REDACTED COPY

Oklahoma Gas & Electric Co .

Integrated Resource Plan

Prepared January, 2010 by: Oklahoma Gas & Electric Co. 321 N Harvey Oklahoma City, Oklahoma 73102

Contact: Leon Howell Manager Resource Planning 405-553-3296

2010 Integrated Resource Plan

EXECUTIVE SUMMARY

INTRODUCTION

OG&E submits this IRP pursuant to OCC Electric Utility Rules and APSC’s Resource Planning Guidelines for Electric Utilities. This report fulfills the requirement to submit Integrated Resource Plans as stated in each state’s Electric Utility Rules or Guidelines.

OG&E last updated the IRP in February 2009. This IRP builds on its conclusion that actions such as the timely termination of wholesale contracts, deploying energy efficiency and smart grid programs, and adding wind generation continue to offer benefits to customers. These actions defer the need for new fossil fuel generation beyond the year 2020, and are referred to within OG&E as the “2020 Plan”.

The table below summarizes the effects of the Company’s proposed demand side actions for the first 5 years of this IRP.

Actions to Reduce Peak Demand (MW) 2010 2011 2012 2013 2014 Forecast Peak Demand 6,035 6,108 6,179 6,304 6,399 Wholesale Contracts 0 1 280 291 329 Load Curtailment 142 144 146 149 151 Demand Energy Efficiency 13 26 38 38 38 Reductions DR - Smart Grid 0 0 68 136 206 DA - Capacitors 0 2 6 13 20 Total Reductions 155 173 538 627 744 Peak Demand 5,880 5,935 5,641 5,677 5,655

Along with the demand reduction, the five year action plan includes adding 300 MW of wind in 2012 through a request for proposals to be submitted in 2010. Also included in the action plan is the expansion of the transmission system as directed by the Southwest Power Pool (SPP).

METHODOLOGY

The OG&E IRP process has remained fundamentally unchanged since it was developed in 2006. All of the assumptions used in the model have been updated with the most recent information available from Cadmus, EIA, NREL, Sargent & Lundy, and Ventyx. OG&E continues to test the uncertainty of assumptions such as fuel and emission prices, construction costs, and alternative views of the future using scenarios.

ENERGY AND DEMAND

OG&E’s most recent load forecast was provided on September 22, 2009. Energy and demand are forecasted using econometric models representing OG&E’s Oklahoma and Arkansas service territories. The Oklahoma economy is outperforming the rest of the nation but is slowing due to weak energy prices and the effects of the national economy.

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In Arkansas, a decline in manufacturing has led to severe job loss, including the loss of relatively high paying jobs.

OG&E’s weather-normalized historical energy growth rate has been approximately 1.8%. As a result of the recent economic downturn, OG&E’s energy sales growth, before demand side management programs are included, is expected to be slightly lower at 1.6% from 2010 to 2014. Peak demand is anticipated to grow at an average annual rate of 1.4% over the next decade, which is slightly less than the growth rate for retail energy sales.

GENERATION NEEDS

The contributions from OG&E’s existing assets to the Company’s ability to meet peak demand requirements is 7,119 MW, and is presented in the following chart.

225 MW 9 MW 3% 459 MW 0.1% 6% Gas Fired Steam

Coal Fired Steam 1,191 MW 17% 2,693 MW Combined Cycle 38% Long Term Purchase Agreements 2,542 MW Combustion Turbine 36% Wind

Matching the Company’s generation capability with the load assumption, adjusted for demand reduction programs, produces what is commonly referred to as a needs analysis. The needs analysis reflected in this IRP indicates that existing assets, additional wind, new energy efficiency programs, and smart grid demand response will allow OG&E to exceed the SPP minimum 12% planning capacity margin until 2022.

TRANSMISSION

While OG&E provides input to the SPP planning process, it is not ultimately responsible for the planning of the OG&E system. In this IRP, transmission has been divided into two categories: improvements SPP has identified that must be constructed for reliability and economic purposes, and improvements necessary to support OG&E’s generation expansion. The estimated construction cost of the projects SPP has directed OG&E to construct for reliability and economic purposes is approximately $860 million over the next 8 years, of which OG&E customers will pay their allocated share.

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REGIONAL HAZE

The Environmental Protection Agency (EPA), pursuant to the federal Clean Air Act, requires the State of Oklahoma to develop a plan to improve the visibility in national parks and wilderness areas. As a result, the DEQ has developed rules that require certain resources to install Best Available Retrofit Technology (BART) by 2018. The OG&E units affected are: Seminole 1, 2, and 3, Muskogee 4 and 5, and Sooner 1 and 2.

The BART rules address two different types of emissions from these units that have the potential to affect visibility. The first type of emission OG&E addressed are nitrogen oxides or NOx. OG&E has determined it will install low NOx combustion technology to minimize the creation of NOx during combustion. OG&E understands that the DEQ agrees with the proposed BART determination for NOx at the affected Seminole, Sooner and Muskogee units. Both the cost and effects of the installation of low NOx combustion technology have been included in this IRP.

The second type of emission addressed in the BART rules is sulfur dioxide or SO2. Under presumptive BART requirements, OG&E would need to install scrubbers on Muskogee 4 and 5, and Sooner 1 and 2. OG&E’s evaluation concluded that scrubbers were not a cost effective way to reduce SO2. Instead, OG&E proposed that BART was continued use of low sulfur coal without the installation of additional technology and offered an alternative plan for achieving visibility improvements in nearby national parks and wilderness areas. This alternative involves a step-wise lowering of annual SO2 emissions from the affected coal units beginning in 2016. OG&E has assumed this recommendation will be accepted and has included the effects of this proposal in this IRP.

CONCLUSION

To achieve the goal of the 2020 Plan, OG&E has: provided wholesale customers notice of termination, begun the smart grid initiative, filed comprehensive energy efficiency plans, constructed the OU Spirit wind generation facility, and is proposing the addition of 280 MW of additional wind generation as a result of the 2008 RFP.

Through these actions, OG&E believes it can defer any capacity expansion until the year 2022. Since the longest construction lead time on the plants considered for capacity expansion is 10 years for a nuclear plant, a decision on the type of capacity need in 2022 is not needed at this time. OG&E will be able to gain more knowledge of the uncertainties associated with greenhouse gas legislation, regional haze, and developing technologies before deciding the type of capacity that should be added.

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Contents I. INTRODUCTION ...... 4 II. Assumptions and Inputs ...... 5 A. Electric Demand and Energy Forecast ...... 5 1. Description of OG&E Service Territory ...... 5 2. Load Forecast Methodology ...... 6 3. Forecast of Key Assumptions ...... 7 4. Energy Sales Forecast ...... 8 5. Peak Demand Forecast ...... 9 B. Existing Resources ...... 9 1. Supply Resources ...... 9 2. Fuel Procurement and Risk Management Plan ...... 11 3. Changes in Resources ...... 13 4. Demand Side Resources ...... 13 5. Transmission Resources ...... 21 C. Resource Options ...... 22 1. Supply Side Resource Alternatives ...... 22 2. Demand Side Resource Options ...... 24 3. Transmission Options ...... 29 D. Needs Assessment ...... 32 1. Calculation of Capacity Needs ...... 32 2. Transmission Needs ...... 33 E. Fuel and Emissions Assumptions ...... 36 1. Natural Gas ...... 36 2. Coal ...... 36

3. Carbon Dioxide (CO2) ...... 36

4. Sulfur Dioxide (SO2) ...... 36 F. Environmental Considerations ...... 37 1. Renewable Energy Standards ...... 37 2. Carbon Dioxide Restrictions ...... 38 3. Regional Haze ...... 39 G. Scenarios ...... 41 1. OG&E Expected Scenario ...... 41

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2. Ventyx Horizons ...... 41 III. Resource Plan ...... 44 A. Integrated Resource Plan Process ...... 44 B. Analysis Process ...... 45 1. Develop Distinct Portfolios ...... 45 2. Portfolio Analysis ...... 47 3. Risk Evaluation ...... 49 4. SPP Market Analysis ...... 50 IV. SCHEDULES ...... 53 Schedule A – Electric Demand and Energy Assumption ...... 53 Schedule B – Existing Resources ...... 55 Schedule C – Transmission Capability and Needs...... 57 Schedule D – Needs Assessment ...... 58 Schedule E – Resource Options ...... 59 Schedule F – Fuel Procurement and Risk Management Plan ...... 62 Schedule G – Action Plan ...... 62 Schedule H – Requests for Proposals ...... 63 Schedule I – Modeling Methodology and Assumptions ...... 64 Schedule J – Transmission System Adequacy ...... 67 Schedule K – Resource Plan Assessment ...... 69 Schedule L – Proposed Resource Plan Analysis ...... 69 Appendices ...... 70 Appendix A ...... 70 Appendix B ...... 72 Appendix C ...... 89 Appendix D ...... 91 Appendix E ...... 96

List of Tables TABLE 1: OG&E ENERGY SALES FORECAST ...... 8 TABLE 2: OG&E PEAK DEMAND FORECAST ...... 9 TABLE 3: OG&E GENERATION RESOURCES...... 10 TABLE 4: DSM PROGRAM BY PRODUCT AREA...... 13 TABLE 5: 2008 DEMAND RESPONSE PERFORMANCE ...... 14 TABLE 6: LOAD CURTAILMENT RIDER CONTRACT DEMAND AND PERFORMANCE ...... 15 TABLE 7: INTERRUPTIBLE RIDER PERFORMANCE ...... 15 TABLE 8: PACE CONTRACT DEMAND AND PERFORMANCE ...... 16

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TABLE 9: THE POSITIVE ENERGY HOME PROGRAM PERFORMANCE ...... 16 TABLE 10: THE GEO-THERMAL HOME PROGRAM PERFORMANCE ...... 17 TABLE 11: OKLAHOMA ENERGY EFFICIENCY SAVINGS ...... 19 TABLE 12: ARKANSAS ENERGY EFFICIENCY SAVINGS ...... 21 TABLE 13: OG&E TRANSMISSION LINES ...... 21 TABLE 14: NEW SUPPLY SIDE RESOURCES ...... 23 TABLE 15: NEW WIND RESOURCES ...... 23 TABLE 16: LOAD CURTAILMENT ASSUMPTION ...... 24 TABLE 17: OKLAHOMA ENERGY EFFICIENCY PEAK DEMAND REDUCTION ...... 26 TABLE 18: OKLAHOMA ENERGY EFFICIENCY ANNUAL ENERGY REDUCTION ...... 26 TABLE 19: ARKANSAS ENERGY EFFICIENCY PEAK DEMAND REDUCTION ...... 28 TABLE 20: ARKANSAS ENERGY EFFICIENCY ANNUAL ENERGY REDUCTION ...... 28 TABLE 21: TOTAL SYSTEM ENERGY EFFICIENCY ...... 28 TABLE 22: DEMAND RESPONSE LEVELS ...... 29 TABLE 23: SITES FOR FUTURE GENERATION RESOURCES ...... 30 TABLE 24: PLANNING CAPACITY MARGIN ...... 33 TABLE 25: ESTIMATED COST FOR OG&E COMMITTED PROJECTS (IN MILLIONS) ...... 35 TABLE 26: ANNUAL AVERAGE OF ASSUMED NATURAL GAS PRICE ...... 36 TABLE 27: ASSUMED COAL PRICE ...... 36 TABLE 28: ASSUMED CO2 PRICE ...... 36 TABLE 29: ASSUMED SO2 PRICE ...... 37 TABLE 30: WIND ADDITIONS TO MEET 20% RES BY 2021 ...... 37 TABLE 31: SO2 TARGETS AND CAPACITY FACTORS FROM REGIONAL HAZE PROPOSAL ...... 41 TABLE 32: SUMMARY OF VENTYX SCENARIO DRIVERS AND KEY ASSUMPTIONS ...... 43 TABLE 33: NEW SUPPLY SIDE RESOURCE OPTION SCREENING REQUIREMENTS ...... 45 TABLE 34: RESOURCE PORTFOLIOS ...... 47 TABLE 35: 30-YEAR NPV OF OPERATING COST ...... 48 TABLE 36: 30-YEAR NPV OF CAPITAL COST ...... 48 TABLE 37: 30-YEAR NPV OF REVENUE REQUIREMENT ...... 49 TABLE 38: SCENARIO ANALYSIS RESULTS, 30-YEAR LEVELIZED $/MWH ...... 49 TABLE 39: SPP GENERATION EXPANSION (MW) ...... 52 TABLE 40: 10-YEAR NPV OF OPERATING COSTS IN DAM...... 52

List of Figures FIGURE 1: OG&E SERVICE AREA ...... 6 FIGURE 2: 2010 OG&E PEAK PLANNING CAPACITY ...... 9 FIGURE 3: SPP BALANCING AUTHORITIES ...... 22 FIGURE 4: SPP 2008 GI CLUSTER STUDY PROPOSED UPGRADES ...... 31 FIGURE 5: 20% RES BY 2021 ...... 38 FIGURE 6: OG&E CO2 PRODUCTION ...... 39 FIGURE 7: IRP PROCESS ...... 44 FIGURE 8: SENSITIVITY ANALYSIS RESULTS, 30-YEAR LEVELIZED $/MWH ...... 50

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I. INTRODUCTION

OG&E submits this IRP pursuant to Title 165: OCC, Chapter 35 Electric Utility Rules, and Subchapter 37 Integrated Resource Plan, and APSC’s Resource Planning Guidelines for Electric Utilities, approved in Docket No. 06-028-R. This report fulfills the requirement to submit Integrated Resource Plans as stated in each state’s Electric Utility Rules or Guidelines.

Following this Introduction, Section II presents an overview of OG&E, the demand and energy forecast, and modeling assumptions and inputs used in the analysis. Section III presents a discussion of the analysis methodology and results. Section IV concludes the report with a tabular summary of each section as described in OAC 165:35-37-4(c) and outlined below:

A. Electric demand and energy forecast B. Forecast of capacity and energy contributions from existing and committed supply- and demand-side resources C. Description of transmission capabilities and needs covering the forecast period D. Assessment of the need for additional resources E. Description of the supply, demand-side and transmission options available to the utility to address the identified needs F. Fuel procurement plan, purchased power procurement plan, and risk management plan G. Action plan identifying the near-term (i.e., across the first five (5) years) actions H. Proposed RFP(s) documentation, and evaluation I. Technical appendix for the data, assumptions and descriptions of models J. Description and analysis of the adequacy of its existing transmission system K. Assessment of the need for additional resources to meet reliability, cost and price, environmental or other criteria L. An analysis of the utility’s proposed resource plan

In addition, this filing contains several appendices that provide supporting materials, including studies and reports that have been prepared by OG&E, by vendors retained by OG&E, and stakeholders.

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II. ASSUMPTIONS AND INPUTS

This section includes a description of major assumptions and inputs to the models used to develop this integrated resource plan.

A. Electric Demand and Energy Forecast OG&E retained the services of The Cadmus Group, Inc. to prepare the September 2009 load forecast that is presented in Appendix E. Their report describes the data inputs, assumption methodologies, and models developed jointly with OG&E’s Load Research and Forecasting department with input from OG&E’s Interdepartmental Forecasting Task Force.

The 2009 retail sales forecast utilized the revenue class based econometric modeling framework that has been in place for over a decade. The 2009 load responsibility peak demand forecast is based on an hourly econometric model of weather and economic effects on OG&E’s hourly load responsibility, used since the 2000 forecast.

The load forecasting framework relies on independently produced forecasts of service area economic and population growth, actual and normal weather data, and projections of electricity prices for price-sensitive customer classes. The final energy and demand forecast includes Federal Energy Regulatory Commission (FERC) jurisdictional wholesale contracts as post-modeling adjustments. 1. Description of OG&E Service Territory OG&E serves more than 776,000 retail customers in Oklahoma and western Arkansas, as well as several wholesale customers throughout the region. The service territory covers approximately 30,000 square miles, includes 269 communities and surrounding areas, and has a population of approximately 2 million. OG&E serves Oklahoma City, which is the largest city in Oklahoma, as well as Ft. Smith, Arkansas. Of the 269 communities served by OG&E, 243 are in Oklahoma, and 26 are in Arkansas. OG&E’s retail service area is shown in Figure 1.

OG&E’s system control area peak demand for 2009, as reported by the OG&E system dispatcher, was 6,418 MW on July 13. The control area peak demand includes both retail and wholesale demands.

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Figure 1: OG&E Service Area

2. Load Forecast Methodology a) Energy Sales Forecast Methodology The 2009 retail energy forecast is based on retail sector-level econometric models representing OG&E’s Oklahoma and Arkansas service territories. Historical and forecast economic variables (drivers) are provided from the following sources:

• The Oklahoma Economic Outlook, prepared by the Oklahoma State University (OSU) College of Business Administration, Center for Applied Economic Research. • Moody’s Economy.com was used as a source of forecasts of economic drivers for Arkansas

In past forecasts, The University of Arkansas at Little Rock (UALR) provided economic drivers that were used to predict energy sales in OG&E’s Arkansas service territory. This year, OG&E made the decision to purchase forecasts of economic drivers from Moody’s Economy.com. The move from UALR to Moody’s Economy.com was made because Moody’s Economy.com was capable of providing forecasts of drivers for the Fort Smith region of Arkansas, rather than for the state as a whole, as UALR has traditionally produced. b) Peak Demand Forecast Methodology The 2009 load responsibility forecast relies on an hourly econometric model specification. The modeling framework reflects the following:

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1. Impact of different weekdays on hourly system load. 2. Impact of different summer months on hourly system load. 3. Influence of heat buildup during heat waves. 4. Impact of the combined effects of humidity and warm temperatures. 5. Non-linearity in the load and temperature relationships at very high temperatures.

As has been the case for the past several years, weather-adjusted retail energy sales are the main economic driver for the peak model. 3. Forecast of Key Assumptions a) Economic Outlook While Oklahoma’s economy has continued to outperform the national economy as a whole, the continuing national recession has created an uncertain economic environment in Oklahoma. Historically, Oklahoma’s economy has outperformed the rest of the nation during national recessions, as most recessions have been concurrent with rising energy costs. However, while Oklahoma’s momentum from its energy sector heading into the recession has protected it from the impacts seen in some of the worst hit states, low energy prices are adding to the economic pressures within the state. Dr. Mark Snead from OSU notes two underlying factors slowing growth within Oklahoma’s economy.1 These are:

• Weak Energy Prices: The OSU macroeconomic forecast drivers anticipates the price of oil hovering around $50/barrel, and natural gas a $5.50 per million Btu’s in 2009. Dr. Snead writes: “These prices are uncomfortably close to the threshold where we believe energy switches from providing a net boost to restricting growth in the state economy.” While the price of oil is beginning to increase, it has been under $50 a barrel for most of the year, and the price of natural gas has been below $5.50 per million Btu’s. Moody’s Economy.com2 forecasts suggest that natural gas will remain below $5 per million Btu’s through the end of the year, with oil climbing to an average of $55 a barrel in the fourth quarter.

• The duration of the national recession: A protracted recession nationally could drag down Oklahoma’s economy. This could cause additional turmoil in the economy including state and local budget problems, and increasing defaults on consumer debt.

Dr. Snead summarizes the economic outlook for 2009 and 2010: “In short, we believe Oklahoma will slow along with the nation in the next six months, but remain one of the few states positioned to come through the current recession unscathed relative to many areas of the country. However, if energy prices continue to fall and the national recession lasts much longer than expected, 2010 becomes the risk year for the

1 The Oklahoma Economy: 2009 Oklahoma Economic Outlook, http://economy.okstate.edu/outlook/ 2 Moody’s economy.com series: “Natural Gas: Henry Hub”, last updated 5/7/2009, and “Petroleum Crude Oil Price: West Texas Intermediate – Sweet Wellhead” last updated 5/7/2009.

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Oklahoma economy and may well signal the return of the familiar ‘Oklahoma Lag’ relative to the nation.”

In Arkansas, a declining manufacturing sector has led to severe job losses, impacting the greater economy through the loss of these relatively high-paying jobs. While the local unemployment rate is lower than the national one, it is higher than in the previous recession. Job losses are predicted to slow by the end of 2009 but job gains are not expected until late 2010. b) Weather Input Peak demand and energy sales are highly sensitive to year-to-year weather variations. Both can appear to decline even with positive economic growth when a hot year is followed by an unusually cool year. Conversely, if a hot year follows a cool year, energy sales and peak demand can increase even though there may be little or no economic growth.

Weather uncertainty is represented through a Monte Carlo modeling approach where the last 35 years of actual weather are systematically input into the energy and peak models to produce a possible outcome distribution.

OG&E’s weather-year Monte Carlo approach runs weather years 1974 to 2008 through weather-sensitive energy models, along with the peak demand model, to develop a probability distribution of possible outcomes. 4. Energy Sales Forecast The 2009 energy sales forecast, which is summarized in Table 1, adds FERC wholesale sales contracts and line losses to retail econometric model forecast projections. The forecast is based on normal weather in both Oklahoma and Arkansas. The underlying retail forecast is anticipated to grow at an average annual rate of 1.6% over the next decade.

Projected growth rates associated are comparable to those observed over the last decade. Weather-normalized sales grew by approximately 1.8% annually from 1997 through 2007. Growth is projected to be slightly lower from 2010 to 2014 (1.6%). Sales growth in the last half of the forecast, 2015–2019, will be slightly higher (2%), consistent with economic driver growth rate projections.

Table 1: OG&E Energy Sales Forecast GWh 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Sales 28,684 28,963 28,376 28,903 29,178 29,735 30,338 30,913 31,502 32,128 Growth Rate (%) 0.86 0.97 -2.02 1.86 0.95 1.9 2 1.9 1.9 2

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5. Peak Demand Forecast Table 2 shows the final load responsibility forecast, adjusted for wholesale loads3 and line losses. The forecast is based on average weather conditions over the past 35 years. Underlying retail peak loads are anticipated to grow at an average annual rate of 1.4% over the next decade, which is slightly less than the growth rate for retail energy sales. Table 2: OG&E Peak Demand Forecast MW 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Load Responsibility 6,035 6,107 5,899 6,013 6,070 6,176 6,265 6,386 6,488 6,596 Growth Rate (%) 0.76 1.18 -3.4 1.93 0.94 1.76 1.43 1.93 1.6 1.66

B. Existing Resources This section includes a description of OG&E’s existing supply, demand-side, and transmission resources. 1. Supply Resources OG&E's generation resources include coal-fired units, gas-fired steam units, gas-fired combined cycle (CC) units, gas-fired combustion turbine (CT) units, and wind energy. Figure 2 depicts the composition of OG&E’s generation resources.

Figure 2: 2010 OG&E Peak Planning Capacity

225 MW 9 MW 3% 0.1% 459 MW 6% Gas Fired Steam

Coal Fired Steam 1,191 MW 17% 2,693 MW Combined Cycle 38% Long Term Purchase Agreements Combustion Turbine 2,542 MW 36% Wind

OG&E’s net dependable rated capability for each unit is determined from unit testing during the summer months in accordance with SPP Criteria 12. The latest Capability

3 This forecast reflects the termination of existing wholesale contracts by 2014.

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Report was published on December 18, 2008 and reported a net dependable rated capability of 6,012 MW from OG&E’s ten power plants. Since the testing for that report was completed, maintenance on gas steam units has increased their capacity, construction of the OU Spirit wind farm has begun, and OG&E purchased a 51% interest in the Redbud plant. These events increased OG&E’s net dependable rated capability to 6,661 MW. This number is the basis for OG&E’s capacity margin for 2009. The complete capability report can be found in Appendix C.

OG&E generates approximately 68% of its electric energy from low-sulfur Wyoming coal and 30% from natural gas and 2% wind. OG&E purchases 320 MW from the qualifying facility AES plant at Shady Point that burns coal. OG&E also purchases 120 MW from the natural gas fired combined cycle PowerSmith plant, 51 MW of wind energy (1.5 MW of peak capacity) from FPL Energy at the Sooner Wind facility, and 17 MW of hydro generation from Southwest Power Administration (SPA). The hydro generation is transferred from wholesale customers to OG&E as part of the wholesale customers purchase power agreements. When wholesale customers are terminated, the 17 MW of hydro generation would no longer be available to OG&E.

OG&E’s current portfolio of electric generating facilities is presented in Table 3. With the exception of the McClain and Redbud plants, OG&E fully owns all of its plants. OG&E is the operator of all of its plants, including McClain and Redbud. All units have remaining expected lives that extend beyond the 30-year study.

Table 3: OG&E Generation Resources First Expected Max Full Load Variable Fixed O&M Year In Life Capacity Heat Rate O&M (2010 (2010 $/ Unit Type Unit Name Service (Years) (MW) (Btu/kWh) $/MWh) kW-yr) Muskogee 4 1977 >30 477 10,443 1.29 23.35 Muskogee 5 1978 >30 517 10,415 1.29 20.82 Coal Fired Muskogee 6 1984 >30 502 10,106 1.29 20.37 Steam Sooner 1 1979 >30 522 9,994 0.99 22.32 Sooner 2 1980 >30 524 10,187 0.99 20.87 Subtotal Capacity 2,542 Horseshoe Lake 6 1958 >30 172 10,089 1.61 13.6 Horseshoe Lake 8 1968 >30 380 10,157 1.61 6.64 Muskogee 3 1956 >30 171 10,486 1.59 9.78 Mustang 1 1950 >30 54 11,725 1.59 12.5 Mustang 2 1951 >30 50 11,725 1.59 13 Gas Fired Mustang 3 1955 >30 113 10,497 1.59 7.2 Steam Mustang 4 1959 >30 251 10,124 1.59 3.56 Seminole 1 1971 >30 506 10,568 1.08 8.54 Seminole 2 1973 >30 494 10,215 1.08 9.37 Seminole 3 1973 >30 502 9,996 1.08 9.47 Subtotal Capacity 2,693

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First Expected Max Full Load Variable Fixed O&M Year In Life Capacity Heat Rate O&M (2010 (2010 $/ Unit Type Unit Name Service (Years) (MW) (Btu/kWh) $/MWh) kW-yr) Horseshoe Lake 7 1963 >30 227 9,590 1.61 10.21 Combined McClain* 2001 >30 363 6,900 2.63 10.98 Cycle Redbud* 2004 >30 601 7,420 2.4 10.82 Subtotal Capacity 1,191 Enid 1GT 1965 >30 11 17,417 2.95 1.77 Enid 2GT 1965 >30 11 17,417 2.95 1.77 Enid 3GT 1965 >30 11 17,417 2.95 1.77 Enid 4GT 1965 >30 11 17,417 2.95 1.77 Horseshoe Lake 9 2000 >30 45 9,945 1.61 41.81 Combustion Horseshoe Lake 10 2000 >30 45 9,945 1.61 41.81 Turbine Seminole 1GT 1971 >30 17 16,000 6.28 1.18 Mustang 5A 1971 >30 32 15,432 1.59 7.44 Mustang 5B 1971 >30 32 15,432 1.59 7.44 Woodward 1963 >30 10 16,000 4.11 1.93 Subtotal Capacity 225 Centennial 2007 >30 4 N/A 0 30.89 Wind OU Spirit 2009 >30 5 N/A 0 24.29 Subtotal Capacity 9 AES Shady Point 1991 >30 320 N/A N/A N/A PowerSmith 1998 >30 120 N/A N/A N/A Purchase FPL Wind 2003 >30 2 N/A N/A N/A Power SPA Hydro N/A >30 17 N/A N/A N/A Subtotal Capacity 459 Total 7,119 * Represents OG&E owned interest 2. Fuel Procurement and Risk Management Plan OG&E files an annual Fuel Supply Portfolio and Risk Management Plan with the Oklahoma Corporation Commission which details OG&E’s fuel procurement and risk management plans. The plan was filed on May 15, 2009 under Cause No. PUD 200100095. This section is a summary of OG&E’s fuel procurement and risk management plan.

OG&E’s power supply portfolio consists of Company-owned electric generation facilities fueled by coal, natural gas, wind, and purchased capacity from a cogeneration contract, purchased power contracts, and the energy purchases from SPP Energy Imbalance (EIS) Market. The fuel cost to produce electricity from OG&E’s coal generation is typically less expensive compared to gas-fired generation. Taking into account that each technology and resource option has its own cost structure, operational characteristics, and economic drivers, OG&E’s primary fuel risk management strategy is to maximize the utilization of its coal generation capacity and wind energy within these constraints.

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a) Fuel Planning Process In the spring of each year, OG&E develops a forecast of load responsibility for peak demand and energy requirements on a weather normalized basis for each month of the next calendar year. The Company then analyzes expected generation availability, fuel price assumptions and contractual commitments and obligations. Additional factors include such items as generation unit efficiencies, minimum loading requirements, ramp rates, maintenance schedules, allowances for forced outages, and gas storage status.

OG&E develops a dispatch commitment plan based on these inputs. This plan provides the Company with an estimate of annual usage by fuel type. The annual projection incorporates OG&E’s assumed natural gas burn requirements for the next year that is then broken down into monthly requirements. The assumed natural gas burn is subject to change due to the potential purchase or sale of generation in the SPP hourly EIS market. b) Resource Procurement Practices 1) Coal Coal is procured under long-term contracts utilizing the widely accepted risk management laddering strategy. Contractual adjustments are made to the price of coal each quarter (up or down) due to quality variations. Currently, coal is purchased from four (4) producers located in the Southern Powder River Basin of Wyoming. Rail transportation is provided under long-term contracts with the Burlington Northern and Santa Fe Railroads for the Sooner Plant. For the Muskogee plant, OG&E is currently operating under a Common carrier tariff service from the Union Pacific Railroad pending a determination by the Surface Transportation Board on a maximum jurisdictional threshold rated prescription. 2) Natural Gas The Company acquired approximately 66% of its anticipated 2008 annual natural gas burn through an RFP process. OG&E obtains less than 0.1% of its natural gas requirements from older contracts with fixed prices. The other 32.9% is bought on a monthly, weekly, and daily basis. The key volumetric risk for natural gas procurement derives from securing sufficient supplies during the high electricity demand periods of April through October. OG&E currently transports its gas through the OGT pipeline (to the McClain, Tinker and Redbud plants) and through the Enogex pipeline (to the Horseshoe Lake, Seminole, Mustang, Enid and Muskogee plants.) OG&E has gas storage service under contract with Enogex4 that allows OG&E’s gas units to swing load in response to customer demands. 3) Fuel Oil Fuel oil is purchased through a competitive bidding process for delivery to the consuming plant. Fuel oil is primarily used for startup fuel at the coal-fired Sooner plant. Fuel oil is transported to the plants via truck.

4 Oklahoma Gas & Electric Co. and Enogex LLC are subsidiaries of OGE Energy Corp.

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3. Changes in Resources Since the last IRP filing, OG&E has proceeded with its plan to add wind generation. OG&E has taken ownership of the 101 MW OU Spirit wind facility.

In addition, subject to OCC approval, 280 MW of wind generation will be obtained through purchase power agreements. These projects are referred to in this plan as the ‘Taloga’ and ‘Keenan’ wind farms, and will be operational as of October 1, 2010, and January 1, 2011, respectively. Details on this process and the results are presented in Schedule H. 4. Demand Side Resources Demand Side Management (DSM) is composed of two product areas that are focused on the customer end of the value chain. These areas are:

• Demand Response (DR)—DR programs are designed to encourage customers to reduce their load during peak loading periods. These programs are either event based or price response driven. Event based programs are initiated by OG&E in response to varying external stimuli. Price response programs are tariffs with predefined, recurring pricing.

• Energy Efficiency (EE)—EE measures are designed to encourage customers to become more efficient in how they use energy. Measures are designed to educate customers, encouraging them to change their energy use habits and finally for them to act on these new behaviors. OG&E offers myriad measures designed to increase educational awareness and decrease monetary barriers which may inhibit adoption of energy efficiency behaviors by customers.

OG&E currently has active DSM products in both product areas. These products take the form of both tariffed and non-tariffed programs. OG&E manages 24 various programs as shown in Table 4.

Table 4: DSM Program by Product Area Product Program Number of Area Type Programs Demand Event Based 13 Response Price Response 9 Energy Legacy 7 Efficiency Quick Start 5 Total 24

Both product areas have an effect on OG&E’s peak load demand forecast. OG&E uses historical hourly load responsibility demands as the dependent variable, or forecasted variable, in the econometric load forecast models. Since legacy EE measures and price response products are on-going programs, the results of these programs are reflected

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in OG&E’s historical load responsibility information. This means the effect of legacy measures and price response products are represented in OG&E’s annual load forecast that includes both system peak and energy.

However, the event based DR products and OG&E’s quick start EE measures are not represented in the load forecast. The effects of the quick start programs on future loads are discussed later in this section. The event based products are designed to provide relief on an as needed basis. These events can be initiated within hours and can be used to support system reliability, economical in nature, or used to lower peak system loads. Since 1997, OG&E has initiated 34 load curtailment events. One of the events was for economical purposes. The remaining events were due to system reliability needs. Event based programs are not reflected in the load forecast, but are subtracted from OG&E’s forecasted peak demand as reflected in the Needs Assessment section on page 32. a) Demand Response Programs Both Event Based and Price Response programs are designed to encourage customers to reduce their load during peak loading periods.

OG&E manages three event based programs that are available as voluntary riders for larger commercial and industrial customers to reduce their load during peak loading periods: Curtailment Rider, Interruptible Rider, and Performance Award for Curtailed Energy. Table 5 summarizes results for 2008.

OG&E currently offers 9 tariffed price response programs. These programs are designed to encourage customers to permanently shift usage on the distribution system from high production cost (peak) hours to lower production cost (off-peak) hours. Eight of the tariffs are focused specifically at summer seasonal peak hours use. The Real Time Pricing tariff focuses on all hours of the year.

Table 5: 2008 Demand Response Performance Energy Peak Period Program Reduction Demand Program Name Initiated (MWh) Reduction (MW) Event Curtailment Rider (CR-1) 1997 No Events No Events Based Interruptible Rider (IR-1) 1997 No Events No Events Demand Performance Award for Curtailed 2003 No Events N/A Response Energy (PACE-1) Residential - Time of Use 1985 577.9 1.09 General Service – Time of Use 1986 1,720.8 1.93 Price Power and Light – Time of Use 1985 17,621.0 16.06 Response Public Schools – Demand* 2007 389.0 0.37 Programs Public Schools – Non Demand* 2007 19.1 0.13 Oil & Gas Producers 1997 0.7 0.01 Real Time Pricing (RTP)-DAP 1996 N/A 24.20 * Includes two tariffs: Standard TOU and Compressed TOU

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1) Load Curtailment (Curtailment Rider CR-1) This is a voluntary rider available to customers with the capability to reduce their demand by at least 500 kW. Customers on CR-1 create a mandatory obligation to reduce their load by a Contracted Curtailable Demand (CCD measured in kW) or to not exceed a Contracted Demand (CD measured in kW) level during periods of requested reduction. OG&E has 46 CR-1 contracts yielding about 115 MW in curtailable load as of December 2008. OG&E’s Load Curtailment program is its most successful event based DR program.

A credit is awarded for subscription and penalties exist for non-compliance. Customer subscription awards range from $1.93 to $2.23 per kW of CCD. Customers failing to curtail face significant financial penalties and may be assigned to the PACE-1 rider.

Table 6 summarizes annual net contract demand and average performance during curtailment events. Since the end of 2005 the amount of curtailable load under contract has decreased nearly 80 MW. A significant number of contracts were dropped due to their failure to perform as required. There were no events called in 2008.

Table 6: Load Curtailment Rider Contract Demand and Performance MW 2004 2005 2006 2007 2008 Net Contract Demand 183.9 201.0 170.8 141.0 121.2 Average Performance n/a n/a 142.5 123.4 n/a

2) Interruptible Service (Interruptible Rider IR-1) This rider covers mandatory load reduction. A credit is paid for subscriptions ranging from $2.53 to $2.57 per kW demand. OG&E currently has 11.6 MW under contract. Table 7 summarizes the rider’s contracts and average performance since 1999.

Table 7: Interruptible Rider Performance MW 2004 2005 2006 2007 2008 Net Contract Demand 11.6 11.6 11.6 11.6 11.6 Average Performance n/a n/a 11.6 11.6 n/a

3) Energy Curtailment (Performance Award for Curtailed Energy PACE-1) This rider provides for voluntary reduction in energy consumption. A payment will be rendered for the amount of energy (kWh) reduced during a curtailment event. Energy prices for each kWh reduction are set and communicated to customers on the day of each curtailment event. No penalties are assessed for non-performance. Energy from the program is non-firm and cannot be recognized as providing an avoided capacity and therefore cannot be used as a capacity resource for planning purposes. Table 8 summarizes the program’s contracts and average performance since 2005.

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Table 8: PACE Contract Demand and Performance MW 2005 2006 2007 2008 Number of Customers 0 19 35 31 Average Performance n/a 43.6 62.1 n/a

4) Real Time Pricing [Day-Ahead-Pricing (DAP)] Hourly prices are provided day ahead to participants for each hour of the next day. These signals provide customers indications they need to shift their energy usage to more beneficial energy cost periods. OG&E maintains 11 active real time pricing customers resulting in a decrease of 24.2 MW during the system peak hour. This reduced consumption is beneficial to both participants (lower bills) and all other customers on the OG&E system (lower total fuel costs). 5) Time-of-Use Time-of-use programs are seasonally and time-differentiated programs that communicate varying prices to customers signaling them to shift their energy use habits. A higher price signal for energy usage during the summer season (June 1st through September 30th) on-peak hours (between 2:01 pm and 7:00 pm) encourages customers to shift usage to off-peak hours (lower priced hours). OG&E manages seven time-of-use programs which are summarized in Table 5 on page 14. b) Energy Efficiency Energy Efficiency (EE) programs are designed to encourage customers to permanently improve how they use energy. Encouragement is provided through programs and services designed to educate customers to choose energy efficient end-uses (e.g. Energy Star® appliances or improved construction designs). The programs described below are offered in both Oklahoma and Arkansas. The actual performance of these programs in 2009 is still being analyzed; therefore the 2008 data is the most recent data available. 1) The Positive Energy Home This program combines a strict set of construction standards with properly sized high efficiency heating and cooling equipment. The Positive Energy Home meets the DOE Energy Star® Homes program requirements. The Energy Star® program requires that a home be at least 30% more efficient than the 1993 model energy code and certified by a third party (OG&E is a certified rater for Energy Star®). An important target for the Positive Energy Home program is low-income new construction projects. These projects are a part of a HUD grant program focusing on improving access to affordable new homes. Table 9: The Positive Energy Home Program Performance 2004 2005 2006 2007 2008 Number of Homes 48 9 14 94 190 Energy Savings (kWh) 113,184 21,222 33,012 221,652 448,020 Demand Savings (kW) 59.5 11.2 17.4 116.6 235.6

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2) The Geo-Thermal Home This program combines a strict set of construction standards with properly sized geothermal heating and cooling equipment. Geo-Thermal Homes meet the DOE Energy Star® Homes program requirements (OG&E’s Geo-Thermal Home program was the first utility program in the nation certified to meet the Energy Star® Homes program requirements). OG&E targets both the residential and commercial markets and focuses on both new and retrofit appliances. Equipment rated at more than 3,000 tons capacity has been installed since 2001.

Table 10: The Geo-Thermal Home Program Performance Geo-tons Installed 2004 2005 2006 2007 2008 Residential 146 223 195 190 331 Commercial 130 923 954 1,489 1,150 Multi-Family 0 24 55 1,500 330 Total 276 1,170 1,204 3,179 1,811

3) Heat Pumps This program promotes high efficiency heating and cooling options for customers. The program educates customers, as well as heating and cooling professionals, on the energy savings available with higher efficiency choices. More than 8,200 total electric, HVAC residential units have been installed in Oklahoma. This resulted in 959.18 MWh5 of energy and 4.81 MW in demand savings in 2008. 4) Rate Tamer® This is an energy information service targeting larger commercial and industrial customers. Customers are provided on-line access to their business’ energy consumption patterns via the internet. Customers use this information to make energy decisions and manage their loads. These decisions include: shifting usage to lower cost periods; reducing total energy usage through efficiency; decreasing peak demands during higher cost periods; or redesigning processes to shift peak demand to non-peak times. There are currently 254 customers using this innovative program. No direct program costs are recovered through the regulatory process. 5) Power Factor Correction Power factor is a calculation used to determine how efficient a customer is using energy. A low power factor indicates inefficient energy use requiring OG&E to generate more energy to meet that customer’s needs. Customers can improve their power factor by employing power quality correction assets. OG&E currently requires demand charge customers (i.e. PL-1, LPL-1, etc.) to be as close to a 100% (unity) power factor as possible. Customers with metered usage resulting in power factors below 85% are subject to billing demand adjustments up to the minimum 85% power factor. This

5 Results are based on deemed savings calculated from California’s Database for Energy Efficient Resources (DEER) 2004 – 2005 for the Red Bluff’s weather area.

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information is communicated to the customer and signals their opportunity to improve operations, bypassing this adjustment. c) Oklahoma Quick Start Energy Efficiency In Cause No. PUD 200700012, OG&E proposed a series of new demand side management programs for implementation in Oklahoma. These programs are designed to encourage and enable customers to make the most efficient use of utility capacity and energy, and to discourage inefficient and wasteful use of energy. In Order No. 545240, the Oklahoma Corporation Commission found the portfolio of programs proposed by OG&E would be beneficial to ratepayers and shareholders alike. OG&E introduced this portfolio of programs as the “Oklahoma DSM Programs – Quick Start” in July, 2008. The portfolio consists of seven programs. 1) Residential Weatherization The purpose of the Residential Weatherization program is to improve comfort and reduce energy costs by upgrading the thermal envelope and appliances in hard-to- reach, energy inefficient homes. Some of the improvements may include, but are not limited to: attic, floor, and wall insulation; duct sealing, repair, and insulation; air infiltration; furnace and air conditioner tune-ups; lighting retrofits and replacement. 2) LivingWise® This program provides 6th grade school teachers with a custom designed energy curriculum so they may educate the students and their families about natural resources. The curriculum teaches the importance of conservation in their daily lives. The curriculum consists of a teaching guide that promotes awareness of our energy and water resources, in addition to a LivingWise® kit that includes: a CFL, sink aerator, high efficiency shower head, Lime Light night light, air filter alarm, digital thermometer, toilet leak tablets, natural resources fact chart, and a mini tape measure. 3) Custom Energy Report The purpose of this program is to educate and assist customers on ways to improve their level of comfort while lowering energy costs in their homes. The measure provides online or mailed surveys that produce personalized reports showing where homes use electricity and gas, and recommend actions and measures for saving energy. 4) Education The Energy Efficiency Education program is designed to: increase the level of awareness of our customers and the public, to help facilitate the need to preserve our natural resources, and to reduce the amount of electricity they use. This program will help customers of all classes make knowledgeable choices in acquiring appliances, heating and cooling equipment, building materials, lighting, motors, and usage patterns. 5) Compact Fluorescent Lights This program is designed to help reduce the energy use and demand for residential customers by displacing conventional incandescent light bulbs with low wattage

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compact fluorescent lights (CFL). OG&E partners with General Electric (GE) to provide coupons that can be redeemed at any store that sells GE CFL’s. This program builds on the ENERGY STAR “Change a Light, Change the World” campaign. 6) Commercial Lighting This program is designed to reduce both demand and energy use by commercial and industrial customers through the replacement of fluorescent lighting fixtures with more efficient electronic ballasts and low-wattage lamps. 7) Motor Replacement The Motor Replacement program’s purpose is to reduce both demand and energy use for commercial and industrial customers through retrofit or replacement of burned-out motors with more efficient models. High efficiency motors lower operating costs and extend motor life, both benefits for the consumer. 8) Oklahoma Results Table 11 shows the savings of the existing energy efficiency programs in Oklahoma.

Table 11: Oklahoma Energy Efficiency Savings 2008 Actual 2009 Estimated Quick Start Program Energy (kWh) Demand (kW) Energy (kWh) Demand (kW) Residential Weatherization 370,000 93 3,164,599 891 LivingWise® 60,588 6 276,262 29 Custom Energy Report 2,355,584 765 7,101,044 2,705 Education 0 0 0 0 Compact Fluorescent Lights 215,498 26 1,266,984 169 Commercial Lighting 942,315 317 16,719,614 4,677 Motor Replacement 67,462 8 704,405 116 Total 4,011,447 1,215 29,232,934 8,587

d) Arkansas Quick Start Energy Efficiency In the state of Arkansas an Energy Efficiency Program will be offered by OG&E as mandated by the Arkansas Public Service Commission (APSC), pursuant to Order #18 of Docket No. 06-004-R, for the period of October, 2007 through December, 2009. OG&E introduced this portfolio of programs as the “Arkansas Energy Efficiency Programs – Quick Start” in October, 2007. The portfolio consists of seven programs. 1) Weatherization The Weatherization program was opened to all residential customers and provides energy improvements to severely energy inefficient homes, thereby decreasing demand and energy usage. OG&E will participate in a collaborative statewide effort with other utilities offering a weatherization program, providing a unified approach and more cost effective means of reaching more homes in our territory and the state.

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2) LivingWise® The LivingWise program provides teachers a curriculum to educate students on energy efficiency, and a LivingWise Kit that includes: a CFL, air filter alarm, sink aerator, high efficiency shower head, and a night light demonstrating energy efficiency measures. After the students learn about energy efficiency, they take the LivingWise Kit home and install the various components with the help of their parents and siblings who become educated as well. 3) Residential Energy Audit The Residential Energy Audit program will provide energy audits via surveys to residential customers. The energy surveys will be mailed out to OG&E customers. The customers that complete the survey and return them will receive a personalized energy report providing an analysis and recommendations on how to save energy. The customer survey will also be available online at: www.oge.com. 4) Education The Education program provides energy efficiency information to all customers and classes, encouraging participation in understating of how electricity is used and the impact it can have on our budgets. This program will help customers of all classes make knowledgeable choices in acquiring appliances, heating and cooling equipment, building materials, lighting, motors, and usage behavioral patterns. 5) Compact Fluorescent Lights The objectives of the CFL program are to: save energy and demand, change behavior, attitudes, awareness and knowledge about CFL technology with our customers, improve affordability of energy, and reduce the cost of upgrading to the newer technology. 6) Commercial Lighting The Commercial Lighting program will decrease energy usage and demand for commercial customers by replacing inefficient lighting. This program may be included in an overall performance contracting arrangement that includes a lighting retrofit by a qualified lighting contractor. 7) Motor Replacement The design of this program will be to educate customers and motor distributors on the operating cost benefits of high efficiency motors and also provide an incentive to replace existing or burned-out motors with higher efficiency premium motors. 8) Arkansas Results Table 12 shows the savings of the existing energy efficiency programs in Arkansas.

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Table 12: Arkansas Energy Efficiency Savings 2008 Actual 2009 Estimated Quick Start Program Energy (kWh) Demand (kW) Energy (kWh) Demand (kW) Weatherization 147,600 41 464,593 178 LivingWise 333,060 37 242,743 27 Residential Energy Audit 727,804 284 1,357,595 489 Education 0 0 0 0 Compact Fluorescent Lights 0 0 689,962 854 Commercial Lighting 1,215,394 301 1,623,058 449 Motor Replacement 10,880 4 72,553 26 Total 2,434,738 667 4,450,504 2,023

5. Transmission Resources OG&E operates approximately 4,300 miles of transmission lines, 69 kV through 500 kV, throughout its service territory. Table 13 provides details of OG&E’s transmission system line mileage at various voltages. A map of OG&E’s transmission system is available upon request. These electric transmission lines move large amounts of power at high voltages from power plants. To increase reliability OG&E’s transmission system is directly interconnected to seven other utilities’ transmission system at over 50 interconnection points. Indirectly OG&E is connected to the entire eastern interconnection through the Southwest Power Pool (SPP) regional transmission organization.

Table 13: OG&E Transmission Lines Voltage Miles 500kV 47 345kV 790 161kV 193 138kV 1,845 69kV 1,468 Total 4,343

The SPP footprint covers 370,000 square miles and its 54 members serve over 5 million customers. It covers all of Kansas and Oklahoma and parts of seven other states: Arkansas, Louisiana, Mississippi, Missouri, New Mexico, Nebraska, and Texas.

The SPP footprint is comprised of 16 balancing authorities, which are operated by investor-owned utilities, cooperatives, and municipal and state agencies. A balancing authority is responsible for managing the supply and demand for electricity within its borders to assure reliability. The territories of these balancing authorities are shown in Figure 3.

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Figure 3: SPP Balancing Authorities

C. Resource Options 1. Supply Side Resource Alternatives The new supply side resources considered in this IRP are those used by the Department of Energy’s Energy Information Administration (EIA) in developing their Annual Energy Outlook. The Annual Energy Outlook 20096, prepared by the EIA, presents long-term projections of energy supply, demand, and prices through 2030, based on results from EIA’s National Energy Modeling System (NEMS). A summary of their characteristics is shown in Table 14.

6 http://www.eia.doe.gov/oiaf/aeo/

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Table 14: New Supply Side Resources Size Capital Cost Variable O&M Fixed O&M Heat rate Technology (MW) ($/kW) ($/MWh) ($/kW-yr) (Btu/kWh) Advanced CC 400 1,142 2.04 11.96 6,752 Advanced CC with CCS 400 2,276 3.01 20.34 8,613 Advanced CT 230 764 3.24 10.76 9,289 Biomass 80 4,534 6.86 65.88 9,646 Combined Cycle (CC) 250 1,158 2.12 12.76 7,196 Combustion Turbine (CT) 160 807 3.65 12.38 10,810 Fuel Cells 10 6,454 48.98 5.78 7,930 Hydropower 500 2,700 2.48 13.93 N/A IGCC 550 2,864 2.98 39.53 8,765 IGCC With CCS 380 4,209 4.54 47.14 10,781 Landfill Gas 30 3,062 0.01 116.78 13,648 Nuclear 1,350 3,994 0.50 92.01 10,434 Photovoltaic (Solar) 5 7,270 0.00 11.94 N/A Scrubbed Coal 600 2,478 4.69 28.14 9,200 Solar Thermal 100 6,045 0.00 58.04 N/A Wind 50 2,316 0.00 30.97 N/A

The operational characteristics for wind resources are determined by the wind profile at the resource site. Table 15 shows general characteristics of the potential sites for wind resources in this resource plan. The sites chosen are near EHV transmission lines proposed by the Eastern Wind Integration and Transmission Study (EWITS) and SPP studies. The Eastern Wind Dataset, originally created for EWITS, consists of modeled data created by AWS-Truewind, with oversight and assistance from NREL7 for 1,326 simulated wind plants.

Table 15: New Wind Resources NREL Capacity Potential Site Site ID Location Factor (%) Output (MW) 631 Ellis County, OK 42 1,291 754 Ellis County, OK 42 436 496 Ellis County, OK 43 301 365 Beaver County, OK 42 558 505 Comanche County, OK 44 1,031 239 Ford County, KS 43 334 342 Kiowa County, KS 42 577 390 Meade County, KS 42 520 173 Lipscomb County, TX 44 1,046

7 http://www.nrel.gov/wind/integrationdatasets/eastern/methodology.html

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2. Demand Side Resource Options In addition to supply side resources, OG&E has analyzed additional demand side management programs to defer the need to build additional generating units to meet capacity margin requirements. a) Load Curtailment The Load Curtailment program is designed for customers 500 kW and greater. OG&E had 115 MW of load contracted in 2008 and has contracted more as shown below. It is assumed that load curtailment will increase at the same rate as customer load. Table 16 shows the load curtailment values used in the 10 year planning horizon.

Table 16: Load Curtailment Assumption 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Load Curtailment (MW) 142 144 146 149 151 154 156 159 161 164

b) Energy Efficiency On September 15, 2009, OG&E filed Cause No. PUD 200900200 with the OCC as a comprehensive plan to expand the energy efficiency programs in Oklahoma. On June 30, 2009, Docket No. 07-075-TF was filed with the APSC as the plan to expand the energy efficiency programs in Arkansas. The following section is a summary of the plans for each state. 1) Oklahoma Energy Efficiency Programs In November 2007, OG&E contracted with Frontier Associates LLC to perform a comprehensive two-part potential study for its Oklahoma jurisdiction to identify potential energy efficiency and demand programs for implementation. The OG&E management team evaluated the Frontier Potential study programs and chose to implement eight programs based upon customer benefit, market potential and budget criteria, as well as the creation of an optimum portfolio to meet the goal of no new fossil fuel generation until 2020. (a) Low Income Weatherization OG&E will provide weatherization services to nine thousand (9,000) OG&E customer homes over a three year period. This program is designed to increase energy efficiency by improving the thermal efficiency of homes occupied by low income persons. This program is designed to reduce energy consumption, lower energy costs, increase the comfort of homes, and safeguard occupant’s health. (b) Fixed Income Weatherization OG&E has intentionally created a separate weatherization program to capture fixed income customers who may not necessarily qualify under the Low Income Weatherization program. This separate weatherization program is essentially identical to the Low Income Weatherization program in terms of the work to be performed, but it has a separate qualification criteria designed to capture customers on fixed incomes.

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(c) Residential Thermal Efficiency This program is targeted to residential customers who need assistance in identifying areas to improve the efficiency of their home’s thermal envelope, assistance in improving the efficiency of their existing HVAC equipment, assistance in sealing or repairing HVAC duct work and information about pricing for work recommended by audit results. (d) Positive Energy – New Home Construction (PE-NHC) This program is designed to encourage builders and homeowners to utilize energy efficient PE-NHC practices in the construction of new homes. The program is designed to increase the overall efficiency, quality and sustainability of customer homes. Efficiency programs that are recommended by these guidelines include: the use of geothermal heat pump technology, tighter home construction, higher levels of wall, ceiling, floor and slab insulation, and high efficiency windows. PE-NHC design will reduce both energy consumption and peak demand for OG&E. (e) Geothermal Heating, Cooling and Water Heating This program offers incentives to customers who install geothermal heat pumps into their new or existing homes. Geothermal systems essentially use the constant temperatures of the earth to heat and cool a home. In the heating season, a geothermal system absorbs heat from the earth and carries it to your home to be distributed throughout the home using traditional duct systems. In the air conditioning season, this process is reversed, and the geothermal unit absorbs heat from inside the home and sends it back to the cooler earth or utilizes it for hot water storage. (f) Commercial Lighting This program is an expanded version of the Commercial Lighting program implemented in the OG&E Quick Start portfolio, which promoted the replacement of traditional fluorescent lighting with more efficient fluorescent lighting in small offices, government offices and schools and new construction. The expanded program not only promotes fluorescent lighting, but also new lighting technologies such as light emitting diode sources (LED). The expanded program targets commercial, public authority and industrial facilities of all sizes with a focus on the small to medium-sized facilities, where saturation rates and awareness levels of high-efficiency lighting are expected to be lower than in larger operations. (g) Commercial/Industrial Standard Offer Program (SOP) This program offers financial incentives for the installation of a wide range of measures that reduce customer energy costs, reduce peak demand, and/or save energy in non- residential facilities that qualify for the Power and Light rate or Large Power and Light rate in the Oklahoma jurisdiction. (i) Education This program is a continuation of OG&E’s education program that will help expedite market transformation in Oklahoma. The first part Education program is an online

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Custom Energy Report for residential customers who have lived in their residences for at least twelve months. The second part is an appropriate energy education curriculum and kit for fifth grade students such as the LivingWise® program utilized in Quick Start. The third part is an increased media campaign to educate Oklahoma customers on the benefits of energy efficiency and the opportunities available to them. 2) Oklahoma Energy Efficiency Forecast The combined forecasted peak reduction and energy savings from the Oklahoma Energy Efficiency programs are found in Table 17 and Table 18.

Table 17: Oklahoma Energy Efficiency Peak Demand Reduction MW 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Low Income Weatherization 3.1 6.2 9.4 9.4 9.4 9.4 9.4 9.4 9.4 9.1 Fixed Income Weatherization 0.9 1.7 2.6 2.6 2.6 2.6 2.6 2.6 2.6 2.5 Residential Thermal Efficiency 3.3 6.6 9.9 9.9 9.9 7.9 6.0 4.1 4.1 3.9 PE - NHC 0.1 0.3 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 Geothermal 0.8 1.6 2.4 2.4 2.4 2.4 2.4 2.4 2.4 2.4 Commercial Lighting 2.8 5.5 8.3 8.3 8.3 8.3 8.3 8.3 8.3 8.3 SOP 1.0 2.0 3.0 3.0 3.0 3.0 2.9 2.9 2.8 2.8 Education 0.3 0.5 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 Total 12.2 24.4 36.6 36.6 36.6 34.6 32.7 30.7 30.7 30.1

Table 18: Oklahoma Energy Efficiency Annual Energy Reduction MWh 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Low Income 15,073 30,146 45,220 45,220 45,220 45,220 45,220 45,220 45,220 43,235 Weatherization Fixed Income 4,186 8,371 12,557 12,557 12,557 12,557 12,557 12,557 12,557 12,006 Weatherization Residential Thermal 4,649 9,298 13,947 13,947 13,947 12,030 10,113 8,196 8,196 8,017 Efficiency PE - NHC 188 375 563 563 563 563 563 563 563 563 Geothermal 3,239 6,478 9,717 9,717 9,717 9,717 9,717 9,717 9,717 9,717 Commercial Lighting 10,778 21,556 32,334 32,334 32,334 32,334 32,334 32,334 32,334 32,334 SOP 7,380 14,759 22,139 22,139 22,139 22,139 21,807 21,475 21,143 21,143 Education 2,653 5,306 7,958 7,958 7,958 7,958 7,958 7,958 7,958 7,958 Total 48,146 96,289 144,435 144,435 144,435 142,518 140,269 138,020 137,688 134,973

3) Arkansas Energy Efficiency Programs The energy efficiency programs in Arkansas (AR-EE) continue the work started through the Quick Start program.

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(a) Weatherization This program targets severely energy inefficient homes. In this program, OG&E will hire independent contractors to weatherize 500 severely inefficient homes in the OG&E service territory for the year 2010, with an additional 250 homes weatherized during 2011. OG&E will work through its independent contractors and in conjunction with various social service agencies such as the Community Clearing House Agency. (b) LivingWise® LivingWise® teaches sixth grade students the importance of conservation. During the training session, OG&E provides each student with a LivingWise® kit which includes: a compact fluorescent bulb, a kitchen aerator, a high efficiency shower head, a LimeLite® night light, a FilterTone® alarm, a mini tape measure, a digital thermometer, a flow rate test bag, toilet leak detector tablets, a natural resources fact chart, and a parent comment card. Corresponding curriculum is provided with a structured outline to enable teachers to educate their students on energy efficiency. At the conclusion of the course students take the LivingWise® kit home and are encouraged to install the energy efficiency measures with the assistance of their parents. (c) Custom Energy Report This program provides a self-administered energy survey to residential customers. Upon completion of the on-line survey, the customer will receive a personalized energy report by email providing analysis and recommendations on how to save energy. (d) Commercial Lighting This program focuses on Commercial Lighting by educating, offering performance contracting services, and providing incentives on replacement of T-12 lamps to commercial and industrial customers to encourage installation of high efficiency lighting systems. (e) Motor Replacement This program provides education courses on the advantages of high efficiency motors, and offers incentives to commercial and industrial customers to replace inefficient motors with high efficiency motors. OG&E will offer incentives to commercial and industrial customers that replace motors between 10 and 100 horsepower. (f) Education This program continues our education efforts in Arkansas to educate all customer classes on energy efficiency and conservation. 4) Arkansas Energy Efficiency Forecast The combined forecasted peak reduction and energy savings from the Arkansas Energy Efficiency programs are found in Table 19 and Table 20.

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Table 19: Arkansas Energy Efficiency Peak Demand Reduction MW 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Weatherization 0.6 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 LivingWise® 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Custom Energy Report 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Commercial Lighting 0.3 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 Motor Replacement 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Education 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Total 1.0 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5

Table 20: Arkansas Energy Efficiency Annual Energy Reduction MWh 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Weatherization 1,557 2,336 2,336 2,336 2,336 2,336 2,336 2,336 2,336 2,029 LivingWise® 116 174 174 174 174 174 174 174 174 174 Custom Energy Report 168 252 252 252 252 252 252 252 252 252 Commercial Lighting 1,125 1,875 1,875 1,875 1,875 1,875 1,875 1,875 1,875 1,875 Motor Replacement 63 101 101 101 101 101 101 101 101 101 Education 0 0 0 0 0 0 0 0 0 0 Total 3,029 4,738 4,738 4,738 4,738 4,738 4,738 4,738 4,738 4,431

5) OG&E Energy Efficiency Forecast The combined forecasted peak reduction and energy savings from the Oklahoma and Arkansas Energy Efficiency programs are found in Table 21.

Table 21: Total System Energy Efficiency 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Peak Reduction (MW) 13 26 38 38 38 36 34 32 32 32 Energy Savings (MWh) 51,175 101,027 149,173 149,173 149,173 147,256 145,007 142,758 142,426 139,404

c) Demand Response OG&E has two new programs for demand response: Real Time Pricing (DR-RTP) and the distribution automation program Integrated Voltage and VAR Control (DA-IVVC).

DR-RTP utilizes a Home Area Network (HAN), which is an internet based web application that will be made available to all customers free of charge. This system will provide customers with near real time information on their energy consumption, cost to date, current price, and assumed cost. It will provide guidance and tips on how to manage and reduce their bill, as well as provide comparisons to other comparable homes. Other key components of the HAN are the communication devices of the network within a premise. The purpose is to allow communication to in home devices; primarily Programmable Communicating Thermostats (PCT) or In Home Displays (IHD).

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The HAN could eventually communicate to other devices like intelligent appliances, Plug-in Hybrid Electric Vehicle (PHEV), or wall plugs for control of any device. A PCT is capable of accepting commands over the HAN, which allows the remote manual or automatic adjustment of temperature based on personal preferences or pricing signals. For example, a consumer could choose to set a lower temperature setting on their air conditioner that would automatically be set based on a Peak Price signal. This setting could potentially be set directly on the PCT or remotely programmed through a customer web portal. Customers will have override capability of this feature. This thermostat may also serve as the in-home display panel described below.

An IHD operates the same as a PCT except that they have no control capability. The purpose of the IHD is to send information to the consumer for the purpose of eliciting demand response actions or energy conservation. This display provides continuous feedback on energy cost, which improves customer awareness and effectiveness of the price signals. This information could consist of price signals, historic usage as compared to other customers, or usage month to date. Field tests have indicated that this technology is highly effective in influencing energy consumption patterns.

DA-IVVC allows reactive and voltage control elements on the circuit to be operated in a coordinated fashion to reduce the voltage profile or reactive power requirements along the feeder. The ability to reduce peak demand and minimize line losses using this technology are important considerations.

Over the next ten years, OG&E is planning for 20% of the residential customers to adopt the in home devices, each reducing their energy consumption during OG&E system peak hours by 1.3 kW. Likewise, over the next ten years, the distribution automation program will reduce OG&E system peak load by more than 50 MW. The current annual planned reductions from these programs are reflected in Table 22.

Table 22: Demand Response Levels (MW) 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 DR - RTP 0 0 68 136 206 208 209 211 213 214 DA - IVVC 0 2 6 12 20 28 36 45 56 56 Total 0 2 74 148 226 236 245 256 269 270

3. Transmission Options Supply side resource options will require transmission investments, a fact that must be reflected in the optimization model. OG&E has identified a number of potential future power plant sites and estimated the transmission costs associated with these sites. Table 23 identifies three sites that were chosen based upon existing infrastructure, fuel deliverability, and existing transmission lines.

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Table 23: Sites for Future Generation Resources Site No. Site Description Resource Type County 1 Woodward Geographical Area Wind Various 2 Seminole Power Plant 1 - 500 MW Unit Seminole, Oklahoma 3 Seminole Power Plant 1 – 1,000 MW Unit Seminole, Oklahoma 4 Sooner Power Plant 1 - 500 MW Unit Noble, Oklahoma 5 Sooner Power Plant 1 – 1,000 MW Unit Noble, Oklahoma

a) Woodward Geographical Area OG&E used information from a SPP transmission expansion study referred to by the SPP as the “2008 GI Impact Cluster Study” to estimate transmission improvements and costs associated with the expansion of OG&E wind generation. The estimated construction costs associated with the projects located in the Woodward area is approximately $480 million.

In 2009, SPP posted the results of the first Generation Interconnection (GI) Impact Cluster Study8. This study analyzed multiple GI requests associated with new wind generation, which would be located within several transmission systems. The primary objective of this study was to identify system constraints associated with connecting the new wind generation. This cluster study resulted in an effective expansion plan to integrate new wind generation into the approved SPP Transmission Expansion Plan. The full report includes a description of the constraints and mitigations for each of the cluster groups studied.

Figure 4 shows the proposed upgrades resulting from the 2008 GI Impact Cluster Study.

8 The 2008 Impact Cluster Study for Generation Interconnection Requests can be found at http://sppoasis.spp.org/ documents/swpp/transmission/studies/files/2008_Generation_Studies/ICS-2008-001_final.pdf

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Figure 4: SPP 2008 GI Cluster Study Proposed Upgrades

b) Seminole Power flow analysis has indicated that connecting a new unit up to 1,000 MW at Seminole will require transmission upgrades to correct overloads in the OG&E and AEP control areas. The associated construction cost for a new unit at Seminole is estimated to be $9 million. There may be additional stability cost that will be determined in the SPP Study Process c) Sooner Power flow analysis has indicated that connecting a new 500 MW unit at Sooner will require transmission upgrades to correct overloads in the OG&E control area. The associated construction cost for a new 500 MW unit at Sooner is estimated to be $7 million.

Power flow analysis has indicated that connecting a new 1,000 MW unit at Sooner will require transmission upgrades to correct overloads in the OG&E and Entergy control areas. The associated construction cost for a new 1,000 MW unit at Sooner is estimated

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to be $32 million. There may be additional stability cost that will be determined in the SPP Study Process. d) Summary Schedule E summaries the transmission projects that OG&E has determined must be complete to allow for the delivery of generation expansion options analyzed in this IRP. After a decision has been made as to the type and location of the addition of a new resource, the SPP will determine required upgrades and associated costs.

D. Needs Assessment 1. Calculation of Capacity Needs Capacity needs are defined as the additional capacity required to meet the Company’s customer requirement and to satisfy SPP's minimum 12% planning capacity margin requirement. Section 4.3.5 of the SPP Criteria establish the basis and define the required minimum capacity planning reserve margin for SPP members as follows:

“The SPP performs generation reliability assessments to examine the regional ability to maintain a North American Electric Reliability Council (NERC) based target probabilistic Loss of Load Expectation (LOLE) standard of no more than one day in ten years. Historical studies indicate that the LOLE of one day in ten years minimum can be maintained with a minimum capacity margin between 10- 11%. Based on this, the SPP has established that each control area is required to maintain a minimum planned capacity margin of 12% for steam-based utilities and minimum planned margin of 9% for hydro-based utilities.”

Therefore, OG&E is required to maintain capacity levels that allow for a minimum of 12% margin between capacity and demand. This calculation is shown in the following equation:

(Total Net Dependable Capability) - (Net On System Demand) Capacity Margin % = (Total Net Dependable Capability)

Table 24 utilizes the above equation to provide a ten-year capacity need forecast. This table includes all resources currently owned or under contract by OG&E. This table also includes OG&E’s load responsibility and capacity margins. The resource gap, or capacity needed to satisfy customer demand and the SPP minimum 12% margin, is shown as Needed Capacity.

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Table 24: Planning Capacity Margin MW 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Owned Capacity 6,660 6,660 6,660 6,660 6,659 6,659 6,659 6,659 6,659 6,659 Resources Purchase Contracts 459 449 442 442 442 442 442 442 442 442 Total Capacity 7,119 7,109 7,102 7,102 7,101 7,101 7,101 7,101 7,101 7,101 Forecast 6,035 6,107 5,899 6,013 6,070 6,176 6,265 6,386 6,488 6,596 Load Curtailment 142 144 146 149 151 154 156 159 161 164 Demand New Energy Efficiency 13 26 38 38 38 36 34 32 32 32

Net On System Demand 5,880 5,937 5,715 5,826 5,881 5,986 6,075 6,195 6,295 6,400 Needed Capacity 0 0 0 0 0 0 0 0 53 172 Capacity Capacity Margin 1,239 1,172 1,387 1,276 1,220 1,115 1,026 906 806 701 Needs Capacity Margin (%) 17 16 20 18 17 16 14 13 11 10 Load Reserve Margin (%) 21 20 24 22 21 19 17 15 13 11

Demand Forecasted DR 0 2 74 148 226 236 245 256 269 270 Response Net On System Demand 5,880 5,935 5,641 5,678 5,655 5,750 5,830 5,939 6,026 6,130 Capacity Needed Capacity 0 0 0 0 0 0 0 0 0 0 Needs Capacity Margin 1,239 1,174 1,461 1,424 1,446 1,351 1,271 1,162 1,075 971 with Demand Capacity Margin (%) 17 17 21 20 20 19 18 16 15 14 Response Load Reserve Margin (%) 21 20 26 25 26 24 22 20 18 16

2. Transmission Needs In compliance with FERC Order 890 for transmission planning, the SPP does annual expansion planning for the entire SPP footprint. Therefore OG&E provides input to the SPP planning process, but is not ultimately responsible for the planning of the OG&E system.

The main objective of SPP’s ten-year regional reliability assessment is to create a reliable long-range transmission expansion plan for the SPP footprint. The assessment identifies problems for normal conditions (no contingency) and single contingency scenarios using NERC Reliability Standards, SPP Criteria, and local planning criteria. It also coordinates appropriate mitigation plans to meet the SPP region’s reliability needs.

The 2008 SPP Transmission Expansion Plan9 (STEP) is a result of SPP’s 2008 transmission planning activities. The plan describes improvements necessary for regional reliability, zonal reliability, long-term tariff studies due to transmission service requests and transmission owner sponsored improvements. Projects that must be constructed inside the 2009-2012 timeframe to maintain regional reliability are identified.

9 The 2008 STEP can be found at: http://www.spp.org/publications/2008_Approved_STEP_Report_Redacted.pdf

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Also identified are regional reliability projects in the 2013-2018 timeframe that do not need immediate action and will be considered in future plans.

In the spring of 2009 SPP completed the first Balanced Portfolio Report. The Balanced Portfolio10 was an initiative to develop a group of economic transmission upgrades that benefit the entire SPP region, and to allocate those project costs regionally. The Balanced Portfolio contains a diverse group of 345KV transmission projects addressing many of SPP’s top flowgates. OG&E will construct all or part of four of the seven projects identified in the Balanced Portfolio:

• The 250 mile “Woodward -Tuco” line between Hale County, Texas (north of Abernathy) and Woodward, Oklahoma. • The 100 mile “Seminole-Muskogee” line between Seminole County and Muskogee, Oklahoma. • The 36 mile “Sooner-Cleveland” line between Sooner Lake in Noble County, Oklahoma and Cleveland, Oklahoma. • The “Anadarko Transformer” in Anadarko, Oklahoma.

a) OG&E Transmission Expansion for IRP Transmission improvements identified in the STEP and the Balanced Portfolio studies were included in the transmission models for this resource plan. All projects with construction commitments are shown in Figure 4. The construction cost associated with projects OG&E will construct is approximately $860 million, and the cost allocated to OG&E customers is included in this IRP analysis. A complete list of these projects that impact OG&E can be found in Schedule J. Transmission Upgrades associated with new generating resources are outlined in Schedule E. b) Transmission Expansion Cost Recovery Transmission system expansion provides benefits to members throughout the SPP; therefore, the cost of these projects is shared through various cost allocation methods, depending on the type of project. For this resource plan, the costs of projects OG&E has committed to construct were allocated through the appropriate method specified by the SPP. Table 25 shows the estimated total Annual Transmission Revenue Requirement (ATRR) for the SPP, and the portion of the cost that will be allocated to OG&E.

10 The SPP Balanced Portfolio Report can be found at http://www.spp.org/publications/2009%20Balanced%20Portfolio%20-%20Final%20Approved%20Report.pdf

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Figure 4: SPP Projects with Construction Commitments

Table 25: Estimated Cost for OG&E Committed Projects (In Millions) SPP OG&E SPP OG&E Year ATRR Allocation Year ATRR Allocation 2010 $ 39 $ 35 2025 $ 111 $ 61 2011 $ 58 $ 50 2026 $ 107 $ 59 2012 $ 86 $ 68 2027 $ 104 $ 57 2013 $ 105 $ 76 2028 $ 100 $ 55 2014 $ 136 $ 80 2029 $ 97 $ 53 2015 $ 142 $ 79 2030 $ 93 $ 51 2016 $ 138 $ 77 2031 $ 90 $ 49 2017 $ 136 $ 75 2032 $ 86 $ 47 2018 $ 134 $ 73 2033 $ 82 $ 45 2019 $ 132 $ 73 2034 $ 79 $ 43 2020 $ 129 $ 71 2035 $ 75 $ 41 2021 $ 125 $ 69 2036 $ 72 $ 39 2022 $ 122 $ 67 2037 $ 68 $ 37 2023 $ 118 $ 65 2038 $ 65 $ 35 2024 $ 114 $ 63 2039 $ 61 $ 33

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E. Fuel and Emissions Assumptions This section includes the expected fuel and emissions price assumptions. 1. Natural Gas The natural gas price assumption was provided by Ventyx in their Power Market Advisory Service: Electricity & Fuel Price Outlook. Natural gas prices are sensitive to seasonal changes, so a monthly price is used by the model to adequately account for generation operation and dispatch changes throughout the year. An annual summary is shown in Table 26.

Table 26: Annual Average of Assumed Natural Gas Price 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Natural Gas ($/MMBtu) 5.75 6.40 6.35 6.65 7.25 7.88 8.55 9.06 9.58 9.84 2. Coal The coal price assumption was created by the OG&E Operations, Dispatch and Fuels group, and Ventyx. The OG&E forecast was used for the first five years and the Ventyx MarketVision data was used for the rest of the study period. This assumption is provided in Table 27. Table 27: Assumed Coal Price 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Coal ($/MMBtu) 1.81 1.91 2.09 2.17 2.27 2.33 2.38 2.49 2.54 2.61

3. Carbon Dioxide (CO2)

The CO2 price assumption was provided by Ventyx in their MarketVision data. This assumption is provided in Table 28.

Table 28: Assumed CO2 Price 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

CO2 ($/tonne) - - 10.18 12.51 15.14 18.08 19.44 20.91 22.47 24.17

4. Sulfur Dioxide (SO2)

The 1990 Clean Air Act (CAA) includes an acid rain program to reduce SO2 emissions. Reductions were obtained through a program of emission (release) allowances issued by the EPA to power plants covered by the acid rain program. Each allowance is worth one ton of SO2 released. Plants may only release as much SO2 as they have allowances. Allowances may be banked and traded or sold nationwide.

Beginning in 2000, OG&E became subject to more stringent SO2 emission requirements in Phase II of the acid rain program. The EPA allocated SO2 allowances to OG&E starting in 2000 and OG&E started banking allowances in 2001. These lower limits have not had a significant financial impact due to OG&E’s reliance on low sulfur coal. In each

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of the years since 2000, OG&E’s SO2 emissions were well below the allowable limits. OG&E is allowed to retain 10% of the proceeds from all sales of allowances. The remaining revenues from these transactions are flowed through to customers under the fuel clause.

The SO2 price assumption was provided by Ventyx in their MarketVision data. This assumption is provided in Table 29.

Table 29: Assumed SO2 Price 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

SO2 ($/ton) 441 556 694 725 775 764 708 604 551 526

F. Environmental Considerations The uncertainty regarding environmental legislation and regulation of greenhouse gas emissions is very important to consider in resource planning. There are three main environmental concerns that were considered in this resource plan: Renewable Energy Standard (RES), federal legislation limiting carbon dioxide emissions, and Regional Haze restrictions imposed by the Oklahoma Department of Environmental Quality (DEQ). 1. Renewable Energy Standards There are 33 states that currently have mandatory or voluntary standards for the amount of energy that must be supplied by renewable resources11. Whether imposed at the federal or state level, OG&E is assuming a RES will be in place that calls for 20% of the energy sold to be considered renewable by 2021. This is in line with other states’ standards, as well as the standard passed in the American Clean Energy and Security Act (ACES).

Oklahoma is one of the leading states in wind generation development; therefore, additional wind resources, as described in the Resource Options section on page 23, are the primary renewable energy source for this resource plan. Table 30 shows the additional wind generation needed to meet the 20% by 2021 RES. Wind generation was added throughout the remaining years of the study to maintain this standard.

Table 30: Wind additions to meet 20% RES by 2021 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021

Additional Wind (MW) 300 150 150 150 150 150 150 Cumulative Capacity (MW) 854* 854 854 854 1,004 1,154 1,304 1,454 1,604 1,754 * Includes existing capacity from Centennial, Sooner, OU Spirit, Taloga, and Keenan

11 http://www.epa.gov/chp/state-policy/renewable_fs.html

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Renewable Energy Credits (REC’s) are accrued to meet the RES. These credits can be obtained through renewable energy production as well as other qualifying sources. Each MWh of renewable energy is equivalent to one REC. ACES includes a provision for banking credits for up to 3 years. Also, electricity savings relative to business as usual projections would accrue REC’s. This plan assumes that the savings associated with the energy efficiency programs, described in the Resource Options section on page 24, will provide REC’s. Figure 5 shows how the RES is met each year of the study with wind, banked credits, and qualifying energy efficiency.

Figure 5: 20% RES by 2021

8,000

7,000

6,000

5,000 hours - 4,000

3,000 Gigawatt

2,000

1,000

0 2010 2015 2020 2025 2030 2035

Banked Credits Qualified Energy Efficiency Wind Energy Credits Required for 20% by 2021 2. Carbon Dioxide Restrictions The American Clean Energy and Security Act, passed by the House of Representatives, and the Clean Energy Jobs and American Power Act, proposed in the Senate, include a cap-and-trade system for reducing greenhouse gas output. Both of these bills include the same caps and allocation mechanisms; therefore, OG&E is assuming this system will be in place in 2012. The cap is set at graduated levels relative to 2005 CO2 output.

In this resource plan, a per unit price for CO2 production is applied. These prices vary as described in the Scenarios section on page 41, that reflect various levels of compliance with a hard cap.

Figure 6 shows the projected levels of CO2 production if OG&E dispatches its existing fleet, including additional wind resources to achieve the 20% RES. This is then compared to the representative target from ACES for OG&E CO2 output and allocated allowances. Currently, CO2 makes up approximately 97% of the greenhouse gasses

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emitted by OG&E generation facilities. The targets begin in 2012 at 97% of the 2005 emission levels, while the allowances decrease annually to 0 by 2030. As Figure 6 clearly shows, significant changes to the way OG&E provides energy will need to be made to achieve these targets.

Figure 6: OG&E CO2 Production

25,000

20,000

15,000

10,000

Thousands of Tonnes of Thousands 5,000

0 2010 2015 2020 2025 2030 2035

CO Production CO Target CO Allowance Allocation

₂ ₂ ₂ 3. Regional Haze In 2005, EPA, pursuant to the federal Clean Air Act, promulgated regulations to improve the visibility in national parks and wilderness areas (“Regional Haze Regulations”). These Regional Haze Regulations require the state, over approximately a 50-year period, to move toward the elimination of man-made impacts on visibility in Class I areas. The DEQ has developed rules that require certain resources to install Best Available Retrofit Technology (BART) by 2018. The OG&E units affected are: Seminole 1, 2, and 3, Muskogee 4 and 5, and Sooner 1 and 2. In May 2008, OG&E submitted BART evaluations for its affected generating units at Muskogee, Seminole and Sooner Stations.

The BART evaluations were performed in accordance with EPA guidelines and address two different types of emissions from these units that have the potential to affect visibility. The first type of emission addressed in the BART evaluation is nitrogen oxides or NOx. The BART evaluations demonstrate that OG&E should install low NOx combustion technology to minimize the creation of NOx during combustion. One of the five factors considered in selecting BART is the cost effectiveness of available control technologies. According to EPA’s cost-effectiveness guidelines, the low NOx combustion techniques are cost effective, ranging from $233 to $270 per ton of NOx removed annually at the coal-fired units at Muskogee and Sooner stations. DEQ has agreed with the proposed BART determination for NOx at the affected Seminole, Sooner and Muskogee units.

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The second type of emission addressed in the BART evaluation is sulfur dioxide or SO2. EPA established a presumptive BART emission rate for the coal-fired units at Muskogee and Sooner of 0.15 pounds of SO2 emissions per million Btu’s of heat input. This emission rate can be achieved with the installation of dry flue gas desulfurization, which also is known as a scrubber.

OG&E believes the presumptive BART emission rate for SO2 does not apply if one performs a complete analysis of the five factors used to establish BART and determines a specific BART emission rate for the unit that considers its particular characteristics and circumstances. The BART analysis performed by OG&E’s consultant Sargent & Lundy for the affected units at Muskogee and Sooner concludes that those units are different because they burn low sulfur coal that dramatically changes the cost effectiveness equation. For these units, scrubbers would have an average cost of $10,078 per ton of SO2 removed annually (approximately ten times the average cost of $919 per ton estimated by the EPA), and the costs would range from $9,625 to $10,883 per ton of SO2 removed annually depending on the particular unit. As a result, the BART evaluation concluded that scrubbers were not cost effective and recommended emission limits that require the units to continue burning low sulfur coal.

In the report from Sargent & Lundy that OG&E submitted to the DEQ on September 17, 2009, the capital cost for scrubbers at the affected coal units (computed in accordance with EPA standards) was $1.527 billion. OG&E believes that, at $1.527 billion, this would be the largest privately-funded capital project in the history of the State of Oklahoma. Besides the capital costs, and as shown in the S&L Report, OG&E expects to incur approximately an additional $150 million annually to operate and maintain the scrubbers.

OG&E has developed a proposal to address SO2 emissions that OG&E believes can be adopted by DEQ as a reasonable further progress goal under the regional haze rules. The proposal is based on a step-wise lowering of annual SO2 emission limits to achieve concrete visibility results and, ultimately, the same visibility improvement that scrubbers would achieve. Table 31 shows the proposed limits as a percentage of current SO2 output levels. The table also shows the associated maximum capacity factor at which the affected coal units could run and conform to the limits.

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Table 31: SO2 Targets and Capacity Factors from Regional Haze Proposal Muskogee 4 & 5 Sooner 1 & 2 Target (% of Maximum Target (% of Maximum Current Level) Capacity Factor Current Level) Capacity Factor

2010-2015 100% 76% 100% 76% 2016 90% 69% 97% 74% 2017 83% 63% 95% 72% 2018 75% 58% 93% 70% 2019 68% 52% 91% 69% 2020 61% 47% 89% 67% 2021-2025 60% 46% 87% 66% 2026-2039 20% 15% 30% 22%

This resource plan includes the steps proposed by OG&E to address SO2 emissions. These limits are met by replacing the energy typically provided by coal-fired units to gas-fired units, as natural gas emits approximately 0.1% of the SO2 of coal emissions.

G. Scenarios Scenarios are used to test each portfolio in a wide range of possible futures. This is done to determine the best portfolio in the expected future, as well as how each plan performs under changes in the expected assumptions. OG&E uses five planning scenarios which are described in the following sections. 1. OG&E Expected Scenario OG&E’s expected scenario includes all the assumptions provided in the Assumptions and Inputs section. 2. Ventyx Horizons OG&E is currently using the Ventyx Electric Power Horizons 2009 “Scenarios of the Global Energy Future” for scenario analysis. These scenarios were developed at the spring 2009 Electric Power Horizons workshop. Ventyx advisors and energy industry experts identified four distinct themes that are expected to have the greatest impact on the future energy business environment over the next 25 years. They are intended to represent a range of potential future energy business environments. The themes are outlined below and defined more explicitly in Table 32.

• Global Turmoil o Disruptions in gas supply leads to global stagnation, and a U.S. recession, which is followed by sustained low economic growth where energy independence away from Middle East oil and LNG imports is critical.

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• Technology Evolution o Undeniable evidence of global warming leads to regulation to reduce CO2 and a societal shift to greater energy conservation and “zero emission” supply side technologies.

• Global Economy o The shift of industrial U.S. load to the service industries and a policy of global consolidation drive the U.S. to forge a pact with G8 + 5 to stabilize global economy inflationary pressures and wealth disparity.

• Return to Reliability o Growing concern of electricity reliability due to brownouts and increase outages drives a lack in consumer confidence. The Electric Reliability Organization (ERO) recognizes the shortfall of the aging transmission structure and leads to further consolidation of planning areas.

In addition, Ventyx used a PriceWaterhouseCoopers survey of utility executives from 65 power companies in 39 countries. In the report, PriceWaterhouseCoopers stated, “In the coming decade, technological innovation is seen as having the most impact on energy efficiency, solar power, combined heat and power, distributed generation and combustible renewable generation. Carbon capture and storage will be essential for the sector’s long-term contribution to the mitigation of climate change.” The survey found the shift in utility executives’ thinking consistent with the Ventyx scenarios of the global energy future.

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Table 32: Summary of Ventyx Scenario Drivers and Key Assumptions Technology

Global Turmoil Evolution Global Economy Return to Reliability Economic Growth Low Status Quo High Status Quo Slow Growth Electricity Reduced - Medium - Expanded Increased in later Medium High - EES Demand conservation works Markets years 3.6% increase due to 3.6% decrease due EES standard Load Factor addition of heavy No Change to loss of heavy modifies load factor industry industry Energy Efficiency Low Medium High; 15% by 2020 Medium High Gas Supply LNG Constrained Status Quo LNG accelerated Status Quo Gas Price High Medium High Low Medium Coal Price High Low Medium Low Medium High Oil Price High Medium High Low Medium CO2 Price None None High Low Re-introduce of Re-introduction of Pollutants: SO NO , CAMR; existing SO Environmental CAMR; existing SO , Pollutants: SO and 2, x 2, 2 2 CO ; ACES Act 20% NO , and regulations Regulation and NO regulations NO 2 x x x below 2005 by 2020 enforced; CO tax enforced 2 with no cap

Emission Caps Base + Hg Base + CO2 goal Base + CO2 Base + Hg Build Permitted & Nuclear New 7 GW APWR 100 GW PBMR 3 GW APWR Application Pending Builds Units (47 GW APWR) Meet State RPS Renewable 20% by 2026 Additional Generation 25% by 2025 mandates; reduced Generation wind for reliability CO sequestration 2 CO sequestration Technology Renewables Nuclear 2 Transmission Energy efficiency Superconductor Improvements PBMR Energy Energy efficiency Energy efficiency efficiency Clean coal Target zero emission Target zero emission Coal Generation Pulverized Coal technologies resource resource Reserve Margin Target 15% reserve Target 15% reserve Target 15% reserve Target 18% reserve Additional capacity to Additional capacity to Additional capacity to Additional capacity accommodate shift of accommodate Transmission accommodate for reliability and capacity due to retirements and renewable additions congestion nuclear builds renewable additions

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III. RESOURCE PLAN

A. Integrated Resource Plan Process The flowchart in Figure 7 illustrates how the integrated resource plan is developed. First, OG&E collected input data and declared assumptions. Then OG&E used a four step process to analyze potential expansion plans. This analysis resulted in identifying the best resource portfolios for meeting capacity needs. The input data and assumptions were provided in Section II of this report. The analysis process and action plan are explained in the remainder of this section.

Figure 7: IRP Process

Input Data Load Existing Unit New Unit Demand Energy Assumption Characteristics Characteristics Response Efficiency (Cadmus) (OG&E) (EIA, NREL) (Structure) (Frontier)

Fuel Prices Emissions Cost Scenarios Transmission Cost (OG&E, Ventyx) (Ventyx) (Ventyx) (SPP, OG&E)

Analysis Process

• Develop Screen supply side resources Distinct • Portfolio Development Portfolios

• Analyze portfolio cost in expected case, Portfolio Cost four Ventyx scenarios, and sensitivities Analysis

• Analyze impact of changes to inputs Risk Evaluation

• Determine how options perform in SPP Market Market Evaluation

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B. Analysis Process 1. Develop Distinct Portfolios The portfolios analyzed in the IRP represent the possible resources OG&E can use to meet capacity needs over the study period. These portfolios include a wide range of resources to ensure a comprehensive set of portfolios were analyzed. a) Screening Process The first step in developing portfolios is to decide which resources should be considered for analysis. OG&E utilized the Annual Energy Outlook 2009, prepared by the EIA, for identifying potential supply side resources. OG&E then established four requirements for selecting supply side resource options to analyze. These supply side resource options and selection requirements are illustrated below in Table 33 and explained in the following subsections. Only resources that meet all requirements were selected.

Table 33: New Supply Side Resource Option Screening Requirements New Supply Side Total Cost / Proven Cost/ Public Resource Options MW kW Technology Scale Sentiment

Advanced CC 400 $1,142

Advanced CC with CCS 400 $2,276

Advanced CT 230 $764

Biomass 80 $4,534

Combined Cycle (CC) 250 $1,158

Combustion Turbine (CT) 160 $807

Fuel Cells 10 $6,454

Hydropower 500 $2,700

IGCC 550 $2,864

IGCC With CCS 380 $4,209

Landfill Gas 30 $3,062

Nuclear 1,350 $3,994

Photovoltaic (Solar) 5 $7,270

Scrubbed Coal 600 $2,478

Solar Thermal 100 $6,045

Wind 50 $2,316 – Meets requirement

(i) Proven Technology In addition to providing construction and operating costs associated with the potential supply side resources, the Annual Energy Outlook 2009 also discusses how some technologies are more developed than others. For example, while carbon capture and sequestration is discussed as a solution to reduce CO2 emissions, repeated utility scale facilities have not been developed and operated. Therefore this technology is not considered proven and is not included in a resource portfolio.

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(ii) Cost/Scale The second requirement considers the cost and scale of the supply side option. The Photovoltaic solar option has a cost of $7,270/kW. This is significantly more expensive than any other renewable or baseload resource option; therefore it would not be a prudent addition to a portfolio. Likewise, the generating output for Landfill gas is less than what OG&E would need to meet system load growth and provide baseload energy. While these technologies may provide business development opportunities in the future, they will not be included in a 30 year plan until more information is available. (iii) Public Sentiment Several proposed coal fired generating units have received considerable opposition from environmental groups and the general public. Furthermore, the permitting of these coal plants has experienced resistance and there is no evidence that these trends will change in the future. For this reason, OG&E has decided not to consider coal fired generating units in this resource plan. b) Portfolio Development Considering the screening requirements for new supply side resources, two resource options were used to develop portfolios: Natural Gas Combined Cycle and Nuclear.

As shown in the Needs Assessment section of this report, OG&E does not need to add capacity for the next twelve years. The following resource additions will meet capacity needs for the years of 2022 through 2032:

1. Combined cycle units in 2022 and 2027. 2. Combined cycle units in 2022 and 2027, and convert the existing coal fired steam units to gas. This portfolio was developed to achieve additional greenhouse gas emission reductions. 3. Joint venture nuclear units in 2022 and 2027.

The specific timing of the units installed in each portfolio is shown in Table 34. All portfolios are the same after 2027 with the addition of joint venture nuclear plants in 2033 and 2038.

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Table 34: Resource Portfolios Portfolio 1 2 3 Short Name CC Convert Nuclear Natural Gas Convert Existing Coal to Natural Nuclear Combined Cycles Gas & New Combined Cycles 152MW Keenan 152MW Keenan 152MW Keenan 2011 130MW Taloga 130MW Taloga 130MW Taloga 2012 300MW Wind 300MW Wind 300MW Wind 2013 2014 2015 2016 150MW Wind 150MW Wind 150MW Wind 2017 150MW Wind 150MW Wind 150MW Wind 2018 150MW Wind 150MW Wind 150MW Wind 2019 150MW Wind 150MW Wind 150MW Wind 2020 150MW Wind 150MW Wind 150MW Wind 2021 150MW Wind 150MW Wind 150MW Wind 150MW Wind 150MW Wind 150MW Wind 2022 500MW NG CC 500MW NG CC 500MW JV Nuclear 2023 Convert Sooner 1 150MW Wind 150MW Wind 150MW Wind 2024 Convert Sooner 2 Convert Muskogee 4 2025 Convert Muskogee 5 2026 Convert Muskogee 6 2027 500MW NG CC 500MW NG CC 500MW JV Nuclear

2. Portfolio Analysis The following section describes the process and results of the analysis of the portfolios in each of the five planning scenarios and six price sensitivities. a) Planning and Risk Model The Ventyx Planning and Risk program is utilized to calculate production cost and risk for comparing portfolios. Below is a description of Planning and Risk from the user manual:

The Planning and Risk Management™ solution is a portfolio management tool used to analyze, report, and actively manage your energy market assets, including power plants, customer loads, fuels, and contractual positions. Planning and Risk allows for comprehensive description of energy assets and markets, and can be used to estimate the optimal dispatch of a generation portfolio against either a market price or a load requirement.

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OG&E enters the input data into the PAR model and conducts analysis over a thirty year test period (2010-2039). b) Operating Cost The operating cost includes the total cost of fuel, purchase power, variable production costs, fixed operations and maintenance cost, cost associated with emission of greenhouse gases, and revenue from the sale of SO2 and renewable energy credits. The 30-year NPV of the operating cost for the three portfolios in each of the planning scenarios and sensitivities is shown in Table 35. The scenario analysis changes multiple variables at the same time. Sensitivity analysis changes only one variable in order to determine how sensitive each portfolio is to a single variable.

Table 35: 30-Year NPV of Operating Cost In Billions CC Convert Nuclear Expected $ 25.7 $ 26.5 $ 23.6 Global Economy $ 29.4 $ 30.8 $ 28.7 Global Turmoil $ 32.7 $ 34.7 $ 29.2 Return to Reliability $ 31.2 $ 31.3 $ 28.7 Technology Evolution $ 23.2 $ 24.7 $ 20.9 2 x CO₂ $ 30.8 $ 30.5 $ 28.2 2 x Natural Gas $ 36.5 $ 38.7 $ 32.5 2 x Coal $ 30.4 $ 29.9 $ 28.2 ½ x CO₂ $ 23.0 $ 25.8 $ 21.1 ½ x Natural Gas $ 20.1 $ 19.3 $ 18.9 ½ x Coal $ 23.6 $ 24.1 $ 21.5 c) Capital Cost A similar analysis is conducted for the capital cost associated with each portfolio. Table 36 shows capital costs which include the cost of environmental improvements on existing plants, additional wind to meet the RES, and each portfolio’s individual unit additions or conversions.

Table 36: 30-Year NPV of Capital Cost In Billions CC Convert Nuclear Expected $ 4.3 $ 4.3 $ 6.1 High $ 6.8 $ 6.9 $ 13.0 Low $ 3.8 $ 3.8 $ 5.4 d) Total Revenue Requirement The operating costs are added to the expected capital costs to show the total revenue requirement for each option, as shown in Table 37.

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Table 37: 30-Year NPV of Revenue Requirement In Billions CC Convert Nuclear Expected $ 30.0 $ 30.8 $ 29.7 Global Economy $ 33.7 $ 35.1 $ 34.8 Global Turmoil $ 37.0 $ 39.0 $ 35.3 Return to Reliability $ 35.5 $ 35.6 $ 34.8 Technology Evolution $ 27.5 $ 29.0 $ 27.0 2 x CO₂ $ 35.1 $ 34.8 $ 34.3 2 x Natural Gas $ 40.8 $ 43.0 $ 38.6 2 x Coal $ 34.7 $ 34.2 $ 34.3 ½ x CO₂ $ 27.3 $ 30.1 $ 27.2 ½ x Natural Gas $ 24.4 $ 23.6 $ 25.0 ½ x Coal $ 27.9 $ 28.4 $ 27.6

3. Risk Evaluation The previous section outlined the cost associated with each portfolio for the planning scenarios and price sensitivities. This section evaluates the risks of each portfolio. a) Scenario Analysis Table 38 shows the performance of each portfolio in the five planning scenarios. This comparison utilizes a 30-year, levelized dollar per megawatt-hour operating cost as the metric which accounts for the difference in timing and magnitude of capital costs.

Table 38: Scenario Analysis Results, 30-Year Levelized $/MWh In $/MWh CC Convert Nuclear Expected $ 73.26 $ 75.61 $ 67.89 Global Economy $ 86.33 $ 92.11 $ 86.68 Global Turmoil $ 88.61 $ 93.18 $ 80.33 Return to Reliability $ 83.65 $ 83.47 $ 77.82 Technology Evolution $ 66.73 $ 70.22 $ 60.87

b) Sensitivity Analysis OG&E evaluates sensitivity by analyzing how changes to a single variable impact total cost. Ranking these changes then allows OG&E to see which variable has the largest impact on each portfolio, and which portfolio is the most sensitive to input changes. The charts in Figure 8 show the change in total cost caused by each variable.

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Figure 8: Sensitivity Analysis Results, 30-Year Levelized $/MWh

$60 $70 $80 $90 $100 $110 $120 $130

Gas $69 $115

CO2 $78 $100 CC Coal $79 $99

Capital $84 $91

$60 $70 $80 $90 $100 $110 $120 $130

Gas $67 $121

CO2 $85 $98 Convert Coal $80 $98

Capital $86 $94

$60 $70 $80 $90 $100 $110 $120 $130

Gas $71 $110

Capital $83 $103 Nuclear Coal $78 $98

CO2 $77 $97

4. SPP Market Analysis The SPP consists of 16 balancing authorities who are responsible for maintaining the load-resource balance within their area. As a balancing authority, OG&E is required to

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make sure that adequate generating resources are committed and dispatched to serve the load in the OG&E area12.

On April 28, 2009, the SPP Board of Directors approved an action plan to develop and implement a Day Ahead Market (DAM) for energy and ancillary services. This involves the SPP administering a consolidated balancing authority with unit commitment and dispatch responsibilities. In a consolidated balancing authority, all generating resources in the SPP will be committed and dispatched to meet the load of the entire SPP region while considering transmission limitations to manage system congestion. Studies13 have shown this will provide a more efficient dispatch of resources resulting in cost savings for OG&E customers.

This will impact the daily operation of OG&E’s generation resources, and therefore their operating costs. To capture the impact of the DAM on the portfolios, a market analysis was completed using the PROMOD market simulation tool. The Ventyx PROMOD program is used to calculate production cost through a security constrained economic dispatch for the entire SPP.

This analysis is intended to be a high level, general impact study of the DAM on the three portfolios developed. This process is described below, but forecasting expansion of this scale introduces significant uncertainty to the study. a) Market Structure The Market Working Group of the SPP is in the process of developing the detailed structure of the DAM, and there are still many operational details to be resolved. The market analysis done for this resource plan assumes the DAM will be operational on January 1, 2015, and the study period will cover the first 10 years of the market through 2024. This allows for the impact of the market to be seen on the first resource added in each portfolio. b) Transmission Model The transmission model used in this study began with the 2008 series of the STEP model for the year 2019. Projects from the Balanced Portfolio and Cluster studies, as well as projects needed to deliver the 20% RES and additional generation resources for each portfolio, were added. c) Generation Expansion Ventyx provides generator characteristics for all existing units in the SPP through the MarketVision database. This data includes future units which are currently under construction and will be in service by 2014. To meet SPP planning capacity margin requirements through 2024, additional units are required. Wood-Mackenzie forecasts generation expansion for the SPP, and this information was used to determine the type

12 There are generating resources and loads in the OG&E balancing area that are not owned or served by OG&E. 13 http://www.spp.org/publications/Economies_of_Scale_Market_Benefits.pdf

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and amount of generation added. Table 39 shows the generation expansion for the SPP as forecast by Wood-Mackenzie.

Table 39: SPP Generation Expansion (MW) Resource Type 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 Nuclear 0 0 0 0 0 0 0 0 0 0 Coal 0 0 0 0 500 0 0 500 0 0 IGCC Coal 0 0 0 0 0 500 0 0 0 500 Gas CC 0 1,000 1,000 1,000 1,000 500 1,000 500 1,000 500 Gas Peaking 0 100 300 300 200 100 300 500 200 100 Total SPP 0 1,100 1,300 1,300 1,700 1,100 1,300 1,500 1,200 1,100

d) Results The portfolios analyzed in the DAM are the same portfolios analyzed in the Resource Plan section; therefore the operating costs are the only costs that will change. In Table 40, the operating costs of the portfolios in the DAM are compared to the operating costs for the local (OG&E only) dispatch from the PAR analysis.

Table 40: 10-Year NPV of Operating Costs in DAM In Billions CC Convert Nuclear OG&E 14.9 14.9 14.6 DAM 13.5 13.7 12.7

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IV. SCHEDULES

This section is intended to provide a tabular summary of each section as described in the Commission’s Rules, Subchapter 37 of Chapter 35, section 4 (c).

Schedule A – Electric Demand and Energy Assumption This schedule is the electric demand and energy sales assumptions provided by the Cadmus Group in August, 2009. Details of these assumptions can be found in the Electric Demand and Energy Forecast section on page 5.

Demand (MW) 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 MUNICIPAL 9.0 11.2 0.0 0.0 ------

FERC COOPERATIVE 230.9 238.0 0.0 0.0 ------Load SPA 17.8 7.4 0.0 0.0 ------without OMPA PSA 25.0 25.0 25.0 25.0 ------Losses MDEA 20.0 20.0 20.0 10.0 ------Total FERC Load 302.7 301.6 45.0 35.0 ------Losses 26.2 26.1 3.9 3.0 ------Total FERC Load (with losses) 328.9 327.7 48.9 38.0 ------Growth Rate 0.57% -0.4% -85% -22% -100% 0% 0% 0% 0% 0% Total Retail Load with losses 5,706.6 5,779.0 5,850.5 5,975.1 6,070 6,176 6,265 6,386 6,488 6,596 Growth Rate 0.77% 1.27% 1.24% 2.13% 1.58% 1.76% 1.43% 1.93% 1.60% 1.66% Load Responsibility 6,035 6,107 5,899 6,013 6,070 6,176 6,265 6,386 6,488 6,596 Growth Rate 0.76% 1.18% -3.4% 1.93% 0.94% 1.76% 1.43% 1.93% 1.60% 1.66%

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Energy Sales (MWh) 2010 2011 2012 2013 2014 MUNICIPAL 33,368 31,082 5,125 - - AVEC 1,011,175 953,837 - - - FERC Sales SPA 79,029 33,012 12,048 - - without OMPA 219,000 219,000 219,000 219,000 - losses MDEA 122,640 122,640 109,498 70,072 23,357 Total FERC Sales 1,465,213 1,359,570 345,671 289,072 23,357 Growth Rate 0.65% -7.2% -75% -16% -92% Residential 9,044,847 9,172,778 9,331,941 9,539,616 9,749,229 Commercial 6,616,523 6,718,032 6,877,941 7,076,997 7,274,072 Retail Industrial 4,052,242 4,097,286 4,160,398 4,212,353 4,239,954 Sales Industrial Petroleum 2,680,556 2,688,637 2,684,692 2,687,789 2,694,580 without losses Total Industrial 6,732,798 6,785,923 6,845,090 6,900,143 6,934,534 Public Authority and Lighting 2,950,357 3,034,294 3,121,810 3,208,779 3,290,748 Total Retail Sales 25,344,525 25,711,026 26,176,782 26,725,534 27,248,583 Growth Rate 0.87% 1.45% 1.81% 2.10% 1.96% Total Retail Sales + FERC 26,809,737 27,070,596 26,522,453 27,014,606 27,271,941 Losses 1,874,001 1,892,235 1,853,919 1,888,321 1,906,309 Total Retail Sales + FERC + Losses 28,683,738 28,962,831 28,376,372 28,902,927 29,178,249 Growth Rate 0.86% 0.97% -2.0% 1.86% 0.95% Energy Sales (MWh) 2015 2016 2017 2018 2019 MUNICIPAL - - - - - AVEC - - - - - FERC Sales SPA - - - - - without OMPA - - - - - losses MDEA - - - - - Total FERC Sales - - - - - Growth Rate -100% 0% 0% 0% 0% Residential 9,955,280 10,163,308 10,363,577 10,566,713 10,780,067 Commercial 7,471,906 7,672,188 7,863,345 8,057,675 8,260,967 Retail Industrial 4,271,401 4,307,122 4,346,324 4,388,764 4,439,681 Sales Industrial Petroleum 2,713,225 2,739,955 2,758,190 2,776,070 2,796,844 without losses Total Industrial 6,984,626 7,047,077 7,104,513 7,164,834 7,236,525 Public Authority and Lighting 3,380,746 3,473,356 3,562,116 3,654,566 3,751,771 Total Retail Sales 27,792,558 28,355,929 28,893,551 29,443,788 30,029,331 Growth Rate 2.00% 2.03% 1.90% 1.90% 1.99% Total Retail Sales + FERC 27,792,558 28,355,929 28,893,551 29,443,788 30,029,331 Losses 1,942,700 1,982,079 2,019,659 2,058,121 2,099,050 Total Retail Sales + FERC + Losses 29,735,257 30,338,008 30,913,210 31,501,909 32,128,381 Growth Rate 1.91% 2.03% 1.90% 1.90% 1.99%

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Schedule B – Existing Resources This schedule provides a summary of existing supply and demand side resources. Details on this data can be found in the Existing Resources section on page 9.

OG&E Generation Resources First Expected Max Full Load Variable Fixed O&M Year In Life Capacity Heat Rate O&M (2010 (2010 $/ Unit Type Unit Name Service (Years) (MW) (Btu/kWh) $/MWh) kW-yr) Muskogee 4 1977 >30 477 10,443 1.29 23.35 Muskogee 5 1978 >30 517 10,415 1.29 20.82 Coal Fired Muskogee 6 1984 >30 502 10,106 1.29 20.37 Steam Sooner 1 1979 >30 522 9,994 0.99 22.32 Sooner 2 1980 >30 524 10,187 0.99 20.87 Subtotal Capacity 2,542 Horseshoe Lake 6 1958 >30 172 10,089 1.61 13.6 Horseshoe Lake 8 1968 >30 380 10,157 1.61 6.64 Muskogee 3 1956 >30 171 10,486 1.59 9.78 Mustang 1 1950 >30 54 11,725 1.59 12.5 Mustang 2 1951 >30 50 11,725 1.59 13 Gas Fired Mustang 3 1955 >30 113 10,497 1.59 7.2 Steam Mustang 4 1959 >30 251 10,124 1.59 3.56 Seminole 1 1971 >30 506 10,568 1.08 8.54 Seminole 2 1973 >30 494 10,215 1.08 9.37 Seminole 3 1973 >30 502 9,996 1.08 9.47 Subtotal Capacity 2,693 Horseshoe Lake 7 1963 >30 227 9,590 1.61 10.21 Combined McClain* 2001 >30 363 6,900 2.63 10.98 Cycle Redbud* 2004 >30 601 7,420 2.4 10.82 Subtotal Capacity 1,191 Enid 1GT 1965 >30 11 17,417 2.95 1.77 Enid 2GT 1965 >30 11 17,417 2.95 1.77 Enid 3GT 1965 >30 11 17,417 2.95 1.77 Enid 4GT 1965 >30 11 17,417 2.95 1.77 Horseshoe Lake 9 2000 >30 45 9,945 1.61 41.81 Combustion Horseshoe Lake 10 2000 >30 45 9,945 1.61 41.81 Turbine Seminole 1GT 1971 >30 17 16,000 6.28 1.18 Mustang 5A 1971 >30 32 15,432 1.59 7.44 Mustang 5B 1971 >30 32 15,432 1.59 7.44 Woodward 1963 >30 10 16,000 4.11 1.93 Subtotal Capacity 225 Centennial 2007 >30 4 N/A 0 30.89 Wind OU Spirit 2009 >30 5 N/A 0 24.29 Subtotal Capacity 9

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First Expected Max Full Load Variable Fixed O&M Year In Life Capacity Heat Rate O&M (2010 (2010 $/ Unit Type Unit Name Service (Years) (MW) (Btu/kWh) $/MWh) kW-yr) AES Shady Point 1991 >30 320 N/A N/A N/A PowerSmith 1998 >30 120 N/A N/A N/A Purchase FPL Wind 2003 >30 2 N/A N/A N/A Power SPA Hydro N/A >30 17 N/A N/A N/A Subtotal Capacity 459 Total 7,119 * Represents OG&E owned interest

2008 Demand Response Performance Energy Peak Period Program Reduction Demand Program Name Initiated (MWh) Reduction (MW) Event Curtailment Rider (CR-1) 1997 No Events No Events Based Interruptible Rider (IR-1) 1997 No Events No Events Demand Performance Award for Curtailed 2003 No Events N/A Response Energy (PACE-1) Residential - Time of Use 1985 577.9 1.09 General Service – Time of Use 1986 1,720.8 1.93 Price Power and Light – Time of Use 1985 17,621.0 16.06 Response Public Schools – Demand* 2007 389.0 0.37 Programs Public Schools – Non Demand* 2007 19.1 0.13 Oil & Gas Producers 1997 0.7 0.01 Real Time Pricing (RTP)-DAP 1996 N/A 24.20 * Includes two tariffs: Standard TOU and Compressed TOU

Oklahoma Energy Efficiency Savings 2008 Actual 2009 Estimated Quick Start Program Energy (kWh) Demand (kW) Energy (kWh) Demand (kW) Residential Weatherization 370,000 93 3,164,599 891 LivingWise® 60,588 6 276,262 29 Custom Energy Report 2,355,584 765 7,101,044 2,705 Education 0 0 0 0 Compact Fluorescent Lights 215,498 26 1,266,984 169 Commercial Lighting 942,315 317 16,719,614 4,677 Motor Replacement 67,462 8 704,405 116 Total 4,011,447 1,215 29,232,934 8,587

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Arkansas Energy Efficiency Savings 2008 Actual 2009 Estimated Quick Start Program Energy (kWh) Demand (kW) Energy (kWh) Demand (kW) Weatherization 147,600 41 464,593 178 LivingWise 333,060 37 242,743 27 Residential Energy Audit 727,804 284 1,357,595 489 Education 0 0 0 0 Compact Fluorescent Lights 0 0 689,962 854 Commercial Lighting 1,215,394 301 1,623,058 449 Motor Replacement 10,880 4 72,553 26 Total 2,434,738 667 4,450,504 2,023

Schedule C – Transmission Capability and Needs This schedule provides a description of the OG&E transmission system as described in the Transmission Resources section on page 21. A map of the OG&E transmission system is available upon request.

OG&E Transmission Lines Voltage Miles 500kV 47 345kV 790 161kV 193 138kV 1,845 69kV 1,468 Total 4,343

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Schedule D – Needs Assessment This schedule provides a description of the capacity needs as described in the Needs Assessment section on page 32.

MW 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Owned Capacity 6,660 6,660 6,660 6,660 6,659 6,659 6,659 6,659 6,659 6,659 Resources Purchase Contracts 459 449 442 442 442 442 442 442 442 442 Total Capacity 7,119 7,109 7,102 7,102 7,101 7,101 7,101 7,101 7,101 7,101 Forecast 6,035 6,107 5,899 6,013 6,070 6,176 6,265 6,386 6,488 6,596 Load Curtailment 142 144 146 149 151 154 156 159 161 164 Demand New Energy Efficiency 13 26 38 38 38 36 34 32 32 32

Net On System Demand 5,880 5,937 5,715 5,826 5,881 5,986 6,075 6,195 6,295 6,400 Needed Capacity 0 0 0 0 0 0 0 0 53 172 Capacity Capacity Margin 1,239 1,172 1,387 1,276 1,220 1,115 1,026 906 806 701 Needs Capacity Margin (%) 17 16 20 18 17 16 14 13 11 10 Load Reserve Margin (%) 21 20 24 22 21 19 17 15 13 11

Demand Forecasted DR 0 2 74 148 226 236 245 256 269 270 Response Net On System Demand 5,880 5,935 5,641 5,678 5,655 5,750 5,830 5,939 6,026 6,130 Capacity Needed Capacity 0 0 0 0 0 0 0 0 0 0 Needs Capacity Margin 1,239 1,174 1,461 1,424 1,446 1,351 1,271 1,162 1,075 971 with Demand Capacity Margin (%) 17 17 21 20 20 19 18 16 15 14 Response Load Reserve Margin (%) 21 20 26 25 26 24 22 20 18 16

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Schedule E – Resource Options This schedule provides a description of the supply, demand side, and transmission options available to OG&E to address the needs identified in Schedule D.

New Supply Side Resources Size Capital Cost Variable O&M Fixed O&M Heat rate Technology (MW) ($/kW) ($/MWh) ($/kW-yr) (Btu/kWh) Advanced CC with CCS 400 2,276 3.01 20.34 8,613 Advanced CT 230 764 3.24 10.76 9,289 Advanced CC 400 1,142 2.04 11.96 6,752 Biomass 80 4,534 6.86 65.88 9,646 Fuel Cells 10 6,454 48.98 5.78 7,930 Hydropower 500 2,700 2.48 13.93 N/A IGCC 550 2,864 2.98 39.53 8,765 IGCC With CCS 380 4,209 4.54 47.14 10,781 Landfill Gas 30 3,062 0.01 116.78 13,648 Combustion Turbine (CT) 160 807 3.65 12.38 10,810 Combined Cycle (CC) 250 1,158 2.12 12.76 7,196 Nuclear 1,350 3,994 0.50 92.01 10,434 Photovoltaic (Solar) 5 7,270 0.00 11.94 N/A Scrubbed Coal 600 2,478 4.69 28.14 9,200 Solar Thermal 100 6,045 0.00 58.04 N/A Wind 50 2,316 0.00 30.97 N/A

New Wind Resources NREL Capacity Potential Site Site ID Location Factor (%) Output (MW) 631 Ellis County, OK 42 1,291 754 Ellis County, OK 42 436 496 Ellis County, OK 43 301 365 Beaver County, OK 42 558 505 Comanche County, OK 44 1,031 239 Ford County, KS 43 334 342 Kiowa County, KS 42 577 390 Meade County, KS 42 520 173 Lipscomb County, TX 44 1,046

Total System Energy Efficiency 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Peak Reduction (MW) 13 26 38 38 38 36 34 32 32 32 Energy Savings (MWh) 51,175 101,027 149,173 149,173 149,173 147,256 145,007 142,758 142,426 139,404

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Demand Response Levels (MW) 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 DR - RTP 0 0 68 136 206 208 209 211 213 214 DA - IVVC 0 2 6 12 20 28 36 45 56 56 Total 0 2 74 148 226 236 245 256 269 270

Estimated Transmission Construction Cost for CC and Gas Conversion Options Total In Service Description Type Source (In Millions) 12/31/2012 New Line Woodward - Comanche County Wind SPP Cluster $ 107.10 12/31/2012 New Tatonga Sub Upgrade to 12 Breakers Wind SPP Cluster $ 15.00 12/31/2012 Upgrade Woodward Substation Wind SPP Cluster $ 15.00 12/31/2012 New Line Woodward 345 to Woodward 138kV Wind SPP Cluster $ 4.88 12/31/2013 New Line Woodward - Tatonga Wind SPP Cluster $ 84.00 12/31/2014 New Line Tatonga - Cimarron 345kV Wind SPP Cluster $ 104.50 12/31/2014 GEN07-043 - Cimarron 345kV ckt 1 Wind SPP Cluster $ 0.25 12/31/2014 Sunnyside - LES 345kV ckt 1 Wind SPP Cluster $ 0.50 12/31/2014 New Line Comanche - Medicine Lodge 345kV ckt 1 Wind SPP Cluster $ 60.00 12/31/2014 New Line Medicine Lodge - Wichita 345kV ckt 1 Wind SPP Cluster $ 90.00 12/31/18 Arcadia 345/138 Transformer (Install 3rd Transformer) CC OG&E $ 6.75 12/31/18 Upgrade McAlester Tap to McAlester RP CC OG&E $ 2.50 Total $ 490.48

Estimated Transmission Revenue Requirement for CC and Gas Conversion Options (In Millions) SPP OG&E SPP OG&E Year ATRR Allocation Year ATRR Allocation 2010 $ 0 $ 0 2025 $ 66 $ 17 2011 $ 0 $ 0 2026 $ 64 $ 16 2012 $ 2 $ 0 2027 $ 62 $ 16 2013 $ 26 $ 6 2028 $ 60 $ 15 2014 $ 43 $ 10 2029 $ 58 $ 15 2015 $ 84 $ 21 2030 $ 56 $ 14 2016 $ 82 $ 21 2031 $ 54 $ 14 2017 $ 80 $ 20 2032 $ 52 $ 13 2018 $ 79 $ 20 2033 $ 50 $ 13 2019 $ 78 $ 19 2034 $ 48 $ 12 2020 $ 76 $ 19 2035 $ 46 $ 12 2021 $ 74 $ 19 2036 $ 44 $ 11 2022 $ 72 $ 18 2037 $ 42 $ 11 2023 $ 70 $ 18 2038 $ 40 $ 10 2024 $ 68 $ 17 2039 $ 38 $ 10

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Estimated Transmission Construction Cost for Nuclear Option Total In Service Description Type Source (In Millions) 12/31/2012 New Line Woodward - Comanche County Wind SPP Cluster $ 107.10 12/31/2012 New Tatonga Sub Upgrade to 12 Breakers Wind SPP Cluster $ 15.00 12/31/2012 Upgrade Woodward Substation Wind SPP Cluster $ 15.00 12/31/2012 New Line Woodward 345 to Woodward 138kV Wind SPP Cluster $ 4.88 12/31/2013 New Line Woodward - Tatonga Wind SPP Cluster $ 84.00 12/31/2014 New Line Tatonga - Cimarron 345kV Wind SPP Cluster $ 104.50 12/31/2014 GEN07-043 - Cimarron 345kV ckt1 Wind SPP Cluster $ 0.25 12/31/2014 Sunnyside - LES 345kV ckt1 Wind SPP Cluster $ 0.50 12/31/2014 New Line Comanche - Medicine Lodge 345kV ckt 1 Wind SPP Cluster $ 60.00 12/31/2014 New Line Medicine Lodge - Wichita 345kV ckt 1 Wind SPP Cluster $ 90.00 12/31/18 Arcadia 345/138 Transformer (Install 3rd Transformer) Nuke OG&E $ 6.75 12/31/18 Reconductor L-642TP to LIVON Nuke OG&E $ 25.00 Total $ 512.98

Estimated Transmission Cost for Nuclear Option (In Millions) SPP OG&E SPP OG&E Year ATRR Allocation Year ATRR Allocation 2010 $ 0 $ 0 2025 $ 70 $ 17 2011 $ 0 $ 0 2026 $ 68 $ 16 2012 $ 2 $ 0 2027 $ 66 $ 16 2013 $ 26 $ 6 2028 $ 64 $ 15 2014 $ 43 $ 10 2029 $ 62 $ 15 2015 $ 84 $ 21 2030 $ 59 $ 14 2016 $ 82 $ 21 2031 $ 57 $ 14 2017 $ 80 $ 20 2032 $ 55 $ 13 2018 $ 79 $ 20 2033 $ 53 $ 13 2019 $ 78 $ 20 2034 $ 51 $ 12 2020 $ 80 $ 19 2035 $ 49 $ 12 2021 $ 78 $ 19 2036 $ 47 $ 11 2022 $ 76 $ 18 2037 $ 45 $ 11 2023 $ 74 $ 18 2038 $ 43 $ 10 2024 $ 72 $ 17 2039 $ 41 $ 10

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Schedule F – Fuel Procurement and Risk Management Plan On May 15, 2009, OG&E filed a Fuel Supply Portfolio and Risk Management Plan with the OCC as part of Cause No. PUD 200100095.

A summary of this plan is in the Existing Resources section on page 11.

Schedule G – Action Plan This schedule outlines the proposed actions for the next five years. These actions are in accord with this resource plan, and will position OG&E to complete the plan as described in this report. As described in the Needs Assessment section on page 32, the capacity additions from new wind, and demand reductions from DSM programs are a critical piece in completing the 2020 plan.

OG&E has already begun the process of adding wind generation. OG&E has taken ownership of the 101 MW OU Spirit wind facility. In addition, the OCC is currently reviewing OG&E’s proposal to add 280 MW of wind generation resulting from the 2008 RFP. These projects would be operational as of October 1, 2010, and January 1, 2011. OG&E plans to submit a RFP for an additional 300 MW of wind power in 2010. This RFP is expected to result in the additional wind resources being online by January 1, 2012. Schedule H provides information on this process.

Studies done by the SPP have identified many projects that will be constructed over the next five years, and OG&E plans to participate in this expansion. A list of the projects in the OG&E area is found in Schedule J.

OG&E plans to expand current DSM programs and offer new programs in both Oklahoma and Arkansas. The energy efficiency programs will continue as described in Cause No. PUD 200900200 filed with the OCC on September 15, 2009, and Docket No. 07-075-TF filed with the APSC on June 30, 2009. Details of these programs are in the Resource Options section on page 24. The demand response programs include expanding Smart Grid technology on the OG&E distribution system and in customers’ homes. In addition to demand reductions through DSM programs, OG&E will decrease peak demand through terminating existing wholesale contracts as they expire. This results in a reduction of load responsibility that is necessary to achieve the 2020 Plan.

The first table below summarizes the actions to reduce peak demand over the next 5 years. The second table summarizes the actions to increase system capacity. Due to these actions, OG&E will not need to add fossil fuel generation during the next 5 years, and is on track to achieve the goal of the 2020 plan.

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Actions to Reduce Peak Demand (MW) 2010 2011 2012 2013 2014 Forecast Peak Demand 6,035 6,108 6,179 6,304 6,399 Wholesale Contracts 0 1 280 291 329 Load Curtailment 142 144 146 149 151 Demand Energy Efficiency 13 26 38 38 38 Reductions DR - Smart Grid 0 0 68 136 206 DA - Capacitors 0 2 6 13 20 Total Reductions 155 173 538 627 744 Peak Demand 5,880 5,935 5,641 5,677 5,655

Actions to Increase Capacity (MW) 2010 2011 2012 2013 2014 Forecast System Capacity 7,114 7,104 7,097 7,097 7,096 OU Spirit – 101 MW 5 5 5 5 5 Capacity 2008 RFP – 280 MW 0 14 14 14 14 Additions 2010 RFP – 300 MW 0 0 15 15 15 Total Additions 5 19 34 34 34 System Capacity 7,119 7,124 7,131 7,131 7,130

Schedule H – Requests for Proposals In December, 2008, OG&E issued a request for proposals (RFP) for wind power. This request resulted in agreements reached in September, 2009 with two developers for 280 MW. These projects are: a 130 MW facility developed by Edison Mission Energy in Dewey County, OK, and a 150 MW facility developed by CPV Keenan in Woodward County, OK. Both contracts are currently being considered by the OCC. Details on this RFP and a description of the process used can be found at:

http://www.oge.com/about/DoingBusinessWithOGE/RFPs/Pages/2008WindRFP.aspx

OG&E has plans to issue a RFP for additional wind power in 2010. The procurement process for these resources will be the same that was used in the 2008 RFP, and is pursuant to OAC 165:35-34-3.

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Schedule I – Modeling Methodology and Assumptions This schedule is a technical appendix for the data, assumptions, and descriptions of models needed to understand the derivation of the resource plan.

The table below explains who supplied each assumption and provides a reference for where this information is found in the IRP. Since the load assumption was provided in Schedule A, it has not been repeated here.

Assumption Source Page Load The Cadmus Group, Inc. 5 Natural Gas Ventyx 36 Coal OG&E, Ventyx 36

CO2 Ventyx 36

SO2 Ventyx 36

Natural Gas Coal CO2 SO2 Natural Gas Coal CO2 SO2 Year ($/MMBtu) ($/MMBtu) ($/tonne) ($/ton) Year ($/MMBtu) ($/MMBtu) ($/tonne) ($/ton) 2010 5.75 1.81 - 441 2025 9.43 3.21 37.33 436 2011 6.40 1.91 - 556 2026 10.14 3.31 40.14 428 2012 6.35 2.09 10.18 694 2027 11.10 3.42 43.16 419 2013 6.65 2.17 12.51 725 2028 12.01 3.55 46.39 339 2014 7.25 2.27 15.14 775 2029 13.31 3.69 49.88 275 2015 7.88 2.33 18.08 764 2030 14.13 3.81 53.64 253 2016 8.55 2.38 19.44 708 2031 14.83 3.96 57.67 259 2017 9.06 2.49 20.91 604 2032 15.57 4.11 62.01 265 2018 9.58 2.54 22.47 551 2033 16.34 4.22 66.67 271 2019 9.84 2.61 24.17 526 2034 17.18 4.33 71.68 278 2020 9.69 2.71 25.98 505 2035 18.02 4.44 77.07 284 2021 9.45 2.80 27.94 495 2036 18.89 4.55 82.87 290 2022 8.37 2.94 30.04 485 2037 19.78 4.66 89.10 296 2023 8.36 3.04 32.28 475 2038 20.72 4.77 95.80 302 2024 8.71 3.14 34.72 466 2039 21.70 4.88 103.00 309

The table below explains who supplied the information for each resource option and provides a reference for where this information is found in the IRP.

Resource Source Page New Unit Characteristics EIA 22 Existing Unit Characteristics OG&E 9 New Energy Efficiency Frontier Associates 24 New Demand Response The Structure Group 28 Transmission Costs OG&E 33

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Descriptions of Models OG&E uses two modeling programs offered by Ventyx for developing an integrated resource plan. The Planning and Risk program provides the production cost along with risk analysis tools for evaluating resources. The PROMOD program performs a security constrained economic dispatch of the SPP to analyze the portfolio in a day-ahead energy market. Planning and Risk Below is a description from the Planning and Risk user manual:

“The Planning and Risk Management™ solution is a portfolio management tool used to analyze, report, and actively manage your energy market assets, including power plants, customer loads, fuels, and contractual positions. Planning and Risk allows for comprehensive description of energy assets and markets, and can be used to estimate the optimal dispatch of a generation portfolio against either a market price or a load requirement.”

PROMOD Below is a description from the PROMOD user manual:

“PROMOD IV is the ultimate in electric power system simulation. It is a comprehensive computer software package designed for use by utility planners to calculate system production cost and plant operation for the purposes of rate-case filings, integrated resource planning, Clean Air Act assessments, and similar decision-making situations. PROMOD IV is distinguished from other utility simulation programs by combining sophisticated generating unit commitment modeling with a fully integrated transmission analysis.”

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The following table describes when resources were put in service in each portfolio to meet capacity needs.

Portfolio 1 2 3 Short Name CC Convert Nuclear Natural Gas Convert Existing Coal to Natural Nuclear Combined Cycles Gas & New Combined Cycles 152MW Keenan 152MW Keenan 152MW Keenan 2011 130MW Taloga 130MW Taloga 130MW Taloga 2012 300MW Wind 300MW Wind 300MW Wind 2013 2014 2015 2016 150MW Wind 150MW Wind 150MW Wind 2017 150MW Wind 150MW Wind 150MW Wind 2018 150MW Wind 150MW Wind 150MW Wind 2019 150MW Wind 150MW Wind 150MW Wind 2020 150MW Wind 150MW Wind 150MW Wind 2021 150MW Wind 150MW Wind 150MW Wind 150MW Wind 150MW Wind 150MW Wind 2022 500MW NG CC 500MW NG CC 500MW JV Nuclear 2023 Convert Sooner 1 150MW Wind 150MW Wind 150MW Wind 2024 Convert Sooner 2 Convert Muskogee 4 2025 Convert Muskogee 5 2026 Convert Muskogee 6 2027 500MW NG CC 500MW NG CC 500MW JV Nuclear

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Schedule J – Transmission System Adequacy This schedule is a description of the transmission system adequacy over the study period.

The 2008 SPP Transmission Expansion Plan14 (STEP) is a result of SPP’s 2008 transmission planning activities. The plan describes improvements necessary for regional reliability, zonal reliability, long-term tariff studies due to transmission service requests and transmission owner sponsored improvements.

In the spring of 2009 SPP completed the first Balanced Portfolio Report. The Balanced Portfolio15 was an initiative to develop a group of economic transmission upgrades that benefit the entire SPP region, and to allocate those project costs regionally.

Included in below is a list of the projects from the 2008 STEP and the Balanced Portfolio that SPP has determined must be complete for reliability and economic purposes.

14 The 2008 STEP can be found at: http://www.spp.org/publications/2008_Approved_STEP_Report_Redacted.pdf

15 The SPP Balanced Portfolio Report can be found at http://www.spp.org/publications/2009%20Balanced%20Portfolio%20-%20Final%20Approved%20Report.pdf

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Estimated Capital Expenditures for OG&E Committed Projects Year Description Type of Upgrade Type Cost 2010 Northwest-Woodward 345 kV New Line and 2 new subs STEP $ 194,500,000 2010 Russett - WFEC Russett 138kV Substation Upgrade STEP $ 347,073 2010 Muldrow to 3rd St. 69 kV Substation Upgrade STEP $ 100,000 2011 Arkansas Conversion Convert from 69kv to 161 kV STEP $ 26,664,386 2011 Johnson County Project New Line and 345/138kV sub STEP $ 27,581,274 Dover-Twin Lake-Crescent-Cottonwood 2011 Convert 69kV line to 138kV STEP $ 4,500,000 conversion 138 kV 2011 Ardmore - Rocky Point 69KV CKT 1 Reconductor Line STEP $ 1,627,500 2011 Dillard - Healdton Tap 138KV CKT 1 Substation Upgrade STEP $ 300,000 2011 Sunnyside - Uniroyal 138KV CKT 1 Substation Upgrade STEP $ 50,000 2011 Bodle 138 kV Substation Upgrade STEP $ 1,476,650 Balanced 2011 Anadarko (Gracemont) New 345/138 kV Sub $ 8,000,000 Portfolio 2012 VBI-Adabell 161 kV New Tap for Adabell STEP $ 850,000 2012 Hugo - Sunnyside 345KV New Line STEP $ 120,000,000 Sunnyside 345/138/13.8KV 2012 Install 2nd Bus Tie Transformer STEP $ 6,750,000 Transformer CKT 1 2012 Rose Hill - Sooner 345 kV New Line STEP $ 68,000,000 Balanced 2012 Sooner - Cleveland 345 kV New Line $ 40,600,000 Portfolio 2013 Kilgore - VBI 69 kV Substation Upgrade STEP $ 10,000 Balanced 2013 Seminole - Muskogee 345 kV New Line $ 131,000,000 Portfolio Balanced 2014 Tuco to Woodward 345 kV line New Line $ 105,000,000 Portfolio 2016 HSL East - HSL West 69 kV Substation Upgrade STEP $ 250,000 Ft. Smith 500/161/13.8KV Transformer 2017 Substation Upgrade STEP $ 11,000,000 CKT 3 2017 VBI - VBI North 69KV CKT 1 Substation Upgrade STEP $ 100,000 Identified Future Projects Reliability, New Load, etc STEP $ 110,826,511 Total $ 859,533,394

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The SPP has a proposed cost allocation method to collect transmission owners’ revenue requirements from transmission customers. The table below represents OG&E’s estimate of total revenue requirements of the projects listed above along with OG&E’s customers’ portion of revenue requirements. This revenue requirements calculation is an estimate for IRP purposes and SPP will calculate the final revenue requirements.

Estimated Cost for OG&E Committed Projects (In Millions) SPP OG&E SPP OG&E Year ATRR Allocation Year ATRR Allocation 2010 $ 39 $ 35 2025 $ 111 $ 61 2011 $ 58 $ 50 2026 $ 107 $ 59 2012 $ 86 $ 68 2027 $ 104 $ 57 2013 $ 105 $ 76 2028 $ 100 $ 55 2014 $ 136 $ 80 2029 $ 97 $ 53 2015 $ 142 $ 79 2030 $ 93 $ 51 2016 $ 138 $ 77 2031 $ 90 $ 49 2017 $ 136 $ 75 2032 $ 86 $ 47 2018 $ 134 $ 73 2033 $ 82 $ 45 2019 $ 132 $ 73 2034 $ 79 $ 43 2020 $ 129 $ 71 2035 $ 75 $ 41 2021 $ 125 $ 69 2036 $ 72 $ 39 2022 $ 122 $ 67 2037 $ 68 $ 37 2023 $ 118 $ 65 2038 $ 65 $ 35 2024 $ 114 $ 63 2039 $ 61 $ 33

Schedule K – Resource Plan Assessment This resource plan assessed the need for additional resources to meet reliability, cost and price, environmental, and other criteria established by the Commission, the State of Oklahoma, the Southwest Power Pool, North American Electric Reliability Council, and the Federal Energy Regulatory Commission. All criteria were met by all portfolios considered in this resource plan, in the base line condition. These criteria were also met in scenarios and uncertainties which included variations in load growth, fuel prices, emissions prices, environmental regulations, technology improvements, demand side resources, and fuel supply, among others. This plan provides a comprehensive analysis of the proposed options.

Schedule L – Proposed Resource Plan Analysis This resource plan demonstrates that all proposed options meet all planning criteria as outlined in Schedule K. The proposed action plan and qualifying analysis outlined in Schedule G best meets these criteria. Documentation of the planning analysis and assumptions used in preparing this analysis are described in Schedule I.

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APPENDICES

Appendix A On December 14, 2009, pursuant to the Joint Stipulation and Settlement Agreement approved by the Oklahoma Corporation Commission in PUD200900167, OG&E held a stakeholder technical conference on the 2010 IRP. During this technical conference, OG&E delivered a presentation that explained the contents of and the analysis behind the draft 2010 IRP. The technical conference also provided an opportunity for interested stakeholders to ask questions and provide feedback on the draft 2010 IRP. The discussion, questions and feedback were recorded by an independent facilitator and circulated among the stakeholders in the form of meeting minutes (see, Appendix B).

In addition, pursuant to OAC 165:35-37-3 and after OG&E notified the Commission and other interested parties of the intention to submit this 2010 IRP, the Commission conducted a public meeting on January 21, 2010 to allow further public comments on the OG&E’s draft IRP. Prior to the public meeting both the Attorney General and the Oklahoma Industrial Energy Consumers (“OIEC”) circulated written comments on the draft 2010 IRP.

OG&E appreciates both the discussion at the technical conference and public meeting and appreciates the written comments provided by the Attorney General and the OIEC. While OG&E has considered all comments and questions, it does not conclude that any reasonable changes to the 2010 IRP are necessary. However, as described in OAC 165:35-37-4(b), OG&E recognizes its obligation to monitor markets and inputs that may materially change the Company’s plan, including, but not limited to the issues presented in the technical conference and public meeting. The company will submit interim updated plans if needed.

OG&E provides the following comments in response to some of the specific feedback from interested stakeholders:

• The 2010 IRP is premised on OG&E’s goal of avoiding any new fossil fuel generation before 2020. That is why we did not study any other supply portfolios between 2011 and 2021.

• In this IRP, the next resource to be added is 300MW of wind generation to be delivered in 2012. OG&E’s IRP dated February 2009, pages 52 through 55, analyzed OG&E’s generation portfolio with and without the addition of 300 MW wind generation in 2010 and an additional 300MW of wind generation in 2012. In addition, this IRP assumes that OG&E will actually or effectively be subject to a renewable portfolio standard which OG&E plans to meet with additional wind generation and energy efficiency. The assumption of additional 300MW wind

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generation by 2012 is significantly driven by the expiration of the production tax credits (which are set to expire at the end of 2012). OG&E recognizes the obligation to demonstrate that future resource additions are reasonable and prudent and will conduct that analysis at the time of application for any such resource.

• Transmission project descriptions and explanation of need (as provided by the SPP) were included in this IRP. The Transmission Needs section summarizes the SPP process for determining the transmission reliability and economic projects. Footnotes on pages 33 and 34 provide web addresses of both the SPP Transmission Expansion Plan (STEP) and the Balanced Portfolio Plan.

• This IRP incorporates OG&E’s September 2009 proposal to the ODEQ regarding compliance with the EPA’s Regional Haze rule, which addresses the regulation of visibility impairing emissions such as SO2 under the federal Clean Air Act. The Regional Haze section starting on page 39 provides an explanation of this issue. OG&E is currently negotiating with the ODEQ to reach a solution that avoids the installation of expensive scrubber technology and minimizes costs to customers. Any agreement with DEQ will be reflected in the Oklahoma State Implementation Plan which will be subject to approval by the EPA. OG&E has the option of seeking a legal remedy if it disagrees with the final EPA determination. Future IRP plans will incorporate the outcome of this process.

OG&E recognizes that the development and construction of a nuclear project by 2022 will require a significant amount of time and resources and OG&E must decide within the next few years whether to pursue this option. OG&E will continue to monitor costs associated with the development and operation of nuclear facilities. For example, OG&E has already analyzed the sensitivity associated with a 300% increase in costs of nuclear capital projects, which has increased the estimated cost to approximately $12,000/kW (in 2010 dollars). This analysis can be found in the Sensitivity Analysis section on page 49 of the OG&E IRP. OG&E will also continue to monitor federal and state legislation and regulation that may impact the feasibility of a nuclear project.

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Appendix B OGE 2010 IRP Oklahoma Technical Conference December 14, 2009 Meeting Documentation

1. Introduction Pursuant to an agreement reached in the Commission-approved joint stipulation and settlement agreement in the OU Spirit docket (Cause No. PUD 200900167). The stipulation reads in relevant part: For purposes of OGE’s January 2010 IRP submittal, the Stipulating Parties further agree that OGE will, in addition to any requirements of OAC 165:35-37-3, hold a collaborative technical conference for all stakeholders during the first two weeks of December 2009 in order to allow all stakeholders the opportunity to review and provide input at that technical conference regarding utility objectives, assumptions, and planning scenarios contained in the draft IRP.

OGE provided a copy of its draft IRP filing on December 7, 2009 in order to provide stakeholders with an opportunity to review the filing before the stakeholder meeting. OGE also provided copies of the presentation relied upon by OGE to review its IRP. As both documents contained confidential materials, they were issued subject to a protective agreement that had to be signed by stakeholders.

The meeting was held on December 14, 2009 in OGE’s offices. Several stakeholders participated by teleconference. The participants were: • OGE: Leon Howell, Kimber Shoop, Bill Bullard, Roger Walkingstick, Phil Bartholomew, Bob Koenig, Zac Hager, Michael Collins, Ronda Redden, Bill Wilkerson • Commission Staff: Fairo Mitchell, Karen Forbes, Joel Rodriguez, Nicholas • Attorney General: Dan Peaco • OIEC: Tom Schroedter, Mark Garrett, Scott Norwood • AES Shady Point: Kendall Parish • Walmart: Rick Chamberlain • Chermac: Rick Goodwin • Other: Deborah Thompson • OGE Shareholders: Ron Stakem

The meeting was divided into two segments. The first part focused on a presentation that was made by Leon Howell, OGE’s Manager, Resource Planning. Stakeholders were encouraged to ask clarifying questions throughout the presentation. The second part of the meeting was devoted to stakeholder feedback on OGE’s IRP, based on their review of the draft IRP and OGE’s presentation and responses to stakeholder questions.

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The meeting notes that follow incorporate the presentation materials, followed by a summary of questions by stakeholders and the OGE response.

The meeting began with an introduction by OGE, introduction of the participating stakeholders and brief comments on the conduct of the meeting by the facilitator.16 The facilitator indicated that he would prepare and distribute meeting notes to the stakeholders and provide an opportunity to offer improvements to these notes. These improvements have been reflected in the notes.

2. OGE Presentation and Questions

A. OGE’s 2020 Plan

• OGE made a strategic decision to not add any fossil fuel generation until 2020 and will accomplish this by reducing demand and adding renewable generation • OGE has already taken steps toward this goal including filing of energy efficiency plan with the OCC, termination notices to wholesale customers, and negotiations with wind developers

16 The meeting was facilitated by Robert C. Yardley, Jr. a former regulator and Executive Advisor to Concentric Energy Advisors. Mr. Yardley has provided advise to OGE on the development of its recent IRP filings.

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B. Load Forecast and Demand Reductions

• Economic downturn and termination of wholesale contracts have reduced our load forecast. Relative to the February 2009 IRP, the economic downturn has reduced our load forecast by approximately 100 MW. • All wholesale contracts are to be terminated by 2014 • OGE commissioned studies by Frontier and Structure to develop DSM forecasts • Demand reduction comes from expansion of existing programs and from new programs

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Questions: • Is the cost of the Smart Grid deployment included in the IRP? o No. OGE is developing a Smart Grid business case that will provide all of the costs and benefits of Smart Grid, including portfolio costs and benefits.

• Do the DSM forecasts reflect the reduction in peak demand associated with these programs? o Yes.

• Has OGE reevaluated its plans to terminate its wholesale contracts in light of its efforts to satisfy regional haze requirements? o No. C. Fuels and Emissions Price Forecasts

NOTE: the OGE presentation slide presenting these inputs contains confidential information and is not included in the meeting notes.

• OGE relies on Ventyx for fuel and emission price forecasts and scenarios

Questions: • The environmental regulatory regime will not be clear until legislation is passed. Does the IRP assume that a market for CO2 will be established in 2012? o Yes.

• Does OGE address this uncertainty through scenario analyses? o Yes. Scenarios have been designed to reflect a later effective date for CO2 markets as well as the potential that climate change legislation will not be enacted during the forecast period.

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D. Renewable Energy Standards

• OGE believes there will be a federal RES, similar to what has been proposed in ACES, and this is reflected in the IRP (20% by 2021). • OGE will be ahead of the standard in the early years and need to add wind later in the period

Questions: • Has OGE examined the impact of not adding wind in order to meet the RES? o No. All of the model runs assume that OGE must meet the assumed RES requirements.

• Is the RES modeled based on the Waxman-Markey bill? o The RES reflects the Waxman-Market bill, but it is not an exact representation.

• Does the ramping up of wind resources reflect the bill, or is it an assumed ramp up to meet the 2021 20% renewable energy target? o The House Bill incorporates ramping language and the assumptions are modeled after the bill.

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E. Regional Haze

• OGE is required to comply with a regional haze rule to remove any man-made impact to visibility in national parks and wilderness areas. • OGE has modeled a Best Available Retrofit Technology (BART) to determine how to respond to the regional haze rule, focusing on two pollutants: SO2 and NOx. • The Oklahoma DEQ has accepted OGE’s proposal to install low-NOx combustion technology at Sooner 1 and 2, Muskogee 4 and 5, and Seminole 1, 2, and 3. • OGE has modeled an “alternative plan” that it has made to the Oklahoma DEQ and the EPA that would satisfy regional haze BART requirements by limiting the dispatch of its coal units, rather than adding scrubbers. • The scrubbers are cost prohibitive for OGE because of the high capital costs (estimated at $1.5 billion) and incremental annual O&M costs of $150 million. • OGE is also concerned about the potential impact of CO2 legislation on its coal units. • One factor driving the economic evaluation of scrubbers is the fact that OGE already uses low-sulfur coal, reducing the value of scrubbers as measured by sulfur reductions. • OGE believes very strongly that it is on solid legal ground to propose this AP to DEQ. OGE has checked its analysis and validated the results. • From a legal perspective, OGE intends to pursue this issue through the courts if necessary.

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• Given the potential for litigation, OGE will need to be careful with respect to the information that it is able to make public. • There are three reasons why the alternative plan has been reflected in the IRP: first, pursuit of the alternative plan is the right thing to do and complies with the regulations; second, the scrubbers are too costly for customers and are not cost-effective; and third, given the uncertainty around CO2 legislation, it does not make sense to expend a billion or more for scrubbers when the plants may become obsolete in five years.

Questions: • Is the alternative plan reflected in all IRP analyses? o Yes.

• Setting aside CO2 issues, will OGE’s alternative plan have any impact on Seminole? o No. Seminole will have to add NOx controls on Seminole but, as a gas-fired facility, Seminole does not emit significant levels of SO2.

• How many years into the future is OGE committing to reduce its coal plant output under the alternative plan? o As proposed by OGE, the alternative plan provides OGE with greater time to comply with regional haze requirements and also allows OGE to ramp down emissions to comply with the requirements.

• Is OGE willing to share its BART (scrubber) analysis? o Yes, subject to the caveat that this issue may become the subject of litigation, which may have an impact on the level of detail that can be provided.

• Has the EPA ever approved a plan similar to that proposed by OGE? o No, as far as we know, no alternative such as this has been proposed to the EPA.

• Has the EPA provided any positive response to OGE’s proposal? What is the timing of EPA’s review? o OGE is currently working on getting its alternative plan approved by DEQ and reflected in the Oklahoma State Implementation Plan that will be sent to the EPA for approval. Thus, OGE is still in an advocacy role. The DEQ has asked for additional details regarding OGE’s coal plant operations, but has not shared its perspectives on the alternative plan.

• Would OGE be bound by the terms of the alternative plan if it were to be approved?

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o OGE would retain the flexibility to take other actions should they meet the goals more cost-effectively. For example, if scrubber technology were to become more economical, it would be possible to pursue this option at some point.

• What is the expected life of OGE’s coal plants? o OGE’s coal plants could have 20-30 years left in their life. Coal plants have expected lives of approximately 50-60 years and can be in operation longer than that.

• Have any retirements of OGE plants been included in the IRP? o No. OGE performed a retirement study of the gas generation assets last year and determined that its aging, and largely depreciated plants, provide a relatively inexpensive source of capacity relative to a new build option.

• Did the retirement study reflect new OGE build as the only replacement option? o Yes. For analysis purposes, OGE assumes that a PPA option would have a similar cost to a new build option.

• Are the capacity factor restrictions meant to comply with SO2 constraints? o Yes. The capacity factors represent the operational impact the SO2 constraints will have on these units.

• Was seasonality reflected in the capacity factors? How will the units be curtailed? o While OGE’s capacity factors are designed to meet an annual SO2 target, the plants are dispatched throughout the year to meet seasonal loads. Thus, the plants are likely to be dispatched during the summer peak load months and curtailed during non-peak periods.

• Are emissions of particulate matter a concern? o Particulate matter is reflected in the rules, but is not a significant issue for OGE as OGE has electrostatic precipitators to address particulate matters. Thus SO2 is the issue that restricts coal plant operations.

• PSO has installed scrubbers reflected in their IRP. What makes OGE different? o PSO burns coal with a higher sulfur content and therefore gets a much larger reduction in sulfur emissions than OG&E which improves the economics of adding a scrubber, relative to OGE. Nonetheless, it is OGE’s understanding that scrubbers are not cost-effective for PSO either.

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• Did OGE specify a base capacity factor? o No. The capacity factors are a function of dispatch required to meet the SO2 targets.

• Were the regional haze requirement reflected in all IRP scenarios? o Yes, OGE’s alternative regional haze plan was in all scenarios of the IRP.

• Is it possible to translate the capacity factors to MWH? o Yes. See below. 2010 - 2021- 2026- Max Energy Production (GWh) 2015 2016 2017 2018 2019 2020 2025 2039 Muskogee 4 & 5 6,649 5,983 5,500 5,017 4,534 4,051 3,989 1,323 Sooner 1 & 2 6,934 6,744 6,601 6,458 6,316 6,173 6,030 2,050

• Will OGE be making a regulatory filing that addresses the alternative plan, given the potential cost impact on customers from a reduced reliance on coal? o No. It is premature at this time for OGE to make a regulatory filing to the OCC and it is not clear what OG&E would be asking for. It is management’s prerogative to take action on behalf of its customers on this issue. OGE will make filings when it is time for significant expenditures to be made.

• Has OGE performed a study of the potential rate impacts by customer class of pursuit of the alternative plan? o OGE’s analysis estimates the impact on the retail class, but not on all customer classes. OGE can make this information available subject to potential litigation constraints.

• Are any other utilities impacted by Regional haze rules, and have they challenged the law? o Utilities throughout the western US are affected by the Regional Haze rules. The validity of the rules was addressed in two separate decisions by the US Court of Appeals for the DC Circuit. OGE understands that other utilities in Nebraska have made similar claims that scrubbers are not cost effective. However, OG&E is not aware of any litigation challenging the cost-effectiveness of scrubbers.

• Why doesn’t OGE pursue the litigation option before committing to the alternative plan? o The alternative proposal meets the requirements of the regulation and OG&E hopes that DEQ and the EPA will accept the more cost effective alternative

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instead of mandating scrubbers. If DEQ and/or the EPA require scrubbers despite our analysis and alternative proposal, OG&E will consider litigation.

• Are the AES units affected by the regional haze issue? o No. Neither the AES units, nor OGE’s Muskogee 6 unit are impacted by the rule because they were constructed more recently than specified in the rule.

• How much of OGE coal capacity is affected by regional haze concerns? o Approximately 2,000 MW of OGE’s 2,500 MW of owned coal-fired facilities is affected

F. Capacity Needs

• OGE’s capacity responsibility is the sum of the load forecast and SPP’s minimum required capacity margin • Absent the 2020 Plan, OGE would need to add capacity in 2015 • As shown in the gray area, termination of wholesale contracts defers the need until 2018 • The demand side programs defer this need further until 2022

Questions: • How does the new wind necessary to meet the RES show up in the planning margin? o Pursuant to SPP rules, wind is reflected in the capacity line at 5% of the nameplate capacity.

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G. Transmission Investments

• As a signatory to the SPP OATT, OGE has relinquished its responsibility for transmission planning to the SPP • SPP has determined transmission improvements that must be made for reliability and economic purposes through the development of the SPP Transmission Expansion Plan (STEP) and the Balanced Portfolio pan. • This table lists projects that OGE has agreed to construct. • OGE will only have to pay a portion of the costs associated with these projects.

Questions: • How was this list developed? o These projects are from the SPP’s System Transmission Expansion Program (STEP) and its Balanced Portfolio program. OGE has committed to build these projects. The balanced portfolio program is an economic study performed by the SPP to identify new lines that would make all generation in the SPP deliverable to serve SPP load.

• Are “priority projects” included in this list? o No.

• Does this list of projects reflect all of SPP or just those within OGE’s control area?

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o The list does not represent all SPP projects; those listed are within the OGE footprint.

• Will other SPP projects have costs that will be allocated to OGE? o Yes. Other projects in the SPP are being built and their costs are not included in the IRP. The costs of these projects are not yet available from the SPP. These costs will be allocated to OGE using allocation formulas that vary by type of project.

• Has the impact of OGE’s alternative regional haze plan (e.g., reduced capacity factors for OGE coal plants) been reflected in SPP’s transmission studies? o No. The SPP studies reflect current dispatch of generation units. H. IRP Modeling and Results

• The IRP process requires several inputs from various sources and then follows a 5-step process • The first step in the process is to screen new supply options

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• OGE relied on EIA data to identify possible supply-side options before subjecting them to a three-part test. • The options that pass all three tests are used to construct portfolios

Questions: • Why was Biomass not considered? o The cost is prohibitive and there are limited sources of biomass fuel available (primarily chicken litter).

• Why were CTs not considered? o As the production from coal units is reduced due to regional haze restrictions, baseload generation is needed; which cannot be economically provided with CT’s.

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• The portfolios are intended to reflect a diverse range of options and each portfolio should be feasible to implement. • The “convert” portfolio allows those units to provide energy with no restrictions. The capacity remains unchanged through the conversion from coal to natural gas.

Questions: • Was a strategy considered to convert coal units earlier? o Yes, but it didn’t appear to be necessary. OGE can utilize its Seminole, McClain and Redbud plants to increase gas-fired energy production as there is room for increased output.

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• Resource options are considered based on both capital costs and operating costs • Operating costs are determined for a number of scenario and sensitivity cases • Nuclear appears to have the lowest NPVRR in most scenario cases

Questions: • Are higher nuclear capital costs reflected in any of the scenarios? o Yes.

• The sensitivity cases are shown using tornado charts • Natural gas prices have the highest impact on costs • CO2 appears to have the second highest risk in the portfolios that rely on natural gas, whereas capital costs are the second highest risk in the nuclear portfolio.

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• This analysis reflects SPP’s plans to implement a day-ahead market • SPP has conducted its own cost/benefit analysis. This analysis indicated that OGE would save approximately $10-20 million/year or 1-2% of OGE’s overall fuel budget.

Questions • Do the “savings” represent customer savings? o No. They represent savings in the costs of operating OGE units. A Customer savings calculation must also reflect the savings from purchasing cheaper energy from the market and revenue from selling energy into the market.

• What is included in the “operating costs” for the market analysis comparison? Does this reflect the total cost of energy to OGE customers? o The fuel and VOM costs are included. This is the variable operating cost, not the total cost of energy to customers.

OGE Correction • Do the “savings” represent customer savings? o The following table represents the total customer savings due to the SPP market. This operating cost includes the production cost of OG&E units as well as revenues from sales to the market and expenses from market purchases. These numbers have been updated since the meeting on December 14. The intent of this analysis was to compare the portfolios in the market environment, and the following table shows that all three portfolios have equal savings in the market

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10 Year NPV of Operating Cost In Billions CC Convert Nuclear OG&E Current Dispatch $ 14.8 $ 14.9 $ 14.6 Day Ahead Market $ 13.8 $ 13.9 $ 13.6 Savings $ 1 $ 1 $ 1

3. Stakeholder Feedback

Stakeholders provided the following feedback to OGE:

• There is an overriding concern with the potential short-term and longer-term rate impacts of the IRP, particularly given the current economic climate. These impacts are attributable to the alternative regional haze plan, new wind resources, and transmission investments.

• Given these potential rate impacts it is essential that customers understand the potential rate impact of OGE’s alternative regional haze plan. More information should be provided, subject to constraints that may be imposed on sharing information due to the potential for litigation. As much information should be shared as is possible.

• There should be an assessment of the cost impact of wind that is added to the portfolio to meet the RES rather than simply plugging wind resources into the portfolio.

• The OU Spirit Stipulation created an expectation that OGE would be providing an analysis of additional wind resources in its 2010 IRP filing; this expectation has not been met. For example, there is no analysis of the size and timing of OGE’s next wind RFP.

• OGE should perform a study of the potential to integrate wind energy as it is forecast to comprise 20% of OGE’s energy requirements.

• More analysis and information should be provided with respect to transmission investments within SPP, including those that will be constructed by OGE. The costs of the OGE projects are approximately $70 million per year in increased revenue requirements and the majority of these projects appear to be economic projects.

• OGE should examine nuclear costs closely given the relatively short time period before OGE would have to pull the trigger to meet a 2022 capacity need. The South Texas project has experienced a 30% increase in projected capital costs overnight and is now

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estimated to be approximately $5,000/kW. Cost estimates at other proposed projects should also be examined.

• OGE indicated that it would provide the scrubber analysis and the results of an SPP wind integration task force to the stakeholders when these are available.

Appendix C This appendix contains the OG&E Capability Report as of 12/18/2008.

89 2010 Integrated Resource Plan

REDACTED

90 2010 Integrated Resource Plan

Appendix D This appendix contains OG&E transmission service studies for the three expansion portfolios as described in the Resource Options section on page 29.

OGE Transmission Service Study 2010 IRP Transmission Report November 20, 2009

Executive Summary

A Transmission Service study was performed for the purpose of analyzing the transmission constraints associated with the interconnection of a 500 MW to 1,000 MW unit at Seminole or a 500 MW to 1,000 MW unit at Sooner. Seminole is located in the service territory of Oklahoma Gas & Electric (OGE) in Seminole County, near Konawa Oklahoma. Sooner Power Plant is located in the service territory of Oklahoma Gas & Electric (OGE) in Noble County near Red Rock, Oklahoma.

Contingency Analysis was performed for the 2019 Summer Peak Season. The purpose of the contingency analysis study was to determine if any overloads were present due to the connection of the new units at Seminole or Sooner. Power flow analysis has indicated that transmission upgrades will be required to correct the overloads due to connecting the new unit in the summer of 2019. The network constraints are in the Oklahoma Gas & Electric (OKGE), Entergy (EES) and American Electric Power West (AEPW) control areas.

The network constraints can be corrected by Network upgrades, the estimated upgrade costs for the new unit at Seminole or Sooner is shown in table 1.

Table 1: Estimated Upgrade Costs for new unit at Seminole or Sooner

Unit Estimated Cost 500 MW Unit at Seminole $ 9,250,000 1000 MW Unit at Seminole $ 9,250,000 500 MW Unit at Sooner $ 6,750,000 1000 MW Unit at Sooner $ 31,750,000

Contingency Analysis

A MUST AC Contingency Analysis study was performed to analyze the feasibility of connecting a 500 MW or 1000 MW unit at Seminole in the OG&E Control Area or a 500 MW or 1000 MW unit at Sooner in the OG&E Control Area. Seminole is located in Seminole County, Oklahoma and Sooner is located in Noble County, Oklahoma. The

91 2010 Integrated Resource Plan

2019 Summer Peak Season was studied. The primary objective of this study is to identify the system problems associated with generation interconnection to the grid.

A power flow contingency analysis was conducted using a modified version of the 2009 series 2019 Summer Peak STEP Model. The model name is shown in Table 2.

Table 2: SPP Model used in the Contingency Analysis Study

Model 2019 Summer SPP 2009 STEP BASE BUILD III: 2009STEPB3-19SP (07-10-2009)

The contingency analysis indicates that violations will occur on existing OKGE, AEPW, and EES facilities in the 2019 Summer Peak Seasons for the addition of a new unit at Seminole or Sooner.

Power Flow Methodology

Using the created model and the MUST AC Contingency analysis function single contingencies in all of Southwestern Power Administration, AEP Central and Southwest, Grand River Dam Authority, Oklahoma Gas and Electric, Western Farmers Electric Cooperative, Oklahoma Municipal Power Authority, KPL a Western Resources Company was applied and resulting scenarios analyzed. In Entergy only 100 KV and above was analyzed.

The OGE generating units were re-dispatched to serve the OGE Load with the addition of the new units. An economic dispatch was performed using GenTrader and the OGE unit dispatch was changed as shown in table 3 for the 2019 Summer Season.

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Table 3: OGE Generation Changes for 2019 summer

Base Seminole Seminole Sooner Sooner Genr Genr 1 Genr 2 Genr 1 Genr 2 Bus Name (MW) (MW) (MW) (MW) (MW) TALOGA_WNDG 0 13 13 13 13 WOODWRDG 12 11 11 11 11 MUSTNG3G 118 83 83 83 83 MUSTNG4G 250 192 192 192 192 HSL 6G 167 133 133 133 133 HSL 7S 217 192 192 192 192 HSL 8G 387 300 300 300 300 SEMINL1G 469 391 200 388 202 SEMINL2G 501 390 242 390 242 SEMINL3G 519 446 446 446 446 MUSKOG3G 166 160 0 160 0 OUSPRT 1 0 9 9 9 9 KEENAN_WND 0 15 15 15 15 New Unit 0 500 1000 500 1000 Table 4: Network Constraints for units

Facility 500 MW Unit at Seminole 514908 ARCADIA7 345 B$0266 ARCADIA2 1.00 1 510908 MCALT-S4 138 B$0976 MCALESTR 1.00 1 100 MW Unit at Seminole 514908 ARCADIA7 345 B$0266 ARCADIA2 1.00 1 510908 MCALT-S4 138 B$0976 MCALESTR 1.00 1 500 MW Unit at Sooner 514908 ARCADIA7 345 B$0266 ARCADIA2 1.00 1 1000 MW Unit at Sooner 514908 ARCADIA7 345 B$0266 ARCADIA2 1.00 1 335456 4L-642TP 138 335505 4LIVON 138 1

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Table 5: Contingency Analysis Results

Facility Loading% Contingency 500 MW Unit at Seminole

514908 ARCADIA7 345 3Wnd: OPEN B$0267 ARCADIA3 B$0266 ARCADIA2 1.00 1 106.7 1 510908 MCALT-S4 138 510897 LONEOAK4 138 B$0976 MCALESTR 1.00 1 100.2 510906 SMCALTP4 138 1 1000 MW Unit at Seminole

514908 ARCADIA7 345 3Wnd: OPEN B$0267 ARCADIA3 B$0266 ARCADIA2 1.00 1 107.3 1 510908 MCALT-S4 138 510897 LONEOAK4 138 B$0976 MCALESTR 1.00 1 100.0 510906 SMCALTP4 138 1 500 MW Unit at Sooner

514908 ARCADIA7 345 3Wnd: OPEN B$0267 ARCADIA3 B$0266 ARCADIA2 1.00 1 105.0 1 1000 MW Unit at Sooner

514908 ARCADIA7 345 3Wnd: OPEN B$0267 ARCADIA3 B$0266 ARCADIA2 1.00 1 104.0 1 335456 4L-642TP 138 335368 8WELLS 500 335505 4LIVON 138 1 100.2 335500 8WEBRE 500 1

The estimated cost of network upgrades for new units is shown in Table 6.

Table 6: Estimated Cost of Network Upgrades

Facility Mitigation Estimated Cost 500 MW Unit at Seminole Add a 3rd Transformer at 514908 ARCADIA7 345 B$0266 ARCADIA2 1.00 1 Arcadia $ 6,750,000 510908 MCALT-S4 138 B$0976 MCALESTR 1.00 1 RP W/100MVA $ 2,500,000 500 MW Unit at Seminole Add a 3rd Transformer at 514908 ARCADIA7 345 B$0266 ARCADIA2 1.00 1 Arcadia $ 6,750,000 510908 MCALT-S4 138 B$0976 MCALESTR 1.00 1 RP W/100MVA $ 2,500,000 500 MW Unit at Sooner Add a 3rd Transformer at 514908 ARCADIA7 345 B$0266 ARCADIA2 1.00 1 Arcadia $ 6,750,000 1000 MW Unit at Sooner Add a 3rd Transformer at 514908 ARCADIA7 345 B$0266 ARCADIA2 1.00 1 Arcadia $ 6,750,000 335456 4L-642TP 138 335505 4LIVON 138 1 *Recond. 50Mi $ 25,000,000

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Conclusion

The estimated upgrade costs for a new unit at Seminole or Sooner is shown in table 7. There may be additional stability cost that will be determined in the SPP Study Process

Table 7: Estimated Upgrade Costs

Unit Estimated Cost 500 MW Unit at Seminole $ 9,250,000 1000 MW Unit at Seminole $ 9,250,000 500 MW Unit at Sooner $ 6,750,000 1000 MW Unit at Sooner $ 31,750,000

95 2010 Integrated Resource Plan

Appendix E This appendix contains the OG&E 2009 Load Forecast as prepared by the Cadmus Group, Inc., published September, 2009.

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Final Report

OG&E 2009 Load Forecast

Prepared for: OG&E Electric Services September 22, 2009

Prepared by: The Cadmus Group, Inc.

K:\2008 Projects\2008-117 (OGE) 2009 Load Forecast\Reports and Presentations\FINAL REPORT\OGE 2009 LF Report.doc

Table of Contents

1. Executive Summary ...... 1 2009 Energy Sales Forecast ...... 1 2009 Load Responsibility Peak Demand Forecast ...... 5 Weather Uncertainty ...... 6

2. Economic Outlook ...... 11 Economic Summary ...... 11 Oklahoma City Metropolitan Area ...... 12 Economic Drivers for Energy Forecast ...... 14

3. Load Responsibility Peak Demand Forecasting Model ...... 15 Peak Demand Forecasting Methodology ...... 15 Forecasting Peak Loads ...... 16 Expected Loads by Weather Probability ...... 17 FERC Wholesale Load Adjustments ...... 19

4. Retail Energy Models ...... 21 Econometric Modeling Process ...... 21 2009 Energy Forecast ...... 22 FERC Wholesale Sales Adjustments ...... 22 Energy Forecast Uncertainty...... 25

5. Retail Customer Forecasting Models ...... 27 Retail Customer Modeling Process and Forecast ...... 27

6. Data Sources ...... 29 Internal Company Information ...... 29 Information Obtained from External Sources ...... 30

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1. Executive Summary

This report presents Oklahoma Gas & Electric Services’ (OG&E) 2009 load forecasts. It describes both peak demand and energy forecasting models developed by OG&E’s Load Research and Forecasting department and The Cadmus Group with input from OG&E’s Interdepartmental Forecasting Task Force. The 2009 retail sales forecast utilized the revenue class-based econometric modeling framework that has been in place for over a decade. The 2009 load responsibility peak demand forecast is based on an hourly econometric model of weather and economic effects on OG&E’s hourly load responsibility series. The hourly modeling approach has been used since the 2000 forecast. The load forecasting framework relies on independently produced forecasts of service area economic and population growth, actual and normal weather data, and projections of electricity prices for price-sensitive customer classes. The final energy and demand forecast includes Federal Energy Regulatory Commission (FERC) jurisdictional wholesale contracts as post- modeling adjustments.

2009 Energy Sales Forecast The 2009 retail energy forecast is based on retail sector-level econometric models representing OG&E’s Oklahoma and Arkansas service territories. Historical and forecast economic variables (drivers) are provided from the following sources: • The Oklahoma Economic Outlook, prepared by the Oklahoma State University (OSU) College of Business Administration, Center for Applied Economic Research. • Moody’s Economy.com was used as a source of forecasts of economic drivers for Arkansas In past forecasts, The University of Arkansas at Little Rock (UALR) provided economic drivers that were used to predict energy sales in OG&E’s Arkansas service territory. This year, OG&E made the decision to purchase forecasts of economic drivers from Moody’s Economy.com. The move from UALR to Moody’s Economy.com was made because Moody’s Economy.com was capable of providing forecasts of drivers for the Fort Smith region of Arkansas, rather than for the state as a whole, as UALR has traditionally produced. In 2007 the Oklahoma economic driver series were adjusted by Dr. Mark Snead, Director of OSU’s Center for Applied Economic Research, for recent structural changes in the state’s economy. Dr Snead’s research had revealed a “billionaire” effect that inflates the real income and gross state product series that are critically important in forecasting OG&E’s energy sales. Table 1, below, compares the growth rates of 2009 and 2008 forecast drivers. The “ex-energy” variables, where the “billionaire” effect is removed, are compared to their unadjusted counterparts. The comparison reveals:

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• That the difference in growth rates between the ex-energy series and their counterpart is still a significant factor, and is in fact increasing for several of the series compared to the forecasts from 2008. • Most of the 2009 drivers exhibit lower growth rates as a result of the recent economic downturn.

Table 1. Economic Driver Growth Rate Comparison

2009 Drivers 2008 Drivers 2009 Drivers 2008 Drivers 2009 Drivers 2008 Drivers Average Average Average Average Average Average Growth Rate Growth Rate Growth Rate Growth Rate Growth Rate Growth Rate Economic Drivers 2009 to 2019 2009 to 2019 2009 to 2014 2009 to 2014 2015 to 2019 2015 to 2019 Real Manufacturing Output-OKC 1.62% 2.28% 0.66% 2.24% 2.22% 4.03% Real Manufacturing Output Ex-Energy-OKC 3.20% 3.95% 2.35% 4.10% 3.96% 6.28% Difference -1.58% -1.67% -1.69% -1.85% -1.75% -2.25% Real Personal Income-OKC 3.81% 3.48% 3.55% 3.30% 4.14% 2.75% Real Personal Income Ex_Energy-OKC 3.42% 3.20% 3.18% 3.20% 3.61% 2.67% Difference 0.38% 0.27% 0.37% 0.09% 0.53% 0.08% Real GSP 2.99% 3.05% 2.30% 2.92% 3.56% 2.79% Real GSP Ex-Energy 2.23% 2.28% 1.82% 2.32% 2.76% 2.31% Difference 0.76% 0.76% 0.48% 0.60% 0.80% 0.47%

Underlying Economic Fundamentals While Oklahoma’s economy has continued to outperform the national economy as a whole, the continuing national recession has created an uncertain economic environment in Oklahoma. Historically, Oklahoma’s economy has outperformed the rest of the nation during national recessions, as most recessions have been concurrent with rising energy costs. However, while Oklahoma’s momentum from its energy sector heading into the recession has protected it from the impacts seen in some of the worst hit states, low energy prices are adding to the economic pressures within the state.

Dr. Mark Snead from OSU notes two underlying factors slowing growth within Oklahoma’s economy.17 These are:

1. Weak Energy Prices: The OSU macroeconomic forecast drivers anticipates the price of oil hovering around $50/barrel, and natural gas a $5.50 per million btu’s in 2009. Dr. Snead writes: “These prices are uncomfortably close to the threshold where we believe energy switches from providing a net boost to restricting growth in the state economy.”

17 The Oklahoma Economy: 2009 Oklahoma Economic Outlook, http://economy.okstate.edu/outlook/

OG&E 2009 Load Forecast 2

While the price of oil is beginning to increase, it has been under $50 a barrel for most of the year, and the price of natural gas has been below $5.50 per million btu’s. Moody’s Economy.com18 forecasts suggest that natural gas will remain below $5 per million btu’s through the end of the year, with oil climbing to an average of $55 a barrel in the fourth quarter.

2. The duration of the national recession: A protracted recession nationally could drag down Oklahoma’s economy. This could cause additional turmoil in the economy including state and local budget problems, and increasing defaults on consumer debt. Dr. Snead summarizes the economic outlook for 2009 and 2010: “In short, we believe Oklahoma will slow along with the nation in the next six months, but remain one of the few states positioned to come through the current recession unscathed relative to many areas of the country. However, if energy prices continue to fall and the national recession lasts much longer than expected, 2010 becomes the risk year for the Oklahoma economy and may well signal the return of the familiar “Oklahoma Lag” relative to the nation.”

In Arkansas, a declining manufacturing sector has led to severe job losses, impacting the greater economy through the loss of these relatively high-paying jobs. While the local unemployment rate is lower than the national one, it is higher than in the previous recession. Job losses are predicted to slow by the end of 2009 but job gains are not expected until late-2010.

Energy Sales Forecast The 2009 retail energy sales forecast is summarized in Table 2 below. The table also contains the energy sales forecast adjusted for wholesale sales contracts and line losses to wholesale and retail sales. The forecast (and actual 2008 sales) is based on normal weather in both Oklahoma and Arkansas. The underlying retail forecast is anticipated to grow at an average annual rate of 1.6%. The energy sales forecast adjusted for wholesale sales projects average growth at 1.1%, with the difference relative to retail growth due to expiring wholesale contracts. Table 3 and Table 4 provide the annual growth rates of the retail sales forecasts for all sectors in Oklahoma and Arkansas, respectively. Table 5 presents the forecasted annual growth rates of the different wholesale sales contracts. Note that by 2015, all wholesale contracts will have expired.

18 Moody’s economy.com series: “Natural Gas: Henry Hub”, last updated 5/7/2009, and “Petroleum Crude Oil Price: West Texas Intermediate – Sweet Wellhead” last updated 5/7/2009.

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Table 2. 2009 Retail and Wholesale Energy Sales Forecasts

Energy Forecast (MWh) Energy Growth Rates Including Wholesale Including Wholesale Retail Energy Forecast Retail Energy Year Sales and Line Losses Sales and Line Losses (MWh) Growth Rates 2008 (Actual) 28,447,903 25,218,518 2009 28,438,978 -0.03% 25,125,213 -0.37% 2010 28,683,738 0.86% 25,344,525 0.87% 2011 28,962,831 0.97% 25,711,026 1.45% 2012 28,376,372 -2.02% 26,176,782 1.81% 2013 28,902,927 1.86% 26,725,534 2.10% 2014 29,178,249 0.95% 27,248,583 1.96% 2015 29,735,257 1.91% 27,792,558 2.00% 2016 30,338,008 2.03% 28,355,929 2.03% 2017 30,913,210 1.90% 28,893,551 1.90% 2018 31,501,909 1.90% 29,443,788 1.90% 2019 32,128,381 1.99% 30,029,331 1.99%

Table 3. 2009 Oklahoma Retail Sales Forecast Growth Rates by Sector Public Street Year Residential Commercial Industrial Authority Petroleum Lighting 2008 (Actual) 2009 1.6% 1.9% -1.1% -0.9% -6.5% 1.6% 2010 0.6% 1.5% 1.7% -0.4% 1.3% 1.4% 2011 1.4% 1.5% -0.2% 2.8% 0.3% 1.4% 2012 1.7% 2.1% -0.3% 2.8% -0.1% 1.3% 2013 2.1% 2.6% -0.3% 2.8% 0.1% 1.3% 2014 2.2% 2.6% -0.3% 2.6% 0.3% 1.2% 2015 2.1% 2.7% 0.0% 2.8% 0.7% 1.2% 2016 2.1% 2.7% 0.1% 2.8% 1.0% 1.2% 2017 2.0% 2.5% 0.2% 2.6% 0.7% 1.2% 2018 2.0% 2.5% 0.3% 2.6% 0.7% 1.2% 2019 2.1% 2.5% 0.6% 2.7% 0.8% 1.2%

OG&E 2009 Load Forecast 4

Table 4. 2009 Arkansas Retail Sales Forecast Growth Rates by Sector Public Street Year Residential Commercial Industrial Authority Petroleum Lighting 2008 (Actual) 2009 1.1% 0.5% -8.6% -2.8% -6.9% 0.9% 2010 0.0% 0.8% -0.3% 2.1% -1.0% 0.8% 2011 1.2% 2.2% 4.8% 4.2% 0.7% 0.9% 2012 2.6% 4.5% 6.8% 5.9% 0.6% 0.8% 2013 3.2% 5.4% 5.2% 4.2% 0.5% 0.7% 2014 2.3% 3.9% 2.9% 3.0% 0.1% 0.7% 2015 1.8% 3.0% 2.5% 3.0% 0.0% 0.7% 2016 1.7% 2.8% 2.5% 3.0% 0.1% 0.7% 2017 1.7% 2.8% 2.5% 2.9% 0.1% 0.7% 2018 1.6% 2.6% 2.4% 2.8% 0.1% 0.6% 2019 1.6% 2.5% 2.3% 2.7% 0.1% 0.6%

Table 5. 2009 Wholesale Sales Forecast Growth Rates

Year Municipal AVEC SPA OMPA MDEA Total 2008 (Actual) 2009 3.5% 1.7% -0.1% 0.5% -5.1% 0.9% 2010 -19.0% 1.5% 3.5% 0.0% 0.0% 0.6% 2011 -6.9% -5.7% -58.2% 0.0% 0.0% -7.2% 2012 -83.5% -100.0% -63.5% 0.0% -10.7% -74.6% 2013 -100.0% -100.0% 0.0% -36.0% -16.4% 2014 -100.0% -66.7% -91.9% 2015 -100.0% -100.0%

2009 Load Responsibility Peak Demand Forecast The 2009 load responsibility forecast relies on an hourly econometric model specification first used for the 2000 forecast. The modeling framework reflects the following: • Impact of different weekdays on hourly system load. • Impact of different summer months on hourly system load. • Influence of heat buildup during heat waves. • Impact of the combined effects of humidity and warm temperatures. • Non-linearity in the load and temperature relationships at very high temperatures.

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As has been the case for the past several years, weather-adjusted retail energy sales are the main economic driver for the peak model. Table 6 shows the actual 2008 retail load, along with the final load responsibility forecast, adjusted for wholesale loads and line losses, for 2009 and beyond. The forecast is based on average weather conditions over the past 35 years. Underlying retail peak loads are anticipated to grow at an average annual rate of 1.4% over the next decade, which is slightly less than the growth rate for retail energy sales. Table 6. 2009 Load Responsibility Peak Demand Forecast Total Load Responsibility Peak Demand (MW) Total Load Retail Load Responsibility Retail Load Year Forecast* (Average Responsibility Peak Demand (MW) Forecast Responsibility Weather) Growth Rates (Average Weather) Growth Rates 2008 5,988 5,666 2009 5,990 0.03% 5,663 -0.05% 2010 6,035 0.76% 5,707 0.77% 2011 6,107 1.18% 5,779 1.27% 2012 5,899 -3.39% 5,851 1.24% 2013 6,013 1.93% 5,975 2.13% 2014 6,070 0.94% 6,070 1.58% 2015 6,176 1.76% 6,176 1.76% 2016 6,265 1.43% 6,265 1.43% 2017 6,386 1.93% 6,386 1.93% 2018 6,488 1.60% 6,488 1.60% 2019 6,596 1.66% 6,596 1.66% * Includes wholesale loads and line losses

Weather Uncertainty As is well known within the electric industry, and especially at OG&E, peak demand and energy sales are highly sensitive to year-to-year weather variations. Both can appear to decline even with positive economic growth when a hot year is followed by an unusually cool year. Conversely, if a hot year follows a cool year, energy sales and peak demand can increase even though there may be little or no economic growth. Weather uncertainty is represented through a Monte Carlo modeling approach where the last 35 years of actual weather are systematically input into the energy and peak models to produce a possible outcome distribution. OG&E’s weather-year Monte Carlo approach runs weather years 1974 to 2008 through weather- sensitive energy models, along with the peak demand model, to develop a probability distribution of possible outcomes. Figure 1 shows the 95% confidence interval around the expected energy sales forecast, including wholesale adjustments, resulting from this modeling process. Note that the decline in sales of approximately 550,000 MWh from 2011 to 2012 is principally the result of the assumption by OG&E that the current AVEC wholesale contract,

OG&E 2009 Load Forecast 6

which is currently set to expire on November 30th, 2011, is not renewed. Figure 1. Energy Model Forecast Outcomes by Weather Probability

34,000,000

33,000,000

32,000,000

31,000,000

30,000,000 MWh 29,000,000

28,000,000

27,000,000 1 out of 30 Years 1 out of 2 Years 29 out of 30 Years 26,000,000 Normal Weather

25,000,000 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

The 1 out of 2 years forecast line shows energy sales, including wholesale adjustments, assuming average weather years over the 35-year period. We note this “distribution average” is not the same as normal weather. This thinking is consistent with research findings by Chuck Doswell of the National Severe Storms Laboratory in Norman, Oklahoma. Mr. Doswell suggests: “…what is considered ‘normal’ may not . . . correspond precisely to the average. ‘Normality’ is a matter of definition. In order to understand what ‘normal’ means, you have to understand what was done to the data [in the normalization process].”19

The 1 out of 2 years average weather line indicates there is a 50% probability that energy sales will reach this level or higher. The normal weather forecast is actually closer to the lower end of the distribution, with sales approximately 1.2% less (370,000 MWh on average per year) than the 50% probability line. Now, consider the 1 out of 30 years forecast. This line, which is approximately 1,450,000 MWh higher than the normal weather forecast, shows energy sales under more extreme weather events occurring just 3% of the time. Finally, the lower bound forecast (29 out of 30 year case) shows sales may fall below the normal weather forecast by approximately 140,000 MWh if weather is milder than normal given expected economic performance.

Figure 2 shows a similar graph for the load responsibility distribution. The weather modeling indicates the 95% confidence interval has a range of approximately 600 MW, with the upper

19 Doswell, Chuck, “Misconceptions About what is ‘Normal’ for the Atmosphere,” 1997.

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bound approximately 175 MW higher than the load under expected weather conditions and a lower bound over 420 MW lower than the expected load. Again, the decline in demand of approximately 200 MW from 2011 to 2012 is principally the result of the expiration of AVEC’s wholesale contract.

Figure 2. Load Responsibility Outcomes by Weather Probability

7,500

7,000

6,500 MW

6,000

1 out of 30 Years 5,500 1 out of 2 Years

29 out of 30 Years

3 out of 4 Years

5,000 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Historical Weather Normalized Retail Energy and Peak Demand To put the forecasted retail sales and native load responsibility in perspective, we show weather normalized sales and peak demand data during the model estimation period. Figure 3 shows the retail and combined retail and wholesale forecasts of energy sales including losses as well as the weather normalized historical sales, while Figure 4 shows the weather normalized historical and forecasted native load responsibility. Both the retail energy and native load responsibility forecasts demonstrate growth similar to that in the historical model estimation period.

OG&E 2009 Load Forecast 8

Figure 3. Retail and Wholesale Energy - Weather Normalized Historical and Forecast Sales

30,000,000

29,000,000

28,000,000

27,000,000

26,000,000 MWh

25,000,000

24,000,000 Historical Weather Normalized Retail Sales Forecast of Weather Normalized Retail Sales

Historical Weather Normalized Total Sales + FERC 23,000,000 Forecast of Weather Normalized Total Sales + FERC

22,000,000 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Figure 4. Native Load Responsibility - Weather Normalized Historical and Forecast Loads

6,800

6,600

6,400

6,200

6,000 MW

5,800

5,600

5,400 Historical Weather Normalized Retail Load Responsibility Forecast of Weather Normalized Retail Load Responsibility 5,200 Historical Weather Normalized Total Load Responsibility Forecast of Weather Normalized Total Load Responsibility

5,000 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

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2. Economic Outlook

OG&E’s load forecast relies on the estimated, historical relationships between economic variables and customer loads and on independently produced service area economic and population growth forecasts. Historical and forecast economic variables (drivers) are provided from the following sources: • The Oklahoma Economic Outlook, prepared by the Oklahoma State University (OSU) College of Business Administration, Department of Economics and Legal Studies • Moody’s Economy.com was used as a source of forecasts of economic drivers for Arkansas

The OSU forecasts are derived from a combination of national economic forecasts prepared by Global Insight, DRI-WEFA, and from their own state and local economic models. The Oklahoma Economic Outlook was produced in December 2008, and then updated in March of 2009.20

Economic Summary The current economy is characterized by low energy prices, a tight credit market, slowing in the Oklahoma housing market and instability and uncertainty within the national economy21. The following is a summary of the main state specific economic indicators:

1. Energy Prices The OSU macroeconomic forecast drivers anticipates the price of oil hovering around $50/barrel, and natural gas at $5.50 per million btu’s in 2009. Snead writes: “These prices are precariously close to the threshold where we believe energy switches from providing a net boost to restricting growth in the state economy.” While the price of oil is beginning to increase, it has been under $50 a barrel for most of the year, and the price of natural gas has been below $5.50 per million btu’s. Moody’s economy22 forecast suggests that natural gas will remain below $5 per million btu’s through the end of the year, with oil climbing to an average of $55 a barrel in the fourth quarter. 2. Employment: In contrast to the nation, which lost 0.1 percent of jobs in 2008, Oklahoma experienced 1.1% job growth. In 2009, OSU forecasts that Oklahoma will have a job loss of -0.2% whereas nationally the rate is predicted to be -1.5%.

20 This section, through the “State of Arkansas Forecast” section, contains a brief summary of the information contained in the OSU (http://economy.okstate.edu/outlook), and some of the text is verbatim. 21 This text in this section refers to the Oklahoma and Oklahoma City economies, and is sourced from: The Oklahoma Economy: 2009 Oklahoma Economic Outlook, http://economy.okstate.edu/outlook/ 22 Moody’s economy.com series: “Natural Gas: Henry Hub”, last updated 5/7/2009, and “Petroleum Crude Oil Price: West Texas Intermediate – Sweet Wellhead” last updated 5/7/2009.

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3. Household Income: Household income has grown at an average pace of 8% since 2004. OSU expects this to slow down to the 3-4% range through 2010. While slower, this is still higher than income growth nationally, and OSU estimates that by 2010 Oklahoma’s per capita income will hit 95% of the national level. 4. Industry Growth: OSU anticipates that the largest decline will be in temporary employment, followed by wholesale trade, retail trade, transportation, and warehousing. OSU believes that oil and gas, health services, utilities, education and government will grow, as well as consumer services such as arts, entertainment, recreation, accommodation and food services. 5. Population: The relatively strong economy of Oklahoma continues to pull net migration to the state; the US Census reports growth above 1% since 2006, although the OSU model estimates lead Snead to believe these estimates will be revised upwards. Snead reports that this growth is mostly due to the oil and gas sector, the agricultural sector and the growth in Indian nations and tribes.

Oklahoma City Metropolitan Area OSU forecasts that housing prices and employment figures will be stronger for Oklahoma City than the nation and the state. Unlike the statewide decline forecast for 2009, OSU expects that Oklahoma City will post a 0.2% job gain in 2009, and a 1.1% gain in 2010. The OSU forecast calls for metro area unemployment to push above 5%; in May of 2009 the Bureau of Labor Statistics reported the metro area had 5.7 percent unemployment23. Though the housing market has considerably weakened in Oklahoma City, OSU forecasts that housing price gains should continue above 3% through 2009. Foreclosures are limited compared to the nation, with Oklahoma’s foreclosures per household ranked 33rd.

Fort Smith Metropolitan Area Fort Smith is currently facing a declining manufacturing sector, which is, in turn, impacting the service sector and leading to significant job losses. Additionally, population growth has slowed from previous years, though the relatively low cost of living combined with proximity to other metropolitan areas has kept net migration positive.24 The following is a summary of the main MSA-specific economic indicators:

1. Employment: Employment in the manufacturing sector has declined, impacting the greater economy through the loss of these relatively high-paying jobs. Manufacturing employment is down 7.6% from last year, with the only bright spot an increase of 3.4%

23 Unemployment Rates for Metropolitan Areas, May 2009,Bureau of Labor Statistics http://www.bls.gov/web/laummtrk.htm

24 The text in this section refers to the economy of the Forth Smith Metropolitan Area, and is sourced from: Précis METRO by Moodys.com published in March of 2009

OG&E 2009 Load Forecast 12

in Education and Health Services. While the local unemployment rate is lower than the national one, it is higher than in the previous recession. Job losses are predicted to slow by the end of 2009 but job gains are not expected until late-2010. 2. Housing Market: While the Ft. Smith housing market grew rapidly, it did not overheat, resulting in a relatively mild but ongoing correction. Housing prices have fallen 8% and are expected to fall another 4% by early 2010. Credit conditions will continue to erode through 2009, hindering housing recovery. 3. Household Income: Compared to increases of 7.6% and 7.4% in 2006 and 2007 respectively, personal income is expected to grow 0.1% in 2009 and then 2.4% in 2010. Moody’s predicts that once 2012 hits personal income will begin to grow at 6%. 4. Industry Growth: While local manufacturing was experiencing double-digit declines in output at the end of 2008 and beginning of 2009, these declines are less than the national average. However, Moody’s predicts that the local manufacturing industry will not improve until 2010. 5. Population: Population is steadily increasing, following the previous years’ trend.

13

Economic Drivers for Energy Forecast Table 7 below shows key economic drivers from the 2009 OSU and Moody’s Economy.com forecasts, the OG&E econometric models they support, and the drivers’ historical and forecast growth rates. Table 7. Economic Drivers’ Growth Rates, 2009 Forecast Average Economic Driver Annual Growth Rates 1998 – 2009 – 2015 – Economic Drivers and Models 2008 2014 2018 Arkansas Residential: Fort Smith Real Personal Income 3.1% 2.9% 2.4% Commercial: Fort Smith Real Personal Income 3.1% 2.9% 2.4% Public Authority: Fort Smith Real GMP 2.5% 2.4% 2.2% Industrial: Fort Smith Real GMP 2.5% 2.4% 2.2% Industrial: Fort Smith Manufacturing Employment -1.9% -0.9% -0.7% Street lighting: Fort Smith Population 0.9% 1.0% 0.8% Oklahoma Residential: OKC Real Personal Income* 4.0% 3.2% 3.6% Commercial: OKC Real Personal Income* 4.0% 3.2% 3.6% Public Authority: Real Oklahoma GSP* 2.1% 1.8% 2.8% Industrial: OKC Manufacturing Employment -2.8% -1.5% -1.2% Industrial: OKC Real Manufacturing Output * 4.4% 2.3% 4.0% Petroleum: Nominal U.S. Natural Gas Price 20.6% 6.8% 8.2% Street Lighting: OKC Population 1.2% 1.1% 1.0% * Adjusted using definition from OSU

OG&E 2009 Load Forecast 14

3. Load Responsibility Peak Demand Forecasting Model

This section describes the 2009 load responsibility peak demand forecasting model. The forecast follows a discussion of the basic methodology and related hourly econometric framework.

Peak Demand Forecasting Methodology Econometric Modeling Framework The econometric modeling framework has been in place at OG&E since 2000. The modeling structure consists of 24 separate hourly equations, one for each hour of the day, with separate intercept and slope coefficients in the various models. The hourly equations are estimated over the May through September period. The dependent variable is OG&E’s normalized load responsibility, less the fixed 25 MW Oklahoma Municipal Power Authority (OMPA) Power Sales Agreement (PSA) load, and includes line losses. Key independent variables include: • Cooling degree hours, base 76. This cooling degree hour variable is calculated in a manner similar to cooling degree days and effectively represents temperature impacts when temperatures exceed 76 degrees. • A second temperature variable, defined as temperature—102°, which addresses the “topping off” effect in which there is a reduction in the rate of load increases at very high temperatures. • National Oceanic and Atmospheric Administration’s (NOAA) misery index reflecting the combined effects of humidity and warm temperatures. The misery build-up or duration of the misery index is captured through the weighted average of past hourly values of the misery index.25 • Wind speed. • School end date in May and start-up in August.

25 The lag structure is designed to pick up the effects of a heat wave lasting a few days or more. More electricity is demanded later (vs. earlier) in a heat wave, even when temperatures decline slightly. The implication is that “design temperature” is not sufficient for peak forecasting purposes. The temperature of the building is the result of the accumulated outdoor temperatures, less the impact of the HVAC system. The weighted average is capable of capturing the effects of both duration and nighttime cooling since high daytime temperatures and lower nighttime temperatures are reflected in the average.

15

• Economic growth as reflected through weather-adjusted retail energy sales, where weather is effectively removed from the energy series such that the resulting retail total represents the aggregate impact of economic conditions on the OG&E system. The sales are also normalized by the number of days in each month. Other variables in the hourly models include binary (dummy) variables representing different days of the week and different months within the year, which interact with the weather variables in most of the hourly equations. Relevant weather stations are shown below in Table 8, along with the OG&E population estimates from the 2000 census used to weigh data from each station:

Table 8. Weather Station Weights Population in OG&E Weight (% of OG&E Weather Station Territory population) Oklahoma City (Will Rogers) 1,215,619 63.4% Fort Smith 285,644 14.9% Guthrie 154,327 8.0% Stillwater26 153,029 8.0% Muskogee 109,834 5.7%

Forecasting Peak Loads The peak demand forecast is generated via a probabilistic approach by using all available years of weather data, rather than a single year or an average of weather years. This Monte Carlo approach essentially runs all weather years from 1973 to 2008 through the peak demand model, while alternating the weather year “starting day” seven times, so extreme weekday (weekend) weather event probability is treated directly in the simulations. For example, the most extreme heat wave in the past might have begun on a Thursday and topped out on a Sunday. Since loads are much lower on weekends, the heat wave would not have led to a system peak for the year. However, the extreme weather did occur and might indeed have led to a peak event if it began on a Monday and ended on a Thursday. This is why the starting day for historical weather from past years must be translated into seven distinct possible outcomes. This results in a matrix of 36 weather years by seven days, or a total of 252 simulations given the historical hourly weather data available to OG&E. The process for constructing the peak demand forecast is as follows: • Obtain a range of weather-feasible load forecasts for each year over the forecast horizon (2009–2019) by multiplying the regression model coefficients by the corresponding values of weather-related variables. As described above, this step generates 245 weather- feasible forecasts.

26 While OG&E does not serve Stillwater, this weather station was the northernmost station within the required weather history.

OG&E 2009 Load Forecast 16

• Rank order these 252 annual load forecasts from highest to lowest, and assign probabilities to the occurrence of each forecast under the assumption of a uniform distribution (i.e., each weather has an equal chance of occurrence). All of the highest values (peaks) in the resulting forecast distribution occur between 3:00 p.m. and 7:00 p.m. (Central Daylight Time), with the majority occurring at 5:00 p.m. Table 9 illustrates mapping between event occurrence and the occurrence probability. The median load projections come from the 50th percentile of the distribution. This means that half of the time, the peak load would be expected to exceed this level; and half of the time, the peak load would be below this level. In other words we would expect to hit this level at least once over a two-year period, so we call this the 1 out of 2 year case.

Table 9. Probability Assignments Event Occurrence27 Occurrence Probability 1 out of 30 years 3% 1 out of 10 years 10% 1 out of 4 years 25% 1 out of 2 years 50% 3 out of 4 years 75% 9 out of 10 years 90% 29 out of 30 years 97%

Consider now the 10th percentile of the distribution. There is a 10% chance loads will be at this level or higher in any future year, which we interpret as a 1 out of 10 year event. On the other side of the distribution, consider row 225 out of 252 (or the 90th percentile). There is a 90% chance loads will be at this level or higher in any future year, which we interpret as a 9 out of 10 year event.

Expected Loads by Weather Probability

Table 10 and Figure 5 summarize the peak load model forecasts with a 95% confidence interval around potential weather events, assuming no changes in the expected economic outlook. These estimates include wholesale loads and the assumption of expiring wholesale contracts. Following the probability assignments in Table 6, the interpretation of these results is as follows. The 1 out of 2 years or “expected” forecast shows the peak demand level given the 50th percentile of the load forecast distribution, using all available historical weather data. In this case, there is a 50% probability the peak load will reach this load level or higher. Considering the 1 out of 10 years forecast, which is approximately 145 MW higher than the 1 out of 2 years case, shows the estimated peak demand under a more extreme weather event that occurs just 10% of the time. Put differently, over a 10-year planning horizon, it is likely that

27 This means that the weather is at least as hot as in X out of Y years.

17

OG&E will hit a summer peak consistent with the 1 out of 10 years forecast at least once. The key area of uncertainty is in which year this event will occur. Table 10. Peak Demand Model Forecasts by Weather Probability

1 out of 1 out of 1 out of 4 1 out of 2 3 out of 4 9 out of 29 out of Year 30 Years 10 Years Years Years Years 10 Years 30 Years 2009 6,157 6,133 6,089 5,990 5,788 5,671 5,571 2010 6,207 6,178 6,138 6,035 5,833 5,720 5,617 2011 6,277 6,250 6,209 6,107 5,904 5,790 5,688 2012 6,074 6,043 6,006 5,899 5,697 5,587 5,480 2013 6,188 6,156 6,120 6,013 5,810 5,700 5,593 2014 6,244 6,213 6,176 6,070 5,867 5,756 5,650 2015 6,350 6,320 6,282 6,176 5,973 5,861 5,756 2016 6,440 6,408 6,372 6,265 6,062 5,951 5,844 2017 6,562 6,530 6,493 6,386 6,183 6,072 5,965 2018 6,663 6,632 6,594 6,488 6,284 6,173 6,066 2019 6,770 6,739 6,702 6,596 6,392 6,280 6,174

1. Figure 5. Peak Demand Model Forecasts by Weather Probability

7,000

6,500

6,000 MW

1 out of 30 Years

1 out of 10 Years

1 out of 4 Years 5,500 1 out of 2 Years

3 out of 4 Years

9 out of 10 Years

29 out of 30 Years

5,000 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

It is possible—even likely—weather conditions will vary markedly from one year to the next. For example, the weather-year forecast simulations reveal 2004 weather was the fourth coolest of

OG&E 2009 Load Forecast 18

the 36 weather years, 2007 was in the middle of the range, and 2006 weather was the fourth hottest. Dramatic weather condition changes, not economic growth, are responsible for year-to- year differences. Overall, the 95% confidence interval associated with weather conditions represents a significant source of risk responsible for approximately 630 MW of potential peak load variability.

FERC Wholesale Load Adjustments FERC wholesale load adjustments are conducted in two steps based on known and verifiable events. First, the OMPA wholesale load Power Sales Agreement (PSA) contract is added to the normalized load responsibility forecast from the model. Second, expiring contracts are subtracted to obtain final 2009 Load Responsibility forecasts. Table 11 includes the expected dates that all existing wholesale sales contracts will end assuming customers find alternate suppliers.

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Table 11. 2008 Load Responsibility Forecast

Demand (MW) 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 FERC Load (without losses) MUNICIPAL12 11.3 11.1 9.0 11.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 COOPERATIVE 13 223.5 227.5 230.9 238.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 SPA 14 16.7 17.3 17.8 7.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 OMPA PSA 15 25.0 25.0 25.0 25.0 25.0 25.0 0.0 0.0 0.0 0.0 0.0 0.0 MDEA 16 20.0 20.0 20.0 20.0 20.0 10.0 0.0 0.0 0.0 0.0 0.0 0.0 Total FERC Load (w/o losses) 296.4 301.0 302.7 301.6 45.0 35.0 0.0 0.0 0.0 0.0 0.0 0.0 Losses (Loss factor = 0.0867) 25.7 26.1 26.2 26.1 3.9 3.0 0.0 0.0 0.0 0.0 0.0 0.0 Total FERC Load (losses added) 322.1 327.1 328.9 327.7 48.9 38.0 0.0 0.0 0.0 0.0 0.0 0.0 Percentage Change in Total FERC Load 1.53% 0.57% -0.36% -85.08% -22.22% -100.00% 0.00% 0.00% 0.00% 0.00% 0.00% Total Retail Load (with losses) 5,666 5,663 5,707 5,779 5,851 5,975 6,070 6,176 6,265 6,386 6,488 6,596 Percentage Change in Total Retail Load -0.05% 0.77% 1.27% 1.24% 2.13% 1.58% 1.76% 1.43% 1.93% 1.60% 1.66% Load Responsibility (with losses) Load Responsibility = Total Retail Load + FERC, Losses Added (includes curtailable load)* 5,988 5,990 6,035 6,107 5,899 6,013 6,070 6,176 6,265 6,386 6,488 6,596 Percentage Change in Load Responsibility 0.03% 0.76% 1.18% -3.39% 1.93% 0.94% 1.76% 1.43% 1.93% 1.60% 1.66% Load Factor Load Responsibility = Total Retail Load + FERC, Losses Added* 5,988 5,990 6,035 6,107 5,899 6,013 6,070 6,176 6,265 6,386 6,488 6,596 Total Retail Sales + FERC, Losses Added 28,447,903 28,361,894 28,683,738 28,962,831 28,376,372 28,902,927 29,178,249 29,735,257 30,338,008 30,913,210 31,501,909 32,128,381 Load Factor 54.23% 54.05% 54.25% 54.14% 54.91% 54.87% 54.88% 54.96% 55.28% 55.26% 55.43% 55.60% 2. * Values may not add up due to rounding 12. 12 Watonga contract can expire on February 28, 2012, Paris Contract can expire on September 30, 2011, Orlando contract can expire on January 20, 2010 and the Geary contract can expire on March 17, 2010 13. 13 AVEC contract can expire on November 30, 2011 14. 14 Paris contract can expire on January 31, 2011 and Vance contract can expire on May 31, 2012 15. 15 OMPA PSA contract terminates on December 31, 2013 and is removed from forecast at that time due to the absence of an Evergreen clause in the contract. 16. 16 MDEA contract 2 can expire on September 30, 2012 and MDEA contract 1 can expire on April 30, 2014

OG&E 2008 Load Forecast 20

4. Retail Energy Models

This section describes the methodology and results associated with sales equations estimates by state and revenue class.

Econometric Modeling Process The monthly energy consumption analysis for each market segment follows a four-step process: Step 1. Review 2008 forecast results to determine which segments require the most attention to alternative model specifications and visual inspection of each sales series to identify sudden changes in usage that might require dummy variables. Step 2. Generate initial estimates using 2008 model specification. Step 3. Inspect goodness-of-fit and other important statistics (e.g., R-squared, t-statistics, multicollinearity statistics); visual inspection of actual versus predicted values of the dependent variable over the historical period. Step 4. Repeat steps 1 through 3 as needed until a final specification is generated. Between 10 and 50 models were estimated for each segment. The final model was not always the one with the “best fit.” The overriding selection criterion was the model providing the best forecast. For example, if a model with an R-square of 0.95 had a larger error in the out-of-sample period than an alternative model with an R-square of 0.93, the latter model was selected. Table 12 and Table 13 illustrate the final model variables used for Oklahoma and Arkansas, respectively.

Table 12. Oklahoma Energy Model Drivers, 2009

Economic Drivers Oklahoma Economic Outlook Other Drivers Residential OKC Real Personal Income^ Real Residential electric price, Heating- Degree Days (HDD), Cooling-Degree Days (CDD) Commercial OKC Real Personal Income^ Real Commercial electric price, HDD, CDD Industrial OKC Real Manufacturing Output ^ OKC Manufacturing Employment, Real Industrial electric price Petroleum Nominal Natural Gas Price Nominal Petroleum electric price Public Authority Real GSP^ Real Public Authority electric price, HDD, CDD Street lighting OKC Population Free Street Lighting Service Variable * Some models also have monthly-specific intercept and interaction terms. ^ Adjusted using definitions from OSU

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Table 13. Arkansas Energy Model Drivers, 2009

Economic Drivers Arkansas Economic Outlook Other Drivers Residential Fort Smith Real Personal Income Real Residential electric price, HDD, CDD Commercial Fort Smith Real Personal Income Real Commercial electric price, HDD, CDD Industrial Fort Smith Real Manufacturing GMP Fort Smith Manufacturing Employment Petroleum Nominal Natural Gas Price Real Electric Petroleum electric price Public Authority Fort Smith Real GMP Real Public Authority electric price, HDD, CDD Street lighting Fort Smith Population * Some models also have monthly-specific intercept and interaction terms.

2009 Energy Forecast Retail Forecast Table 14 summarizes the 2009 retail energy forecast (excluding line losses) by state and for the company as a whole. Weather-normalized annual retail sales are expected to grow from 25,219 GWh in 2008 to 30,029 GWh in 2019, which translates into a 19% increase over OG&E’s planning horizon, or an average annual increase of 1.6%. Projected growth rates associated with these data are comparable to those observed over the last decade. Weather-normalized sales grew by approximately 1.8% annually from 1997 through 2007. Average annual growth is projected to be lower from 2009 to 2013 (1.2%), consistent with economic growth rates noted in the Economic Outlook section of this report. Average annual sales growth in the last half of the forecast, the 2013–2018 period, will be higher (2%), again consistent with economic driver growth rate projections.

FERC Wholesale Sales Adjustments In 2009 Cadmus assumed responsibility for producing the forecasts of FERC wholesale sales. OG&E provided Cadmus with historical wholesale sales data and the expiration dates for current FERC wholesale contracts. Using an econometric forecasting approach similar to what was used for the retail energy forecast models, Cadmus produced separate forecasts of wholesale sales for all of the wholesale contracts. Out of model adjustments were then made to those forecasts to remove sales of expiring contracts from the overall wholesale forecast. Table 15 combines the forecasts of wholesale sales with the retail energy forecast from Table 14, yielding the final 2009 total energy sales forecast.

OG&E 2008 Load Forecast 22

Table 14. 2009 Retail Energy Forecast (MWh)

Public Street

Year Residential Commercial Authority Lighting Industrial Petroleum Total 2008 728,746 735,603 132,804 8,864 1,140,160 10,376 2,756,553 2009 736,434 739,223 129,125 8,946 1,041,916 9,661 2,665,304 2010 736,514 745,437 131,783 9,021 1,038,390 9,563 2,670,708 2011 745,580 761,500 137,266 9,107 1,088,214 9,633 2,751,299 2012 764,712 795,444 145,409 9,177 1,161,701 9,693 2,886,136 2013 789,033 838,612 151,451 9,243 1,221,860 9,737 3,019,937 2014 807,507 871,410 155,936 9,307 1,257,239 9,744 3,111,142 Arkansas Arkansas 2015 822,247 897,577 160,645 9,370 1,289,127 9,744 3,188,710 2016 836,370 922,648 165,433 9,432 1,321,842 9,753 3,265,478 2017 850,705 948,096 170,280 9,494 1,355,056 9,759 3,343,389 2018 864,688 972,917 175,042 9,555 1,387,410 9,766 3,419,379 2019 878,625 997,657 179,750 9,617 1,419,091 9,774 3,494,515 2008 8,125,791 5,676,337 2,788,358 54,259 2,996,484 2,820,735 22,461,965 2009 8,256,525 5,783,399 2,764,232 55,111 2,962,929 2,637,714 22,459,909 2010 8,308,333 5,871,086 2,753,659 55,893 3,013,852 2,670,993 22,673,817 2011 8,427,198 5,956,532 2,831,259 56,662 3,009,072 2,679,004 22,959,727

2012 8,567,229 6,082,497 2,909,811 57,413 2,998,697 2,674,999 23,290,646 2013 8,750,583 6,238,384 2,989,938 58,147 2,990,494 2,678,052 23,705,598 2014 8,941,723 6,402,662 3,066,634 58,871 2,982,715 2,684,836 24,137,441

Oklahoma 2015 9,133,033 6,574,330 3,151,144 59,587 2,982,273 2,703,481 24,603,847 2016 9,326,938 6,749,539 3,238,190 60,301 2,985,279 2,730,202 25,090,450 2017 9,512,871 6,915,249 3,321,329 61,013 2,991,268 2,748,430 25,550,161 2018 9,702,025 7,084,758 3,408,243 61,726 3,001,354 2,766,304 26,024,409 2019 9,901,442 7,263,310 3,499,962 62,442 3,020,590 2,787,070 26,534,816 2008 8,854,537 6,411,941 2,921,162 63,124 4,136,644 2,831,111 25,218,518 2009 8,992,959 6,522,621 2,893,356 64,056 4,004,845 2,647,375 25,125,213 2010 9,044,847 6,616,523 2,885,443 64,914 4,052,242 2,680,556 25,344,525 2011 9,172,778 6,718,032 2,968,525 65,769 4,097,286 2,688,637 25,711,026

2012 9,331,941 6,877,941 3,055,220 66,590 4,160,398 2,684,692 26,176,782 2013 9,539,616 7,076,997 3,141,389 67,390 4,212,353 2,687,789 26,725,534 2014 9,749,229 7,274,072 3,222,570 68,178 4,239,954 2,694,580 27,248,583

Total OG&E 2015 9,955,280 7,471,906 3,311,789 68,957 4,271,401 2,713,225 27,792,558 2016 10,163,308 7,672,188 3,403,623 69,733 4,307,122 2,739,955 28,355,929 2017 10,363,577 7,863,345 3,491,609 70,507 4,346,324 2,758,190 28,893,551 2018 10,566,713 8,057,675 3,583,285 71,281 4,388,764 2,776,070 29,443,788 2019 10,780,067 8,260,967 3,679,711 72,060 4,439,681 2,796,844 30,029,331

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Table 15. Energy Forecast Accounting for Changes in Wholesale Load

Energy (MWH) 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 FERC Sales (without losses) MUNICIPAL17 39,804 41,193 33,368 31,082 5,125 0 0 0 0 0 0 0 AVEC18 979,748 996,599 1,011,175 953,837 0 0 0 0 0 0 0 0 SPA19 76,380 76,324 79,029 33,012 12,048 0 0 0 0 0 0 0 OMPA 20 217,877 219,000 219,000 219,000 219,000 219,000 0 0 0 0 0 0 MDEA21 129,250 122,640 122,640 122,640 109,498 70,072 23,357 0 0 0 0 0 Total FERC Sales 1,443,059 1,455,755 1,465,213 1,359,570 345,671 289,072 23,357 0 0 0 0 0 Growth Rate in FERC sales 0.88% 0.65% -7.21% -74.57% -16.37% -91.92% -100% 0% 0% 0% 0% Retail Sales (without losses) Residential 8,854,537 8,992,959 9,044,847 9,172,778 9,331,941 9,539,616 9,749,229 9,955,280 10,163,308 10,363,577 10,566,713 10,780,067 Commercial 6,411,941 6,522,621 6,616,523 6,718,032 6,877,941 7,076,997 7,274,072 7,471,906 7,672,188 7,863,345 8,057,675 8,260,967 Industrial 4,136,644 4,004,845 4,052,242 4,097,286 4,160,398 4,212,353 4,239,954 4,271,401 4,307,122 4,346,324 4,388,764 4,439,681 Industrial Petroleum 2,831,111 2,647,375 2,680,556 2,688,637 2,684,692 2,687,789 2,694,580 2,713,225 2,739,955 2,758,190 2,776,070 2,796,844 Total Industrial 6,967,755 6,652,220 6,732,798 6,785,923 6,845,090 6,900,143 6,934,534 6,984,626 7,047,077 7,104,513 7,164,834 7,236,525 Public Authority and Street Lighting 2,984,286 2,957,413 2,950,357 3,034,294 3,121,810 3,208,779 3,290,748 3,380,746 3,473,356 3,562,116 3,654,566 3,751,771 Total Retail Sales 25,218,518 25,125,213 25,344,525 25,711,026 26,176,782 26,725,534 27,248,583 27,792,558 28,355,929 28,893,551 29,443,788 30,029,331 Growth Rate in Retail Sales -0.37% 0.87% 1.45% 1.81% 2.10% 1.96% 2.00% 2.03% 1.90% 1.90% 1.99% Total MWH Sales (with losses) Total Retail Sales + FERC 26,661,577 26,580,969 26,809,737 27,070,596 26,522,453 27,014,606 27,271,941 27,792,558 28,355,929 28,893,551 29,443,788 30,029,331 Losses22 1,786,326 1,858,010 1,874,001 1,892,235 1,853,919 1,888,321 1,906,309 1,942,700 1,982,079 2,019,659 2,058,121 2,099,050 Total Retail Sales + FERC, Losses 28,447,903 28,438,978 28,683,738 28,962,831 28,376,372 28,902,927 29,178,249 29,735,257 30,338,008 30,913,210 31,501,909 32,128,381 Add d Growth Rate in Total Sales -0.03% 0.86% 0.97% -2.02% 1.86% 0.95% 1.91% 2.03% 1.90% 1.90% 1.99% 17. 18. 17 Watonga contract can expire on February 28, 2012, Paris Contract can expire on September 30, 2011, Orlando contract can expire on January 20, 2010 and the Geary contract can expire on March 17, 2010 19. 18 AVEC contract can expire on November 30, 2011 20. 19 Paris contract can expire on January 31, 2011 and Vance contract can expire on May 31, 2012 21. 20 OMPA PSA contract terminates on December 31, 2013 and is removed from forecast at that time due to the absence of an Evergreen clause in the contract. 22. 21 MDEA contract 2 can expire on September 30, 2012 and MDEA contract 1 can expire on April 30, 2014 23. 22 The energy loss factor is 0.067 for 2008, and 0.0699 for 2009 and beyond.

OG&E 2008 Load Forecast 24

Energy Forecast Uncertainty Weather Uncertainty As with the load responsibility peak demand forecast, weather uncertainty in the energy models is represented through a Monte Carlo modeling approach where the last three decades of weather are systematically inputted into the various energy models to produce a distribution of possible sales outcomes. The weather-year Monte Carlo approach essentially runs all weather years from 1974 to 2008 through the weather-sensitive energy models and the peak demand model to develop a probability distribution of possible outcomes. Figure 6 shows the results directly from this modeling process for energy sales and includes FERC adjustments. Figure 6. Energy Model Forecast Outcomes by Weather Probability

34,000,000

33,000,000

32,000,000

31,000,000

30,000,000 MWh 29,000,000

28,000,000

27,000,000 1 out of 30 Years 1 out of 2 Years 29 out of 30 Years 26,000,000 Normal Weather

25,000,000 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

The 1 out of 2 years average weather line indicates there is a 50% probability that energy sales will reach this level or higher. The normal weather forecast is actually closer to the lower end of the distribution, with sales approximately 1.2% less (370,000 MWh on average per year) the 50% probability line. Now, consider the 1 out of 30 years forecast. This line, which is approximately 1,450,000 MWh higher than the normal weather forecast, shows energy sales under more extreme weather events occurring just 3% of the time. Finally, the lower bound forecast (29 out of 30 year case) shows sales may fall below the normal weather forecast by approximately 140,000 MWh if weather is milder than normal given expected economic performance.

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5. Retail Customer Forecasting Models

This section describes the methodology and results associated with state and revenue class customer forecasting. We first estimated these models in 2005, following the general approach for energy sales outlined in this report’s previous section.

Retail Customer Modeling Process and Forecast Approximately five to ten models were estimated for each segment, with 2008 data held as an “out-of-sample” forecasting test period. During the initial model specification phase, attempts were made at specifying models with a variety of different economic drivers. Table 16 and Table 17 illustrate the final model variables used for the Oklahoma and Arkansas retail customer forecasts, respectively. Table 16. Oklahoma Customer Model Drivers, 2009

Economic Drivers Oklahoma Economic Outlook Residential Population of Oklahoma City Commercial Population of Oklahoma City Industrial Employment in the Oklahoma City Manufacturing Sector Petroleum Stepped Nominal Natural Gas Price Forecast Public Authority Population of Oklahoma City Street lighting Population of Oklahoma City and Free Street Lighting Service Variable

Table 17. Arkansas Customer Model Drivers, 2009

Economic Drivers Arkansas Economic Outlook Residential Population of Ft. Smith Commercial Population of Ft. Smith Industrial Employment in the Ft. Smith Manufacturing Sector Petroleum Stepped Nominal Natural Gas Price Forecast Public Authority Population of Ft. Smith Street lighting Population of Ft. Smith

Table 18 summarizes the 2009 annual retail customer forecast by state and sector, and for the company as a whole.

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Table 18. 2009 Retail Customer Forecast

Public Street Residential Commercial Authority Lighting Industrial Petroleum Total 2008 53,718 8,644 1,421 26 379 55 64,244 2009 54,040 8,781 1,447 26 358 48 64,701 2010 54,365 8,932 1,484 27 352 44 65,203 2011 54,691 9,091 1,522 27 354 44 65,729

2012 55,019 9,222 1,539 27 356 45 66,209 2013 55,349 9,345 1,559 27 360 45 66,685 2014 55,681 9,465 1,581 28 360 45 67,160 Arkansas 2015 56,015 9,581 1,600 28 359 45 67,629 2016 56,351 9,696 1,619 28 358 45 68,098 2017 56,689 9,811 1,636 28 357 45 68,567 2018 57,030 9,926 1,650 28 356 45 69,034 2019 57,372 10,041 1,662 28 355 45 69,504 2008 603,678 75,917 13,870 224 2,743 6,294 702,726 2009 609,111 77,020 14,262 225 2,727 6,299 709,644 2010 614,593 77,969 14,651 226 2,753 6,227 716,419 2011 620,124 78,804 15,015 227 2,764 6,212 723,146

2012 625,706 79,613 15,371 227 2,767 6,193 729,877 2013 631,337 80,404 15,719 228 2,767 6,179 736,635 2014 637,019 81,185 16,062 229 2,766 6,167 743,428 Oklahoma 2015 642,752 81,957 16,402 229 2,763 6,163 750,267 2016 648,537 82,727 16,740 230 2,761 6,165 757,160 2017 654,374 83,495 17,078 231 2,758 6,171 764,106 2018 660,263 84,263 17,416 231 2,756 6,175 771,103 2019 666,205 85,036 17,756 232 2,754 6,180 778,163 2008 657,396 84,560 15,291 250 3,122 6,349 766,969 2009 663,151 85,800 15,709 252 3,086 6,347 774,345 2010 668,958 86,901 16,135 253 3,105 6,271 781,623 2011 674,815 87,895 16,537 254 3,118 6,257 788,875

2012 680,725 88,836 16,910 255 3,123 6,237 796,086 2013 686,686 89,749 17,278 256 3,127 6,225 803,320 2014 692,700 90,649 17,643 256 3,126 6,212 810,587

Total OG&E 2015 698,767 91,539 18,002 257 3,122 6,208 817,896 2016 704,888 92,423 18,360 258 3,119 6,210 825,258 2017 711,063 93,306 18,714 259 3,115 6,216 832,673 2018 717,293 94,189 19,065 260 3,112 6,220 840,138 2019 723,577 95,077 19,418 261 3,109 6,225 847,667

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6. Data Sources

OG&E’s service territory encompasses approximately half of Oklahoma and a small area in western Arkansas, including and surrounding Ft. Smith. Historical data sources used to estimate the econometric equations and prepare the 2009 forecast are divided into the following categories: • OG&E company data (energy sales, revenue, and load responsibility peak demand); • Constructed variables for the models (usually binary variables); • Weather information; and • Economic and demographic data from OSU and Moody’s Economy.com. This section describes each of these categories and the types of variables used in the econometric models.

Internal Company Information Sales and Prices OG&E’s Accounting Department provides sales (MWh), revenue, and customer data by revenue class. This information is recorded in the monthly energy sales report for both Oklahoma and Arkansas jurisdictions. The monthly energy sales report contains information from the 1970s to the present. The six revenue classes are: • Residential • Commercial • Industrial • Industrial-Petroleum • Public Authority • Street Lighting Monthly residential, commercial, industrial, industrial-petroleum, public authority, and street lighting sales data are modeled separately by state. In the econometric models with statistically significant electric price variables, these variables are defined as “average” prices (energy revenues divided by energy sales).

Load Responsibility The peak load forecasts are obtained based on historical “Normalized Load Responsibility” data (defined as the System Load minus OMPA Total Load plus OMPA PSA28 plus Load Curtailment plus real-time pricing (RTP) induced self-generation). The normalized load responsibility series was further adjusted for peak demand modeling purposes by subtracting variable OMPA PSA loads and forecasting these directly as wholesale FERC loads.

23 OMPA PSA contract terminates 12/31/2013 and is removed from forecast at that time due to the absence of an Evergreen clause in the contract.

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Information Obtained from External Sources Weather Data OG&E obtained the following information from the Department of Commerce, NOAA: • Cooling-degree days (CDD). • Heating-degree days (HDD). • A variety of hourly weather indicators, including temperature, humidity, dew point, precipitation, wind speed, and cloud cover. NOAA’s definition of HDD is 65° minus the average of the high and low temperatures of the day (or zero if the average of the high and low temperatures is greater than 65°). The definition of CDD is the average of the high and low temperatures of the day minus 65° (or zero if the average of the high and low temperatures of the day is less than 65°). HDD and CDD for Ft. Smith and Oklahoma City have been used in weather-sensitive sales forecasting equations. Hourly weather data from these stations, and from Guthrie, Stillwater, and Muskogee, were used to model and forecast peak loads.

Economic and Demographic Data OG&E purchases economic and demographic data from OSU and Moody’s Economy.com. The data include historical and forecasted time series used in the econometric models; these data include population, real income, wages and salaries, price deflators, various production and output series, including industrial production and GSP, and natural gas prices, and employment.

OG&E 2008 Load Forecast 30