,639,057 5,875,334

South Dakota 2,914,666 1,818,850 1,818,850 1,818,850 1,818,850

Tennessee 836,458 2,605,058 4,305,814 1,810,322 2,292,760

Texas 34,016,697 67,689,311 85,962,502 55,388,864 64,607,260
Utah 1,099,724 1,903,020 2,482,103 1,607,517 1,814,865 Virginia 2,358,444 8,608,808 11,192,008 6,287,155 8,429,425

Washington 8,214,350 14,214,545 18,539,981 12,007,295 13,556,072

West Virginia 1,296,563 5,559,307 10,273,036 3,456,386 4,634,107

Wisconsin 3,223,178 5,355,156 6,859,301 4,582,807 5,130,122

Wyoming 4,369,107 7,560,533 9,861,177 6,386,526 7,210,300DRAFT DELIBERATIVE 11 April 2014



### 25 The annual rates used to set state RE goals under this best practices scenar io are comparable to rates that leader states have been able to approach in the past. Eleven states across four regions have already achieved over 10% of total generation from RE , surpassing the lowest regional target applied in the Southeast. Two states, Maine and Iowa, have alre ady equaled or surpassed the highest regional target of 25% of generation, with South Dakota close behind at 24%. Finally, five states have already reached their region’s required target.

4.3 Cost Effectiveness of RE

The costs of building new RE capacity and genera ting more RE have changed significantly in the past decade, particularly for wind and solar. Accordi ng to an EPA analysis based on EIA levelized costs, costs of new RE, particularly on-shore wind, are b ecoming comparable to the cost-effectiveness of other re-dispatch technologies such as new NGCC plants. 26



### The economics of the fastest growing RE technologies – on-shore wind and solar PV – are improving. According to recent analyses of wind and solar project costs and pricing trends by U.S. Department of Energy, levelized long-term power pur chase agreement (PPA) prices have been declining. PPA prices, in general, reflect actual agreements to pay for power from wind or solar projects over a longterm and cover the cost of installing, operating, a nd maintaining a wind or solar project, along with a profit margin. 27 

### For utility-scale solar PV, those levelized PPA prices have fallen by more than two-thirds in the past five years “driven primarily by lower in stalled PV project prices (which, in turn, have been driven primarily by declining module prices), as well as expectations for further cost reductions in future years.” 28 

### More recent PPAs in the West are reporting levelized PPA prices in the range of $50-60/MWh (in 2012 dollars). 29 

### For wind, PPA prices have fallen since 2009 despite a trend within the wind industry to build projects at lower-quality wind resource sites. 30 

### “The average levelized long-term price from wind

26 EPA calculations of estimated dollar per tonne costs, based on EIA AEO 2013 levelized costs of electricity. 27 Bolinger, Mark, and Samantha Weaver. Utility-Scale Solar 2012: An Empirical Analysis of Project Cost, Performance, and Pricing Trends in the United States. Lawrence Berkel ey National Laboratory. LBNL-6408E. September 2013. p. 19. 28 Bolinger, Mark, and Samantha Weaver. Utility-Scale Solar 2012: An Empirical Analysis of Project Cost, Performance, and Pricing Trends in the United States. Lawrence Berkel ey National Laboratory. LBNL-6408E. September 2013. p. ii. 29 Ibid. 30 Wiser, Ryan H., and Mark Bolinger. 2012 Wind Tec hnologies Market Report. Lawrence Berkeley National Laboratory. August 2013. p. viii.DRAFT DELIBERATIVE 11 April 2014



### 26 PAs signed in 2011/2012—many of which were fo r projects built in 2012—fell to around $40/MWh
nationwide.” 31



### Examining RE resource availability regionally, sev eral recent studies have found cost-effective or
economic RE resources are available to serve future needs. The National Renewable Energy Laboratory (NREL) examined the future availability of RE in th e West after Western state RPS requirements level off
in 2025. 32 

### The study compares the cost of RE generation from the West's most productive RE resource areas—including any needed transmission and integrat ion costs—with the cost of energy from a new natural gas-fired generator built near the customers it serves. The report indicates that by 2025 wind and solar PV generation could become cost-competitive, if new RE development occurs in the most productive locations. 33 

### It also has shown that a cost decrease of 10% in 2025 would br ing solar power to cost parity with NGCC in the West, with si milar possibilities for utility scale geothermal. In 2010, the Southeast Energy Efficiency Alliance published a report by Marilyn Brown et al. titled Renewable Energy in the South. 34 

### In addition to highlighting significant RE resources in different parts of the region, it stated, “Under realistic renewable expansion a nd policy scenarios, the region could economically supply a large proportion of its future electricity needs from both utility-scale and customer-owned RE
sources.” 35 

### This study suggested that increased RE utili zation should not necessarily lead to significant rate increases in part because RE resources may modera te forecasted rate increases in the next decade or

two. 36



### Several studies have found the cost of RPS-driven RE deployment to be modest. One comparative analysis that "synthesize[d] and analyze[ d] the results and methodologies of 28 distinct state or utility-level RPS cost impact analyses" found the me dian change in retail electricity price to be $0.0004 per kilowatt-hour (only a 0.7 percent increase), the me dian monthly bill impact to be between $0.13 and $0.82, and the median CO 2 

### reduction cost to be $3 per metric ton. 37 

### This finding has been confirmed with

31 Ibid. 32 Hurlbut, David, Joyce McLaren, and Rachel Gelman. Beyond Renewable Portfolio Standards: An Assessment of Regional Supply and Demand Conditions Affecting the Futu re of Renewable Energy in the West. NREL/TP-6A20- 57830. Golden, CO: NREL, August 2013. 33 Ibid. p. xvi. 34 Brown, Marilyn A., Etan Gumerman, Youngsun Baek, Joy Wang, Cullen Morris, and Yu Wang. 2010. Renewable Energy in the South. Atlanta, GA: S outheast Energy Efficiency Alliance, December 2010. See also Brown, Marilyn A., Etan Gumerman, Xiaojing Sun, Kenneth Sercy, and Gyungwon Kim. 2012. “Myths and Facts about Clean Electricity in the U.S. South,” Energy Policy, 40: 231-241. 35 Ibid. p. xxii. 36 Ibid., p. 109. 37 Chen et al., "Weighing the Costs and Benefits of State Renewable Portfolio Standards: A Comparative Analysis of State-Level Policy Impact Projections," Lawrence Berk eley National Laboratory, March 2007, available atDRAFT DELIBERATIVE 11 April 2014



### 27 more recent RPS cost data, including a report that determined 2010-2012 retail electricity price impacts due to state RPS policies to be less than two percen t, with only two states experiencing price impacts of greater than three percent. 38



### 4.4. Cost Effectiveness of Nuclear Energy

Nuclear generating capacity facilitates CO 2 

### emission reductions at fossil fuel-fired EGUs by providing carbon-free generation that can replace gene ration at those EGUs. Increasing the amount of nuclear capacity relative to the amount that would ot herwise be available to operate is therefore a technically viable approach for reducing CO2 em issions from affected fossil fuel-fired EGUs.

One way to increase the amount of available nuc lear capacity is to build new nuclear EGUs. However, nuclear generating capacity is relatively expensive to build compared to other types of generating capacity, and little new nuc lear capacity has been constructe d in the U.S. in recent years. Nevertheless, five new nucl ear EGUs at three plants are currently under construction: Watts Bar 2 in Tennessee, Vogtle 3-4 in Georgia, and Summer 2-3 in South Carolina. The EPA believes that since the decisions to construct these units were made prior to th is proposal, it is reasonable to view the incremental
cost associated with the CO 2 

### emission reductions available from completion of these units as zero for purposes of setting states’ CO 2 

### reduction goals. Completion of these units therefore represents a highly cost-effective opportunity to reduce CO 2 

### emissions from affected fossil fuel-fired EGUs. For this reason, we are proposing that the emission reductions achie vable at affected sources due to the generation provided at the identified new nuclear units should be f actored into the state goals for the respective states
where these new units are located.

Another way to increase the amount of available nuclear capacity is to preserve existing nuclear EGUs that would otherwise be retired. While each retirement decision is based on the unique circumstances of that individual unit, the EPA believ es that increased fixed cost s associated with unit age play a role, particularly as the units approach the point of deciding whether to apply for renewal of their initial operating licenses (which have 40-year terms). Of the existing fleet of nuclear EGUs, units with 7.8 GW of capacity, representing approximately eight pe rcent of total existing U.S. nuclear generating capacity, have not yet submitted applications for li cense renewal to the Nuclear Regulatory Commission. Without making any judgment about the likelihood that any individual EGU will retire, we view this eight

http://emp.lbl.gov/publications/weighing-costs-and-benefits-state-renewables-portfolio-standards-comparativeanalysis-s. 38 Galen Barbose, “Renewables Portfolio Standards in th e United States: A Status Update,” Lawrence Berkeley National Lab, November 2013.DRAFT DELIBERATIVE 11 April 2014



### 28 percent share of nuclear capacity as a reasonable prox y for the amount of nuclear capacity at risk of retirement for reasons including, but not limited to, ad ditional fixed costs related to age and relicensing.

We believe that, based on available informati on regarding the cost and performance of the nuclear fleet, preserving the operation of this existing, at-risk nuclear cap acity is likely to be a relatively cost-effective approach to achieving CO2 reductions fr om affected EGUs. According to a recent report, nuclear units may be experiencing up to a $6/MWh sh ortfall in covering their operating costs with electricity sales. 39 

### Assuming that such a revenue shortfall is representative of the incentive to retire the estimated eight percent of at-risk nuclear capacity, one can estimate the value of offsetting the revenue loss at these at-risk nuclear units to be about $12 to $17 per metric ton. The EPA views this cost as reasonable. We therefore propose that the emission re ductions achievable by retaining in operation eight percent of each state’s existing nuclear capacity should be factored into the state goals for the respective

states.

39 “Nuclear... The Middle Age Dilemma?” Eggers , et al., Credit Suisse, February 2013