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Home My WebLink About20110401Vol II 2011 IRP.pdfPACIFICORP Rocky Mountin Power Pacifc Power PaclfiCorp Energ I Interat d sure ~-...~:: . \lumell.. ppendices PAC-E-ll-10 March 31., 20.1 1 This 2011 Integrated Resource Plan (IRP) Report is based upon the best available information at the time of preparation. The IRP action plan wil be implemented as described herein, but is subject to change as new information becomes available or as circumstances change. It is PacifCorp's intention to revisit and refresh the IRP action plan no less frequently than annually. Any refreshed IRP action plan wil be submitted to the State Commissions for their information. For more information, contact: PacifCorp IRP Resource Planning 825 NE. Multnomah, Suite 600 Portland, Oregon 97232 (503) 813-5245 irp(iacfficorp. com http://wvvw.pacificorp.com This report is printed on recycled paper Cover Photos (Left to Right): Wind: McFadden Ridge I Thermal-Gas: Lake Side Power Plant Hydroelectric: Lemolo 1 on North Umpqua River Transmission: Distribution Transformers Solar: Salt Palaee Convention Center Photovoltaic Solar Project Wind Turbine: Dunlap I Wind Project PACIFiCORP-2011 IRP TABLE OF CONTENTS TABLE OF CONTENTS TABLE OF CONTENTS............................................................................................................................................1 INDEX OF TABLES.............................................................................................................................................. IV INDEX OF FIGURES .............................................................................................................................................. VI APPENDIX A - LOAD FORECAST DETAILS .....................................................................................................1 INTRODUCTION ........................................................................................................................................................1 Load Forecast. ....... ...... ......... ...... ... ....... ..... ...... ....... ..... ......... .... ..... ...... ....... ......... ..... .... ... .... ....... ............. ..... .......1 METHODOLOGY OVERVIEW ....................................................................................................................................1 Class 2 Demand-side Management Resourees in the Load Forecast ..................................................................3 Modeling overview .... ...... .... .... ..... .... ....... .... ....... .... ... .... .... .............. ...... ....... .... ..... .... ....... .... ....... ............. ..... ....... 3 SALES FORECAST AT THE CUSTOMER METER........................................................................................................5 State Summaries.. ... .... ....... .... ..... .... ....... ..... .... ....... .... ... .... ....... .... ......... ..... ....... .... ..... ...... ..... ....... ............. ....... .....5 Oregon..............................................................................................................................................................................5 Washington .......................................................................................................................................................................6 California .......... .... ........ .......... .... ..... ...... .... ...... .... ............ ...... .... .... .... ...... ...... ...... ....... .......... ....... .... .... ........ ........ .... .... ..... 7 Utah ..................................................................................................................................................................................8 Idaho.................................................................................................................................................................................9 Wyoming..........................................................................................................................................................................9 LOAD FORECAST AT THE GENERATOR ................................................................................................................10 Energy Forecast.................................................................................................................................................10 Jurisdictional Peak Load Forecast ....................................................................................................................11 System-Wide Coincident Peak Load Forecast ............................;...................................................................... II ALTERNATIVE LOAD FORECAST SCENARIOS........................................................................................................13 APPENDIX B - IR REGULATORY COMPLIACE .......................................................................................15 INTRODUCTION .....................................................................................................................................................15 GENERAL COMPLIACE ........................................................................................................................................15 California ..... ......... ......... .... ....... .... ......... ..... ....... .... ....... .... .... ..... ..... ....... ...... ..... .... ..... ...... ...... ....... ......... ........... .16 Idaho..................................................................................................................................................................16 Oregon...............................................................................................................................................................17 Utah ...................................................................................................................................................................17 Washington ........................................................................................................................................................17 Wyoming............................................................................................................................................................18 APPENDIX C - ENERGY GATEWAY SCENARO PORTFOLIOS.................................................................47 TRASMISSION SCENARIO ANALYSIS AND COST DETAIS..................................................................................47 SYSTEM OPTIMIZER PORTFOLIO TABLES.............................................................................................................52 APPENDIX D - SYSTEM OPTIMIZER DETAILED MODELING RESULTS................................................89 PORTFOLIO CASE BUILD T ABLES.........................................................................................................................93 ANNUAL CARON DIOXIDE EMISSION TRENDS .................................................................................................132 APPENDIX E - STOCHASTIC PRODUCTION COST SIMULATION RESULTS.......................................133 CORE CASE STUDY STOCHASTIC RESULTS.........................................................................................................133 Mean versus Upper-tail Mean PVRR Scatter-plot Charts ...............................................................................133 COAL PLANT UTILIZATION SENSITIVITY AND LOAD FORECAST SCENARO STOCHASTIC STUDY RESULTS ...144 PORTFOLIO PVR COST COMPONENT COMPARISON ......................................................................................146 Core Case Portfolios........................................................................................................................................146 APPENDIX F - THE PUBLIC INPUT PROCESS ..............................................................................................153 PARTICIPANT LIST .............................................................................................................................................153 1 P ACIFICORP - 20 11 INTEGRATED RESOURCE PLAN TABLE OF CONTENTS Commissions ....................................................................................................................................................153 Intervenors................................................................................................................................ ...................... .154 Others...............................................................................................................................................................155 PUBLIC INPUT MEETINGS ....................................................................................................................................155 General Meetings.............................................................................................................................................155 April 28, 2010 ............................................................................................................................................................... 155 August 4, 2010..............................................................................................................................................................155 October 5,.2010.............................................................................................................................................................155 Decembet 15, 2010....................................................................................................................................................... 156 January 27, 2011........................................................................................................................................................... 156 Januar 31, 2011 ........................................................................................................................................................... 156 February 23,201 1 ......................................................................................................................................................... 156 March 23, 2011 ............................................................................................................................................................. 156 State Meetings. ..... ....... ............. ..... ............... ....... ......... ....................... ...... ....... ....... .... ....... ...... ..... ............ .......156 June 16,2010 - Oregon / California .............................................................................................................................156 June 29, 2010 - Uta .................................................................................................................................................... 156 July 28, 2010 - Idaho.................................................................................................................................................... 157 August 11,2010 - Wyoming ........................................................................................................................................157 PARG LOT ISSUES...........................................................................................................................................158 PUBLIC REVIW OF IRP DRA DOCUMENT ......................................................................................................158 CONTACT INFORMTION .....................................................................................................................................158 APPENDIX G - HEDGING STRATEGY ............................................................................................................161 INTRODUCTION ....................................................................................................................................................161 ÌlEDGING ....................................................................................................................:.........................................161 Purpose of Hedging .........................................................................................................................................161 Needfor Hedging.............................................................................................................................................161 Impact of Hedging and Hedging Costs.... ...................... .................. ......... ....... ............. ......... ....... ........... ..... ...162 Hedge Products................................................................................................................................................163 No "Best" Hedging Strategy......................................................................... ...................................................163 SAMPLE PORTFOLIO SIMULATIONS ....................................................................................................................164 RESULTS ...............................................................................................................................................................164 CONCLUSION ........................................................................................................................................................169 APPENDIX H - WESTERN RESOURCE ADEQUACY EVALUATION........................................................171 INTRODUCTION ....................................................................................................................................................171 WESTERN ELECTRICITY COORDINATING COUNCIL RESOURCE ADEQUACY ASSESSMENT .............................171 PACIFIC NORTHWEST RESOURCE ADEQUACY FORUM'S ADEQUACY ASSESSMENT ........................................177 MART RELIANCE STRESS TEST .......................................................................................................................177 Market Stress Test Design................................................................................................................................177 Stress Test Results ............................................................................................................................................178 CUSTOMER VERSUS SHARHOLDER RISK ALLOCATION ....................................................................................179 APPENDIX I - WIND INTEGRATION STUDy...............................................................................................181 2010 WIND INTEGRATION RESOURCE STUDy....................................................................................................183 1. EXECUTIVE SUMY ..............................................................................................................................183 2. DATA COLLECTION ..................................................................................................................................185 2.3.1 Overview of the Wind Generation Data Used in the Analysis ................................................................186 2.3.2 Historical Wind Generation Data ...........................................................................................................186 2.4.1 Categorization of Historical Wind Data to Determine Simulation Scope............................................... 189 2.4.2 Simulation Process..................................................................................................................................190 3. METHODOLOGy........................................................................................................................................192 4. RESULTS.....................................................................................................................................................209 ApPENDIX A..........................................................................................................................................................217 Simulation of Wind Generation Data... .... ..... ....... .... ... .... ... ..... ...,.. ..... ......... .... ... ....... ...... ..... ....... .... ... .... ..... .... .217 A.1 Detailed Discussion of Statistical Patterns of the Historical Wind Output Data ......................................217 A.2 Time Pattern of the Historical Wind Data.................................................................................................219 11 PACIFICORP - 2011 IRP TABLE OF CONTENTS A.3 Data Clean-up and Verifcation ................................................................................................................222 A.4 Wind Data Simulation Methodology..................,.......................................................................................224 A.4.1 General Description.............................................................................................................................................224 AA.2 Wind Generation Estimation Model Specification.............................................................................................. 224 AA.3 Wind Generation Estimation Model for Constrined Output .............................................................................. 225 AAA Using NREL's Wind Data to Faciltate Wind Simulation for Sites without Historical Information ................... 226 AA.5 Pairing of Wind Profiles Used for Regression .................................................................................................... 228 A.4.6 Regression Analysis ............................................................................................................................................230 AA.7 Estimate Mean Values of the Predicted............................................................................................................... 230 AA.8 Calculating the Regression Residuals.................................................................................................................. 231 AA.9 Sample of Residuals According to Simulated Output Ranges............................................................................. 232 AA.1O Application of a Non-Linear 3-Step Median Smoother to the Sampled Residuals............................................ 233 ApPENDIX B..........................................................................................................................................................234 Regression Coeffcients and Relative Signifcanee ..........................................................................................234 ApPENDIX C..........................................................................................................................................................241 Operating Reserve Demand Seasonal Detail...................................................................................................241 APPENDIX J - STOCHASTIC LOSS OF LOAD STUDY .................................................................................245 INTRODUCTION ....................................................................................................................................................245 Loss OF LOAD PROBABILITY METRICS ..............................................................................................................245 SIMULATION PERIOD ...........................................................................................................................................246 MODELING ApPROACH OVERVIW .....................................................................................................................246 PLANING RESERVE MARGIN BUILD-UP ............................................................................................................246 MONTE CARLO PRODUCTION COST SIMULATION..............................................................................................248 MODELING OPERATING RESERVES.....................................................................................................................251" STUDY RESULTS ...................................................................................................................................................252 SELECTION OF A LOLP R1LIAILITY TARGET .....................................................................................254 CAPACITY PLANNING RESERVE MARGIN DETERMINATION ..............................................................................255 CONCLUSION ........................................................................................................................................................255 APPENDIX K - HYROELECTRIC CAPACITY ACCOUNTING ................................................................257 INTRODUCTION ....................................................................................................................................................257 ELIGmLE SUSTAIED PEAKNG HYDRO FACILITIES..........................................................................................257 Sustained Hydro Peaking Capabilty for Lewis River Facilties......................................................................258 ApPLICABILITY OF AN 18-HOUR SUSTAIED PEAKG CAPABILITY STANDAR FOR PACIFCORP .................259 CONCLUSION .......................................................................................................................................................259 APPENDIX L - PLANT WATER CONSUMPTION .....................................................................................;....261 iii P ACIFICORP - 2011 IR INDEX OF TABLES INDEX OF TABLES TABLE A,1 - SYSTEM ANAL SALES FORECAST (IN GIGAWATT-HOUR) 2011 THROUGH 2020...................................1 TABLE A.2 - FORECASTED SALES GROWTH IN OREGON ................................................................................................6 TABLE A.3 - FORECASTED SALES GROWTH IN WASHINGTON........................................................................................6 TABLE A.4 - FORECASTED RETAIL SALES GROWTH IN CALIFORNIA.............................................................................. 7 TABLE A.5 - FORECASTED RETAIL SALES GROWTH IN UTAH ........................................................................................8 TABLEA.6 -FORECASTED RETAIL SALES GROWT IN IDAHO.......................................................................................9 TABLE A.7 - FORECASTED RETAIL SALES GROWTH IN WyOMING...............................................................................1 0 TABLE A.8 - FORECASTED AVERAGE ANAL ENERGY GROWTH RATES FOR LOAD ............................................ ......11 TABLE A.9 - ANAL LOAD FORECASTED (IN MEGAWATT-HOUR) 2011 THOUGH 2020 .................................... ......11 TABLE A.lO - FORECASTED COINCIDENTAL PEAK LOAD GROWT RATES .................................... ........... ...................12 TABLE A.ll - FORECASTED COINCIDENAL PEAK LOAD IN MEGA WA TI.................... ........ ...................................... .12 TABLE B.l - INTEGRATED RESOURCE PLANING STANDARS AN GUIDELINS SUMMAY BY STATE ..................... .19 TABLE B.2 - HANDLING OF 2008 IR ACKNOWLEDGEMENT AND OTHER IR REQUIREMENTS ..... ....... ............. ..........23 TABLE B.3 - OREGON PUBLIC UTILITY COMMISSION IR STANDAR AND GUIDELINS .............................................31 TABLE B.4 - UTAH PuLIC SERVICE COMMISSIONIR STANDAR AND GUIDELINS .................................................38 TABLE B.5 - WASHINGTON UTILITIES AN TRASPORTATION COMMISSION IRP STANARD AND GUIDELINES (WAC 480-1 00-238)......................................................................................................................................................43 TABLE B.6 - WYOMING PUBLIC SERVICE COMMISSION IRP STANAR AND GUIDELINS (DOCKET 90000-107 -XO- 09)......................................................................................................................................................................46 TABLE C.l - TRSMISSION COST DETAILS, GREEN RESOURCE Fu ....................................................................50 TABLE C.2 - TRSMISSION COST DETAILS, INCUMBENT RESOURCE Fu ................. ......... ........... .... ...................51 TABLE C.3 - ENERGY GATEWAY SCENARO DEVELOPMENT TABLE ......................................................... ...................53 TABLE C.4 - ENERGY GATEWAY SCENARO PVR RESULTS ........................................................ ..............................54 TABLE C.5 - ENERGY GATEWAY SCENARO PORTFOLIO RESULTS...............................................................................56 TABLE C.4 - ENERGY GATEWAY SCENARO EVALUATION RESULTS (W STUIES) ........................ ....... ................... 72 TABLE D.l - RESOURCE NAME AN DESCRITION ............................... ............................. ......... ..................................90 TABLE D.2 - TOTAL PORTFOLIO CUMATIVE CAPACITY ADDITIONS BY CASE AN RESOURCE TYE, 2011 - 2030..94 TABLE D.3 - CORE CASE SYSTEM OPTIMIZER PVR RESULTS ..................................................... ..............................95 TABLED.4-CORECASEPORTFOLIOS(CASE 1 TO 14) ................................................................................................96 TABLE D.5 - HA CAP C02 POLICY CORE CASE (15 TO 18)....................................................................................111 TABLE D.6 - 2011 BusINSS lO-YEAR PLAN CASE STUY 19....................................................................................115 TABLE D. 7 _ PORTFOLIO DEVELOPMENT ASSUMTIONS AN SYSTEM OPTIMIZER PVR RESULTS FOR SENSITVITY CASES (20 TO 33) ..............................................................................................................................................116 TABLE D.8 - COAL PLAN UTILIZATION SENSITITY CASES (20 TO 24) ...................................................................117 TABLE D.9 - LOAD FORECAST SENSITIIT CASES (25 TO 27) ..................................................................................122 TABLE D.lO - RENEWABLE RESOURCE SENSITVIT CASES (28 TO 30A)...................................................................125 TABLE D.ll - DEMAND-SIDE MAAGEMENT SENSITVITY CASES (31 TO 33) ...........................................................129 TABLE E.l- STOCHASTIC MEAN PVR BY CO2 TAX LEVEL, CORE CASE PORTFOLIOS...... ......... ..............................138 TABLE E.2 - STOCHASTIC RISK RESULTS BY CO2 TAX LEVEL, CORE CASE PORTFOLIOS ..........................................138 TABLE E.3 - CARBON DIOXIDE AN OTHER POLLUTANT EMISSIONS...................................................... .................. .140 TABLE E.4- CUMULATIV 10-YEAR CUSTOMER RATE IMPACT, CORE CASE PORTFOLIOS ........................................140 TABLE E.5 - Loss OF LOAD PROBABILITY FOR A MAJOR (:; 25,000 MWH) JULY EVENT, CORE CASE PORTFOLIOS ..142 TABLE E.6 - AVERAGE Loss OF LOAD PROBABILITY DURIG SUMMER PEAK ....................................... ............. ......143 TABLE E. 7 - STOCHASTIC MEAN PVR BY CO2 TAX LEVEL, SENSITIVITY PORTFOLIOS ..........................................144 TABLE E.8 - STOCHASTIC RISK RESULTS BY CO2 TAX LEVEL, SENSITVITY PORTFOLIOS .................. .......................144 TABLE E.9 - CORE CASES 1 THROUGH 8, PORTFOLIO PVR COST COMPONENTS ($19 CO2 TAX LEVEL) ....... ..... .....146 TABLE E.1 0 - CORE CASES 9 THROUGH 16, PORTFOLIO PVR COST COMPONENTS ($19 CO2 TAX LEVEL) ... ..........147 TABLE E.ll - CORE CASES 17 THROUGH 19, PORTFOLIO PVR COST COMPONETS ($19 CO2 TAX LEVEL) ...........148 TABLE E.12 - COAL PLANT UTILIZATION SENSITVITY AND LOAD FORECAST SCENARO ($19 CO2 TAX LEVEL) .....149 TABLE E.1 3 - COAL PLANT UTILIZATION SENSITIVITY AN LOAD FORECAST SCENARIO ($0 CO2 TAX LEVEL) .......150 TABLE E.1 4 - COAL PLAN UTILIZATION SENSITIVIT AN LOAD FORECAST SCENARIO ($12 CO2 TAX LEVEL) .....151 TABLE G.l - COMPARISON OF MULTIPLE SAMPLE PORTFOLIOS ....................................... .................... .....................165 iv PACIFiCORP-2011 IR INDEX OF TABLES TABLE H.l - PEAKG RESOURCE MEGAWATT CAPACITY REQUIMENTS AN FIXD COSTS .................................178 TABLE H.2 - STOCHASTIC PVR DETAILS FOR STRESS TEST AND BASE PORTFOLIO SIMLATIONS .........................179 TABLE 1. ANAL AVERAGE OPERATING RESERVE DEMAN BY PENETRATION SCENARO. ........................................183 TABLE 2. ANAL AVERAGE OPERATIG RESERVE DEMAND INCREMENTAL TO THE LOAD ONLY SCENARO.............. 183 TABLE 3. WIN INTEGRATION COSTS PER MWH OF WI GENERA TED AS COMPARD TO THOSE IN THE 2008 IR ....184 TABLE 4. STATISTICAL PROPERTIES OF WI SITE CAPACITY FACTOR DATA. .............................................................188 TABLE 5. HOURLY CORRLATION OF SYSTEM WIN AND SYSTEM LOAD. ...................................................................188 TABLE 6. COMPARSON OF OPERATING RESERVE DEMAND CALCULATED FROM ACTUAL WI GENERATION PLANT DATA AND SIMUATED WI GENRATION PLAN DATA ESTIMATED USING A LEAST SQUARS REGRESSION AND APPLYING DIFFERENT SCALING OF ERRORS ADDED BACK INO THE RAW PREDICTION....................................... 190 TABLE 7. WIN PENETRATION SCENARIOS USED IN PAR AS A PERCENTAGE OF TOTALFLEETCAPACIT...................202 TABLE 8. WIN INGRATION COST SIMULATIONS IN PAR.........................................................................................203 TABLE 9. ALLOCATION OF OPERATING RESERVE DEMAN TO REGULATION, SPINING AN NON-SPING RESERVE CATEGORIES IN PAR................. ............... ..... ........................ ............... .............. .................... .... ................... .....205 TABLE 10. RESERVE SERVICE CAPABILITY OF EACH GENERATING UNIT IN PAR. ........................................................206 TABLE 11. ANAL AVERAGE OPERATING RESERVE DEMAND BY PENETRTION SCENARO.......................................209 TABLE 12. PAR SIMULATION RESULTS FOR THE LOAD ONLY SCENARO AND THE 425 MW WI PENETRTION SCENARIO..........................................................................................................................................................214 TABLE 13. PAR SIMUATION RESULTS FOR THE 1,372 MW AND 1,833 MWWIDPENETRATION SCENARIOS............215 TABLE 14. WIND INTEGRATION COST COMPARSON TO THE 2008 IR........................................................................216 TABLE lA. SUMMARY OF WI PLAN START DATES AN NAMEPLATE CAPACITY. ...................................................223 TABLE 2A. NRL PROXIES SELECTED FOR PERTINT P ACIFICORP PLANS. ..................... .......................................227 TABLE 3A. PAIRS OF WIN PROJECTS USED IN DATA SIMUATION. ............................. ................................................229 TABLE 4A. PREDICTIVE CAPACITY FACTOR COEFFICIENTS FOR THE SIMUATION OF GOODNOE HILLS WI GENERATION USING LEANING JUNIPER ACTUAL GENERATION DATA. ................................................................230 TABLE 1.1- RESOURCE CAPACITY ADDITIONS NEEDED TO REACH PRM TARGET LEVELS .......................................247 TABLE K.l - PEAKIG CAPABILITY COMPARISON FOR LEWIS RIR HYDRO FACILITIES.......... ..... ...................... .....258 TABLE L.l ~ PLANT WATER CONSUMPTION WITH ACRE-FEET PER YEAR.. ...................... ................................... ......262 TABLE L.2 - PLAN WATER CONSUMPTION BY STATE ...................................... ........................................................263 TABLE L.3 - PLAN WATER CONSUMPTION BY FUEL TYPE .......................................................................................263 TABLE LA - PLAN WATER CONSUMPTION FOR PLANTS LOCATED IN THE UPPER COLORADO RIER BASIN ...........264 V PACIFiCORP-2011 IR INDEX OF TABLES INDEX OF FIGURES FIGURE A.l- LOAD FORECAST SCENAROS FOR Low, MEDIU, HIGH AN PEAK ......................................................14 FIGURE A.2 - COINCIDENT PEAK LOAD FORECAST COMPARISON TO PAST IRs ................................. ........................14 FIGURE C.l - WESTERN RENEWABLE ENERGY ZONES PLUS ENERGY GATEWAY SCENARO 1.......... ........ ...................48 FIGURE D.l - CORE CASES: CO2 EMISSION PROFILE FOR MEDIU CO2 TAX COSTS .................................................132 FIGURE E.l - STOCHASTIC COST VERSUS UPPER-TAIL RISK, ZERO CO2 TAX SCENARIO ...................... ..... ................134 FIGUR E.2 - STOCHASTIC COST VERSUS UPPER-TAIL RISK, MEDIU CO2 TAX SCENARIO ............. .........................135 FIGURE E.3 - STOCHASTIC COST VERSUS UPPER-TAIL RISK, Low TO VERY HIGH CO2 TAX SCENARIO ................. ...136 FIGURE E.4 - STOCHASTIC COST VERSUS UPPER-TAIL RISK, AVERAGE FOR CO2 TAX SCENARos............................137 FIGUR E.5 - AVERAGE ANNAL ENERGY NOT SERVED (2011 - 2030), $19 CO2 CORE CASE PORTFOLIOS .............141 FIGURE G.l- PACIFICORP'S ANAL ELECTRCITY AN NATU GAS HEDGING COSTS .......................................162 FIGURE G.2 - REFERENCE PORTFOLIO VERSUS LESS HEGED PORTFOLIO................................................................. 166 FIGURE G.3 - REFERENCE PORTFOLIO VERSUS MORE HEDGED PORTFOLIO............................................................... 167 FIGUR G.4 - REFERENCE PORTFOLIO VERSUS HEDGING ONLY NATUL GAS ........................................................168 FIGURE G.5 - REFERENCE PORTFOLIO VERSUS HEDGING ONLY ELECTRICITY ...........................................................169 FIGURE H.l - WECC FORECASTED POWER SUPPLY MAGINS ............................................. ............................... ......172 FIGURE H.2 - BASIN FORECASTED POWER SUPPLY MAGINs.................................. ............................... ......... ..........173 FIGURE H.3 -BASIN FORECASTED POWER SUPPLY MAGINS WI SELECTED CAPACITY ADDITIONS ......................174 FIGURE H.4 - DESERT SOUTHWEST FORECASTED POWER SUPPLY MAGINs............................................................. 175 FIGUR H.5 - ROCKIES FORECASTED POWER SUPPLY MAGINS ...............................................................................176 FIGURE H.6 - FRONT OFFICE TRASACTION MAT PRICE COMPARSON............................................................... 178 FIGUR 1. RAw HISTORICAL WIN PRODUCTION AN LOAD DATA INORY. ...................................... ...................185 FIGURE 2. MA OF PACIFICORP WI GENERATIG STATIONS USED IN THIS STIY .............................................. .....187 FIGURE 3. CA TEGORIZA TION OF WI GENRATION DATA. ...............................................;............................ ............190 FIGURE 4. SAMPLE OF INNDED SCHEDULE TE-MIN LOAD ESTIMATE AN OBSERVED SYSTEM LOAD................ 194 FIGUR 5. VARBILIT BETWEN THE LIN OF INNDED SCHEDULE AN OBSERVED LOAD WITH ERRORS HIGHLIGHTED BY GREEN AROWS. ..................................................... ........... ........................................ ............195 FIGURE 6. INDEPENDENT FORECAST ERRORS IN TEN-MIN INTERVAL LOAD AN WIND GENERATION (DECEMBER 2008, APPROXIMATELY 890 MW OF WI PENETRTION). ...............................................................................196 FIGUR 7. WIND REGULATION ERRORS PLOTTD FOR THE MAYS OF THE INITIA TERM AT THE 1,372 MW WIN CAPACITY PENETRTION LEVEL. ..... .................... .......................................... ........... ....... ..................................197 FIGURE 8. LOAD REGULATION ERRORS PLOTTED FOR THE MAYS OF THE INITIAL TERM. .. .................... ......... ............197 FIGUR 9. EXAMPLE OF BIN ANALYSIS FOR LOAD FOLLOWIG RESERVE SERVICE FROM LOAD VARIABILITY IN THE WEST BALANCING AUTORITY ARA (MY 2007-2009).................................................................................199 FIGURE 10. EXAPLE OF BIN ANALYSIS FOR LOAD FOLLOWIG RESERVE SERVICE FROM LOAD VARILITY IN THE EAST BALANCING AUTORITY ARA (MY 2007-2009)..................................................................................199 FIGURE 11. EXAPLE OF BIN ANALYSIS FOR LOAD FOLLOWIG RESERVE SERVICE FROM WI VARILITY AT THE 1,372 MW PENETRATION LEVEL FOR THE WEST BALANCING AUTORITY ARA (MAY 2007-2009). ........ ......200 FIGUR 12. EXAMPLE OF BIN ANALYSIS FOR LOAD FOLLOWING RESERVE SERVICE FROM WID VARBILITY AT THE 1,372 MW PENETRATION LEVEL FOR THE EAST BALANCING AUTORITY AREA (MAY 2007-2009). ...............200 FIGUR 13. PAR TRASMISSION TOPOLOGY. .............................................................................................................208 FIGUR 14. LOAD FOLLOWIG UP OPERATING RESERVE SERVICE DEMAND IN THE WEST BALANCING AUTHORIY ARA. ...............................................................................................................................................................210 FIGURE 15. LOAD FOLLOWING DOWN OPERATING RESERVE SERVICE DEMAD IN THE WEST BALANCING AUTHORIY ARA. ...............................................................................................................................................................210 FIGURE 16. REGULATION UP OPERATING RESERVE SERVICE DEMAN IN THE WEST BALANCING AUTHORITY ARA. 211 FIGURE 17. REGULATION DOWN OPERATING RESERVE SERVICE DEMAN IN THE WEST BALANCING AUTHORITY ARA. .........................................................................................................................................................................211 FIGURE 18. LOAD FOLLOWIG UP OPERATIG RESERVE SERVICE DEMA IN THE EAST BALANCING AUTHORITY ARA. ...............................................................................................................................................................212 FIGURE 19. LOAD FOLLOWIG DOWN OPERATING RESERVE SERVICE DEMAND IN THE EAST BALANCING AUTHORITY ARA. ...............................................................................................................................................................212 FIGUR 20. REGULATION UP OPERATING RESERVE SERVICE DEMAN IN THE EAST BALANCING AUTHORITY ARA. .213 VI PACIFiCORP-2011 IRP INDEX OF TABLES FIGUR 21. REGULATION DOWN OPERATING RESERVE SERVICE DEMAN IN THE EAST BALANCING AUTHORI ARA. .........................................................................................................................................................................213 FIGUR lA. LEANING JUNIPER 2009 MONTLY CAPACITY FACTORS. .........................................................................217 FIGUR 2A. COMPARSON OF LEANG JUNIPER AND COMBIN HILLS CAPACITY FACTORS................ .......................218 FIGUR 3A. DAILY GENERATION PATTERNS OF SEVERA PACIFICORP WID PLANTS. ................................................218 FIGUR 4A. DISTRIBUTION OF OBSERVED 2009 HOURY CAPACITY FACTORS AT LEANING JUNIPER..........................219 FIGUR 5A. DISTRIBUTION OF OBSERVED 2009 HOURY CAPACITY FACTORS AT COMBINE HILLS.............................219 FIGUR 6A. AUTOCORRLATION COEFFICIENTS FOR SUCCESSIV TEN MINE LAGS IN CAPACITY FACTOR FOR LEANING JUNIPER. ....................................................... .......................... ................................. ................ ..........220 FIGUR 7 A. AUTOCORRLATION COEFFICIENTS FOR SUCCESSIVE TEN MINE LAGS IN CAPACITY FACTOR FOR COMBINE HILLS. ... ........... ...... ................................................................... .... .... ............................. ...................221 FIGUR 8A. PARTIA AUTOCORRLATION COEFFICIENTS FOR LAGS IN CAPACITY FACTOR FOR LEANING JUNIPER.....221 FIGUR 9A. PARTIAL AUTOCORRLATION COEFFICIENTS FOR LAGS IN CAPACITY FACTOR FOR COMBIN HILLS. ......222 FIGURE 10A. WIN GENERATION DATA DEVELOPMENT FLOW CHART. .......................... ...... ...................... .................229 FIGURE llA. COMPARSON OF ACTUAL GOODNOE HILLS CAPACITY FACTORS WITH PREDICTED MEAN GOODNOE HILLS CAPACITY FACTORS DERID OFF OF LEANING JUNIPER GENERATION DATA. ...................................................231 FIGUR 12A. HIGHLY NON-NORMAL RESIDUALS FROM BIN 5 OF THE MARCH REGRESSION OF GOODNOE HILLS CAPACITY FACTOR DERIVED FROM OBSERVED LEANG JUNIPER DATA. ..........................................................232 FIGUR 13A. HIGHLY NON-NORMAL RESIDUALS FROM BIN 7 OF THE MACH RERESSION OF GOODNOE HILLS CAPACITY FACTOR DERED FROM OBSERVED LEANING JUNIPER DATA. ..........................................................232 FIGUR J. - EXISTING RESOURCES, LOADS & SALES, AND RESOURCES WITH RESERVE REQUIMENTS .................248 FIGURE 1.2 - UTAH NORTH LOAD ARA ....................................................................................................................249 FIGURE J.3 - UTAH SOUT LOAD ARA.....................................................................................................................249 FIGUR J.4 - WALLA WALLA, WASHINGTON LOAD ARA .... ...................... ................................... ............................249 FIGUR 1.5 - WEST MAIN (OREGON, NORTHERN CALIFORNIA) LOAD ARA .............................................................250 FIGUR 1.6- YAKMA LOAD ARA ............................................................................................................................250 FIGUR 1. 7 - GOSHEN IDAHO LOAD ARA .................................................................................................................250 FIGURE J.8 - NORTHEAST WYOMING LOAD ARA .....................................................................................................251 FIGURE 1.9 - SOUTHWEST WYOMING LOAD ARA ............................. ....... ............. ............... ....... ..............................251 FIGURE J.1O - SYSTEM LOLH BY PLANING RESERVE MAGIN LEVEL ....................................................................253 FIGUR 1.11 - SYSTEM LOLP INDEX BY PLANNING RESERVE MAGIN LEVEL..........................................................253 FIGUR 1.12 - RELIAILITY RESOURCE FIXED COSTS ASSOCIATED WITH MEETING PRM LEVELS ............................254 FIGUR 1.13 - RELATIONSHIP BETWEEN RESERVE MAGIN AND LOLP .....................................................................255 vii PACIFiCORP-2011 IRP APPENDIX A -LOAD FORECAST DETAILS ApPENDIX A - LOAD FORECAST DETAILS This appendix reviews the load forecast used during the 2011 Integrated Resource Plan and scenario development for case sensitivities to varing levels in the load forecast. The load forecasting review starts with the final system level retail sales forecast reflecting the chosen Class 2 DSM effciencies from the 2011 IRP preferred portfolio. The next section elaborates the methodology for .long-range load forecasting and provides an overview of the modeling involved. For the state level summaries, retail sales at the customer meter are discussed at the state-level reflecting the chosen Class 2 DSM effciencies from the 2011 IRP preferred portfolio. Finally, the system level and state level load forecast at the generation as used in the 2011 IRP modeling are discussed. Load Forecast Table A.1 shows the final retail sales values at the customer meter for the total system as well as individual state level after the load reduction impacts of Class 2 DSM programs included in the 2011 IRP preferred portfolio. Table A.l- System Annual Sales forecast (in Gigawatt-hours) 2011 through 2020 Year Residential Commercial Industrial Irrgation Lightig Other Total 2011 16,272 16,949 20,469 1,285 141 436 55,553 2012 16,522 17,699 20,688 1,301 141 437 56,789 2013 16,454 18,004 21,524 1,302 141 436 57,861 2014 16,567 18,247 22,233 1,302 141 436 58,927 2015 16,715 18,529 22,629 1,302 141 436 59,752 2016 16,896 18,973 23,050 1,302 142 437 60,801 2017 16,953 19,190 23,250 1,302 141 436 61,273 2018 17,078 19,452 23,553 1,302 141 436 61,963 2019 17,215 19,723 23,842 1,302 141 436 62,660 2020 17,335 20,036 24,202 1,303 142 437 63,454 PacifiCorp estimates total load by staring with customer class sales forecasts in each state and then adds line losses to the customer class forecasts to determine the total load required at the generators to meet customer demands. Forecasts are based on statistical and econometrc modeling techniques and customer-specific sales forecast for large customers. These models 1 PACIFiCORP-2011 IR APPENDIX A - LOAD FORECAST DETAILS incorporate the county and state level forecasts that are provided by public agencies or purchased from commercial econometrc forecasting services. The 2010 load forecast was used for the development of the load and resource balance and portfolio evaluations. Portfolio analysis staed in November 2010 with preliminary load forecast and continued through December 2010. In 2008, to improve sales and load forecastig methods, capabilities, and accuracy, several improvements in the load forecasting approach were identified jointly by the Company and the Company's consultat, ITRON (a fi specializing in load forecasting softare and services), and the load forecast methodology was changed to incorporate some improvements. The major assumption changes drving the forecast improvements were discussed in detail in 2008 IRP. Those assumptions were revisited and updated as a par of routine forecast development in this IR. First, load research data was updated to include six years (2004 -2009) of daily data. This data is used to model the impact of weather on monthly retail sales and peaks by state by class. The Company collects hourly load data from a sample of customers for each class in each state. These data are priarily used for rate design, but they also provide an opportity to better understand usage patterns, paricularly as they relate to changes in temperature. The greater frequency and data points associated with this daily data make it better suited to captue load changes drven by changes in temperatue. Second, in 2008, the time period used to defie normal weather was updated from the National Oceanic and Atmospheric Admnistration's 30-year period of 1971-2000 to a 20-year time period - the latest forecast is based on 1990-2009 as the 20 year time period. The Company identified a trend of. increasing sumer and winter temperatues in the Company's service terrtory that was not being captúed in the thir year data. ITRON sureys have identified that many other utilities are also using more recent data for determining normal temperatures. Based on this review and on the recommendation from ITRON, the Company adopted a 20-year rollng average as the basis for determining normal temperatues. This better captues the trend of increasing temperatues observed in both summer and winter. Third, The Company updated the economic forecasts from IHS Global Insight using the most recent information available for each of the Company's jursdictions. Fourth, the historical data period used to develop the monthly retail sales forecasts was updated to cover January 1997 through July 2010 for all classes except for industral class which goes back to January 2002. The Company updated the forecast of individual industrial customer usage based on the best information available as of August 2010. Fifth, monthly jursdictional peaks were forecasted for each state using a peak model and estimated with historical data from 1990-2009. As discussed in the 2008 IRP, as an improvement to the forecasting process, the Company developed a model that relates peak loads to the weather that generated the peaks. This model allows the Company to better predict monthly and seasonal peaks. The peak model is discussed in greater detail in the following section. Sixth, system line losses were updated to reflect actual losses for the 5-years ending December 31, 2009. Prior to 2008, the Company relied on periodic line loss studies. The Company 2 PACIFiCORP-2011 IR APPENDIX A - LOAD FORECAST DETAILS observed that actual losses were higher than those from the previous line loss study. The use of actual losses is a reasonable basis for captung total system losses and has been incorporated in this forecast. Class 2 Demand-side Management Resources in the Load Forecast PacifiCorp modeled Class 2 DSM as a resource option to be selected as part of a cost-effective portfolio resource mix using the Company's capacity expansion optimization model, System Optiizer. The load forecast used for IRP portfolio development excluded forecasted load reductions from Class 2 DSM. System Optimizer then determines the amount of Class 2 DSM- expressed as supply curves that relate incremental DSM quantities with their costs-given the other resource options and inputs included in the modeL. The use of Class 2 DSM supply cures, along with the economic screening provided by System Optimizer, determines the cost-effective mix of Class 2 DSM for a given scenaro. For retail load forecast reporting, PacifiCorp develops a load forecast reflecting the chosen Class 2 DSM efficiencies from the 2011 IRP preferred portfolio. Modeling overview This section describes the modeling techniques used to develop the load forecast. The load forecast is developed by forecasting the monthly sales by customer class for each jurisdiction. The residential, commercial,. irrgation, public street lighting, and sales to public authority sales forecasts by jurisdiction is developed as a use per customer times the forecasted number of customers. The customer forecasts are generally based on a combination of regression analysis and exponential smoothing techniques using historical data from Januar 1997 to July 2010. For the residential class, the Company forecasts the number of customers using IRS Global Insight's forecast of each state's number of households as the major driver. For the commercial class, the Company develops the forecast for number of customers with the forecasted residential customer numbers used as the major drver. For irrigation and street lighting classes, the forecast of number of customers is fairly static and developed using regression models without any economic drvers. The residential use-per-customer is forecasted by statistical end-use forecasting techniques. This approach incorporates end use information (satuation forecasts and efficiency forecasts) but is estimated using monthly biling data. Satuation trends are based on analysis of the Company's satuation survey data and effciency trends are based on EIA forecasts that incorporate market forces as well as changes in appliance and equipment effciency standards. Major drvers of the statistical end use based residential model are weather-related variables, end-use information such as equipment shares, satuation levels and efficiency trends, and economic drvers such as household size, income and energy price. The company updated the residential use-per- customer-per-day model with appliance satuation and efficiency results released in June 2009. The SAE models also reflect impacts associated with the Energy Independence and Security Act of 2007, which mandates strcter efficiency standards for incandescent bulbs begining in 2012. 3 PACIFICORP - 2011 IRP APPENDIX A - LOAD FORECAST DETAILS The commercial, irgation, street lighting, and sales to public authority use-per-customer forecast is developed using an econometric modeL. For the commercial class, the Company forecasts sales per customer using regression analysis techniques with employment used as the major economic drver in addition to weather-related varables. For other classes, the Company forecasts sales per customer through regression analysis technques using time trend variables. The sales forecast for the residential, commercial and irgation classes is the product of the number of customer forecast and the use-per-customer forecast. However, the development of the forecast of monthly commercial sales involves an additional step. To reflect the addition of a large "lumpy" change in sales such as a new data center, monthly commercial sales are increased based on input from the Customer Account Managers ("CAMs"). Although the scale is much smaller, the treatment of large commercial additions is similar to the methodology for industrial sales which is discussed below. Monthly sales for lighting and public authority are forecasted directly for the class, instead of the product of the use-per-customer and number of customers. The forecast is developed by class because the customer sizes in these two classes are more diverse. The industral sales forecast is developed for each jursdiction using a model which is dependent on input for the Customer Account Managers (CAMs). The industrial customers are separated into three categories: existing customers that are tracked by the CAMs, new large customers or expansions by existing large customers, and industral customers that are not tracked by the CAMs. Customers are tracked by the CAMs if(l) they have a peak load of five MW or more or if (2) they have a peak load of one MW or more and have a history of large varations in their monthly usage. The forecast for the fist two categories is developed through the data gathered by the CAM assigned to each customer. The account managers have ongoing direct contact with large customers and are in the best position to know about the customer's plans for changes in business processes, which might impact their energy consumption. The Company develops the total industral sales forecast by aggregating the forecast for the three industral customer categories. The portion of the industrial forecast related to new large customers and expansion by existing large customers is developed based on direct input of the customers, forecasted load factors, and the probability of the project occurence. Projected loads associated with new customers or expansions of existing large customers are categorized into three groups. Tier 1 customers are those with a signed master electrc service agreement ("MESA") and Tier 2 customers are those with a signed engineering material and procurement agreement ("EMP A"). When a customer signs a MESA or EMP A, this contractually commits the Company to provide services under the terms of agreement. Tier 3 includes customers with a signed engineering services agreement (ESA). This means that customer paid the Company to perform a study that determines what improvements the Company wil need to make to serve the requested load. Tier 4 consists of customers who made inquires but have not signed a formal agreement. Projected loads from customers in each of these tiers are assigned probabilities depending on project-specific information received from the customer. Smaller industral customers are more homogeneous and are modeled using regression analysis with trend and economic variables. Manufactug employment serves as the major economic drver. The total industrial sales forecast is developed by aggregating the forecast for the three industral customer categories. 4 PACIFiCORP-2011 IRP APPENDIX A - LOAD FORECAST DETAILS The segments are forecasted differently within the industral class because of the diverse makeup of the customers within the class. In the industrial class, there is no "tyical" customer. Large customers have very diverse usage patterns and power requirements. It is not unusual for the entire class to be strongly influenced by the behavior of one customer or a small group of customers. In contrast, customer classes that are made up of mostly smaller, homogeneous customers are best forecasted as a use per customer multiplied by number of customers. Those customer classes are generally composed of many smaller customers that have similar behaviors and usage patterns. No small group of customers, or single customer, influences the movement of the entire class. This difference requires the different processes for forecasting. After monthly energy by customer class is developed, hourly loads are estimated in two steps. First, PacifiCorp derives monthly and seasonal peak forecasts for each state. The monthly peak model uses historic peak-producing weather for each state, and incorporates the impact of weather on peak loads through several weather variables which drve heating and cooling usage. These weather variables include the average temperatue on the peak day and average. daily temperatues for two days prior to the peak day. The peak forecast is based on average monthly historical peak-producing weather for the period 1990-2009. Second, hourly load forecasts for each state are obtained from the hourly load models using state-specific hourly load data and daily weather variables. Hourly load forecasts are developed using a model that incorporates the 20-year average temperatues, the actual weather pattern for a year, and day-tye variables such as weekends and holidays. The model incorporates both mild and extreme days in weather patterns by mapping the normal temperatues to an actual weather pattern. This method effectively represents the daily volatility in weather experienced durg a tyical year. Also, the method preserves the extreme temperatues and maps them to a year to produce a more accurate estimate of daily temperatures. The hourly load forecasts are adjusted for line losses and calibrated to monthly and seasonal peaks. After PacifiCorp develops the hourly load forecasts for each state, hourly loads are aggregated to the total Company system leveL. System coincident peaks are then identified as well as the contribution of each jursdiction to those monthly system peaks. This section provides total system and state-level forecasted retail sales summaries measured at the customer meter. The factors influencing the forecasted sales growth rates also influence the forecasted peak demand growth rates. State Summaries Oregon Table A.2 summarizes Oregon state forecasted retail sales growth by customer class. 5 PACIFiCORP-2011 IRP APPENDIX A - LOAD FORECAST DETAILS Table A.2 - Forecasted Sales Growth in Oregon Year Residential Commercial Industral Irrgation Lighting Other Total 2011 5,624 5,142 2,298 266 38 0 13,368 2012 5,672 5,399 2,324 282 38 0 13,715 2013 5,573 5,490 2,367 283 38 0 13,750 2014 5,563 5,526 2,368 283 38 0 13,778 2015 5,570 5,557 2,355 283 38 0 13,803 2016 5,612 5,603 2,350 283 38 0 13,886 2017 5,610 5,616 2,325 283 38 0 13,872 2018 5,641 5,647 2,310 283 38 0 13,920 2019 5,675 5;677 2,299 283 38 0 13,971 2020 5,705 5,720 2,297 283 38 0 14,043 The forecast of residential sales is expected to grow at a relatively slower rate of 0.2% annually compared to average annual growt rate of around 1.3% experienced in the past ten years. This slow down is mainly attbuted to housing market deterioration worsening economic conditions in the service terrtory. Beyond20l2, use per customer is expected to decline - this decline is mainly due to the impact of long-term lighting effciency gains resulting from 2007 Federal Energy legislation and other energy efficiency and conservation programs. Over the forecast horizon, forecasted commercial class sales are projected to grow anually at 1.2%, and are higher than the ten year average annual growt rate in history. Anual growt rate is much higher in the near term as a result of new data centers in the service terrtory. Usage per customer is projected to decline slightly due to increased equipment effciency. As an aftermath of housing market slowdown and economic recession affecting wood products and semi-conductor manufactug, forecasted industral class sales are projected to grow at a very slow rate in the forecast horizon. Continued diversification in the manufactug base in the state and good export opportities may continue to add to some positive growt in the area. Washington Table A.2 summarizes Washington state forecasted retail sales growth by customer class. Table A.3 - Forecasted Sales Growth in Washington Year Residential Commercial Industral Irrgation Lighting Other Total 2011 1,639 1,445 843 160 10 0 4,097 2012 1,652 1,471 858 160 10 0 4,150 2013 1,636 1,481 865 160 10 0 4,151 2014 1,638 1,487 866 160 10 0 4,161 2015 1,645 1,493 866 160 10 0 4,174 2016 1,662 1,503 868 160 10 0 4,203 6 PACIFiCORP-2011 IRP APPENDIX A - LOAD FORECAST DETAILS The forecast of residential sales is expected to grow at a slower average annual growth rate of 0.4% compared to ten year historical growth rates of around 1.4% due to the continuing impact of housing market slowdown and economic recession. The slight growth in residential class sales is due to continuing customer growt drven by population growth and household formation in the service area. Beyond 2012, use per customer is expected to decline - this decline is mainly due to the impact of long-term lighting efficiency gains resulting from 2007 Federal Energy legislation and other energy efficiency and conservation programs. Over the forecast horizon, forecasted commercial class sales are projected to grow at an average anual rate of 0.5% due to the aftermath of economic recession. The industrial class sales are projected to grow at an average annual growth rate of 0.3% reflecting slow recovery in wood products and food processing sectors. California Table A.4 summarizes California state forecasted sales growth by customer class. Table A.4 - Forecasted Retail Sales Growth in California Year Residential Commercial Industral Irrgation Lighting Other Total 2011 398 288 40 98 2 0 827 2012 402 290 44 98 2 0 836 2013 398 294 45 98 2 0 837 2014 399 297 44 98 2 0 840 2015 401 297 43 98 2 0 842 2016 405 298 42 98 2 0 846 2017 405 298 41 98 2 0 845 2018 407 299 40 98 2 0 847 2019 409 300 39 98 2 0 849 2020 411 302 38 98 2 0 851 The residential sales are expected to grow at an average annual rate of 0.3%. Beyond 2012, use per customer is expected to decline - this decline is mainly due to the impact of long-term lighting efficiency gains resulting from 2007 Federal Energy legislation and other energy effciency and conservation programs. 7 PACIFICORP - 20 lllR APPENDIX A - LOAD FORECAST DETAILS The continuing population growth also affects sales in the commercial sector though continued commercial customer growt. However, some of this growt is being offset from increased equipment effciency over the forecast horion. Declines over the decade in the lumber and wood product industres production resulted in an overall decline in the industral sales for the past two years, and is stil facing hardship. Utah Table A.5 summarizes Utah state forecasted sales growt by customer class. Table A.S - Forecasted Retail Sales Growth in Utah Year Residential Commercial Industral Irgation Lighting Other Total 2011 6,776 8,104 8,377 188 77 436 23,958 2012 6,908 8,508 8,221 187 77 437 24,339 2013 6,943 8,655 8,594 187 77 436 24,893 2014 7,023 8,804 8,873 187 77 436 25,401 2015 7,120 9,005 8,978 187 77 436 25,803 2016 7,206 9,346 9,114 187 77 437 26,368 2017 7,245 9,520 9,185 187 77 436 26,650 2018 7,307 9,711 9,299 187 77 436 27,018 2019 7,374 9,914 9,395 187 77 436 27,384 2020 7,430 10,135 9,513 187 77 437 27,779 Utah continues to see natual population growth that is faster than many of the surounding states. Durg the historical period, Utah experienced rapid population growth with a high rate of in-migration. However, the rate of population growth is expected to be relatively lower in the coming decade as in-migration into the state slows down relative to history. Over the forecast horizon, residential sales are expected to grow at a slower rate of 1.0% compared to what has been experienced. historically in the past ten years due to slower in-migration and slow recovery in housing market in near-term. Beyond 2012, the decline in use per customer is drven by the impact of long-term lighting effciency gains resulting from 2007 Federal Energy legislation and other energy effciency and conservation programs. The continuing population growth also affects sales in the commercial sector by continued commercial customer growth. Commercial sales are growing at an average annual rate of 2.5% in the forecast horizon mainly due to several data centers starting services in Utah. However some of this growth is being slightly offset from equipment efficiency gains over the forecast horizon. The industral class in the state is diversified and wil continue to cause sales growth in the sector. Utah has a strategic location in the western half of the United States, which provides easy access into many regional markets. The industral base has become more lined to the region and is less dependent on the natual resource base within the state. This provides a strong foundation 8 PACIFiCORP-2011 IRP APPENDIX A - LOAD FORECAST DETAILS for continued growth into the futue. As a result of economic slowdown, over the forecast horizon, industral sales are growing at a moderate 1.4% as compared to the recent ten year growth rate of 1.6%, but are lower than the pre recession annual average growt rate. As the economy recovers, industral expansions in a broad range of industres are expected to pick up, and industral sales are expected to grow again reflecting improvement in overall economic conditions. In 2011, the industral sales are higher due to a one year load increase by a large industral customer. Idaho Table A.6 summarizes Idaho state forecasted sales growt by customer class. Table A.6 - Forecasted Retail Sales Growth in Idaho Year Residential Commercial Industral Irgation Lighting Other Total 2011 732 432 1,665 550 3 0 3,381 2012 756 450 1,690 550 3 0 3,448 2013 764 467 1,778 550 3 0 3,562 2014 784 484 1,883 550 3 0 3,704 2015 805 499 1,950 550 3 0 3,806 2016 829 512 2,007 550 3 0 3,901 2017 846 522 2,016 550 3 0 .3,937 2018 865 533 2,020 550 3 0 3,972 2019 885 544 2,025 550 3 0 4,007 2020 905 557 2,033 550 3 0 4,048 Over the forecast horizon, the residential sales are projected to grow at 2.4% annually compared to historical ten year average annual growth rate of 2.8%. Beyond 2012, use per customer is expected to decline - this decline is mainly due to the impact of long-term lighting efficiency gains resulting from 2007 Federal Energy legislation and other energy efficiency and conservation programs. The growth rate for commercial class sales is expected to continue to be strong due to customer growth in response to the increasing residential customer growth resulting in increasing service sector demand such as education and health care servces. Usage per customer growth is somewhat offset by equipment efficiency gains over the forecast horion. Industrial sales are expected to grow at an average annual rate of 2.2%. This growth is primarily due to expansions by a few large industral customers. Wyoming Table A. 7 summarizes Wyoming state forecasted sales growth by customer class. 9 PACIFiCORP-2011 IRP APPENDIX A - LOAD FORECAST DETAILS Table A.7 - Forecasted Retail Sales Growth in Wyoming Year Residential Commercial Industral Irgation Lighting Other Total 2011 1,103 1,538 7,246 23 12 0 9,921 2012 1,134 1,581 7,552 23 12 0 10,301 2013 1,141 1,617 7,875 23 12 0 10,668 2014 1,159 1,650 8,199 23 12 0 11,043 2015 1,173 1,678 8,437 23 12 0 11,324 2016 1,182 1,710 8,669 24 12 0 11,596 2017 1,181 1,730 8,818 24 12 0 11,765 2018 1,182 1,753 9,019 24 12 0 11,990 2019 1,186 1,778 9,221 24 12 0 12,220 2020 1,188 1,808 9,457 24 12 0 12,489 Residential sales is expected to grow at an average annual rate of 0.8%, compared to an average annual growth rate of around 2.4% experienced durng the past ten years. Population growth is stil expected to continue in the service area, which contrbutes to some of the sales growth. Beyond 2012, use per customer is expected to decline - this decline is mainly due to the impact of long-term lighting effciency gains resulting from 2007 Federal Energy legislation and other energy effciency and conservation programs. Over the forecast horizon, commercial class sales are projected to grow at an annual growth rate of 1.8%. Sales growt is drven mainly by the customer growth in response to stil continuing residential customer growth and the growth of the offce sector. Wyoming industrial sales growth, drven by expansion in oil and gas extraction industres, is expected to continue, but at a much reduced rate in the near years due to uncertainty in energy prices. As the economy recovers, industrial growt continues in outer years. Continuing growth in industral customers in the service area also contrbutes to the load growth in the residential and commercial customer sectors. This section provides the load forecast at the generator information used for 2011 IRP portfolio modeling for each state and the system as a whole by year for 2011 through 2020 before Class 2 DSM load reductions are applied. Energy Forecast Table A.8 shows average annual energy load growth rates for the PacifiCorp system and individual states. Growth rates are shown for the forecast period 2011 through 2020. 10 PACIFICORP - 2011 IR APPENDIX A - LOAD FORECAST DETAILS Table A.8 - Forecasted Average Annual Energy Growth Rates for Load The total net control area load forecast used in this IRP reflects PacifiCorp's forecasts of loads growing at an average rate of 2.1 % percent annually from year 2011 to 2020. Table A.9 shows the forecasted load for each specific year for each state served by PacifiCorp and the average anual growt (AAG) rate over the entire time period. Table A.9 - Annual Load forecasted (in Megawatt-hours) 2011 through 2020 2011 63,131,207 14,968,933 4,579,565 954,604 26,106,815 10,611,408 3,721,679 2,188,202 2012 64,958,409 15,487,788 4,676,478 969,067 26,746,468 11,040,464 3,804,258 2,233,885 2013 66,388,259 15,669,033 4,703,107 972,280 27,389,581 11,451,701 3,937,679 2,264,877 2014 68,035,127 15,853,824 4,754,379 982,164 28,151,361 11,883,924 4,106,332 2,303,143 2015 69,442,054 16,038,453 4,809,526 991,175 28,805,998 12,220,507 4,234,971 2,341,424 2016 71,110,972 16,283,652 4,880,687 1,002,320 29,650,389 12,548,966 4,357,547 2,387,412 2017 72,151,300 16,419,176 4,921,944 1,009,109 30,196,791 12,770,304 4,415,978 2,417,998 2018 73,424,134 16,602,014 4,977,007 1,018,716 30,840,594 13,055,537 4,473,968 2,456,298 2019 74,713,621 16,789,205 5,030,425 1,028,331 31,491,637 13,346,735 4,532,675 2,494,611 2020 76,136,508 16,998,651 5,089,930 1,039,248 32,188,156 13,680,764 4,598,606 2,541,153 2011-20 2.1%1.4%1.2%0.9%2.4%2.9%2.4%1.7% 2021-30 1.7%0.9%0.9%0.8%1.9%2.5%1.2%1.4% 2011-30 1.9%1.1%1.1%0.9%2.1%2.7%1.8%1.5% Jurisdictional Peak Load Forecast The economies, industr mix, appliance and equipment adoption rates, and weather patterns are different for each jursdiction that PacifiCorp serves. Because of these differences the jursdictional hourly loads have different daily and hourly patterns. In addition, the growth for the jursdictional peak demands can be different from the growth in the jurisdictional contribution to the system peak demand. As explained in the methodology section, development of the coincident peaks is based on jurisdictional peaks. However, the jursdictional peak forecast is not directly used in the IRP portfolio development process. System-Wide Coincident Peak Load Forecast The system coincident peak load is the maximum load required on the system in any hourly period. Forecasts of the system peak for each month are prepared based on the load forecast produced using the methodologies described above. From these hourly forecasted values, the coincident system peaks and the non-coincident peaks (within each state) during each month are extracted. Since 2000, the annual system peak has generally occured in the sumer. The sumer system peak is a result of several factors. First, the increasing demand for sumer space conditioning in 11 PACIFiCORP-2011 IR APPENDIX A - LOAD FORECAST DETAILS the residential and commercial classes and a decreasing demand for electrc related space conditioning in the winter contrbutes to a sumer peak. This trend in space conditioning is expected to continue. Second, Utah with a sumer peak that is relatively higher than the winter peak has been growing faster than the system. This growt also contrbuted to a summer peaking system. Total system load factor is expected to be relatively stable over the 2011 to 2020 time period. There are several factors workig in opposite directions, leadig to this result. First, the relatively high growt in high load factor industral sales, particularly in Wyoming, tends to push up the system load factor. Second, as discussed above, the shift in space conditioning tends to push down the system load factor. And, third, advancing lighting efficiency standards, such as those found in the 2007 Energy Independence and Securty Act, which begin to tae effect in 2012, also tend to push down the system load factor. Table A.tO - Forecasted Coincidental Peak Load Growth Rates PacifiCorp's eastern system peak is expected to continue growing faster than the western system peak, with average annual growth rates of 2.4 percent and 1.4 percent, respectively, over the forecast horizon. The main drivers for the higher coincident peak load growt for the eastern states include the following: · Customer growth in residential and commercial classes · New large commercial customers such as data centers · Increased usage by Industral class due to addition of new large industral customers or expansion by existing customers Table A.ll below shows that for the same time period the total peak is expected to grow by 2.1 percent. Table A.ll - Forecasted Coincidental Peak Load in Megawatts 2011 10,449 2,332 775 160 4,840 1,329 679 336 2012 10,716 2,396 813 163 4,935 1,376 691 341 2013 10,960 2,429 802 164 5,074 1,423 721 346 2014 11,252 2,466 817 163 5,231 1,471 750 353 2015 11,501 2,496 830 166 5,354 1,509 787 359 2016 11,740 2,528 843 169 5,474 1,545 817 365 2017 11,960 2,557 855 171 5,602 1,574 831 370 2018 12,194 2,584 893 173 5,726 1,601 842 376 2019 12,378 2,611 880 174 5,845 1,633 854 381 2020 12,607 2,644 894 174 5,975 1,668 864 388 2011-20 2.1%1.4%1.6%0.9%2.4%2.6%2.7%1.6% 2021-30 1.7%0.9%1.3%1.0%2.0%2.3%1.4%1.4% 2011-30 1.9%1.2%1.4%1.0%2.2%2.4%2.0%1.5% 12 PACIFiCORP-2011 IRP APPENDIX A - LOAD FORECAST DETAILS The main purpose of the alternative load forecast cases is to determine the resource tye and timing impacts resulting from a strctual change in the economy. The focus of the load growt scenarios is from 2014 onward. The Company assumes that economic changes begin to significantly impact loads begining in 2014, the curently planned acquisition date for the next CCCT resource. The October 2010 forecast was considered to be the baseline (Medium) scenario. For the high and low growth scenarios, assumptions from IRS Global Insight were applied to the economic drivers in the Company's load forecastig models. These growth assumptions were extended for the entire forecast horizon. Recognizing the volatility associated with oil and gas extraction industries, PacifiCorp applied additional assumptions for Utah and Wyoming industral classes for the high scenaro. For 2014 and 2015, industral sales were projected based on historic average growth rates for boom years (2003-2008), and for 2016 and beyond, industral sales were projected based on historic average growth rates for 2000-2008 (time period with one economic boom and one recession). For Oregon, the probability of new loads from data centers is increased, and a steady growt rate based on the historical average is applied for 2014 onwards for the industrial class. For the low scenario, the Company assumed a reduced probability of data center growt materializing. Also, for Utah and Wyoming, a double dip recession starting with slower 2011 and 2012 growth was assumed, accompanied by a recovery track from the double-dip recession less than complete for the forecast horizon. For the 1-in-1O year (10% probability) extreme weather scenario, the Company used 1-in-10 year peak weather for winter (January) and summer (July) months for each state. The 1-in-1O year peak weather is defined as the year for which the peak has the chance of occurg once in 10 years. Figue A.1 shows the comparison of the above scenarios relative to the Medium scenario. Figue A.2 compares the system coincident peak load forecast with those used for the 2008 IRP Update and 2008 IRP. 13 P ACIFICORP - 2011 IR APPENDIX A - LOAD FORECAST DETAILS Figure A.l- Load Forecast Scenarios for Low, Medium, High and Peak 14,000 tl"~13,000"""Qj~ 12,000 16,000 15,000 11,00 10,000 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 -+Medium ..Low ..High ..Peak Figure A.2 - Coincident Peak Load Forecast Comparison to Past IRPs ~ ~ ~.... ~ 14,500 14,000 13,500 13,000 12,500 12.000 11,500 11,000 10,500 , 10,000 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 ""201 I IRP(October 2010)- -2008IRPUpdate(November2009)"" "' -2008 IRP(November2008) 14 PACIFICORP - 2011 IRP APPENDIX B - IRP REGULATORY COMPLIANCE ApPENDIX B - IRP REGULATORY COMPLIANCE This appendix describes how PacifiCorp's 2011 IRP complies with (1) the varous state commission IRP standards and guidelines, (2) specific analytical requirements stemming from acknowledgment orders for the Company's last IRP ("2008 IRP"), and (3) state commission IRP requirements stemming from other regulatory proceedings. Included in this appendix are the following tables: . Table B.l - Provides an overview and comparison of the rules in each state for which IRP submission is required. 1 . Table B.2 - Provides a description of how PacifiCorp addressed the 2008 IRP acknowledgement requirements and other commission directives. . Table B.3 - Provides an explanation of how this plan addresses each of the items contained in the new Oregon IRP guidelines issued in January 2007. . Table B.4 - Provides an explanation of how this plan addresses each of the items contained in the Utah Public Service Commission IRP Standard and Guidelines issued in June 1992. . Table B.5 - Provides an explanation of how this plan addresses each of the items contained in the Washington Utilities and Trade Commission IRP guidelines issued in January 2006. . Table B.6 - Provides an explanation of how this plan addresses each of the items contained in the Wyoming Public Service Commission IRP guidelines. PacifiCorp prepares the IRP on a biennial basis and fies the IRP with the state commissions. The preparation of the IRP is done in an open public process with consultation between all interested parties, including commissioners and commission staff, customers, and other stakeholders. This open process provides parties with a substantial opportity to contrbute information and ideas in the planning process, and also serves to inform all paries on the planning issues and approach. The public input process for this IRP, described in Volume 1, Chapter 2, as well as in Appendix F, fully complies with the IRP Standards and Guidelines. The IRP provides a framework and plan for futue actions to ensure PacifiCorp contiues to provide reliable and least-cost electrc service to its customers. The IRP evaluates, over a twenty- year planning period, the futue loads of PacifiCorp customers and the capability of existing resources to meet this load. i California guidelines exernpt a utility with less than 500,000 custorners in the state from filing an IRP. However, renewable portfolio stadad rules require that PacifiCorp file 1R supplements that address how the Cornpany is cornplying with RPS compliance requirements. 15 PACIFICORP - 2011 IR APPENDIX B - IR REGULATORY COMPLIANCE To fill any gap between changes in loads and existing resources, the IR evaluates all available resource options, as required by state commssion rules. These resource alternatives include supply-side, demand-side, and transmission alternatives. The evaluation of the alternatives in the IRP, as detailed in Chapters 7 and 8 meets ths requirement and includes the impact to system costs, system operations, supply and transmission reliabilty, and the impacts of vanous nsks, uncertainties and externality costs that could occur. To perform the analysis and evaluation, PacifiCorp employs a suite of models that simulate the complex operation of the PacifiCorp system and its integration within the Western Interconnection. The models allow for a ngorous testing of a reasonably broad range of commercially feasible resource alternatives available to PacifiCorp on a consistent and comparble basis. The analytical process, including the risk and uncertinty analysis, fully complies with IR Stadads and Guidelines, and is descnbed in detail in Chapter 7. The IRP analysis is designed to define a resource plan that is least cost, after consideration of nsks and uncertainties. To test resource alternatives and identify a least..cost, nsk adjusted plan, portfolio resource options were developed and tested against each other. This testing included examination of vanous tradeoffs among the portfolios, such as average cost versus nsk, reliability, customer rate impacts, and average annual C02 emissions. This portfolio analysis and the results and conclusions drawn from the analysis are described in Chapter 8. Consistent with the IRP Standads and Guidelines of Oregon, Utah, and Washington, this IRP includes an Action Plan (See Chapter 9). The Action Plan details near-term actions that are necessar to ensure PacifiCorp continues to provide reliable and least-cost electric service after considenng nsk and uncertainty. Chapter 9 also provides a progress report on action items contained in the 2008 IRP Update Action Plan. The 2011 IRP and the related Action Plan. are fied with each commission with a request for prompt acknowledgement. Acknowledgement means that a commission recognizes the IRP as meeting all regulatory requirements at the time the acknowledgement is made. In the case where a commission acknowledges the IRP in part or not at all, PacifiCorp works with the commission to modify and re-fie an IRP that meets acknowledgement stadads. . State commission acknowledgement orders or letters tyically stress that an acknowledgement does not indicate approval or endorsement of IRP conclusions or analysis results. Similarly, an acknowledgement does not imply that favorable ratemaking treatment for resources proposed in the IRP wil be given. California Subsection (i) of California Public Utilities Code, Section 454.5, states that utilities serving less than 500,000 customers in the state are exempt from filing an Integrated Resource Plan for California. PacifiCorp serves only 45,072 average customers in the most northern parts of the state. PacifiCorp filed for and received an exemption on July 10,2003. Idaho The Idaho Public Utilities Commission's Order No. 22299, issued in Januar 1989, specifies integrated resource planing requirements. The Order mandates that PacifiCorp submit a 16 PACIFICORP -2011 IR APPENDIX B - IR REGULATORY COMPLIACE Resource Management Report (RM) on a biennial basis. The intent of the RMR is to describe the status ofIR efforts in a concise format, and cover the following areas: Each utility's RMR should discuss any flexibilties and analyses considered during comprehensive resource planning, such as: (1) examination of load forecast uncertainties; (2) effects of known or potential changes to existing resources; (3) consideration of demand and supply side resource options; and (4) contingencies for upgrading, optioning and acquiring resources at optimum times (considering cost, availabilty, lead time, reliabilty, risk, etc.) as future events unfold. This IRP is submitted to the Idaho PUC as the Resource Management Report for 2007, and fully addresses the above report components. The IRP also evaluates DSM using a load decrement approach, as discussed in Chapters 6 and 7. This approach is consistent with using an avoided cost approach to evaluating DSM as set forth in IPUC Order No. 21249. Oregon This IRP is submitted to the Oregon PUC in compliance with its new planning guidelines issued in January 2007 (Order No. 07-002). These guidelines supersede previous ones, and many codify analysis requirements outlined in the Commission's acknowledgement order for PacifiCorp's 2004IRP. The Commission's new IRPguidelines consist of substantive requirements (Guideline 1 ), procedural requirements (Guideline 2), plan fiing, review, and updates (Guideline 3), plan components (Guideline 4), transmission (Guideline 5), conservation (Guideline 6), demand response (Guideline 7), environmental costs (Guideline 8, Order No. 08-339), direct access loads (Guideline 9), multi-state utilities (Guideline 10), reliabilty (Guideline 11), distrbuted generation (Guideline 12), and resource acquisition (Guideline 13). Consistent with the earlier guidelines (Order 89-507), the Commission notes that acknowledgement does not gurantee favorable ratemaking treatment, only that the plan seems reasonable at the time acknowledgment is given. Table C.3 provides considerable detail on how this plan addresses each of the requirements. Utah This IRP is submitted to the Utah Public Service Commission in compliance with its 1992 Order on Standards and Guidelines for Integrated Resource Planing (Docket No. 90-2035-01, "Report and Order on Standards and Guidelines"). Table CA documents how PacifiCorp complies with each of these standards. Washington This IRP is submitted to the Washington Utilities and Transportation Commission (WUTC) in compliance with its rule requiring least cost planning (Washington Administrative Code 480- 100-238), and the rule amendment issued on January 9, 2006 (WAC 480-100-238, Docket No. UE-030311). In addition to a least cost plan, the rule requires provision of a two-year action plan and a progress report that "relates the new plan to the previously fied plan." The rule amendment also now requires PacifiCorp to submit a work plan for informal commssion review not later than 12 months prior to the due date of the plan. The work plan is to 17 PACIFICORP - 2011 IR APPENDIX B - IR REGULATORY COMPLIANCE layout the contents of the IRP, the resource assessment method, and timing and extent of public participation. PacifiCorp filed a work plan with the Commission on Februar 21,2006, and had a follow-up conference call with WUC staff to make sure the work plan met staff expectations. Finally, the rule amendment now requires PacifiCorp to provide an assessment of transmission system capabilty and reliabilty. This requirement was met in this IRP by modeling the company's curent transmission system along with both generation and transmission resource options as part of its resource portfolio analyses. These analyses used such reliability metrcs as Loss of Load Probabilty and Energy Not Served to assess the impacts of different resource combinations on system reliability. The stochastic simulation and risk analysis section of Chapter 7 reports the reliability analysis results. Wyoming In 2008, Wyoming proposed draft rule 253 for any utility serving Wyoming to file their Integrated Resource Plan with the commission. The rule went into effect in September 2009. Rule 253: Integrated Resource Planning. Any utilty serving in Wyoming required to file an integrated resource plan (IRP) in any jurisdiction, shall file that IRP with the Wyoming Public Service Commission. The Commission may require any utilty serving in Wyoming to prepare and file an IRP when the Commission determines it is in the public interest. Commission advisory staff shall review the IRP as directed by the Commission and report its findings to the Commission in open meeting. The review may be conducted in accordance with guidelines set from time to time as conditons warrant. 18 PA C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X B - I R P R E G U L A T O R Y C O M P L I A N C E Ta b l e B . t - I n t e g r a t e d R e s o u r c e P l a n n i n g S t a n d a r d s a n d G u i d e l i n e s S u m m a r y b y S t a t e So u r c e Fi l n g Re q u i r e m e n t s Fr e q u e n c y Or d e r N o . 0 7 - 0 0 2 , In v e s t i g a t i o n I n t o In t e g r a t e d R e s o u r c e Pl a n n i n g , J a n u a r y 8 , 2 0 0 7 , as a m e n d e d b y O r d e r N o . 07 - 0 4 7 . Or d e r N o . 0 9 - 0 4 1 , N e w Ru l e O A R 8 6 0 - 0 2 7 - 0 4 0 0 , ir n p l e m e n t i n g G u i d e l i n e 3 , "P l a n F i l i n g , R e v i e w , a n d Up d a t e s " . Le a s t - c o s t p l a n s m u s t b e fi e d w i t h t h e C o m r n i s s i o n . Pl a n s f i e d b i e n n i a l l y , wi t h i n t w o y e a r s o f i t s pr e v i o u s I R P ac k n o w l e d g e r n e n t o r d e r . An a n n u a l u p d a t e t o t h e mo s t r e c e n t l y ac k n o w l e d g e d l R P i s re q u i r e d t o b e f i e d o n o r be f o r e t h e o n e - y e a r an n i v e r s a r y o f t h e ac k n o w l e d g m e n t o r d e r da t e . W h i l e i n f o r m a t i o n a l on l y , u t i l i t i e s m a y r e q u e s t ac k n o w l e d g m e n t o f pr o p o s e d c h a n g e s to t h e ac t i o n p l a n . Do c k e t 9 0 - 2 0 3 5 - 0 1 St a n d a r d s a n d Gu i d e l i n e s f o r I n t e g r a t e d Re s o u r e e P l a n n i n g J u n e 18 , 1 9 9 2 . An I n t e g r a t e d R e s o u r c e Pl a n ( I R P ) i s t o b e su b r n i t t e d t o Co r n m i s s i o n . Fi l e b i e n n i a l l y . WA C 48 0 - 1 0 0 - 2 5 1 L e a s t co s t p l a n n i n g , M a y 1 9 , 19 8 7 , a n d a s a m e n d e d fr o m W A C 4 8 0 - 1 0 0 ~ 2 3 8 Le a s t C o s t P l a n n i n g Ru l e m a k i n g , J a n u a r 9 , 20 0 6 ( D o c k e t # U E - 03 0 3 1 1 ) Su b m i t a l e a s t c o s t p l a n t o th e C o m m i s s i o n . P l a n t o be d e v e l o p e d w i t h co n s u l t a t i o n o f Co m m i s s i o n s t a f f , a n d wi t h p u b l i c i n v o l v e r n e n t . Fi l e b i e n n i a l l y . Or d e r 2 2 2 9 9 El e c t r i c U t i l t y Co n s e r v a t i o n S t a n d a r d s an d P r a c t i e e s Ja n u a r y , 1 9 8 9 . Su b m i t " R e s o u r c e Ma n a g e r n e n t R e p o r t " (R M R ) o n p l a n n i n g st a t u s . A l s o f i e p r o g r e s s re p o r t s o n c o n s e r v a t i o n an d l o w - i n c o m e 'r o g r a r n s . RM P t o b e f i e d a t l e a s t bi e n n i a l l y . C o n s e r v a t i o n re p o r t s t o b e f i e d an n u a l l y . Wy o r n i n g G e n e r a l Re g u l a t i o n s , C h a p t e r 2 , Se c t i o n 2 5 3 . An y u t i l i t y s e r v i n g i n Wy o m i n g r e q u i r e d t o f i e an i n t e g r a t e d r e s o u r c e p l a n (I R P ) i n a n y j u r i s d i c t i o n , sh a l l f i e t h a t I R P w i t h t h e Wy o r n i n g P u b l i c S e r v i c e Co m m i s s i o n . Th e C o m m i s s i o n m a y re q u i r e a n y u t i l i t y s e r v i n g in W y o m i n g t o p r e p a r e a n d fi e a n I R P w h e n t h e Co r n m i s s i o n d e t e r m i n e s i t is i n t h e p u b l i c i n t e r e s t . 19 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X B - I R P R E G U L A T O R Y C O M P L I A N C E Co m m i s s i o n re s p o n s e Pr o c e s s Le a s t - c o s t p l a n ( L C P ) ac k n o w l e d g e d i f f o u n d t o co m p l y w i t h s t a n d a r d s a n d gu i d e l i n e s . A d e c i s i o n rn a d e i n t h e L C P p r o c e s s do e s n o t g u a r a n t e e fa v o r a b l e r a t e - m a k i n g tr e a t m e n t . T h e O P U C m a y di r e c t t h e u t i l t y t o r e v i s e th e I R P o r c o n d u c t ad d i t i o n a l a n a l y s i s b e f o r e an a c k n o w l e d g e m e n t o r d e r is i s s u e d . No t e , h o w e v e r , t h a t R a t e Pl a n l e g i s l a t i o n a l l o w s p r e - ap p r o v a l o f n e a r - t e r m re s o u r c e i n v e s t m e n t s . Th e p u b l i c a n d o t h e r ut i l i t i e s a r e a l l o w e d si g n i f i c a n t i n v o l v e m e n t i n th e p r e p a r a t i o n o f t h e p l a n , wi t h o p p o r t n i t i e s t o co n t r i b u t e a n d r e c e i v e in f o r m a t i o n . O r d e r 0 7 - 0 0 2 re q u i r e s t h a t t h e u t i l i t y pr e s e n t I R P r e s u l t s t o t h e OP U C a t a p u b l i c m e e t i n g pr i o r t o t h e d e a d l i n e f o r wr i t t e n p u b l i c c o m r n e n t s . Co m m i s s i o n s t a f f a n d pa r t i e s s h o u l d c o m p l e t e th e i r c o m m e n t s a n d re c o m m e n d a t i o n s w i t h i n si x r n o n t h s a f t e r I R P f i i n g . Co m p e t i t i v e s e c r e t s m u s t be p r o t e c t e d . IR P a c k n o w l e d g e d i f fo u n d t o c o m p l y w i t h st a n d a r d s a n d g u i d e l i n e s . Pr u d e n c e r e v i e w s o f n e w re s o u r c e a c q u i s i t i o n s wi l o c c u r d u r i n g r a t e rn a k i n g p r o c e e d i n g s . Pl a n n i n g p r o c e s s o p e n t o th e p u b l i c a t a l l s t a g e s . IR P d e v e l o p e d i n co n s u l t a t i o n w i t h t h e Co m r n i s s i o n , i t s s t a f f , wi t h a m p l e o p p o r t u n i t y fo r p u b l i c i n p u t . Th e p l a n w i l b e co n s i d e r e d , w i t h o t h e r av a i l a b l e i n f o r m a t i o n , wh e n e v a l u a t i n g t h e pe r f o r m a n c e o f t h e u t i l i t y in r a t e p r o c e e d i n g s . WU T C s e n d s a l e t t e r di s c u s s i n g t h e r e p o r t , ma k i n g s u g g e s t i o n s a n d re q u i r e m e n t s a n d ac k n o w l e d g e s t h e r e p o r t . In c o n s u l t a t i o n w i t h Co m m i s s i o n s t a f f , de v e l o p a n d i m p l e m e n t a pu b l i c i n v o l v e m e n t p l a n . In v o l v e r n e n t b y t h e p u b l i c in d e v e l o p m e n t o f t h e pl a n i s r e q u i r e d . F o r t h e am e n d e d r u l e s i s s u e d i n Ja n u a r y 2 0 0 6 , P a c i f i C o r p is r e q u i r e d t o s u b m i t a wo r k p l a n f o r i n f o r m a l co m m i s s i o n r e v i e w n o t la t e r t h a n 1 2 m o n t h s p r i o r to t h e d u e d a t e o f t h e pl a n . T h e w o r k p l a n i s t o la y o u t t h e c o n t e n t s o f t h e IR P , r e s o u r c e a s s e s s m e n t me t h o d , a n d t i m i n g a n d ex t e n t o f p u b l i c pa r t i c i p a t i o n . Re p o r t d o e s n o t c o n s t i t u t e pr e - a p p r o v a l of pr o p o s e d re s o u r c e a c q u i s i t i o n s . Id a h o s e n d s a s h o r t l e t t e r st a t i n g t h a t t h e y a c c e p t th e f i l i n g a n d ac k n o w l e d g e t h e r e p o r t a s sa t i s f y i n g C o m m i s s i o n re q u i r e m e n t s . Ut i l i t i e s t o w o r k w i t h Co m m i s s i o n s t a f f w h e n re v i e w i n g a n d u p d a t i n g RM R s . R e g u l a r p u b l i c wo r k s h o p s s h o u l d b e p a r t of pr o c e s s . Co m m i s s i o n a d v i s o r y s t a f f sh a l l r e v i e w t h e l R P a s di r e c t e d b y t h e Co m m i s s i o n a n d r e p o r t i t s fi n d i n g s t o t h e Co m m i s s i o n i n o p e n me e t i n g . Th e r e v i e w m a y b e co n d u c t e d i n a c c o r d a n c e wi t h g u i d e l i n e s s e t f r o m ti m e t o t i m e a s c o n d i t i o n s wa r r a n t . Th e P u b l i c S e r v i c e Co m m i s s i o n o f Wy o m i n g , in i t s L e t t e r O r d e r o n Pa c i f i C o r p ' s 2 0 0 8 I R P (D o c k e t N o . 2 0 0 0 - 3 4 6 - E A - 09 ) a d o p t e d C o m m i s s i o n St a f f s r e c o m m e n d a t i o n t o ex p a n d t h e r e v i e w pr o c e s s to i n c l u d e a t e c h n i c a l co n f e r e n c e , a n e x p a n d e d pu b l i c c o r n m e n t p e r i o d , an d f i i n g o f r e p l y co m m e n t s . 20 P A C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X B - I R P R E G U L A T O R Y C O M P L I A N C E Fo c u s I 2 0 - y e a r p l a n , w i t h e n d - 20 - y e a r p l a n , w i t h s h o r t - 20 - y e a r p l a n , w i t h s h o r t - 20 - y e a r p l a n t o m e e t l o a d Id e n t i f i c a t i o n o f l e a s t - ef f e c t s , a n d a s h o r t - t e r m te r m ( f o u r - y e a r ) a c t i o n te r m ( t w o - y e a r ) a c t i o n ob l i g a t i o n s a t l e a s t - c o s t , co s t / l e a s t - r i s k r e s o u r c e s (t w o - y e a r ) a c t i o n p l a n . T h e pl a n . S p e c i f i c a c t i o n s pl a n . wi t h e q u a l c o n s i d e r a t i o n an d d i s c u s s i o n o f IR P p r o c e s s s h o u l d r e s u l t fo r t h e f i r s t t w o y e a r S Th e p l a n d e s c r i b e s m i x o f to d e m a n d s i d e r e s o u r c e s . de v i a t i o n s f r o m l e a s t - c o s t in t h e s e l e c t i o n o f t h a t m i x an d a n t i c i p a t e d a c t i o n s re s o u r c e s s u f f c i e n t t o Pl a n t o a d d r e s s r i s k s a n d re s o u r c e s o r r e s o u r c e of o p t i o n s w h i c h y i e l d s , f o r in t h e s e c o n d t w o y e a r s rn e e t c u r e n t a n d f u t u e un c e r t a i n t i e s . E m p h a s i s co r n b i n a t i o n s . so c i e t y o v e r t h e l o n g r u n , to b e d e t a i l e d . T h e I R P lo a d s a t " l o w e s t on c l a r i t y , th e b e s t c o r n b i n a t i o n o f pr o c e s s s h o u l d r e s u l t i n re a s o n a b l e " c o s t t o u t i l t y un d e r s t a n d a b i l i t y , ex p e c t e d c o s t s a n d th e s e l e c t i o n o f t h e an d r a t e p a y e r s . R e s o u r c e re s o u r c e c a p a b i l i t i e s a n d va r i a n c e o f c o s t s . op t i r n a l s e t o f r e s o u r c e s co s t , r n a r k e t v o l a t i l i t y pl a n n i n g f l e x i b i l i t y . gi v e n t h e e x p e c t e d ri s k s , d e m a n d - s i d e co m b i n a t i o n o f c o s t s , re s o u r c e u n c e r t a i n t y , ri s k a n d u n c e r t a i n t y . re s o u r c e d i s p a t c h a b i l i t y , ra t e p a y e r r i s k s , p o l i c y ir n p a c t s , a n d en v i r o n m e n t a l r i s k s , m u s t be c o n s i d e r e d . El e m e n t s I B a s i c e l e r n e n t s i n c l u d e : IR P w i l i n c l u d e : Th e p l a n s h a l l i n c l u d e : Di s c u s s a n a l y s e s Pr o p o s e d C o m m i s s i o n . A l l r e s o u r c e s e v a l u a t e d . R a n g e o f f o r e c a s t s o f . A r a n g e o f f o r e c a s t s o f co n s i d e r e d i n c l u d i n g : St a f f g u i d e l i n e s i s s u e d o n on a c o n s i s t e n t a n d fu t u e l o a d g r o w t h fu t u r e d e m a n d u s i n g . L o a d f o r e c a s t Ja n u a r y 2 0 0 9 c o v e r : co m p a r a b l e b a s i s . . E v a l u a t i o n o f a l l me t h o d s t h a t e x a m i n e un c e r t a i n t i e s ; . Su f f c i e n c y o f th e . R i s k a n d u n c e r t a i n t y pr e s e n t a n d f u t u r e th e e f f e c t o f e c o n o m i c . K n o w n o r p o t e n t i a l pu b l i c c o r n m e n t mu s t b e c o n s i d e r e d . re s o u r c e s , i n c l u d i n g fo r c e s o n t h e ch a n g e s t o e x i s t i n g pr o c e s s . T h e p r i m a r y g o a l m u s t de m a n d s i d e , s u p p l y co n s u m p t i o n o f re s o u r c e s ; . Ut i l t y s t r a t e g i c g o a l s be l e a s t c o s t , c o n s i s t e n t si d e a n d m a r k e t , o n a el e c t r i c i t y a n d t h a t . E q u a l c o n s i d e r a t i o n o f an d p r e f e r r e d p o r t f o l i o wi t h t h e l o n g - r u n p u b l i c co n s i s t e n t a n d ad d r e s s c h a n g e s i n t h e de r n a n d a n d s u p p l y s i d e . Re s o u r c e n e e d a n d in t e r e s t . co m p a r a b l e b a s i s . nu m b e r , t y e a n d re s o u r c e o p t i o n s ; ch a n g e s i n e x p e c t e d . T h e p l a n m u s t b e . A n a l y s i s o f t h e r o l e o f ef f c i e n c y o f e l e c t r i c a l . C o n t i n g e n c i e s f o r re s o u r c e a c q u i s i t i o n s co n s i s t e n t w i t h O r e g o n co m p e t i t i v e b i d d i n g en d - u s e s . up g r a d i n g , o p t i o n i n g . En v i r o n m e n t a l an d f e d e r a l e n e r g y . A p l a n f o r a d a p t i n g t o . A n a s s e s s m e n t o f an d a c q u i r i n g r e s o u r c e s im p a c t s po l i c y . di f f e r e n t p a t h s a s t h e co m m e r c i a l l y a v a i l a b l e at o p t i m u m t i r n e s ; . Ma r k e t p u r c h a s e . E x t e r n a l c o s t s m u s t b e fu t u e u n f o l d s . co n s e r v a t i o n , i n c l u d i n g . R e p o r t o n e x i s t i n g ev a l u a t i o n co n s i d e r e d , a n d . A c o s t e f f e c t i v e n e s s lo a d m a n a g e m e n t , a s re s o u r c e s t a c k , l o a d . Re s e r v e m a r g i n qu a n t i f i e d w h e r e me t h o d o l o g y . we l l a s a n a s s e s s m e n t fo r e c a s t a n d a d d i t i o n a l an a l y s i s po s s i b l e . O P U C . A n e v a l u a t i o n o f t h e of c u r e n t l y e r n p l o y e d re s o u r c e r n e n u . . De r n a n d - s i d e sp e c i f i e s e n v i r o n m e n t a l fi n a n c i a l , c o r n p e t i t i v e , an d n e w p o l i c i e s a n d ma n a g e r n e n t a n d ad d e r s ( O r d e r N o . 9 3 - re l i a b i l t y a n d pr o g r a m s n e e d e d t o en e r g y e f f c i e n c y 69 5 , D o c k e t U M 4 2 4 ) . op e r a t i o n a l r i s k s ob t a i n t h e co n s e r v a t i o n . I d e n t i f v a c q u i s i t i o n as s o c i a t e d w i t h im p r o v e r n e n t s . 21 P A C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X B - I R P R E G U L A T O R Y C O M P L I A N C E st r a t e g i e s f o r a c t i o n p l a n re s o u r c e s , a s s e s s ad v a n t a g e s / d i s a d v a n t a g es o f r e s o u r c e ow n e r s h i p v e r s u s pu r c h a s e s , a n d i d e n t i f y be n c h m a r k r e s o u r c e s co n s i d e r e d f o r co m p e t i t i v e b i d d i n g . . M u l t i - s t a t e u t i l i t i e s sh o u l d p l a n t h e i r ge n e r a t i o n a n d tr a n s m i s s i o n s y s t e r n s o n an i n t e g r a t e d - s y s t e m ba s i s . . A v o i d e d c o s t f i i n g re q u i r e d w i t h i n 3 0 d a y s of a c k n o w l e d g e m e n t . re s o u r c e o p t i o n s , a n d ho w t h e a c t i o n p l a n ad d r e s s e s t h e s e r i s k s . . D e f i n i t i o n o f ho w ri s k s a r e a l l o c a t e d be t w e e n r a t e p a y e r s an d s h a r e h o l d e r s . D S M a n d s u p p l y s i d e re s o u r c e s e v a l u a t e d a t "T o t a l R e s o u r c e C o s t " ra t h e r t h a n u t i l t y c o s t . . A s s e s s r n e n t o f a w i d e ra n g e o f c o n v e n t i o n a l an d c o m m e r c i a l l y av a i l a b l e no n c o n v e n t i o n a l ge n e r a t i n g t e c h n o l o g i e s . A n a s s e s s r n e n t o f tr a n s m i s s i o n s y s t e m ca p a b i l i t y a n d re l i a b i l t y ( A d d e d p e r am e n d e d r u l e s i s s u e d i n Ja n u a r 2 0 0 6 ) . . A c o r n p a r a t i v e ev a l u a t i o n o f e n e r g y su p p l y r e s o u r c e s (i n c l u d i n g t r a n s m i s s i o n an d d i s t r i b u t i o n ) a n d ir n p r o v e m e n t s i n co n s e r v a t i o n u s i n g "l o w e s t r e a s o n a b l e co s t " c r i t e r i a . . I n t e g r a t i o n o f th e de m a n d f o r e c a s t s a n d re s o u r c e e v a l u a t i o n s in t o a l o n g - r a n g e ( a t le a s t 1 0 y e a r s ) p l a n . . A l l p l a n s s h a l l a l s o in c l u d e a p r o g r e s s re p o r t t h a t r e l a t e s t h e ne w p l a n t o t h e re v i o u s l v f i e d D I a n . 22 PACIFICORP - 2011 IRP APPENDIX B - IRP REGULATORY COMPLIACE Table B.2 - Handling of 2008 IRP Acknowledgement and Other IRP Requirements Acceptace of Filing, Case No. PAC-E-09-06, p. 7. Acceptace of Filing, Case No. PAC-E-09-06, p. 8. - Acceptance of Filing, Case No. P AC-E-09-06, p. 8. Acceptance of Filing, Case No. PAC-E-09-06, p. 7. PUR A QF Wind, ID PAC-E-07-07, p. 6. PUR A QF Wind, ID PAC-E-07-07, p. 6. Prior to its next IRP filing, Staff requests that the Cornpany explain and justify why its integration costs have more than doubled. Staff further recommends that the Cornpany perform stochastic rnodeling to ascertin a value as par of its next IR. Staff is concerned that the (portfolio performance rneasure importce weights) were chosen arbitrarly and may ultimately impact the selection of one portolio over another having equal or greater rnerit. Staff requests that the Cornpany correct this discrepancy in futue planing processes and document the wei ht deviation in the fial Ian. Staff does not believe that PacifiCorp has adequately quatified the cost associated with meeting an RPS. Staff believes comparg portfolios with and without RPS constraints may facilitate discussions regarding cost allocation and trading rules forrenewable energy credits. Staff recommends that the Company conduct sensitivity analyses on the choice of discount rates on resource tirning and selection. A standard inflation Treasur bond rate, Staff contends, rnay serve as a potential lower bound, and the after-tax W ACC may serve well as an upper bound. Expected wind integration cost information wil be included in the Cornpany's integrated resource planning (IR) process in the same way that costs for other generating resources are included in the IRP. (PacifiCorp) shall hereafter file notice with the Commission of any changes to its wind integration charge as reflected in subsequent changes to its IRP. The Company provided its 2010 wind integration study to IPUC staffin Septernber 2010. This study, included as Appendix I, thoroughly describes the rnethodology used to derive wind integration cost results. Stochastic modeling is considered impractical given the modeling technology. For exarnple, one key methodology step involved importing unit commitment data from one production cost ru into another. This step is not curently possible with multiple stochastic iterations due to the volume of data bein rocessed. The Company dropped the numerical weightig scheme frorn the portolio selection process. See Chapter 7, "Modeling and Portfolio Evaluation Approach". PacifiCorp included a portfolio development scenaro for which RPS requiements were removed as resource selection constraints (Case #30). . Chapter 8 documents the resource and portolio cost irnpact of removing RPS requirernents (See the section entitled, "Renewable Portolio Stadard Impact". Due to time constraints for preparation of this IR, PacifiCorp intends to conduct the recommended sensitivity analysis as par of the 2011 IR Update, to be filed with the state commissions in 2012. The wind integration cost information is included in the 2011 IRP as Appendix i. The Cornpany also filed the wind integration study as an attachment to its stipulation commitment compliance fiing under Order No. 30497, dated February 14,2011. In its stipulation commitment compliance fiing under Order No. 30497, the Cornpany did not request a change to the curent Commission approved wind integration rate of $6.501M. 23 P ACIFICORP - 2011 IRP APPENDIX B - IR REGULATORY COMPLIACE PUR A QF Wind, ID PAC-E-07-07, p. 7. Idaho wind developers wil be notified as part of the public meetig process and can contrbute their input at those meetigs to discuss PacifiCorp s wind integration study and new data related to wind integrtion costs pnor to the publishing of the Corn an s next IR. PacifiCorp continued to invite Idaho wind developers to IR public input meetigs. Information on the 2010 wind integration study and wind resource modeling in general is posted to the Company's IR Web site. Order No. 10-066, Docket No. LC 47, p.26. Order No. 10-066, Docket No. LC 47, p.26. Order No. 10-066, Docket No. LC 47, p.26. Order No. 10-066, Docket No. LC 47, p.26. Action Item 3 (Peaking/ntermediate/Base- load Supply- side Resources) - In recognition of the unsettled U.S. econorny, expecte volatility in natual gas markets, and regulatory uncertainty, continue to seek cost-effective resource deferr and acquisition opportties in line with near-term updates to load/pnce forecasts, rnarket conditions, tranmission plans and regulatory developrnents. PacifiCorp wil reexamine the timing and tye of gas resources and other resource changes as par of a comprehensive assumptions update and portfolio analysis to be conducted for the 2008 RFP final short- list evaluation in the RFP, approved in Docket UM 1360, the next business plan and the 2008 IRP u date. Additional Action Itern 4 - For futue IR planning cycles, include on-going financial analysis with regard to transmission, which includes: a comparson with altemative supply side resources, deferred timing decision cntena, the unique capital cost nsk 'associated with transrnission projects, the scenaro analysis used to determine the implications of this nsk on customers, and all sumares of stochastic annual production cost with and without the proposed transrnission segments and base case se ents. Additional Action Item 5 - By Augut 2, 2010, complete a wind integrtion study that has been vetted by staeholders though a public paricipation process. Additional Action Itern 6 - Durg the next planing cycle, work with paries to investigate carbon dioxide emission levels as a measure for portfolio erformnce sconn . PacifiCorp updated its resource needs assessment and rnodeling input assumptions as par of the all- source RFP bid evaluation process, 2011 business planing process, and 2011 IRprocess. Documentation on these updates was provided as par of the Company's application for approval of its 2008 RFP bidder fial shortlist by the Oregon Commission (Docket UMJ360). This IRP also fully documents the cornprehensive assumptions update for the 2011 IR. See Chapter 5, "Resource Needs Assessrnent", Chapter 7, "Modeling and Portfolio Evaluation Approach", and Appendix A, "Load Forecast Review". Energy Gateway financial analysis is included in Chapter 4 of the 2011 IRP. Supportg information is included as Appendix C. PacifiCorp completed the wind integrtion study and distrbuted it to the public via email and Web site postig on September 1, 2010 in accordance with the Oregon Commssion granting a deadline extension frorn August 1 to September 1, 2010. The stud is included in the 2011 IRP as A endix i. Total CO2 emissions for the 20-year simulation penod were included as a final screening performance measure for portfolio evaluation and detennnation of the 2011 IR preferred portfolio. See the "Final Screenin " section of Cha ter 7 and 24 PACIFiCORP~2011 IRP APPENDIX B - IRP REGULATORY COMPLIACE Order No. 10-066, Docket No. LC 47, p.27. Order No. 10-066, Docket No. LC 47, p.27. Order No. 10-066, Docket No. LC 47, p.27. Order No. 10-066, Docket No. LC 47, p.26. Order No. 10-066, Docket No. LC 47, p.26. Additional Action Item 7 - In the next IR, provide information on total CO2 emissions on a year-to year basis for all portolios, and specifically, how they com are with the referred ortolio. Additional Action Itern 8 - For the next IR planning cycle, PacifiÇorp will work with paries to investigate a capaCity expansion rnodeling approach that reduces the influence of out-year resource selection on resource decisions covered by the IRP Action Plan, and for which the Cornpany can suffciently show that portfolio performance is not unduly influenced by decisions that.are not relevant to the IR Action Plan. Additional Action Item 9 - In the next IR planning cycle, PacifiCorp wil incorporate its assessment of distrbution effciency potential resources for planing puroses. Revised Action Item 9 (Planing Process Improvements) - For the next IRP planning cycle complete the implementation of System Optimizer capacity expansion model enhancements for irnproved representation of CO2 and RPS regulatory requirements at the jursdictional leveL. Use the enhanced model to provide more detailed analysis of potential hard-cap regulation of carbon dioxide emissions and achievement of state or federal ernissions reduction goals. Also use the capacity expansion model to evaluate the cost-effectiveness of coal facility retirernent as a potential response to futue regulation of carbon dioxide emissions. Revised Action Itern 9 (Planning Process Improvernents) - In the next IRP planing cycle provide an evaluation of, and contiue to investigate, the formulation of satisfactory proxy intermediate-term rnarket purchase resources for puroses of portolio modeling and contingent on ac uiin suitable market data. portfolio evaluation results in Chapter 8, "Modeling and Portolio Evaluation Results". CO2 emissions trend chars for each portfolio, including the preferred portolio, are included in AppendixD. PacifiCorp used portolio development case nuiber 9 for testig how out-year resource selection (years 2021-2030) irnpacts selection of near-term resources (years 2011~2020). The Company cornpared two portolios: a base 20-year System Optimizer ru and a test 20-year ru where resources for the first 10 years are fixed based on a prior 10-year simulation. Results are sumarzed in Chapter 8, "Modeling and Portfolio Evaluation Results". PacifiCorp is conducting a conservation voltage reduction study, targetig 19 distrbution feeders in Washington. The study is expected to be cornpleted by the end of May 2011. Based on prelirninary data . provided by the contractor for the study, PacifiCorp developed a distrbution effciency resource for testing with the System Optimizer modeL. Results of the portfolio development testing are provided in Chapter 8, "Modeling and Portfolio Evaluation Results". PacifiCorp successfully implemented the Systern Optimier model enhancernents, and defined five emission hard cap evaluation cases for modeling (nos. 15-18, pIus a hard cap case for coal plant utilization scenaro analysis). PacifiCorp conducted System Optimizer modeling for five coal plant utilization scenaros in which coal units are allowed to be replaced by CCCT resources, taking into account coal plant incremental costs. Modeling results are described in Chapter 8, "Modeling and Portolio Evaluation Results". As noted in this chapter, the coal utilization study is intended as a modeling proof-of-concept only. PacifiCorp's All-sourceRFP, reactivated in December 2009, yielded no satisfactory proxy intermediate-term market purchasè resources. 25 PACIFICORP - 2011 IRP APPENDIX B - IR REGULATORY COMPLIANCE Order No. 10-066, Docket No. LC 47, p.27. Order No. 10-066, Docket No. LC 47, p.24. Additional Action Itern (not numbered) - In addition, the Company wil file its 2008 IRP Update approximtely one year after the date of this Order, in compliance with Guideline 3. With regàrd to NWC's suggestion that appropriate reserves be separtely determed, we direct the paries to discuss this issue in the next plang. The 2011 IRfulfills the filing requirernent, given that the March 31, 2011 filing date is approximately one yea after the acknowledgment of the 2008 IRP (Febru 24, 2010). PacifiCorp discussed planing reserve margin analysis at its August 4,2010, public input rneeting. The Company outlined a 10ss of load study to determne an appropriate planing reserve rnargin to apply for portfolio development. Public staeholders did not take issue with the study approach. The study was distrbuted for IRP artci ant review November 18 2010. UT Docket No. 09- 2035-01, Report & Order, p. 24. UT Docket No. 09- 2035-01, Report & Order, p. 24-25. UT Docket No. 09- 2035-01, Report & Order, p. 30. UT Docket No. 09- 2035-01, Report & Order, p. 30. UT Docket No. 09- 2035-01, Report & Order, p. 30. UT Docket No. 09- 2035-01, Report & Order, p. 30. At a minimum, we direct the Company to perform a sensitivity case in its next IRP or IRP update wherein the ENS cost is flat and based on the Federal Energy Re lato Commssion rice ca . Additionally, in an IR public input rneeting, we direct the Company to identify a reasonable number of cases, includig high and low 10ad growt cases, to cornpare the costs and risks to custorners, or to identify a reasonable alternative rnethod, e.g., a LOLP study, for evaluating an appropriate planning reserve. At a minimum we direct the Company to include the costs of hedging in its IR analysis of resources that rely on fuels subject to volatile prices. We also direct the Company to pedorm sensitivity analysis to determne a hedging strategy which minimizes costs and risks for custorners. Additionally, we direct the Company to include an analysis of the adequacy of the western power rnarket to support the volumes of purchases on which the Cornpany expects to rely. We concur with the Office (of Consumer Services), the WECC is a reasonable source for this evaluation. We direct the Company to identify whether customers or shareholders wil be expected to bear the risks associated with its reliance on the wholesale market. Finally, we direct the Cornpany to discuss rnethods to augment the Cornpany's stochastic analysis of this issue (WECC rnarket depth and liquidity) in an IRP This sensitivity analysis is described in the section entitled, "Cost of EnergyNot Served (ENS) Sensitivity Analysis" in Chapter 8. PacifiCorp conducted a stochastic loss of load study for this IR, which was published November 18, 2010 for review by stakeholders, and is presented as Appendix 1. The Company also developed high/low economic growth and l-in-1O peak-producing temperatue scenarios for evaluating portfolio irnpacts of alternative load forecasts. The results of these alternative 10ad forecasts are described in Chapter 8. Stochastic production cost results are re ortd in A endix E. PacifiCorp addresses hedging costs in Appendix G, "Hedging Strategy". The Company discusses hedging strategies and the impacts of varous hedging levels on risk and expected cost in Appendix G, "Hedgig Strategy". The Cornpany's analysis of western resource adequacy is provided as Appendix H. Identification of who bears the risk ofrnarket reliance (custorners versus shareholders) is identified as welL. Based on feedback from partes attending the June 2010 Uta IR stakeholder input rneeting, PacifiCorp developed a rnarket purchase stress test proposal, which was vetted at the October 5th IR 26 PACIFICORP - 2011 IRP APPENDIX B - IR REGULATORY COMPLIACE public input rneeting for inclusion in the next IR or IRP update. general public input meeting. The results of the stress test, which used stochastic production cost simulation, are described in Appendix H. UT Docket No. 09- 2035-01, Report & Order, p. 35. UT Docket No. 09- 2035-01, Report & Order, p. 35. UT Docket No. 09- 2035-01, Report & Order, p. 35. UT Docket No. 09- 2035-01, Report & Order, p. 38. We direct the Company to discuss rnethods for irnproving the evaluation of nontraditional resources in an IRP public input meeting. At a minirnum, this discussion should include ideas for improving the evaluation of distributed solar technologies which provide opportities for customer partcipation, i.e., a solar rooftop customer buy-down program, and options for improving the evaluation of storage technologies designed to enhance the value and pedormance of intermittent renewable resources. We also concur with the Division and Offce regarding the need for review of geothermal resources and direct the Company to fie a geothermal resource study as described by the Division within 60 days of the date of this order. We wil initiate a comment period upon its fiing and this information can be included in the next IRP or IRP u date. In the futue, the Company is directed to ornit from its core cases any resource for which it does not already have a signed final procurement contract or certificate of public convenience and necessity. However, this does not preclude the Company from including such resources in sensitivity cases. This wil assist with the consistent and comparable treatment of resources oin forward. ... we again direct the Company to address these issues in the next IR or IR update: i.e., . Number of years relied upon for developing stochastic parameters. . Role of planning reserve in managing the risks of forecast error. PacifiCorp discussed the evaluation of nontraditional resources, including energy storage, at the August 4, 2010 IR public input meeting. A consultat study on incremental capacity value and ancilary service benefits of energy storage is planed for 2011 or 2012. This study is identified in the 2011 IRP action plan. The geothermal resource report was filed with the Utah Commission on August 10,2010 in accordance with the Commission's deadline extension. A conference call with Uta pares to discuss the report and the Cornpany's follow-up activities was held December 9, 2010. No resource has been fixed in the core portfolios, except for the 2011 business plan core case #19, which is intended as a reference case for planed resources identified in the business plan. PacifiCorp discussed stochastic parameter updates at the December 15,2010 IRP public meeting. Due to time constraints, PacifiCorp tageted its 10ad stochastic parameters for updating in the 2011, using a three-year data set originally prepared for the 2010 wind integration study. UT Docket No. 09- 2035-01, Report & Order, p. 39. (We) direct the Cornpany and interested paries to exarnine and consider all of the suggestions contained in (the ODS) report. At a minimum, the Cornpany is directed to provide a range of 10ad forecasts that cornport with industr standads as recommended by ODS. Furer, as recommended by ODS, we direct the Com an to rovide the As noted above, PacifiCorp adopted the ODS recommendations for inclusion of 10ad growt scenaros based on different assumptions concerning economic drvers. The Company also developed a l-in-l0 peak-producing ternperatue scenario. The results of these alternative load forecasts are described in Chapter 8. A endix A constitutes the Com an's stadalone 27 PACIFICORP - 2011 IRP APPENDIX B - IRP REGULATORY COMPLIACE UT Docket No. 09- 2035-01, Report & Order, p. 40. UT Docket No. 09- 2035-01, Report & Order, p. 41. UTDocketNo.09- 2035~01, Report & Order, p. 42. UT Docket No. 09- 2035-01, Report & Order, p. 54. UT Docket No. 09~ 2035-01, Report & Order, p. 55. Uta Commission Docket No. 08-035- 56, DSM Potential Study, Report & Commission with a comprehensive stad- alone load forecast report when the forecast is updted. The GDS suggestions could reduce last minute revisions due to 10ad forecast changes and thereby assist in the timel corn letion of futue IRs. We again diect the Company to address (hydro capacity accounting) in its next IR or IRP update and provide the results of its analysis. For example, it may be useful to conduct sensitivity analysis regarding this assumption to identify potential risks or shortomings of the curent rnethodolo . We concur with the Division and direct the Cornpany to complete its own wind integration study. We understand this process is underway and that the Cornpany is circulating the study for review. We direct the Company to address the Division's concerns and include this study in the next IR or IR u date. (W)edirect the Company to solicit and discuss fuer improvements to its resource acquisition path analysis and decision rnechanism and address the Division's concerns in its next IR or IR update. In order to ensure tirnely and meaningful informtion exchange, we diect the Cornpany to adopt two of the Division's recommendations on improvig public input meetigs. · First, materials should be distrbuted one week prior to the public input meeting. · Secondly, a wrtten report should be provided after each meeting to provide follow-up to issues or uestions raised in the meetin . We concur with the Division and UAB, training on the Company's models in order for paries to validate the models and to gain confdence in the modeling results is wortwhile. We diect the Company to convene at least a full~day meetin to this end. The Company proposes to adjust the technical potential using its assumptions regarding achievable levels ofDSM to serve as the supply cures in its IRP. It load forecast report. PacifiCorp provided a detailed analysis of I8-hour sustaned hydro peaking capability and its applicability to hydro capacity accounting in the load & resource balance in Appendix H. PacifiCorp cornpleted the wind integration study and distrbuted it to the public via email and Web site posting on September 1,2010. The study is included in the 2011 IRP as Appendix i. PacifiCorp expanded the acquisition path analysis to include alternative reguatory policy scenaros, and applied sensitivity analysis results to identify acquisition paths and resource quantities for 10ad growt and natul gas price forecast trends. A more extensive discussion of the decision mechanisrn has been provided in response to the Utah Division of Public Utilities wrtten comments on the 2008 IR. PacifiCorp has complied with the requirernent to distrbute meeting rnaterials one week prior to public meetings. Written reports on public rneetings have been prepared and distrbuted to paricipants via email and postings to the IRP Web site. PacifiCorp is planng to hold tutorial sessions durg the second quarer of 20 11 for both Systern Optimizer and the Planning and Risk modeL. A non- disclosure agreement between parcipants and the model vendor, Venty, wil be required due to sharing of proprietary information. PacifiCorp ra System Optimizer with DSM supply cures based on unadjusted techncal potentiaL. Given the paricular input assumptions used, the rnodel deferred CCCT resources. The results of this 28 P ACIFICORP - 2011 IRP APPENDIX B - IRP REGULATORY COMPLIACE Order, p. 8. DSM Pótential Study, Docket No. 08-035-56, Report & Order, p. 9. DSM Potential Study, Docket No. 08-035-56, Report & Order,p. 9. would then use these adjusted supply cures in IR to determne cost-effective amounts ofDSM. UCE and WR disagree and propose that the Cornpany use the unadjusted technical potential to form the supply cures in IRP to determne the full cost-effective level of DSM and then rnake provision in its path or contingency analysis for the possibility that the cost-effective amouít ofDSM may not be achieved in the time-frame rnodeled...we direct the Company to evaluate the two approaches in its next IR or IRP update. We encourage the Cornpany to solicit input from interested paries on methods for evaluating the two approaches. We wil request pares' comments on the Cornpany's evaluation of the two approaches in an appropriate IRP or IR u date docket. With respect to estimating the cost of solar resources, UCE and WR provide considerably different cost estimates than PacifiCorp. The differences are large enough that we would expect significant differences to appear in the Company's IR action plan depending on the assumptions used in the IR process. We direct the Cornpany to perform sensitivity analysis with respect to the assumed cost of solar resources in its next IRP or IR u date. Going forward, the Company shall provide information on both the total cost of solar resources in comparson to other resources, and also the cost to the utility of a utility-sponsored program to encourge custorner adoption of this resource. The Company could begin such analysis with prelirninar data frorn the solar incentive pilot program. We direct PacifiCorp to work with interested paries regarding how to evaluate solar resources in the ongoing IRP process and we will consider comments on this effort in an appropriate IRP proceedig. study are described in Chapter 8, "Dernand-side Management Cases." PacifiCorp updated all distrbuted generation cost estiates for the 2011 IR, including solar resources. The Cadmus Group prepared input assumptions memos that were distrbuted to public staeholders for review and comment in July and August, 2010. PacifiCorp discussed with interested paries System Optimizer portolio development scenarios reflecting a solar PV cost buy-down program. A conference call was held Janua 27,2011, to finalize the study approach. The modeling approach is described in the section titled "Case Definitions" in Chapter 7. Modeling results are sumarzed in the section titled, "Renewable Resource Cases" in Chapter 8. 29 P ACIFICORP - 2011 IRP APPENDIX B - IR REGULATORY COMPLIANCE Letter Order, UE- 080826, i\ttchnent p.1. Letter Order, UE- 080826, Attchnent p.1. Letter Order, UE- 080826, Attchnent p.4. Transmission Planning (Chapter 4). The next IR should discuss alternative transmission options. Transmission Planning (Chapter 4). The next IR should discuss alternative deployment schedules for the transmission projects it considers and the benefits of each of the alternative deployment schedules of any transmission segments considered in the modeling. Specifically, the varous portolios have different resource selections durng the first five years of the planing period. This rnight result in PacifiCorp, in its planning process, choosing a set of early resources because they are in a portfolio with lower risks in the later years of the planing horizon, even though the portolios with higher risks could be rnitigated by futue flexibility rather than by choosing a different portolio. · PacifiCorp should address this issue in its next IR The action plan does not specifically rnention the utility's obligation under RCW 19.285 to determne and meet certin energy effciency targets. The Commission reminds the Company that it ci t t thO bI'. t Chapter 4 outlines an analysis of seven Energy Gateway deployment scenarios that considers alternative transmission footprints, investment costs, in-servce dates, and economic drvers. Chapter 4 focuses on two deployment scenaros based on alternative directions for state and federal resource policies: a Green Resource Futue and Incumbent Resource Futue. Additionally, the section entitled "Custorner Load and Resources" in Chapter 4 sumarzes the process that PacifiCorp follows, in compliance with its Open Access Transmission Tarff, to plan for and invest in trnsmission to meet network customer load re uirements. PacifiCorp conducted a sensitivity analysis to isolate the near-term resource selection impact of out-year resources in the context of capacity expansion optirnization modeling. The results of the sensitivity analysis are provided in Chapter 8. Action Itern Number 6, Class 2 DSM, explicitly mentions PacifiCorp's obligation to meet energy effciency targets under RCW 19.285. .;; /;; :m ;: - 7: ;; ;. 2'%01;", ?/:m..%%v .%% -i8/ ~/ / . .../%%./ ¿¡ *..¿¡./ Y 1í.ø;"' ;: m ;; 31:jjß ÆS% ;ø ;; ,,~7; z;:~ ~ "~,, %/"%;;øßJ:i~ .;; ;: vA J4t;;;; %;:;: YlYÆ r&! :I"d;~__~". The Wyoming Public Service Commission provided the following comment in its Letter Order (Docket No. 20000-346- EA-9, dated 11/23/2010) on PacifiCorp's 2008 IR: Pursuant to open meeting action taken on January 11,2008, PacifCorp d/b/a Rocky Mountain Power's 2007 Integrated Resouree Plan (IRP) is hereby plaeed in the Commission's files. No further action wil be taken and this docketed matter is closed. 30 P ACIFICORP - 2011 IR APPENDIX B - IR REGULATORY COMPLIACE Table B.3 - Oregon Public Utilty Commission IRP Standard and Guidelines l.a.1 All resources rnust be evaluated on a consistent and comparable basis: All known resources for rneetig the utility's load should be considered, including supply- side options which focus on the generation, purchase and trnsmission of power - or gas purchases, transporttion, and storage - and demand-side options which focus on conservation and dernand response. PacifiCorp considered a wide range of resources including renewables, demand-side management, distrbuted generation, energy storage, power purchases, thermal resources, and transmission. Chapters 4 (Transmission Planning), 6 (Resource Options), and 7 (Modeling and Portolio Evaluation Approach) document how PacifiCorp developed these resources and modeled them in its portfolio analysis. All these resources were established as resource options in the Company's capacity expansion optimization model, System Optimizer, and selected by the rnodel based on relative economics, resource size, availability dates, and other factors. All portfolios developed with Systern Optimizer were subjected to Monte Carlo production cost simulation. These portfolios contained a varety of resource tyes with different fuel tyes (coal, gas, biomass, nuclear fuel, "no fuel" renewables), lead-times (ranging from front offce transactions to nuclear plants), in-service dates, life-tirnes, and locations. PacifiCorp fully complies with this requirement. The company developed generic supply-side resource attbutes based on a consistent characterization rnethodology. For dernand-side resources, the company used the Cadmus Group's supply cure data developed in 2010 for representation ofDSM and distrbuted generation resources, which was also based on a consistently applied methodology for determining technical, rnarket, and achievable DSM potentials. All portolio resources were evaluated using the same sets of price and 10ad forecast inputs. These inputs are documented in Chapters 6 and 7. PacifiCorp applied its after-tax W ACC of 7.17 percent to discount all cost streams. PacifiCorp fully complies with this requirement. Each of the sources of risk identified in this gudeline is treated as a stochastic variable in Monte Carlo production cost simulation with the exception of CO2 emission compliance costs, which are treated as a scenario risk. See the stochastic rnodeling rnethodology section in Chapter 7. PacifiCorp complied with this guideline by discussing resource risk mitigation in Chapter 9 as well as addressing market reliance risk and hedging strategies in Appendix G and H, respectively. Topics covered include: (1) managing carbon risk for existing plants, (2) the use of physical and l.a.2 All resources must be evaluated on a consistent and cornparable basis: Utilities should compare different resource fuel tyes, technologies, lead tirnes, in-servce dates, durations and locations in portfolio risk modeling. 1.a.3 All resources rnust be evaluated on a consistent and comparable basis: Consistent assumptions and methods should be used for evaluation of all resources. l.aA All resources rnust be evaluated on a consistent and comparable basis: The after-tax rnarginal weighted-average cost of capital (W ACC) should be used to discount all futue resource costs. Risk and uncertinty must be considered: At a miimum, utilities should address the followig sources of risk and uncertainty: 1. Electrc utilities: load requirements, hydroelectric generation, plant forced outages, fuel prices, electricity prices, and costs to cornply with any regulation of greenhouse gas emissions. Risk and uncertinty rnust be considered: Utilities should identify in their plans any additional sources of risk and uncertinty. l.b.1 l.b.2 31 P ACIFICORP - 2011 IRP APPENDIX B - IR REGULATORY COMPLIACE I.c .I.c.l I.c.2 I.c.3.1 I.c.3.2 l.cA I.d The priar goal must be the selection of a portolio of resources with the best combination of expected costs and associated risks and uncertainties for the utilty and its customers ("best cost/risk portolio"). The planing horizon for analyzing resource choices should be at least 20 years and account for end effects. Utilities should consider all costs with a reasonable likelihood of being included in rates over the long term, which extends beyond the planning horizon and the life of the resource. Utilities should use present value of revenue requirernent (PVR) as the key cost metrc. The plan should include analysis of curent and estirnated futue costs for alllong-lived resources such as power plants, gas storage facilties, and pipelines, as well as all short- lived resources such as gas supply and short- term power purchases. To address risk, the plan should include, at a minimum: 1. Two measures of PVR risk: one that measures the varability of costs and one that measures the severity of bad outcomes. To address risk, the plan should include, at a rninimum: 2. Discussion of the proposed use and impact on costs and risks of physical and financial hedging. The utility should explain in its plan how its resource choices appropriately balance cost and risk. The pIan must be consistent with the long-ru public interest as expressed in Oregon and fedeml energy policies. financial hedging for electrcity price risk, and (3) managing gas supply risk. Regulatory and financial risks associated with resource and transmission investments are highighted in seveml areas in the IRP document, including Chapters 4 and 8. PacifiCorp evaluated cost/risk tradeoffs for each of the portolios considered, See Chapter 8 for the cornpany's portolio cost/risk analysis and determation of the preferred portolio. PacifiCorp used a 20-year study period for portfolio modeling, and a reallevelized revenue requirement methodology for treatment of end effects consistent with past IRP practice. PacifiCorp fuly complies. Chapter 7 provides a description of the PVR methodology. PacifiCorp uses the stadad deviation of stochastic production costs as the measure of cost variability. For the severity of bad outcornes, the company calculates several rneasures, includig stochastic upper-tail mean PVR (rnean of highest five Monte Carlo itemtions) and the 95th percentile stochastic production cost PVR. A discussion on costs and risks of hedging is provided in Appendi G. Chapter 8 sumarzes the results ofPacifiCorp's cost/risk tradeoff analysis, and describes what criteria the company used to determine the best cost/risk portfolios and the preferred portfolio. PacifiCorp considered both curent and potential state and fedeml energy/pollutat emission policies in portfolio modeling. Chapter 7 describes the decision process used to derive portolios, which includes considemtion of state resource policies. The IR action plan chapter also presents an acquisition path analysis that describes resource strategies based on reguatory trgger events. 32 PACIFiCORP-2011 IRP APPENDIX B - IR REGULATORY COMPLIACE 2.a The public, which includes other utilities, should be allowed significant involvernent in the preparation of the IRP. Involvement includes opportities to contrbute information and ideas, as well as to receive information. Paries must have an opportity to make relevant inquires of the utility formulatig the plan. Disputes about whether informtion requests are relevant or uneasonably burdensorne, or whether a utility is being properly responsive, may be submitted to the Commission for resolution. While confidential information rnust be protected, the utility should make public, in its pIan, any non-confidential information that is relevant to its resource evaluation and action plan. Confidential information may be protected through use of a protective order, through aggregation or shielding of data, or through any other mechanism approved by the Commission. The utility rnust provide a draft IRP for public review and comment prior to filing a final plan with the Commssion. PacifiCorp fuly complies with this requirement. Chapter 2 provides an overview of the public process, while Appendix D documents the details on public meetings held for the 2008 IRP. Both IR volumes provide non-confidential information the cornpany used for portfolio evaluation, as well as other data requested by staeholders. PacifiCorp also provided staeholders with non-confidential information to support public rneeting discussions via emaiL. PacifiCorp distrbuted a parial draft IRP document for external review on February 23, 2011 and the rernaining chapters on March 7, 2011. 2.b 2.c (3)A utility must fie an IRP within two years of its previous IR acknowledgment order. If the utility does not intend to take any significant resource action for at least two years after its next IRP is due, the utility rnay request an extension of its filing date frorn the Commission. The utility rnust present the results of its fied plan to the Commission at a public meeting prior to the deadline for wrtten public comment. Commission staff and parties rnust cornplete their comments and recommendations within six rnonths of IR filing. The Commission must consider comments and recommendations on an energy utility's pIan at a public meeting before issuing an order on acknowledgment. The Commission rnay provide the energy utility an opportity to revise the IRP before issuig an acknowledgment order. The Commission rnay provide direction to a utility regarding any additional analyses or actions that the utility should underte in its nextlRP. This PIan complies with this requirement. Not applicable; activity conducted subsequent to fiing this IRP. Not applicable; activity conducted subsequent to fiing this IRP. Not applicable; activity conducted subsequent to fiing this IR. Not applicable; activity conducted subsequent to filing this IRP. (4) (5) (6) (7) 33 P ACIFICORP - 2011 IRP APPENDIX B - IR REGULATORY COMPLIACE (8)Each energy utility rnust submit an anual update on its rnost recently acknowledged IR. The update is due on or before the acknowledgrnent order aniversar date. The energy utility must sumare the anual update at a Commission public meetig. The energy utility may request acknowledgment of changes, identified in its update, the IR action pIan. The annual update is an informational fiing that: (a) Describes what actions the energy utility has taken to implement the action pIan to select best portolio of resources contained in its acknowledged IR; (b) Provides an assessrnent of what has changed since the acknowledgment order that affects the action plan to select best portolio of resources, including changes in such factors as load, expiration of resource contrcts, supply-side and demand-side resource acquisitions, resource costs, and transmission availability; and (c) Justifies any deviations from the action plan contained in its acknowledged IR. As soon as an energy utility anticipates a significant deviation from its acknowledged IRP, it must fie an update with the Commission, unless the energy utility is within six rnonths of fiing its next IRP. This update rnust meet the requirements set fort in section (8) of this rule. If the energy utility requests Commission acknowledgernent of its proposed changes to the action plan contained in its acknowledged IRP: (a) The energy utility must fie its proposed changes with the Commission and present the results of its proposed changes to the Commission at a public meeting prior to the deadline for wrtten public comment; (b) Commission staff and partes must file any comments and recommendations with the Commission and present such comments and recommendations to the Commission at a public meeting within six rnonths of the energy utility's filing of its request for acknowledgement of proposed changes; (c) The Commission may provide direction to an energy utility regardig any additional analyses or actions that the utility should underte in its next IR. (9) Not applicable; activity conducted subsequent to filing this IR. Not applicable; activity conducted subsequent to fiing this IR. Not applicable; activity conducted subsequent to filing this IRP. 34 PACIFICORP - 2011 IRP APPENDIX B - IRP REGULATORY COMPLIACE 4.a 4.b An explanation of how the utility met each of the substative and procedural requirernents. Analysis of high and low load growth scenaros in addition to stochastic load risk analysis with an explanation of major assumptions. 4.c For electrc utilities, a determination of the levels of peaking capacity and energy capability expected for each year of the plan, given existing resources; identification of capacity and energy needed to bridge the gap between expected loads and resources; rnodeling of all existing transmission rights, as well as futue transmission additions associated with the resource portfolios tested. F or gas utilities only Identification and estimated costs of all supply- side and dernand side resource options, taking into account anticipated advances in technology The purose of this table is to cornply with this guideline. PacifiCorp developed low and high load growt forecasts for scenaro analysis based on economic growt assumptions using the Systern Optimizer model for portfolio development. Stochastic varability of loads was also captued in the risk analysis. See Chapters 5, 7, and 8, as well as Appendix A, for load forecast information. Chapter 8 also describes how 10ads are handled in the stochastic modeling. This Plan complies with the requirement. See Chapter 5 for details on anual capacity and energy balances. Existig trmission rights are reflected in the IRP model topologies, as rnentioned in Chapter 7. Not applicable Chapter 6 identifies the resources included in this 1R, and provides their detailed cost and performance attbutes. See Tables 6.2 through 6.10 for supply-side resources, and Tables 6.15 through 6.20 for demand-side resources. In addition to incorporating a planing reserve margin for all portolios evaluated, the company used several measures to evaluate relative portfolio supply reliability. These are described in Chapter 7 (Energy Not Served and Loss of Load Probability). PacifiCorp conducted a stochastic loss ofload study in 2010 to support selection of the planing reserve rnargin. This study is included as Appendix J. Chapter 7 describes the key assumptions and alternative scenarios used in this IRP. This Plan documents the development and results of 67 portfolios designed to determe resource selection under a variety of input assumptions (Chapter 8). Chapter 8 and Appendix E present the stochastic portfolio rnodeling results, and describes portolio attibutes that explain relative differences in cost and risk performance. Chapter 8 provides tables and char with performnce rneasure results, including ran ordering. 4.d 4.e 4.f Analysis of rneasures the utility intends to take to provide reliable service, including cost-risk tradeoffs 4.g Identification of key assumptions about the futue (e.g., fuel prices and environmental cornpliance costs) and alternative scenaros considered Constrction of a representative set of resource portolios to test varous operating characteristics, resource types, fuels and sources, technologies, lead tirnes, in-service dates, durations and generallocations - system- wide or delivered to a specific porton of the system Evaluation of the performance of the candidate portfolios over the range of identified risks and uncertinties Results of testing and ran orderig of the portfolios by cost and risk metrc, and interpretation of those results. 4.h 4.i 4.j 35 P ACIFICORP - 2011 IRP APPENDIX B - IRP REGULATORY COMPLIACE 4.k Analysis of the uncertinties associated with each portfolio evaluated. Selection of a portfolio that represents the best cornbination of cost and risk for the utility and its customers. Identification and explanation of any inconsistencies of the selectedportolio with any state and federal energy policies that may affect a utility's plan and any barers to irnplementation. An action plan with resource activities the utility intends to underte over the next two to four year to acquire the identified resources, regardless of whether the activity was acknowledged in a previous IR, with the key attbutes of each resource specified as in portolio testing. 4.1 4.m PacifiCorp fully complies with this guideline. See the responses to I.b.1 and I.b.2 above. See I.c above. This IR is presumed to have no inconsistencies. Chapters 9 and 10 presents the 2011 IRP and transrnission expansion action plans, respectively. 5 Portolio analysis should include costs to the utility for the fuel trsportation and electrc trnsmission required for each resource being considered. In addition, utilities should consider fuel trnsporttion and electrc transmission facilities as resource options, taing into account their value for making additional purchases and sales, accessing less costly resources in rernote locations, acquirg alternative fuel supplies, and improving reliability. PacifiCorp evaluated proxy transmission resources on a comparable basis with respect to other proxy resources in this IR. Fuel transporttion costs were factored into resource costs. 6.a 6.b Each utility should ensure that a conservation potential study is conducted periodically for its entire service terrtory. To the extent that a utility controls the level of fuding for conservation prograrns in its service terrtory, the utility should include in its action plan all best cost/risk portolio conservation resources for meeting projected resource needs, specifYing annual savings tagets. To the extent that an outside par adisters conservation program in a utility's servce terrtory at a level of fuding that is beyond the utility's control, the utility should: 1. Determe the amount of conservation resources in the best cost/risk portfolio without regard to any limits on funding of conservation programs; and 2. IdentifY the preferred portfolio and action plan consistent with the outside par's projection of conservation acquisition. 6.c A multi-state dernand-side management potentials study was cornpleted in late 2010, and those results were incorporated into this plan. PacifiCorp's energy effciency supply cures incorporate Oregon resource potentiaL. Oregon potential estimates were provided by the Energy Trust of Oregon. See the dernand- side resource section in Chapter 6. See the response for 6.b above. 36 P ACIFICORP - 2011 IRP APPENDIX B - IRP REGULATORY COMPLIANCE 7 Plans should evaluate demand response resources, including voluntary rate programs, on par with other options for rneeting energy, capacity, and transmission needs (for electrc utilities) or gas supply and transporttion needs (for natual gas utilities). PacifiCorp evaluated demand response resources (Class 3 DSM) on a consistent basis with other resources in a portfolio sensitivity study. Class 3 DSM programs are addressed in !tern 7 of the IR action pIan in Chapter 9. 8 / .~~;gji ;;;; ll 1!/ i/ %7/ ;;WJ ru :ø: m~ ;; / Y' 0i ;; ,;/"' /ÝZ;: 1% ;: *XW/;;¿¿. 8l Al _ilL ////III1Jl /; % /; // $;;/ "" %/;; / ;ff~ ~ a. Base Case and Other Compliance Scenarios b. Testing Alternative Portolios Against the Compliance Scenarios c. Trigger Point Analysis d. Oregon Compliance Portfolio This IRP fully complies with the CO2 compliance cost analysis requirernents in Order No. 08-339. Performance results for CO2 compliance scenaro portfolios are reported in Chapter 8, including hard cap scenaros using the Oregon emission targets in HB 3543. 10 Multi-state utilities should plan their generation and transmission systems, or gas supply and delivery, on an integrated systern basis that achieves a best cost/risk portfolio for all their retail custorners. The 2011 IRP conforms to the multi-state planing approach as stated in Chapter 2 ("The Role ofPacifiCorp's Integrated Resource Planing"). The Company notes the challenges in complying with rnulti-state integrated planning given differig state energy policies and resource preferences. 11 Electrc utilities should analyze reliability within the risk rnodeling of the actul portfolios being considered. Loss ofload probability, expected planing reserve rnargin, and expected and worst-case unserved energy should be determined by year for top-performing portfolios. Natual gas utilities should analyze, on an integrated basis, gas supply, transporttion, and storage, along with demand- side resources, to reliably meet peak, swing, and base-load system requirements. Electrc and natual gas utility plans should dernonstrate that the utility's chosen portfolio achieves its stated reliability, cost and risk objectives. PacifiCorp fully complies with this guideline. See the response to l.c.3.1 above. Chapter 8 describes the role of reliability, cost, and risk measures in determning the preferred portfolio. Scatter plots of portolio cost versus risk at different CO2 cost levels were used to inform the cost/risk tradeoff analysis. (Chapter 8). 12 ~"~l\P."ip _~i; ~ .~2£!1P~..f!../ / Vi/gAy /0/0 øuiv % %/;¡ i¡ % / %.i 0. Electrc utilities should evaluate distrbuted generation technologies on par with other supply-side resources and should consider, and quantify where possible, the additional benefits of distrbuted generation. PacifiCorp evaluated several tyes of distrbution generation, including cornbined heat and power and solar. The results of these evaluations are documented in Chapter 8. 37 P ACIFICORP - 2011 IRP APPENDIX B - IR REGULATORY COMPLIACE l3.a An electrc utility should, in its IRP:Chapter 9 outlines the procurement approaches for resources identified in the preferred portolio. A discussion of the advantages and disadvantages of owning a resource instead of purchasing it is included in Chapter 9. Company resources included in RFPs is addressed in the action pIan (Table 9.1 and accompanying narative). 1. Identify its proposed acquisition strtegy for each i:esource in its action pIan. 2. Assess the advantages and disadvantages of owning a resource instead of purchasing power from another par 3. Identify any Benchmark Resources it plans to consider in competitive bidding l3.b For gas utilities only Not applicable Table B.4 - Utah Public Service Commission IR Standard and Guidelines 1 The Commission has the legal authority to promulgate Standards and Guidelines for integrated resource planning. Informtion Exchange is the most reasonable rnethod for developing and implementing integrated resource planng in Utah. Prudence Reviews of new resource acquisitions wil occur durg raternakg proceedings. PacifiCorp's integrated resource planing process wil be open to the public at all stages. The Commission, its staff, the Division, the Committee, appropriate Utah state agencies, and other interested paries can partcipate. The Commission will pursue a rnore active-directive role if deerned necessar, after formal review of the planing process. Consideration of environmental externalities and attendat costs must be included in the integrated resource planning analysis. Not addressed; this is a Utah Public Service Commission responsibility. Information exchange has been conducted thoughout the IR process. Not addressed; raternaking occurs outside of the IR process. PacifiCorp's public process is described in Chapter 2. A record of public meetings is provided as Appendix D. PacifiCorp used a scenario analysis approach along with externality cost adders to rnodel environmental externality costs. See Chapter 7 for a description of the methodology employed, including how CO2 cost uncertainty is factored into the determation of relative portfolio performance. Supply, trsmission, and demand-side resources were evaluated on a comparable basis using PacifiCorp's capacity expanion optimization modeL. Also see the response to number 4.b.ii below. Consistent with the Utah rules, PacifiCorp determination of avoided costs wil be handled in a maer consistent with the IR, with the caveat that the costs may be updated if better information becornes available. 2 3 4 5 6 The integrated resource plan must evaluate supply-side and demand-side resources on a consistent and comparable basis. 38 7 A voided Cost should be determined in a manner consistent with the Cornpany's Integrated Resource PIan. PACIFiCORP-20ll IRP APPENDIX B - IRP REGULATORY COMPLIANCE 8 The planning standards and guidelines must rneet the needs of the Utah servce area, but since coordination with other jursdictions is importnt, must not ignore the rues governg the planning process already in place in other jursdictions. The Company's Strategic Business PIan must be directly related to its Integrated Resource Plan. 9 This IR was developed in consultation with pares frorn all state jursdictions, and meets all formal state IR guidelines. Chapter 9 describes the linage between the 2011 IR preferred portfolio and 2011 business plan resources approved in December 2010. Significant resource differences are highlighted. 1 2 Definition: Integrated resource planning is a utility planing process which evaluates all known resources on a consistent and comparable basis, in order to meet curent and futue customer electrc energy services needs at the lowest total cost to the utility and its custorners, and in a manner consistent with the long-ru public interest. The process should result in the selection of the optimal set of resources given the expected combination of costs, risk and uncertinty. The Company wil submit its Integrated Resource Plan biennially. Chapter 7 outlines the portfolio performance evaluation and preferred portfolio selection process, while Chapter 8 chronicles the rnodeling and preferred portfolio selection process. This IRP also addresses concerns expressed by Uta staeholders and the Utah commission concernng comprehensiveness of resources considered, consistency in applying input assumptions for portfolio rnodeling, and explanation ofPacifiCorp's decision process for selecting top-performg portfolios and the preferred portfolio. The company submitted its last IR on May 28, 2009, and filed this IR on March 31,2011. PacifiCorp files the IRP with all commissions on March 31 in each odd-numbered year. 3 PacifiCorp's public process is described in Chapter 2. A record ofpublic rneetings is provided as Appendix F. 4.a IR will be developed in consultation with the Commission, its staff, the Division of Public Utilities, the Committee of Consumer Services, appropriate Utah state agencies and interested paries. PacifiCorp wil provide arnple opportity for public input and information exchange durg the development of its Plan. PacifiCorp's integrated resource plans will include: a range of estimates or forecasts ofload growt, including both capacity (kW) and energy (kWh) requirements. 4.a.i The forecasts wil be rnade by jurisdiction and by general class and wil differentiate energy and capacity requirements. The Company wil include in its forecasts all on-systern loads and those off- system loads which they have a contrctul obligation to fulfiL. Non-fir off-systern sales are uncertin and should not be explicitly incorporated into the load forecast that the utility then plans to rneet. However, the Plan must have PacifiCorp implemented a 10ad forecast range for both capacity expansion optimization scenarios as well as for stochastic variability, covering both capacity and energy. Details concerning the 10ad forecasts used in the 2011 IRP are provided in Appendix A. Figure 7.4 in Chapter 7 shows the range of forecasts used for capacity expansion modeling. Figues 7.i 8 though 7.24 show the range of stochastic loads modeled for each 1000 area by the Monte Carlo production cost sirnulations. Price risk associated with rnarket sales is captued in the cornpany's stochastic sirnulation results. Curent off- system sales agreements are included in the IRP rnodels. 39 PACIFICORP - 2011 IRP APPENDIX B - IR REGULATORY COMPLIACE some analysis of the off-system sales market to assess the impacts such makets wil have on nsks associated with different acquisition strategies. 4.a.ii Analyses of how vanous economic and dernographic factors, includig the pnces of electrcity and alternative energy sources, wil affect the consumption of electrc energy services, and how changes in the number, tye and effciency of end-uses wil affect futue load. 4.b An evaluation of all present and futue resources, including futue maket opportities (both dernand-side and supply-side), on a consistent and comparable basis. 4.b.i An assessment of all technically feasible and cost- effective improvements in the efficient use of electrcity, including load managernent and conservation. 4.b.i An assessment of all technically feasible generating technologies including: renewable resources, cogeneration, power purchases from other sources, and the constrction of thermal resources. 4.b.i The resource assessments should include: life ii expectancy of the resources, the recognition of whether the resource is replacing/adding capacity or energy, dispatehability, lead-time requirements, flexibility, efficiency of the resource and opportnities for custorner paricipation. 4.c An analysis of the role of competitive bidding for dernand-side and supply-side resource acquisitions A 20-year planing honzon. An action plan outlining the specific resource decisions intended to implement the integrted resource plan in a maner consistent with the Company's strtegic business pIan. The action plan wil span a four-year honzon and wil descnbe specific actions to be taen in the first two years and outline actions anticipated in the last two year. The action pIan will include a status report of the specific actions contained in the previous action pIan. 4.d 4.e Appendix A documents how dernographic and pnce factors are used in PacifiCorp's new 10ad forecasting methodology. Resources were evaluated on a consistent and comparable basis using the System Optimizer rnodel and Planng and Risk production cost modeL. PacifiCorp included supply cures for Class 1 DSM (dispatchable/schedulable load control) and Class 2 DSM (energy effciency measures) in its capacity expansion modeL. Details are provided in Chapter 6. A sensitivity study of dernand-response prograrns (Class 3 DSM) was also conducted (See Chapter 8). PacifiCorp considered a wide range of resources including renewables, cogeneration (combined heat and power), power purchases, thermal resources, energy storage, and Energy Gateway trsmission segments. Chapters 4, 6 and 7 document how PacifiCorp developed and assessed these technologies and resources. PacifiCorp captues and rnodels these resource attbutes in its IR models. Resources are defined as providing capacity, energy, or both. The DSM supply cures and distrbuted generation resources used for portfolio modeling explicitly incorporate estimated rates of prograrn and event parcipation. Dispatchability is accounted for in both IRP models used; however, the Planing and Risk model provides a more detailed representation of unt dispatch than Systern Optier, and includes modeling of unit commtment and reserves. A descnption of the role of cornpetitive bidding and other procurement methods is provided in Chapter 9. This IR uses a 20-year study horizon (2011-2030) The IR action pIan is provided in Chapter 9. A status report of the actions outlined in the previous action plan (2008 IR update) is provided in Chapter 9 as well. The action plan (Table 9.1) also identifies actions anticipated to extend beyond the next two years, or occur aftr the next two years 40 P ACIFICORP - 2011 IRP APPENDIX B -lR REGULATORY COMPLIANCE 4.f A plan of different resource acquisition paths for different economic circumstances with a decision mechanisrn to select among and modify these paths as the futue unfolds. Chapter 9 includes an acquisition path analysis that presents broad resource strategies based on regulatory trgger events, combinations of load growt and gas price futues, and procurement delays. The associated decision mechanisrn is also described in more detail relative to the 2008IRP. PacifiCorp provides resource-specific utility and total resource cost information in Chapter 7. The lR document addresses the impact of social concerns on resource cost-effectiveness in the following ways: . Portolios were evaluated using a range of CO2 cost futues. . A discussion of environmental policy status and impacts on utility resource planning is provided in Chapter 3. . State and proposed federal public policy preferences for clean energy are considered for developrnent of the preferred portfolio, which is documented in Chapter 8. . Appendix L reports historical water consumption for PacifiCorp's thermal plants. The handling of resource risks is discussed in Chapter 9, and covers managing carbon risk for existig plants and managing gas supply risk. Transmission expansion risks are discussed in Chapter 3. Appendix G discusses hedging. Appendix'H discusses rnarket reliance risks and identifies who bears associated risks. Resource capital cost uncertinty and technological risk is addressed in Chapter 6 ("Handling of Technology Irnprovernent Trends and Cost Uncertainty"). For reliability risks, the stochastic simulation model incorporates stochastic volatility of forced outages for new thermal plants and hydro availability. These risks are factored into the comparative evaluation of portolios and the selection of the preferred portolio upon which the action plan is based. Identification of the classes of risk and how these risks are allocated to ratepayers and investors is discussed in Chapter 9. Flexibility in the planing and procurement processes is highlighted in Chapter 9 and the action plan (Table 9.1). PacifiCorp exarnined the trade-off between portolio cost and risk. This trade-off analysis is documented in Chapter 8, and highlighted through the use of scatter-plot graphs showig the relationship between stochastic mean and upper-tail mean stochastic PVR. 4.g An evaluation of the cost-effectiveness of the resource options from the perspectives of the utility and the different classes of ratepayers. In addition, a description of how social concerns might affect cost effectiveness estirnates of resource options. 4.h An evaluation of the financial, competitive, reliability, and operational risks associated with various resource options and how the action plan addresses these risks in the context of both the Business Plan and the 20-year Integrated Resource Plan. The Company wil identify who should bear such risk, the ratepayer or the stockholder. 4.i Considerations permtting flexibility in the planning process so that the Company can take advantage of opportities and can prevent the prematue foreclosure of options. An analysisoftradeoffs; for exarnple, between such conditions of service as reliability and dispatchability and the acquisition of lowest cost resources. 4.j 41 P ACIFICORP - 2011 IRP APPENDIX B - IR REGULATORY COMPLIACE 4.k A range, rather than attempts at precise quantification, of estimated external costs which rnay be intangible, in order to show how explicit consideration of thern might affect selection of resource options. The Company will attempt to quantify the magnitude of the externalities, for example, in terms of the amount of emissions released and dollar estimates of the costs of such externalities. A narrative describing how curent rate design is consistent with the Company's integrted resource planning goals and how changes in rate design might facilitate integrated resource planning objectives. PacifiCorp wil submit its IRP for public comment, review and acknowledgement. 4.1 5 6 The public, state agencies and other interested paries wil have the opportity to make formal comment to the Commission on the adequacy of the Plan. The Commission wil review the Plan for aderence to the principles stated herein, and wil judge the rnerit and applicability of the public comment. If the Plan needs fuer work the Commission wil retu it to the Cornpany with comments and suggestions for change. This process should lead more quickly to the Commission's acknowledgement of an acceptable Integrated Resource Plan. The Cornpany will give an oral presentation of its report to the Commission and all interested public paries. Formal hearngs on the acknowledgement of the Integrated Resource PIan rnight be appropriate but are not required. Acknowledgernent of an acceptable PIan wil not guarantee favorable ratemaking treatment of futue resource acquisitions. The Integrated Resource PIan will be used in rate cases to evaluate the performce of the utilty and to review avoided cost calculations. 7 8 PacifiCorp incorporated environmental externality costs for CO2, NOx, S02, and mercur with use of cost adders and assumptions regarding the form of compliance strategy (for example, a per-ton tax and hard emissions caps for COi). For CO2 externality costs, the cornpany used scenaros with varous cost levels to captue a reasonable rage of cost impacts. These cost assumptions are described in Chapter 7. The role of Class 3 DSM (price response programs) at PacifiCorp and how these resources are modeled in the IR are described in Chapter 6. PacifiCorp distrbuted a parially completed draft IRP document for public review and comment on Febru 23, 2011, and the cornplete drft IRP document (Volume 1) on March 7, 2011. Not addressed; this is a post-fiing activity. Not addressed; this is not a PacifiCorp activity. Not addressed; this refers to a post-fiing activity. 42 PACIFICORP - 2011 IRP APPENDIX B - IR REGULATORY COMPLIACE Table B.5 - Washington Utilities and Transportation Commission IR Standard and Guidelines (WAC 480-100-238) (5) (2)(a) (2)(a) (2)(a) (2)(b) (2)(b) (2)(b) (2)(b) (2)(b) (4)Work plan fied no later than 12 rnonths before next IRP due date. Work plan outlines content ofIR, PacifiCorp fied the IR work plan on March 31,2010, given an anticipated IR fiing date of March 31, 2011. See pages 1-2 of the Work Plan document for a sumaration of IR contents. See pages 2-5 of the Work Plan document for a sumarzation of resource analysis. See pages 6-7 of the Work PIan. Figue 2, page 6, document for the IR schedule. The Commission issued an Order on December 11,2008, under Docket no. UE-070117, granting the Company permssion to file its IRP on March 31 of each odd numbered year. PacifiCorp fied the 2011 IR on March 31, 2011. Not applicable; activity conducted subsequent to filing this IR. Not applicable; activity conducted subsequent to filing this IRP. Chapter 5 describes the mix of existing resources, while Chapter 8 describes the 2011 IR preferred portfolio. For exarnple, see Tables 8.1 6 and 8.17, as well as Fi es 8.11 and 8.1 2. See Chapter 8 for a description of how conservation supplies are represented and modeled. Refer to Tables 8.16 and 8.17, as well as Figues 8.11 and 8.12. The 2010 resource potential study upon which conservation supplies are based is available frorn PacifiCorp's demand-side management Web site, h ://VolWW. cifico .comlesídsm.html. The 2011 IR preferred portolio was based on a resource needs assessment that accounted for forecasted load growt, expirtion of existing power purchase contracts, resources under constrction, contrct, or reflected in the Cornpany's capital budget, as well as a capacity planning reserve margin. Details on PacifiCorp's findigs of resource need are described in Chapter 5. For example, see Table 5.11 for PacifiCo's ca aci 10ad and resource balance. PacifiCorp uses portfolio performance measures based on the Present Value of Revenue Requirernents (PVR) methodology. See the section on ortfolio erformance measures in Cha ter 7. Chapter 6, Resource Options, provides detailed information on costs and other attributes for all resources analyzed for the IRP. For exam Ie, see Tables 6.1 thou h 6.8,6.10, and 6.12. PacifiCorp ernploys Monte Carlo production cost simulation with a stochastic rnodel to characterie market price and gas price volatility. See the section entitled, "Monte Carlo Production Cost Simulation" in Cha ter 7 for a sum of the modelin a roach. PacifiCorp captued demand-side resource uncertainties through the development ofnurnerous portolios based on different sets of input assum tions. PacifiCorp uses two IR rnodels that simulate the dispatch of existing and futue resources based on such attbutes as heat rate, availability, fuel cost, and varable O&M cost. The chronological roduction cost simulation model also inco orates unit (4) (4)Work plan outlines method for assessing potential resources. (See LRC analysis below Work pIan outlines timing and extent of ublic arici ation. Integrated resource plan submitted within two years of previous plan. (5) (4) (5)Commission issues notice of public hearg after company files plan for review. Commission holds public hearng. Plan describes the rnix of energy supply resources. PIan describes conservation supply. Plan addresses supply in terms of curent and futue needs. Plan uses lowest reasonable cost (LRC) analysis to select the mix of resources. LRC analysis considers resource costs. LRC analysis considers rnarket- volatility risks. LRC analysis considers dernand side resource uncertinties. LRC analysis considers resource dispatchability . 43 PACIFICORP - 2011 IRP APPENDIX B - IR REGULTORY COMPLIACE (2)(b) (2)(b) (2)(b) (2)(b) (2)(c) (3)(a) (3)(a) LRC analysis considers resource effect on system operation. LRC analysis considers nsks imposed on ratepayers. LRC analysis considers public policies regardig resource preference adopted by Washington state or federal governent. LRC analysis considers cost of nsks associated with environmental effects including ernissions of carbon dioxide. Plan defines conservation as any reduction in electrc power consumption that results fÌorn increases in the efficiency of energy use, production, or distrbution. PIan includes a range of forecasts of futue demand. Plan develops forecasts using methods that examine the effect of economic forces on the consumption of electrcity. commtment logic for handling start-up, shutdown, rarnp rates, minimum up/down times, and ru up rates, and reserve holding chactenstics of individual enerators. PacifCorp's IR models simulate the operation of its entire systern, reflectig dispatch/unit commitment, forced/unforced outages, access to markets, and system reliability and trnsmission constrints, PacifiCorp explicitly models nsk associated with uncertin CO2 regulatory costs, wholesale electrcity and natual gas pnce escalation and volatility, load growt uncertainty, resource reliability, renewable portfolio stadard requirement uncertinty, plant constrction cost escalation, and resource affordability. These . nsks and uncertainties are handled through stochastic rnodeling and scenanos depicting alternative futues. In addition to nsk rnodeling, the IRP discusses a number of resource nsk topics not addressed in the IRP system simulation rnodels. For example, Chapter 9 covers the following topics: (1) managing carbon nsk for existing plants, (2) managing gas supply risk, and (3) procurement delays. Chapter 4 covers similar nsks associated with trnsmission s stem ex ansion. The IR modeling incorporates resource expansion constraints tied to renewable portolio stadads (RS) curently in place for Washington, Oregon, Califomia, and Utah. (See Chapter 7, "Representation and Modeling of Renewable Portfolio Standads", as well as Appendix A for RPS cornpliance report developed for each resource portfolio assessed for the IR). PacifiCorp also evaluated vanous CO2 reguatory schernes, including a CO2 tax, hard cap, and cap-and-trade. Futue modeling enhancernents are planed for improved representation of state-level resource re lations. Cntena pollutat and CO2 emissions under the Clean Air Act are discussed in Chapter 3. A descnption of PacifiCorp' s rnodeling of CO2 cost nsk is provided in Chapter 7. Chapter 9 discusses the im lications of CO2 cost uncertain on resource ac uisition lans. A descnption of how PacifiCorp classifies and defines energy conservation is provided in Chapter 6, "Demand-side Resources". PacifiCorp irnplernented a load forecast range for both capacity expansion optiization scenanos as well as for stochastic short- term and long-term vanability. Details concerning the 10ad forecasts used in the 2011 IR are provided in Chapters 5 and 8, and Appendix A. Figues 7.4 in Chapter 7 show the range of forecasts used for capacity expansion modeling. Figues 7.18 though 7.24 show the rage of stochastic 10ads modeled for each load area by the Monte Carlo roduction cost sirnulations. PacifiCorp's load forecast methodology employs econornetrc forecasting techniques that include such economic vanables as household income, ernployment, and population. See Chapter 5, "Load Forecast", for a descnption of the load forecasting methodolo . 44 PACIFiCORP-20ll IRP APPENDIX B - IR REGULATORY COMPLIACE (3)(a) (3)(b) (3)(b) (3)(c) (3)(d) (3)(e) (3)(f) (3)(g) (3)(h) Plan develops forecasts using methods that address changes in the number, type and efficiency of electrcal end-uses. PIan includes an assessment of commercially available conservation, including load rnanagement. Plan includes an assessment of curently employed and new policies and prograrns needed to obtain the conservation im rovernents. Plan includes an assessment of a wide range of conventional and commercially available nonconventional generating technologies. PIan includes an assessment of transmission systern capability and reliability (as allowed by curent law). Plan includes a comparative evaluation of energy supply resources (includig transmission and distrbution) and improvements in conservation using LRC. Dernand forecasts and resource evaluations are integrted into the long range plan for resource acquisition. (5) PIan includes a two-year action plan that im lements the Ion ran elan. Plan includes a progress report on the implementation of the previously filed plan. Plan includes description of consultation with commission staff. (Description not re uired Residential sector load forecasts use a statistically-adjusted end-use model that accounts for equipment satution rates and effciency. See Appendix A, Load Forecast Details, for a description of the residential sector 10ad forecastin methodol0 . PacifiCorp updated the system-wide demand-side management potential study in 2010, which served as the basis for developing DSM resource supply cures for resource portfolio modeling. The supply cures account for technical and achievable (market) potential, while the IRP capacity expansion rnodel identifies a cost- effective mi ofDSM resources based on these limits and other model inputs. As noted above, the 2010 DSM potentials study is available on PacifiCo's DSM Web site. A description of the curent status ofDSM programs and on-going activities to implement curent and new programs is provided in Chapter 5, Resource Needs Assessment ("Existing Resources"). PacifiCorp considered a wide range of resources including renewables, cogeneration (combined heat and power), customer standby generation, power purchases, thermal resources, energy storage, and transmission. Chapters 6 and 7 document how PacifiCo develo ed and assessed these technolo ies. PacifiCorp rnodeled transmission system capability to serve its 10ad obligations, factorig in updates to the representation ofmajor 10ad and generation centers, regional transrnission congestion impacts, importexport availability, external rnarket dynarnics, and significant transmission expansion plans (See Chapters 4 and 7). System reliability given transmission capability was analyzed using stochastic production cost sirnulation and measures of insufficient energy and capacity for a load area (Energy Not Served and Unmet Ca aci , res ectivel . PacifiCorp's capacity expansion optimization rnodel (System Optimizer) is designed to compare alternative resources-including trnsmission expansion options-for the least-cost resource mix. System Optimizer was used to develop numerous resource portfolios for comparative evaluation on the basis of cost, risk, reliability, and other performance attbutes. The DSM potentials study considered improvements in conservation Distrbution considered alternative transmission ex ansion 0 tions. PacifiCorp integrates demand forecasts, resources, and system operations in the context of a systern modeling framework described in Chapter 7. Portfolio evaluation covers a 20-year period (2011- 2030). PacifiCorp developed its preferred portolio of resources judged to be least-cost after considerig 10ad requirernents, risk, uncertinty, supply adequacy/reliability, and governent resource olicies in accordance with this rule. See Table 9.1, Chapter 9, for PacifiCorp's 2011 IRP action plan. A status report on action pIan irnplernentation is provided in the "Progress on Previous Action PIan Items" section of Chapter 9. Chapter 2 includes a sumar of the 2011 IR public process, while Appendix F provides details on specific meetings held. 45 P ACIFICORP - 2011 IRP APPENDIX B - IR REGULATORY COMPLIACE Plan includes description of completion of work pIan. (Description not requied) Not applicable; the IR schedule was modified to accommodate planng events. See the response to WAC 480-100-238(4). Table B.6 - Wyoming Public Service Commission IR Standard and Guidelines (Docket 90000- L07-XO-09) A The public comment process employed as par of the formulation of the utility's IR, including a description, timing and weight given to the public process; The utility's strategic goals and resource planning goals and preferred resource portfolioB C The utility's ilustration of resource need over the near-term and long-term planning horizons; PacifiCorp's public process is described in Chapter 2. A record of public meetings is provided as Appendix F. Chapters 9 and 10 presents the 2011 IRP and transmission expansion action plans, respectively. Chapter 8 presents the preferred portfolio. Additionally, the acquisition path anlysis (Table 9.2) describes alternative resource strtegies based on trgger events and trends. See Chapter 5, Resource Need Assessrnent. D A study detailing the tyes of resources considered; Chapter 6, Resource Options, presents the resource options used for resource portfolio rnodeling for this IRP. F Changes in expected resource acquisitions and load growt from that presented in the utility's previous IR; G The environmental impacts considered; H Market purchases evaluation; H Reserve Margin analysis; and I Demand-side management and conservation options; A comparison of resource changes relative to the 2008 IRP Update is presented as Table 9.3 in Chapter 9. A chart comparg the pea load forecasts for the 2008 IRP, 2008 IR Update, and 2011 IR is included in Appendix A. Tables and grphs showig CO2 and EPA criteria pollutat emissions are presented in Chapter 8 and Appendix E. Modeling offi maket purchases (front offce transactions) and spot market balancing trnsactions is included in this IR. PacifiCorp's stochastic loss ofload study and selection ofa capacity planning reserve magin is included as Appendix 1. See Chapter 6 for a detailed discussion on DSM and conservation resource options. 46 PACIFICORP - 2011 IRP APPENDIX C - ENERGY GATEWAY SCENARO PORTFOLIOS ApPENDIX C - ENERGY GATEWAY SCENARIO PORTFOLIOS This appendix provides additional modeling inputs and results for the Energy Gateway transmission scenarios documented in Chapter 4 of Volume 1. The appendix consists of detailed transmission cost information incorporated into System Optimizer and portfolio Present Value Revenue Requirements (PVR) reporting, as well as resource tables indicatig resource differences between the base Energy Gateway portfolio (developed assuming only the Energy Gateway Central segments are built) and portfolios developed with incremental Energy Gateway segments, The Transmission Scenario Analysis section of Chapter 4, Transmission Planning, assesses resource additions and 20-year present value revenue requirement (PVRR) for various Energy Gateway scenarios. These scenarios range from a "base case" strategy with the minimal planned transmission (Scenario 1 ~ including the Populus to Terminal, Mona to Oquirh, and Sigud to Red Butte projects) to the full "incremental" Energy Gateway strategy (Scenario 7 - including Gateway Central, Gateway West, Gateway South and west-side projects). The PVRR calculations are for 20-years discounted back to 2011 dollars assuming a 7.17 percent discount rate in order to be consistent with other IRP analyses. However, a full financial analysis would assume a 58-year lifecycle and include stochastic analysis through the Planning and Risk (PaR) model as described in Chapter 7. The System Optimizer's selection of wind resources for the "Green Resource Futue" used various Energy Gateway scenarios as input assumptions and then determined general placement of additional wind resources. Wind resource requirements were assumed at the Waxman-Markey level (20 percent by 2020). The System Optimizer acts as a screening tool for resource selection but has limited abilty to take into account transmission constraints and/or operational requirements. This limitation requires Transmission Planning, in some cases, to choose between planning adequate transmission facilities appropriate for the resource location, moving wind resources to alternative renewable energy zones, or both. PacifiCorp's Transmission Planning Departent did not pre-determine the entie transmission infrastructue/cost for each scenaro, other than providing the Energy Gateway scenarios as tested using System Optimizer. However, The Transmission Planing Departent determined whether the wind resources selected by the System Optimizer had adequate location-based transmission facilities and, in one scenario, relocated wind resources in consideration of transmission constraints and operational considerations. Placement and megawatt capacity of wind resources in scenarios 1, 3 and 7 selected by the System Optimizer were left as is; however, resource-location-dependent transmission was added to accommodate the incremental resources. In scenario 2, The Transmission Planning Departent determined that some of the resources selected for Wyoming had to be relocated to Uta due to transmission constraints and operational limits. 47 PACIFICORP - 2011 IRP APPENDIX C - ENERGY GA TEW A Y SCENARIO PORTFOLIOS West-side wind resource additions under the "Green Resource Futue" (see Table 4.1) for Scenaro 1 range between 871 MW and 1,021 MW of new wind generation primarly in Washington. Figue C.L, the Western Renewable Energy Zones map, shows "bubbles" in Washington and Oregon where wind resources are strongest, plus the Energy Gateway Scenario 1 map which shows PacifiCorp's service area in blue. Figure C.L- Western Renewable Energy Zones plus Energy Gateway Scenario 1 Wf ~iwWl!' ÀiÆ¿i Energ Gateway Transmission Expansion Plan System Optimizer Scenario I l.HypnlM1-10 10.100 ""100,,50-..:5-__I8.10 .10~100 .. 100.50 A.50---..-MIWi~""-_-_1tnD3_-MisMI.Ml7SO1l~ON(l-_rl 86.5"6.75Hlt1S??_7.1.25_1.25.7.5 Ml7.5 Source: Western Renewable Energy Zones - Phase 1 Report (http.;lwww.westaov.orqJrtp/219) 48 PACIFICORP - 2011 IRP APPENDIX C - ENERGY GATEWAY SCENARIO PORTFOLIOS Tables C.1 and C.2 outline the line item details for the transmission costs presented in Tables 4.2 and 4.4 of Chapter 4. Given that Scenario 1 includes no incremental transmission capacity on the west side and lacked available capacity in this region, new transmission additions would be required to bring up to 1,021 MW of west-side wind generation to customer load centers in Oregon, Washington and California. PacifiCorp estimated that $1.5 bilion (20- Year PVRR) in new west-side transmission investment would be required to deliver this energy to customers under the Green Resource Scenario. 2 2 See the west side line items in Table C.l. 49 P ACIFICORP - 2011 IRP APPENIX C - ENERGY GATEWAY SCENARO PORTFOLIOS Table C.i - Transmission Cost Details, Green Resource Future $1.118 $920 $945 $1,118 $920 $945 $738 295 295 295 295 295 295 295 9 9 9 9 9 9 9 0 657 657 0 657 657 657 0 0 477 0 0 477 307 0 0 0 0 0 0 270 0 0 0 0 0 0 207 ndet Transsio 142 107 ios 45 142 107 105 45 0 475 0 0 0 475 0 0 1,503 0 0 0 1,503 0 0 0 Wheeli Char e Soutwest UT - Mea NY 35 35 35 36 35 35 35 35 Total (20-year PVR) 'i $3,103 $2,499 $2,524 $2,564 $3,103 $2,499 $2,524 $2,563 $1,776 $3,329 $460 $5,888 $1,776 $3,329 $4.60 $5,888 ndnt Transmisio: $1,118 $920 $945 $738 $1,118 $920 $945 $738 295 295 295 295 295 295 295 295 9 9 9 9 9 9 9 9 0 657 657 657 0 657 657 657 0 0 477 307 0 0 477 307 0 0 0 270 0 0 0 270 0 0 0 207 0 0 0 207 ndent Transmisio 142 107 105 45 142 107 105 45 0 475 0 0 0 475 0 0 1,503 0 0 0 1,53 0 0 0 Soutest UT - Me NY 35 35 35 35 36 36 36 36 Total (20-year PVRR) 11 $3,103 $2,499 $2,524 $2,563 $3,104 $2,500 $2,525 $2,564 $1,776 $3,329 $4,60 $5,888 $1,776 $3,329 $4,60 $5.888 ndent Transmision: 337 253 248 I 337 253 248 107 0 1,124 0 0 0 1,124 0 0 2,802 0 0 0 2,802 0 0 0 $4,915 $4,706 $4,857 $5,995 $4,915 $4,706 $4,857 $5,995 If Westside ResolDce Loation Dependent Transsio assind to be in-serve the begig of year 2016.11 Transmision deprciable assets have a 58-year bok lie, however the present vahi revenue requment were hased on 20-years of fu trnssio costs usin a 7.17"10 dicoi rate in order to be conistent wi 1RP date parameters. 31 Gross capitl estites came frm standard trnsmision base assemblis priced in 200 except for the Pop - Terml segmnt where 2010 forecaste completi costs wer used 50 P ACIFICORP - 2011 IRP APPENDIX C - ENERGY GA TEWA Y SCENARO PORTFOLIOS Table C.2 - Transmission Cost Details, Incumbent Resource Future $1,118 $920 $945 $738 $1,118 $920 $945 $738 295 295 295 295 295 295 295 295 9 9 9 9 9 9 9 9 0 657 657 657 0 657 657 657 0 0 477 307 0 0 477 307 0 0 0 270 0 0 0 270 0 0 0 207 0 0 0 207 ndet Transmisio 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wheeli Char e Sontwes UT-Mea NY 35 35 35 35 35 35 35 35 Tota (20-year PVR) 11 $1,458 $1,916 $2,419 $2,518 $1,457 $1,916 $2,419 $2,518 $1,776 $3,329 $4,60 $5,888 $1,776 $3,329 $4,60 $5.888 ndent Transmisio: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 $1,776 $3,329 $4,609 $5,888 $1,776 $3,329 $4,609 $5,888 $1,118 $920 $945 $738 $1,118 $920 $945 $738 295 295 295 295 295 295 295 295 9 9 9 9 9 9 9 9 0 657 657 657 0 657 657 657 0 0 477 307 0 0 477 307 0 0 0 270 0 0 0 270 0 0 0 207 0 0 0 207 ndnt Transmisio 0 0 0 0 142 107 105 45 0 0 0 0 475 0 0 0 0 0 0 0 0 0 0 Wheeli Char e 35 35 35 35 36 36 36 36 Tota (20-year PVR) 11 $1,458 $1,916 $2,419 $2,518 $1,600 $2,499 $2,525 $2,564 $1,776 $3,329 $4.60 $5,888 $1.776 $3,329 $4,609 $5,888 ndent Transmisio: 0 0 0 0 337 254 248 107 0 0 0 0 1,123 0 0 0 0 0 0 0 0 0 0 $1,776 $3,329 $4,609 $5,888 $2,113 $4,706 $4,857 $5,995 11 Transmisio depreciable assets have a 58-year bok lie. however thc present valn revenne requiements were based on 20-years of fu transmisio costs usin a 7.17% dicou rate in order to be conistent wit IRP date pa1Ìinters.2! Gross capil estites came from standard trnsmisio base assemblis prced in 200 except for the Poplu - Tennl segmnt where 2010 forcasted comletin costs were used. 51 PACIFICORP - 2011 IRP APPENIX C - ENERGY GATEWAY SCENARO PORTFOLIOS This section presents System Optimizer portfolio output tables for the Energy Gateway transmission scenaros discussed in Chapter 4, Transmission Planing. Table C.3 sumarizes the input assumptions used for developing each Energy Gateway portfolio. Table C.4 reports the portfolio PVRRs, indicating post-model-ru adjustments for transmission costs and reversal of the stochastic value adjustment applied to CCCT resources. (See Chapter 7 for a discussion of this adjustment). Table C.5 consists of the resource capacity difference tables. The base Energy Gateway scenario is shown first, followed by the resource difference tables for scenarios with the matching input assumptions. For example, resource differences for scenarios EG2, EG3, and EG4 are shown with respect to EG 1. 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S - E n e r g y G a t e w a y S c e n a r i o P o r t f o l i o R e s u l t s En e r g y G a t e w a y C a s e 1 53 1,2 2 2 Bl u R 3 35 . 45 80 80 Iõ h e n i G r e n f i e k l 35 35 Wi n d , W v o , 3 5 % C a o o c i t v F a c t o r 2 0 2 'o t a l W i n 2 0 2 CH P . Bi o m s s 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 50 10 0 CH P - R e c i D o c a £ Î n a E n l l e I I I 2 2 DS M , C l a s s t , U t a h - C o o l k e n e r 5.5 5. 0 11 II DS M C l a s s 1 G o h e n . D L C . l r r t k 19 . 8 0.9 4. 0 20 25 DS M . C l a s s 1 U t a h . C o n n d . T h n n E n e , " S i o 3.5 3 3 DS M . C l a s s i U t a h - C u r i h n t 21 . 21 21 DS M , C l a s s i , U t a h - O l e - R e s i d n t i a l 21 . 0 10 . 7 32 32 DS M , C l a s s i T o t a l 26 . 5 40 . 6 19 . 8 0.9 4. 0 87 92 DS M . C l a s s 2 I d a l m 2.0 2.5 2.2 2.8 3.4 3. 9 4.2 4. 4 4.3 4.6 4.7 4.8 5.7 6.1 6. 5 6.1 6.5 6.1 6.1 5.6 34 92 DS M . C l a s s 2 U t a h 83 . 9 92 . 1 93 . 9 40 . 1 41 . 4 43 . 9 45 . 1 46 . 1 47 . 8 50 . 1 51 . 4 54 . 9 51 . 53 . 1 53 . 0 57 . 4 52 . 0 54 . 6 53 . 8 56 . 2 58 4 1.1 2 2 DS M , C l a s s 2 W v m Í I 3.6 4.6 4.8 5.5 5.6 6.3 6.9 8. 7 8.7 9.3 10 . 9 11 . 5 13 . 3 16 . 3 17 . 4 22 . 5 23 . 9 28 . 1 35 . 0 37 . 2 64 28 0 DS M C l a s s 2 T o t l 89 . 6 99 . 2 10 0 . 9 48 . 4 50 . 3 54 . 1 56 . 2 59 . 1 60 . 8 64 . 0 66 . 9 71 . 1 70 . 3 75 . 6 76 . 8 86 . 0 82 . 4 88 . 8 94 . 9 99 . 1 68 3 1,4 9 4 ic r o S o l a r - W a t e r H e a t e r 3 3 3 3 3 3 3 3 3 2 2 24 28 ic r o S o l a r - P h o t o v o l l i c 1 51 1 54 54 16 8 26 4 25 4 99 78 5 78 5 15 4 20 0 20 0 20 0 78 17 4 87 -. 1. 0 9 2 1.0 9 2 15 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 25 13 4 23 8 29 0 30 0 30 0 30 0 30 0 30 0 30 22 5 23 7 2 37 65 69 10 5 17 3 83 17 14 3 15 1 N/ A 10 0 19 27 28 2 34 3 32 8 N/ A 10 0 17 59 10 0 36 25 9 27 3 25 2 N/ A 10 0 70 Î t . t - 12 12 70 70 eit F a c t o T - T . Î - t - T - i 11 4 41 56 II 4 41 56 4 4 4 4 4 4 4 4 4 4 4 4 4 42 84 DS M C l a s s i C a l i o m . D L C . l r r i s t D n 5. 5 5 5 DS M . C l a s s i O r e v o - C u r i h n t 17 . 2 17 17 DS M . C l a s s i O r e D ' o n - D L C - l n i t i i 0.5 12 . 7 13 13 DS M . C l a s s i , O r e 2 O - D L C . R e s i d n t i a l 3. 6 6.5 10 10 DS M . C l a s s 1 W a s h " o t . . D L C . 1 m . a t i 3.8 4. 7 9 9 DS M , C l a s s 1 W a s l i o o . D L C . R e s i d n t i a t 4. 8 5 5 DS M , C l a s s i T o t l 4.3 48 . 4 6.5 59 59 DS M . C l a s s 2 C a l i o r 0.6 0. 8 0.8 1. 1. 1.4 1. 5 1.5 1.4 1.6 1. 6 1.6 2. 0 2.1 2. 2 2. 0 2.0 1. 9 1.9 1.9 12 31 DS M . C l a s s 2 O r e . o n 52 . 6 52 . 8 56 . 0 60 . 7 61 . 7 60 . 8 60 . 3 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 44 . 0 36 . 1 36 . 1 36 . 1 56 2 1,0 2 8 DS M . C l a s s 2 , W a s h m o t ~ 10 . 0 12 . 5 8.2 8.0 8.4 8. 2 8.5 8.8 9.3 9.5 10 . 0 10 . 9 10 . 9 11 . 4 11 . 8 9. 3 8.1 8.5 8.6 8. 9 91 19 0 DS M , C l a s s 2 T o t l 63 . 2 66 . 1 65 . 0 69 . 8 71 . 4 70 . 4 70 . 3 62 . 7 63 . 1 63 . 4 63 . 9 64 . 9 65 . 3 65 . 9 66 . 3 63 . 7 54 . 1 46 . 4 46 . 5 46 . 9 66 5 1, 2 4 9 R S o l a r C a D S t a n d d 2 2 2 3 9 9 So l a r Pi l 4 2 2 1 10 10 fO S o l a r - W a t e r H e a t e r 2 2 2 2 2 2 2 2 2 1 1 1 I 1 16 21 CO B 3 r d O l r I l L H 15 0 15 0 15 0 15 0 50 65 33 Mid C o h i i a 3 r d O t t H L H 40 0 40 0 40 0 40 0 39 3 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 35 9 38 0 Mi d o l u i a 3 r d O t t H L H 1 0 % P r r e P r e m i 19 3 14 7 34 17 So u C e n t r l O r e i m n I o r e m C a L 3 r d O t r H L H 26 50 36 50 50 50 26 13 .w t R e s o u c e W a U a W a l l . . 4 65 20 5 17 N/ A 44 .w t h R e s o u c e O R I C A . . 12 5 N/A 12 Ya k i . . 77 61 26 16 9 14 9 17 5 52 17 7 14 6 N/A 10 3 ll ' , ' ~ " " ~ ~. N " ~ ~ '~ ' , : 1 & ' $ ~ ~,' ~ ' b ' 1 ' ~ .. F o r t h e 2 0 Y e a r c o l u m n H G r o w i h S t a t i o n s " a r e a n 1 0 y e a r av e r a g e r e f l e c t i n g t h e a v a i l a b l e ye a r s fr o m 2 0 2 1 . 2 0 3 0 . 56 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 2 c o m p a r e d t o E n e r g y G a t e w a y C a s e 1 Re s o u r e d i f r e n c e s f r o m b a e t r n s m i i o n s c e n a r i a r e s h o w n . P V R d i f r e n c e i n d r a t e a s a n i n r e a s e o r ( d e r e a s e ) . 0. 2 T . T . T . T u 0 0.2 l . 0 0 . 1 (2 ) (2 4) å 0\1 01 1 0 0 1 I 6 10 17 (2 ) _ (1 3 6 4 40 (2 7 18 0 26 39 II (4 6 ) (8 N/A (0 ) 12 ) (4 5 ) (3 8 ) 87 13 28 (2 7 ) N/A (0 ) (l l (4 ) (4 1 ) (5 6 ) (l l (4 ) 41 (5 6 .s 0 .. (0 ) ii - T - T mr - T . T - 5)' tr H L H 1 I 1 1 1 I 1 (0 ) 1 :. J . Î . Î . Î . Î . T - i . 1 0) (0 ) , 40 1 . 1 28 N/A 7 (1 2 ~ 6 57 PA C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 3 c o m p a r e d t o E n e r g y G a t e w a y C a s e 1 Re s o u r d i f r e n c e s f r m b a t r I l m i i o n s c e n a r i a r e s h o w n P V R d i f r e n c i n i c a t e a s a n i n r e a s e o r ( d e c r e a s ) . 0. 2 T . ì - T . T - ì 0 0 0. 2 . - . . - . . . . 1 0 0 (2 2 1 (2 ) 4 0 0 1 6 io 17 J! 3 ) 6 4 40 27 8 -- 26 39 IL L 51 13 -- 12 ) (4 5 ) 38 87 13 33 (3 2 ) .. Fa c t o r .. - i - 1 - . . . i . i - . . - . . - i - 1 . . . . i - 1 . I Il l ) . ( 4 ) (4 1 (5 6 ) 11 (4 ) El (5 6 ) ..E 10 E 10 15 ) 'u l l L I I I I I I I I i (0 ) 1 I I I I I I I I =- 1 - - i . i .1 (0 ) .J 7 IT6 . F o r t h e 2 0 Y e a r c o l u m n " G r o w t h S t a t i o n s " a r e a n 1 0 y e a r a v e r a g e r e f l e c t i n g t h e a v a i l a b l e y e a r s / r o m 2 0 2 1 - 2 0 3 0 . 58 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 4 c o m p a r e d t o E n e r g y Ga t e w a y C a s e 1 Re s o u r e d i f r e c e s f r o m b a s e t r n s m i i o n s c e n a r i a r e s h o w n . P V R d i f n c e i n i c a t e d a s a n i n r e a s e o r ( d e c r e a s e ) . etv F a c t o I 1 I 1 1 1 1 1 L ' 1 . I "j 01 , 4 34 74 .. 74 ,e T j j j 12 (2 ) 1 19 . 8 11 9 . 8 0.9 0.9 10 8" ' ~ (3 . 5 13 (3 ) (1 9 . 5 ) 19 . 5 4.9 5 5 21 . 0 (1 0 . 7 25 . 7 1 1 . 5 5 5.4 1.4 7 7 (2 1 . 0 ) (2 8 . 2 19 . 5 19 . 8 (1 9 . 8 ) 32 . 0 11 . (0 . 9 ) 0.9 14 14 (0 . 5 ) (0 . 7 (0 . 2 ) (1 ) (1 -¡ 4 D . (4 5 . 5 ) 54 . 9 1.9 2. 0 2.1 3.4 13 2 11 3 2 (0 . 2 ) (0 . 2 ) 0. 3 0. 6 0.7 0.8 1.0 0.2 3 3 (4 1 . ) (4 6 . 4 (5 4 . 8 ) 0. 6 0.7 0.8 2.9 2. 0 2.1 3.6 (1 3 0 ) (1 3 0 0 2 2 0 (2 ) 3 51 (I 54 54 10 19 9 62 ,. 27 27 96 1 50 50 63 (2 0 0 ) 62 12 2 11 4 11 3 18 3 18 3 27 5 16 6 62 10 51 3 -i 2 ) 7 56 10 2 4 57 0 48 (2 6 (3 0 0 2 (2 7 9 10 6 N/A 0 51 16 13 6 93 15 9 65 N/A -¡ ò Wi n Y a k i m , 2 9 % C a " " c ì f F a c t o .T . ì ' ì . ì 11 ) (4 ) (4 1 ) (5 6 ) .o t a i W i n .- 1 ' I ' J ' I ' . l . . . (1 1 ) (4 ) (4 1 ) (5 6 1 1 DS M C l a s s 1 C a l i o m i - D L C - I r r a a t i 5. 5 (5 . 5 ) : DS M C l a s s 1 O r e a o o - C u r i l n t 17 . 2 (1 . 2 ' DS M C l a s s t , O r e ~ - D L C - I r r a t i o 13 . 2 0.5 (1 2 . 7 ) DS M , C l a s s 1 O r e l ' o n - D L C - R e s i d n t i a l 3. 6 3. 6 (6 . 5 ) 1 0.3 DS M C l a s s 1 , W a s h i n 2 t o n - D L C - I r r i r t i 2.1 3.8 6.4 4. 7 DS M . C l a s s 1 , W a s h i a t o n - D L C - R e s i d n t i l 0. 7 4.1 (4 . 8 ) DS M . C l a s s i T o t l 42 . 2 (4 . 3 ) 10 . 5 (4 8 . 4 ) (6 . 5 0.3 (( ) (6 ) 1 DS M . C l a s s 2 C a l i o r 0.1 0.2 0.2 0.2 0 0 DS M , C l a s s 2 , W a s h i n l r o n 0.1 0.1 0. 4 0.1 0. 3 0.1 1 1 10 8 M C l a s s 2 T o t l 0.2 0.1 0. 4 0.1 0. 3 0.2 0.3 (0 . 2 ) 1 1 Mi r o S o l a r . W a t e r H e a t e r 1 1 FO T M i d o l i i a 3 r d O t t H L H 59 7 29 18 4 8 (8 lfT M i d o l w n b i a 3 r d O t r H L H 1 0 0 1 0 P r i c e P r e m i 51 60 11 6 So u t h C e n t l O r e J R o r e r n C a l 3 r d 0 t r H L H 50 50 24 50 50 14 50 ) 9 4 ~1 I ' '- 20 5 11 3 (0 ) 13 19 5 16 N/ A 54 18(J 59 P A C I F I C O R P - 2 0 1 1 I R P En e r g y G a t e w a y C a s e 5 Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S 35 - I - I 45 35 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 50 10 0 ati n ø E n a i n T i I I 2 2 5.5 5.0 II II 19 . 8 4.9 20 25 St o - - 3.5 3 3 21 . 5 3.2 1. 6 26 26 31 . 7 5.4 37 37 5.4 1. 4 7 7 5.5 61 . 6 28 . 4 8.4 4.9 10 4 10 9 2.0 2.5 2.5 3. 0 3.7 4.4 4.7 4.9 5. 0 5.4 5.2 5. 6 6.7 7.3 7. 6 7.2 7.7 7. 6 7.6 7.1 38 10 8 83 . 9 92 . 1 10 1 . 44 . 0 64 . 3 67 . 2 66 . 5 50 . 6 61 . 69 . 5 55 . 5 59 . 6 57 . 8 60 . 1 60 . 2 63 . 5 57 . 2 60 . 1 59 . 3 62 . 1 70 1 1,2 9 6 3.9 5.0 5.3 6. 2 6. 3 7.3 8.1 8. 9 9. 0 9.7 1i . 11 . 8 13 . 7 16 . 8 17 . 9 23 . 5 25 . 0 29 . 5 36 . 7 39 . 9 70 29 5 89 . 8 99 . 6 10 9 . 0 53 . 2 74 . 3 78 . 9 79 . 3 64 . 5 75 . 2 84 . 6 71 . 8 77 0 78 . 2 84 . 2 85 . 7 94 . 1 89 . 9 97 . 2 10 3 . 6 10 9 . 1 80 8 1,6 9 9 3 3 3 3 3 3 3 3 3 3 3 3 3 3 0 24 37 51 I 54 54 16 8 26 4 21 4 99 99 84 5 84 5 17 5 - L 20 0 20 0 63 17 6 20 0 20 0 1,2 1 3 1,2 1 3 15 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 22 5 26 3 15 6 17 28 89 10 7 11 4 14 0 21 1 27 4 N/ A 10 0 10 9 18 7 20 5 24 3 25 6 N/ A 10 0 45 52 36 92 20 7 20 4 17 4 18 8 N/ A 10 0 12 12 70 35 70 70 70 70 31 5 38 5 10 0 I - I 10 0 10 0 10 0 1 . . 1 . . . 1 10 0 10 0 50 50 50 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 42 84 DS M C l a s i C a l i o m . D L C - I r i m t i o 5. 5 5 5 DS M C l a s s i O r e l l o . C u r i h n t 17 . 2 17 17 DS M C l a s s i O r e i m n - D L C - I r r i i m t i 13 . 2 13 13 DS M C l a s 1 O r e i w n - D L C - R e s m n t i l 3. 6 6.8 10 10 DS M C l a 1 W a s b i o o - D L C - I n i t m 8. 5 9 9 DS M C l a s 1 W a s h i n m o - D L C - R e s i l n t i l 4. 8 5 5 Io S M C h s s i T o t l 52 . 8 6.8 60 60 DS M . C l a s 2 . C a l i o r 0. 7 0.8 0.9 1.2 1. 1. 6 1. 7 1.7 1.7 1.8 1. 8 1.9 2. 2 2.4 2.6 2. 3 2.4 2.2 2. 2 2.3 14 36 DS M . C l a s 2 Q r e i r 52 . 6 52 . 8 56 . 0 60 . 7 61 . 7 60 . 8 60 . 3 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 44 . 0 36 . 1 36 . 1 36 . 1 56 2 1, 0 2 8 DS M . C l a s 2 . W a s _ 12 . 0 12 . 6 9.0 8. 8 8. 9 8.7 8.9 9.2 9. 4 9.6 10 . 8 11 . 8 11 . 5 12 . 1 12 . 4 9.6 8.3 8.7 8. 6 9.2 97 20 0 8M C h s s 2 T o t l 65 . 3 66 . 2 65 . 9 70 . 8 72 . 1 71 . 70 . 9 63 . 3 63 . 4 63 . 8 65 . 0 66 . 1 66 . 1 66 . 8 67 . 3 64 . 3 54 . 7 46 . 9 46 . 9 47 . 5 67 3 1, 2 6 4 R S o l a C a n S t a n d r d 2 2 2 3 9 9 QR So l a Pil 4 2 2 1 10 10 '0 S o l a r . W a t e r H e a t e r 2 2 2 2 2 2 2 2 2 2 2 I I I 16 23 15 0 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 40 0 40 0 40 0 36 5 39 5 40 0 71 38 5 40 0 40 0 40 0 40 0 40 0 40 0 40 40 0 35 6 36 1 14 3 90 23 12 50 50 50 50 50 50 50 35 18 27 19 6 43 18 N/ A 28 N/ A 7 N/ A 20 0 60 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 6 c o m p a r e d t o E n e r g y G a t e w a y C a s e 5 Re s o u r e d i f r e n c e s f r m b a s e t r n s m i i o n s c e n a r i o a r e s h o w n P V R d i f r e i x e i n d k : a t e d a s a n i n r e a s e o r ( d e c r e a s e ) . pa c i l y F a c t o r -'" 1- - . 1 .1 - 1 - . . 1 0. 1 0.2 0.2 (0 1 18 . 9 09 . 0 0.5 (2 . 0 38 40 0.1 0.1 0.1 0. 1 (0 . 1 ) 0. 3 0. 3 (0 . 1 ) 0. 8 0 2 (1 8 . 9 ) (1 9 . 1 0.1 0.1 0.4 ) 0. 1 (0 . 2 ) (2 . 1 0. 3 0. 3 (0 . 2 0.1 ) 0. 8 (3 8 (3 9 ) 0) (0 ) (0 (0 (0 ) 15 1 01 I I I -I . T . T 15 15 (8 1 1 23 1 - 31 39 11 9 C7 (3 4 2 69 (9 1 -- (0 ) 34 (1 8 7 ) 55 37 61 ~ 14 6 (9 2 98 (4 4 14 48 N/ A 35 1 I I I I I I 70 (7 0 \ 35 1 35 0. 1 1 0. 1 1 I (0 ) 0 (7 1 ) (1 0 3 ) (5 8 ) 0 (1 2 ) .Q ~I N/A I (9 22(i 61 P A C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y Ca s e 7 c o m p a r e d t o E n e r g y G a t e w a y C a s e 5 Re s o u r e d i f r e e s f r m b a s e t r n s m i i o n s c e n a r i a r e s h o w n P V R d i f e i n a t e d a s a n i n r e a s e o r ( d e c r a s e ) . (0 . 1 ) (0 . 2 ) 0.2 (0 ) (1 18 . 9 19 . 0 0.5 2.0 38 40 0.1 0. 1 0.1 0.1 (0 . 1 0.3 0. 3 (0 . 1 0. 8 0 2 (1 8 . 9 ) (1 9 . 1 ) 0.1 0. 1 0.4 0.1 (0 . 2 ) (2 . 1 ) 0.3 0. 3 0.2 0.1 0. 8 (3 8 ) 39 ) 1 0 0 0 (0 ) (0 ) 0 .1 5 0 15 i5 23 31 39 11 9 12 ) 34 2 69 91 0 34 18 7 37 24 92 N/ A 0) (I ) (6 ) (1 4 ) (6 92 10 2 26 26 17 N/ A (0 ) !l ! l ~ 35 70 (7 0 ) 35 35 0.1 0.0 0.1 0.2 0.1 0.1 0. 1 0.3 0 I 0.1 0.0 0.1 0.2 0.1 0.1 0. 1 0.3 0 I I I 71 10 3 58 0 12 (0 ) (0 ) 0 43 ) (8 ) N/A 9 N/A 22 N/A (1 ) ' '" F o r t h e 2 0 Y e a r c o l u m n " G r o w t h S t a t i o n s " a r e a n / 0 y e a r a v e r a g e r e f l e c t i n g t h e a v a i l a b l e y e a r s fr o m 2 0 2 / - 2 0 3 0 . 62 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 8 c o m p a r e d t o E n e r g y G a t e w a y C a s e 5 Re s o u r c e d i f r e e s f r o m b a s e t r n s m i i o n s c e n a r i o a r e s h o w n . P V R d i f r e n c e i n i c a t e d a s a n i n c r e a s e o r ( d e c r e a s e ) . 19 . 8 (1 9 . 8 ) Sl o 3.5 1.6 1.6 6. 6 6.6 5. 4 5. 4 0) 5.4 (5 . 4 ) (1 . 4 ) 1.4 6. 6 (4 . 7 19 . 8 25 . 2 ) 8. 4 11 . 9 0 (0 . 5 0.6 0.4 (0 . 1 ) 0.1 ) 0. 1 0.2 0.2 (1 ) 2 38 . 1 ) 42 . 7 57 . 5 17 . 7 19 . 0 3.4 15 . 5 5. 7 2.0 (1 5 7 ) 15 9 ) (0 . 1 ) 0.2 ) (0 . 1 ) (0 . 0 ) 0.1 0.3 0. 2 0.1 (0 . 1 ) 0.3 0.3 (0 . 1 ) (0 . 2 ) 0 1 (3 8 . 6 43 . 5 58 . 0 17 . 7 19 . 1 3.4 15 . 9 6. 0 0.1 0.2 2. 1 0.3 0.3 0. 2 0.1 0.2 15 8 16 1 0 0 0 (1 51 1 (5 4 54 50 99 49 49 ) ' 25 (7 ) 13 7 17 6 20 0 22 1 22 1 34 44 58 65 47 53 (3 4 7 10 5 15 5 0 35 18 7 15 61 76 N/ A 0 36 13 16 3 26 27 99 N/ A 0 (3 5 ) 1 I 70 I I ot h e r m ~ G r e e n f i e l d I I I I I I I 70 (7 0 ) 35 35 'o t a l W i n CA P - R e c i D o c a t i i i i E n i r e 0 0 --- - - - DS M C l a s s 1 C a l i o r n - D L C - I r r i i m f u 5.5 5. 5 DS M C l a s s I , O r e o o n - C w t i h n t 17 . 2 17 . 2 DS M , C l a s s i , O r e g o n - D L C - I r r Î l t i o 13 . 2 13 . 2 DS M . C l a s s i O r e o o o - D L C - R e s i d n t i a l 10 . 3 3. 6 ) 1 I (6 . 8 DS M C l a s s i W a s h i n n t o n ~ D L C - I r r - t i o 2.1 4. 8 6. 9 DS M . C l a s s i W a s h i r u i t o n - D L C - R e s I d n t i a l 1.2 (1 . 2 ,8 M C l a s s 1 T o t l 49 . 5 4.8 14 7 . 6 6.8 t- - 0 0 DS M C l a s s 2 C a l i o r n i a 0. 1 0.1 0. 0 0. 0 0.2 0. 2 0. 2 0.1 0. 1 0.1 0.3 1 1 DS M , C l a s s 2 W a s h . , a t o n 0.1 0.1 0 0 '8 M . C b s s 2 T o t a l 0. 1 0.2 0. 0 0. 0 0.2 0. 2 0. 2 0.1 0. 1 0.1 0.3 1 2 o S o l a r - W a t e r H e a t e r 1 1 Mid C o h i b i a 3 r d O t t H L H 62 14 6 35 5 71 10 6 43 7) 14 Mi d C o h i b i a 3 r d O t r l I L H 1 0 " 1 0 P e k e P r e 10 2 11 1 21 11 So u t h C e n t r a l O r e o o n I o r e m C a L 3 r d ( ) t r H L H (5 0 15 39 0 0 'a D a W a l l ' " .. (2 7 ) (2 4 ) 14 3 18 N/ A (1 1 ) RI C A ' " 21 9 N/ A 22 ak i ' " 39 10 7 (6 ) (2 8 ) (5 9 ) (7 7 ) 24 (4 3 ) 43 N/ A (0 ) 1 63 P A C I F I C O R P - 2 0 1 1 I R P AP P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 9 28 0 53 62 5 . 1 59 7 1.2 2 2 1.2 2 2 35 45 80 80 35 35 Wn d U t a h 2 9 ' % C a o c I l F a c t o r 4 4 Wi l W v 0 . 3 5 % C a o a c i t F a c t o 2 0 2 IT . . I W i n d 2 4 6 lf l l P - B i o s s 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 50 10 0 -IP - R e c i i a t i a E n a i I I I 2 2 DS M C o s s 1 , U t a h - C o o l r e p e r 5.5 5. 0 II II DS M C h s s i , G o h e n - D L C - i ~ t i n 19 . 8 0.9 1. 2.7 20 25 DS M C l a s s i U t a C o n n c u s - T h e r m E n e n w S t o 3. 5 3 3 DS M C l a s s I U t a h . C u r i k n t 21 . 4. 9 26 26 DS M C l a s s i U t a h . D L C - R e s i d n t i l 31 . 7 32 32 DS M . C l a s s i , W v o m i £ l . . u r i l n t 6. 7 7 7 SM C l s i T o t l 5. 5 61 . 6 19 . 8 11 . 6 0.9 1.3 2.7 99 10 3 DS M C l a s s 2 . I d a h o 2. 0 2.5 2.2 2.8 3. 4 3.9 4. 2 4.5 4.7 5.1 5. 2 5.4 6.5 7.0 7. 3 6.8 7.2 6.8 7. 1 6.5 35 10 1 DS M C l a s s 2 U t a 83 . 9 92 . 1 93 . 9 40 . 1 41 . 4 43 . 9 45 . 1 48 . 1 49 . 9 52 . 3 54 . 2 58 . 1 54 . 4 56 . 4 57 . 9 61 . 55 . 4 58 . 2 57 . 3 59 . 9 59 1 11 6 4 DS M C l a s s 2 W v o 3. 6 4. 6 4.8 6.1 6. 2 7.1 7.9 8. 7 8.7 9.3 10 . 9 11 . 8 13 . 6 16 . 7 17 . 8 23 . 0 24 . 5 28 . 8 35 . 9 38 . 9 67 28 9 'S M . C l s 2 T o t l 89 . 6 99 . 3 10 0 . 9 49 . 0 51 . 0 54 . 9 57 . 2 61 . 63 . 3 66 . 6 70 . 3 75 . 3 74 . 5 80 . 1 83 . 0 91 . 2 87 . 1 93 . 8 10 0 . 3 10 5 . 3 69 3 15 5 4 . W a t e r H e a t e r 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 24 44 . P h o t o v l t i c I 51 I 54 54 !! n 1 O t t II L H 16 8 26 4 23 0 99 76 1 76 1 Hi l 17 5 20 0 20 0 19 4 56 15 7 69 1. 0 5 1 1.0 5 1 15 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 5 II I 21 6 27 0 30 0 30 0 30 0 30 0 30 0 30 0 22 5 23 3 6 7J 11 2 11 7 15 9 12 4 14 8 14 1 12 0 N/A 10 0 32 12 3 29 4 55 2 N/A 10 0 19 9 23 32 5 30 3 15 0 N/A 10 0 IU r u l ) T - T - T - T -T 22 7 22 7 !! U n i l J. - . 1 - . l . . 1 . J . 21 6 21 6 8 12 12 70 35 70 10 5 Ic I l F a c t o r 2 2 2 2 ;H P - B i o s s 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 42 84 DS M C l a s s i C a I i O l - D L C - l r Û O 5.5 5 5 DS M C l a s s i O r e o n - e i J n t 17 . 2 17 17 DS M C l a s i O r e i z - D L Ç . l r i i t b n 0.5 12 . 7 13 13 DS M C l a s s i O r e o n - D L C - R e s i i n t ø l 10 . 0 10 10 DS M C l a s s i W a s l i - D L e - l r t i 8. 5 9 9 DS M C l a s s i W a s h i - D L C - R e s n e n t i l 3.3 3 3 8M , C l a s i T o t l 9. 0 48 . 7 58 58 DS M C l a s 2 C a l i o r 0.7 0.8 0.8 i. 1.3 1. 4 1. 1.7 1. 6 1.7 1.8 1. 9 2.2 2. 4 2.5 2.2 2.3 2. 2 2.2 2.0 13 34 DS M C i a 2 O r . . 52 . 6 52 . 8 56 . 0 60 . 7 61 . 7 60 . 8 60 . 3 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 44 . 0 36 . 1 36 . 1 36 . 1 56 2 10 2 8 DS M C l a s s 2 W a s ü m t o r 10 . 1 12 . 5 8.5 8.5 8. 6 8.4 8.8 9.1 9.4 9. 6 10 . 7 11 . 7 11 . 4 12 . 1 12 . 4 9.6 8.3 8.7 8.6 9.0 93 19 6 ID 8 M C W , 2 T " ' I 63 . 3 66 . 2 65 . 3 70 . 3 71 . 5 70 . 6 70 . 7 63 . 2 63 . 3 63 . 7 64 . 8 65 . 9 66 . 0 66 . 8 67 . 2 64 . 2 54 . 6 46 . 9 46 . 9 47 . 0 66 8 1,2 5 9 OR S o m C ' D S i a f i d 2 2 2 3 9 9 ~R S o m P i l 4 2 2 I 10 10 2 2 2 2 2 2 2 2 2 I I I 1 I 16 21 15 0 15 0 15 0 15 0 50 65 JJ 40 0 40 0 40 0 40 0 38 6 40 0 40 0 40 0 40 0 26 39 1 30 8 40 0 40 0 14 6 35 9 26 3 14 3 96 24 12 50 50 50 50 29 50 50 50 38 19 25 53 17 3 49 20 4 96 20 2 19 9 N/A 10 0 N/A 10 0 N/A 20 0 m " ~ \ S ' ; k a ¡ : ¡S ' ;t; l i l ~ R, ,~ ' l ' m .. ~ "* ~ ~ '" F o r th e 2 0 Y e a r c o l u m n " G r o w t h S t a t i o n s " a r e a n 1 0 y e a r a v e r a g e r e f l e c t i n g t h e a v a i l a b l e y e a r s f r n m l O l ' . l O W 64 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 1 0 c o m p a r e d t o E n e r g y G a t e w a y C a s e 9 Re s o u r e d i l r e n c e s f r m b a s e t r n s m i i o n s c e n r i a r e s h o w n P V R d i f r e o c e i n i c a t e d a s a n i n c r a s e o r ( d e c r e a s e ) . 41 2 0.5 r - T - i . i - T - i - i . T - T . T . T - T - T . T - T - 0 0 05 .1 - . 1 . . 1 - . L - 1 _ T - I - 1 2.2 0 3 (0 2 ! (2 2 1 2) 1 (2 ) (2 ) 2) 1 (1 2 ) (0 ) 0 (1 ) (l To 19 T . T 18 55 ) 1 ( 5 8 ) 1 15 1 11 6 (4 4 57 31 0 0 11 6 11 1 ) 18 13 N/ A 0 14 (1 0 ) 15 2 22 15 0 N/ A 0 (3 35 (2 ) (2 ) 1 (2 (2 (0 . 1 ) (0 ) 0 (0 . 1 ) (0 ) 0 0. 2 0 0 0. 2 0 0 0 1) 1 (0 26 37 (4 9 14 6 (0 ) 2 0) 1 I T ro (õ j fo fo 88 13 48 0 96 0 0 N/ A 0 0 Õ 65 PA C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 1 1 c o m p a r e d t o E n e r g y G a t e w a y C a s e 9 Re s o u r e d i f e r e c e s f r o m b a e t r m i i o n s c e n a a r e s h o w n P V R d i f e r e n c e i n d i c a t e d a s a n i n r e a s e o r ( d e c r e a s e ) . 2.2 2 0. 5 . I - 1 0 0 O. H - 1 - . 1 . . 1 - 1 . . . . . 1 . . . - i . - . . 2. 2 0 3 (0 ) (2 ) (2 ) (2 ) (2 (2 ) 12 10 0 0l l - l . . . (0 l l (0 2 1 (0 . 2 . . l - l ri I) 0 19 18 55 ) (5 7 ) 15 83 13 4 49 0 0 0) i 14 13 II I N/A 0 97 34 (4 ) ¡ N/A 0 :i 13 5 2) (2 ) 2 2 0.1 ) 1 . I 0 (0 ) (0 . 1 ) - I (0 ) 0 0.2 . I 0 0 0. 2 . 1 - . 1 - J . . . . . 1 - J 0 0 I I /2 6 17 14 9 12 6 (0 ) 2 (0 ) - I - 1 (0 0 10 0 49 88 (1 ) (2 8 ) 0 19 6 0 0 N/ A 0 .!(0 ) 1 . F o r th e 2 0 Y e a r c o l u m n " G r o w t h S t a t i o n s " a r e a n 1 0 y e a r ov e r a g e r e f l e c t i i i g t h e a v a i l a b l e y e a r s f r o m 2 0 2 J - 2 0 3 0 . 66 PA C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 1 2 c o m p a r e d t o E n e r g y G a t e w a y C a s e 9 Re s o u r e d i f r e n c e s f r m b a s e t r n s m i i o n s c e n a a r e s h o w n . P V R d i f r e n c e i n i c t e d a s a n i n r e a s e o r ( d e c r e a s ) . CC C T F 2 . i Wl n d U l . i - t - _ t . t - Î - t -1 18 Î 8t 71 4Î Wi n W v n m i n o 3 5 % C a r e c i t F a c t o r 34 To i a l W i n - I - I 18 ~ 81 - 7- 1 (I l l 34 DS M , C l a s s i , G o h e n - D L C - I r r m a t i 19 . 8 19 . 8 ) . I . I - I - I . ~ I. . . (1 . ~ DS M C l a s s i U t i : h . C o n n d . T h e r m E n e r o v S t o a (3 . 5 DS M C l a s s i U t a h . C u r i b n t 4.9 (4 . 9 -- - - - - DS M C l a s s I , U t a . OL e . Re s i d n t i l 6.6 (6 . 6 ) -. DS M , C l a s s . l , W v o m o - C u a i h n t 5.4 1.4 (6 . 7 ) ~ 8M C l a s s 1 T o t a l 6.6 (4 . 8 ) 19 . 8 (1 9 . 8 ) 6.3 (1 1 . 6 ) I. (1 . ) DS M C l a s s 2 I d a h o 0.5 (0 . 7 0. 1 10 . 2 0.4 ~ DS M , C l a s s ' U t a h (3 8 . 1 ) (4 2 . 7 ) (5 0 . 4 1.9 2. 2 DS M , C l s s 2 , W v o m . 0.1 0.2 0. 4 I SM . C h s s 2 T o t l (3 8 . 5 (4 3 . 2 ) (5 0 . 1 ) 1.9 .I Ò . 2 (0 . 4 ) 2. 2 ~ (2 2 ;5 4 ) t 1) (5 1 ) (1 ) 34 99 12 == 25 (8 ) 13 _ ( ! 2 41 12 3 15 7 12 3 (3 3 29 5 18 9 84 30 1 _i n 84 (4 1 68 22 71 18 1 -- 57 78 22 11 5 7 10 15 1 34 45 (1 5 0 -f 35 13 5 (2 (2 ) (2 ) 2 0 I I I I I I I I I I I 1 ti o n 5. 5 5.5 17 . 2 (1 7 . 2 13 . 2 0.5 12 . 7 10 . 3 10 . 0 Ó 0 2. 1 8.5 6.4 0 0 1. (3 . 3 ) (2 ) (2 ) 1 49 . 5 9.0 6.4 48 . 7 2 2 0.1 0.1 0. 1 0 0 0.1 0.2 0.2 0.3 0.3 ) (0 . 1 ) 0.1 0) (0 ) 0.1 0.2 0.3 (0 . 3 ) (0 . 3 ) 0.1 ) 0.1 (0 ) (0 ) 10 9 14 90 18 1 9 69 25 4 15 7 18 24 10 1 11 0 21 11 50 ) 50 21 (5 0 ) (3 I) 36 (4 0 ) (0 ) (9 6 ) (0 ) (0 ) N/ A (0 ) N/ A N/ A (0 ) 67 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 1 3 35 . I - I 45 35 Fa c t o r I dv F a c t o r I i I I I 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 50 10 0 aÜ l E n J l e T I I I 2 2 5.5 5.0 II II 19 . 8 2.2 2.7 20 25 Sl o m - - 3.5 3 3 21 . 5 3.2 1. 6 26 26 31 . 7 5.4 37 37 5.4 1. 4 7 7 5.5 61 . 6 28 . 4 8.4 2.2 2.7 10 4 10 9 2.0 2.5 2. 5 3. 0 3.7 4.4 4.7 5.1 5.0 5.4 5. 4 5.6 7.0 7.6 8.0 7.6 8.0 7. 6 7. 6 7.1 38 11 0 83 . 9 92 . 1 10 1 . 44 . 0 45 . 4 48 . 2 61 . 8 50 . 6 60 . 8 69 . 5 57 . 2 61 . 5 57 . 8 60 . 1 60 . 2 63 . 5 57 . 2 60 . 1 59 . 3 62 . 1 65 7 1,2 5 6 3.9 5.0 5. 3 6. 2 6.3 7.3 8.1 9.0 9.1 9.8 11 . 11 . 8 13 . 9 17 . 2 18 . 3 23 . 6 25 . 1 30 . 1 37 . 5 39 . 9 70 29 8 89 . 8 99 . 6 10 9 . 0 53 . 2 55 . 5 59 . 9 74 . 6 64 . 6 74 . 8 84 . 7 73 . 8 78 . 9 78 . 7 84 . 9 86 . 5 94 . 7 90 . 3 97 . 8 10 4 . 4 10 9 . 1 76 6 1. 6 6 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 24 42 51 I 54 54 16 8 26 4 21 4 99 99 84 4 84 4 17 5 J 20 0 20 0 74 17 2 20 0 20 0 1.2 2 1 1, 2 2 1 15 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 74 22 5 25 1 7 32 75 76 13 7 18 4 14 3 12 3 10 4 11 7 N/A 10 0 24 16 5 35 3 45 8 N/A 10 0 13 8 15 9 II I 60 13 9 19 20 22 0 13 5 N/A 10 0 IU Ù . I 22 7 22 7 !! U o i ) .L - . . - . . - . . - . . 21 6 21 6 8 12 12 70 70 70 70 70 35 35 35 0 42 0 Fa c t o r 10 0 10 0 10 0 10 0 10 0 20 0 20 0 CH P - B k : s 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 42 84 DS M C l a s s I C a l i o n - D L C - I r r i u t i 5.5 5 5 DS M C l a J O r e l l - C u r i k n t 17 . 2 17 17 DS M . e B B i O r e R ~ . D L C . I ~ û m 13 . 2 13 13 DS M _ C l a i O r e i r . D L C - R e s i d n t l 3.6 6.8 10 10 DS M C l a s s i W a s h i n l 1 o n - D L C . l r r t i 8.5 9 9 DS M . C l a s s i W a s b i - D L C - R e s k l n t l 4.8 5 5 SM . C I i , I T o t l 52 . 8 6.8 60 60 DS M C l a s s 2 . C a i f o m 0.7 0.9 0. 9 1. 1.5 1.6 1.7 1. 7 1.7 2. 0 1.8 1.9 2.3 2.5 2.6 2.3 2.7 2.5 2.5 2.3 14 37 DS M C ø s s 2 . O r e a o n 52 . 6 52 . 8 56 . 0 60 . 7 61 . 7 60 . 8 60 . 3 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 44 . 0 36 . 1 36 . 1 36 . 1 56 2 1, 0 2 8 DS M C l a s s , . _ W a s m n ø t o n 12 . 0 12 . 7 9. 0 8. 8 8.9 8.7 8.9 9.2 9.4 9. 6 10 . 8 11 . 8 11 . 5 12 . 5 12 . 8 9.9 8.5 8. 9 8.9 9.3 97 20 2 DS M . CIi 2 T o t l 65 . 3 66 . 4 65 . 9 70 . 8 72 . 1 71 . 2 70 . 9 63 . 3 63 . 4 63 . 9 65 . 0 66 , 2 66 . 2 67 . 3 67 . 8 64 . 6 55 . 2 47 . 5 47 . 5 47 . 6 67 3 1, 2 6 8 lO R S o l a C a n S t a n d a 2 2 2 3 9 9 OR So h r Pil 4 2 2 I 10 10 Mir o S o - W a t e r H e a t e r 2 2 2 2 2 2 2 2 2 2 2 2 2 I I I I 16 28 FO T C O B 3 r d O t t H L H 15 0 15 0 15 0 15 0 50 - 65 33 FO T M i d C o h . i a 3 0 0 O t t H L H 40 0 40 0 40 0 40 0 40 0 40 0 36 5 39 5 40 0 29 8 40 0 40 0 40 0 40 0 44 40 0 35 6 29 5 FO T M k i C o b n b i a 3 r d O l r H L H 1 0 % 1 P r i e P r e m i 14 3 90 23 12 'Q T S o u t C e n l O r e a o n o r e m C a L . 3 r d O l r H L U 50 50 50 50 50 50 50 35 18 N/A 61 N/A 5 N/A 20 0 : a ¡ " ' ~ W *\ , 'i W i W '. ~~ ~ ~ ~ .., ," ' , "., . " , ' T ' ¿ *, 1 ) *ii ~ , i W ; , ~ ; ~ ! W "'T h ' - : * , \, \~ i l "l \ i g ~ ¡ s F ¡ ¥ ., * 'it ' l " ,, " ~ "~ - 0 : ' 1m ' " :# ~ : ~ "~ : ' & , , W i . : ~ :,l : " : ' . F o r t h e 2 0 Y e a r c o l u m n " G r o w t h S t a t i o n s " a r e a n 1 0 y e a r a v e r a R e r e f l e c t I n f ! t h e a v a i l a b l e y e a r s fro m 2 0 2 1 . 2 0 3 0 . 68 P A C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 1 4 c o m p a r e d t o E n e r g y G a t e w a y C a s e 1 3 Re s o u r e d i f r e n c e s f r m b a s e t r n s m i i o n s c n a a r e s h o w n . P V R d i f r e n c e i n i c a t e d a s a n i n c r e a s e o r ( d e c r e a s e ) . 20 0 26 16 0 1 - 1 -I - 1 -I i 20 0 . 1 20 0 . . 20 0 . 1 14 1 . 1 20 0 1 26 1 29 1 i - (2 . 2 ) 2. 2 (2 . 2 ) 2.2 I- (0 3 1 (0 . 1 ) t (0 . 2 i l - ï (0 . 3 ) (I ) (i 0. 3 i ( 1 . ) 9.7 (1 4 . 6 ) 26 (2 6 o. õ T -T _ i o. i f 0.1 (0 . 0 ) (0 . 2 ) 1 (0 . 2 ) 0.2 0.2 (0 . 1 ) 0.3 0.4 0.5 (0 1 0. 0 . - J _ - . 1 - . . O.u . (O . m . ( 1 . 6 ) (1 O . 0 1 l 14 . 9 ) 0.2 0.2 (0 . 3 ) (0 . 1 0.3 0.4 0.5 (2 7 ) (2 5 -. 0 ) Õ) 0) (0 ) 10 ) 10 ~ 22 6 37 1 51 19 3 14 15 3 16 5 7 33 0 -w (0 (2 4 ) (1 6 5 (6 7 (1 7 9 ) 43 5 26 6 11 4 35 20 75 17 20 9 Ni 35 35 13 5 35 ~-- O. l Î _ Î _ T _ Î o. õ T - T - T 10 . 2 0.1 0. 3 0.3 0.3 (0 1 0.1 . 1 - . 1 - . 1 - . 1 0.0 . 1 - . . - . 1 (0 . 2 0.1 0. 3 0.3 0.3 (0 1 1 1 (3 0 ) (2 2 ) 51 (1 4 (1 4 ) 35 6 (5 ) 16 .í.!56 0 69 P A C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 1 5 c o m p a r e d t o E n e r g y G a t e w a y C a s e 1 3 Re s o u r e d i f l r e c e s f r m b a s e t r n s m i i o n s c e n a r i a r e s h o w n P V R d i f r e n c e i n i c a t e a s a n : i r e a s e o r ( d e c r e a s e ) . 70 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 1 6 c o m p a r e d t o E n e r g y G a t e w a y C a s e 1 3 Re s o u r c e d i f r e c e s f r m b a s e t r n s m i i o n s c e n a a r e s h o w n . P V R d i l r e n c e i n i c a t e a s a n i n r e a s e o r ( d e c r a s e ) . ~ Wi n d , W Y E 3 5 % C a m . ~ i h F a c t o r 16 0 .1 . T . T . T . T . T . T . T . T .T . ~ Wi n W v o i n l 1 . 3 5 % C a n a c i t F a c t o r . I 18 8 20 0 I 20 0 20 0 20 0 I 20 0 20 0 19 9 I 2 0 0 . To t a l Win 16 0 . I 18 8 20 0 . . 20 0 . 1 20 0 1 20 0 . . 20 0 . 1 20 0 1 19 9 . . 2 0 0 J 1 6 0 DS M C l a s s i G o h e n ~ D L C . l r r i t m t i o n 19 . 8 19 . 8 . I . T (2 . 2 ) ( 2. 2 DS M , C l a s s 1 U t a h . C o m d u - T h e n n E n e r i i S t o a 13 . 5 DS M _ C l a s s 1 U t a - C u r i h n t 1.6 1. 6 -- f - DS M . C l a s s 1 , U t a h - D L C ~ R e s i d n t i l 6. 6 (6 . 6 (5 . 4 5.4 (0 ) DS M . C l a s s 1 W v o m i i u l ' - C u r a i h n t 5.4 (5 . 4 1.4 1. 4 DS M , C l a s s i T o t l 6.6 (4 . 7 ) 19 . 8 (2 5 . 2 ) (8 . 4 8.4 (2 . 2 ) 2. 2 (3 ) 3) DS M . C l a s s ' I d a h o (0 . 5 (0 . 6 0.4 ) 0.1 (0 . 1 0.3 (2 ) (2 ) DS M , C l a s s 2 U t a h (3 8 . 1 ) (4 2 . 7 ) (5 7 . 5 12 . 4 0. 6 (1 5 0 ) (1 5 0 ) OS M . C l a s s ' W v o m a 0.1 (0 . 2 0. 1 10 . 0 0.0 0.1 0. 1 0.1 0.2 0. 2 (0 . 1 0.3 0. 4 0.5 0 1 DS M C l a s s 2 T o t l (3 8 . 6 ) (4 3 . 5 (5 8 . 0 ) 10 . 0 ) (0 . 1 (1 2 . 5 ) 0. 1 0. 7 0.2 0. 2 0.3 ) (0 . 1 0.3 0. 4 0.5 (1 5 2 (1 5 1 ) Mi c r o S o l a r . W a t e r H e a t e r 10 (0 Mic r o S o l a r - P h o t o v o l t i c (1 ) (5 1 1 (5 4 ) (5 4 FO T M e a d 3 r d O t r H L H 50 (9 9 (4 9 (4 9 FO T U t a h 3 , d 0 ' , H L H 25 (7 12 6 17 2 (2 0 0 22 8 ) (2 2 8 ) 'T Mo n I NU B 22 6 22 6 tw t h R e s o u r e G o h é n I I 52 15 62 49 13 6 53 64 0 1 73 -N (O ) i .! t a h N o r . :. 22 40 06 5 16 4 08 6 45 3 ~ 40 10 8 83 60 13 9 19 20 19 1 66 49 3 äW (3 5 ) i 70 I I I 35 (3 ) (3 ) 35 CH P - R e c ' o c a t ' En i n e 0 0 DS M C l a s s i C a l i o m Î a - D L C - I 00 5.5 5.5 os Cl a s i O r e .C u r î h e n t 17 . 2 17 . 2 DS M , C l a s s 1 , O r e o n - D L C - I .i o 13 . 2 (1 3 . 2 ) OS Cla s l O r e o n - O l e - R e s i d n t i a l 10 . 3 3.6 6.8 DS M , C l a s s 1 , W a s ' on - O L e - i 00 2.1 4. 8 (6 . 9 ) OS Cla s s i . W a s h i o n - O L e - R e s i d e n t i a l 1.2 4.1 2.9 DS M , C l a s s i T o t l 49 . 5 4. 8 50 . 4 (6 . 8 ) 2.9 0 0 OS Cl a s s 2 C a l i o r 0.1 0.0 0. 0 0. 2 0.1 0.3 0. 3 0 1 OS Cla s s 2 , W a s h i n o n 0.1 0 0 DS M , C l a s s 2 T o t l 0.1 0.0 0. 0 0. 2 0.1 0.3 0.3 0 1 Mi r o S o l a r - W a t e r H e a t e r 1 1 FO T M i d C o 1 m i a 3 r d t r H L H 92 65 35 5 13 2 33 3 61 35 6 12 38 FO T M k l C o l m i a 3 r d t r H L H 1 0 " 1 0 P r Î c e P r e m i 10 2 11 1 21 11 lO r e or t h e r n C a l 3 r d t r H L H 1 50 8 6 4 2 'a l i W a l l ' " (8 0 4 3 0 18 4 N/ A 10 'R I C A ' " 24 8 (4 3 ) N/ A 20 0 71 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S Ta b l e C . 4 - E n e r g y G a t e w a y S c e n a r i o E v a l u a t i o n R e s u l t s ( W M S t u d i e s ) En e r g y G a t e w a y C a s e 1 _ W M he n n l P l a n t T u r n e U i w d e s 12 . 1 18 . 9 1.8 18 . 0 2 51 53 'C C T F 2 x l 62 5 59 7 1,2 2 2 1.2 2 2 ,o i l i B l t B 3 35 45 80 80 Wi n ; G o h e n , i 9 " / n C a n a c i t v F a c t o r 66 98 35 20 0 20 0 Wi n d U t a h , 2 9 0 1 0 C a n a c i t F a c t o 10 0 10 0 10 0 18 88 43 29 22 30 0 50 0 WÎ n i t W v o m i n a . 3 5 0 1 0 C a n a c i t F a c t o r 2 0 0 2 2 .o i l W i i 66 20 0 13 5 10 0 18 88 43 29 22 50 2 70 2 Hp . B i o s s I I I I I I I I I I I I I I I I I I I I 10 20 DS M C l a s s J , U t a b - C o e o e 5.5 5.0 II II DS M , e m s s i G o h e n - D L C - l r t i o 19 . 8 4. 9 20 25 DS M C l a s s 1 U t a h - e w t i k n t 21 . 4.9 26 26 DS M . C l a s s I U t a h ~ D L C - R e s K l n t i a l 9.0 5.4 12 . 3 27 27 DS M , C l a s s I , W v o m l Z - C u i k n t 5.4 1. 4 7 7 8M , C h s s 1 T o t l 5.5 40 . 9 19 . 8 11 . 6 12 . 3 4.9 90 95 DS M . C l a s 2 I d a h o 1. 5 1. 8 2.0 2.8 3. 3.9 4.2 4.4 4.3 4.6 4.7 4.8 5.7 6.1 6.5 6.1 6.5 6.1 6.1 5.6 33 91 DS M C l a s 2 U t a . 43 . 3 46 . 6 39 . 0 40 . 1 41 . 4 43 . 9 45 . 1 46 . 1 47 . 8 50 . 1 51 . 4 54 . 9 51 . 3 53 . 1 53 . 0 57 . 4 52 . 0 54 . 6 53 . 8 56 . 2 44 3 98 1 DS M C l a s s 2 W V o m l l 3.5 4.3 4.5 5.5 6.2 7.1 7.9 8.7 8.7 9. 3 10 . 9 11 . 5 13 . 3 16 . 3 17 . 4 22 . 5 23 . 9 28 . 1 35 . 0 37 . 2 66 28 2 I 48 . 3 52 . 8 45 . 5 48 . 4 51 . 0 54 . 9 57 . 2 59 . 1 60 . 8 64 . 0 66 . 9 71 . 70 . 3 75 . 6 76 . 8 86 . 0 82 . 4 88 . 8 94 . 9 99 . 1 54 2 1, 3 5 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 24 47 16 8 26 6 26 6 90 78 9 78 9 22 9 25 0 72 10 9 24 3 25 0 1,1 5 2 1. 1 5 2 15 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 22 5 26 3 29 10 2 10 7 15 3 16 1 22 9 13 0 89 N/ A 10 0 8 26 5 32 1 40 6 N/ A 10 0 15 6 25 7 27 2 30 9 N/ A 10 0 Tb n n l P l a n t T u r b n U m m l . d e s 4 8 12 12 Wil Y a k i 2 9 0 1 0 C a o a c i t F a c l o 10 0 10 0 10 0 Wi l Y a k i 2 9 % C a o a c i t F a c t o 65 10 0 28 24 10 0 58 95 46 10 0 16 4 61 6 WD I O r e 2 o o 2 9 0 1 0 C a o a c i l v F a c l O 86 86 Wm . W a l l W a l l , 2 9 % C a n a e l v F a c t 10 0 10 0 10 0 lT o i l W i n 20 0 65 10 0 28 24 10 0 58 95 46 18 6 36 4 90 2 Ut i l i B i o s s 50 50 50 CH P - B i o s 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 42 84 DS M C l a s s i C a l i o m - D L C - I l l t i 5.5 5 5 DS M , C l a s s i O r e i r - C u r i k n t 17 . 2 17 17 DS M . C l a s s i O r e l I D - D L C - I r t i o 13 . 2 13 13 DS M C l a s s i O r e l l - D L C - R e s i d n t i l 3.6 4 4 DS M _ C l a s s i W a s b i n a t o n - D L C . I r r l i o 2.1 6.4 9 9 DS M , C B S S I t W a s b i n o n D L C . R e s i d i a l 1. 3.6 5 5 tp S M . C b S S i T o t a l 42 . 8 10 . 0 53 53 DS M C e s s 2 C a 1 i o r 0.7 0.8 0.8 1. 1. 3 1.4 1. 1.5 1.4 1. 1. 6 1. 6 2.0 2.1 2.2 2.0 2.0 1. 9 1.9 1. 7 12 31 DS M C l a s s 2 O r e 2 0 n 52 . 6 52 . 8 56 . 0 60 . 7 61 . 7 60 . 8 60 . 3 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 44 . 0 36 . 1 36 . 1 36 . 1 56 2 1.0 2 8 DS M , C h s s 2 , W a s h i i ò ß 7. 8.0 8.2 8.0 8.4 8.2 8.5 8.8 9.0 9.2 10 . 0 10 . 9 10 . 9 11 . 4 11 . 8 9.3 8.1 8.5 8.6 8.9 84 18 2 rO S M . Q i s s 2 T o t l 60 . 7 61 . 6 65 . 0 69 . 8 71 . 4 70 . 4 70 . 3 62 . 7 62 . 8 63 . 1 63 . 9 64 . 9 65 . 3 65 . 9 66 . 3 63 . 7 54 . 1 46 . 4 46 . 5 46 . 7 65 8 1.2 4 1 OR S o a r C a n S t a n d 2 2 2 3 9 9 OR SO Ð r Pi l 4 2 2 I 10 10 r1 i c r o S o l a r - W a t e H e a t e r 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 I I 16 31 OT C O B 3 r d O f r H L H 15 0 15 0 15 0 15 0 50 65 33 'O T M i d C o h . o o m 3 e d O t r H L H 27 40 0 40 0 40 0 36 5 40 0 40 0 40 0 40 0 40 0 36 9 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 35 9 37 8 'O T M i d o l u i a 3 r d O t H L H i o o l a P r k e P r e m i 27 1 21 1 48 24 OT S o u h C e n t r l O r e l ! o i o r h e m C a l 3 e d O t t H L H 50 50 50 50 50 50 15 50 36 18 N/ A 86 N/ A 53 N/A 16 2 72 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 2 _ W M c o m p a r e d t o E n e r g y G a t e w a y C a s e 1 _ W M Re s o u r c e d i f r e c e s f r o m b a s e t r n s m i i o n s c e n a r i o a r e s h o w n . P V R d i f r e n c e i n k a t e d a s a n i n c r a s e o r ( d e c r e a s e ) . (2 ) 20 0 20 0 T 15 T 73 1 38 T 48 T 20 1 99 T 50 T 80 1 39 T 15 4 94 (2 0 0 ) 65 io o T (4 2 1 (l 5 J (5 . l 19 l . 20 - 1 78 . . 50 l . 80 - 1 39 1 15 4 (o . m 8.6 1.9 (0 . 1 ) 8.6 1.9 3.0 0.1 0.6 0.1 0. 6 3.0-I - 1 0) (3 ) (3 ) - I - 1 (1 ) 1 -I . T (2 ) 7 - 1 - 1 53 . . 75 l . 07 (1 (1 2 3 00 32 49 (3 10 (5 ) ~ 17 (3 5 4 23 (9 ) N/A Fa c t o r I - T . 1 . 1 . 1 . i i6 O O O r (2 8 ) 24 10 0 58 95 (4 6 11 0 0 16 4 61 6 Fa c t o r - I - 1 . I 86 ) (8 6 ) cî t F a c t o -. - . . 27 ) 1 . 1 (2 7 ) (2 7 ) (2 7 2 1 - . . ,- . (6 5 ) (1 0 0 ) 28 12 4 (1 0 0 ) (5 8 ) (9 5 ) 46 11 8 6 (1 9 1 ) (7 2 9 6.5 6 6 6.5 6 6 0. 3 Î O. i t _ Î .1 0.2 0 0 - T - I 0. 4 1 . T 0.3 0.3 I I 0.3 1 0. 4 1 0. 1 . 1 0.3 0.5 2 2 1 - I - I i I (2 ) I I (5 ~ (0 2 L - . . 0 - I 0 0 (0 (0 II -- - - - I I 3Z 7 47 I (3 8 8 59 N/A 0 (I 3 fu w ~ " .. F o r t h e 2 0 Y e a r c o l u m n " G r o w t h S t a t i o n s " a r e a n J O y e a r av e r a g e r e f l e c t i n g t h e a v a i l a b l e ye a r s fr o m 2 0 2 1 - 2 0 3 0 . 73 PA C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 3 _ W M c o m p a r e d t o E n e r g y G a t e w a y C a s e 1 _ W M Re s o u r e d i f r e n c e s f r m b a t r n s m i i o n s c e n a m a r e s h o w n - P V R d i f r e n c e i n i c a t e a s a n i n r e a s e o r ( d e c r e a s e ) . 35 % C a p a c a y F a c t o r l - l - I (2 20 0 20 0 I 15 1 73 1 39 l 47 l 20 l 10 1 1 51 1 80 l 42 1 17 7 - I 94 (2 0 0 ) 65 10 0 41 1 (1 5 ) 1 (5 l 1 18 . 20 1 79 - 1 51 1 . 80 . 1 42 . . 17 7 (0 . 1 ) 1 8. 6 1.9 .l . l l L 8. 6 1.9 3.0 0.1 0. 6 0.1 0. 6 3. 0 0 (I ) (2 ) 7 53 . . 75 1 . (l 14 (1 2 3 (1 0 32 'N 24 16 9 I 15 9 14 23 15 ~ Fa c t o r T - T - T - T - T - T . T . T - T (6 5 (1 0 0 28 (2 4 (1 0 0 58 95 (4 6 (1 0 0 ~ ii 1 6 l cit y F a c t o r 1 - i - 1 . I 86 ) (8 6 ) ~i t F a c t ( l -1 - . 1 - 1 - - 1 - . 1 (2 7 ) 1 - 1 - I (2 7 ) (2 7 ) 1 -ß 7 l L - 1 . - . . - 1 . 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C l a s s i U t a h - C u r i h n t 21 . 5 4.9 26 26 DS M C l a s s 1 U t a h - O L e - R e s i d n t i l 5.2 5 5 DS M . C l a s s 1 , W v o i i - C m t i l n t 5.4 1.4 7 7 iS M C l a s s i T o t l 5. 5 37 . 0 19 . 8 6. 3 2.2 2.7 69 73 DS M C l a s s 2 I d a h o 1. 1. 8 2.1 3. 0 3.6 4.2 4. 5 4.8 4.7 5.2 5.2 5.4 6.7 7. 3 7.6 7.2 7.5 7. 6 7.6 7.1 35 10 5 DS M . C l a s s 2 U t a h 43 . 3 47 . 8 41 . 7 42 . 9 44 . 3 47 . 0 48 . 2 50 . 6 52 . 4 54 . 9 55 . 5 59 . 6 55 . 8 60 . 1 60 . 2 63 . 5 57 . 2 60 . 1 59 . 3 62 . 1 47 3 1,0 6 7 DS M , C l a s s 2 . 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D L C . I m . 1 i 5.5 5 5 DS M C l a s s 1 O r e ~ . C u r i l . . 17 . 2 17 17 DS M C l a s s 1 O r e u o o - D L C - I r r i 2 t i 13 . 2 13 13 DS M C l a s s 1 O r e m i . D L C - R e s i d n t i a l 3. 6 4 4 DS M C l s s i W a s h . . o t n n . D L C - l r i o A t i o 2.1 6.4 9 9 DS M C l a s s J W a s l w u r t o n - D L C . R e s i d n t i a l 1.2 3.6 5 5 DS M C l a s s i T o t a l 42 . 8 10 . 0 53 53 DS M , C l a s s ? C a 6 f o m i a 0.7 0.9 0.9 1. 2 1. 1.6 1. 7 J. 1.7 1. 8 1.9 1.9 2.3 2.5 2.6 2.3 2.4 2.2 2. 5 2.3 14 36 DS M C l a s s 2 0 , e o o 52 . 6 52 . 8 56 . 0 60 . 7 61 . 7 60 . 8 60 . 3 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 44 . 0 36 . 1 36 . 1 36 . 1 56 2 10 2 8 DS M , C l a s s , . 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T 1. 0 ij 0. 1 . 1 . 1 . . . 1 . . 1 1.2 (0 . 5 ) 1. ) I (0 ) 3 2 2 10 7 7 20 1 24 1 (6 ) 1 20 46 53 (J 19 (9 0 ) 16 (2 1 ) 95 N/ A 0 20 Cl 4 44 56 67 N/ A (0 ) 1 2i i i i o ô l i I O Õ i (2 8 24 (1 0 0 58 95 '4 6 CL O O 22 2 67 2 ) 1 1 (5 6 ) (5 6 ) 1 (2 2 ) L C L O O ) (1 0 0 ) (2 8 (2 4 ) 10 0 (5 8 ) 95 '4 6 (1 5 6 ) (2 2 2 ) (7 2 1 l 1 :. - . 0.1 (0 . 3 0.1 ) 0. 3 ) (I ) (I ) (2 ) (2 ) (1 2 1 (lj ' 79 PA C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 9 _ W M 51 53 1, 2 2 2 1,2 2 2 80 80 Win d , G o h e n . 2 1 ) 1 0 C a r n c a v F a c t o r 66 98 35 20 0 20 0 w;l U t a h 2 9 % C a n a c i t F a c t o r 10 0 10 0 10 0 18 88 43 51 29 30 0 52 9 Wi n d _ W V o i i n l l . 3 5 % C a n a c i t v F a c t o 2 0 0 2 2 .o t l W i n 66 20 0 13 5 10 0 18 88 43 51 29 50 2 73 1 'H P - B i o s s 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 10 20 DS M C l a s s I , U t a h - C o o l k e n e r 5.5 5.0 11 11 DS M C l a s s i G o h e n - D L C - I r r i i i t i o n 19 . 8 0. 2 2. 0 2.7 20 25 DS M . C l a s s i U t a . C u r l l n t 21 . 5 4.9 26 26 DS M C l a s i U t a h - O L e - R e s i d n t i a l 8.2 5.4 14 14 DS M , C l a s s i W v n i n o - C u r i h n t 5.4 1. 4 7 7 (O S M C l a s s i T o t l 5.5 40 . 0 19 . 8 11 . 6 0.2 2.0 2.7 77 82 DS M C l a s s 2 . I d a h o 1.5 1.8 2. 0 2.8 3.4 3. 9 4.5 4.8 4. 7 5.1 5.2 5.4 6.5 7.0 7.3 6. 8 7. 2 6.8 7. 1 6.5 34 10 0 DS M C l s s i U t a h 43 . 3 46 . 6 39 . 0 40 . 1 41 . 4 45 . 8 47 . 0 49 . 1 5l . 53 . 5 54 . 2 58 . 1 54 . 4 56 . 4 57 . 9 . 61 . 3 55 . 4 58 . 2 57 . 3 62 . 1 45 7 1. 0 3 2 DS M . C l a s s 2 W v o m 3.5 4. 8 5.1 6.1 6.2 7. 1 8.0 8.9 8.9 9.5 10 . 9 11 . 8 13 . 6 16 . 7 17 . 8 23 . 0 24 . 5 28 . 8 35 . 9 38 . 9 68 29 0 DS M Cl a s s 2 T o l i 48 . 3 53 . 2 46 . 1 49 . 0 51 . 0 56 . 8 59 . 5 62 . 8 64 . 7 68 . 1 70 . 3 75 . 3 74 . 5 80 . 1 83 . 0 91 . 2 87 . 1 93 . 8 10 0 . 3 10 7 . 55 9 1.4 2 2 Mir o S o l a r . W a t e r H e a t e r 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 24 50 FO T M e a d 3 r d 0 1 . H L H 16 8 26 6 26 6 88 78 7 78 7 FO T U t a h 3 r d O ~ H L H 22 9 25 0 71 10 5 23 6 25 0 1,1 4 1 1. 1 4 1 FO T M o o I N U B 15 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 22 5 26 3 IW t h R e s o u e G o h e n . .- 14 4 25 6 86 23 6 23 3 45 N/ A 10 0 iw t R e s o u e U t a h N o r . 68 83 28 7 56 3 N/ A 10 0 Re s o u r c e W v n m . . . . * 49 39 24 2 28 1 38 9 N/ A 10 0 ie r m l P l a n t T u r b i n U n a r a d e s 4 8 12 12 Wò n Va k i 2 9 % C a m c i l v F a c t o 10 0 10 0 10 0 Wo " Ya k i m 2 9 % C a t v c i t F a c t o 65 10 0 6 46 10 0 58 97 10 0 10 0 16 5 67 1 Wo " Or e o n 2 9 0 / 0 C a D a c Î l v F a c t o Wo " Wa l l W a l l 2 9 0 1 0 C a r n c i t F a c t o r 10 0 10 0 10 0 ..1 Win 20 0 65 10 0 6 46 10 0 58 97 LO L 10 0 36 5 87 1 It i l v B i o s s 50 50 50 'H P - B i o s s 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 42 84 DS M C l a s s i C a l i o r i a . D L C - I r r t i o n 5.5 5 5 DS M C l a s i O r e c t . C w 1 i h n t 17 . 2 17 17 DS M C l a s s i O r e l õ o n - D L C - I r r i t t i o 13 . 2 13 13 DS M C l a s s i O r e o o n - D L C - R e s i d n t m l 3.6 4 4 DS M C l a s s 1 W a s h i o _ . D L C - l n i o a l i 2.1 6. 4 9 9 DS M C l a s s i W a s h i n D t O l - D L C - R e s i d n t i l 1.2 3. 6 5 5 ¡P S M C l a s s i T o t l 42 . 8 10 . 0 53 53 DS M C l a s s 2 C a l i o r i a 0.7 0.8 0.8 1. 1. 1.6 1.7 1. 7 1.6 1.7 1.8 1.9 2.2 2. 4 2.5 2.2 2. 3 2.2 2.2 2.0 13 35 DS M C l a s s ' O r e o o n 52 . 6 52 . 8 56 . 0 60 . 7 61 . 7 60 . 8 60 . 3 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 44 . 0 36 . 1 36 . 1 36 . 1 56 2 10 2 8 DS M C l a s s 2 . W a s h m - 7.7 8.0 8.6 8.5 8.6 8.6 . 8. 8 9.1 9.3 9.6 10 . 7 11 . 7 11 . 4 12 . 1 12 . 4 9.6 8. 3 8.7 8.6 9. 0 87 18 9 ,S M C l a s s 2 T o t a l 60 . 9 61 . 6 65 . 4 70 . 3 71 . 5 7l . 70 . 7 63 . 2 63 . 2 63 . 7 64 . 8 65 . 9 66 . 0 66 . 8 67 . 2 64 . 2 54 . 6 46 . 9 46 . 9 47 . 0 66 2 12 5 2 R S o l a r C a n Sta n d a r d 2 2 2 3 9 9 OR So l a r Pil 4 2 2 1 10 10 o S o l a r - W a t e r H e a t e r 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 16 32 , C O B 3 r d n ~ H L H 15 0 15 0 15 0 15 0 50 65 33 iT M ü C o k n b i a 3 r d 0 t r H L H 27 40 0 40 0 40 0 36 4 40 0 40 0 40 0 36 6 40 0 36 7 40 0 40 0 40 0 40 0 40 0 40 0 33 5 11 4 35 6 33 9 iT M ü C o l u b i a 3 r d O t r H L H 1 0 " 1 0 P r ~ e P r e m i 27 1 2l 48 24 iT S o u C e n t r l O r Ð : o n o r t h e m C a L 3 r d O t r H L H 50 50 50 50 50 50 50 35 18 th R e s o u e W a l l W a l l . 24 74 11 ' 95 18 9 11 18 7 18 4 N/A 10 0 N/A 10 0 N/A 20 0 80 P A C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 1 0 _ W M c o m p a r e d t o E n e r g y G a t e w a y C a s e 9 _ W M Re s o u r e d i f r e n e s f r m b a e t r n s m i i o n sc e a r e s h o w n P V R d i f r e n ; e i n d i a t e d a s a n i n r e a s e o r ( d e c r e a s ) . 10 5 20 0 20 0 15 71 26 39 T 24 T lO o T 45 T 67 T 37 T 93 94 93 65 10 0 4 17 (1 (l 1 1 L 24 l - lO o i 45 . 1 67 ~ 3Ü 13 6 JÏ Q _ T - T (0 . 2 0.2 4.9 4.9 '- - - - Z 4 (3 . 6 ) 8.8 18 . 3 1. 4 (l. 4 ) (3 . 6 ) 15 . 1 12 . 0 (0 . 2 0.2 24 24 0. 2 0.3 0.2 I I 2.0 2.7 2.8 4. 0 2.4 2.4 3.0 4.4 16 . 0 40 40 O. 3 t 0.0 0. 1 0. 1 0.1 0.2 I I 0. 3 . . 2.0 2.7 2.9 4.3 2.8 2.4 3.0 4.4 16 . 3 41 41 0 (3 3 3 18 11 11 11 14 14 -- 1 21 11 65 (5 6 44 (1 2 56 (3 8 ) 5 ~ 68 11 9 24 19 23 0 N/ A (6 5 1 (1 0 0 l - i . i - T -¡ 6 (4 6 i r (l0 0 ) (5 8 ) 97 (1 0 0 ) (1 0 0 (1 6 5 ) (6 7 1 ) 1 (6 5 ) 10 0 1 1 - I 6)1 (4 6 ) (1 0 0 ) (5 8 ) 97 10 0 ) (1 0 0 ) 16 5 (6 7 1 ) 15 0 - T - T - i . I 50 50 .D L e - R e s i d n t i a l Î - - r - T - T 6.5 - 1 - ~ 0. 3 1 - I . I - - . - . . . . . 7 7 6.4 16 . 4 i 3.6 (3 . 6 ) 1 6. 3.6 10 . 0 6. 5 0.3 - 7 7 0. 2 i o. I T o. l T 0. 1 0. 2 0. 1 0. 0 0.1 1 1 0. 4 1 0.4 0. 4 0.1 0.1 0. 1 0.1 2 2 0. 2 - 0. 4 J 0. 1 . 1 0.5 0. 5 0.1 0.1 0.2 0.1 0.1 2 2 (l 1 2 12 1 -,( , 32 14 _ 0 65 (5 0 5 3 0 (0 ) J. l l 76 (6 ) (l9 ) 0 (4 0 ) 0 0 N/ A JQ 0 0 81 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R i O - P O R T F O L I O S En e r g y G a t e w a y C a s e 1 1 _ W M c o m p a r e d t o E n e r g y G a t e w a y C a s e 9 _ W M Re s o u r e d i f r e n c e s f r o m b a s e t r n s m i s i o n s c n a r i a r e s h o w n P V R R d i f r e n c e i n a t e d a s a n i n c r e a s e o r ( d e c r a s e ) . Go h e n , 2 9 % C a p a c i t y F a c t o r Uta h . 2 9 1 0 C a p a c i t y F a c t o r WY E 3 5 % C a p a c i t l ' a c t o r Wi n W v o n . 3 5 % C a o a c l v F a c t o 10 5 20 0 20 0 15 71 26 39 1 24 1 lO O t 47 1 67 1 37 t 15 3 'o t a l W i n 94 93 65 10 0 4 17 (J (1 ) 1 24 1 10 0 47 67 1 37 12 4 DS M C l a s s i G o h e n - D L C . I r r t i (0 . 2 0.2 DS M . C l a s s i U t a h - C u r i h n t 4. 9 (4 . 9 DS M . C l a s s i U t a h - O L e - R e s i d n t i a l (3 . 6 ) 8. 8 18 . 3 24 24 DS M , C i a " 1 . W y o m R - C u r i J n l 1.4 (1 . 4 ) DS M C i a " i T o t l (3 . 6 15 . 1 12 . 0 (0 . 2 ) 0.2 24 24 DS M . C l a s s 2 . I d a h o 0. 2 0.3 0.2 1 1 DS M C l a s s 2 , U t a h 2.0 2.7 2.8 4. 0 2.4 2.4 3. 0 4.4 16 . 0 - 40 40 DS M , C l a s s 2 W v o m l l 0.3 0.0 0.1 0.1 0,1 0.2 1 1 DS M , C l s s 2 T o t l 0.3 2.0 2.7 2.9 4.3 2.8 2.4 3. 0 4.4 16 . 3 41 41 (0 3 3 13 13 (l l ) II '. II II 14 14 21 21 21 42 7 27 44 0 01 44 38 5 N/ A 0 37 14 4 23 40 24 4 N/ A 0 65 (0 0 ) 61 1 (4 6 ) 1 O O O ~ (5 8 ) (9 7 (1 0 0 10 0 (1 6 5 ) (6 7 1 (6 5 00 0 6) 1 (4 6 ) 1 ( 1 0 0 1 1 (5 8 (9 7 00 0 10 0 16 5 ) 67 1 (5 0 - 1 - 1 (5 0 (5 0 6.5 0.3 . I 7 7 :o n - D L C - I r r i i i a t i T - T 6. 4 (6 . 4 :o n - D L C . R e s i d n t i a l 3.6 (3 . 6 6. 4 3.6 10 . 0 6.5 0. 3 7 7 0.1 0.1 0.1 0.2 0.1 0.0 0. 1 i i 0. 2 0.4 0. 4 0.4 0.1 0. 1 0.1 0.1 2 2 0.2 . 1 0.4 0. 1 0. 5 0.5 0.1 0. 1 0.2 0.1 0. 1 2 2 i 2 (2 2 1 7 32 14 0 65 44 5 3 (0 ) (0 11 ) 76 (6 ) (9 ) 0 (4 0 1 0 0 N/A (! !0 0 82 PA C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 1 2 _ W M c o m p a r e d t o E n e r g y G a t e w a y C a s e 9 _ W M Re s o u r e d i f r e n e s r o m b a e t r n s m i i o n s c e n a i o a r e s h o w n P V R d i f r e n c e i n d i c a t e d a s a n i n r e a s e o r ( d e c r e a s e ) . ~Wir Win .. ~ . . ~ ~ v ' v ~ _ _ _ . . _ _ _ . _ . 24 " t lO O t 47 t 67 " t 37 t Wi n d W v o r m p : . 3 5 % C a n a c i t v F a c t o 10 5 20 0 20 0 15 71 26 39 15 3 To t l Win 94 (9 3 65 10 0 4 (1 7 17 (I I I 24 1 . lO o t 47 1 67 1 37 T 12 4 DS M C l a s s i G o h e n - D L C - ¡ r r t i o n 0. 2 0.2 DS M C l a s s i U t a b - C u r i h e n t 4.9 4.9 I- DS M , C l a s s 1 U t a h - D L e . R e s i d n t i l (3 . 6 ) 8. 8 18 . 3 ~ DS M , C l a s s 1 , ~ ~ ~ ~ C w i h n t 10 4 (1 0 4 ) ~ '8 M C h s s i T o t l 13 . 6 15 . 1 12 . 0 (0 . 2 ) 0. 2 DS M C l a s s " I d a h o 0. 2 0.3 0.2 r- DS M C l a s s , . _ U t a h 2.0 2.7 2.8 4.0 20 4 2.4 3.0 4.4 16 . 0 f- DS M , C l a s s 2 , ; ¡ - ; 0. 3 0.0 0.1 0. 1 0.1 0.2 f- DS M , C l a s s 2 T o t l 0. 3 2. 0 2.7 2.9 4. 3 2.8 20 4 3.0 4.4 16 . 3 -- Wa t e r . H e a t e r 10 3 3 13 3 -- dO t r H L H 11 -- HL H 2 (9 14 14 -- 12 0 29 50 44 ) --.. (1 1 ) 70 (3 8 ) 21 ~ 62 20 7 27 93 38 9 Nf A Fa c t o r I I 1 L - T (6 5 i l i o o ) l - i - T - T (6 ) 1 (4 6 ) r e i O O (5 8 ) 97 (1 0 0 ) 10 0 (1 6 5 ) (6 7 1 ) 65 ) 1 (1 0 0 ) . T 6) (4 6 ) 1 (1 0 0 ) (5 8 ) 97 ) (1 0 0 (1 0 0 ) (1 6 5 (6 7 1 ) 1 50 - I - I . 1 50 50 6.5 . I 0.3 - 1 . 1 - I . 1 7 7 6. (6 . 4 3. 6 (3 . 6 ) , i- 6.4 3.6 10 . 0 6.5 0.3 7 7 o. I T 0.1 1 " 0.1 0.2 0.1 0.0 0.1 1 I 0. i T 0.4 . I I 00 4 0.4 0. 1 0. 1 0.1 0.1 2 2 O. U O.' ! O.U 0.5 0.5 0. 1 0.1 0. 2 0.1 0.1 2 2 I) 2 2 2 'I (7 32 14 0 65 44 5 3 (0 ) 1 iõ -I (0 ) (O y 76 (6 ) (2 ~ 0 34 ) 0 0 NfA (0 ) ' 0 Õ '" F o r t h ë 2 0 Y e a r c o l u m n " G r o w t h S t a t i o n s " a r e . a n / 0 y e a r a v e r a g e r e f l e c t i n g t h e a v a i I a b l e y e D r s f r o m 2 0 2 1 - 2 0 3 0 . 83 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 1 3 _ W M 28 0 51 53 Ie c C T F i x i 62 5 59 7 1,2 2 2 1,2 2 2 1g o t l r m l B h m f t 3 35 45 80 80 Win o i G o s h e n 2 9 0 1 0 C a p a c i t F a c t o 67 79 67 14 6 Win d U t a h , 2 9 % 1 C a p a c i t F a c t o 10 0 10 0 10 0 21 88 43 48 30 0 50 0 Wil d W v o 3 5 % C a o a c i t F a c t o 2 0 2 2 'o t l W i i 67 10 2 10 0 10 0 21 88 43 48 79 36 8 64 8 'H P - B i o s s I I I I I I I I I I I I I I I I I I I I 10 20 DS M , C l a s s i U t a h - C o o e e n r 5.5 5. 0 II II DS M C l a s s i G o b e n - D L e - I r t i 19 . 8 2.2 2. 7 20 25 DS M C l a s I U i a b , C t u i l n t 21 . 5 4.9 26 26 DS M C b s s i U t a b - D L C - R e s i d n t l 3.7 4.5 8 8 DS M . C l a s I W v o m i e - C u i k n t 5.4 1.4 7 7 iS M , C e s s i T o t l 5.5 35 . 5 19 . 8 10 . 7 2. 2 2.7 71 76 DS M C l a s s 2 I d a h o 1. 1. 9 2.1 3.0 3. 6 4.2 . 4.6 4.9 4.9 5.4 5.4 5. 6 7.0 7.6 8.0 7.6 8. 0 7. 6 7.6 7.1 36 10 8 DS M C l a s s 2 U t a h 44 . 4 48 . 6 41 . 42 . 9 44 . 3 48 . 2 49 . 4 50 . 6 52 . 4 54 . 9 57 . 2 61 . 5 57 . 8 60 . 1 60 . 2 63 . 5 57 . 2 60 . 1 59 . 3 62 . 1 47 7 1, 0 7 6 DS M , C m s , 2 . W y o n 3.8 4.8 5.2 6.2 6. 3 7. 2 8.0 9. 1 9.1 9.7 11 . 12 . 0 13 . 9 17 . 2 18 . 6 24 . 0 25 . 6 30 . 1 37 . 5 39 . 9 69 29 9 l. T o t l 49 . 7 55 . 3 49 . 0 52 . 1 54 . 2 59 . 6 62 . 0 64 . 6 66 . 3 70 . 0 73 . 9 79 . 1 78 . 7 84 . 9 86 . 8 95 . 1 90 . 8 97 . 8 10 4 . 4 10 9 . 1 58 3 1, 4 8 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 24 50 16 8 26 6 26 6 81 78 0 78 0 23 1 25 0 69 96 23 5 25 0 1, l 3 1.1 3 1 15 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 22 5 26 3 69 n 10 4 83 14 5 12 6 86 22 1 26 69 N/ A 10 0 3 39 19 6 26 9 49 2 N/A 10 0 33 15 8 89 25 0 24 8 22 3 N/A 10 0 ,I U o . I - I - I - I - I 22 7 22 7 IU Ù ) .l - . . - 1 . - 1 . . 1 . 21 6 21 6 8 12 12 10 0 10 0 10 0 98 10 0 10 0 9 45 10 0 92 80 98 10 0 29 8 82 1 10 0 10 0 10 0 20 0 98 10 0 10 0 9 45 10 0 92 80 98 10 0 49 8 1.0 2 1 50 50 50 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 42 84 Cl a s s i C a l i o r i a - D L C - I n i t i 5.5 5 5 DS M , C l a s i u r e i r - C u r i l D t 17 . 2 17 17 DS M C l a s s i O r i r - D L C - I r r w t i 13 . 2 13 13 DS M . C l a s s i O r e J R - D L C , R e s i d n l t i l 3.6 4 4 DS M C l a s s i W a s h i u r t O l - D L C - l r r Î 2 t i 2. 1 6.4 9 9 DS M C l a s s i W a s h i i 2 t o n - D L C - R e s i d e n t i l 1.2 3.6 5 5 DS M , Cl a s s i T o t l 42 . 8 10 . 0 53 53 DS M C l a s 2 C a l o r 0.7 0.9 0. 9 1.2 1.5 1. 6 1. 1. 7 1. 1.8 1.9 1.9 2.6 2.8 2.9 2. 6 2. 7 2.5 2.5 2.3 14 39 DS M C l a s 2 O r e l l O D 52 . 6 52 . 8 56 . 0 60 . 7 61 . 60 . 8 60 . 3 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 52 . 4 44 . 0 36 . 1 36 . 1 36 . 1 56 2 1.0 2 8 DS M C l a s 2 W a s h i i ~ 8.0 8.4 9. 0 8. 8 8.9 8.7 8.9 9.2 9.4 9. 6 10 . 8 1l. 8 1l. 5 12 . 5 12 . 8 9. 9 8. 5 8.9 8.9 9.3 89 19 4 SM C l a 2 T o t l 61 . 62 . 1 65 . 9 70 . 8 n. 1 71 . 70 . 9 63 . 3 63 . 4 63 . 8 65 . 0 66 . 2 66 5 67 . 7 68 . 1 64 . 9 55 . 2 47 . 5 47 . 5 47 . 6 66 5 1.2 6 1 R S o l a r C a D S t a n d a d 2 2 2 3 9 9 lQ R S o m P o o t 4 2 2 I 10 10 He a t e r 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 I 16 32 15 0 15 0 15 0 15 0 50 65 33 26 40 0 40 0 40 0 30 9 40 0 40 0 40 0 36 7 40 0 29 5 40 0 40 0 40 0 40 0 40 0 40 0 26 6 27 6 27 0 35 0 35 0 27 1 21 0 48 24 50 50 50 50 50 50 50 50 40 20 13 4 18 9 18 6 19 5 N/ A 70 N/ A 81 N/ A 20 0 84 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O PO R T F O L I O S En e r g y G a t e w a y C a s e 1 4 _ W M c o m p a r e d t o E n e r g y G a t e w a y C a s e 1 3 _ W M Re s o u r e d i f r e n c e s f r m b a e t r n s r r i o n s c e n a r i o a r e s h o w n P V R d i f r e n c e i n i c a t e d a s a n i n c r e a s e o r ( d e c r a s e ) . 16 0 10 5 20 0 20 0 15 71 26 39 1 17 6 - I 13 4 44 93 5 10 0 10 0 6) 17 (1 7 1 (8 1 L 17 6 . 1 - 1 - . . 13 4 . 1 - 1 49 72 . 2 2.2 4. 9 4.9 (1 . 6 ) 7. 4 23 . 1 29 29 1.4 (1 . 4 (1 . 6 13 . 6 16 . 9 (2 . 2 2.2 29 29 O.1 T 0.1 0.1 0.1 0.1 0.1 1 1 0.7 1 1. 1. 1. 3.4 9. 2 17 17 0.0 1 0.1 0.1 0.1 0.1 0. 2 0.1 I 1 0. 8 1 1. 1. 1.2 -- - 0. 2 0.2 3.7 0.3 9. 3 0. 1 ) 18 18 (0 3 2 (5 ) 19 19 19 18 15 -- - -- ¡. 6 26 19 ) 30 80 78 42 25 86 65 23 61 i- 15 (3 9 ) (1 3 ) 12 50 ~ 22 (7 9 89 30 21 18 1 N/ A Fa c t o 1 1 1 1 1 (9 s ¡ ( i o m r (1 0 0 j f .T - i - 1 (9 i r (4 5 ) (1 0 0 92 ) 80 (9 8 ) (1 0 0 ) (2 9 8 ) (8 2 1 ) ! (9 8 ) 1 10 0 ) 1 (1 0 0 ) - I (9 ) 1 (4 5 ) 10 0 92 (8 0 ) (9 8 ) (1 0 0 ) (2 9 8 (8 2 1 ) ' 50 - i .1 ' - 1 (5 0 50 0.3 1 - I 6.5 1 . I - I - . 1 -- 1 7 7 6.4 6.4 3. 6 (3 . 6 ) 6.4 3. 6 (1 0 . 0 0.3 6. 5 i- 7 7 0.0 0.0 0.2 0.2 0. 2 0.3 ) I 0 O.3 T - ì 0 0 0. 3 J . -l 0.0 0.0 0.2 0.2 0.2 0.3 1 I I (I (I I 3 36 -- - 14 (2 0 2 12 13 4 12 4 12 7 0 5 9 íÐ l 9 16 0 85 P A C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 1 5 _ W M c o m p a r e d t o E n e r g y G a t e w a y C a s e 1 3 _ W M Re s o u r e d i f r e n e s f r m b a s e t r n s m i i o n s c e n a r i a r e s h o w n . P V R d i f r e n c e i n d e a t e a s a n i n r e a s e o r ( d e c r a s e ) . Go h e n , 2 9 % C a p a c i t y F a c t o r in U t a h . 2 9 0 1 0 C a o a c ï . v F a c t o r Win d W Y E 3 5 % C a n a c n v F a c t o r Wi n W y ~ 3 5 % C a p a c ì y F a c t o r (2 ) (0 ) 42 20 0 20 0 i 20 0 T 20 0 T 20 0 T 20 0 T 20 0 T 18 .o t l W i n 93 (1 0 2 10 0 10 0 ) (2 1 47 15 l 15 2 . 1 20 0 . L 20 0 i 20 0 . 1 20 0 . L 20 0 i (6 1 DS M C l a s s i G o h e n . D L C - I r i i a t i (2 . 2 ) 2.2 DS M C l a s s i U t a h . C u r i h n t 4.9 4. 9 DS M , C l a s s i U t a h - D L C - R e s Î d n t i l l (2 . 2 ) 70 4 23 . 8 29 29 DS M , C l a s s 1 , W v m - C u r i l n t 1.4 (1 0 4 ) DS M C l a s s i T o t a l (2 . 2 ) 13 . 6 17 . 5 (2 . 2 ) 2.2 29 29 DS M , C l a s s 2 . I d a h o 0.1 0.1 0. 1 0.1 0.1 0. 1 I 1 DS M , C l a s 2 . U i a h 0.7 0.8 1. 1. 1. 2.6 9. 2 17 17 DS M . C l a s s 2 . W y o m g 0.0 0. 1 0.1 0.1 0. 1 0. 2 (0 . 1 ) I 1 DS M . C l a s s 2 T o t l 0.8 0.8 1. 1. 1. 0. 2 0.2 2.9 0.3 9. 3 0.1 18 18 0 3 f3 2 (8 ) 19 19 19 17 15 25 25 J. 9 1 91 80 10 2 30 16 86 (1 0 4 26 (2 3 0 26 39 20 8 2 N/ A 0 43 36 39 80 89 49 68 16 0 N/A 0 fa c t o r I I I I I (9 8 ) (1 0 0 (1 0 0 ) (9 ) (4 5 ) 10 0 1 1 92 80 98 10 0 (2 9 8 ) (8 2 1 (9 8 ) (l0 0 (1 0 0 (9 ) (4 5 ) (1 0 0 ) 1 92 80 98 10 0 (2 9 8 ) (8 2 1 50 50 (5 0 Ol e - R e s i d n t i a l T - T - T - T 0. 3 6.5 -- ~ "" . D L C - I m . l i - I 60 4 (6 . :m - D L C . R e s i d n l i a l i - l - . 1 - . L 3. 6 . ( 3 . 6 ) 60 4 3. 6 (1 0 . 0 0. 3 6.5 7 7 0.0 0.0 0. 2 0. 2 0.2 (0 . 3 I 0 0.3 I 0 0 0.3 . 1 - . L 0.0 0.0 0. 2 0. 2 0.2 (0 . 3 I 1 ii I ii ii 3 36 14 12 4 2 80 42 13 4 12 4 27 0 5 (1 6 (0 ) (0 ) 58 52 24 0 84 0 (1 1 \ N/ A 21li 0 . F o r t h e 2 0 Y e a r c o / u r n " " G r o w t h S t a t i o n s " a r e a n J O y e a r a v e r a g e r e f l e c t i n g t h e a v a i l a b l e y e a r s fr o m 2 0 2 1 - 2 0 3 0 . 86 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X C - E N E R G Y G A T E W A Y S C E N A R I O P O R T F O L I O S En e r g y G a t e w a y C a s e 1 6 _ W M c o m p a r e d t o E n e r g y G a t e w a y C a s e 1 3 _ W M Re s o u r e d i f r e n c e s f r m b a s e t r n s m i i o n s c n a i o a r s h o w n P V R d i f r e r i e i n i c a t e d a s a n i n r e a s e o r ( d e c r e a s e ) . (2 ) (0 ) 20 0 20 0 T 20 0 T 20 0 T 20 0 T 20 0 T 20 0 T 20 0 T 20 0 93 ii 0 2 10 0 10 0 21 11 2 15 i 15 2 - 1 20 0 . 1 20 0 1 20 0 . l 20 0 . 1 20 0 1 12 1 1z . 2 2.2 4. 9 4.9 1.6 ) 7. 4 23 . 1 29 29 1.4 1.4 (1 . 6 13 . 6 16 . 9 (2 . 2 ) 2.2 29 29 o. l T 0.1 0.1 0.1 0.1 0.1 (0 . 3 ) 1 0 0.7 1 1. 1. 1. 3.4 9.2 17 17 0.0 I 0.1 0.1 0.1 0.1 0.2 (0 . 1 ) 1 1 0.8 T 1. i. 1. 0. 2 0.2 3.7 0.3 9. 3 (0 . 3 ) (0 . 1 ) 18 18 CO 3 3 2 8 19 19 19 18 15 26 26 11 4 80 64 86 52 15 4 86 18 7 5 69 ) 0 3) (3 9 ) (5 5 ) 50 48 N/ A (0 31 14 8 3 58 89 9 73 fl 0 9 N/ A 0 Fa c t o r 1 I 1 1 I (9 š ) (L 0 0 ) ! i i o ô î (9 (4 5 (1 0 0 ) 92 ) 80 (9 8 (1 0 0 ) (2 9 8 ) (8 2 1 ) (9 8 ) 1 (1 0 0 ) (lO m l 9 45 ) (1 0 0 ) (9 2 80 (9 8 (1 0 0 ) (2 9 8 (8 2 1 ) 50 - 1 15 0 50 0.3 1 6.5 1 7 7 6.4 6.4 3. 6 (3 . 6 ) 6. 3. 6 flO . O - 0.3 6. 5 7 7 0.0 0.0 0.2 0.2 0.2 0.3 I 0 0. 3 1 - Î 0 0 O. 3 . . . . . 0.0 0.0 0.2 0.2 0.2 0.3 I I I fl I I) 3 36 )4 12 0 5 63 13 4 12 4 (2 7 0 ) 5 fl2 (0 ) 1 ii 19 0 87 llACIFICORP - 2011 IRP APPENDIX D - DETAIL CAPACITY EXPANSION RESULTS ApPENDIX D - SYSTEM OPTIMIZER DETAILED MODELING RESULTS This appendix reports the detailed portfolio resource selection tables for each of the scenaro development cases outlined in Chapter 7. These tables are outputs from the System Optimizer model used durng portfolio development. 89 PA C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ta b l e D . l - R e s o u r c e N a m e a n d D e s c r i p t i o n CC C T F 2 x l CC C T H CC S H u n t e r - U n i t 3 ( R e p l a c e s O r i g i n a l U n i t ) CH P - B i o m a s s CH P - R e c i p r o c a t i n g E n g i n e Co a l P l a n t T u r b i n e U p g r a d e s DS M , C l a s s 1 , G o s h e n - D L C - l r r i g a t i o n DS M , C l a s s 1 , U t a h - C o o l K e e p e r DS M , C l a s s 1 , U t a h - C u r a i l m e n t DS M , C l a s s 1 , U t a h - D L C - I r r i g a t i o n DS M , C l a s s 1 , U t a h - D L C - R e s i d e n t i a l DS M , C l a s s 1 , U t a h - S c h e d T h e r m E n e r g y S t o r a g e DS M , C l a s s 1 , W y o m i n g - C u r i l m e n t DS M , C l a s s 2 , G o s h e n DS M , C l a s s 2 , U t a h DS M , C l a s s 2 , W y o m i n g DS M , C l a s s 3 , U t a h , C r i t i c a l P e a k P r i c i n g , C o m m / l n d u s DS M , C l a s s 3 , U t a h , D e m a n d B u y b a c k , C o m r n n d u s DS M , C l a s s 3 , U t a h , R e a l - T i r n e P r i c i n g , C o m r n n d u s DS M , C l a s s 3 , U t a h , T i r n e o f Us e , I r r i g a t i o n DS M , C l a s s 3 , U t a h , T i m e o f Us e , R e s i d e n t i a l DS M , C l a s s 3 , W y o m i n g , C r i t i c a l P e a k P r i c i n g , C o m m / I n d u s DS M , C l a s s 3 , W y o m i n g , D e m a n d B u y b a c k , C o m r n n d u s DS M , C l a s s 3 , W y o m i n g , R e a l - T i r n e P r i c i n g , C o m m n d u s DS M , C l a s s 3 , W y o r n i n g , T i m e o f Us e , I r r g a t i o n FO T M e a d 3 r d Q t r H L H FO T M o n a - 3 3 r d Q t r H L H FO T M o n a - 4 3 r d Q t r H L H Co m b i n e C y c l e C o m b u s t i o n T u r b i n e F - M a c h i n e 2 x l w i t h Du c t F i r i n g Co m b i n e C y c l e C o m b u s t i o n T u r b i n e H - M a c h i n e l x l w i t h D u c t F i r i n g IR P C a r b o n C a p t u r e & S e q u e s t r a t i o n H u n t e r 3 Co m b i n e d H e a t a n d P o w e r - B i o m a s s Co m b i n e d H e a t a n d P o w e r - R e c i p r o c a t i n g E n g i n e Co a l P l a n t T u r b i n e U p g r a d e s IR P D S M C l a s s i ( B u b b l e ) D i r e c t L o a d C o n t r o l - I r r i g a t i o n DS M - C l a s s 1 - U t a h C o o l K e e p e r IR P D S M C l a s s 1 ( B u b b l e ) C u r t a i l m e n t IR P D S M C l a s s 1 ( B u b b l e ) D i r e c t L o a d C o n t r o l - I r r i g a t i o n IR P D S M C l a s s 1 ( B u b b l e ) D i r e c t L o a d C o n t r o l - R e s i d e n t i a l IR P D S M C l a s s 1 ( B u b b l e ) S c h e d u l e d - T h e r m a l E n e r g y S t o r a g e IR P D S M C l a s s 1 ( B u b b l e ) C u r t a i l m e n t DS M , C l a s s 2 , G o s h e n DS M , C l a s s 2 , U t a h DS M , C l a s s 2 , W y o m i n g DS M , C l a s s 3 , U t a h , C r i t i c a l P e a k P r i c i n g , C o m r n e r c i a l - I n d u s t r i a l DS M , C l a s s 3 , U t a h , D e m a n d B u y b a c k , C o m m e r c i a l - I n d u s t r i a l DS M , C l a s s 3 , U t a h , R e a l - T i m e P r i c i n g , C o m m e r c i a l - I n d u s t r i a l DS M , C l a s s 3 , U t a h , T i m e o f Us e , I r r i g a t i o n DS M , C l a s s 3 , U t a h , T i m e o f Us e , R e s i d e n t i a l DS M , C l a s s 3 , W y o m i n g , C r i t i c a l P e a k P r i c i n g , C o m m I n d u s DS M , C l a s s 3 , W y o r n i n g , D e r n a n d B u y b a c k , C o m m I n d u s DS M , C l a s s 3 , W y o r n i n g , R e a l - T i m e P r i c i n g , C o m r n n d u s DS M , C l a s s 3 , W y o r n i n g , T i m e o f Us e , I r r i g a t i o n Fr o n t O f f c e T r a n s a c t i o n - 3 r d Q u a r t e r H L H P r o d u c t Fr o n t O f f c e T r a n s a c t i o n - 3 r d Q u a r t e r H L H P r o d u c t Fr o n t O f f c e T r a n s a c t i o n - 3 r d Q u a r t e r H L H P r o d u c t 90 P A C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S FO T U t a h 3 r d Q t r H L H Ge o t h e r m a l , B l u n d e l l 3 Ge o t h e r m a l , G r e e n f i e l d Gr o w t h R e s o u r c e G o s h e n Gr o w t h R e s o u r c e U t a h N o r t h Gr o w t h R e s o u r c e W y o r n i n g Mi c r o S o l a r - W a t e r H e a t e r Nu c l e a r SC C T A e r o U t a h Wi n d , W y o m i n g N E , 3 5 % C a p a c i t y F a c t o r Wi n d , U t a h , 2 9 % C a p a c i t y F a c t o r Wi n d , W y o r n i n g , 3 5 % C a p a c i t y F a c t o r Fr o n t O f f c e T r a n s a c t i o n - 3 r d Q u a r t e r H L H P r o d u c t Ge o t h e r m a l ( E a s t - B l u n d e l l , E a s t - G r e e n f i e l d , W e s t - G r e e n f i e l d ) Ge o t h e r m a l ( E a s t - B l u n d e l l , E a s t - G r e e n f i e l d , W e s t - G r e e n f i e l d ) Gr o w t h R e s o u r c e ( G o s h e n ) Gr o w t h R e s o u r c e ( U t a h N o r t h ) Gr o w t h R e s o u r c e ( W y o r n i n g ) Mi c r o S o l a r - S o l a r W a t e r H e a t i n g Nu c l e a r Si r n p l e C y c l e C o r n b u s t i o n T u r b i n e A e r o Wi n d , P r o j e c t I I Wi n d , U t a h , 2 9 % C a p a c i t y F a c t o r (B u b b l e ) W i n d 3 5 % C a p a c i t y F a c t o r CC S B r i d g e r - U n i t 1 ( R e p l a c e s O r i g i n a l U n i t ) CC S B r i d g e r - U n i t 2 ( R e p l a c e s O r i g i n a l U n i t ) CH P - B i o m a s s CH P - R e c i p r o c a t i n g E n g i n e Co a l P l a n t T u r b i n e U p g r a d e s Di s t r i b u t i o n E n e r g y E f f c i e n c y , W a l l a W a l l a Di s t r i b u t i o n E n e r g y E f f c i e n c y , Y a k i m a DS M , C l a s s 1 , O r e g o n / C a l i f o r n i a - C u r a i l m e n t DS M , C l a s s 1 , O r e g o n / C a l i f o r n i a - D L C - I r r i g a t i o n DS M , C l a s s 1 , O r e g o n / C a l i f o r n i a - D L C - R e s i d e n t i a l DS M , C l a s s 1 , O r e g o n / C a l i f o r n i a - D L C - W a t e r H e a t e r DS M , C l a s s 1 , W a l l a W a l l a - D L C - I r r i g a t i o n DS M , C l a s s 1 , W a l 1 a W a l 1 a - D L C - R e s i d e n t i a l DS M , C l a s s 1 , Y a k i m a - D L C - I r r i g a t i o n DS M , C l a s s 1 , Y a k i m a - D L C - R e s i d e n t i a l DS M , C l a s s 2 , O r e g o n / C a l i f o r n i a DS M , C l a s s 2 , W a l 1 a W a l 1 a IR P C a r b o n C a p t u e & S e q u e s t r a t i o n B r i d g e r 1 ( R e p l a c e s O r i g i n a l U n i t ) IR P C a r b o n C a p t u e & S e q u e s t r a t i o n B r i d g e r 2 ( R e p l a c e s O r i g i n a l U n i t ) Co m b i n e d H e a t a n d P o w e r - B i o r n a s s Co m b i n e d H e a t a n d P o w e r - R e c i p r o c a t i n g E n g i n e Co a l P l a n t T u r b i n e U p g r a d e s Di s t r b u t i o n E n e r g y E f f c i e n c y , W a l 1 a W a l l a Di s t r i b u t i o n E n e r g y E f f c i e n c y , Y a k i r n a IR P D S M C l a s s 1 ( B u b b l e ) C u r a i l m e n t lR P D S M C l a s s 1 ( B u b b l e ) D i r e c t L o a d C o n t r o l - I r r i g a t i o n IR P D S M C l a s s 1 ( B u b b l e ) Di r e c t L o a d C o n t r o l - R e s i d e n t i a l IR P D S M C l a s s 1 ( B u b b l e ) D i r e c t L o a d C o n t r o l - W a t e r H e a t e r lR P D S M C l a s s 1 ( B u b b l e ) D i r e c t L o a d C o n t r o l - I r r g a t i o n IR P D S M C l a s s 1 ( B u b b l e ) D i r e c t L o a d C o n t r o l - R e s i d e n t i a l IR P D S M C l a s s 1 ( B u b b l e ) D i r e c t L o a d C o n t r o l - I r r i g a t i o n IR P D S M C l a s s 1 ( B u b b l e ) D i r e c t L o a d C o n t r o l - R e s i d e n t i a l DS M , C l a s s 2 , - O r e g o n / C a l i f o r n a DS M , C l a s s 2 , - W a l 1 a W a l l a 91 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S DS M , C l a s s 2 , Y a k i m a DS M , C l a s s 3 , C a l i f o r n i a , T i m e o f Us e , I r r i g a t i o n DS M , C l a s s 3 , G o s h e n , C r i t i c a l P e a k P r i c i n g , C o m m n d u s DS M , C l a s s 3 , G o s h e n , T i m e o f Us e , I r r i g a t i o n DS M , C l a s s 3 , O r e g o n , C r i t i c a l P e a k P r i c i n g , C o m m / I n d u s DS M , C l a s s 3 , O r e g o n , T i m e o f Us e , I r r i g a t i o n DS M , C l a s s 3 , W a l l a W a l l a , T i m e o f Us e , I r r g a t i o n DS M , C l a s s 3 , Y a k i m a , T i m e o f Us e , I r r i g a t i o n FO T C O B 3 r d Q t r H L H FO T M i d C o l u r n b i a 3 r d Q t r H L H FO T M i d C o l u m b i a 3 r d Q t r H L H 1 0 % P r i c e P r e m i u m FO T S o u t h C e n t r a l O r e g o n I o r t h e r n C a l i f o r n i a 3 r d Q t r H L H Gr o w t h R e s o u r c e O r e g o n / C a l i f o r n i a Gr o w t h R e s o u r c e W a l l a W a l l a Gr o w t h R e s o u r c e Y a k i m a Mi c r o S o l a r - P h o t o v o l t a i c Or e g o n S o l a r C a p S t a n d a r d Or e g o n S o l a r P i l o t Ut i l t y B i o m a s s Ut i l i t y S c a l e S o l a r - P h o t o v o l t a i c Wi n d , G o s h e n , 2 9 % C a p a c i t y F a c t o r Wi n d , O r e g o n , 2 9 % C a p a c i t y F a c t o r Wi n d , W a l l a W a l l a , 2 9 % C a p a c i t y F a c t o r Wi n d , W a l l a W a l l a , 2 9 % C a p a c i t y F a c t o r Wi n d , W a s h i n g t o n , 2 9 % C a p a c i t y F a c t o r Wi n d , Y a k i m a , 2 9 % C a p a c i t y F a c t o r Wi n d , Y a k i m a , 2 9 % C a p a c i t y F a c t o r DS M , C l a s s 2 , - Y a k i r n a DS M , C l a s s 3 , C a l i f o r n i a , T i m e o f Us e , I r r i g a t i o n DS M , C l a s s 3 , G o s h e n , C r i t i c a l P e a k P r i c i n g , C o m m e r c i a l - I n d u s t r i a l DS M , C l a s s 3 , G o s h e n , T i r n e o f Us e , I r r i g a t i o n DS M , C l a s s 3 , O r e g o n , C r i t i c a l P e a k P r i c i n g , C o m m / n d u s DS M , C l a s s 3 , O r e g o n , T i m e o f Us e , I r r i g a t i o n DS M , C l a s s 3 , W a l l a W a l i a , T i r n e o f Us e , I r r i g a t i o n DS M , C l a s s 3 , Y a k i m a , T i m e o f Us e , I r r i g a t i o n Fr o n t O f f c e T r a n s a c t i o n - ( B u b b l e ) 3 r d Q u a r t e r H L H P r o d u c t Fr o n t O f f c e Tr a n s a c t i o n - ( B u b b l e ) 3 r d Q u a r e r H L H P r o d u c t Fr o n t O f f c e T r a n s a c t i o n - ( B u b b l e ) 3 r d Q u a r t e r H L H P r o d u c t Fr o n t O f f c e T r a n s a c t i o n - ( B u b b l e ) 3 r d Q u a r e r H L H P r o d u c t Gr o w t h R e s o u r c e ( O r e g o n / C a l i f o r n i a ) Gr o w t h R e s o u r c e ( W a l l a W a l l a ) Gr o w t h R e s o u r c e ( Y a k i m a ) Mi c r o S o l a r - P h o t o v o l t a i c Or e g o n S o l a r C a p a c i t y S t a n d a r d Or e g o n S o l a r P i l o t p r o g r a m Ut i l i t y B i o m a s s Ut i l i t y S c a l e S o l a r - P h o t o v o l t a i c Wi n d , G o s h e n , 2 9 % C a p a c i t y F a c t o r Wi n d , O r e g o n , 2 9 % C a p a c i t y F a c t o r Wi n d - W a l l a W a l l a , 2 9 % C a p a c i t y F a c t o r Wi n d - W a l l a W a l l a , 2 9 % C a p a c i t y F a c t o r Wi n d , W a s h i n g t o n , 29 % C a p a c i t y F a c t o r Wi n d - Y a k i m a , 2 9 % C a p a c i t y F a c t o r Wi n d - Y a k i m a , 2 9 % C a p a c i t y F a c t o r No t e s o n M a r k e t a n d T o p o l o g y B u b b l e s : Pl e a s e s e e t h e T r a m ~ m i s s i o n T o p o l o g y c h a r t i n C h a p t e r 7 f o r t h e " b u b b l e s " u s e d f o r l o c a t i o n o f mo d e l e d r e s o u r c e o p t i o n s . 92 PA C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Th i s s e c t i o n p r o v i d e s t h e S y s t e m O p t i m i z e r p o r t f o l i o b u i l d t a b l e s f o r e a c h o f t h e c a s e s c e n a r i o s a s d e s c r i b e d i n t h e p o r t f o l i o de v e l o p m e n t s e c t i o n o f C h a p t e r 7 . . C o r e C a s e S t u d i e s - C a s e 1 t o 1 9 . H a r d C a p S t u d i e s - C a s e 1 5 t o 1 8 . B u s i n e s s P l a n C a s e S t u d y - C a s e 1 9 . C o a l U t i l i z a t i o n S e n s i t i v i t y C a s e S t u d i e s - C a s e 2 0 t o 2 4 . L o a d F o r e c a s t i n g S e n s i t i v i t y C a s e S t u d i e s - C a s e 2 5 t o 2 7 . R e n e w a b l e R e s o u r c e S e n s i t i v i t y C a s e s - 2 8 t o 3 0 a . D e m a n d - s i d e M a n a g e m e n t S e n s i t i v i t y C a s e s - 3 1 t o 3 3 93 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ta b l e D . 2 - T o t a l P o r t f o l i o C u m u l a t i v e C a p a c i t y A d d i t i o n s b y C a s e a n d R e s o u r c e T y p e , 2 0 1 1 - 2 0 3 0 20 - y e a r r e s o u r c e t o t a l s ( M W c a p a c i t y ) Gr o w R e s o i . W a l W a l l Gr o w R e s i . O r e g o n . ! C a l i f o r n i a Gr o w R e s o i . Y a k i m a 1; T r a n s m i s s i o n S c e n a r i o I s r e f e r e n c i n g t h e s c e n a r i o a s d e s c r b e d I n t h e P o r t o l i o C a s e D e v e l o p m e n t p a p e r . 94 P A C I F I C O R P - 2 0 1 1 1 R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ta b l e D . 3 - C o r e C a s e S y s t e m O p t i m i z e r P V R R R e s u l t s PV R R b y C a s e ( $ m i o n s ) '" i i " ' ¡ S $3 0 , 9 3 6 - Ca s e - 0 2 No n e Me d i Ex t e n s i o n t o 2 0 1 5 $3 0 , 8 8 4 Ca s e - 0 3 Me d i Lo w Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $3 9 , 5 8 1 Ca s e - 0 4 I CO i T a x Hi g h Lo w Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $4 , 3 4 6 Ca s e - 0 5 I CO i T a x I Lo w t o v e r y h i g h Lo w Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $4 0 , 0 5 8 Ca s e - 0 6 I CO i T a x I Lo w t o v e r y h i g h Lo w Cu r e n t R P S $3 9 , 8 1 4 Ca s e - 0 7 I CO i T a x Me d i u Me d i Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $4 0 , 7 7 2 Ca s e ~ 0 8 I CO i T a x Hi g h Me d i Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $4 6 , 0 1 5 Ca s e - 0 9 I CO i T a x I Lo w t o v e r y h i g h Me d i Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $4 1 , 5 9 9 Ca s e - 0 9 a I CO i T a x I Lo w t o v e r y h i g h Me d i Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $4 1 , 6 1 6 Ca s e - l O I CO i T a x I Lo w t o v e r y h i g h Me d i Cu r e n t R P S $4 1 , 2 7 7 Ca s e - I I I CO i T a x I Me d i Hi g h Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $4 2 , 0 9 2 Ca s e - 1 2 I CO i T a x I Hi g h Hi g h Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $4 6 , 9 5 4 Ca s e - 1 3 I CO i T a x I Lo w t o v e r y h i g h Hi g Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $4 2 , 7 0 5 Ca s e - 1 4 I CO i T a x I Lo w t o v e r y h i g h Hi g Cu r e n t R P S $4 1 , 9 8 2 Ca s e - 1 5 Me d i Lo w Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $3 1 , 0 4 9 Ca s e - 1 6 Me d i Me d i u m Ex t e n s i o n t o 2 0 1 5 Cu r r e n t R P S $3 2 , 8 4 5 Ca s e - 1 7 Me d i Hi g h Ex t e n s i o n t o 2 0 1 5 Cu r r e n t R P S $3 4 , 9 6 8 Ca s e - 1 8 Me d i Me d i Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $3 4 , 9 2 6 Ca s e - 1 9 Me d i Me d i Ex t e n s i o n t o 2 0 1 5 Cu r e n t R P S $4 2 , 5 5 6 95 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ta b l e D . 4 - C o r e C a s e P o r t f o l i o s ( C a s e 1 t o 1 4 ) 1. 2 2 2 il53 35 45 80 80 35 35 Ca n a c i t F a c t o T 44 23 12 23 6 35 14 3 44 23 12 23 6 35 14 3 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1. 0 1.0 1. 0 1.0 1.0 10 20 0.8 0. 8 0.8 0.8 0.8 4 4 5.5 5 1l 1l .li o T 8 2 8 10 21 3 25 25 1l 20 32 32 1l 3 1l 14 S. . . . T 3 3 3 17 50 23 5 90 95 I I 1 I I I 2 2 1 2 I 2 2 3 3 3 3 3 3 2 13 36 46 55 59 44 64 41 44 44 45 48 51 55 52 55 55 60 56 59 59 62 48 9 1.0 5 3 3 4 4 5 5 5 6 6 6 7 8 9 10 12 13 17 18 21 26 28 51 21 l 49 59 64 50 70 47 51 52 53 56 61 65 64 69 71 79 76 82 88 92 55 2 1,3 0 0 2.6 4 2. 6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2.3 7 2. 3 7 2.3 7 2.3 7 23 28 16 8 26 4 26 4 99 80 40 20 O J 20 0 20 0 0 20 0 4 15 4 19 1 11 5 57 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 22 11 6 10 3 10 7 13 1 12 3 12 3 12 7 14 0 N/A 10 0 8 87 18 2 34 7 37 6 N/A 10 0 64 8 13 0 15 6 17 8 20 2 26 3 NIA 10 0 Co a l P l a T w U n l a d s 3.7 8.3 12 12 Ge o t n n a l G r n f i e l d 70 70 70 Uli 1 i B i o s s 50 50 50 Cl i p . B i o 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4. 2 4. 2 4.2 4.2 4. 2 4.2 4.2 4.2 4. 2 4.2 4. 2 4.2 4.2 42 84 Cl i P - R e c ' . 0.3 0.3 0.3 0.3 0.3 2 2 DS M . C l s I W a l b W a n a ~ D L C - R e s i d e n 1 1 I I I DS M . C l a s I W a l l W a B a - D L C - I r r t i 3 3 3 DS M . C l a I O r e i m C a l i u r - C u r i h n t 17 17 17 DS M C l a s s J O r e i i C a l i c . - Î a - D L C . R e s i n t l 6 6 6 DS M C l a s l O r e o o o / C a l i c m . D L C - W a t e H e a t e r 4 4 4 DS M C l a s I O r e o o a l i u m - D L C . l r t i 18 18 18 DS M C l a s I Y a k . D L C - R e s i d n t i a l 4 4 4 DS M C l a I Y a k D - D L C - l l T t i o 6 6 6 8M C l a s I T O O I 50 10 60 60 OS M C l a s 2 . W a l b W a l l 4 4 4 5 5 5 5 4 4 4 4 5 5 5 5 4 4 3 3 3 44 85 DS M C l a s s 2 O r u o / C a l i o r 51 51 54 59 60 59 59 51 51 51 51 51 52 52 52 52 44 36 36 36 54 7 1,0 0 9 DS M C l a s s 2 Y a k i 10 1l 6 6 6 6 6 6 6 6 '7 7 7 8 8 6 5 6 6 6 68 13 í1 S M C l a s 2 T o t l 65 66 65 70 71 69 69 61 61 61 62 63 63 64 64 62 53 45 45 45 65 9 1.2 2 6 i1 r e i r S o l a C a D S t a n d r d 2 2 2 3 9 9 nS o l a Pik i t 4 2 2 1 10 10 So l a - W a t e r H e a t e r 1. 8 1 1.8 1 1.8 1 1.8 1 0. 9 7 1. 9 0.9 7 0.9 7 0. 9 7 0. 9 7 0.9 7 0. 9 7 12 15 15 0 15 0 15 0 15 0 50 65 33 40 0 40 0 40 40 0 40 0 40 0 40 0 33 7 40 0 30 9 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 35 4 37 2 24 4 20 5 45 22 50 50 50 50 2 50 50 50 33 50 50 50 50 50 5l 50 50 35 39 NIA 10 0 NIA 4 NIA 11 9 0', ' " , R Z ' i R' .' , ;" ~ " f " , ' " R ",' ~ ~ , ~~ ~ ''\ '1 , 8 , ,,. ~ '~ , ~ " ~ ~ ~ ',; ' ! ' ¡ , § ''' . ' ' '" ~ ,~ ~ ~ ~" 1 :W ' ¡ w * F r o n t o f f e t r n s a c t i o a n d g r t h r e s o m c e a m u n t s r e f l t o n - y e a r t r n s a c t i o n p e i o , a n d a r e n o t a d d i . *' F r o n o f c e t r n s a c t i n s a r e r e p o d a s a 2 0 - y e a r s t m u a l a v e r a g e . G r t h r e s o u e s a r e r e p o d a s a i o - y e a r a v e r a g e . 96 P A C I F i C O R P - 2 0 1 1 1 R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S :C C T F 2 x 1 b:¿ : : ,O J " ! 1.2 2 2 1, 2 2 2 :C C T H 47 5 47 5 47 5 'o a t P l a t T u r ~ U n . . d e s 12 . 1 18 . 9 1. 8 18 . 0 2.4 51 53 eo t e r m a L B l u e R 3 35 45 80 80 'H P - B k m s s 1.0 1. 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 10 20 'H P ~ R e c i n o c a t i n a E n i r e 0. 8 0.8 0.8 0,8 0.8 0.8 0.8 0. 8 6 6 DS M C l a s s 1 V t a h - C o o l k e n P f 5. 5 5 11 11 DS M C l a s s I G o h e n - D L C - I r r w a t X 8 2 8 10 DS M , C l a s s i U t a h . Cu r i l e n t 21 5 26 26 DS M C l a s s i , U t a h . O L e . R e s i d n t i l 11 20 5 37 37 DS M e h s s 1 , U t a h - D L C . l m i i t i 11 3 11 14 DS M C l a s s i V t a h . S e h e d T h e r E n e r ø S t Q r l Y 2 2 3 3 DS M , C l a s s i T o t a l 17 48 20 10 2 5 97 10 2 DS M , C k I s s 2 , G o h e n I I 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 38 DS M , C l a s s 2 . U t a h 46 57 59 43 44 47 52 55 56 74 51 55 53 55 55 60 56 59 63 66 53 5 1, 1 0 9 DS M . C h i s s 2 , W v o m i n o ~ 3 4 4 4 5 6 6 7 7 8 8 9 10 12 13 17 18 21 26 28 55 21 4 3M , C l a s s 2 T ~ I 49 62 64 48 51 55 60 64 65 84 61 66 65 70 . 7 1 79 76 82 92 95 60 3 1.3 6 1 2. 6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2.6 4 24 24 16 8 26 4 26 4 39 73 37 20 0 I 20 0 20 0 16 62 20 0 20 0 10 8 54 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 20 70 12 5 14 9 14 8 10 9 11 i 12 5 13 8 N/ A 10 0 21 10 9 15 0 37 7 34 4 N/ A 10 0 50 11 6 19 3 15 0 27 3 21 9 N/ A 10 0 3.7 8.3 12 12 It i t n B i o m a s s 50 50 50 'H P - B D m a s s 4. 2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4. 2 4. 2 4.2 4. 2 4.2 4.2 4. 2 4.2 4.2 4. 2 4.2 4.2 42 84 'H P - R e c Ï D o c a t m O ' E n i r e 0. 3 0.3 0.3 0.3 0. 3 0.3 0.3 0.3 3 3 DS M . C l a s s i W a l l W a ß a . D L C - R e s i d n t i a l I I 1 DS M . C l a s s i W a l l W a l l . D L C - I r r i l J l l t i 3 3 3 DS M . C l a s s 1 O r e g o n C a t i o m - C u r t i h e n t 17 17 17 DS M C l a s s 1 O r ø o / C a l i o r i a - D L C - R e s n e n t i a l 6 6 6 DS M C l a s s i O r e a r / C a l i o r i i . D L C - W a t e r H e a t e 4 4 4 DS M , C l a s s i O r e i i C a l i o m i a - D L C - I r . . t i m 18 18 18 DS M C l a s s i Y a k - O l e - R e s i d e n t i l 4 4 4 DS M C h s s 1 Y a k - D L C - l r w a t I m 6 6 6 DS M C l a s s i T o t l 50 10 60 60 DS M , C e s s 2 , W a l l W a O a 4 4 5 5 5 5 5 4 5 5 4 5 5 5 5 4 4 3 3 4 45 87 DS M , C l a s s ' 2 , O r e l l o n l C a l i o r n i a 51 51 54 59 60 60 59 52 52 52 51 51 52 52 52 52 44 36 36 36 55 0 1.0 1 1 DS M , C l a s s 2 , Y a k i a 10 11 6 6 6 6 . 7 7 7 7 7 7 7 8 8 6 5 6 6 7 73 14 1 DS M . C h s s 2 T o t a l 65 66 65 70 71 70 71 63 63 64 63 63 63 64 64 62 53 46 46 46 66 9 1,2 3 9 Or e o o S o l a r C a n S t a n d a r d 2 2 2 3 9 9 Or e g o n S o l a r P i l o t 4 2 2 I 10 10 Mi : r o S o l a r . W a t e r H e a t e r 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1. 8 1 16 16 FO T C O B 3 , d O t H L H 15 0 15 0 15 0 15 0 50 . 65 33 FO T M k l o l m n b i a 3 r d O t r H L H 40 0 40 0 40 0 31 5 40 0 40 0 40 0 37 1 40 0 32 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 34 9 37 0 'T M i d C o h u i a 3 r d O t H L H 1 0 0 1 0 P r i c e P r e m i 24 4 20 5 45 22 'T S o u h C e n t r l O r g o n I o r t h e m C a l i r n 3 r d Q t H L H 50 50 50 50 50 50 50 43 50 50 50 50 50 50 50 50 35 40 90 14 6 10 7 20 3 23 6 N/ A 78 N/ A 68 N/ A 10 0 ;'" , ~ l \ ; ' , : ~~ ' § % ~~ i n ~ ; : " ~ ~ : " ~ " , ~~ ~ \ i t ~ , ~~ " " : ' ' ' , ': l % ~ ~ ~ ' - .' ~R ¡ y ~w ' ~ :' ~ " ' ~ . . * ~, '0 " ' % 5 'll : ~ , " * F r o n t o f f i c e t r n s a c t i o a n d g r w t h r e s o u e a m o u n t r e f l c t o n e . y e a r t r n s a c t i o p e r i o d , a n d a r e n o t ad d i t v e . ** F r o n o f f e t r a n s a c t k m s a r e r e p o d a s a 2 O . y e a r a n n u a l a v e r a g e . G r h r e s o u c e s a r e r e p o e d a s a i o - y e a r a v e r a g e . 97 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ca s e 3 'C C T F 2 K 1 1.2 2 2 CC T l I 47 5 47 5 03 1 P l a n t T u r b i n e U de s 12 . 1 18 . 9 1.8 18 . 0 2.4 53 ie o t e r m B l u d e D 3 35 45 80 ie o t e m i G r e e n f i e l d 35 35 Win W m i 3 5 % C a c i t F a c t o r 13 49 21 8 9 4 34 13 9 .o t a l W i n 13 49 21 8 9 4 34 13 9 :H P - B i o s 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 10 20 CH P - R e c ' o c a t i n E n . e 0. 8 0. 8 0.8 0. 8 0.8 0.8 0.8 5 5 DS M C l a s s 1 U t a h . C o o l k e e r 5. 5 5 11 11 DS M C l a s i G o h e n . D L C - I r r ' i i o n 8 8 8 DS M C l a s s i U t a h - C u r i h n t 21 5 26 26 DS M C l a s s J U t a h - O L e - R e s i d n t i a l 11 20 5 37 37 DS M C l a s s i U t a h - O L e - l i t ' l i 11 11 11 DS M C l a s s i U t a h - S c h e d T h e o n E n e r S e 3 3 3 8M C l a s I T o t a l 17 50 20 5 5 97 97 DS M C l a s s 2 G o s h e n 1 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 38 OS Cla s 2 U t a 46 55 59 43 44 47 50 53 55 64 52 60 57 59 60 65 60 63 64 69 51 7 1.1 2 5 OS Cla s 2 W 3 4 4 4 5 6 6 7 7 8 8 9 10 12 13 17 20 23 29 28 55 22 1 SM . C l a s s 2 T o t l 49 59 64 48 51 55 58 62 64 74 62 70 69 74 75 84 82 89 95 99 58 6 1,3 8 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2. 3 7 24 37 16 8 26 4 26 4 24 72 36 20 0 20 0 20 0 17 57 19 8 20 0 10 7 54 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 20 32 68 90 17 9 10 9 19 6 16 1 13 9 N/A 10 0 20 16 8 35 2 35 3 10 7 N/A 10 0 33 4 32 9 33 6 N/A 10 0 oil P l a T u r b i e U de s 3.7 8.3 12 12 ie o l e m i G r e e t U i e l d 70 35 70 10 5 HP - B i o s 4.2 4.2 4.2 4. 2 4. 2 4.2 4.2 4.2 4.2 4.2 4. 2 4. 2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 42 84 li P - R e c ' a" 0.3 0.3 0.3 0.3 1 1 DS M C l a s s i W a l h W a l h - D L C - R e s i d n t i i l 1 1 1 DS M C l a s s i W a l l W a l h - D L C - I , . û c 3 3 3 DS M C l a s s i O r e o n C a l i o m . . u r i h n t 17 17 17 DS M C l a s s J O r e o n / C a l i o r - D L C - R e s i d n t i a l 6 6 6 DS M C l a s s i O r e o n C a l i o r n i a - D L C - W a t e r H e a t e r 4 4 4 DS M C l a s s i O r e Ca l i o r i a - D L C - I li 18 18 18 DS M C l a s s 1 Y a k - D L C - R e s i d n t l 4 4 4 OS Cl a s s i Y a k - D L C - I ii i 6 6 6 8M C l a s 1 T o t a l 50 6 4 60 60 DS M C l a s Wa l l Wa l l 4 4 4 5 5 5 5 4 5 5 4 5 5 5 5 4 4 . 3 3 4 45 87 OS M C l a s ar e Ca l i o r 51 51 54 59 60 60 59 52 52 52 51 51 52 52 52 52 44 36 36 36 55 0 1,0 1 4 OS M C l a s 2 Y a k 8 11 6 6 6 6 6 7 7 7 7 7 7 8 8 6 5 6 6 7 70 13 8 DS M . C l a s s 2 T o t a l 63 66 65 70 71 70 70 63 63 64 63 63 64 65 65 63 53 46 46 46 66 5 1.2 3 9 So l a C a S t a d a r d 2 2 2 3 9 9 So l a P i l o t 4 2 2 1 10 10 Wa t e r He a t e r 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1. 8 1 0.9 7 0.9 7 16 18 15 0 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 29 9 40 0 40 0 40 0 37 0 40 0 69 40 0 40 0 40 0 40 0 40 40 0 40 0 40 0 34 7 33 7 24 4 20 6 45 23 50 50 50 50 50 50 50 35 18 52 13 1 20 9 20 5 20 3 20 0 N/A 10 0 N/A 10 0 N/A 10 0 * F r o n t o f l c e t r a n s a c t i o a n d g r w t h r e s o u c e a m o u n t s r e f l c t o n e - y e a r t r a n s a c t i o n p e r i , a n d a r e n o t a d d i t i . .. F r o n t o f f i c e t r n s a c t i n s a r e r e p o t e d a s a 2 0 - y e a r a n n u a l a v e r a g e . G r o w h r e s o u c e s a r e r e p o r t e d a s a l ( ) y e a r a v e r a g e . 98 P A C I F i C O R P - 2 0 1 1 l R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S 28 0 1,2 2 2 47 5 47 5 47 5 47 5 1,4 2 5 ,d e s I 12 . 1 I 18 . 9 1 1.8 1 I 18 . 0 2.4 51 53 35 45 80 80 35 35 oC t y F a c t o r I 12 49 20 8 9 4 34 13 6 12 49 20 8 9 4 34 13 6 HP - B i o m a s s 1.0 1.0 1.0 1.0 1. 0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1. 0 10 20 HP - - R e c l n o c a t i ø E n i r e 0.8 0.8 0. 8 0.0 2 2 DS M C l a s s i . U t a h . C o o k e e n t f 5.5 5 II II DS M C l a s s i G o h e n - D L C . T l ' t i o 8 2 8 10 DS M C l a s s i U t a h . C u r i h n t 21 5 26 26 DS M C l a s s i U t a h - D L C - R e s i d n t i i l II 21 5 37 37 DS M C l a s s i U t a b - D L C - I r r i i m t i o II 3 II 14 DS M , C l a s s 1 , U t a h - S c h e d T h e o n E n e r l J S t o r l J 3 3 3 DS M , C m s s i T o l a l 16 51 20 10 5 97 10 2 DS M , C l a s s 2 G o h e n I I I I I 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 14 41 DS M _ C l a s s 2 U t a h 47 54 59 43 44 51 52 54 57 60 56 63 61 63 64 68 63 67 68 74 52 0 1. 1 6 6 DS M . C l a s s 2 W v o m i n a 3 4 4 5 5 6 7 7 7 8 9 9 II 14 15 19 20 24 29 28 56 23 3 '8 M . C l a s s 2 T o t a l 50 58 64 49 51 58 60 63 66 69 67 74 74 80 82 90 86 94 10 0 10 4 59 0 1,4 4 1 ~ro S o l a - W a t e r H e a t e r 2.6 4 2.6 4 2. 6 2.6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2. 6 4 2. 6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.3 7 24 39 'T M e a d 3 e d t r H L H 16 8 26 4 26 4 21 72 36 iT U t a h 3 e d O t t H i l 20 0 20 0 20 0 17 44 18 5 20 0 10 5 52 OT M o n a - 3 3 e d n t H L H 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 OT M o n a 4 3 e d O t H L H 15 0 15 8 ow t R e s o u r e G o h e n ' " 6 20 32 13 7 97 18 5 97 16 7 12 3 13 6 N/ A 10 0 ow t h R e s o u r e U t a h N o r . . 10 5 24 2 28 7 36 6 N/ A 10 0 14 4 17 7 20 4 17 3 30 2 N/ A 10 0 ¡U n i T _ T - T 22 7 22 7 ",l U n n ) .1 - . 1 . . l 21 6 21 6 3. 7 8.3 12 12 4. 2 1 70 35 70 10 5 4.2 T 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 42 84 O. 3 I 0.3 . 1 0. 3 1 I 1 I I 3 3 3 17 17 17 6 6 6 4 4 4 18 18 18 4 - . 4 4 6 6 6 41 50 10 60 60 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 46 91 51 51 54 59 60 60 59 52 52 52 52 52 52 52 53 52 44 37 37 36 55 1 1,0 1 8 81 II 6 6 6 6 7 7 7 .7 8 8 8 9 9 7 6 7 6 7 71 14 7 6J l 66 65 70 72 71 . 7 1 63 63 64 64 65 66 67 67 64 55 47 47 47 66 8 1,2 5 7 2 2 2 3 9 9 2 2 I 10 10 15 0 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1. 8 1 1. 8 1 1. 8 1 1.4 8 0.9 7 0. 9 7 16 21 15 0 15 0 15 0 50 65 33 HL H T 40 0 40 0 40 0 29 8 40 0 40 0 40 0 35 7 40 0 10 7 31 2 40 0 35 0 34 5 23 1 HL H 1 0 0 / 0 P r i c e P r e m i 24 4 20 6 45 23 Q! ' : . 1 50 50 50 50 50 50 50 35 18 43 20 4 20 0 20 2 19 9 N/A 10 0 N/A 10 0 -. A 20 0 " ~ i ~ 'W ~ : 'J ' ;'' * ' ' j W ' ;; ' ¡ ~ ~ , ' ~ "fu ~ ' R l; ~ ~ ; &,' ~~ * ,. : , ~ : '\' ~ , #¥ ;¡ , . ' \ ' :m , : * ; - ' R , \1 T " -'! ' ~ m " , q f f . Æ ~. , WI ' '; ~ ~ ~ ' Ì ' !I . F r o n t o f i c e t r n s c t K l a n d g r o w t h r e s o u r c e a m o r e f l c t o n e - y e a r t r n s a c t p e r i , a n d a r e n o t a d d i v . *. F r o n o f l c e t r n s a c t i s a r e r e p o e d a s a 2 O , y e a r a n n u a l a v e r a g e . G r w t h r e s o e s a r r e d a s a i o - y e a r a v e r a g e . 99 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S 'c s H u n e r . U n I 3 R e l a c e s 0 . 28 0 'C C T F 2 x l 1,8 1 9 CC T H 47 5 47 5 47 5 47 5 2, 3 7 5 'o a l P l a n t T u r b i n U ad e s 12 . 1 18 . 9 1.8 18 . 0 2. 53 ot e m i B h i D . 3 35 45 80 ot e n n G r e e n f i k l 35 35 Wm d W 35 % C a c ' F a c t o r 13 13 9 21 8 9 4 34 22 7 'o t a I W i i d 13 13 9 21 8 9 4 34 22 7 Hp . B . , m a s s 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 10 20 'H P - R e c ' at i n E 0.8 0.8 0. 8 0.8 0.8 0.8 0. 8 5 5 DS M , C l a s s I , U t a h - C o l k e e r 5.5 5 11 11 DS M C l a s s i G o h e n - D L e - l r r " t Ð 8 8 8 DS M . C l a s s i U t a h - C u r i h n t 21 5 26 26 DS M C l a s s i U t a h - O L C . R e s i d n t i a l 11 20 5 37 37 DS M . C l a s s I , U t a h - O l e . li o 11 11 11 DS M , C l a s t , U t a h - S c h e d T h n n E n e r St a . 3 3 3 '8 M , C l a s s i T o t a l 17 50 20 5 5 97 97 DS Ce s s Go h e n 1 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 14 41 DS M C l a s s Ut a h 46 54 59 43 44 47 52 53 56 61 56 60 57 63 64 68 64 67 68 74 51 7 1.1 5 8 DS M , C l a s s 2 W 3 4 4 4 5 6 6 7 7 8 9 9 11 13 15 19 20 24 29 28 55 23 2 DS M . C l a s s 2 T w i t 49 59 64 48 51 55 60 62 66 71 67 71 70 80 82 90 87 94 10 0 10 5 58 6 1.4 3 1 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.3 7 2.6 4 2. 6 4 2.6 4 2. 3 7 24 36 16 8 26 4 26 4 24 72 36 20 0 I 20 0 20 0 17 56 19 6 20 0 10 7 54 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 21 0 15 0 15 8 20 32 45 11 0 16 1 14 4 17 1 17 3 13 9 N/A 10 0 34 6 49 4 16 0 N/A 10 0 14 22 4 21 8 41 2 13 2 N/A 10 0 22 7 22 7 21 6 21 6 3.7 8.3 12 12 70 70 70 4.2 4. 2 4.2 4.2 4.2 4.2 4. 2 4.2 4. 2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4. 2 4.2 4. 2 4.2 42 84 0.3 0. 3 0.3 0.3 1 1 DS M C l a S s i W a l l W a D a . D L C . R e s i d n t l 1 1 1 DS Cl a s s i W a B a W a l l - O L e - I r r ' i i o 3 3 3 DS Cl a s s i O r e n ' C a l i o m . C u r i l n t 17 17 17 OS M C l a s s i O r e Ca l i o r . Ol e - R e s i d e n t l 6 6 6 DS M C l a s s i O r n f C a l i o r . D L C - W a t e r H e a t e r 4 4 4 DS Cl a s s i O r e o n C a l i o m - D L C - 1 1m 18 18 18 DS M C l a s s i Y a k - D L e . R e s i d n t i l 4 4 4 DS M , C o s s i Y a k m - D L C - I r ' t i o 6 6 6 'S Cl a s s ! T o t l 50 6 4 60 60 DS M , C b s s 2 , W a l l W a l l 4 4 4 5 5 5 5 4 5 5 5 5 5 5 5 5 4 4 4 4 45 90 DS M C b s s 2 O r e Ca l i o m 51 51 54 59 60 60 59 52 52 52 52 52 52 52 53 52 44 37 37 36 55 0 1,0 1 7 DS M C l a s s 2 Y a k i m 8 11 6 6 6 6 6 7 7 7 8 8 8 9 9 7 6 7 6 7 70 14 5 '8 M , C l a s s 2 T o t a l 63 66 65 70 71 70 70 63 63 64 64 65 65 66 67 64 55 47 47 47 66 6 1, 2 5 3 So l a r C a S t a r d 2 2 2 3 9 9 So l a r P i l t 4 2 2 I 10 10 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1. 8 1 1.8 1 1.8 1 0.9 7 0. 9 0. 9 7 0.9 7 16 20 15 0 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 29 9 40 0 40 0 40 0 36 8 40 0 31 4 40 0 40 0 28 4 34 7 24 3 24 4 20 6 45 23 50 50 50 50 50 50 50 35 18 N/A 50 N/A 12 0 '" F r o n o f f i c e t r a n s c t i a n d g r w t r e s o u c e a m o r e f l e c t o n e - y e a r t r a n s a c t i p e r i , a n d a r e n o t a d d i t . ** F r o n t o f f c e t r a n s a c t i o a r e r e p o r t e d a s a 2 0 - y e a r a n n t a v e r a g e . G r o w t h r e s o u c e s a r e r e p o e d a s a t o - y e a r a v e r a g e . 10 0 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y EX P A N S I O N R E S U L T S 28 0 1, 2 2 2 1.8 1 9 . i 47 5 47 5 47 5 47 5 47 5 2. 3 7 5 "a d e s I 12 . 1 I 18 . 9 1 1.8 1 _, _ L 18 . o T . T 2.4 51 53 3s 1 - J . . J . 45 80 80 35 35 35 Fa c t o r T 40 29 21 8 9 4 34 40 14 5 ~i t F a c t o r -l 16 0 16 0 16 0 20 0 29 21 8 9 4 34 20 0 30 5 ¡r C H P . B i o m a s s 1.0 1.0 1. 0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1. 0 1. 0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 10 20 lC H P - R " m n a t i . E n " ; 0.8 0.8 0.8 2 2 DS M , C l a s s i U i a h . C o o l k e e n P f 5.5 5 II II DS M , C l a s s 1 , G o s h e n - D L C . 1 r r i m t i o n 8 8 8 DS M . C l a s s t , U t a h . C u r i l t 21 5 26 26 DS M C l a s s i U t a h - O L e . R e s i d n t i a l 10 21 5 36 36 DS M C l a s s i U t a h - O L e - l r " a r i II II II DS M , C l a s s i , U t a b - S c h e d T h e r m E n e r a v 8 t o m - 3 3 3 DS M , C l a s s 1 T o t a l 16 51 29 96 96 DS M C l a s s 2 G o s h e n I I 1 I I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 14 41 DS M . C l a s s 2 U t a h 46 53 59 38 44 47 49 50 52 54 56 60 57 63 64 68 64 67 68 74 49 2 1.1 3 4 DS M C l a s s 2 W v o m a 3 4 4 4 5 5 6 7 6 7 9 9 II 13 15 19 20 24 29 28 51 22 8 DS M C l a s s 2 T o t a l 49 57 64 43 50 54 56 59 60 63 67 71 70 80 82 90 87 94 10 0 10 5 55 7 1,4 0 2 Mic r o S o l a . W a t e r H e a t e r 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2. 3 7 2. 3 7 21 26 !r O T M e a d 3 n 1 ( ) H L H 16 8 26 4 26 4 99 80 40 Uta h 3 r d O - - H L H 20 0 20 0 20 0 41 12 15 8 20 0 19 8 12 1 60 Mo n - 3 3 r d O t r H L H 30 0 30 0 30 0 30 0 30 0 30 0 . 3 0 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 21 0 Mo n - 4 3 r d Q t t H L H 15 0 15 8 20 33 46 10 7 16 0 15 0 16 8 in 13 9 N/A 10 0 31 9 46 4 21 8 N/A 10 0 38 18 9 22 7 41 4 13 2 N/ A 10 0 IU n i : ; T - T . T 22 7 22 7 'la I U n i t ) i - i - i 21 6 21 6 3.7 8.3 12 12 35 35 35 70 10 5 4.2 4.2 4.2 4.2 4. 2 4. 2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4. 2 4.2 4.2 4.2 4.2 42 84 'H P . R ~ ~ ; ' E ~ a i 0.3 0.3 0.3 i i DS M C l a s i W a l h W a l l . D L C . R e s k l t t i l i i i DS M , C l a s s i W a l k W a l h - D L C . I r t i o 3 3 3 DS M C l a s s 1 O r e n o n C a l i m i i a - C u r i h t 17 17 17 DS M . C l a s s i O r e n o n C a i f o m i - D L C - R e s i J n t i a l 6 6 6 DS M C l a s s 1 O r e i m n / C a i f o m i - D L C - W a t e r H e a t e 4 4 4 DS M . C l a s s i O r e u n C a l i o r - D L C - I r r n t m . 18 18 18 DS M C l a s s 1 Y a k i n . D L C - R e s i d n t i a l 4 4 4 DS M C l a 1 , Y a k i m - D L C - I r Ï l t i 6 6 6 DS M , C l a s s i T o t a l 50 10 60 60 DS M C l a s s 2 W a l h W a l l 4 4 4 5 5 5 5 4 4 4 5 5 5 5 5 5 4 4 4 4 44 89 DS M C l a s s 2 O r e o o n C a l i o m i 51 51 54 59 60 60 59 52 51 52 52 52 52 52 53 52 44 37 37 36 54 9 1,0 1 6 DS M C l a s s 2 Y a k 8 II 6 6 6 6 6 7 6 6 8 8 8 9 9 7 6 7 6 7 67 14 2 ID S M C l a s s 2 T o t a l 63 66 65 69 71 70 70 62 61 62 64 65 65 66 67 64 55 47 47 47 66 0 1,2 4 7 Or o n n S o l a C a ' " S t a n d r d 2 2 2 3 9 9 Or i m n S o e r P O O 4 2 2 i 10 10 Jli c r o S o l a . W a t e r H e a t e r 1. 8 1 1. 8 1 1. 8 1 1.8 1 1.8 1 1.8 1 1.8 1 1. 8 1 0. 9 7 14 15 15 0 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 38 5 40 0 40 0 40 0 33 9 40 0 31 3 40 0 40 0 32 6 35 2 24 8 24 4 20 6 45 23 50 50 50 50 50 50 50 35 18 N/A 38 ~ 12 9 !§ ' :, - ~ ~ ~ t ' ~\ £ *~ " § ' 'f * ' " ~~ ~ f u 1 i " " ''' * ~q ~ t ' :~ : ~ ' ," * ~ " : ~ ~ ' " , :'t ~ ~ , ~ ~ 1 t ~ § ' i ", ' 'W i ' ~ :h \ ' % " : ~ - l l ~. : ' \ W ' , ' * F r o n o f f i c e t r n s a c t i o a n d g r o w t h r e s o u e a m o t s r e f l c t o n e - y e a r t r a n s a c t i o p e , a n d a r e n o t a d d i v e . "'' ' F r o o f f i c e t r n s a c r n n s a r e r e p o e d a s a 2 0 - y e a r a n n l a v e r a g e . G r o w r e s o u c e s a r r e p o d a s a i o - y e a r a v e r a g e . 10 1 P A C I F i C O R P - 2 0 1 1 I R P AP P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S CC C T F 2 x 1 62 5 59 7 1,2 2 2 1,2 2 2 CC C T H 47 5 47 5 47 5 Co a l P l a n t T u r i n e U n a r d e s 12 . 1 18 . 9 1.8 18 . 0 2.4 51 53 Ge o t h e n n a L B h m d e U 3 35 45 80 80 Ge o t h e r m a l G r e e n f e k i 35 35 35 Wi n W y o 3 5 % C a p a c i t F a c t o r 8 9 4 34 55 Win d , W v o i n N E 3 5 % C a n a d v F a c t o 16 0 16 0 'o t l W i l d 16 0 8 9 4 34 21 5 CH P - B i o a s s I I I I I I I I I I I I I I I I I I I I 10 20 li P - R e c i o a t i i m E n m e 0.8 0. 8 0.8 2 2 DS M C l a s s i U t a h - C o o l k e e v e l 6 5 II II DS M . C l a s i G o h e n - D L C - I r r i m t i o 8 2 8 10 DS M C l a s I U t a h . C u r i h n t 21 5 26 26 DS M C l a s 1 U t a h - D L e . R e s i d e n t i a l 32 3 35 35 DS M C l a s I U t a h - D L C . l r r t i o II 3 II 14 DS M C l a s s I , U t a h - S e h e d T h n n E n e r Æ Y S t o l ! e 3 3 3 'S M C i s " i T o t l 6 62 20 8 5 95 10 0 DS M C l a s 2 G o h e n I I i I I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 38 DS M C l a s s 2 U t a h 46 55 59 43 44 47 49 50 52 54 56 60 57 60 60 65 60 63 64 69 49 9 1.1 1 3 DS M C l a s s 2 W v o i n g 3 4 4 4 5 6 6 7 7 8 9 9 II 13 14 18 20 23 29 28 55 22 9 SM . C l s s s 2 T o t l 49 59 64 48 51 55 57 59 61 64 67 71 70 76 77 86 82 89 95 99 56 8 1,3 8 0 ~ro S o l a r - W a t e r H e a t e r 3 3 3 3 3 3 3 3 3 2 2 0 . - 24 29 'T M e s d 3 r d O t t H L H 16 8 26 4 26 4 28 72 36 'T U t a h 3 r d O t t I I L H 20 0 20 0 22 57 20 0 19 3 87 44 'T M o o - 3 3 r d O t r H L H 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 ¡I F O T M o o - 4 3 r d O t H L H 15 0 15 8 tl G r t h R e s o c e G o h e n . 34 81 18 4 23 7 23 8 16 9 57 N/A 10 0 J( g R e s o u e U t a h N o r . 30 6 33 5 35 8 N/A 10 0 53 26 1 29 0 39 5 N/A 10 0 3.7 8.3 12 12 70 70 70 HP - B i o s s 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 42 84 HP - R e c i o c a t i u i E n a i 0.3 0.3 0.3 I 1 DS M C l a s i W a l l W a l l - D L C - R e s i l n t i l I I I DS M C l a s I W a l l W a l l - D L C . l r r t i 3 3 3 DS M . C l a s i O r e g o n C a l i o r n i a - C u r i l n t 17 17 17 DS M . C l a s I O r e l ! o n C a l i o m i a - D L C - R e s i d i a l 6 6 6 DS M C l a s 1 O r e i . o n C a l i o m i a - D L C - W a t e r H e a t e r 4 4 4 DS M C l a s i O r e i i o n C a l i o m i a - D L C - I r r i m t i 18 18 18 DS M C l a s s i Y a k i m a - D L C - R e s i d n t i l 4 4 4 DS M C l a s I Y a k i m a - D L C - I r r i i a t i o 6 6 6 SM . C l a s s I T o t a l 50 io 60 60 DS M . C l a s s 2 W a l l W a l l 4 4 5 5 5 5 5 4 4 4 5 5 5 5 5 5 4 4 4 4 45 90 DS M C l a s s 2 O r e i r C a l i o m i a 51 51 54 59 60 60 59 52 52 52 52 52 52 52 52 52 44 36 36 36 55 0 1,0 1 5 DS M C l a s s 2 Y a k i n a 6 6 6 6 6 6 6 7 7 7 8 8 8 9 9 7 ,; 7 6 7 63 13 8 . SM . C l s s s 2 T o t a l 61 62 65 70 71 70 70 63 63 63 64 65 65 66 66 64 54 47 47 47 65 8 1,2 4 3 eii o n S o l a r C a n S t a n d a r d 2 2 2 3 9 9 'e i i O ß S o l a r P i l t 4 2 2 I 10 io ) S o l a r - W a t e r H e a t e r 1.8 1.8 1.8 1.8 1. 8 1.8 1.8 1. 1. 1.0 1.0 1.0 1.0 15 19 CO B 3 r d O t r H L H 15 0 15 0 15 0 15 0 50 65 33 Mid C o l w b i a 3 r d O t t H L H 25 40 0 40 0 40 0 30 3 40 0 40 0 40 0 37 6 40 0 96 29 2 38 8 40 0 40 0 40 0 40 0 40 0 40 0 40 0 35 0 35 4 Mid C o l w b i a 3 r d t r H L H 1 0 0 1 0 P r i c e P r e m i u 27 1 21 1 48 24 So u h C e n t r a l O r e g o n l N o r h e r n C a l i o r n i a 3 r d O t r H 50 50 50 50 50 50 50 35 18 12 56 52 16 7 32 ~ N/A 48 N/A 41 N/A 20 0 ;¡s " iI l T i t ~ 't . !i , ~ Ii L ~ . it ' t ~ '; , ' I l i t î1 1 ' " , '; ' ~ ~ ' W ' ~ ' '" F r o t o f f c e t r n s a c t i o a n d g r w t h r e s o u e a m o t s r e f l c t o n e - y e a r t r a n s a c o o n p e r i d s , a n d a r e n o t a d d i t i v e . *' F r o n t o f f i c e t r a n s a c t i o n s a r e r e p o e d a s a 2 0 - y e a r a n n u a l a v e r a g e . G r o w t h r e s o u c e s a r e r e p o r t d a s a 1 0 - y e a r a v e r a g e . 10 2 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S 28 0 1,2 2 2 47 5 12 . 1 I 18 . 9 I 1.8 1 I - T 18 . o T - T _ T _ T - T 2. 4 ì _ T - T . T - T - T 51 53 35 1 . J . - 1 . - . L 45 . L - J . .1 - 1 . - l 80 80 35 . L . J . .1 35 3 9 4 34 50 3 9 4 34 50 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1. 0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 10 20 , 0.8 0.8 0.8 -. 2 2 5.5 5 11 11 ~t i J. 8 1 1 8 10 21 5 26 26 10 21 5 37 37 :ti o n I 11 I 2 11 14 16 48 20 10 2 3 94 99 1 I 1 1 1 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 15 42 47 57 59 43 46 50 52 54 55 60 59 63 61 63 65 69 64 67 68 77 52 4 1,1 8 1 3 4 4 5 5 6 7 7 7 8 9 10 11 14 15 19 20 24 29 28 56 23 4 51 62 64 49 53 57 61 63 65 69 70 75 74 80 83 91 87 94 10 0 10 8 59 4 1.4 5 7 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2. 6 4 2.6 4 2. 3 7 2.3 7 24 34 16 8 26 4 26 4 20 72 36 20 0 I 20 0 20 0 17 43 18 4 20 0 10 4 52 30 0 30 0 30 0 30 0 30 0 JO O 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 19 32 44 58 19 5 14 4 19 5 17 1 13 6 N/ A 10 0 11 7 20 5 J0 8 37 0 N/ A 10 0 22 2 18 5 36 5 22 8 N/ A 10 0 :e r - U n i t i Ï R e n l a c e s O Æ i I U n i ) 22 7 22 7 'C S B r i - - ~ . U n i t : Z e n l a c e s D r i î n l U n i ) 21 6 21 6 'o a t P l a n t T u r b i n e U . . . . d e s 3.7 8.3 12 12 Ge o t h e n n a l G r e e n i e k l 70 70 70 14 0 eR P - B i o s s 4.2 4. 2 4.2 4. 2 4.2 4. 2 4.2 4.2 4. 2 4.2 4. 2 4.2 4.2 4.2 4. 2 4.2 4. 2 4.2 4. 2 4.2 42 84 lC H P . R e c i n a t . . o E n . . e 0.3 0. 3 0.3 I 1 DS M C l a s i , W a O a W a l l - D L e - R e s i d n t l 1 I 1 DS M C l a s s 1 W a I l W a l l . D L C - l r r l m t i o 3 3 3 DS M C l a s 1 O r e a n / C a l i Q l Ï 8 - C u r i h n t 17 17 17 DS M C l a s s 1 O r e " o n C a l i o m i a . D L C . R e s i d n t i a l 6 6 6 DS M C l a s s I O r l ! o i C a l i o r Ï i - D L C - W a t e r H e a t e r 4 4 4 DS M C l a s I O r e o o n C a l i o r . D L C - I r r t i 18 18 18 DS M . C l a s i , Y a k i m - O l e - R e s i d l 4 4 4 DS M C l a s s i Y a k i - D L C - I r r - t i o 6 6 6 8M C 1 a s s l T o t l 50 10 60 60 DS M C l a s 2 W a l l W a l l 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 46 92 DS M C l a s s 2 Q r e n o n C a l i o n 51 51 54 59 60 60 59 52 52 52 52 52 52 52 53 52 44 37 37 36 55 1 1,0 1 9 DS M C l a s 2 Y i l 8 11 6 6 6 7 7 7 7 7 8 9 9 9 9 7 6 7 6 7 72 14 9 SM , C l a s s 2 T o t l 63 66 66 70 72 71 71 63 63 64 65 66 66 67 67 64 55 47 47 47 67 0 1,2 6 0 11 : a n S o l i r C a n S t a n d r d 2 2 2 3 9 9 1" e l ! 0 I S o l a r P i l 4 2 2 1 10 10 ) S o n r - W a t e r H e a t e r 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 0.9 7 0.9 7 0.9 7 0.9 7 16 20 CO B 3 r d n t r H L H 15 0 15 0 15 0 15 0 50 65 33 Mi l o h m b i 3 r d O l H L H 40 0 40 40 0 29 7 40 0 40 40 0 31 7 40 0 99 40 0 37 1 40 0 40 0 40 0 10 3 34 1 27 9 MO C o l u 3 r d O H L H i o o / o P r K : e P r e m i 24 4 20 6 45 23 So u C e n a l O r g o n o r e m C a l i o m 3 r d Q t r J t 50 50 50 50 50 50 50 35 18 14 2 20 6 20 4 20 1 19 9 Nf A 10 0 Nf A 10 0 Nf A 20 0 , .i" î k 4 ìt\ ~ ; " ~ : m ' k ' li . ~, ~ , " " , §¡ , ' W ~ % - " :~ ' ~ ;~ : ~ " : ::m ' ~ '~ ; ~ l ~ g , ~ ~~ ~ ~ , ' * Mi "\\ ~ ~ ,* m , ",' , ' ; m , ~ ~ ~ 0 ~" ' ¡ w " ", ; ; '" F r o t o f f i c e t r n s a c t i a n d g r o w t h r e s o u r a m o i u t s r e f l c t o n - y e a r t r n s a c t i p e r i , a n d a r e n o t a d d i v . ** F r o n t o f f c e t r a n s a c t i o n s a r e r e ¡ X r t e d a s a 2 O y e a r a n u a l a v e r g e . G r w t r e s o u c e s a r e r e p o d as a t o - y e a r a v e r a g . 10 3 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S 28 0 1,8 1 9 12 . 1 1 18 . 9 1 1.8 1 . I 47 5 47 5 47 5 47 5 1,4 2 5 "a d e s T 18 . 0 2. 4 51 53 35 45 80 80 35 35 dv F a c t o r T 13 49 21 8 9 20 0 20 0 50 0 13 49 21 8 9 20 0 20 0 50 0 1.0 1.0 1.0 1.0 1. 0 1.0 1. 0 1.0 1. 0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1. 0 10 20 'H P M R e c i n a t Ì ß I l E n ~ 0. 8 0.8 0. 8 2 2 DS M _ C l a s 1 U t a b . C o o k e e n e 5. 5 5 11 11 DS M , C l a s 1 G o h e D L C . J r i m t i o 8 2 8 10 DS M , C l a s s 1 . U t a h - C u r i b t 21 5 26 26 DS M . C l a s s 1 U t a D L C - R e s i J n t i a l 10 21 5 37 37 DS M , C l a s s i U t a b - D L C . l r t i o 11 3 11 14 '8 M . C l a s s i T o t l 16 48 20 5 5 5 94 99 DS M . C l a s s 2 G o l i I 1 I I 1 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 14 42 DS M . 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'ì ~ \ : ' il * ~ " * ,: * , ~ , % .' " i i ' , "\ 0 1 ; '. ' , ~ ,i i : ' ~ % 4 J " ~ * 0" ~ ~ .. F r o n t o f f i c e t r n s B C t i a n d g r r e s o u e a m o r e f l c t o n - y e a r t r n s a c h o n p e o d , a n d a r e n o a d d ï w e . .. F r o t o f f i c e t r n s a c t i o n a r e r e p o d a s a i o - y e a r a n n u a l a v e m g e . O r o w t h r e s o u e s a r e r e p o e d a s a i o - y e a r a v e r a g e . 10 4 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S 1, 8 1 9 2.4 1 " _ 1 " 47 5 47 5 47 5 1, 4 2 5 .d e , I 12 . 1 1 18 . 9 1 1.8 1 - T . T 18 . o T - T . T _ T _ T _ T . T 51 53 35 . 1 . . 1 . . 1 - . 1 - . 1 45 . 1 . . 1 . J . - l - l 80 80 35 35 cit F a c t o r I 8 9 20 0 20 0 41 8 8 9 20 0 20 0 41 8 1.0 1. 0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1. 0 1.0 1.0 1.0 1.0 1. 0 1. 0 10 20 '0 T 0. 8 0.8 0.8 0. 8 3 3 I 5.5 5 11 11 it io .. 8 2 8 10 21 3 25 25 10 21 32 32 11 3 11 -c - 1 4 16 48 23 5 87 92 I I I I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 14 42 47 57 59 47 62 47 49 50 52 54 56 63 61 63 65 69 64 70 70 77 52 5 1,1 8 4 3 4 4 5 5 5 6 7 7 8 9 9 11 14 15 19 20 24 30 29 54 23 4 51 62 64 53 68 54 56 59 61 64 67 75 74 80 83 91 88 97 10 3 10 9 59 3 1,4 6 0 2.6 4 2. 6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2. 6 4 2.3 7 11 23 16 8 26 4 26 4 99 80 40 20 0 I 20 0 20 0 0 20 0 14 6 17 9 11 3 56 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 24 0 15 0 15 8. 20 77 75 59 82 99 15 1 19 6 23 3 N/ A 10 0 24 85 14 3 89 23 8 33 2 89 N/ A 10 0 7 36 17 3 26 4 25 2 26 7 N/ A 10 0 . i a l - U n i i T .T . T - T . T 22 7 22 7 la l U o Î t ) i .i . - I 21 6 21 6 3.7 J . - J . 8. 3 12 12 70 35 35 70 70 70 28 0 4. 2 t 50 50 50 4.2 T 4.2 4. 2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4. 2 42 84 '0 I 0. 3 J . 0. 3 l 0.3 0.3 I I I I I 3 3 3 17 17 17 6 6 6 4 4 4 tD o I I I 18 18 18 2 I 4 4 6 6 6 50 9 I 60 60 4t 4 5 5 5 5 5 4 5 5 5 5 5 5 5 5 4 4 4 4 46 91 51 1 51 54 59 60 60 59 52 52 52 52 52 52 52 53 52 44 37 37 37 55 0 1.0 1 9 10 1 11 7 7 7 6 6 7 7 7 8 9 9 9 9 7 6 7 . 6 7 73 15 0 65 . 1 66 66 71 72 70 70 62 63 63 65 66 66 67 67 64 55 47 47 48 66 9 1, 2 6 0 2 2 2 3 9 9 2 2 I 10 10 1. 8 1 1.8 1 1.8 1 1.8 1 0.9 7 0.9 7 0.9 7 0.9 7 0. 9 7 7 12 15 0 I 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 40 0 40 0 40 0 40 0 32 8 40 0 28 1 39 6 40 0 40 0 40 0 35 3 27 0 24 5 20 5 45 22 50 50 50 50 2 50 50 50 35 18 25 20 6 N/ A 23 N/ A 14 N/ A 20 0 il, ~ " '~ m ¡¡, ,~ % ~ , ," . : ¡ ¡ " ' * " ' , "& ~ ' l nrn m ~ : ' ¡¡ '% 1 ' ' " ~ , ' t T j~ ¡ ' d l ' ~ W ~ mf f ;- * ~ " '" , \ ~ '! i ' * F r o t o f f c e t r n s a c t i o n a n d g r o w h r e s o u r e a m o t s r e f l c t o n - y e a r t r a n s a c t i p e r i , a n d a r n o a d d . .* F r o t o f f i c e t r n s a c t i o a r e r e p r t d a s a 2 Q y e a r a n u a l a v e r a g e . G r t h r e s o u c e s a r e r e p e d a s a i o - y e a r a v e g e . 10 5 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S 28 0 1.8 1 9 95 0 1I 8 1I8 1I8 'a d e s I 12 . ' - 18 . 9 . . 1. 8 J . - . . 18 . 0 2.4 51 53 35 45 80 80 35 35 35 Fa c t o r 20 0 20 0 20 0 20 0 60 0 Fa c t o r 16 0 16 0 16 0 16 0 20 0 20 0 20 0 36 0 76 0 :r C H P - B i o i m s s 1. 0 1. 0 1.0 1.0 1. 0 1. 0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1. 0 1. 0 1.0 1.0 1.0 1.0 1. 0 10 20 l.C H P . R e c f n a t i n o E n . . 0.8 0.8 0.8 2 2 DS M C l s s i U t a h - C o o k e e . . r 5.5 5 1I II DS M C l a s s i G o h e n - D L C - t r r t i o 8 2 8 10 DS M C l a s s i U t a h - C u r i l e n t 21 5 26 26 OS M C l a s s i U t a h - D L C . R e s i d e n t n l 9 22 5 37 37 DS M C m s I U l a h . 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" F r o o f f c e t r n s a c t i o n s a r e r e p o d a s a 2 o - y e a r a n n u a l a v e m g e . G r o w t h r e s o u e s a r e r e p o d a s a H ) - y e a r a v e r a g e . 10 6 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S 1. 2 2 2 1, 2 2 2 51 53 35 45 80 80 35 35 35 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1. 0 1.0 1. 0 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1. 0 10 20 ;; " . E n . " e 0.8 0. 8 0.8 0.0 0.8 3 3 DS M C l a s i U t a h ~ C o o l k e e n e r 5.5 5 11 11 DS M C l a s s i G o l i e n - D L C - I r r t i o 8 2 8 10 DS M C l a s t , U t a h - C u r i h e n t 21 2 1 2 26 26 DS M _ C l a s i U t a h - O L e - R e s i d n t i a l 10 22 5 37 37 DS M C l a s i U t a h . D L C . l r r i , . " t i 11 3 11 14 DS M , C l a s t , U t a h - S e h e d T h e n n E n e n i v S t o r r e 3 3 3 DS M , C l a s s 1 T o t a l 16 48 22 1 10 5 97 10 2 DS M C h s s 2 G o h e n I 1 I 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 15 44 DS M , C l a s 2 , U t a h 47 57 59 47 58 52 54 71 72 74 61 65 62 67 68 72 66 70 70 77 59 1 1. 2 6 9 DS M . C b s s 2 . W v o m " . 3 4 4 5 5 6 7 8 8 8 9 10 11 14 15 19 20 24 31 29 57 24 0 DS M , C l a s s 2 T o t a l 51 62 64 53 65 60 62 80 81 85 72 77 76 84 86 94 90 97 10 4 10 9 66 4 1. 5 5 3 Mi c r o S o l a r - W a t e r H e a t e r 2.6 4 2. 6 4 2.6 4 2. 6 4 2.6 4 2.6 2. 6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.6 4 2. 3 7 24 37 Me a d 3 r d ) ) t r H L H 16 8 26 4 26 4 99 80 40 Ut a h 3 r d n t r H L H 20 0 20 0 20 0 2Q O 20 0 10 0 50 Mo n - 3 3 r d 0 " H L H 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 Mo n - 4 3 r d O t r H L H 15 0 15 8 Go s h e n * 5 50 72 77 13 2 13 9 96 14 9 14 5 13 5 N/A 10 0 :e U t a h No r t . 17 0 24 6 25 9 32 5 N/A 10 0 68 17 4 17 8 25 4 32 6 N/A 10 0 3.7 8.3 12 12 70 35 70 70 70 70 35 38 5 42 0 10 0 10 0 10 0 IW u i d 10 0 10 0 10 0 lti 1 i t B i o s s 50 50 50 :H P - B i o m a s s 4.2 4.2 4.2 4.2 4. 2 4.2 4. 2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4. 2 4.2 4. 2 4.2 4.2 4.2 42 84 'H P - R e c i n o c a t i n o E n o i n 0.3 0.3 0.3 0. 3 1 I DS M , C l a s s 1 , W a l l W a l l - D L e . 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W a t e r H e a t e r 1.8 1 1.8 1 1.8 1 1.8 1 1. 8 1 1.8 1 1.8 1 1.8 1 1.8 1 1. 8 1 1.8 1 1. 8 1 1. 9 0.9 7 16 24 FO T C O B 3 r d O N H L H 15 0 15 0 15 0 15 0 50 65 33 FO T M K l o l w b i a 3 r d O H L H 40 0 40 0 40 0 40 0 31 1 34 2 40 0 40 0 40 0 81 39 3 40 0 40 0 40 0 40 0 40 0 40 0 40 0 36 5 34 5 35 5 FO T M i d C o h . b i a 3 r d O t H L H l 0 0 ! o P r i c e P r e m i u 24 4 20 1 45 22 kO T S o u C e n t a l O r e D ' o n o r m C a l i o r 3 r d t r H 50 50 50 50 50 6 34 50 34 17 'O w t h R e s o u r e W a l l W a l l . 23 17 4 N/A 20 'o w t h R e s o u r c e O r e " " / C a l i o m i ' " 29 2 N/A 29 'o w t h R e s o W ' c e Y a k a . nq 70 10 4 26 8 12 4 20 5 27 3 35 6 37 1 N/A 20 0 ~ ~ ~~ d ~ '% 1 ' " .:W ., ,il ' il ¡ ¡ ' "" ' " ''; ' " ; ~ i n ~ " h R . F r o n t o f f e t r n s a c t i n a n d g r o w t h r e s o u c e a m o u n r e f l c t o n e . y e a r t r n s a c t i o n p e r i o , a n d a r e n o t a d d i v . .. 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G r w t h r e s o u r c e s a r e r e p o e d a s a t o - y e a r a v e r a g e . 10 7 PA C I F i C O R P - 2 0 1 l 1 R P 28 0 1.2 2 2 53 35 1 . i . i - i 45 80 80 35 35 35 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 1,8 0 0 16 0 16 0 16 0 16 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 16 0 1,9 6 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1. 0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 !O 20 " 0. 8 0. 8 0.8 2 2 5. 5 5 II II !s t i i 8 1 1 8 !O 21 2 1 2 26 26 !O 22 5 37 37 .t i n I II 1 2 II 14 16 48 22 1 7 2 3 94 99 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 15 45 47 57 59 47 54 52 54 55 57 73 62 67 64 68 68 72 66 70 70 77 55 4 1.2 4 0 3 4 4 5 5 6 7 7 8 8 9 !O II 14 15 20 21 25 31 29 57 24 2 51 62 64 53 61 60 62 65 67 83 74 79 78 85 87 95 91 98 10 4 !O 9 62 7 1.5 2 7 2.6 4 2.6 4 2.6 4 2. 6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.3 7 24 42 16 8 26 4 26 4 99 80 40 2° ° i 20 0 20 0 20 0 20 0 10 0 50 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 59 79 88 63 12 0 12 5 95 11 5 12 1 13 4 N/A !O O 50 3 18 4 30 4 45 9 N/A 10 0 91 21 59 11 5 19 0 20 2 32 1 N/A 10 0 IU m : \ 22 7 22 7 I Un i ) i . i . i 21 6 21 6 3.7 8.3 12 12 70 70 70 70 70 70 42 0 42 0 10 0 !O O 10 0 Fa c t e I I !O O !O O 10 0 !O O !O O 20 0 20 0 50 50 50 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4.2 4. 2 4. 2 4.2 4.2 4.2 4. 2 4.2 4.2 4. 2 4. 2 4.2 4.2 42 84 O.l i 0.3 0.3 i i i i i 3 3 3 17 17 17 6 6 6 4 4 4 ti n I I I 18 18 18 4 4 4 6 6 6 50 6 4 60 60 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 47 93 51 51 54 59 61 60 59 52 52 52 52 52 52 53 53 53 45 37 37 37 55 2 1, 0 2 3 10 ii 7 7 7 7 7 7 7 7 8 9 9 9 !O 7 6 7 7 7 75 15 4 65 1 66 66 71 72 71 71 63 64 64 65 66 66 68 68 65 55 48 47 48 67 4 1, 2 6 9 2 2 2 3 9 9 2 2 i 10 10 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1. 8 1 1.8 1 1.8 1 1. 8 1 1. 8 1 1.8 1 1.2 9 0.9 7 0.9 7 16 29 15 0 i 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 40 0 31 3 31 1 38 8 39 7 40 0 13 4 33 9 38 7 40 0 40 0 40 0 40 0 40 0 40 34 1 33 3 24 4 20 1 45 22 HI I 50 50 50 50 17 50 27 13 N/ A 73 N/ A 56 N/ A 20 0 '2 " "'i l '. m i ~, ~ '~ m " ~~ : ,f u ' ,,~ , ~ ~ ~ i r ~ 's ! " , m :, ~ " ~, , ' ~ i l m ~ ~ ¡g WI ' ' - & R 'm i WI in ~ h . Q _ ~ ~ ' : \W ii ii F r o n t o f f c e t r a n a a c t i n a n g r w t h r e s o u r c e a m o u t s r e f l c t o n e - y e a r t r a n s c t i p e r i o , a n d a r n o t ad d e . "'* F r o o f f i c e t r n s c t a r r e p o e d a s a 2 O . y e a r a n n u a l a v e r a g e . G r w t h r e s o u c e s a r e r e p o d a s a ' I O - y e a r a v e r a g e . 10 8 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S 28 0 1. 2 2 2 2. 4 51 53 35 1 I I I .4 5 1 .- 80 80 35 35 35 1.6 0 0 1,6 0 0 ,-; ¡ f P a c t o 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 1. 6 0 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 1. 6 0 0 'H p . B i o m a s 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 10 20 'U P . R e c i n o c a t i o E n o - e 0.8 0.8 0.8 0.8 3 3 DS M . C l a s I , U t a h . C o o l k e . . r 5.5 5 II II DS M C l a s i G o h e n - D L C - I r r ¡ " t i o 8 I I 8 10 DS M C l a s s I U t a h . C u r i l n t 21 2 I 2 26 26 DS M C l a s s I , U t a h . O L e - R e s i d n t i a l 10 22 5 37 37 DS M C l a s I , U t a h - D L C . I r r t i o n II I 2 II 14 DS M C l a s i U t a h - S e h e d T h e r m E n e r ~ S t o r a g e 3 3 3 8M , C l a s s i T o t l 16 48 22 I 10 2 3 97 10 2 DS M C l a s s 2 G o h e n I I I I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 15 45 DS M C l a s s 2 U t a h 47 57 59 47 58 52 54 71 72 74 61 67 64 68 68 72 66 70 70 73 59 1 1,2 7 1 DS M C l a s 2 , W v o m i n i i 3 4 4 5 5 6 7 8 8 8 9 10 II 14 15 20 21 25 31 33 57 24 6 SM . C l a s s 2 T o t l 51 62 64 53 65 60 62 80 81 85 72 79 78 85 87 95 91 98 10 4 10 9 66 4 1.5 6 2 2. 6 4 2. 6 4 2. 6 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2. 6 4 2.6 4 2.6 4 2. 6 2.3 7 24 45 16 8 26 4 26 4 99 . 80 40 20 0 1 20 0 20 0 20 0 20 0 10 0 50 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 41 67 78 12 0 12 5 11 8 16 0 15 2 13 4 NI A 10 0 81 16 2 19 34 2 39 6 NI A 10 0 71 97 70 14 9 21 1 19 3 21 0 NI A 10 0 . 22 7 22 7 21 6 21 6 'o a l P e n t T u r b i n e U . . . . a d e s 3.7 8.3 12 12 !g o t e n n l G r e e n f i e k i 70 35 70 70 70 70 35 38 5 42 0 Win Y a l d , 2 9 0 1 0 C a o a c i t F a c t o 10 0 10 0 10 0 'o t a l W å i d 10 0 - 10 0 10 0 Ut i l B i o a s s 50 50 50 CH P - B i o m a s 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4. 2 4. 2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 42 84 lç H P . R e c " " o c a t m o E n " " . 0.3 0. 3 0.3 0. 3 I I DS M C l a s s 1 W a l l W a U a - D L C ~ R e s X i n t i a i I I I DS M C l a s s i W a l Ð W a D a . D L C - I r r i a t i o 3 3 3 DS M , C l a s s i O r e l 1 o n l C a l i o r n - C u i h n t 17 17 17 DS M . C l a s s 1 Q r e m m C a l i o m i a - D L C - R e s i d e n t i l 6 6 6 DS M . C l a s s I , O r e i m n I a l i o r i a - D L C - W a t e r H e a t e r 4 4 4 DS M C l a s i O r e l J f C a l i o r i a - D L C - I r ~ o n 18 18 18 DS M C l a s s i Y a k - O L e - R e s i d n t i a l 4 4 4 DS M , C l a s s t , Y a k - D L C - l r r i m i i o n 6 . - 6 6 DS M , C l s s i T o t l 50 6 4 60 60 DS M C l a s s 2 W a U a W a l l 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 47 93 DS M C b s s ? O r e o n n / C a l i o r i a SI 51 54 59 61 60 59 52 52 52 52 52 52 53 53 53 45 37 37 37 55 2 1,0 2 2 DS M C h s s 2 Y a k i a 10 II 7 7 7 7 7 7 7 8 8 9 9 9 10 1 6 7 7 7 75 15 4 SM , C l a s 2 T o t a l 65 66 66 71 72 71 71 64 64 64 65 66 66 67 68 65 55 48 47 48 67 4 1,2 7 0 'a n S t a n d d 2 2 2 3 9 9 iI 4 2 2 I 10 10 1.8 1 1.8 1 1. 8 1 1. 8 1 1. 8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1. 8 1 1. 8 1 1. 9 1.2 9 0.9 7 0.9 7 16 30 15 0 15 0 15 0 15 0 50 6S 33 40 0 40 0 40 0 40 0 34 1 34 2 40 0 40 0 40 0 31 0 40 0 40 40 0 40 0 40 40 0 10 2 34 8 31 5 24 4 20 1 45 22 50 50 50 50 20 6 34 50 31 16 NI A 18 NI A 20 0 *. ' , : ' ; k ' * C ¡¡ '" , , ~ " ' " , ... O ¥ \ ~ ~ . ., ' ~ ~ ~ , , ' " Th ' "~ ~ t ' t ~ ' ß :'l l L ' *. ,' ~ ~ ',: " ~ , ~ ~ ~ ; ,~ ' W , ' 'w ' m '" ~ ~ ' * , ~" i n '\" " , ''' ' ~ . F r o n t o f T c e t r n s a c t l O a n d g r o w t h r e s o u c e a m o w t s r e f l c t o n e - y e a r t r n s a c t i o p e r i , a n d a r n o t a d d i t e . "'. F r o n t o f f c e t r a n s a c t i o a r r e p o d a s a 2 a - y e a r a n n l a v e r a g e . G r o w t h r e s o u e s a r r e p o a s a i a - y e a r a v e r a g e . 10 9 P A C I F i C O R P - 2 0 1 1 1 R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S 28 0 62 47 5 11 8 11 8 11 8 12 . U - 18 . 9 . 1 1.8 J . - l 18 . 0 2.4 51 53 35 . 1 - i 45 80 80 35 35 35 1.6 0 0 1.6 0 0 J5 % C a i i c i t F a c t o 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 60 0 2.0 0 NE . 3 5 % C a n a c i t F a c t o 16 0 16 0 20 0 20 0 20 0 16 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 60 0 2,1 6 0 'H P . B i o m a s s 1.0 1. 0 1. 0 1.0 1.0 1.0 1. 0 1. 0 1. 0 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1. 0 1.0 1.0 10 20 HP . R e c i n a t i l l E n i r e 0.8 0.8 0.8 0. 8 0.8 0.8 5 5 DS M . C l a s s 1 U t a h - C o o l k e o e r 5.5 5 II II DS M C l a s s I G o h e n - D L C - l r t i 8 1 1 8 10 DS M C l a s s I U t a h - C u r i h n t 21 5 26 26 DS M . e m s s I , U t a h - O L e . R e s i d t i a l 10 22 5 37 37 DS M , C l a s i . U t a . D L C . I r r t i II 1 2 II 14 DS M C l a s s i U t a h . S c h e d T h r m E n e r l l S t o i r 2 2 2 '8 M C l a s s I T o t a l 16 48 20 12 2 3 % 10 1 DS M . C l a s 2 C h h e n I 1 I I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 16 45 DS M C J a s s 2 U t a 47 57 60 47 68 71 71 62 72 74 61 67 64 67 68 72 66 70 70 73 62 8 1. 3 0 8 DS M . C l M , 2 . W " " 3 4 4 5 5 6 7 7 8 8 9 10 II 14 15 20 21 25 31 33 57 24 6 ~M . C l s s 2 T o t l 51 62 65 53 75 79 79 71 81 85 72 79 78 84 87 95 91 98 10 4 10 9 70 1 1. 5 9 9 2. 6 2.6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2. 6 2. 6 4 2.6 4 2.6 4 2.6 4 2.3 7 24 45 16 8 26 4 26 4 99 99 89 45 20 0 1 20 0 20 0 32 20 0 18 8 20 0 20 0 14 2 71 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 19 85 98 12 0 12 6 II I 14 7 15 5 13 4 N/ A 10 0 54 13 6 17 31 6 32 3 N/A 10 0 21 53 77 13 8 12 6 48 17 16 4 N/ A 80 " I Un i - I 22 7 22 7 !, u . . i .1 . 1 . - l 21 6 21 6 3.7 . 1 . i 8. 3 12 12 70 70 70 70 70 58 35 0 40 8 10 0 10 0 20 0 20 0 10 0 10 0 20 0 20 0 50 50 50 4.2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4. 2 4. 2 4.2 4.2 4.2 4.2 42 84 CH p . R e c i n ~ ~ ; ~ 0.3 0. 3 0.3 0.3 0.3 0.3 2 2 DS M . C l a s s I W a l l W a D a . D L C . R e s k l n t i I 0 1 I DS M C l a s s I W a B a W a l J . D L C . I i t i 3 3 3 DS M C l a s I , O r e 2 O C a f i o m . C u r i l n t 17 17 17 DS M . C l a s s I , O r e i r C a l i o m . D L C . R e s i d n t i l 6 6 6 DS M C l a s 1 O r e l m C a l i o r - D L C . W a t e r H e a t e r 4 4 4 DS M . C l a s s 1 O r e l ! C a 1 i o c . D L C . l r r i m t i o 18 18 18 DS M C l a s 1 Y a k . O L C . R e s i d n t i a 4 4 4 DS M . C b s s 1 Y a k i . D L C . I r r t h n 4 2 6 6 8M C l s I T o t a l 49 4 6 60 60 DS M . C l a s s 2 W a l l W a l l 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 47 93 DS M C l a s s 2 O r e i : C a J i o m 51 51 54 59 61 60 60 52 52 52 52 52 52 53 53 53 45 37 37 37 55 2 1,0 2 2 DS M C l a s s 2 , Y a k i 10 11 7 7 7 7 7 7 7 7 8 9 9 9 10 7 6 7 7 7 75 15 4 !s M . C O " 2 T o t l 65 66 66 71 72 71 71 63 64 64 65 66 66 67 68 65 55 48 47 48 67 4 1,2 6 9 :8 D S t a n d r d 2 2 2 3 9 9 2 2 1 10 10 1. 8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1. 8 1 1.2 9 0.9 7 0.9 7 0.9 7 16 29 15 0 . 1 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 40 0 40 0 40 0 36 4 39 1 40 0 31 0 40 0 40 0 40 0 40 0 40 0 40 0 35 5 31 3 24 4 20 5 45 22 50 50 50 50 50 50 50 35 18 N/ A 38 N/ A 20 0 , ' '~ m i l "il ~ ~ '. ;" ' ~ "'l " ~ \ l ~ : ; g ' k ~ ¡ k \ ~ i l ' " 'll ~ ¡ ll ~ ' . , n m ' , ~ , ' ' t ~ , i l ". . hi ' '" F r o n o f f i c e t r a c t i a n d g r t h r e s o e a m o t s r e f l c t o n - y e a r tr n s a c t i p e r i , a n d a r n o t a d d e . "'' ' F r o n t o f f i c e t r a n s a c t i o a r e r e d a s a i o - y e a r a n n u a l a v e r a g e . G r r e s o e s a r r e a s a i o - y e a r a v e g e . 11 0 PA C I F i C O R P - 2 0 1 1 1 R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ta b l e D . 5 - H a r d C a p C 0 2 P o l i c y C o r e C a s e ( 1 5 t o 1 8 ) Ca s e 1 5 28 0 1,2 2 2 47 5 47 5 47 5 1.4 2 5 d" I 12 . 1 1 18 . 9 1 1.8 1 ,. 1 18 . 0 2.4 51 53 35 45 80 80 35 .3 5 Fa c t o 14 49 21 8 9 4 34 13 9 14 49 21 8 9 4 34 13 9 'H P * B i o s s 1.0 1.0 1.0 1. 0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 10 20 'H P - R e c i n o c a t i n V ' R m r i n e 0. 8 0.8 0. 8 0.8 0.8 0.8 0.8 0.8 6 6 DS M C l a s s i U t a h . C o o l k e n e r 5. 5 5 11 11 DS M C l a s s i G o h e n - D L C . l r r i m t i 8 . . 8 8 DS M , C l a s s I U t a h - C u r i l n t 21 5 26 26 DS M C l a s s i U t a h - D L C - R e s i d e n t l 11 20 5 37 37 DS M C l a s s i U t a h - D L C - I , . " ' ' ' t i 11 11 11 DS M C h s s i U t a h - S c h e d T h e o E n e . . ' S t o - 3 3 3 8M _ C l a s s I To t l 17 50 20 5 5 97 97 DS M , C h s s 2 . G o h e n 1 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 40 Ut a h 46 55 59 43 44 47 50 53 56 60 56 60 57 60 60 65 63 66 67 69 51 5 1.1 3 6 Wv o n 3 4 4 4 5 6 6 7 7 8 8 9 11 13 14 18 20 23 29 28 54 22 8 To t l 49 59 64 48 50 55 58 62 66 70 66 71 70 76 77 86 85 92 99 99 58 3 1.4 0 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2. 6 4 2.6 4 2. 6 4 2.6 4 2. 6 4 2.6 4 2. 3 7 24 37 16 8 26 4 26 4 73 77 38 20 0 1 20 0 20 0 17 53 19 3 20 0 10 6 53 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 30 0 30 0 21 0 25 5 15 0 15 8 20 32 45 59 18 0 20 2 15 5 16 1 13 9 NI A 10 0 58 38 4 16 NIA 46 24 3 30 7 57 19 6 19 7 NIA 10 0 .. 22 7 2! 21 6 ad 3. 7 8.3 .- ' 12 12 .t h r m G r e n f i e l d 70 35 70 10 5 Hp . B i o r s 8 4. 2 4.2 4. 2 4.2 4. 2 4.2 4.2 4.2 4. 2 4.2 4. 2 4. 2 4.2 4.2 4.2 4. 2 4.2 4. 2 4.2 4.2 42 84 HP _ R e c i n o c a t i n p ' E n m n e 0. 3 0.3 0. 3 0.3 0.3 0. 3 0.3 2 2 DS M C l a s s i W a l l W a l l - O l e - R e s i d n t i a l I I I DS M C l a s s i W a l l W a U a - D L C - l , . . . t i 3 3 3 DS M C l a s s i O r e o n C a l i o r . . u r i l n t 17 17 17 DS M , C l a s s I , O r e n o n C a l i o r - D L C - R e s i d n t i l 6 6 6 DS M C l a s s I O r e " " t r a l i a : n i - D L C . W a t e r H e a t e r 4 4 4 DS M C l a s s I O r e ø r / C a l i o m . D L C . 1 , . " " t i 18 18 18 DS M C l a s s 1 Y a k i - O L e . R e s i d n t l 4 4 4 DS M , C l a s s I Y a k i _ D L C _ I r r l J A t i 6 6 6 as s i T o t l 50 10 60 60 eB s s 2 . W a l l W a l l 4 4 4 5 5 5 5 4 5 5 5 5 5 5 5 5 4 4 4 4 45 89 Ch s s 2 . O r e o o C a t i o r 51 51 54 59 60 60 59 52 52 52 52 52 52 52 52 52 44 37 37 36 55 0 1. 0 1 6 DS M C l a s s - 2 Y a k n a 8 11 6 6 6 6 7 7 7 7 8 8 8 9 9 7 6 6 6 7 71 14 5 8M , C l a s s 2 T o t a l 63 66 65 70 71 70 71 63 63 64 64 65 65 66 66 64 54 47 47 47 66 7 1, 2 5 1 Ca n S t a n d d 2 2 2 3 .' 9 9 PO O 4 2 2 1 10 10 1. 8 1 1.8 1 1. 8 1 1.8 1 1.8 1 1.8 1 1.8 1 1. 8 1 1.8 1 16 16 15 0 15 0 15 0 15 0 50 65 33 40 0 29 9 40 0 40 0 .._ 4 0 ( 36 4 40 0 19 3 40 0 40 0 40 0 40 0 14 7 15 3 15 9 18 7 40 0 34 6 31 5 45 23 30 33 NI A 10 0 ~~ ~¡ h \ W ~~ m" f u \ ~ ' * ~ i t ' ~:' ~ , ir ": l § : " W ' ~ ii ' z~ " 't ~ , ~ ,'~ " " ' " il M " il 'fu ~ , , "'\ , 1 , " ,. oi F r o n t o f f i c t r n s a c t i n a n d g r t h r e s o u e a m o n t r e f l t o n - y e a r t r n s a c t i p e r i a n d a r e n o a d d e . oi ' " F r o n t o f f c e t r a n s a c t i o n s a r e r e p o r t e d a s a 2 0 y e a r a n n u a l a v e r a g e . 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T 18 . 0 2.4 51 53 35 45 80 80 35 35 35 cit y F a c t o T 4 9 4 34 50 4 9 4 34 50 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1. 0 1. 0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1. 0 1.0 10 20 0.8 0.8 0.8 2 2 5.5 5 11 11 li o T 8 2 8 10 21 3 25 25 21 11 32 32 iii o ì 11 3 11 14 26 37 20 3 5 87 92 I 1 I I 1 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 14 42 47 57 59 43 44 47 51 52 54 57 59 63 62 65 65 69 64 67 68 74 51 3 1,1 7 0 3 4 4 5 5 6 6 7 7 8 9 10 11 14 15 19 20 24 29 28 56 23 3 51 62 64 49 51 55 59 62 63 67 71 75 76 82 83 91 87 94 10 0 10 4 58 3 1, 4 4 6 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2. 3 7 24 34 16 8 26 4 26 4 73 77 38 18 9 1 . 20 0 20 0 17 58 20 0 18 8 10 5 53 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 12 2 30 0 21 0 24 6 15 0 15 8 20 32 11 6 11 0 22 3 99 13 3 12 5 13 6 N/ A 10 0 96 N/ A 10 10 7 25 6 45 3 11 4 41 N/A 97 - U n i t i R e n E a c e s Q r i l u n i 22 7 22 7 - U n i 2 R e D l a c e s O r à z l U n i 21 6 21 6 "W ' b i n e U n m a d s 3.7 8.3 12 12 Gr e n l l e k l 70 70 70 14 0 ::I P - B i o m a s s 4.2 4.2 4. 2 4. 2 4. 2 4.2 4.2 4.2 4.2 4. 2 4. 2 4. 2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 42 84 HP - R e c i ø o c a t i J ! E n i r e 0.3 0.3 0.3 1 1 DS M C l a s i W a l l W a l B - D L C - R e s i d n t l 1 1 1 DS M C l a s s 1 W a l l W a l h - D L C - I r r i i t i 3 3 3 DS M C l a s 1 O r e , w n l C a l i o r - C u r i h n t 17 17 17 DS M C l a s i O r e o o l i o r - D L C - R e s i d n t i a l 6 6 6 DS M C l a s 1 O r e ø o / C a l i o r l l - D L C - W a t e r H e a l e r 4 4 4 DS M C l a s s 1 O r e i r a l i o r n i ~ D L C - i r r t i o 18 18 18 DS M C l a s s i Y a k - D L C - I r r C n t i 6 6 6 DS M , C l a s s i T o t a l 50 6 56 56 DS M . C l a s s 2 W a l h W a l l 4 4 5 5 5 5 5 4 5 5 5 5 5 5 5 5 4 4 4 4 46 92 DS M C l a s s 2 . O r e l Z o n C a l i o r n i 51 51 54 59 60 60 59 52 52 52 52 52 52 52 53 52 44 37 37 36 55 1 1,0 1 8 DS M , C l a s s 2 , Y a k 8 11 6 6 6 6 7 7 7 7 8 9 9 9 9 7 6 7 6 7 72 14 9 SM . 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G r t h r e s o u c e s a r e r e p o e d a s a t o - y e a r a v e r a g e . 11 2 Ca s e 1 6 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S 28 0 1. 2 2 2 2.4 51 5i 35 1 I I I 45 80 80 35 35 35 1,6 0 0 1, 6 0 0 Fa c t o r T 40 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 44 0 2.2 4 0 ~i t F a c t o J. 16 0 16 0 16 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 20 0 60 0 2,4 0 0 1.0 1.0 1. 0 1.0 1.0 1. 0 1.0 1.0 1. 0 1.0 1.0 1. 0 1.0 1. 0 1.0 1.0 1.0 1. 0 1.0 1. 0 10 20 " I 0.8 0.8 2 2 I 5.5 5 ii ii lin J. 8 1 1 8 10 21 2 1 2 26 26 10 22 5 37 37 ii 1 2 ii 14 16 48 22 1 7 2 3 94 99 1 1 I 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 16 46 47 57 60 47 54 52 58 71 72 . 74 63 67 64 68 68 72 66 70 70 77 59 3 1, 2 7 9 3 4 4 5 5 6 7 8 8 8 9 10 12 14 15 20 21 25 31 29 58 24 3 51 62 66 53 60 60 67 80 81 85 74 80 79 85 87 95 91 98 10 4 10 9 66 6 1, 5 6 8 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 24 45 16 8 26 4 26 4 99 80 40 20 0 I 20 0 20 0 20 0 20 0 10 0 50 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 18 37 67 12 8 15 9 95 18 9 17 0 13 4 Nl A 10 0 82 38 94 34 4 44 1 N/A 10 0 32 7 33 4 33 9 N/ A 10 0 IU , ; T . T - T 22 7 22 7 !! U n i ) 1- - l . 1 - 21 6 21 6 3.7 8.3 12 12 70 35 70 70 70 70 35 38 5 42 0 Fa c t o r 10 0 10 0 10 0 Ic i t F a c t o r 10 0 10 0 10 0 10 0 10 0 20 0 20 0 ~B Î o i n a s s 50 50 50 HP - B i o m a s s 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4.2 42 84 'U P - R e c : . o c a t ; , . . E . . " ' n e 0.3 0 0 DS M C l a s s l W a l l W a l l - D L e - R e s i d n t l I I I DS M C l a s s I W a l l W a l l - D L C - I r i i z t D n 3 3 3 DS M C l a s I O r e o n / C a l i o m i - C u r e n t 17 17 )7 DS M C l a s s I , O r e a o n C a l i o r - D L C - R e s i d n t l 6 6 6 DS M C l a s s i O r e a o n C a l i o m i - D L C . 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G r o w r e s o u r c e s a r e r e p c d a s a I O - y e a r a v e r a g e . 11 3 PA C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X D ~ D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S 28 0 1,2 2 2 -- ~ - ~ ~ - -- 2,3 7 5 de s I 12 . 1 I 18 . 9 1 1.8 1 I 18 . 0 2. 4 51 53 35 45 80 80 35 35 35 cit y F a c t o r -- - I 42 28 21 8 9 20 0 30 8 42 28 21 8 9 20 0 30 8 1.0 1. 0 1.0 1. 0 1. 0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 10 20 at i m i : E n 2 i 1 0. 8 0.8 0. 8 2 2 5.5 5 Il Il to o .. 8 2 8 10 21 21 21 21 Il 32 32 Il Il 11 26 37 20 2 83 86 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 15 43 47 57 59 43 46 50 51 52 54 58 61 65 62 65 66 70 64 68 70 74 51 8 1.1 8 3 3 4 4 5 5 6 7 7 7 8 9 10 Il 14 15 19 20 24 30 28 56 23 7 51 62 64 49 53 57 60 62 64 68 72 77 76 82 84 92 88 95 10 3 10 5 58 9 1,4 6 3 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2. 6 4 2.6 4 24 34 16 8 26 4 26 4 16 71 36 18 9 . . 20 0 20 0 13 55 19 6 18 4 10 4 52 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 27 2 12 0 24 9 26 0 21 0 19 5 15 0 15 8 16 8 17 1 44 58 83 98 IL L 12 4 13 5 N/A 10 0 59 15 2 .. N/A 21 22 7 22 7 s ¡ ¡ . U i r i l R . . h c e s O r l U n i 21 6 21 6 '0 0 1 P l a n t T u r b i n U m m d e s 3.7 8.3 12 12 :o t h e n n 1 O r e n f l e k i 70 35 70 10 5 Wõ n , l Y a k i m 2 9 % , C a . . c i t F a c t o 10 0 10 0 10 0 .o i l W i i 10 0 10 0 10 0 'H P - B i o s 4.2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4. 2 4.2 42 84 'H P . R e c i n a t i n g E n Ø Ì 0.3 0. 3 0.3 1 1 DS M C l a s s i W a R a W a l a . O L e - R e s i d n t i l 1 I I DS M C l a s s 1 W a D a W a l l . D L C - I l ' l I f u 3 3 3 DS M C h s s 1 O r e ø n / C a l i o r - e i l n t 17 17 17 DS M e m s 1 . 0 r e 2 O C a l i o r - D L C - R e s i l n t l 6 6 6 DS M , e m s s 1 O r e u n C a l i o r - D L C - W a t e r H e a t e r 4 4 4 DS M C l a s s I , O r e 2 O C a l i - D L C . I r r i 2 t D n 18 18 18 DS M C l a s s 1 Y a k i - D L C - I r r i a a t i 6 6 6 SM . C l a s i T o t a l 50 6 56 56 DS M C l a s s 2 W a D a W a l a 4 4 5 5 5 5 5 4 5 5 5 5 5 5 5 5 4 4 4 4 46 92 DS M C b s s 2 0 r 2 O C a l i o m 51 51 54 59 60 60 59 52 52 52 52 52 52 53 53 52 44 37 37 36 55 1 1, 0 1 9 DS M . C l a s s 2 , Y a k i 8 II 6 6 7 7 7 7 7 7 8 9 9 9 9 7 6 7 6 7 72 14 9 To t a l 63 66 66 70 72 71 71 63 63 64 65 66 66 67 67 64 55 47 47 47 67 0 1, 2 6 1 2 2 2 3 9 9 2 2 1 10 10 1. 8 1 1.8 1 1. 8 1 1.8 1 1. 8 1 1.8 1 1. 8 1 1.8 1 1.8 1 1. 8 1 0. 9 7 0.9 7 16 20 15 0 J 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 24 3 40 0 40 0 40 0 28 0 40 0 15 0 15 6 14 5 16 9 33 2 19 7 24 4 20 3 45 22 50 50 50 50 50 50 50 50 50 50 50 50 5 45 30 24 4 15 0 15 3 13 2 13 9 14 4 39 N/A 10 0 ü ¡ § ' *~ ~ ~ ~ t , :: ~ ~ ! W ,, ~ "'t * ~ ,, ' . ,I l ' 1! ' ~: * m ¡ ,~ ' j f " I! , , , * l ~ F \ ~~ ~ ~ ~ 1 i : " ~ il ** , ' : ~ ~ t d â ~'& , ' l& §$ , " ' , . 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B i o s s 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 10 DS M C l a s 1 U t a h - C o o l k e r 5.5 5 11 11 DS M C l a s s i G o s l i e n M D L C - I r r t i o 8 2 8 10 DS M C l a s i U t a h - C u r t a Ü l n t 21 3 2 26 26 DS M C l a s i U t a - O L e - R e s i d n t i a l 21 11 5 37 37 DS M C l a s s i U t a h - D L C - I r r i m t i 11 3 11 14 D~ C b s s i U t a h - S e h e d T h e n n E n e r R V S t o r a i : 3 3 3 8M C l a s s i T o t a l 26 37 26 7 5 97 10 2 DS M C l a s 2 G o s h e n 1 I 1 I 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 15 39 DS M C l a s 2 U t a h 58 65 70 98 10 4 47 49 50 52 54 56 60 57 60 60 65 60 63 64 69 64 8 1.2 6 1 DS M C l a s 2 W _ m o 3 4 4 6 6 6 6 7 7 8 9 9 11 13 14 18 20 23 29 28 58 23 2 SM , C l a s s 2 T o t l 61 70 75 10 5 11 2 55 57 59 61 64 67 71 70 76 77 86 82 89 95 99 72 0 1.5 3 2 OT M e a d 3 r d O r i i L H 16 8 26 4 25 5 99 5 79 40 OT U t a h 3 r d O t t H L H 18 3 19 6 20 0 20 0 50 20 0 16 8 12 0 60 OT M o n - 3 3 r d O t t H L H 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 IT M o o . 4 3 n 1 O t t H L H 15 0 15 8 'o w R e s o u c e G o h e n . 7 21 33 46 60 19 4 12 3 25 3 12 5 13 8 N/ A 10 0 'o w h R e s o u r c e U t a h N o r * 35 3 33 8 30 9 N/ A 10 0 31 33 9 17 1 19 4 26 4 N/A 10 0 fc o a i P l a n t T W ' b i n e U n . . d e s 3.7 8. 3 12 12 tC H ! ' . Bio m a s s 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4. 2 4. 2 42 DS M C l a s 1 W a l l W a U a - D L C - R e s i d n t i a l 1 0 1 1 DS M C l a s i W a l l W a l l - D L C - I r r k m t i 3 3 3 DS M C l a s i O r e o o o C a l i O O - C u r i h e n t 17 17 17 DS M C l a s s i O r e t r o n C a l i o r - D L C - R e s i d n t i a l 6 6 6 DS M . C l a s s i O r e u o n C a l i c i - D L C - W a t e r H e a t e r 4 4 4 DS M C l s s i O ~ . . K ' a l i o r - D L C - I r r t i o 18 18 18 DS M C l a s s 1 Y a k - O l e - R e s i d n t l 4 4 4 DS M C l a s i Y a k i - D L C - I r r i i t i o 6 6 6 8M C l a s s I T o t a l 43 17 60 60 DS M C l a s 2 W a l l W a l h 4 5 6 7 7 5 5 4 4 4 5 5 5 5 5 5 4 4 4 4 51 95 DS M C l a s s 2 O r e o o n i C a l i o r 51 51 55 59 61 60 59 52 52 52 52 52 52 52 52 52 44 36 36 ' 36 55 1 1.0 1 6 DS M C l a s s 2 Y a k 10 11 9 12 12 6 6 7 7 7 8 8 8 9 9 7 6 6 6 7 87 16 1 SM C l a s 2 T o t l 65 67 70 78 80 71 70 63 63 63 64 65 65 66 66 64 54 46 47 47 68 9 1,2 7 2 'r e o n S o l a C a n S t a d a r d 2 2 2 3 9 9 re l Z o n S o l P i l o t 4 2 2 I 10 10 'T C O B 3 r d O t t H L H 15 0 15 0 15 0 15 0 50 65 33 'T M i C o l b i 3 r d r ; H L H 4Ó O 40 0 40 0 40 0 40 0 40 0 40 0 27 4 40 0 28 2 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 34 7 36 8 iT M i d C o l 3 r d O t t H L H 1 0 % P r i e P r e n i 24 4 20 5 45 22 T S o h C e n t r a l O r e o o n o r t h e m C a l i o r 3 r d O t r H 50 50 50 50 50 50 50 50 40 20 iw t h R e s o u c e W a U a W a U a . . 7 19 40 N/ A 7 -l 16 6 ', ' : ~ " ' , ~ ~ ~ ~ , ' : : , i l ~ " ; ' , , ~ " " ' ~ : ~ ~ ~ ' & , r ' " ; , ' : ~ ; ' " i l " : ' ,' ~ ~ , , ~ ~ : , , , , ~ ; , : ~ : ~ ~ : ~ ~ , ' ~ 1 ¥ ' , ~ : : t , ' ~ , ~ : , , : , " ; : : ~ " ~ i ~ " ' , ~ ; ~ , , ~ ~ ~ ~ ~ l : ~ , ~ " , , , ~ .. 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S - C o a l P l a n t U t i l i z a t i o n S e n s i t i v i t y C a s e s ( 2 0 t o 2 4 ) Ca s e 2 0 - 1.2 2 2 47 5 53 35 45 80 8õ 35 35 ,c i t F a c t o r I 11 49 20 8 9 4 34 13 4 11 49 20 8 9 4 34 13 4 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1. 0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 10 20 0.8 0.8 0.8 2 2 5.5 5 11 11 .t K I 8 1 1 8 10 21 5 26 26 21 11 5 37 37 11 1 2 11 14 St o r a . 2 e I 3 3 3 26 41 20 5 5 2 3 97 10 2 1 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 14 39 47 54 59 43 44 51 52 53 56 60 56 60 57 60 60 65 60 63 66 72 51 9 1.1 3 8 3 4 4 5 5 6 7 7 7 8 9 9 11 13 14 18 20 23 29 28 56 23 0 50 58 64 49 51 58 60 63 66 69 67 71 70 76 77 86 82 89 97 10 2 58 9 1,4 0 6 2.6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.3 7 24 39 16 8 26 4 26 4 20 72 36 19 0 I 20 0 20 0 17 50 19 0 20 0 io s 52 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 .. 15 8 19 11 5 13 6 65 14 3 97 15 8 12 4 13 NlA 10 0 51 29 0 30 2 35 7 N/A 10 0 10 11 6 32 8 31 6 23 0 N/A 10 0 3.7 8.3 12 12 70 35 70 10 5 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4.2 4. 2 4.2 4.2 4. 2 4. 2 4.2 4.2 4. 2 4.2 4. 2 4.2 4.2 42 84 0.3 0.3 0.3 1 1 Cla s i W a i W a J . D L C - R e s i d n t i i 1 1 1 Cla s s i W a l h W a l . D L C . I r t i n 3 3 3 Cl a s i O r o r l C a l o r - C u r i h n t 17 17 17 Cl a s i O r i i C a l o n - D L C c R e s i d n b 6 6 6 Cls i O r e o n / C a l o r . D L C . W a t e r H e a t e r 4 4 4 Cl a s i O r e m v C a l i o r - D L C . J r r a t I 18 18 18 Cl a s i . Y a k - O L e - R e s i d n t 4 4 4 l1 t K 6 6 6 50 10 60 60 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 46 91 51 51 54 59 60 60 59 52 52 52 52 52 52 52 52 52 44 36 37 36 55 1 1. 0 1 6 8 11 6 6 6 7 7 7 7 7 8 8 8 9 9 7 6 7 6 7 72 14 6 63 66 66 70 72 71 71 63 63 64 64 65 65 66 66 64 54 47 47 47 66 9 1, 2 5 4 2 2 2 3 9 9 2 2 1 10 10 1.8 1 1.8 1 1.8 1 LS I 1. 8 1 1.8 1 1.8 1 L. S I LS I 1. 8 1 1. 8 1 1.8 1 LS I 0.9 7 0.9 7 16 25 15 0 I 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 29 8 40 0 40 0 40 0 36 2 40 0 37 2 40 40 40 0 40 0 40 40 0 40 0 40 0 40 34 6 37 2 24 4 20 6 45 23 50 50 50 50 50 SO 50 50 50 50 50 50 50 50 50 50 35 40 N/ A 10 0 Nl A 74 N/ A 10 0 Mt fu ~ , " , W , ..¡ ¡ "lO t ' fu ' l '," " ' \$ ~ "ll , , : ¡ i ¡ i , ' t , " ' i h : \~ ~ M ~ ~'§ ' " ,~ . ~'$ ~ ' * ~" ; ; m ' ~ ~ ' :, ~ ~ ~ 1 j ' * ~; , ¿ * ~ " l h ' t " ¡¡ ,l S ¡ ~ " ~ . '! ' 1 1 j '" F r o o f f c e t m n s a c t i a O g r w t h r e s O W c e a m o t s r e f l t o n - y e a r t r a c t i p e r D . a n d a r e n o a d d . "'* F r o t o f f c e t r a n a c t a r e r e d a s a 2 O y e a r a n u a l av e r a g e . G r o w re s o u e s a r e r e p o d a s a i o - y e a r a v e r g e . 11 7 PA C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ca s e 2 1 *- 28 9 1, 2 2 2 47 LZ . L 18 . 9 1.8 . I 18 . 0 . I 2. 4 1 51 53 3U - - i - . 1 - . . - i 45 . 1 - . . - i - . 1 80 80 35 35 11 3 34 48 11 3 34 48 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1. 0 1.0 1. 0 1.0 1.0 1. 0 10 20 0.8 0.8 0.8 0.8 0.8 0. 8 0.8 5 5 5.5 5 11 11 ,l i T 8 I I 8 10 21 5 26 26 11 20 5 37 37 11 i 2 11 14 3 3 3 17 50 20 5 5 2 3 97 10 2 i I I I I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 38 46 55 59 43 44 47 50 53 55 64 56 60 57 60 60 65 60 63 64 69 51 7 1,1 3 0 3 4 4 4 5 6 6 7 7 8 8 9 10 13 14 18 20 23 29 28 55 22 6 49 59 64 48 51 55 58 62 64 74 66 70 69 76 77 86 82 89 95 99 58 6 1.3 9 4 2.6 4 2. 6 4 2.6 4 2, 6 4 2.6 4 2.6 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2. 6 4 2.6 4 24 34 16 8 26 4 26 4 24 72 36 20 0 . 1 20 0 20 0 17 57 19 8 20 0 10 7 54 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 19 32 44 11 8 18 2 11 8 17 3 17 3 13 7 N/ A 10 0 68 66 37 4 32 7 16 4 N/ A 10 0 27 0 32 3 40 7 N/ A 10 0 38 9 38 9 3.7 8.3 12 12 70 70 70 14 0 4.2 4.2 4.2 4.2 4. 2 4.2 4. 2 4.2 4.2 4. 2 4.2 4.2 4. 2 4.2 4. 2 4.2 4.2 4.2 4.2 4. 2 42 84 0.3 0.3 0.3 0. 3 i i Cla s i W a l l W a 1 l . D L C . R e s ü c n t J i i I Cla s I W a l l W a l à - D L C . l n i o a t i o 3 3 3 Cl a s i O r e ~ o W C M Ø o o ~ m 17 17 J7 Cl a s i O r e . . / C a l i c n - D L C . R e s i d n m l 6 6 6 Cla s i O r e i i o n C a l m n - D L C . W a t e r H e a t e r 4 ,. 4 4 Ci 8 s i O r e o n l i o r . D L C - l r i c t i 18 18 18 Cla s i Y a k i - O L e - R e s i d n t 4 4 4 0 Cla s i Y a k - D L C - I r r i i t i 6 6 6 ro S M Cla s I T o t l 50 6 4 60 60 OS Cl a s W a l W a l B 4 4 4 5 5 5 5 4 5 5 5 5 5 5 5 4 4 3 4 4 45 88 DS M C l a s O r e o n / C a l i o m 51 51 54 59 60 60 59 52 52 52 52 52 52 52 52 52 44 36 36 36 55 0 1,0 1 5 OS Cl a s Y a k i 8 iI 6 6 6 6 6 7 7 7 7 7 7 8 9 7 6 6 6 7 70 14 0 To t l 63 66 65 70 71 70 70 63 63 64 63 64 64 65 66 63 54 46 46 47 66 5 1.2 4 3 'a D Sta d 2 2 2 3 9 9 2 2 i 10 10 1.8 1 1.8 1 1. 8 1 1.8 1 1.8 1 1. 8 1 1.8 1 1. 8 1 1.8 1 1.7 0 L.S I LS I LS I 16 23 15 0 15 0 15 0 15 0 50 65 33 HL R T 40 40 0 40 0 29 9 40 40 0 40 0 37 0 40 0 40 0 40 0 40 40 0 40 40 0 40 0 40 40 0 40 0 34 7 37 3 24 4 20 6 45 23 HL I - 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 35 43 N/ A 10 0 N/ A LO L N/ A 10 0 'i l ¡¡ ' " '% " ' ' i i W ' ' " ¡ ~ ~ ~ ~ i 0 .: ' ~ \ ¡ f f ~ ¡t % ' È ' ~ ~ ; , ¡ ¡ , e ¡ 6 - ~ il f: m m ~,% ~ ' % ú \ ~ ' i , & " " " . . . . " . . , ''' ' ' ' ' ' ' ' , ' w * . . . I W . , , ~ ' t ~ ¡ ¡ ~ . " ." . , ,. ~ 'i l i l ",l ! ¡ ~ " , ' *' il . F r o n o f f i c e t m a c t i n a n g r w t r e s o c e a m o t s r e f l c t o n - y e a r t r a n a c t I p e r i , a n d a r e n o a d d . .. F r o t o f f i c e l r a c O O a r e r e p o e d a s a 2 O - y e a a n u a l a v e r a g e . G r o w re s o e s , a r e r e p d a s a i o - y e a r a v e r a g e . 11 8 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ca s e 2 2 12 . 1 2.4 45 35 9 4 34 9 4 34 ~ 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1. 0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 ~a t i E n 2 I e 0.8 0.8 0.8 ~ 5. 5 5 f- li I 8 1 r' ~ 21 5 7 3 1- 10 21 5 I- 11 I 2 f- 16 48 20 10 2 3 7 3 ~ I I I 1 I 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 I- 47 57 59 43 46 50 52 54 55 60 59 63 62 65 65 69 64 69 70 77 ~ 3 4 4 5 5 6 7 7 7 8 9 10 II 14 15 19 20 24 30 28 ~ 51 62 64 49 53 57 61 63 65 69 71 75 76 82 83 91 87 96 10 3 10 8 ~ 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2. 6 2.6 2. 6 4 2.6 4 2. 6 2.6 4 2. 3 7 2.3 7 f- 16 8 26 4 26 4 20 ~ 20 0 1 20 0 20 0 17 43 18 4 20 0 ~ 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 f- 15 0 ~ 19 10 5 53 12 1 14 7 97 15 7 16 1 13 6 'N 57 14 8 33 9 45 6 ~ 42 21 8 34 36 0 34 4 ~ 3.7 8.3 12 12 70 70 70 14 0 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4.2 4. 2 4.2 4.2 4.2 4. 2 4.2 4.2 4.2 42 84 0.3 0. 3 0.3 I 1 Cl a s s 1 W a J W a I h - D L C - R e s i l i i l I I 1 Cla s i W a l b W a l l . D L C - I r a t i n 3 3 3 Cla s I O r e ø o n C a l i o m - C u i k n t 17 17 17 Cl a s s i O r I ! O n / C a l o m - D L C - R e s i d e n t Ø ! 6 6 6 Cla s s I O r e 2 o n C a l i o r - D L C - W a t e r H e a t r 4 4 4 Cl a s s i O r P r / C a l i o m . D L C . l r i i t i 18 18 18 Cl a s I Y a k - O L e - R e s i d t i l 4 4 4 Om C l a s s i Y a l . D L C . I r i u " t i 6 6 6 rD S M C l a s s 1 T o t a l 50 10 60 60 DS M C l a s s 2 W a l W a J 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 46 92 DS M . C l a s s i O r e 2 o n C a l o m 51 51 54 59 60 60 59 52 52 52 52 52 52 52 53 52 44 37 37 36 55 1 1,0 1 9 DS M . C l a s 2 Y a k 8 11 6 6 6 7 7 7 7 7 8 9 9 9 9 7 6 7 6 7 72 14 9 To t 63 66 66 70 72 71 71 63 63 64 65 66 66 67 67 64 55 47 47 47 67 0 1.2 6 0 2 2 2 3 9 9 2 2 I 10 10 1. 8 1 1.8 1 LS I 1.8 1 1.8 1 1.8 1 1.8 1 1.8 1 1. 8 1 1.8 1 1.4 2 0.9 7 0. 9 7 0.9 7 16 22 15 0 . l 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 29 7 40 0 40 0 40 0 31 7 40 0 40 0 40 40 40 0 40 0 40 40 0 40 0 40 0 40 0 34 1 37 24 4 20 6 45 23 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 35 43 N/A 31 N/A 10 0 N/A 10 0 iL w , ; ' ~ 4 N 1 f f W "'m ¡" ~ -¡ g ~~ ¡ ¡ ~ il ~- , i l ' 'm ' f f : ; "W ~ ; " & - % : ~ . . , ;t : l t \ " t ' ., ,, ~ " § , " ; ; ; , ~ , , ' h " ' f ~t , ~ - " , ; . i g ~" ~ l . 0 ' t ' ' ' l i ~ t ~ ~\~ il , i i n , ~ i : l , ¡¡ ; "'M , ' , . F r o o f f c e t r a c t i a n d g r t h r e s o u e a m o t s r e ß x t o n e - y e a r t r n s a c t i p e r i o , a n a r e n o t a d d . .. F r o n t o f f i c e t r c l I n s a r e r e p o d as a 2 O y e a r a n u a l av e r a g e . G r o w re s o u c e s a r e r e p d a s a t o - y e a r a v e r a g e . 11 9 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ca s e 2 3 - 57 8 1.2 2 2 .T . T 18 . o T -T -T - T .T 2.4 T . T .T . T - T - T 1,4 2 5 12 . 1 1 18 . 9 1 1.8 L 51 53 35 1 - . 1 . - L 45 1 - I 80 80 35 35 3 9 4 34 49 3 9 4 34 49 1.0 1.0 1.0 1. 0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1. 0 1.0 LO 1.0 1.0 1.0 1.0 1.0 1.0 10 20 'H P - R e c i n a t i ~ 0. 8 0.8 0. 8 0.0 2 2 DS Cl a s s i U t a o o l k e e n e r 5. 5 5 II II DS Cl a s s i G o h e - D L C . I r t i 8 I I 8 10 DS Cl a s l U t a . C u r n t 21 5 26 26 DS Cl a s i U t a h - O l e - R e s i d t i a l II 21 5 37 37 DS Cla s ) U 1 a . D L C - I 1 T . . t i II I 2 II 14 DS Cla s i U t a - S c h e T h n n E n l ' S t o r a t r 3 3 3 'S M Cl a s s I T o t l 16 51 20 10 1 I 3 97 10 2 DS Cl a s 2 G o h e I 1 I I 1 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 14 41 DS Cl a s ' U t a 47 54 59 43 44 51 52 54 57 60 56 63 61 63 64 69 64 67 68 74 52 0 1,1 6 9 DS Cl a s 2 W v o 2 3 4 4 5 5 6 7 7 7 8 9 9 11 14 15 19 20 24 29 28 56 23 3 ~M . C l a s s 2 T o t 50 58 64 49 51 58 60 63 66 69 67 75 74 80 82 91 87 94 10 0 10 4 59 0 1,4 4 4 2.6 4 2.6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2. 6 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2.3 7 2. 3 7 24 36 16 8 26 4 26 4 21 72 36 20 0 1 20 0 20 0 17 44 18 5 20 0 10 5 52 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 -- 15 8 19 10 0 98 15 1 11 8 11 5 13 4 12 3 13 6 N/A 10 0 10 13 4 35 3 44 57 N/A 10 0 27 35 13 0 76 28 3 30 2 14 1 N/A 10 0 77 8 77 8 3. 7 ., 12 12 70 70 70 14 0 4.2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 42 84 0.3 0.3 0.3 1 i Cl a s I W a l à W a l l . O L e . R e s i d n t l I 1 I Cl a s i W a I B W a l à . D L C . I I ' . . . . t i i 3 3 3 Cla s i Q r a n n l C a l c r - C W 1 m l n 17 17 17 Cl a s 1 O r l ! o o C a l o o - D L C - R e s i d e n t i l 6 6 6 Cla s i O r i r C a l c r - D L C . W a t e r H e a t r 4 4 4 Cla s i Q r ø n n / C a l i O l - D L C - l r r a t i 18 18 18 Cl a s i Y a k - O l e - R e s i d n t l 4 4 4 Cla s i y a k _ D L C . J m o . . t i 6 6 6 ¡L s s ! T o t 50 io 60 60 Cla s ? W a U W a l l 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 46 91 CW , Or e 2 m / C a ! o m 51 51 54 59 60 60 59 52 52 52 52 52 52 52 53 52 44 37 37 36 55 1,0 1 8 DS M C l a s ' Y a k i 8 II 6 6 6 6 7 7 7 7 8 8 8 9 9 7 6 7 6 7 71 14 7 8M C l a s s l T o t l 63 66 65 70 72 71 71 63 63 64 64 65 66 67 67 64 55 47 47 47 66 8 1,2 5 7 2 2 2 , 9 9 2 2 i 10 10 1.8 1 1. 8 1 LS I UL L 1. 1 LS I 1. 8 1 1.8 1 1. 8 1 0.9 7 0.9 7 16 18 15 0 Î 15 0 15 0 15 0 50 65 33 40 0 40 0 40 29 8 40 0 40 0 40 0 35 7 40 40 0 40 0 40 0 40 0 40 0 40 40 0 40 0 40 0 40 34 5 37 3 24 4 20 6 45 23 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 35 43 N/ A 38 N/ A 10 0 if ' t ~ ~ ~ . ii "'" , i l ' - ", ; , ! i 'W I ' " ", . * " ' ê R , .. F r o n o f f i e t r a a c t i o a n g r o w l h r e s o u c e a m o t s r e f l c t o n - y e a r t r n s a c O O p e r i , a n d a r n o a d d . .. F r o t o f f i c e t r a n c t i a r r e p o d a s a 2 O - y e a r a n u a l av e r a g e . G r re s o u e s a r e r e p o e d as a I O - y e a r a v e a g e . 12 0 P A C I F I C O R P - 2 0 1 1 I R P AP P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ca s e 2 4 - 28 9 1. 2 2 2 1. 4 2 5 12 . i T 18 . 9 T 1. 8 T - T IS . O 2.4 51 53 35 45 80 80 35 35 35 Fa c t o r T 3 9 4 34 49 3 9 4 34 49 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1. 0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 10 20 0. 8 0.8 0.8 2 2 5.5 5 11 11 ti T 8 1 I 8 10 21 5 26 26 21 II 32 32 11 1 2 II 14 26 37 20 5 2 3 88 93 1 I I I 1 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 14 42 47 57 59 43 44 47 51 52 54 57 59 63 61 65 65 69 64 67 68 77 51 1,1 7 1 3 4 4 5 5 6 6 7 7 8 9 10 II 14 15 19 20 24 29 28 56 23 4 51 62 64 49 51 55 59 61 63 67 71 75 74 82 83 91 87 94 10 0 10 8 58 3 1,4 4 7 2. 6 4 2.6 4 2. 6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2. 6 4 2. 6 4 2.6 4 2.6 4 2.3 7 2. 3 7 24 36 16 8 26 4 26 4 73 77 38 18 9 1 20 0 20 0 17 57 19 9 18 7 10 5 52 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 20 41 12 2 15 1 17 8 97 12 6 12 13 6 N/A 10 0 66 18 4 57 9 17 0 N/A 10 0 14 6 23 9 25 6 18 9 16 9 N/A 10 0 77 8 77 8 3. 7 8.3 12 12 70 70 70 14 0 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 42 84 0.3 0.3 0. 3 1 I Cl a s I W a l l W a l h - D L C - R e s i d l 1 1 I Cla s i W a l h W a i h - D L C - I r r i r i r 3 3 3 Cl a s 1 O r e i i o n C a l i m i . C w i h n t 17 17 17 Cl s i Q r e . l o o C a l m i . D L C - R e s i d n t l 6 6 6 Cl a s i O r e i i o n C a l o r . D L C . W a ! e r H e a t e r 4 4 4 Cla s I O r e i z æ i C a l i o r - D L C - l r t i 18 18 18 DS M _ C l a s t , Y a k i - D L C - I r i i m t i 6 6 6 '8 M C h s s I T o t a 50 6 56 56 DS M . C l a s Wa l W a l J 4 4 5 5 5 5 5 4 5 5 5 5 5 5 5 5 4 4 4 4 46 92 DS M . C l a s 2 . û r e . e o n C a l o m 51 51 54 59 60 60 59 52 52 52 52 52 52 52 53 52 44 37 37 36 55 1 1,0 1 8 DS M . C l a s 2 . Y a k i 8 11 6 6 6 6 7 7 7 7 8 9 9 9 9 7 6 7 6 7 72 14 9 iS M e m s 2 T o t l 63 66 66 70 72 71 71 63 63 64 65 66 66 67 67 64 55 47 47 47 66 8 1.2 5 9 ~e i t o n S o r C a o S t a n d 2 2 2 3 9 9 2 2 1 10 10 1.8 1 LS I 1.8 1 LS I 1.8 1 1.8 1 1.8 1 1. 8 1 1.8 1 0. 9 7 0.9 7 0. 9 7 16 19 15 0 I 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 29 8 40 0 40 40 0 33 40 0 40 0 40 0 40 0 40 0 40 0 40 40 0 40 0 40 0 40 0 34 3 37 2 24 4 20 6 45 23 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 30 40 N/A 51 N/A 10 0 "S i ' *~ ' W , ~t' t 1 i .~ il ''' , * in " ~ ~ '% ~in ~ ~ \ ~ ",' a " : ' ~ ':" . ~ g " , . m %" " '" , " " , ' " ~, " ' , ~: , * ~ % " " " ,. % ' W : ~ ' . ~ : ~ ~ ~ 't L 0 l b ~ il ~~ .. F r o n t o f f e t r a c t i a n g r w t h r e s o u e a m o r e f l c t o n y e a r t r n s a c t i p e r i o , a n a r e n o t a d d e . "'. F r o o f f i c é t r a n a c t i s a r e r e p o as a 2 O y e a r a n l a v e r a g e . Gro w t r e s o i c s a r r e p o r t e d a s a I O - y e a r a v e r g e . 12 1 P A C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ta b l e D . 9 - L o a d F o r e c a s t S e n s i t i v i t y C a s e s ( 2 5 t o 2 7 ) Ca s e 2 5 CC C T F 2 x l 1. 2 2 2 Co l P l a n t T u r b i i e U 53 Ge o t h r m B l u e D 3 35 45 80 Ge o t e r m G r e e n f i e l d 35 35 Wi l d W o m n 3 5 % C a c ' F a c t o r 20 20 Wil d , W o m i n N E 3 5 % C a c ' F a c t o 16 0 16 0 Wi n d 16 0 20 18 0 -B i o m a s 1.0 1.0 1. 0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1. 0 1. 0 1.0 1.0 1.0 10 20 CH P - R e c ' o c a t i . E " e 0.8 0.8 0.8 0,8 0.8 0.8 5 5 DS M C b s s i U t a h _ C o o D r 5.5 5 II II DS M C l a s s i G o s h e n - D L C - I r ' t i 8 2 8 10 DS M C a s s i U t a h - C u r i b n l 21 3 2 26 26 DS M , C l a s s i U t a h - D L e - R e s i d n t l 32 5 37 37 DS M C l a s s i . U t a h - D L e - . l i i II 3 II 14 DS M C b s s J U t a - S c b e d T h E n e Sl m o 3 3 3 DS M , C l a s i T o t a l 6 58 26 7 5 97 10 2 DS M C l a s s Go h e n I I I I I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 39 DS M C l a s s Ut a 47 63 62 65 49 52 59 53 56 64 56 60 57 60 60 65 60 63 64 69 57 1 1,1 8 4 DS M C l a s s 2 . W o m i 3 4 4 5 5 6 7 7 7 8 9 9 II 13 14 18 20 23 29 28 56 23 1 DS M , C l a s 2 T o t l 51 68 67 71 55 59 67 63 66 74 67 71 70 76 77 86 82 89 95 99 64 2 1. 4 5 3 2.6 2.6 2.6 2.6 2.6 2.6 2.6 2.6 2. 6 24 24 16 8 26 4 26 4 4 99 80 40 19 5 19 9 20 0 68 20 0 20 0 10 6 53 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 83 12 0 20 1 20 1 21 3 15 0 31 NIA 10 0 42 32 2 27 3 36 4 NIA 10 0 43 23 2 34 3 38 1 NIA 10 0 Co l P l a n t T u r b i n e U ad e s 3.7 8. 3 12 12 Oe e r m G r e e n f J e k i 70 70 70 CH P - B i o s s 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 42 84 CH P - R e c ' o e a ' E . e 0.3 0.3 0.3 0.3 0.3 0.3 2 2 DS M C l a s s i W a I B W a I - D L C - R e s i d n t l I 0 I I DS M C l a s s i W a l l W a l l - D L C . "" 3 3 3 DS M C l a s s l O r e Ca f i o m - C u i l n t 17 17 17 DS M C l a s s I O r e o n l C a l i o m - D L C - R e s i d n t i a l 6 6 6 DS M C l a s s i O r e Ca t i o r i a . D L C - W a t e r H e a t e r 4 4 4 DS M , C b s s I O r e Ca l i o r i a . O L e - l a ' i i m 18 18 18 DS M C n s s I , Y a k i - D L C - R e s i 1 m i a l 4 4 4 DS M , C l a s s t , Y a k - D L C . I . t i o 6 6 6 8M , Cl a s s i T o t l 43 17 60 60 DS Cla s s 2 W a l h W a U a 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 47 91 DS M C l a s s 2 O r e Ca l i o r i a 51 51 54 59 60 60 59 52 52 52 52 52 52 52 52 52 44 36 36 36 55 1 1.0 1 6 DS M C l a s s 2 Y a k i 6 6 7 7 7 7 7 7 7 7 8 8 8 9 9 7 6 7 6 7 67 14 1 DS M , C l a s 2 T o t a l 62 62 66 71 72 71 71 63 63 64 64 65 65 66 66 64 54 47 47 47 66 5 1,2 4 9 So l a r C a S t a n d r d 2 2 2 3 9 9 So l a P i b 4 2 2 I 10 10 Wa t e r He a t e r 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1. 8 1. 8 16 16 15 0 15 0 15 0 15 0 50 65 33 23 40 0 40 0 40 0 40 0 40 0 40 0 25 8 39 6 40 0 24 9 34 2 35 9 40 0 40 0 40 0 40 0 40 0 40 0 34 8 34 1 27 1 21 0 48 24 HL H I 50 50 50 50 50 50 50 35 18 NI A 53 NI A 41 NI A 20 0 - F r o n t o t T i c e t r n s a c t i o a n d g r o w t h r e s o u e a m o t s r e f l c t o n e - y e a r t r a n s a c t i o p e r m , a n a r e n o t a d d i t . b F r o n t o f f i c e t r n s c t i a r e r e p o d a s a 2 o - y e a r a n n u a l a v e r a g e . G r o w t r e s o u e s a r e r e p o e d a s a i o - y e a r a v e a g e . 12 2 PA C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ca s e 2 6 - '~ ' , " ' " ' ~ " ~ ~ , \ ~ ' 1 ~ ¥ ¥ ~ , * 1 & \ ' % Y ' i l l l ' l " ' \ ~ § , v ~ ' , , ~ , 1.8 1 9 ii 18 . 9 1 1.8 1 .1 18 . 0 2.4 51 53 35 45 80 80 35 35 35 Fa c t o r 52 52 Ca n a d v F a c t o r 16 0 16 0 16 0 52 21 2 'H P - B i o s 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 10 20 'H P - R e c i n o c a t i n g E n m n e 0. 8 0.8 0.8 0.8 0.8 4 4 DS M C l a s i U t a b - C o o l k e n e r 5. 5 5 II II DS M , C l a s s i G o h e n - D L C - I r r i l m t I o n 8 2 8 10 DS M C l a s s I U t a b - C u i k n t 21 3 2 26 26 DS M C l a s s i U t a h . D L e . R e s i d n t i a l 32 5 37 37 DS M , C l a s s 1 U i a h - D L C . l r t i II 3 II 14 DS M , C l a s s i , U t a h - S e h e d T h e n E n e r i i S t o r a l ! e 3 3 3 8M C b s s i T o t a l 6 62 23 7 5 97 10 2 DS M , C l a s s 2 G o h e n I I I I I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 39 DS M . C l a s s 2 U t a h 46 55 59 54 47 51 52 55 71 74 56 60 57 60 60 65 60 63 64 72 56 3 1,1 7 9 DS M C l a s 2 W v o l I 3 4 4 5 5 6 7 7 7 8 9 9 II 13 14 18 20 23 29 28 56 23 0 Iõ S M C l o s 2 T o t l 49 59 64 60 53 58 60 64 81 84 67 71 70 76 77 86 82 89 95 10 2 63 3 1. 4 4 7 2.6 2. 6 2.6 2.6 2.6 2.6 2.6 2. 6 2. 6 2.6 2.4 2.4 2.4 2.4 24 36 16 8 26 4 26 4 45 99 84 42 20 0 20 0 20 0 11 9 8 20 0 93 46 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 45 35 15 5 18 6 12 0 14 6 19 8 10 3 12 N/ A 10 0 31 8 30 0 38 2 N/A 10 0 10 5 24 1 26 3 39 1 N/ A 10 0 3. T . T 8.3 12 12 70 70 70 50 50 50 4. 2 1 4. 2 1 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4. 2 4.2 42 84 0.3 0.3 l 0. 3 0. 3 I I I I I 3 3 3 17 - 17 17 6 6 6 4 4 4 to o T 18 18 18 I 4 4 4 to o I 6 '. 6 6 50 10 60 60 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 47 91 51 51 54 59 60 60 59 52 52 52 52 52 52 52 52 52 44 36 36 36 55 1 1.0 1 6 6 6 7 7 7 7 7 7 7 7 8 8 8 9 9 7 6 7 6 7 67 14 1 61 62 66 71 72 71 71 63 63 64 64 65 65 66 66 64 54 47 47 47 66 4 1.2 4 8 2 2 2 3 9 9 2 2 I 10 10 1.8 1.8 1. 8 1. 8 1.8 1.8 1.8 1.8 1.8 1.0 1. 0 1. 0 1. 0 1.0 16 21 15 0 1 15 0 15 0 15 0 50 65 33 25 40 0 40 0 40 0 40 0 40 0 20 8 36 0 40 0 40 0 14 25 5 28 0 31 8 40 0 40 0 40 0 40 0 40 0 40 0 33 9 33 3 27 1 21 0 48 24 HL H T 50 50 50 50 50 50 50 35 18 18 5 16 0 17 3 17 8 17 4 N/A 94 N/A 39 N/A 20 0 '" m ~ ' : ~ ' % '. ',, ~ ; ¡ !m om ''' ~ % i il " ~ 1 ( ~ '- ~ , : : ~ ~ " , ;iw ' , . :" '~ ~ : ~ ' ~ ,* ~ : "': W ' + , " ",' ~ ' , ~ - ' \ ~ , ~ ~ " "! í ~, " , , ' .o m .. F r o t o f f i c e t r n s a c t i a n d g r o w t h r e s o u r e a n u n t s r e f l c t o n - y e a r t r s a c t p e r h d , a n d ar e n o t a d d i t . .. . F r o n t o f f l C e t r n s c t i o s a r e r e p o e d a s a 2 Q y e a r a n n l a v e r a g e . G r w t r e s O W e s a r e r e p o e d a s a i o - y e a r a v e g e . 12 3 PA C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ca s e 2 7 ,2 ~ % ~ ~ ~ ì ~ ~ ~ ~ ~ : § I ~ ~ '~ "" ~~ ~ 2 ' t ~ t " , , 1 j ¡ . 1 j ~ l l N ¡ . ~ t l t ~ ~ ~ i l ~ ¡ u R ~ iW !I il iW iW I 62 5 59 7 59 7 1,8 1 9 1,8 1 9 ,u i a h 23 6 23 6 23 6 'o a ! P l a n t T u r b i n U r n d e s 12 . 1 , 18 , 9 1.8 18 , 0 2A 51 53 il G e o t , n n B h m d e D 3 35 45 80 80 ~G e o t h e n n G r n l i e k i 35 35 35 Wii W v o m Î n ø . 3 5 % C a n A c Ï l F a c t o r 9 9 Win W v n m a N E 3 5 % C a m i l ' t v F a c t o r 16 0 16 0 IT o t a l W i n d 16 0 9 16 9 CH P . B i o m a s s 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 10 20 ât' l C H P - R e c i n o c a t 1 1 1 E n i r e 0,8 0- 8 0,8 0, 8 0, 8 0, 8 0. 8 0-8 6 6 DS M C l a s s i U m h - C o o l k e n e r 55 5 11 11 DS M _ C l a s s i G o h e n - D L C - I n k m t i 8 2 8 10 DS M C l a s s 1 U t a b . C u i m n t 21 3 2 26 26 DS M C l a s s i U l a h - O L e - R e s i d n t i l 32 5 37 37 DS M C l a s s i U t a - D L C - I r T i m t Ï J 11 3 II 14 DS M , C l a s s t , U t a h . S c h e d T l e r E o e r l 7 S t o a l J e 3 3 3 8M C l a s 1 To t l 6 58 23 2 9 5 97 10 2 DS M ; C l a s s 2 G o h e n I I I i I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 39 DS M C l a s s 2 U c a b 46 59 59 46 49 52 53 61 71 74 56 60 57 60 60 65 60 63 64 69 56 9 1,1 8 3 DS M C B S S Wv r n . 3 4 4 5 5 6 7 7 7 8 9 9 11 13 14 18 20 23 29 28 56 23 0 'S M , C l a s 2 T o t l 49 63 64 52 55 59 62 70 81 84 67 71 70 76 77 86 82 89 95 99 64 0 1,4 5 2 ) S o l r - W a t e r H e a l e r 2, 6 2,6 2, 6 2, 6 2, 6 2,6 2, 6 2, 6 2.6 24 24 Me a d 3 r d O t H L H 16 8 26 4 26 4 99 80 40 Uta 3 r d O t t H L H 20 0 20 0 17 7 50 20 0 20 0 10 3 51 Mo n a - 3 3 r d O t t H L H 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 Mo n - 4 3 r d O t t H L H 15 0 15 8 Go h e n ' 57 11 9 96 21 3 25 5 13 5 12 5 N/ A 10 0 Uta h No r h , 31 0 35 6 33 4 N/ A 10 0 52 27 5 29 3 38 0 N/ A 10 0 3,7 1 I 83 12 12 70 70 70 50 50 50 'H P - B i o s s 4. 2 4. 4.2 4, 2 4. 4. 4,2 4.2 4. 4,2 4,2 4. 4.2 4,2 4,2 4, 2 4, 2 4, 2 4.2 4.2 42 84 HP . R e c i n o c a t i o E n o i e 03 03 03 03 03 0.3 03 03 3 3 DS M C l s s i W a l l W a l h . D L C - R e s k l n t i a l I I i DS M C l a s s i W a l l W a l l . D L C - J r M m f h n 3 3 3 DS M C l a s i O r e o n / C a l i o r - C u i h n t 17 17 17 DS M C b s s i O r e o - o n C a t i o r - D L C - R e s I f o t i a l 6 6 6 DS M C l a s s 1 O r e n n / C a H f o m i l - D L C - W a t e r H e a t e r 4 4 4 DS M C l a s s I O r e i i n / C a H f o r n - D L O I . . t o o 18 18 18 DS M C l a s s I Y a k i - D L C - R e s m n t i a l I 2 4 4 DS M C l a s s I Y a l c - D L C - I r r i m t i o 6 6 6 SM C n s s I T o t a l 50 6 I 2 60 60 DS M C l a s s 2 W a l l W a l l 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 47 91 DS M C l a s s 2 O r e a o n / C a H f o r 51 51 54 59 60 60 59 52 52 52 52 52 52 52 52 52 44 36 36 36 55 1 1, 0 1 6 DS M , C l a s s 2 Y a k i 6 6 6 7 7 7 7 7 7 7. 8 8 8 9 9 7 6 7 6 7 66 14 0 SM . Cl a s 2 T o t l 61 62 66 71 72 71 71 63 63 64 64 65 65 66 66 64 54 47 47 47 66 12 4 8 So l a r C a n S t a n d d 2 2 2 3 9 9 So m P O O 4 2 2 i 10 10 r- W a t e r H e a t e 1.8 1. 8 1. 8 1.8 1.8 1.8 1.8 1.8 1.8 1.0 1.0 16 18 3r d O t H L H 15 0 15 0 15 0 15 0 50 ,6 5 33 'o l u 3 r d O t H L H 25 40 0 40 0 40 0 40 0 40 0 40 0 26 6 40 0 40 0 19 8 34 2 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 34 9 36 2 ilu 3 r d O t H L H 1 0 " 1 0 P r i c e P r e m i 27 1 21 1 48 24 Ce n t r l O r e u o n o J t e m C a H f o r n i a 3 r d O t r H L H 50 50 50 22 50 50 0 50 32 16 Wa l l Wa l l * 20 8 16 1 20 3 14 6 17 0 N/A 89 're a o n C a H f o r * 41 8 N/A 42 ak i * 13 1 12 8 12 7 11 9 24 1 29 6 25 6 15 6 25 2 29 3 N/A 20 0 R ~:1 M ~ , ~ i w ~ w J~ ¡g ' "' " ~ ~ ~ W i n ~ ~~ : ' ' ~'ì t ~ ~ ~ ' % h ' % ~ ~ i % ' ~ # ' , R R ' 0 . ~ k l : * F r o n o f f l C e t r a c t m i a n d g r o w t h r e s o u r e a m o w i t s r e f l c t o n - y e a r t r a n s a c t m i p e r m , a n d a r e n o a d d i t I V . ** F r o n t o r r e e t r n s a c t i a r e r e p o d as a 2 o - y e a r a n n u a l a v e r a g e . G r r e s o u r e s a r e r e p o r t e d a s a I O - y e a r a v e r a g e . 12 4 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ta b l e D . I O - R e n e w a b l e R e s o u r c e S e n s i t i v i t y C a s e s ( 2 8 t o 3 0 a ) Ca s e 2 8 ~ ~1 : \ h ~ ~ * \ ~ ~ . " k ~ i h i L ~ ~ ~ ~ .. , j ; ~ ! i . ~ ' ~~ ì h S " " ~'t , ¥I " it "' ~ , 'C C T F 2 , d 62 5 59 7 1,2 2 2 1. 2 2 2 'C C T H 47 5 47 5 47 5 '0 0 1 P l a T u r b n e U n i r d e s 12 . 1 18 . 9 1.8 18 . 0 2. 4 51 53 ie o t h e r m l . B l u d e ß 3 35 45 80 80 'H P - B i o s s 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 10 20 'H P ø R e c i r a t i n i i E m m i e 0.8 0.8 0.8 2 2 DS M , C l a s s i U t a h . C o o k e e n e r 5. 5 5 II II DS M C l a s s i . G o h ( m - D L C - I m l ' t i 8 2 8 10 DS M . C l a s s i U t a h - C u r i k e n t 21 5 26 26 DS M e m s i U t a h - D L e - R e s i d e n t l 21 II 5 37 37 DS M C l a s s 1 U t a h ~ D L C . T r r t i n II 3 II 14 DS M , C l a s s 1 , U t a h . S e h e d T h e n E n e r ø S t o r a l ' 3 3 3 DS M , C l a s i T o t a l 26 41 20 5 5 5 97 10 2 DS M C l a s s 2 G o h e n I I I I I 2 2 2. 2 2 2 2 2 3 3 3 3 3 3 2 14 38 DS M C l a s s 2 U t a h 47 54 59 43 44 51 52 53 56 60 56 60 57 60 60 65 60 63 64 72 51 9 1,1 3 5 DS M , C l s s 2 , W v n p ' 3 4 4 5 5 6 6 7 7 8 9 9 II 13 14 18 20 23 29 28 56 23 0 em s 2 To t l 50 58 64 49 51 58 60 63 66 69 67 71 70 76 77 86 82 89 95 10 2 58 9 1,4 0 3 So l a r - W a t e r H e a t e r 2.6 2. 6 2. 6 2. 6 2. 6 2.6 2.6 .2 . 6 2.6 24 24 iT M e a d 3 r d t r H L H 16 8 26 4 26 4 20 72 36 iT U t a h 3 e d 0 t r H L H 19 0 20 0 20 0 17 53 19 4 20 0 10 5 53 iT M o n - 3 3 r d t r H L H 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 iT M ~ - 4 ) r d t r H L H 15 0 15 8 Go h e n . . 6 20 56 10 0 11 4 15 4 10 0 15 9 15 4 13 8 N/ A 10 0 Uta No r h . . 24 28 7 34 3 34 6 N/ A 10 0 10 5 34 2 21 3 34 0 N/ A 10 0 %l o a l P l a n t T u r b i n e U D m d e s 3. 7 8.3 12 12 Ge o t e n n a G r e e n f i e k i 70 70 70 CH P - B i o s s 4.2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 42 84 CH P - R e c i r o c a t Î l E m r i e 0.3 0.3 0. 3 I I DS M C l a s s i W a l l W a l i a - O L e - R e s i d n t i l I I I DS M , C l a s s I W a 1 J W a D a - D L C . I r i l i a b : i 3 3 3 DS M C l a s s I O r e i r C a l i o r - C u i l n t 17 17 17 DS M C l a s s i O r i r C a t i o m i a . D L C . R e s n e n t t 6 6 6 DS M C l a s s I O r e i r C a l i o r i a . D L C ~ W a t e r H e a t e r 4 4 4 DS M C l a s s I O r l ! o n C a l i o r i a - D L C l r r i i t i 18 18 18 DS M C l a s s I , Y a k m . D L C - R e s i d e n t i a l 4 4 4 DS M C l a s s I Y a k . D L C - l m l l t Î o 6 6 6 DS M C l a s I T o t a l 50 6 4 60 60 DS M C l a 2 W a l l W a l l 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 46 91 DS M C l a s s 2 O r e i r C a l i o m i 51 51 54 59 60 60 59 52 52 52 52 52 52 52 52 52 44 36 36 36 55 1 1,0 1 6 DS M , C l a s 2 , Y a k i 8 II 6 6 7 7 7 7 7 7 8 8 8 9 9 7 6 7 6 7 72 14 7 ~M . Ç i . s 2 T o t l 63 66 66 70 72 71 71 63 63 64 64 65 65 66 66 64 54 47 47 47 66 9 1,2 5 4 So l a r C a n S t n d a 2 2 2 3 9 9 PO O 4 2 2 I 10 10 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 16 16 15 0 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 29 8 40 0 40 0 40 0 36 6 40 0 26 8 37 7 39 5 40 0 40 0 40 0 40 0 40 0 40 0 34 6 34 5 24 4 20 6 45 23 HL H T . T 50 50 50 50 50 50 50 35 18 16 5 12 8 18 0 15 6 15 5 N/ A 80 N/ A 33 N/ A 20 0 "" " ~ _. ' ! k ~ ~ ' t r ' ~ ~ ' \ . t'i t W ~ ~ ' ~ " " 1 : ' " ;" t M ' " ' ~~ t i l * il " " i l " ' 1 * ~~ : . ~ i l ': M & " i ~ ' \ $ ' M ,,' ~ ~ ' ~ ' \ ~ " ' - ' ~ , ,:\ w t 'i i i t . . ." * "', ' " , ~ i l ,'. ~ i . '" ~ t t ~ ~ ~ ;~ - . ' " ~ ~ I I ~ "il il. . . ~ . ,, ' § ~ ~ , ~ ~ ~ h % % ~ ' ~ i l ~ r ,,~ ~ ~" " ~ ~ ' " , ' : ~ ~ t t t " " , ~ , , ~ .. F r o n o f I l C e t t n s c t l O a n d g r o w r e s o u e a m o t s r e f l c t o n - y e a r t r a c t k J p e r O O , a í i a r e n o t a d d i t . "'. F r o n t o f f i c e t r n s a c t i a r e r e p o e d a s a 2 0 - y e a r a n n l a v e r a g e . G r w t h r e s o u e s a r e r e p o d a s a i o . y e a r a v e r a g e . 12 5 PA C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ca s e 2 9 CC C T F 2 x l 1.2 2 2 CC C T H 47 5 Co l P l a n t T u r i i e U es 12 . 1 18 . 9 1.8 18 . 0 2. 4 53 Ge o t h e i m B k i U 3 35 45 80 Ge o t h e r m G r e e n f i e k l 35 35 W' W 35 % C a c ' F a c t o 4 8 9 4 34 58 W' W NE 3 5 % C a Fa c t o r 16 0 16 0 To t a l Win d 16 0 4 8 9 4 34 21 8 CH P . B i o s s 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1. 0 1.0 1.0 1.0 1.0 10 20 CH P - R e c ' o c a t i E . e 0.8 0.8 0.8 2 2 DS M C l a s s 1 U t a h - C o o k e , 5.5 5 II II DS M C l a s s 1 G o l i . D L C - I r " l i 8 2 8 10 DS M , C l a s s I U t a h - C u i k t 21 5 26 26 DS M C l a s s i U t a h - O L e - R e s i d n t i l 21 II 32 32 DS M , C l a s s i U t a h - O L e - I," II 3 II 14 DS M C l a s s i U t a h - S e h e d T h E n e r Sl o m 3 3 3 DS M , C l a s i T o t a l 26 41 20 5 5 92 97 DS M C l a s s 2 G o h e n I 1 I I I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 38 DS M C l a 2 U t a h 47 54 59 43 44 47 49 50 52 54 56 60 57 60 60 65 60 63 64 69 50 0 1,1 1 3 DS M , Cla s s 2 W 3 4 4 4 5 6 6 7 7 8 9 9 II 13 14 18 20 23 29 28 55 22 9 DS M C l a s 2 T o t l 50 58 64 48 51 55 57 59 61 64 67 71 70 76 77 86 82 89 95 99 56 8 1,3 8 0 2.6 2.6 2.6 2.6 2. 6 2.6 2.6 2. 6 2. 6 24 24 16 8 26 4 26 4 24 72 36 19 0 I 20 0 20 0 17 57 20 0 19 3 10 6 53 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 is o 15 8 20 36 83 14 1 15 8 10 0 15 6 16 2 13 8 N/A 10 0 33 26 9 36 2 33 6 N/A 10 0 81 36 6 21 2 34 1 N/A 10 0 3.7 8. 3 12 12 70 70 70 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4. 2 4. 2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 42 84 " 0.3 0.3 0.3 I I I I I 3 3 3 17 17 17 6 6 6 4 4 4 18 18 18 2 2 2 6 6 6 50 8 58 58 4 4 5 5 5 5 5 4 4 4 5 5 5 5 5 5 4 4 4 4 45 90 51 51 54 59 60 60 59 52 52 52 52 52 52 52 52 52 44 36 36 36 55 0 1,0 1 5 8 II 6 6 6 6 6 7 7 7 8 8 8 9 9 7 6 7 6 7 70 14 5 63 66 65 70 71 70 70 63 63 63 64 65 65 66 66 64 54 47 47 47 66 5 1,2 4 9 2 2 2 3 9 9 2 2 I 10 10 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1. 0 1. 0 1. 0 15 16 15 0 I 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 29 9 40 0 40 0 40 0 37 6 40 0 11 7 28 1 38 9 40 0 40 0 40 0 40 0 40 0 40 0 40 0 34 7 35 3 24 4 20 6 45 23 HL H I I 50 50 50 50 50 50 50 35 18 N/ A 59 N/ A 32 N/ A 20 0 '" F r o n t o f f i c e t r n s a c t i a n d g r o w r e s o u e a i o r e f l c t o n e - y e a r t r a n a c t i o p e r l , a n d a r e n o t a d d ß v . .. F r o n t o l T r e t r n s a c t i : s a r r e p o a s a 2 O y e a r a n u a l a v e r a g e . G r w t r e o u r e s a r e r e ¡ x d a s a i o - y e a r a v e r a g e . 12 6 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S .. ~ , . " m ' " ~ ''' : , 1,2 2 2 47 5 2.4 . . 51 53 35 45 80 80 35 35 ,c i t F a c t o T 4 48 21 8 9 4 34 12 7 4 48 21 8 9 4 34 12 7 1.0 1.0 1. 0 1. 0 1. 0 1.0 1.0 1.0 1.0 1. 0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 10 20 0.8 0. 8 0.8 2 2 55 5 II II ,l i I 8 2 8 10 21 5 26 26 21 II 5 37 37 II 3 II 14 Sto r a i r T 3 3 3 26 41 20 5 5 5 97 10 2 I I I I I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 38 47 53 59 43 44 48 52 53 55 60 56 60 57 60 60 65 60 63 64 69 51 4 1.1 2 7 3 4 4 5 5 6 6 7 7 8 9 9 II 13 14 18 20 23 29 28 56 23 0 50 57 64 49 51 56 60 62 64 69 67 71 70 76 77 86 82 89 95 99 58 4 1,3 9 5 1.2 1.2 1.2 1. 1.2 1. 2 1. 1. 1. 1.2 1.2 1.2 1. 1. 1.2 1. 1.2 1.2 12 22 2.6 2.6 2. 6 2.6 2.6 2.6 2. 6 2. 6 2.6 2.6 2.6 2.6 2.6 2.4 24 37 16 8 26 4 26 4 21 72 36 19 0 T 20 0 20 0 16 53 19 4 20 0 10 5 53 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 20 51 92 15 1 15 4 10 0 14 5 14 4 13 7 N/ A 10 0 24 30 8 35 2 31 6 N/A 10 0 34 10 3 30 3 25 8 30 2 N/ A 10 0 :o a t P l a T u r b n e U D l ! a d e s 3.7 8.3 12 12 ie o t h e r m G r e e n f J e k t 70 35 70 10 5 'H P . B i o i n s s 4.2 4.2 4. 2 4. 2 4. 2 4.2 4.2 4.2 4. 2 4. 2 4. 2 4.2 4.2 4.2 4.2 4. 2 4. 2 4.2 4.2 4.2 42 84 UP . R e c i n o c a t i i i E r u e 0.3 0.3 0.3 I I DS M C l a s s i W a l l W a l i - O L e - R e s i d e n t l I I I DS M C l a s s i W a l l W a l l - D L C - I r i i t k : n 3 3 3 DS M C e s s i O r e i r C a l i o r - C u r i h n t 17 17 17 DS M C e s s i O r e i w C a l i o m Ø . D L C - R e s m n t i a l 6 6 6 DS M C h s i O r e i m n l C a l i o m - D L C . W a t e r H e a t e r 4 4 4 DS M e m s i O r e i m n I a l i o r - D L C - l r r i i t 1 18 18 18 DS M C l a s s i Y a k . D L C . R e s i : e n t i a l 4 4 4 DS M C l a s s i Y i l - D L C - I r r t i 6 6 6 rO S M C h s s 1 T o t l 50 6 4 60 60 DS M , C l a s s 2 , W a l l W a l l 4 4 5 5 5 5 5 4 5 5 5 5 5 5 5 5 4 4 4 4 46 91 DS M C l a s s Or e l 1 / C a l i o m i a 51 51 54 59 60 60 59 52 52 52 52 52 52 52 52 52 44 36 36 36 55 1 1,0 1 6 DS M , C l a s s 2 , Y a k m 8 II 6 6 6 7 7 7 7 7 8 8 8 9 9 7 6 7 6 7 72 14 6 M C l a s 2 T o t a l 63 66 66 70 72 71 71 63 63 64 64 65 65 66 66 64 54 47 47 47 66 9 1.2 5 3 Ca n S t a n d d 2 2 2 3 9 9 Pi l t 4 2 2 I 10 10 1.8 1. 8 1.8 1. 8 1.8 1.8 1.8 1.8 1. 8 1. 3 1. 1. 1.0 1.0 16 22 15 0 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 29 7 40 0 40 0 40 0 36 6 40 0 26 6 37 7 39 5 40 0 40 0 40 0 40 0 40 0 40 0 34 6 34 5 24 4 20 6 45 23 50 50 50 50 50 50 50 35 18 30 25 16 4 21 16 8 N/A 43 N/A 26 N/A 20 0 rn ; li lf ~ ~ ''I f ' W ' . . 'i ' ' ~ ~ , l l '; Y A i l *% k tM l §I i ~ . ~ l i ,; i ¡ f ~ ': ~ ~ m " ; " ì % t R ' : : ~ '~ a . " ¡g % " ' " * $ " ' - .. ~ ~ 1 m ~~ ~ : , . * F r o n t o t T l C e t r n s a c t i a n d g r o w t h r e s o u e a m m t s r e f l c t o n e - y e a r t r n s a c t i o n p e r k x , a n d a r n o t a d d i t v e . .. . F r o n t o f f i c e t r n s a c t i o a r r e p o e d a s a 2 O y e a r a n n l a v e r a g e . G r r e s o u r e s a r e r e p o d a s a i o - y e a r a v e r a g e . 12 7 P A C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S -Ca s e 3 0 a -,, ; - " , " , ~ ' i : * ' ~ H ¡ h \ i ~ ~ ~ # ~ - AW . 1, 2 2 2 47 5 de s I 12 . 1 I ..1 . 8 - 2 - ' 1.8 1 . I 18 . 0 2. 4 ,. 53 35 45 80 80 35 35 ic i t F a c t o r 7 49 21 8 9 4 34 13 2 7 49 21 8 9 4 34 13 2 'H P - B i o s s 1.0 1. 0 1.0 1. 0 1.0 1. 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 10 20 'H P - R e c i n o c a t i u E n i r e 0.8 0.8 0.8 2 2 DS M _ C l a s s 1 U t a b - C o l k e l 1 l 5.5 5 11 II DS M , C l a s s i G o h e n - D L C - I r i c m i i o n 8 2 8 10 DS M C l a s s i U l a h - C u i h n t 21 5 26 26 DS M C l a s s i U t a h - O L e - R e s i d t i l 21 11 5 37 37 DS M C l a s s i U t a h . D L C - T r r t i o 11 3 11 14 DS M C l a s s I , U t a h - S e h e d T h e r m E n M v S t a a e 3 3 3 8M , Cl a s l T o t l 26 41 20 5 5 5 97 10 2 DS M C l a s s 2 G o h e n 1 I I 1 I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 38 DS M C l a s 2 U t a h 47 53 59 43 44 48 52 53 55 60 56 60 57 60 60 65 60 63 64 69 51 4 1. 1 2 7 DS M , C l a s s 2 W v n r l , 3 4 4 5 5 6 6 7 7 8 9 9 11 13 14 18 20 23 29 28 56 23 0 SM , C b s s 2 T o t l 50 57 64 49 51 56 60 62 64 69 67 71 70 76 77 86 82 89 95 99 58 4 1. 3 9 5 1. 1. 2 1. 1. 2 1. 2 1. 1.2 1. 1.2 1.2 12 12 2.6 2.6 2.6 2.6 2.6 2.6 2.6 2.6 2.6 2. 6 2. 6 2. 6 2. 6 2.4 24 37 16 8 26 4 26 4 21 72 36 19 0 I 20 0 20 0 16 53 19 4 20 0 10 5 53 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 20 52 93 15 1 15 4 10 0 14 5 14 2 13 7 N/A 10 0 27 30 9 35 8 30 6 N/A 10 0 25 10 0 30 3 25 7 31 5 N/A 10 0 3.7 8.3 12 12 70 35 70 10 5 4.2 1 4. 2 1 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4. 2 4.2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 42 84 0. 3 - ! 0. 3 l 0.3 I I I I I 3 3 3 17 17 17 6 6 6 4 4 4 18 '_ . . 18 18 4 4 4 6 6 6 50 6 4 60 60 4T 4 5 5 5 5 5 4 5 5 5 5 5 5 5 5 4 4 4 4 46 91 51 51 54 59 60 60 59 52 52 52 52 52 52 52 52 52 44 36 36 36 55 1 1,0 1 6 8 II 6 6 6 7 7 7 7 7 8 8 8 9 9 7 6 7 6 7 72 14 6 63 . l _ _ 6 6 66 70 72 71 71 63 63 64 64 65 65 66 66 64 54 47 47 47 66 9 1,2 5 3 2 2 2 3 9 9 2 2 1 10 10 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1. 1. 1. 1.0 1.0 16 22 15 0 I 15 0 15 0 15 0 50 65 33 40 0 40 0 40 0 29 7 40 0 40 0 40 0 36 6 40 0 26 6 37 7 39 6 40 0 40 0 40 0 40 0 40 0 40 0 34 6 34 5 24 4 20 6 45 23 50 50 50 50 50 50 50 35 18 40 28 16 7 23 16 9 N/ A 45 N/ A 26 N/ A 20 0 ~ g ¡ ~ ~ "'\ : è\ §t :M ~ ~ ' t ,i l 'M , , ' "~ ' l - ~ " il " , ' ~ , "& ~ f * ,: ~ ~ : ." : ' 2 ! 0? ' æ '" " . ~ ' ' ' m ~ .A I I ~ " ' % 1 ~ " ìg l k '~ ~ g ¡ t : " 'l' " , k -% ! ? ' . F r o n t o f f i c e t r n s a c t i n a n d g r o w t r e s o e a l O r e f l c t o n e - y e a r t r a n a c t i o p e r h d , a n d a r e n o t a d d i t . "'* F r o n t o f f r e t r a c t i a r e r e p o e d a s a 2 ( ) y e a r a n n u a l a v e r a g e . G r w t h r e s o u e s a r e r e p o e d a s a i o - y e a r a v e r a g e . 12 8 P A C I F I C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ta b l e D . l l - D e m a n d - S i d e M a n a g e m e n t S e n s i t i v i t y C a s e s ( 3 1 t o 3 3 ) . 'Y \ ' l ' ' , " !d47 553 35 45 80 80 35 35 Fa c t o r T 8 9 4 34 55 :c i l F a c t o r 1 16 0 16 0 16 0 8 9 4 34 21 5 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 L. O 1.0 1.0 1. 0 1. 0 1.0 1. 0 1.0 1.0 1.0 1.0 10 20 0. 8 0.8 0.8 2 2 8M e h s s i U t a h . C o h e o e r 5.5 5 II II 8M C l a s 3 G o h e n C r i i c a l P e a k P r i i n o . C o l r i I I I DS M e h s s 3 G o h e n T i m o r U s e I l T t i o 60 60 60 DS M C l a s s 3 U t a h . C r i t i c a l P e a k P r i i i ~ . C o m m I o d s 19 9 28 28 DS M C l a s s i U t a b - C u r i h n t 21 21 21 DS M C l a s s 3 U t a h . D e m a n d B l l b a c k . C o m m 6 3 9 9 DS M C l a s s i U t a h - O L e - R e s i d l 29 29 29 DS M C l a s 3 U t a h . R e a l - i m P r r i i i ! : . C o n n l I n u s 5 5 5 DS M C l s 3 U t a h . T i m o f U s e . l r t i n 11 7 11 11 DS M C l a s s 3 W v o i n i i . C r i i c a l P e a k P r i c i n l ! C o II 10 21 21 DS M e b s s 3 W v o m i D e m a B u v b a c k . C o l i i 5 5 10 10 DS M C h s s 3 W V o m i n i i . R e a ) . T i m P i i i o i i . C o m n i 3 3 5 5 DS M C l a s s 3 W v o e . T i m o f U s e , l r r t i o 5 5 5 SM , C l a s I T o t l 6 66 22 1 30 32 2 32 2 DS M C l a ' G o h e I I I I I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 38 DS M C l a s s 2. Uta 58 65 64 43 44 47 49 50 52 54 56 60 57 60 60 65 60 63 64 69 52 6 1,1 4 0 DS M C l a s 2 . W v o j t 3 4 4 4 5 5 6 7 7 8 9 9 II .1 3 14 18 20 23 29 28 54 22 8 8M . C l a s s 2 T o t a l 61 70 70 48 50 54 57 59 61 64 67 71 70 76 77 86 82 89 95 99 59 5 1,4 0 6 2.6 4 2.6 4 2.6 4 2. 6 4 2.6 4 2. 6 4 2.6 4 2.6 4 2.6 4 2.3 7 2.3 7 24 28 16 8 26 4 20 4 99 74 37 17 8 20 0 15 1 88 19 4 82 89 45 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 38 54 13 3 17 76 21 0 19 4 11 6 N/A 10 0 44 28 2 35 5 31 9 N/A 10 0 30 19 0 22 9 25 4 29 6 N/A 10 0 3.7 8.3 ~ 12 12 70 70 70 4.2 4.2 4. 2 4.2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4.2 4. 2 4. 2 4.2 4.2 42 4.2 42 84 0.3 0.3 0. 3 I I I I I 16 16 16 6 6 6 6 6 6 26 26 26 iii o 72 72 72 .l r t i 7 7 7 ,t i 21 21 21 23 13 15 5 15 5 4 4 5 5 5 5 5 4 4 4 5 5 5 5 5 5 4 4 4 4 45 90 51 51 55 59 60 60 59 52 52 52 52 52 52 52 52 52 44 36 36 36 55 0 1,0 1 5 6 6 6 6 6 6 6 7 7 7 8 8 8 9 9 7 6 6 6 7 62 13 6 61 62 65 70 71 70 70 62 63 63 64 65 65 66 66 64 54 46 47 47 65 7 1,2 4 1 2 2 2 3 9 9 2 2 I 10 10 L.S I 1. 8 1 L.S I I.S I L.S I 1.8 1 1.8 1 LS I 0.9 7 0.9 7 0.9 7 0.9 7 0.8 2 15 19 15 0 15 0 15 0 15 0 50 65 33 15 40 0 40 0 40 0 40 0 34 8 39 4 40 0 40 0 40 0 20 2 33 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 40 0 35 6 36 4 27 1 21 1 48 24 50 50 50 50 50 50 30 15 N/A 42 N/A 10 0 :'~ ~ ' ill ' o¡~ w t *' ,,~ % ~ , ~ :. , , ~ m ¡ '. ' ! ~~ r , 'l ,-. i , ' * " .: ' ' \ ¡ ., ',, - , if ~ ~ * ' ~ II '~ : ~ ~ ~ t II ' ~ -' % ' " : , ~ ~ . . , . F r o o f f i c e t r c t i a n d g r h r e s o u a l 1 r e f l c t o n e - y e a r t r a n a c O O p e r i o , a n d a r e n o a d d . .. . F r o n o f f l r a c m n s a r r e p o e d a s a i Q - y e a r a n n l a v e r a g e . G r t h r e s o u s a r e r e p o e d a s a l O . y e a r a v e r a g e . 12 9 P A C I F i C O R P - 2 0 1 1 1 R P Ap P E N b l X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S Ca s e 32 * ,, ' % ~ ' i f ' ~ ' % 0 ~ ' ~ ' § ' - " : * ' ~ \ ' m ~ i l mr " ì ~ N CC C T F 2 x 1 - - . 6 2 5 - 5 9 7 . - . . . - - - - - - . . - 1.2 2 2 1.2 2 2 CC C T H 47 5 47 5 47 5 Co a l P l a n t T u r b i n e D n i i d e s 12 . 1 18 . 9 1.8 18 . 0 2. 4 51 53 Ge o t e r m l B à i U 3 35 45 80 80 Ge o t h n n l G r e e n f i e l d 35 35 Win d W V o m 2 . 3 5 % C a n a c i v F a c t o 7 7 Win d W v o i n l l N E 3 5 % C a n a c i t F a c t o r 16 0 16 0 ¡r o t l W m d 16 0 7 16 7 CH P - B i o s s 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1. 0 1.0 1.0 1.0 1.0 10 20 CH P - R e c i D o c a t i E i u e 0.8 I I DS M C l a s s 1 U t a - C l k e e o e r 5.5 5 II II DS M C l a s s i G o h e n ~ D L C - I r i i t i 8 2 8 10 DS M C l a s s i U t a h . C u r i m e n t 21 I 2 25 25 DS M . C l a s s i U t a h . O L e - R e s i d n t l 32 32 32 DS M C l a i U t a - D L C - I r l m II 3 II 14 DS M , Cla s s i T o t l 6 58 21 2 5 87 92 DS M C l a s 2 G o h e n I I I I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 16 45 DS M C l a s s 2 U t a h 54 59 55 54 57 61 63 65 67 71 75 80 77 79 79 87 81 85 85 92 60 1, 4 2 8 DS M , C i l , 2 . W v o . 4 5 5 6 6 6 8 9 9 9 II 12 14 17 18 23 24 29 36 35 67 28 4 8M C h s s 2 To t l 59 65 61 61 65 70 74 76 78 83 88 94 93 99 10 0 11 3 10 8 11 7 12 4 12 9 69 1 1, 7 5 8 ) So l a - W a t e r He a t e r 2.6 2.6 2.6 2.6 2.6 2.6 2.6 2.6 2. 6 24 24 Me a d 3 e d O t t H L H 16 8 26 4 26 4 99 80 40 Uia h 3 r d O t t H L H 19 4 20 0 20 0 91 18 1 81 95 47 Mo n . 3 3 r d O t H L H 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 Mo n 4 3 r d O t H L H 15 0 15 8 Go h e n * 13 70 66 91 22 2 15 5 13 9 13 3 IL L N/A 10 0 Ut a h N o r b * 17 2 20 2 20 5 N/A 58 20 6 21 2 23 3 34 9 N/A 10 0 IP i a m T u r U ' ; " 3.7 8.3 12 12 ~r m G r n f i e l d 70 70 70 Bi o a s s 50 50 50 'H P - B i o s s 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4.2 4. 2 4. 2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 42 84 lP . R e c Ï D o c a t i l l E r u 0.1 0 0 DS M . C l a s s i W a l l W a l l - D L C - R e s i i i i t i l I I I DS M . C l a i W a l l W a l l - D L C - I r b n 3 3 3 DS M C l a i 0 r 2 O C a l i o m i a - C 1 i k n l 17 17 17 DS M C l a l O r e i r C a l i o m - D L C - R e s i ; n l m . l 6 6 6 DS M C l a s s i O r i i o n C a l i o r i a - D L C - W a t e r H e a t e r 4 4 4 DS M C l a s s i O r e Ð : o n C a l i o m i a - D L C - I r i i m t i : 18 18 18 DS M C l a s s I , Y a l - D L C - R e s i d t i l l I I I DS M C l a s s i . Y a k . D L C - l r i m t b 6 6 6 ilS M C i l , I T o t l 50 6 I 57 57 DS M C l a s s 2 W a l l W a l l 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 5 4 4 4 4 48 98 DS M C b s s Or e ø n / C a l i o r 51 52 55 59 61 60 59 52 52 52 52 52 52 53 53 52 45 37 37 37 55 2 1.0 2 0 DS M . C l a s Ya k 7 7 8 8 8 7 8 8 8 8 9 10 10 10 10 8 7 8 8 8 76 16 4 li S M C m s 2 T o t a l 63 63 67 72 73 72 72 64 64 65 66 68 68 68 69 66 56 49 48 49 67 7 1,2 8 3 Or e l l n S o l a C a n S t a n d a 2 2 2 3 9 9 Or e o o 8 0 m P i h 4 2 2 i 10 10 ro S o l a - W a t e r H e a t e r 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.0 1.0 1.0 15 17 CO B 3 r d O t r H L H 15 0 15 0 15 0 15 0 50 65 33 Mid C o b m 3 r d 0 t r H L H 18 40 0 40 0 40 0 40 0 38 2 40 0 40 0 40 0 40 0 21 40 0 40 0 40 0 40 40 0 40 0 36 0 30 1 Mid C o b m J r d O t r H U t 1 0 ' % P r k e P r e m i 26 9 20 8 48 24 So t h C e n t r l O r e 2 O o r m C a l i o r 3 r d O t r H L H 50 50 50 50 14 50 50 50 36 18 . N/A 20 0 ,l ~ i n ~ " , : ~ , , " * , , " m r ' ! : " * 0 l § 4 ' ' : i n r ' m l : ~ 1 '~ : ' ~ i m " ' l , " ~ , , , § ¡ ' m : " a ~ ' ~ , * F r o n t o f T l C e t r n s a c t m a n d g r o w t h r e s o u e a m o t s r e f l c t o n - y e a r t r a n s a c t m p e r b d , a n d a r e n o t a d d i t v e . *. F r o t o f T l C e i r a c t i a r e r e p o e d a s a 2 o - y e a r a n n u a l a v e r a g e . G r w t h r e s o u e s a r r e p o e d a s a i o - y e a r a v e r a g e . 13 0 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X D - D E T A I L C A P A C I T Y E X P A N S I O N R E S U L T S -W; ' " ' ' \ ' , ' " ~ 1,2 2 2 ru53 35 45 80 80 35 35 35 Fa c t o T 8 9 4 34 55 ic i t F a c t o I 16 0 16 0 16 0 8 9 4 34 21 5 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1. 0 1.0 1.0 1.0 1.0 1. 0 1. 0 1. 0 1.0 1.0 1.0 1.0 1.0 10 20 " I 0.8 0.8 0. 8 2 2 I 5.5 5 II II ,li o n 8 2 8 10 21 5 26 26 32 3 34 34 II 3 II 14 St o a , g T 3 3 3 6 62 20 8 5 95 99 i I 1 1 I 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 14 38 46 55 59 43 44 47 49 50 52 54 56 60 57 60 60 65 60 63 64 69 49 9 1.1 1 3 3 4 4 4 5 6 6 7 7 8 9 9 II 13 14 18 20 23 29 28 55 22 9 49 59 64 48 51 55 57 59 61 64 67 71 70 76 77 86 82 89 95 99 56 8 1.3 8 0 2.6 2.6 2.6 2.6 2. 6 2.6 2.6 2.6 2.6 2.4 2.4 0. 0 24 29 16 8 26 4 26 4 28 72 36 20 0 20 0 22 57 20 0 19 3 87 44 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 30 0 21 0 25 5 15 0 15 8 34 80 18 4 23 7 23 8 17 0 57 N/A 10 0 30 6 33 5 35 8 N/A 10 0 53 26 2 29 0 39 5 N/A 10 0 3.7 8. 3 12 12 70 70 70 4. 2 4. 2 4.2 4.2 4.2 4.2 4. 2 4. 2 4.2 4.2 4.2 4.2 4.2 4.2 4. 2 4.2 4.2 4.2 4.2 4.2 42 84 0. 3 0. 3 0.3 I 1 DS M C l a s s i W a l l W a l h - D L C - R e s i d n t n l I I I DS M C l a s s i W a l l W a I a - D L C - I r Ì l t Í O 3 3 3 DS M C b s s i O r e o n C a l i o m - C u i l n t 17 17 17 DS M C e s s i O r e o n C a l i o r - D L C ~ R e s i d n t i a l 6 6 6 DS M C l a s I , O r e o n C a l i o r - D L C - W a t e r H e a t e r 4 4 4 DS M C l a s s i O r e g o o C a l i o r i a - D L C - I r i i t k 18 18 18 DS M C b s s i Y a l - D L C - R e s K i e n t i a l 4 4 4 DS M C l a s s i Y a k - D L C - I r t m . 6 6 6 ;M C l a s i T o t a l 50 10 60 60 DS M e m s 2 W a l l W a l l 4 4 5 5 5 5 5 4 4 4 5 5 5 5 5 5 4 4 4 4 45 90 DS M C l a s 2 O r e i i n t C a l i o m 51 51 54 59 60 60 59 52 52 52 52 52 52 52 52 52 44 36 36 36 55 0 1,0 1 5 DS M , C l a s 2 , Y a k i 6 6 6 6 6 6 6 7 7 7 8 8 8 9 9 7 6 7 6 7 63 13 8 8M C h s s 2 T o t l 61 62 65 70 71 70 70 63 63 63 64 65 65 66 66 64 54 47 47 47 65 8 1,2 4 3 Dis t r i b i t i o E n e r m ' E f f i : i e n c v , W a l l W a l l 0.2 0 0 Di s l r i t i o E n e r 2 V E f f r i e n c y . Y a k 0.4 0 0 in S o l a r C a P S t a n d a r 2 2 2 3 9 9 So m P i l 4 2 2 I 10 10 1.8 1.8 1. 8 1. 8 1.8 1.8 1.8 1.3 1.3 1. 0 1. 0 1.0 1.0 15 19 15 0 15 0 15 0 15 0 50 65 33 25 40 0 40 0 40 0 30 3 40 0 40 0 40 0 37 6 40 0 98 29 0 38 8 40 0 40 0 40 0 40 0 40 0 40 0 40 0 35 0 35 4 27 1 21 1 48 24 50 50 50 50 50 50 50 35 18 N/A 48 N/A 41 N/A 20 0 Iì ' , \ ~ ' i l ; " s i l fu ' W " " * ' ' 1 m ': ~ , ~" ~ ~ ~ ~ ~ ~ i l * ~ '~ ~ 1 ' 'm w ' " " ~ ~ ~ , , ' t ~ ~ , ,,~ ~ ~ ~ , : m , ,i l , , . 1: ~ : , ~ " :~ ) ~ i ' .:: i m ,~ % , ¡ , : ', , " :! 1 - ; ' 'm ' - - : : ~ \ ~ ~ ~ \ i ¡~ ~ ~ " t '. ,: ~ \ ~ ~ ,: ~ : " ) '" F r o n t o f f i c e t r n s a c t i a n d g r o w t h r e s o u r e a m o r e f l c t o n e - y e a r t r n s a c t i o p e r C , a n d a r e n o t a d d i t e . .. . F r o n t o f f i : e t r n s c t h n a r e r e p o e d a s a 2 Q y e a r a n m J a v e r a g e . G r w t h r e s o u e s a r e r e p o e d a s a i o - y e a r a V e r a g e . 13 1 PACIFICORP - 2011 IR APPENDIX D - DETAIL CAPACIT EXPANSION RESULTS Figue D.l shows the Preferred Portfolio added to the medium C02 emission profile chart from Chapter 8. Figure D.I - Core Cases: C02 Emission Prorie for Medium C02 Tax Costs ¡--- i C02 Cases - MedUl 65.0 62.5 60.0 57.5 i55.0 8 52.5 g 50.0.. ~47.5~'" 'õ 2 45.0c:: ~42.5 40.0 ..........-.........-----37.5 ------ 35.0 32.5 30.0 ~~~~~~~~~~~~~~~~~~~~ L____Prferd Portfoli ..Case-G3 ..Case-67 ..Case-ll ..Case-19 132 PACIFiCORP-20ll IRP APPENDIX E - STOCHASTIC SIMULATION RESULTS ApPENDIX E - STOCHASTIC PRODUCTION COST SIMULATION RESULTS This appendix reports additional results for the Monte Carlo production cost simulations conducted with PacifiCorp's Planing and Risk (paR) model, including certin sensitivity portfolios: coal utilization cases 20 through 24, and high/low economic growth cases 25 and 26. These results supplement the data presented in Chapter 8 of the main IRP document. The results presented include the following: . Stochastic mean PVR versus upper-tail mean PVRR scatter-plot diagrams that include all CO2 hard cap portfolios . The full complement of stochastic risk and other portfolio performance measures for the portfolios simulated using PaR. . Stochastic mean PVRR component cost details for the portfolios. Mean versus Upper-tail Mean PVRR Scatter-plot Charts The following set of scatter-plot charts incorporates all 19 core cases. The scatter-plot charts in Chapter 8 excluded a number of the CO2 emission hard cap portfolios due to high PVRs that impacted axis scaling and legibility of the data points. 133 PA C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X E - S T O C H A S T I C S I M U L A T I O N R E S U L T S Fi g u r e E . l - S t o c h a s t i c C o s t v e r s u s U p p e r - t a i l R i s k , Z e r o C 0 2 T a x S c e n a r i o Ze r o CO 2 T a x 40 . 5 40 . 0 39 . 5 39 . 0 . , 38 . 5 38 . 0 '" 3 7 . 5 '"i:.~ 3 7 . 0 :::. 3 6 . 5 ~'-~ 3 6 . 0 5: 3 5 . 5 ; 3 5 . 0 ~ . , . " " " " " , , , , , , , , , , , , , l , , , . , , , , , , , , , , , , , , , , , , , , , , , , L , , , , , , . , , . , , , , , . , , . . , , . " . . l " " " " , , , , . , , , , , , , , l , , . . , , , , . . , . , , , , , , , . , , . : ; l J , , , , C a s e l 6 - ~~== 3 4 . 5 =E- 3 4 . 0 i.~ 3 3 . 5 ;; 3 3 . 0 32 . 5 ' 32 . 0 " I ~ t- ~ i ; p R 1 l . ~ ~ ~ C a s b 1 3 31 . 31 . 0 30 . 0 26 . 0 26 . 5 27 . 0 27 . 5 28 . 0 28 . 5 29 . 0 29 . 5 30 . 0 30 . 5 31 . 0 31 . 5 32 . 0 32 . 5 St o c h a s t i c M e a n P V R R ( $ b i l i o n s ) 13 4 P A C I F i C O R P - 2 0 1 1 I R P AP P E N D I X E - S T O C H A S T I C S I M U L A T I O N R E S U L T S Fi g u r e E . 2 - S t o c h a s t i c C o s t v e r s u s U p p e r - t a i l R i s k , M e d i u m C O 2 T a x S c e n a r i o 43 . 0 "V~0 F. 42 . 5 ~e ~¡: 42 . 0 =o:..~-.;E-.. 41 . ~o; 41 . 0 $1 9 C O 2 T a x 44 . 0 I i r ~ r, " ~ 1 7 I . . . . . Ii + Lm m . . C, " I S I _ . _ - _. _ i I - - - - - _ C ' ~ 1 6 I I ". . , . . . . M C a s e i 9 I I Ca e 5 ! C a s e 8 C, , , 2 í ) 6 ; ; , 9 C . " 1 0 ! C' ' ' ~ ~ K C . ~ ~ " 4 C , " I . - c , " . . I C. , , 7 . . - - . . . . - 1 , . C ' " 1 5 I C " ' - 1 2 L I ¡ ¡ ¡ ~ 43 . 5 40 . 5 40 . 0 34 . 5 35 . 0 35 . 5 36 . 0 36 . 5 37 . 0 37 . 5 38 . 0 38 . 5 St o c h a s t i c M e a n P V R R ( $ b i l l o n s ) 13 5 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X E - S T O C H A S T I C S I M U L A T I O N R E S U L T S Fi g u r e E . 3 - S t o c h a s t i c C o s t v e r s u s U p p e r - t a i l R i s k , L o w t o V e r y H i g h C O 2 T a x S c e n a r i o $1 2 C O 2 T a x ( l o w t o v e r y hi g h ) 46 . 5 46 . 0 45 . 5 45 . 0 'ê ¡: .9 :§ 4 4 . 5 ~'-~ 4 4 . 0 ~==~ 4 3 . 5 :==¡.i. 4 3 . 0 ~c.c. ;; 42 . 5 42 . 0 " 41 . ,'* , Ca s e 1 8 i. C~ s e 1 7 ßh . Ca s e 1 6 Ci i s e T 9 .a s ' e . F ! l . S . ~ , , 4 : : : t = . . ç . ! l . t . e 8 .' f . i è ~ ¡ .. " " . . . . . " . " " . . , , ~ . ~ ~ : ~ ë ' . . " " . ' . C a & : 5 ' = ~ . " . " " ' 4 ' ' ' ' ' ' ' ' ' ,. . ¡ ~ Ca s e 6 ! C a s e 1 5 ! 4 i . o - + _ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ~ . . . . . . . - + 35 . 0 3 5 . 5 3 6 . 0 .. " . . . . c a & e . l O " . . . l . " . . ~ C a s e 1 4 .. C a s e 1 2 ! C a s e 1 3 36 . 5 37 . 0 37 . 5 38 . 0 38 . 5 39 . 0 St o c h a s t i c M e a n P V R R ( $ b i l i o n s ) 13 6 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X E - S T O C H A S T I C S I M U L A T I O N R E S U L T S Fi g u r e E . 4 - S t o c h a s t i c C o s t v e r s u s U p p e r - t a i l R i s k , A v e r a g e f o r C O 2 T a x S c e n a r i o s 43 . 5 43 . 0 42 . 5 ~¡g 42 . 0 I 0 ~e 4 1 . 5 '"..'"Qu 41 . 0 "dQ, iS.. 40 . 5 ;:~~ 40 . 0 ;;~= 39 . 5 ~~== 39 . 0 ~Eoi.Q,8: 3 8 . 5 :; I 38 . 0 - j . . . . G a s e . 2 . . . . . . . . Av e r a g e o f C O 2 T a x L e v e l s Ca s e 1 8 rg C ' p 1 7 w' Ca s e 1 6 37 . 5 i c ã ' s e T : i . i ! C a s e a 9 " ' " i. . ; ~ Ca s e 5 C a s e S ¡ C a s e I! ) C a s e 1 4 i ~ ' i J ) ¡ . . : t " C ~ ~ ~ ' 9 l ' . ' . . . . . . . . . t . . . ~ . . . - j . . . . . . . . . . . . . . . . . . ¡. ç i ! . s e . . 2 . . . . . . . . . . 1 ~ . . . . . . . . . . . ~ . ~ . ~ ~ . ~ . . . . . . . . L . . . . . ¡ C a s e l l ¡ r ~ q s e 1 3 Ca s e 7 i C a s e 6 i ' . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . g O p 37 . 0 32 . 0 ! 32 . 5 33 . 0 33 . 5 34 . 0 34 . 5 35 . 0 35 . 5 36 . 0 36 . 5 St o c h a s t i c M e a n P V R R ( $ b i l i o n s ) 13 7 P ACIFICORP - 2011 IR APPENDIX E - STOCHASTIC SIMATION RESULTS Table E.l- Stochastic Mean PVRR by C02 Tax Level, Core Case Portolios Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Case 7 Case 8 Case 9 Case 10 Case 11 Case 12 Case 13 Case 14 Case 15 Case 16 Case 17 Case 18 Case 19 26,623 26,424 26,616 27,002 27,000 27,008 26,650 27,122 27,122 28,555 28,172 29,082 29,182 29,073 27,591 28,441 32,369 30,957 28,108 35,567 35,462 35,488 35,681 35,585 35,516 35,527 35,841 35,738 36,838 36,816 37,103 37,009 37,167 35,560 36,181 38,539 37,206 36,679 34,892 34,768 34,835 35,139 35,087 35,024 34,868 35,271 35,231 36,362 36,154 36,678 36,789 36,698 34,969 35,328 38,036 35,791 36,128 32,360 32,218 32,313 32,607 32,558 32,516 32,348 32,744 32,697 33,918 33,714 34,288 34,327 34,312 32,707 33,317 36,315 34,651 33,638 Table E.2 - Stochastic Risk Results by C02 Tax Level, Core Case Portfolios Case 1 1,948 23,551 29,799 30,808 Case 2 2,029 23,289 29,825 30,836 Case 3 1,934 23,563 29,796 30,752 Case 4 1,954 23,892 30,191 31,139 Case 5 1,974 23,836 30,194 31,092 Case 6 1,919 23,901 30,093 30,938 Case 7 1,915 23,604 29,784 30,727 Case 8 1,930 24,066 30,277 31,232 Case 9 1,918 24,031 30,239 31,140 Case 10 1,515 25,956 30,751 31,556 Case 11 1,550 25,530 30,601 31,267 Case 12 1,351 26,681 30,984 31,603 Case 13 1,337 26,817 31,096 31,715 Case 14 1,368 26,678 31,099 31,678 Case 15 3,094 22,909 32,060 33,036 Case 16 3,852 22,803 34,100 35,053 Case 17 3,702 27,139 37,948 38,792 138 PACIFiCORP-20ll IRP APPENDIX E - STOCHASTIC SIMUATION RESULTS Case 1 3,538 30,185 40,773 41,748 Case 2 3,629 29,986 40,833 41,897 Case 3 3,530 30,116 40,643 41,639 Case 4 3,535 30,308 40,860 41,801 Case 5 3,588 30,125 40,857 41,685 Case 6 3,537 30,112 40,621 41,470 Case 7 3,497 30,198 40,653 41,578 Case 8 3,492 30,527 40,943 41,929 Case 9 3,485 30,425 40,852 41,709 Case 10 2,992 32,117 40,806 41,749 Case 11 3,031 32,052 41,074 41,787 Case 12 2,779 32,666 40,627 41,417 Case 13 2,710 32,664 40,457 41,270 Case 14 2,794 32,693 40,772 41,597 Case 15 3,366 30,376 40,526 41,375 Case 16 4,362 29,774 42,618 43,469 Case 17 4,271 32,485 44,974 45,819 Case 18 5,419 29,490 45,353 46,097 Case 19 3,378 31,435 41,467 42,276 Case 1 3,109 30,050 39,270 40,465 Case 2 3,204 29,836 39,513 40,542 Case 3 3,103 30,012 39,230 40,360 Case 4 3,115 30,300 39,523 40,667 Case 5 3,158 30,177 39,517 40,653 Case 6 3,111 30,173 39,350 40,445 Case 7 3,076 30,080 39,198 40,342 Case 8 3,080 30,479 39,618 40,747 Case 9 3,070 30,426 39,534 40,666 Case 10 2,573 32,206 39,619 40,718 Case 11 2,612 31,976 39,524 40,592 Case 12 2,390 32,783 39,859 40,452 139 PACIFICORP - 2011 IR APPENDIX E - STOCHASTIC SIMATION RESULTS Case 13 Case 14 Case 15 Case 16 Case 17 Case 18 Case 19 2,365 2,391 2,806 3,543 3,381 4,210 2,960 32,896 32,821 30,683 29,877 32,874 29,456 31,450 39,979 39,968 39,117 40,405 42,757 41637 40,155 40,576 40,528 40,197 41,519 43,692 42,791 41,203 Table E.3 - Carbon Dioxide and Other Pollutant Emissions 1 941,203 753 1,092 653 939 5,700 801,497 641 912 5,492 2 943,810 754 1,093 656 94 5,721 807,175 64 918 5,516 3 937,91 751 1,087 649 932 5,681 796,784 638 906 5,473 4 930,958 745 1,075 643 918 5,881 787,44 631 891 5,697 5 929,942 740 1,066 635 906 5,813 782,864 622 877 5,637 6 924,985 737 1,061 631 90 5,791 777,60 619 872 5,618 7 938,503 752 1088 650 933 5,683 797,611 638 907 5,476 8 931,497 748 1,079 64 923 5,912 789,817 635 897 5,722 9 930726 745 1074 642 916 5860 785 834 630 889 5,683 10 917,430 747 1,076 641 912 5,834 764,891 627 882 5,648 11 932,265 756 1095 651 934 5,672 784,279 638 906 5,462 12 907,039 741 1,067 631 898 5,792 751,203 618 869 5,595 13 906,120 742 1,068 633 90 5,735 750,46 620 871 5,559 14 911,849 742 1,067 633 900 5,771 755,99 618 869 5,591 15 814,681 645 916 670 958 6,029 800,509 639 905 5,736 16 770,990 60 854 626 890 5,766 746,912 586 828 5,434 17 673,465 543 766 566 803 5;377 651,663 525 745 5,062 18 677,562 506 709 568 804 5,447 682,971 516 723 5,068 19 922,446 740 1,068 636 911 5,610 779,075 623 883 5;393 Table E.4 - Cumulative to-year Customer Rate Impact, Core Case Portfolios 1 22.6%39.6%33.6%31.9%3 2 22.3%39.4%33.3%31.7%1 3 22.6%39.5%33.5%31.9%2 4 22.9%39.8%33.8%32.2%6 5 22.7%39.6%33.6%32.0%5 6 23.3%39.9%34.0%32.4%9 7 22.7%39.6%33.6%31.9%4 8 23.0%40.0%33.9%32.3%8 9 22.9%39.9%33.8%32.2%7 10 27.3%43.4%37.8%36.2%17 11 26.3%42.6%36.9%35.2%13 140 P ACIFICORP - 2011 IRP ApPENDIX E - STOCHASTIC SIMUATION RESULTS 12 26.9%43.0%37.5%35.8%16 13 26.3%42.6%36.9%35.2%14 14 28.3%44.0%38.7%37.0%18 15 24.1%39.6%33.8%32.5%10 16 26.0%39.9%35.3%33.7%11 17 33.4%45.0%41.6%40.0%19 18 29.5%40.6%37.1%35.7%15 19 25.5%42.3%36.3%34.7%12 Figure E.5 - Average Annual Energy Not Served (2011 - 2030), $19 CO2 Core Case Portfolios ~" õi æ=~ ~"....;.~ 50 ..--.------.---.-.-.--.----..-.----------.~.--.------.-.-________._________.__ 60 141 P ACIFICORP - 2011 IR APPENDIX E- STOCHASTIC SIMUATION RESULTS Table E.5 - Loss of Load Probabilty for a Major (;: 25,000 MWh) July Event, Core CasePortfolios ' 7%7%7%7%7%7%7%7%7%7% 6%6%6%6%6%6%6%6%6%6% 8%8%8%8%8%8%8%8%8%8% 10%10%10%10%10%10%10%10%10%10% 13%12%12%12%12%12%12%12%12%13% 10%10%10%10%10%10%10%10%10%10% 19%19%19%19%19%19%19%19%19%19% 27%27%27%27%27%27%27%27%27%27% 26%26%26%26%26%26%26%25%26%25% 21%21%21%21%21%21%21%21%21%21% 24%24%24%24%24%24%24%24%24%24% 21%21%21%21%21%21%17%21%18%19% 9%13%16%16%16%16%6%16%15%16% 21%18%27%17%33%33%16%33%27%33% 18%14%23%21%17%26%23%26%26%26% 17%16%13%13%14%14%20%13%21%20% 24%27%27%28%19%16%28%19%28%28% 31%31%24%25%16%16%30%24%25%23% 39%39%33%37%24%24%38%30%24%21% 50%51%49%39%35%35%50%47%28%29% 7%7%7%7%7%7%7%7%7% 6%6%6%6%6%6%6%6%6% 8%8%8%8%8%8%8%8%8% 10%10%10%10%10%10%10%10%10% 13%13%13%13%12%12%13%12%13% 10%10%10%10%10%10%10%10%10% 19%19%19%19%19%19%19%19%19% 27%27%27%27%27%27%27%27%27% 25%25%25%25%25%26%25%25%26% 21%21%21%21%21%21%21%21%21% 24%20%24%24%24%24%24%24%24% 18%13%19%21%21%21%21%6%22% 13%11%14%16%16%16%16%2%16% 25%27%24%33%32%19%32%32%32% 15%15%15%19%26%17%14%26%26% 15%16%16%12%13%11%13%21%14% 28%28%23%12%14%27%25%27%23% 29%29%23%27%18%20%20%22%20% 36%37%32%33%28%32%27%32%37% 50%46%36%36%43%39%43%35%48% 142 PACIFICORP - 2011 IRP APPENDIX E - STOCHASTIC SIMUATION RESULTS Table E.6 - Average Loss of Load Probabilty During Summer Peak 143 P ACIFICORP - 2011 IR APPENDIX E - STOCHASTIC SIMUATION RESULTS The following tables report stochastic production cost modeling results for Cases 21 through 24 (coal utilization sensitivities) and Cases 25 and 26 (low and high economic growth sensitivities). Note that the Case 20 coal utilization portfolio (medium C02 tax and gas prices) did not result in any coal plant replacements, so the Company did not consider it wortwhile to conduct a stochastic production cost simulation with ths portolio. Similarly, the Case 27 portfolio, which assumed high peak loads drven by one-in-ten peak load producing temperatues, was not sufficiently different in resource mix relative to the high economic growth portfolio to warant stochastic production cost modeling. Table E.7 - Stochastic Mean PVR by CO2 Tax Level, Sensitivity Portfolios Table E.8 - Stochastic Risk Results by C02 Tax Level, Sensitivity Portolios 144 P ACIFICORP - 2011 IRP APPENDIX E - STOCHASTIC SIMUATION RESULTS 145 vi ~vi ~ 5 ~..:::: ižu ~-.= ~rJ I¡i~ l ~--oN i ~u ¡; ~i: ~§ ~r- ., 00 .9..- i= ., ~ ~ 8. 0. 8 vo ~(, (, tí ~ 8 8 ~ vv ..~ .. i. i-~ ., iã ~ v 0-~~~1:: ~~ ~ ;; .D~...D ~ ~ 8- ;; 8A. 0 i: (,~ tí ë 8v 00.g oS ~ ~ t ~(, 0 ò.s 0....vi ~.~..~ ~'r¡:. ~ ~ ., Q) vi1: - vo ~ oS0. 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Va r i a b l e C o s t s Fu e l & O & M 15 , 8 8 4 15 , 0 4 6 15 , 1 8 0 14 , 8 1 2 14 , 7 2 4 14 , 7 6 5 16 , 1 3 0 15 , 7 1 0 Em i s i o n C o s t 7, 3 2 9 7, 1 0 0 7, 2 8 4 6, 9 5 3 6, 9 6 8 7, 0 0 9 7, 7 3 4 7, 1 7 9 FO T s & L o n g T e r m C o n t r c t s 3, 8 5 5 3, 9 3 2 3, 9 9 7 3, 9 5 7 3, 9 1 3 3, 9 9 8 3, 9 6 1 3, 8 8 2 De m a d S i d e M a n a g e m e n t 4, 0 3 3 4, 5 5 3 4, 5 1 6 4, 4 1 4 4, 5 3 4 4, 6 3 0 3, 6 7 6 3, 8 3 0 Re n e w a b l e s 86 6 1, 2 9 8 1, 3 2 8 1, 3 7 9 1, 3 2 8 1, 3 1 5 84 3 87 0 Sy s t e m B a l a n c i n g S a l e s (6 , 0 4 0 ) (6 , 1 2 0 ) (6 , 1 6 6 ) (6 , 3 1 5 ) (6 , 2 5 6 ) (6 , 3 3 0 ) (6 , 3 5 3 ) (5 , 7 9 8 ) Sy s t e m B a l a n c i n P u r c h a s e s 3, 0 6 7 2, 9 7 5 2, 9 5 4 2, 8 0 1 2, 8 4 5 2, 8 3 1 2, 7 3 0 3, 3 3 3 Nu c l e a r - - - - 88 En e r g y N o t S e r v e d 13 1 13 3 13 8 13 1 13 0 13 3 13 3 13 0 Du Po w e r (1 1 6 ) (1 1 8 ) (1 1 7 ) (1 2 0 ) (1 1 7 ) (1 1 9 ) (1 1 6 ) (1 1 6 ) Re s e r v e D e f i i e n c y 0 1 4 3 2 2 0 0 To t a l V a r i a b l e C o s t s 29 , 0 0 9 28 , 8 0 0 29 , 1 1 8 28 , 0 1 5 28 , 1 5 7 28 , 2 3 3 28 , 7 3 8 29 , 0 2 1 Ca p i t l a n d F i x e d C o s t s 6, 2 2 2 7, 5 6 2 7, 0 3 6 8, 6 6 4 8, 6 3 1 8, 4 6 4 6, 2 3 2 6, 3 0 7 To t a l P V R R 35 , 2 3 1 36 , 3 6 2 36 , 1 5 4 36 , 6 7 8 36 , 7 8 9 36 , 6 9 8 34 , 9 6 9 35 , 3 2 7 14 7 PA C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X E - S T O C H A S T I C S I M U L A T I O N R E S U L T S Ta b l e E . l l - C o r e C a s e s 1 7 t h r o u g h 1 9 , P o r t f o l i o P V R R C o s t C o m p o n e n t s ( $ 1 9 C 0 2 T a x L e v e l ) Va r i a b l e C o s t s Fu e l & O & M 13 , 9 0 9 15 , 2 3 9 15 , 4 4 6 Em i s i o n C o s t 6, 1 1 2 6, 5 2 4 7, 2 4 6 FO T s & L o n g T e r m C o n t r c t s 4, 0 0 1 3, 6 3 9 4, 0 5 4 De m a n d S i d e M a n a g e i r n t 4, 5 3 5 3, 9 3 9 4, 8 0 8 Re n e w a b l e s 1, 3 6 3 84 3 66 8 Sy s t e m B a l a n c i n g S a l e s (5 , 5 8 6 ) (5 , 1 9 7 ) (6 , 0 9 3 ) Sy s t e m B a l a n c i n g P u r c h a s e s 3, 5 4 5 3, 9 4 1 3, 0 7 0 Nu c l e a r 44 En e r g y N o t S e r v e d 13 1 12 8 13 7 Du P o w e r (1 1 9 ) (1 1 4 ) (1 1 5 ) Re s e r v e D e f i c i e n c y 2 0 1 To t a l V a r i a b l e C o s t s 27 , 9 3 7 28 , 9 4 2 29 , 2 2 1 Ca p i t l a n d F i x e d C o s t s 10 , 0 9 9 6, 8 4 9 6, 9 0 7 To t a l P V R R 38 , 0 3 6 35 , 7 9 0 36 , 1 2 8 14 8 PA C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X E - S T O C H A S T I C S I M U L A T I O N R E S U L T S Ta b l e E . 1 2 - C o a l P l a n t U t i i z a t i o n S e n s i t i v i t y a n d L o a d F o r e c a s t S c e n a r i o ( $ 1 9 C O 2 T a x L e v e l ) De s c r i p t i o n I Ca s e 2 1 I C a s e 2 2 I C a s e 2 3 I C a s e 2 4 I C a s e 2 5 I C a s e 2 6 Va r i a b l e C o s t s Fu e l & O & M 15 , 6 5 3 15 , 5 9 4 15 , 8 2 2 15 , 7 7 3 14 , 9 5 4 16 , 5 9 9 Em i s i o n C o s t 7, 4 2 0 7, 4 0 9 7, 2 2 6 7, 2 2 7 7, 1 9 9 7, 6 5 6 FO T ' s & L o n g T e r m C o n t r a c t s 4, 0 5 4 4, 0 4 3 4, 0 4 8 4, 0 3 2 3, 9 8 1 3, 9 5 4 De m a n d S i d e M a n a g e m e n t 3, 6 7 5 4, 1 1 7 3, 9 9 1 4, 0 0 3 3, 9 2 0 3, 8 1 7 Re n e w a b l e s 84 8 87 1 84 7 87 3 83 2 85 1 Sy s t e m B a l a n c i n g S a l e s (5 , 9 5 8 ) (5 , 9 6 2 ) (5 , 9 8 3 ) (5 , 9 8 3 ) (6 , 1 4 2 ) (5 , 9 4 0 ) Sy s t e m B a l a n c i n g P u r c h a s e s 3, 1 5 6 3, 1 4 5 3, 1 2 3 3, 1 1 6 2, 9 7 8 3, 2 3 5 Nu c l e a r En e r g y N o t S e r v e d 14 8 14 7 14 5 11 9 11 1 16 6 Du m p Po w e r (1 1 6 ) (1 1 6 ) (1 1 6 ) (1 1 6 ) (1 1 9 ) (1 1 3 ) Re s e r v e D e f i c i e n c y 2 1 1 1 1 2 To t a l V a r i a b l e C o s t s 28 , 8 8 1 29 , 2 4 9 29 , 1 0 3 29 , 0 4 6 27 , 7 1 5 30 , 2 2 8 Ca p i t a l a n d F i x e d C o s t s 5, 9 7 6 5, 9 9 2 6, 4 5 8 6, 4 5 8 6, 3 5 6 6, 3 5 6 To t a l P V R 34 , 8 5 7 35 , 2 4 1 35 , 5 6 1 I 35 , 5 0 4 I 34 , 0 7 1 I 36 , 5 8 3 14 9 P A C I F i C O R P - 2 0 1 1 I R P Ap P E N D I X E - S T O C H A S T I C S I M U L A T I O N R E S U L T S Ta b l e E . 1 3 - C o a l P l a n t U t i l z a t i o n S e n s i t i v i t y a n d L o a d F o r e c a s t S c e n a r i o ( $ 0 C 0 2 T a x L e v e l ) De s c r i p t i o n I C a s e 2 1 I C a s e 2 2 I C a s e 2 3 I C a s e 2 4 I C a s e 2 5 I C a s e 2 6 Va r i a b l e C o s t s Fu e l & O & M 15 , 7 6 5 15 , 7 2 1 15 , 8 7 9 15 , 8 4 9 15 , 1 3 9 16 , 7 9 8 Em i s i o n C o s t 2 2 2 2 2 2 FO T ' s & L o n g T e r m C o n t r a c t s 3, 8 4 8 3, 8 3 9 3, 8 4 3 3, 8 3 1 3, 7 9 2 3, 7 7 0 De m a n d S i d e M a n a g e m e n t 3, 6 7 5 4, 1 1 7 3, 9 9 1 4, 0 0 3 3, 9 2 0 3, 8 1 7 Re n e w a b l e s 78 8 80 3 78 9 80 7 77 7 81 8 Sy s t e m B a l a n c i n g S a l e s (5 , 5 7 2 ) (5 , 5 7 7 ) (5 , 5 7 4 ) (5 , 5 7 7 ) (5 , 7 6 9 ) (5 , 7 5 4 ) Sy s t e m B a l a n c i n g P u r c h a s e s 2, 1 3 4 2, 1 2 6 2, 1 3 7 2, 1 2 8 1, 9 6 4 2, 1 9 1 Nu c l e a r En e r g y N o t S e r v e d 14 9 14 8 14 7 14 5 11 2 17 3 Du m p Po w e r (1 2 0 ) (1 2 0 ) (1 2 0 ) (1 2 0 ) (1 2 2 ) (1 1 4 ) Re s e r v e D e f i c i e n c v 2 1 1 1 1 2 To t a l V a r a b l e C o s t s 20 , 6 7 2 21 , 0 6 1 21 , 0 9 5 21 , 0 6 9 19 , 8 1 5 21 , 7 0 4 Ca p i t a l a n d F i x e d C o s t s 5, 9 7 6 5, 9 9 2 6, 4 5 8 6, 9 0 7 5, 3 2 7 6, 3 5 6 To t a l P V R 26 , 6 4 8 27 , 0 5 3 27 , 5 5 3 27 , 9 7 6 25 , 1 4 2 28 , 0 5 9 15 0 P A C I F I C O R P - 2 0 1 1 I R P AP P E N D I X E - S T O C H A S T I C S I M U L A T I O N R E S U L T S Ta b l e E . 1 4 - C o a l P l a n t U t i l i z a t i o n S e n s i t i v i t y a n d L o a d F o r e c a s t S c e n a r i o ( $ 1 2 C O 2 T a x L e v e l ) De s c r i p t i o n I Ca s e 2 1 I C a s e 2 2 I C a s e 2 3 I C a s e 2 4 I C a s e 2 5 I C a s e 2 6 Va r i a b l e C o s t s Fu e l & O & M 14 , 1 1 1 14 ; 0 5 0 14 , 3 2 4 14 , 2 8 0 13 , 4 8 4 15 , 0 1 3 Em i s i o n C o s t 7, 3 0 9 7, 2 9 9 6, 9 5 0 6, 9 5 7 7, 1 0 4 7, 6 1 0 Fa T ' s & L o n g T e r m C o n t r a c t s 3, 8 1 3 3, 8 0 5 3, 8 0 9 3, 7 9 3 3, 7 4 5 3, 7 2 3 De m a n d S i d e M a n a g e m e n t 3, 6 7 5 4, 1 1 7 3, 9 9 1 4, 0 0 3 3, 9 2 0 3, 8 1 7 Re n e w a b l e s 84 7 87 0 84 7 87 3 83 0 84 5 Sy s t e m B a l a n c i n g S a l e s (4 , 1 2 6 ) (4 , 1 3 3 ) (4 , 1 5 2 ) (4 , 1 5 9 ) (4 , 3 1 9 ) (4 , 1 1 2 ) Sy s t e m B a l a n c i n g P u r c h a s e s 3, 8 5 2 3, 8 4 0 3, 8 1 8 3, 8 1 1 3, 6 1 9 3, 9 2 0 Nu c l e a r En e r g y N o t S e r v e d 15 3 15 2 15 0 14 8 11 7 17 1 Du m p Po w e r (1 1 6 ) (1 1 6 ) (1 1 6 ) (1 1 6 ) (1 1 8 ) (1 1 2 ) Re s e r v e D e f i c i e n c y 2 1 1 1 1 2 To t a l V a r i a b l e C o s t s 29 , 5 1 9 29 , 8 8 6 29 , 6 2 1 29 , 5 9 2 28 , 3 8 3 30 , 8 7 7 Ca p i t a l a n d F i x e d C o s t s 5, 9 7 6 5, 9 9 2 6, 4 5 8 6, 9 0 7 5, 3 2 7 6, 3 5 6 To t a l P V R 35 , 4 9 5 35 , 8 7 7 36 , 0 7 9 I 36 , 4 9 9 I 33 , 7 1 0 I 37 , 2 3 3 15 1 P ACIFICORP - 2011 IR APPENDIX F - PUBLIC INPUT PROCESS ApPENDIX F - THE PUBLIC INPUT PROCESS A critical element of this resource plan is the public input process. PacifiCorp has pursued an open and collaborative approach involving the Commssions, customers and other stakeholders in PacifiCorp's planning process prior to making resource planning decisions. Since these decisions can have significant economic and environmental consequences, conducting the resource plan with transparency and full participation from Commissions and other interested and affected parties is essentiaL. The public has been involved in this resource plan from its earliest stages and at each decisive step. Paricipants have both shared comments and ideas and received information. As reflected in the report, many of the comments provided by the partcipants have been adopted by PacifiCorp and have contributed to the quality of this resource plan. PacifiCorp wil adopt fuher comments going forward, either as elements of the Action Plan or as futue refinements to the planning methodology. The cornerstone of the public input process has been full-day public input meetings held approximately thoughout the year-long plan development period. These meetings have been held jointly in two locations-Salt Lake City, Utah and Portland Oregon-using telephone and video conferencing technology. IR public process continued with state stakeholder dialogue sessions from mid-June through August 2010. These goal of these sessions, targeting a state-specific audience, were to (1) captue key resource planning issues of most concern to each state, and discuss how these can be tackled from a system planning perspective, (2) ensure that stakeholders understand PacifiCorp's planing principles and the logic behind its planing process, and (3) set expectations for what can be accomplished in the curent IRPlbusiness planning cycle. These State focused meetings contiued to enhance interaction with stakeholders in the planning cycle, and provided a foru to directly address stakeholder concerns regarding equitable representation of state interests durng general public meetings. As far as agenda setting is concerned, PacifiCorp solicited recommendations from the state stakeholders in advance of the session, as well as allowing open time to ensure that participants had adequate time for dialogue. Some follow-up activities arising from the sessions were addressed in subsequent public meetings. The 2010 public input meetings were augmented by a series of focused technical workshops to provide an opportity to discuss complex topics for a multi-state utility in more detaiL. Among the organizations that were represented and actively involved in this collaborative effort were: Commissions · Idaho Public Utilities Commission · Oregon Public Utilties Commission 153 P ACIFICORP - 2011 IR APPENDIX F - PUBLIC INUT PROCESS . Public Service Commission of Uta . Washington Utilities and Transporttion Commssion . Wyomig Public Service Commission Intervenors . Attorney General of Washington . Brigham Young University . Citizen's Utilty Board of Oregon . Committee for Consumer Services State of Uta . ECOS Consulting . Encana Corporation . enXco . Energy Trust of Oregon . Energy Strategies, LLC . HEAL Utah and Utah Physicians for a Healthy Environment . Health Environment Allance of Utah (HEAL) . Horizon Wind Energy . Iberdrola . Industrial Customers of Northwest Utilities . Interwest Energy Allance . Kennecott . Mountain West Consultig, LLC . Northwest Power and Conservation Council . Northwest Pipeline GP . NW Energy Coalition . Oregon Departent of Energy . Powder River Basin Resource Council . Renewables Northwest Project . Salt Lake City . Salt Lake Community Action Progrm . Southwest Energy Efficiency Project . Sierra Club, Utah Chapter . U.S. Deparent of Energy - Intermountain Clean Energy Application Center . U.S. Departent of Energy - Northwest Clean Energy Application Center . Utah Association of Energy Users . Utah Clean Energy Allance . Utah Division of Air Quality . Uta Division of Public Utilities . Utah Energy Office . Utah Geological Surey . Wasatch Clean Air Coalition . Western Resource Advocates . West Wind Wires . Wyoming Industrial Energy Consumers 154 P ACIFICORP - 2011 IRP APPENDIX F - PUBLIC INPUT PROCESS . Wyoming Offce Of Consumer Advocacy Others . A vista Utilities . Cadmus Group Inc. · GDS Associates . Idaho Power Company · John Klingele (Washington Customer) · Portland General Electrc (PGE) PacifiCorp extends its gratitude for the time and energy these participants have given to the resource plan. Your participation has contrbuted significantly to the quality of this plan, and your continued participation will help as PacifiCorp strives to improve its planning efforts going forward. PacifiCorp hosted five full-day public input meetings, two half day meetings, one conference call and six state meetings during the 2010. Durng the 2011 IRP process presentations and discussions covered various issues including inputs and assumptions, risks, modeling techniques, and analytical results. Below are the agendas from the public input meetings and the technical workshops. General Meetings April 28, 2010 · IRP Group and Support Team · Discussion on the wind integration study methodology white paper · IRP Regulatory Compliance (2008 IRP / 2011 IRP) · IRP Preparation Schedule and Public Process . IRP Modeling Plan and Initiatives . 2008 IRP Update August 4,2010 · Demand-side management / distrbuted generation · Supply-side Resources · Planning Reserve Margin (PRM) analysis · Proposed portfolio development cases October 5, 2010 . IRP Schedule Update · Energy Gateway Transmission Constrction Update and Evaluation . Load Forecast · Hedging Strategy . Market Reliance Analysis · Capacity Load & Resource Balance · Portfolio Development Cases 155 P ACIFICORP - 2011 IR APPENDIX F - PUBLIC INUT PROCESS December 15,2010 . Planning Reserve Margin and LOLP . Update on Assumptions . Load Forecast Scenarios . DSM Supply Cures . Update Load and Resource Balance . Preliminar Results for Core Cases and Transmission January 27,2011 . Solar photovoltaic resource modeling January 31,2011 . Review of System Optimizer Core Case Results - Cases i to 19 February 23,2011 . Stochastic production cost modeling results . preferred portfolio selection . coal utilization study results March 23, 2011 . Preferred portfolio discussion, . Remaining portfolio sensitivity results, and . the IRP action plan State Meetings June 16,2010 - Oregon / California . Evaluating distrbution efficiency potential . Wind integration study . Transmission financial analysis . Assumptions update for portolio analysis / All-source RFP . Intermediate-term Market Puchases . Out-year resource selection . Enhanced regulatory impact modeling . Use of carbon dioxide emissions for portfolio performance scorig . Open Discussion Items - Sma Grd and PacifiCorp Modeling June 29, 2010 - Utah . Renewable/non-traditional Resource Evaluation Wind integration study 156 PACIFICORP - 2011 IRP APPENDIX F - PUBLIC INPUT PROCESS Distrbuted solar Resource modeling and characterization Sensitivity analysis of incentive programs (e.g., level of incentive needed to make distrbuted solar cost-effective) Hybrid intennittent/storage technologies Commercial geothermal potential study . DSM Potential Study Treatment of achievable potential adjustments Application of the Utility Cost Test . Market Risk Assessment Price hedging strategy Inclusion of hedging costs in portfolio resources Sensitivity analysis of hedging strategies to minimize costs and risks for customers Market purchase risk assessment WECC Power Supply Assessment Stochastic simulation and risk analysis . Resource Adequacy Planning reserve margin evaluation Sensitivity analysis of Energy Not Served (ENS) price; i.e., flat vs. tiered approach Hydro sustained peaking capability Treatment of planned resources . Load Forecasting GDS Consulting recommendations for the 2008 IRP Load forecast scenarios Stadalone load forecast report Stochastic parameter estimation · Model Training July 28, 2010 - Idaho · 2008 IRP Acknowledgement Letter · Discount rate impact on resource timing and selection · Wind integration costs - justification and stochastic modeling support · Quantifying Renewable Portfolio Standard costs and other jursdictional mandates · Portfolio selection process and weighting scheme August 11,2010- Wyoming · ENS in Portfolio Modeling . Planning Reserve Margin · C02 Modeling: Tax versus Cap-n- Trade . Supply-side Option Table . LOLP . Weighting Schemes 157 P ACIFICORP - 2011 IR APPENDIX F - PUBLIC INPUT PROCESS Durg the course of the public input meetigs, certin concerns or questions needed additional follow-up from PacifiCorp. These questions or issues were taken off-line and addressed in a meeting report or ata subsequent public input meeting or workshop. PacifiCorp distrbuted the draft document materials on February 23 and March 7, 2011 for public review. Public comments were requested by March 24, 2011. Parties that submitted comments include: . Encana Corporation . HEAL Utah and Utah Physicians for a Healthy Environment . Interwest Energy Allance . Powder River Basin Resource Council . Renewable Northwest Project . SieITa Club . Uta Association of Energy Users . Utah Clean Energy . Uta Public Service Commission Staff . U.S. Departent of Energy - Nortwest Clean Energy Application Center . U.S. Deparent of Energy - Intermountain Clean Energy Application Center . Washington Utility and Transporttion Commission . Western Resource Advocates Many of the clarifications and information requested through the wrtten comments, verbal suggestions from the March 23,2011 conference call, and data requests, have been incorporated into the final version of the IRP. PacifiCorp's IRP internet website contains many of the documents and presentations that support recent Integrated Resource Plans. To access it, please visit the company's website at htt://www.PacifiCorp.com click on the menu "Energy Sources" and select "Integrated Resource Planning" . PacifiCorp requests that any informal request be sent in writing to the following address or email address below. 158 PACIFICORP - 2011 IR ApPENDIX F - PUBLIC INPUT PROCESS PacifiCorp IRP Resource Planning Department 825 N.E. Multnomah, Siiite 600 Portland, Oregon 97232 Electronic Email Address: IRP(ã)PacifiCorp.com Phone Number: (503) 813-5245 159 P ACIFICORP - 2011 IR APPENDIX G - HEDGING STRATEGY ApPENDIX G - HEDGING STRATEGY This appendix addresses two Public Service Commission of Utah analysis requirements pertaining to price hedging. · "At a minimum, we direct the Company to include the costs of hedging in its IRP analysis of resources that rely on fuels subject to volatile prices." . "We also direct the Company to perform sensitivity analysis to determine a hedging strategy which minimizes costs and risks for customers.,,3 To address these requirements, this appendix presents a comparison among hedging strategies to demonstrate that while the expected value of all hedging strategies is the same, different strategies have differing risk profiles. The consequence is that selection of a hedging strategy is made not by expected outcome but by risk tolerance, and that hedging outcomes net to a zero expected value on a long-term basis. Purpose of Hedging Hedging is done solely for the purose of limiting financiallosses due to unfavorable wholesale market price changes. The Company has exposure to power and natual gas wholesale market price changes due to its responsibility to serve retail load and to economically dispatch its resources. The Company cannot avoid such exposure but can reduce it though hedging. A long forward power position occurs when the amount of energy anticipated to be economically produced by the Company's resources exceeds the amount of energy forecast to be consumed by retail customers, and the Company risks financialloss if wholesale power market prices fall. A short forward natual gas position occurs when the Company's natural gas generation is expected to economically convert natual gas to power and the Company risks financial loss if wholesale natual gas market prices rise. The Company may also have short power positions and, attimes, long natual gas positions. All of these open positions result in price risk. Need for Hedging Perfect foresight of futue wholesale market prices is unattainable by any hedging entity, including the Company. While the Company may have a view of where it believes prices are heading - up, down, or no change - it does not have the ability to predict without error such price changes. The Company has incentive to protect against unfavorable wholesale market 3 Public Service Commission of Utah, "In the Matter of the Acknowledgment of PacifiCorp' s Integrated Resource Plan", Report and Order, Docket No 09-2035-01, April 1, 2009, p. 30. 161 PACIFICORP - 20 11 INTGRATED RESOURCE PLAN APPENDIX G - HEDGING STRTEGY price changes and does so by hedging to reduce the range of net power cost outcomes for any wholesale market price changes. Impact of Hedging and Hedging Costs Hedging modifies the potential losses and gains in net power costs associated with wholesale market price changes. Increased hedging reduces both the potential losses and potential gains. Therefore, if the Company has a low risk tolerance it would hedge a greater amount than if it has a high risk tolerance. Hedging does not, however, modif the expected outcome of net power costs associated with wholesale market price changes. Any hedging program, whether it utilizes fixed-price forward or option products, would result in the same expected net power costs from the perspective of the time the hedges are transacted. Historical gains and losses due to hedging are only indicative of potential opportity costs for having pursued an alternate hedging strategy once the outcome is already known. With respect to hedging costs, which the Company defines as hedging program expenses, Figue G.1 shows the trend in the Company's annual costs for both electrcity and natural gas hedging activities (broker fees). As can be seen, the hedging costs are too small to be used as a meaningful distinguishing factor among resources and portfolios. Figure G.l- PacifCorp's Annual Electricity and Natural Gas Hedging Costs Annual Hedging Costs, Electricity 700,000 600,000 500,000 f400,000.! 8 300,000 200,000 100,000 o 2007 2008 2009 2010 !I Hedging Costs, Electricity 162 PACIFICORP - 2011 IR APPENDIX G - HEDGING STRTEGY Annual Hedging Costs, Natural Gas 10,000 8,000 II 6,000...!Õc 4,000 2,000 0 2007 $8,746 $627 2008 2009 2010 li Annual Hedging Costs, Natural Gas Hedge Products The basic hedge products available to the company are. fixed-price forwards and, to a lesser extent, vanila options. All basic hedging strategies are in theory implementable using combinations of these two tyes of products. In practice, however, the Company almost exclusively employs fixed-priced forwards. This is because forward markets relevant to the Company are liquid, and the costs have been determined to be recoverable. In contrast, options have a number of disadvantages to the Company. There are not liquid regional options markets, meaning that any options available have a high additional cost reflected in the spread between the buyer's bid price and the seller's ask price. There is an active natual gas options market at Henr Hub, but the price of natual gas in the Company's region does not necessarly move in lock-step with the price of natual gas at Henr Hub. This is known as basis risk, and is undesirable. Finally, because options require payment up-front for benefits that mayor may not occur in the future, it is not clear that the Company would be able to recover the cost of unexercised options in rates. No "Best" Hedging Strategy Among the myriad conceivable hedging strategies there is no purely objective optimization method resulting in the best strategy. Determining a strategy that is best for the Company is necessarily in part a subject evaluation. Parameters that must be considered are market liquidity, tyes and availability of desired hedge products, customer risk tolerance, and cost of hedge program management, to name a few. 163 P ACIFICORP - 20 11 INTEGRATED RESOURCE PLAN APPENDIX G - HEDGING STRTEGY Various hedging programs have been simulated to demonstrte the impact to the range of net power cost outcomes and to demonstrate there is no change to the expected outcome. The measurement of range of net power cost outcomes is the "to-expir value-at-risk" distrbution. This TEVaR distribution is a statistically-generated distrbution of outcomes that is wider or narrower based upon the aggregate volatility of the combined power and natual gas portfolio. Inasmuch as being short natual gas natually offsets being long power, one would expect the TEVaR distrbution of a long-power/short-natual gas portolio to be significantly narrower than the distrbution of either individual component. Five portfolios were simulated using Monte Carlo technique to calculate to-expir value-at-risk. The first portfolio, entitled "Reference portfolio," is comprised of a 500 average MW power long position and a (100,000) MMtuday natual gas short position. This represents the Company's hypothetical combination of retail load, economic generation and transactions that partially hedge the position. The long power and short natual gas positions are largely offsetting. This is used as the reference portfolio for the following scenario analyses. The second portfolio, entitled "less hedged," is comprised of 625 average MW power long position and (125,000) MMtuday natual gas short position. Relative to the reference portfolio, this demonstrates the change in risk profile of a portfolio with 25% less hedged position. In this portfolio, there are 125 average MW fewer hedge transactions resulting in more power lengt, and 25,000 MMBtuday fewer hedge trnsactions resulting in a shorter natual gas short position. The third portfolio, entitled "more hedged," is comprised of 375 average MW power long position and (75,000) MMBtuday natual gas short position. Relative to the reference portfolio, this demonstrates the change in risk profile of a portfolio with 25% more hedged position. In this portfolio, there are 125 average MW more hedge transactions resulting in less power length and 25,000 MMBtuday more hedge transactions resulting in less short natual gas position. The fourh portfolio, entitled "Hedge only power," is comprised of a fully hedged power position and (100,000) MMBtuday natual gas short position. Relative to the reference portfolio, this demonstrates hedging all power but no natual gas. The fifth portfolio, entitled "Hedge only natual gas," is comprised of a 500 average MW power long position and a fully hedged natual gas position. Relative to the reference portfolio, this demonstrates hedging all natual gas but no power. Charts of the results are shown below (Figues G.2 through G.5). In addition, for ease of comparson among portfolios, Table G.1 below shows the expected value, the fifth percentile outcome (very unfavorable prices), and the 95th percentile outcome (very favorable prices). These values shown are relative, so that $0 expected value indicates the potential change in portfolio value due to market price changes is expected to be neutraL This is the statistical 164 P ACIFICORP - 2011 IRP APPENDIX G - HEDGING STRATEGY equivalent of the earlier assertion that hedging can only reduce the range of potential net power costs, but canot reduce expected net power costs. . The reference portfolio, shown in blue in each of the four chars, has an unsymmetrcal fift and 95th percentile result due to the likelihood that prices may increase more than decrease, and due to the reference portfolio being net short. A log-normal price distrbution is used to represent this effect. In the less hedged sample portfolio, both the power and natual gas volumes are 25 percent larger than the reference portfolio. Conversely in the more hedged sample portfolio, both the power and natual gas volumes are 25 percent smaller than the reference portfolio. As expected, the less hedged portfolio shows a wider distrbution of outcomes representing a higher risk to price changes. Similarly, the more hedged portfolio shows a narrower distrbution. The "hedge only power" portfolio shows a much wider distrbution due to the severe reduction in the natual offset between power and natual gas in the reference portfolio. The "hedge only natual gas" has a similar distrbution. Of note is the 5th percentile "hedge only power" portfolio is much greater downside than the "hedge only natul gas" portfolio, and this js due to the log- normal prices. Table G.l - Comparison of Multiple Sample Portfolios ($40)$0 $27 ($48)$0 $33 ($29)$0 $20 ($92)$0 $66 ($48)$0 $62 165 P ACIFICORP - 20 11 INTGRATED RESOURCE PLAN APPENDIX G - HEDGING STRTEGY Figure G.2 - Reference Portfolio versus Less Hedged Portolio Reference Portolio vs Less Hedged Portfolio ~~:eII..o..Q. II Reference Portfolio m Less Hedged Portfolio ($150)($100)($50) $0 $50 Potential Change in Value ($M) $100 $150 In the "Reference Portfolio versus Less Hedged Portfolio" chart, the less hedged portfolio has a wider distribution of results than the reference portfolio. While both portfolios have an expected value of zero over all potential scenarios, the less hedged portfolio wil retu a wider range of outcomes. 166 P ACIFICORP - 2011. IRP APPENDIX G - HEDGING STRATEGY Figure G.3 - Reference Portfolio versus More Hedged Portfolio ~ :aII.ao..Cl m Reference Portfolio El More Hedged Portfolio ($150)($100)($50) $0 $50 Potential Change in Value ($M) $100 $150 In the "Reference Portfolio versus More Hedged Portfolio", the more hedged portfolio has a tighter distribution of results than the reference portfolio. While both portfolios have an expected value of zero over all potential scenarios, the more hedged portfolio wil retu a tighter range of outcomes. 167 P ACIFICORP - 20 11 INTEGRATED RESOURCE PLAN APPENDIX G - HEDGING STRTEGY Figure G.4 - Reference Portolio versus Hedging Only Natural Gas ;:~:aII..o..i: II Reference Portolio II Hedge Only Natural Gas ($150)($100)($50) $0 $50 Potential Change in Value ($M) $100 $150 In the "Reference Portfolio versus Hedgig Only Natual Gas", the portfolio where only natual gas has been hedged (and electrcity positions left unedged) has a significantly wider distribution of results than the reference portfolio. While both portfolios have an expected value of zero over all potential scenarios, the alternate portfolio wil retu a significantly wider range of outcomes. This is due to removing the natual offsetting featues of one commodity (i.e., hedging the short natual gas position) while leaving the long electricity position unedged. 168 PACIFICORP - 2011 IR APPENDIX G - HEDGING STRATEGY Figure G.5 - Reference Portfolio versus Hedging Only Electricity ~~ :eni "Qo..Q. II Reference Portfolio II Hedge Only Electricity ($150)($100)($50) $0 $50 Potential Change in Value ($M) $100 $150 In the "Reference Portfolio versus Hedging Only Electrcity", the portfolio where only electrcity has been hedged (and natual gas positions left unhedged) has a significantly wider distrbution of results than the reference portfolio. While both portfolios have an expected value of zero over all potential scenarios, the alternate portfolio wil retu a significantly wider range of outcomes. This is due to removing the natual offsetting featues of one commodity (i.e., hedging the long electrcity position) while leaving the short natual gas position unedged. Hedging does not modify the expected outcome of net power costs associated with wholesale market price and natual gas price changes. Consequently, the long-term gains and losses from hedging are expected to net to zero. As shown in Figue G.1 above, the Company's hedging costs are not material enough to warrant adjustment to resource costs or influence portfolio selection. IIi regard to assessment of hedging strategies, a hedging strategy should be tailored to fall within a designated risk tolerance and conform to Company financial and administrative capabilities. A rationale must be created taking into account risk tolerance for adverse impacts to net power costs, and effects including market liquidity and hedge product availability, credit risk, and costs such as collateral fuding for margining, Finally, PacifiCorp shows that there is no objective measurement to indicate the optimum amount of hedging, as demonstrated by a sensitivity analysis that compares a reference portfolio, a less hedged portfolio, and a more hedged portfolio. Neverteless, the analysis shows that 169 P ACIFICORP - 201 1 INTGRATED RESOURCE PLAN APPENDIX G - HEDGING STRTEGY hedging should tae full advantage of any natual offsets between long power and short natual gas positions. Not taing advantage results in high risk (a wider distrbution of outcomes) as indicated in the "hedge only power" and "hedge only natul gas" portfolios. 170 P ACIFICORP - 2011 IRP APPENDIX H- WESTERN RESOURCE ADEQUACY Ev ALUA nON ApPENDIX H - WESTERN RESOURCE ADEQUACY EVALUATION The Utah Commission, in its 2008 IRP acknowledgment order, directed the Company to conduct two analyses pertaining to the Company's abilty to support reliance on market purchases: Additionally, we direct the Company to include an analysis of the adequacy of the western power market to support the volumes of purchases on which the Company expects to rely. We concur with the Offce fofConsumer Services), the WECC is a reasonable source for this evaluation. We.direct the Company to identif whether customers or shareholders wil be expected to bear the risks associated with its reliance on the wholesale market. Finally, we direct the Company to discuss methods to augment the Company's stochastic analysis of this issue in an IRP public input meetingfor inclusion in the next IRP or IRP update.4 To fulfill the first requirement, PacifiCorp evaluated the Western Electrcity Coordinating Council (WECC) Power Supply Assessment reports to glean trends and conclusions from the supporting analysis. This evaluation, along with a discussion on risk allocation associated with reliance on market purchases, is provided below. As part of this evaluation, the Company also reviewed the status of resource adequacy assessments prepared for the Pacific Northwest by the Pacific Northwest Resource Adequacy Forum. Finally, this appendix describes a study that involved the development and stochastic simulation of a market "stress" scenario. In developing this study, the Company received input from participants at the June 29, 2010 Utah IRP stakeholder's meeting, and described its proposed study approach at the October 5, 2010, IRP general public input meeting. This appendix describes the study methodology and presents results of the stochastic simulations. The Western Electrcity Coordinating Council (WECC) 2010 Power Supply Assessment (PSA) shows WECC needing additional resources in 2019. Resource need is identified when load (including a target reserve margin) exceeds available resources5. Since 2006, each subsequent PSA study defers resource need to later years. This deferment is a fuction of net changes to: load growth expectations, class I capacity entrants, scheduled retirements, resource performance, transfer capabilities and modeling convention. 6 4 Public Service Commission of Utah, PacifiCorp 2008 Integrated Resource Plan, Report and Order, Docket No. 09- 2035-01, p. 30.5 Available resources = Existing Generation + Class I Addletire - Outage/Derate Adjustments + Net Irnports. 6 The 2010 PSA defines Class I capacity as being actively under constrction and online before Janua 1,2014. The 2009 & 2008 PSA require Class I resources to be online by January 1,2013 and Januar 1,2012, respectively. 171 P ACIFICORP -2011 IR APPENDIX H- WESTERN RESOURCE ADEQUACY Ev ALUA TION As seen in Figue 1, there were two significant capacity deferments: from 2012 (per 2008 PSA) to 2016 (per 2009 PSA) followed by 2019 as seen in WECC's 2010 PSA. While the forecast power supply margins (PSM) of the studies from 2006 though 2009 are comparable, the 2010 PSA employed a different, and superior, modeling convention. Namely, the 2010 PSA used PROMOD IV, a chronological production cost model to assess WECC resource adequacy? PROMOD iv, unlike WECC's previous model, uses coincident peak demand and employs a more robust optimization of sub-regional transfers. It is noteworthy that even the 2009 PSA, using the old modeling convention and non-coincident peak demands, did not forecast a capacity need until 2016. Figure H.t - WECC Forecasted Power Supply Margins -5,000 30,000 25,000 20,000 15,000 10,000 !! 5,000 ~".. :š 0 -10,000 -15,000 -20,000 -25,000 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 ~2006PSA ~2007PSA ..2008PSA ..2009PSA ~2010PSA Note: WECC Power Supply Assessments includes Class 1 Planned Resourees Only Of paricular interest is Basin, a sumer peakig sub-region comprised of Utah, Idaho, and northern Nevada. A review of PSA studies from 2007 through 2010 reveals a similar pattern to that ofWECC.8 The 2009 PSA identified a capacity need in 2013; the 2010 PSA defers the need until 2018. As seen in Figure 2, the target reserve margin is maintained at the "zero" horizontal axis. 7 PROMOD IV is electrcity market simulation softare licensed through Ventyx, an ABB Cornpany. http://ww.venty.com/analytics/promod.asp8 Basin was not broken out as a sub-region in WECC's 2006 PSA. 172 PACIFiCORP-201l IRP ApPENDIX H -WESTERN RESOURCE ADEQUACY EVALUATION The PSA' s target reserve margins, as developed by WECC, are not mandated. Instead, they serve as a reasonable proxy for expected target reserve margìns in WECC's modelìng constrct. Figure B.2 - Basin Forecasted Power Supply Margins -1,000 1,500 1,000 500 2 ~0.... ~ -500 -1.500 -2,000 -2,500 -3,000 -3.500 2008 .2009 2010 20ll 2012 2013 2014 2015 2016 2017 2018 2019 ~2007PSA -t2008PSA ~2009PSA ..2010PSA - Note: WECC Power Supply Assessments includes Class 1 Planned Resourees Only The 2010 PSA, and prevìous PSA versìons, use a four-tìer buìldìng block approach to calculating a sub-regìon's target reserve margìn. The first block, contìngency reserves, ìs set at 6% of a balancìng authority's (BA) load. The second block, regulatìng reserves, ìs the amount of spìnnìng reserves needed to ìnstantly match ìncreases ìn electrc load. Expected regulatìng reserve levels were fuìshed by BAs to WECC ìn a 2010 data request. The thìrd block covers addìtìonal forced outages beyond what ìs covered by operatìng reserves ìn the event of a second contìngency event. The fourh block, temperatue adders, ìs the ìncremental amount of reserves needed to cover a 1- ìn-l 0 temperatue event. For modelìng puroses, a BA' s load requìrement ìs the sum of the BA's peak demand forecast plus the WECC's four-tìer target reserve margìn9. As such, a sub-regìon's calculated target reserve margìn should cover a second contìngency event ìn tandem wìth a l-ìn-l0 temperatue event. Moreover, wìth the addìtìon of Idaho Power's 9 A BA's peak demand forecast incorporates a l-in-2 chance of temperatue exceedace. 173 PACIFiCORP-201l IR APPENDIX H- WESTERN RESOURCE ADEQUACY Ev ALUA nON Langley Gulch10 in 2012 and PacifiCorp's Lake Side 211 in 2014, additional capacity wil not be needed until 2019 as shown in Figue H.3 (Note: Figue H.3 is a modified version of the Original PSA char that includes the Langley Gulch and Lake Side 2 resources.) Figure B.3 -Basin Forecasted Power Supply Margins with Selected Capacity Additions -1,000 3,000 I2,000 Il 1,000 = ~.. ~ o -2,000 -3,000 -4.000 200S 2009 2010 2011 2012 2013 2014 2015 2016 2017 20lS 2019 ..2007PSA _200SPSA ..2009PSA ..2010PSA ..201O+LangleyGulch .. 2010+Laugley Gulch+Lake Side II ~ Note: WECC Power Supply Assessment includes Class 1 Planned Resourees only. Langley Gulch, currently under constrction, and Lake Side 2 as proposed by PacifCorp are included here to better reflect Basin's capacity status in later years. io Langley Gulch is a 280-MW sumer rated cornbined cycle under constrction in Idao. It was not included in the 2010 PSA as a Class I entrant since it was not under constrction at publishing time.11 PacifiCorp is seeking to acquire Lake Side 2, a 637-rnegawatt cornbined-cycle cornbustion tubine plant at the Lake Side site in Utah. 174 P ACIFICORP - 2011 IR APPENDIX H- WESTERN RESOURCE ADEQUACY Ev ALVA nON As seen in Figures 4 and 5, neither the Desert Southwest nor the Rockies subregions are expected to need additional capacity prior to 2020.12 Figure H.4 - Desert Southwest Forecasted Power Supply Margins Ii o 4,000 2,000 -2,000 -4,000 -6,000 -s,OOO -10,000 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 201S 2019 ~2007PSA ~200SPSA %W~2009PSA ..2010PSA ~Coolidge Note: WECC Power Supply Assessments includes Class 1 Planned Resources Only. Coolidge Generating is included. 12 Coolidge Generating is 512-MW gas tubine under constrction in Arzona. It was not included in the 2010 PSA as a Class I entrant since it was not under construction at publishing time. 175 P ACIFICORP - 2011 IRP APPENDIX H- WESTERN RESOURCE ADEQUACY Ev ALUA nON Figure D.5 - Rockies Forecasted Power Supply Margins 4,000 3,000 2.000 I ~ 1,000 ! ~, .. 0! coIi -1,000 -2.000 -3,000 -4,000 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 ~2007PSA ..2008PSA ~2009PSA ~2010PSA Note: WECC Power Supply Assessments includes Class 1 Planned Resourees Only. Market depth refers to a market's ability to accept individual transactions without a perceptible change in market price. While different from market liquidity13 the two are lined in that a deep market tends to be a liquid market. Market depth in electrcity markets is a fuction of the number of economic agents, market period, generating capacity, transmission capability, transparency, and institutional and/or physical constraints. Based on the 2010 PSA, WECC maintains a positive PSM through 2018. The Desert Southwest, Northwestl4, and Rockies subregions are forecasted to maintain a positive PSM through 2019. Only Basin is forecast to need capacity in 2018.15 In total, known market transactions, generation resources, load requirements, and the optimization of transfers within WECC show adequate market depth to maintain positive target reserve margins for several years. 13 Market liquidity refers to having ready and wiling buyers and sellers for large transactions. 14 The Nortwest is comprised of the Pacific Northwest and Montaa. 15 Langely Gulch and Lake Side 2, as discussed earlier, wil defer Basin's need until 2019. 176 PACIFiCORP-20ll IR APPENDIX H- WESTERN RESOURCE ADEQUACY EVALUA nON The Pacific Northwest Resource Adequacy Foru issued resource adequacy standads in April 2008, which were subsequently adopted by the Nortwest Power and Conservation CounciL. The standard calls for assessments three and five years out, conducted every year. The 2008 analysis of 2011 through 2013, conducted before the economic downtu, indicated that "the region has ample supplies over the next five years to avoid significant power curailments.,,16 A resource adequacy report update for 2015 is under development. However, the resource adequacy methodology is now undergoing review. The release of the 2015 report is now expected sometime in 2011. Based on WECC's adequacy evaluation, the Pacific Northwest adequacy situation is expected to remain adequate through 2015 and beyond. Market Stress Test Design PacifiCorp's underlying assumptions for the stress test are as follows: . Based on the WECC resource adequacy assessment, the market reliance risk does not become a factor until at least 2015. Consequently, the market stress period was defined as 2015 though 2020. . Availabilty of front offce transactions for this period is reduced to 50% of levels assumed for development of the test portfolio. . Market prices experience a corresponding increase, reflecting reduced market liquidity; the June 2008 Official Forward Price Cure was applied to simulate high market prices as shown in Figue H.6 . To make up for the reduced front offce transaction availability, PacifiCorp assumed that it would lease mobile simple-cycle combustion turbine units with a fixed cost of $267/kW for a three-month period (July-September). The anual SCCT capacity requirement ranges from 330 to 550 MW to cover the lost FOT capacity. PacifiCorp selected a portfolio from the core case group, Case 14, as the test portfolio for the analysis. Case 14 had the highest front office transaction reliance of the core case portfolios for 2015 - 2020. Table H.1 shows the replacement SCCT resource capacity added to the portfolio by year to make up for the reduced FOT, as well as the annual dollars/kW fixed cost assumed for leasing the peaking units. The Company then simulated this portfolio with the Planing and Risk model, applying the above set of market stress assumptions. Portfolio cost (stochastic mean PVRR and stochastic upper-tail mean PVR) are compared against the original stochastic ru for Case 14. 16 The Pacific Nortwest Resource Adequacy Foru's Web page can be accessed with the following link: htt://www.nwcounci1.org!energv/resourcelDefault.asp. The 2008 resource assessment paper is available for download. 177 PACIFiCORP-2011 IR APPENDIX H- WESTERN RESOURCE ADEQUACY EVALUATION Figure H.6 - Front Offce Transaction Market Price Comparison Mid-Columbia Front Office Transaction Market Price (3rd Quarter Heavy Load Hour) 140 120 100 .c~80:E-'I ñic .e 600z 40 20 0 -~--..- I - .. ~~ 2015 2016 2017 2018 2019 2020 .. Sept. 2010 FPC .. June 2008 FPC Table H.t - Peaking Resource Megawatt Capacity Requirements and Fixed Costs Mead Q3, Heavy Load Hour 50 50 0 0 0 0 Uta Q3, Heavy Load Hour 100 94 100 0 0 100 Mona, Q3, Heavy Load Hour 150 150 150 150 150 150 COB Q3, Heavy Load Hour 25 0 0 0 0 0 Mid-Coh.ia Q3, Heavy Load Hour 200 200 200 184 197 200 West Main Q3, Heavy Load Hour 25 25 25 0 0 25 Total 550 519 475 334 347 475 Anl Fixed Cost of Peaki Resources,$36,683,030 $31,706,2502010$ Stress Test Results Table H.2 reports the PVRR line items details for the base stochastic simulation and the stress test stochastic simulation. The stress test conditions resulted in a $387.3 milion increase in the stochastic mean PVR. 178 PACIFICORP - 2011 IR APPENDIX H- WESTERN RESOURCE ADEQUACY EVALUATION Table B.2 - Stochastic PVRR Details for Stress Test and Base Portfolio Simulations Varble Costs Fuel&O&M 8,461.6 9,312.7 851. Emsion Cost 3,098.1 3,533.6 435.5 FOT's & Long Term Contcts 2,647.2 2,415.5 (231.7) Demad Side Mangement $1,715 $1,715 Renewables $657 $671 13.35 System Balancin Sals (3,389.3)(4,273.9)(884.6) System Balcin Pincbaes 1,710.3 1,805.5 95.2 Energy Not Served 70.9 71.0.1 Du Power (23.0)(24.0)(1.0) Reserve Defiiency 0.0 0.0 (0.0) Total Varble Costs 14,947.9 15,225.7 277.8 Capitl and Fixed Costs 2,973.2 3,082.6 109.4 TotalPVR 17,921.18,308.4 The higher costs for the stress test portfolio are drven by greater generation costs resulting from increased thermal resource utilization to cover the replaced FOT, as well as the higher fixed costs of the replacement peaking units. These costs were partially offset by increased market sales and lower purchases stemming from use of the replacement peaking resources during peak periods. Market purchase costs are reflected in rates. Consequently, customers bear the price risk of the Company's reliance on a given level of market purchases. However, customers also bear the cost. impact of the Company's decision to build or acquire resources if those resources exceed market alternatives and result in an increase in rates. These offsetting risks stress the need for robust IRP analysis, effcient RFPs and ability to captue opportistic procurement opportities when they arise. 179 PACIFiCORP-20ll IRP APPENDIX I - WIN INTEGRATION STUY ApPENDIX I - WIND INTEGRATION STUDY This appendix provides the 2010 Wind Integration Study conducted durg the 2011 IRP planing process. This is the version sent to paricipants on September 1,2010. 181 PACIFiCORP-20ll IR APPENDIX I - WIN INTGRATION STUDY Pacì fi COrp 2010 Wind Integrtion Resource Study September 1, 2010 182 PACIFiCORP-20ll IR APPENDIX I - WIN INTEGRATION STUY 1. Executive Summary The purose of the 2010 Wind Integration Study (the "Study") is twofold. First, the Study quantifies how wind generation affects the amount of operating reserve needed to maintain historical levels of reliabilty. Second, the Study tabulates the cost of integrating wind generation by measurng how system costs change with changes in operating reserve demand and by measuring how system costs are affected by daily system balancing practices. Based upon historical and simulated wind generation data and historical load data, the Study shows that operating reserve demand for both regulation reserve service and load following reserve service increases with higher wind penetration levels. For puroses of this Study, regulation reserve service refers to operating reserves required by variability in both load and wind over ten-minute time intervals and load following reserve service refers to operating reserves required by both load and wind variabilty over hourly time intervals. Table 1 summarzes how operating reserve demand for both reguation and load following services increases as wind penetration levels grow from approximately 425 MW to approximately 1,833 MW. Table 2 depicts the change in operating reserve demand that is incremental to a load only calculation of the same tyes of reserve service. Table 1. Annual average operating reserve demand by penetration scenario. Load Only 425MW 1372MW 1833MW Regulation Up 97 105 137 137 West Regulation Down 72 84 120 120 Load Following Up 101 114 139 141 Load Following Down 106 113 132 133 Regulation Up 138 140 201 231 Regulation Down 107 110 185 222EastLoad Following Up 139 144 207 245 Load Following Down 144 147 198 237 Table 2. Annual average operating reserve demand incremental to the load only scenario. Load Only 425MW 1372MW 1833MW Regulation Up 0 7 39 39 West Regulation Down 0 12 48 48 Load Following Up 0 13 38 39 Load Following Down 0 7 26 27 Regulation Up 0 3 63 93 East Regulation Down 0 3 78 116 Load Following Up 0 4 68 106 Load Following Down 0 3 54 93 183 PACIFiCORP-201l IRP APPENIX I - WIN INRATION STUY The costs of integratig wind as calculated in this Study include costs associated with increased operating reserve demand as outlined above and the costs from daily system balancing practices. Both types of costs were calculated using the Planning and Risk model (paR), which is a production cost simulation model configued with a detailed representation of PacifiCorp's system. For each wind penetrtion scenario, a series of PaR simulations were completed to isolate each wind integration cost component by using a "with and without" approach. For instance, PaR was first used to calculate system costs without any incremental operating reserve demand and then again with the added incremental reserve demand. The change in system costs between the two PaR simulations drves the integration cost calculation. Table 3 summarizes the wid integration costs established in this Study alongside those costs calculated as part of the 2008 Integrated Resource Plan. Table 3. Wind integration costs per MW of wind generated as compared to those in the 2008 IR. Study 200IRP 2010 Wind Integration Study 2010 Wind Integration Study Wind Capacity Penetration 2,734MW 1,372MW 1,833MW Te nor of Cost 2G-Year Levelized 3-Year Levelized 3-Year Levelized Interhour / System Balancing ($/MWh)$2.45 $0.82 $0.86 Reserve ($/MWh)$7.51 $8.03 $8.85 Total Wind Integration ($/MWh)$9.96 $8.5 $9.70 As shown above, the Study finds that operating reserve demand and the associated costs increase with wind capacity penetration. System balancing costs, drven by day-aheac forecast errors for wind and load, trend similarly as wind penetration increases from 1,372 MW to 1,833 MW; . however, as expected, system balancing integration costs are much lower than integration costs for operating reserves. 184 PACIFiCORP-20ll IR APPENDIX I - WIN INTGRATION STUDY 2. Data Collection 2.1 Overview The calculation of Operating Reserve demand was based on load and production data over the 2007 to 2009 period (the "Initial Term"). Figue 1 shows that over this period, ten-minute interval data was not available for all wind resources included in the Study. Nonetheless, PacifiCorp chose to use this data because it represented the best base of observed data available within the company, it includes significant concurent load and wind generation data, and it includes year-on-year variability in weather and other variables affecting load and wind generation levels. Figure 1. Raw historical wind production and load data inventory. Plant name Foote Crek Stateline- Combine Hils Leaning Juniper Woli.rine Creek Marengo Goodnoe Hils Marengo II Mountain Wind i Size, MW Timeline Spanish Fork -g Mountain Wind II ~Rollng Hills Glenrock 94 70.2 60.9 19 79.8 99 99 39 99 20 99 28.5 99 111 Glenrock II Sei.n Mile Hill Sei.n Mile Hil II High Plains McFadden Ridge i Three Buttes Dunlap i Rock Rii.r .: =::= :;~:.;:.:::'I * Capacity represents portion of the plant in PacifiCorp's control area. The data inventory summarized in Figue 1 contains as much real, observed, concurent data as possible, owing to the volatile and unpredictable natue of wind generation output as well as the 185 PACIFICORP - 2011 IRP APPENDIX I - WIN INTGRATION STUY many fie variations available in real load data that can be difficult to captue with simulated data. Nonetheless, the data set selected for the Study contains gaps, and as a result, PacifiCorp utilized the services of the Brattle Group, the techncal advisor that assisted with this study, to simulate missing wind data pertining to the Initial Term. The simulation of wind data is discussed at lengt in its own section later in this report. 2.2 Historical Load and Load Forecast Data The histoncalload data for the East and West Balancing Authonty Areas was collected for the Initial Term from the PacifiCorp PI system17. These data were used for all the calculations involving historical load in the Study. The hourly day-ahead load forecasts were gathered from PacifiCorp's load forecast group, as were the day-ahead hourly load forecasts used to set up the generation system through the Initial Term penod. 2.3 Historical Wind Generation and Wind Generation Forecast Data 2.3.1 Overview of the Wind Generation Data Used in the Analysis Ten-minute interval metered wind generation data were available for a subset of the wind sites as summanzed in Figure 1. The wind output data were collected by PacifiCorp at each physical project location using the PI softare system. In addition to histoncal wid generation data, the Study required historical day-ahead wind forecasts, modeled day-ahead wind forecasts for simulated data, and the creation of an ideal wind profie. All of these data sets were needed to establish wind integration costs using PaR and are discussed in tu below. 2.3.2 Historical Wind Generation Data As shown in Figue 2, a cluster of PacifiCorp owned and contracted wind generation plants is located in Pacific Power's service area (PacifiCorp's West Balancing Authonty Area) and another is located in the Rocky Mountain Power service area (PacifiCorp's East Balancing Authority Area). It is worth noting that two wind sites, Wolvenne Creek in Idaho, and Spanish Fork in Utah are part of the East Balancing Authority Area, but are geographically distant from both the western and the eastern clusters. 17 The PI system collects load and generation data and is supplied to PacifiCorp by OSISoft http://W\.\fw.osisoft.com/software-supportwhat-is-pi/what is PI .aspx. 186 PACIFiCORP-20lllR APPENDIX I - WIN INTEGRATION STUY Figure 2. Map ofPacìfiCorp wind generating stations used in this study. The available historical ten-minute wind generation data were examined to produce some initial statistical diagnostics for each site and betweensItes. For each site, Table 4 shows: (l)number of 10-minute interval data observations available, (2) stadard deviation of observed capacity factors, (3) the minimum capacity factor, and (4) the maximum capacity factor. Small negative capacity factor values (that show up as the minimum) in the data are the result of power consumption associated with routine operation of the wind projects even durng times when the project itself is not producing energy. Table 5 shows the correlation observed among aggregate hourly load and wind generation data in 2008. By and large, hourly changes in load and wind generation output, which drive operational planing, do not appear to be correlated. 187 PACIFiCORP~2011 IRP APPENIX I - WIN INTGRATION STUY Table 4. Statistical properties of wind site capacity factor data. Plant Name Number of Observations Standard Deviation Min Max Goodnoe 83,520 32%0%100!6 LeaningJuniper 157,824 35%0%100% Combine Hills 157,824 38%-3%100% Stateline 157,824 24%-1%100!6 Marengo 79,n6 33%-11%100!6 Wolverine Creek 157,824 29%-1%100% Spanish Fork 74,736 29%-4%87% Mountain Wind 66,æ6 29%0%100% Foote Creek 157,824 30%-2%100!6 Seven Mile Hill 52,704 31%0%100!6 McFadden Ridge 11,952 34%-1%100% High Plains 15,840 21%0%67% Glenrock 50,256 29%0%100!6 Table 5. Hourly correlation of system wind and system load. I Overall "Rolling 6 hour I Rolling 12 Hour January -2.5%-2.9%l -3.4% February -2.8%-0.6%1 -1.7% March -0.4%-1.4%1 -2.2% April -6.4%o ~-5.9%-3.5%~ May -10.4%I -6.4%-3.00A) I ~June -12.0%-9.2%1 -11.9% July -12.4%-12.3%1 -14.2% August -9.1%-8.4%~-9.8% September -6.5%~-4.0%-0.6%1 October ~-6.7%-3.5%-4.8%1 ~November -7.5%-3.6%1 -4.4% ¡¡December -2.0%0.3%1 -1.1% 2.3.3 Historical Day-ahead Wind Generation Forecasts Day-ahead wind forecasts were collected from daily historical fies maintained by PacifiCorp commercial operations. The fies contained day-ahead hour-by-hour wind generation forecasts for the wind projects operating durg the Initial Term. For those projects not operating durg the Initial Term, day-ahead forecasts were created using the daily volumetrc day-ahead forecast error from projects having complete data sets. As such, these data were used to bootstrap18 the daily day-ahead forecast volumetrc errors for the 1,372 MW and 1,833 MW scenarios, and the daily error (positive or negative) was applied to simulated wind generation data to create a 18 Bootstrapping is a common statistical rnethod used to estimate data by extrapolatig frorn existing data. 188 P ACIFICORP - 20 11 IRP APPENIX I - WIN INTGRATION STUY modeled day-ahead forecast. The modeled day-ahead forecast maintained the same general hourly shape as the simulated wind generation data but was shifted vertically hour-by-hour on an equal percentage basis to keep the aggregate volumetric error constant. 2.3.4 Ideal Shape Wind Generation In order to isolate wind integration costs from other system costs, a flat production profie is required for PaR modeling. This profie, deemed the ideal wind shape for puroses of the Study, treats all the energy produced by wind projects as monolithic blocks. Comporting with standad trading products among forward energy markets in the Western Interconnect, the energy produced in each l6-hour daily block between hour ending seven and hour ending 22 was treated as a single block. Similarly, energy produced in the 8-hour block between hour ending 23 and hour ending six was treated as a single block. For each block, the total energy delivered from wind generation is averaged, thereby flattening the generation pattern. 2.4 Wind Generation Data Simulation The technical advisor assisted PacifiCorp in developing the Study methodology and in supplementing the historical wind generation data with simulated ten-minute interval wind generation data. This section summarizes the methodology used to simulate wind generation data and provides sample data and graphics to ilustrate the details involved in each step of the process. The overall approach to simulating wind generation data involved taing an historical data inventory; addressing data quality issues in the data inventory; identifying gaps requirng simulation; and finding the best suited relationship between pairs of sites; and using that relationship to approximate the wind output for periods with missing historical observations. However, it is worth noting that for sites with no historical data, the necessary numerical relationships were estimated between relevant locations by using simulated wind data made available by the National Renewable Energy Laboratory (NL). Additional detail on simulation procedures is available in Appendix A. 2.4.1 Categorization of Historical Wind Data to Determine Simulation Scope The historical wind data were classified into three groups to determine the periods requirig simulation for each site. The three categories are defined in tu below, and Figue 3 depicts how each site was categorized. (1) Fully Available-this category refers to sites for which output data are available for the entirety of the Initial Term. Specifically, these wind plants include: Leaning Juniper, Combine Hils, Stateline, Wolverie Creek, and Foote Creek. These plants sum to 425 MW of capacity. (2) Partially Missing-refers to sites for which output data are unavailable for a portion of the Initial Term. The wind plants that fall into this category are: Goodnoe Hils, Seven Mile Hil, Marengo, Spanish Fork, Mountain Wind, McFadden Ridge, High Plains, and Glenrock. One importnt featue of the partally missing data profies is that the missing portions are always chronologically located at the beginning of the time period--nce a 189 PACIFICORP - 2011 IR APPENIX I - WIN INTGRATION STUY partially missing data profile begins, it contains no fuher data "holes". These plants sum to 848 MW of capacity. (3) Completely Missing-refers to wid projects, for which no output data are available for the 2007-2009 Initial Term. Those sites are: Dunlap I, Rock River, Rollng Hils, Three Buttes, and Top of the World. These plants sum to 560 MW of capacity. Figure 3. Categoriation of wid generation data. ií avableata develop by Tecnica Advi 2.4.2 Simulation Process The simulation process used in the Study evolved to become iterative in natue to ensure that simulated wind generation data used to establish operating reserve demand was reasonably aligned to the operating reserve demand calculated using observed wind generation data. As such, different methods of error sampling and simulation techniques (multiple linear, Tobit; for example) were evaluated in this manner. Tables 6 ilustrates an example of how operating reserve demand calculated from observed and simulated data were used to evaluate different error sampling and re-addition methods used in this iterative process for the West Balancing Authority Area. Table 6. Comparison of operating reserve demand calculated from actual wind generation plant data and simulated wind generation plant data estimated using a least squares regression and applying different scaling of errors added back into the raw prediction. Actual Wind Generation Data Load Following Up 15.0 Load Following Down (19.1) Regulation 15.5 Test (Developed Wind Data) Error Scaling (%) Load Following Up10 9.950 10.675 11.7100 12.4 Load Following Down (13.0) (13.9) (14.2) (15.9) Regulation 11.1 12.3 14.3 17.1 190 PACIFiCORP-20ll IR ApPENDIX I - WIN INTEGRATION STUY Several simulation attempts ended with values above the feasible generation capacity range, or values beneath zero. Attempts to add the error term back into the prediction (a necessary simulation step) also faced significant hurdles in developing reasonable results. The highly variable ten-minute output led to error terms with ranges larger than the simulated values in many cases, which would also test the boundaes of either zero or maximum plant capacity delivered. Several processes were attempted to retu a sampled error estimation back to the modeled estimate, per proper regression, including sampling of trcated error distrbutions, medians of the error distributions, and various bins of errors sampled and added back to the regression estimate. Varous combinations of these methods were put through the operating reserve demand estimation calculations to assess whether the results were reasonable. Ultimately, the Tobit simulation method (described in more detail in section A.4.3) and a 3-step smoothed median of the sampled errors proved to offer reasonably stable results. Ultimately, the iterative simulation process produced a simulation methodology comprised of several sequential steps: (1) estimate the Tobit regressions; (2) using the regression coeffcients, generate estimates of the mean output of the predicted variabl/9 (3) calculate the regression residuals; (4) randomly sample the residuals accordig to predefied simulated output ranges; (5) apply a non-linear 3-step median smoother to the sampled residuals; (6) add the smoothed residual series to the predicted mean output. A more detailed description of each step appears in Appendix A, and the resulting regression coeffcients appear in Appendix B. 19 These are generally referred to in the literatue as "y hat" 191 PACIFICORP - 2011 IR APPENIX I - WIN INTGRATION STUY 3. Methodology 3.1 Method Overview This section of the Study presents the approach used to establish the enumeration of operating reserve demand and the method for calculatig wid integration costs. Ten minute interval load and wid data is used to estimate the amount of operating reserve, both up and down, needed to manage fluctuations in load and fluctuations in wind within PacifiCorp's Balancing Authority Areas. The operating reserve discussed here is limited to spinning reserve and non-spining reserve, which are needed for regulation, load following, and contingency reserve services. For puroses of this Study, regulation service refers to the operting reserve required to manage the varabilty of load and wid generation in ten miute. periods, and load following service represents the operating reserve required to manage the variabilty as measured in hourly periods.2o Contingency reserve, although mentioned, is supplied in accordace with the North American Reliability Corporation (NRC) standards and remains unchanged by the wind generation contemplated in this Study. Therefore, the operating reserve quantities discussed herein are only pertnent to supplying the demands of regulation and load following services, which are assessed in for load, and load net wind scenarios. Once the amount of operating reserve is established for different levels of wind penetration, the cost of holding the reserve on PacifiCorp's system is calculated using PaR. In addition to using PaR for evaluating operating reserve cost, the PaR model is used to estiate wind integration cost associated with daily system balancing activities. These system balancing costs result from the unpredictable natue of wind generation on a day-ahead basis and can be characterized as system costs borne from committing generation resources against a forecast of load and wind generation and then dispatching generation resources under actual load and wind conditions. 3.2 Incremental Operating Reserve Demand A dense data set of ten-minute interval wind generation and system load drves the calculation of the marginal reserve requirement in two components: (1) regulation, which is developed using the ten-minute interval data, and (2) load following, which is calculated using the same data but estimated using hourly variability. The approach for calculating incremental operating reserve necessar to supply adequate capacity for regulation and load following at levels required to maintain current control performance was based on merging curent operational practice with a survey of papers on wind integration, as well as advisory from the technical advisor?! The Initial Term load data is used as the baseline case (zero wind generation) in each scenaro. Coincident wind data (as observed, plus that simulated by the technical advisor) were added in increasing levels of wind capacity penetration to gauge. the change in operating reserve demand. For puroses of the Study, the regulation calculation compares observed ten-minute interval load 20 PacifiCorp's definitions for regulation and load following are based on PacifiCorp's operational practice, and not intended to describe the operational practices or termology used by other power suppliers or system operators.2! The external studies PacifiCorp has relied on can mostly be found on the Utility Wind Integration Group (UIG) website at the following lin: htt://www.uwig.orgiopimpactsdocs.htrnl 192 PACIFiCORP-20ll IRP APPENIX I - WIN INTEGRATION STUDY and wind generation production to a ten minute interval estimate, and load following compares observed hourly averages to an average hourly forecast. 3.2.1 Regulation Operating Reserve Service Demand With no sub-hourly clearg or imbalance market, PacifiCorp must plan to meet sub-hourly load (and load net of wind) deviations with its own resources. This includes generating units on automatic generation control (AGC), demand side management (DSM), and the ramping of flexible generation units in real time operation, which requires that existing units be committed and then dispatched to provide operating reserve. Wind variability among ten-minute intervals can represent a quantity of generation required to ramp up or down to maintain system stability. Regulation service demand for wind generation varability was considered first. To parse the ten-minute interval wind variability from the ensuing load following analysis, a persistence forecast of the rollng prior 60 minutes was used to analyze the variation of each ten minute intervaL. The actual wind generation in each ten minute interval was subtracted from the rolling average of the prior six ten-minute intervals, and the standard deviation was computed for each monthly period. This approach follows the one used by the National Renewable Energy Laboratory (NREL) for its recent "Eastern Wind Integration and Transmission Study".22 RegulationwindlOmin = Pcps2 (Windi) Where: PCPS2 = The percentile of a two-tailed distribution equaling the Balancing Authority Area's CPS2 performance23 Windi == the wind forecast error defined as (WindActuallOmin -WindIO-min-forecast) Wind1o-min-forecast = the rollng average of the wind generation in prior six ten-minute intervals, also referred to as a persistence forecast of the rolling prior 60 minutes WindActuallOmin = the observed wind generation for a given ten-minute interval The load variability and uncertainty was analyzed comparng the ten-minute actual load values to a line of intended schedule, which was represented by a line interpolated between an actual top- of-the-hour load value and the next hour's load forecast target at the bottom of that (next) hour. A sample of how the intended schedule compares to actual load data is shown in Figue 4. The method approximately mimics real time operations process for each hour. At the top of the given hour, the actual load is known and a forecast for the next hour was made. For the puroses of this study, a line joining the two points was made to represent the ideal path for the ramp or decline expected within the given hour. The resulting actual ten-minute load values were compared to this straight line so as to produce a strip of error terms, as depicted in Figue 5 with data from February 2009. 22 NREL, Eastern Wind Integration and Transmission Study, prepared by EnerNex Corporation, (Janua 10,2010), p. 143. The report is available for download frorn the following hyperlin: http://\\'\vw.nreL.goy/wind/systemsintegration/pdfs/20 IO/ewits final report.pdf23 The Control Performance 2 is a reliability standad is maintained by the Nort American Electrc Reliability CounciL. A definition is available on page 30f the document at the following hyperlink: http:/lwww.nerc.com/fies/Reliabilitv Standards Complete Set 201OJan25.pdf 193 PACIFiCORP..2011 IR APPENIX I - WIN INGRATION STUDY The errors were assembled monthly and their Regulation demand estimated similarly to the method used for the 10-minute values of the wind data: RegulatioDloadlOmin = P cps2 (Load¡) Where: Load¡ = the load forecast error, calculated similarly to Wind¡ Figure 4. Sample of intended schedule ten-minute load estimate and observed system load. 7000 6000 II....II;:5500IItleu~ 5000 6500 4500 -10 Minute Load Estimate .. .. ..:'';';';Actuã f I.öãêf .. . 4000 tm ¡ II ¡, ¡ ¡¡ ¡, ¡ n i pj ¡ I ¡ ¡¡ I l ¡ ¡¡ ¡ i ¡ Ii 1!!I ¡ ¡! II ¡rTrrrrrl"~m¡ i, ,i ¡ II ¡ ¡ j II ¡ i i ii ¡ i, ,tT,rr ~ ~ ~ ~ ~ ø ~ ~ ~ ~ ~ ~ ~ w ~ w ~ ~ ~ ~ ~ ø ~ .~ ~ w ~ ~ ~ w~ ~ N N m m e e ~ ~ w w ~ ~ 00 00 ~ ~ 0 0 ~ ~ N N m M e e~ ~ M ~ ~ ~ ~ ~ ~ .~ Time 194 P ACIFICORP - 2011 IR APPENIX I - WIN INTGRATION STUY Figure 5. Variabilty between the line of intended schedule and observed load with errors highlighted by green arrows. 6000 . ~ 10 Minute Load Estimate ~ . Actual Load i .. ~.. I~ .II ~n I ..~ "it ¡il, 6400 6300 6200 .. 1i ! 6100 ~ 5900 5800 2:00 2:10 2:20 2:30 2:40 2:50 3:00 3:10 3:20 3:30 3:40 3:50 4:00 Time As the ten-minute load and wind errors each represent unpredictable change in the need for dispatchable generation, their variability was assessed separately and combined. The regulation demand of load net wind generation was estimated assuming short term varations in load are not correlated with changes in aggregate wind generation output though the use of a geometrc average (shown for Regulation Up): ReguiationUP10min = ReguiationLoadUP10min 2 + ReguiationWindUP10min 2 As the need for regulation service can vary whether the wind is up or down, both Regulation Up and Regulation Down services were estimated at each end of the error distributions. A sample of the errors logged for the same period, for load and wind, are shown in Figue 6. The independence of the forecast errors for wind and load was assumed. These errors, or differences between forecast and actual, comprised an estimate of the demand made on regulation service operating reserves durig power system operations. These differences were calculated for every ten minutes of operation through the Initial Term period, and separated into monthly bins for fuer analysis. 195 P ACIFICORP - 2011 IR APPENDIX I - WIN INTGRATION STUY Figure 6. Independent forecast errors in ten-minute interval load and wind generation (December 2008, approximately 890 MW of wind penetration). 150.00 100.00 3: :E 50.00.:0....u. t;IIu 0.00GI.. i2 ¡ I -50.00 i -100.00 Time Analyzing the results on a monthly basis as opposed tò grouping all the calculations together annually allowed for the fact that some months' power service actually required less regulation (for example, July and August) than others, and so costs could be more accurately attbuted with a weighted average of results as opposed to grouping the entire year's operations into a single analysis bin. This is due to operating reserve being employed to manage the tails of the distributions involved, and a single annual bin would apply the greatest tail occurences to the entire year, as opposed to only the month in which it occurs. Figue 7 demonstrates the resulting distributions of regulation demand for wind generation, where regulation down demand is the negative side of the distribution. The vertical lines drawn on Figue 7 ilustrate the operating reserve threshold defined in the Study and data labels are added to denote outlying data points. Similarly, Figue 8 ilustrates the resulting distrbution of regulation demand for load, where regulation up demand is the positive side of the distrbution. 196 PACIFiCORP-20ll IR APPENIX I - WIN INTEGRATION STUY Figure 7. Wind Regulation errors plotted for the Mays of the Initial Term at the 1,372 MW wind capacity penetration leveL. 6000 Operating Resere 5512Theshold 5000 4000 on..C....'ü.:Õ 3000 êi.. E:iz 2000 1000 1 2 3 1 o 448 426 384 342 299 257 215 173 131 100 68 26 -16 -58 -97 -122 -164 -206 -248 -290 -332 -374 Megawatts Figure 8. Load Regulation errors plotted for the Mays of the Initial Term. 10000 9000 8000 7000 oi Operating Reserve..i:6000 .... . Thesld ai'i.¡: .5-50000..ai,. E 4000~z 3000 2000 ,8800., i~'l'~',. 1000 2 1013 1 1 1 1 1 o 22612182202218631703 154 1385 1225 1066 907 747 588 429 269 133 30 -114 -2æ -368 -527 -687 -84 Megawatts 197 P ACIFICORP - 20 11 IR APPENIX I - WIN INTGRATION STUY 3.2.2 Load Following Operatig Reserve Demand PacifiCorp maintains system balance by optiizing its operations to an hourly forecast with . changes in generation and market activity. Ths planning interval represents hourly changes in generation which are assessed within roughly 20 minutes each hour to account for a bottom-of- the-hour (:30 after) scheduling deadline. Taking into account the conditions of the present and the expected load and wind generation, PacifiCorp must schedule generation to meet demands with an expectation of how much higher or lower system load (net of wind generation) may be. PacifiCorp's real-time desk updates the next hour's system load forecast fort minutes prior to each operating hour. This forecast is created by comparng the curent hour load to the load of a similar-load-shaped day. The hour-to-hour change in load from the similar day and hours (the load delta) was applied to the "curent" hour load and the sum is used as the forecast for the ensuing hour. For example, on a given Monday the PacifiCorp operator may be forecasting hour to hour changes in system load by referencing the hour to hour changes on the prior Monday, a similar-load-shaped day. If the hour to hour load change between the prior Monday's like hours was 5%, the operator wil use a 5% change in load as the next hour forecast. As for the corresponding short term operational wind forecast, the hourly wind forecast is done by persistence; applying the instantaneous sample of the wind generation output 20 minutes past the curent hour to the next hour as a forecast and balancing the system to that point. The resulting operational modeling process therefore went as follows; at the top of the hour, wind generation output, dispatchable generation output, and load values were sumarized, and trended using the methods above. The result was compared to the next hour's schedule for gaps as soon as possible, with the generation and load values updated at roughly 20 minutes past the hour. In real time operations, this result would then be balanced through a combination of market transactions and scheduling adjustments to PacifiCorp resources to produce a balanced schedule for the ensuing hour; with all transactions having to be complete by 30 minutes past the hour. Meanwhile, for puroses of the calculation made in this Study, the hourly wind forecast consisted of the 20th minute output from the prior hour, and the load forecast was modeled per the approximation described above with a shaping factor calculated using the day from one week prior, and applying a prior Sunday to shape any NERC holiday schedules. Using the Initial Term data for PacifiCorp's Balancing Authority Areas, a comparson of the load and wind forecasts was implemented to measure the seasonal or annual trends in the variabilty between the hourly interval load and wind forecasts and the observed average hourly load and wind generation values. These differences were segmented into bins by load magnitude and wind generation magnitude using load and wind data, in order to facilitate making a weighted average of the reserves demand by load level and wind generation output leveL. An example of load and wind data segmented into bins appears in Figues 9 through 12. Figue 9 depicts forecast load in West Balancing Authority Area with a range of over and under predictions tied to Control Performance 2 (CPS2) performance leveL. Figue 10 shows the same data for the East Balancing Authority Area. In similar fashion, Figue 11 displays forecasted wind generation in the West Balancing Authority Area with a range of over and under predictions consistent with a 198 PACIFICORP - 2011 IRP APPENDIX I - WIN INTGRATION STUY 97% CPS2 performance leveL. Figue 12 shows the same wind generation forecast data for the East Balancing Authority Area. Figure 9. Example of bin analysis for load following reserve servce from load variabilty in the West Balancing Authority Area (May 2007-2009). 4000 3500 2000 .............. ..u~òííër... ..Forecast Production 3000 ~Under :i'l le500::: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Analysis Bin I i 1500 1000 Figuré 10. Example of bin analysis for load following reserve service from load variabilty in the East Balancing Autbority Area (May 2007-2009). 7S00 , I 7000 1 6S00 6000 ..Over ___ _,___, '"'__"_ ,_,."'''_,~f:Qrt£~S:tlD?-al!£t!Q.n'''_,. _ -w/1PUnder ,'500 iwl;ooo 4500 4000 3500 3000 9 10 11 12 13 14 15 16 17 18 19 20Analyis Bin 199 P ACIFICORP - 2011 IR APPENIX I - WIN INTGRATION STUY Figure 11. Example of bin analysis for load following reserve servce from wind variabilty at the 1,372 MW penetration level for the West Balancing Authority Area (May 2007- 2009). 600 100 --.----~-". '."'-'-'.'.'~-.'~--"_.-- '----.~Ünde¡.-~---------~--~ -~'_.,' -I Forecast Producton 500 400 ~Over.....__~.____~ h__~_h._". . ......, _m.-._...._...._....__..._ ._._. m"", ..,,__. __.""... 300 .'" l.. :E 200 --,-~--~._- a 1234567 8 9WUU"M~~U~UW -ioa Analysis Bin Figure 12. Example of bin analysis for load following reserve servce from wind variabilty at the 1,372 MW penetration level for the East Balancing Authority Area (May 2007-2009). 800 700 ..Under 600 -I Forecast Production ='~Over500 on ¡¡ i&oo.. ~ 300 200 100 a 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Analysis Bin 200 PACIFICORP - 2011 IRP APPENDIX I - WIN INTEGRATION STUY Probabilities implied by the population of each bin, representing the expected amount of time spent in each load state, were represented by the historical data. The percentile equivalent to the historical CPS2 performance of PacifiCorp was sampled above and below the median of each of the bins. The average CPS2 performance for PacifiCorp's East and West Balancing Authority Areas over the period 2004 to 2009 was just below 97%. As the goal of this Study is to incorporate wind integration in PacifiCorp's curent operations, the CPS2 performance of 97% was emphasized in these calculations. An assessment of the overall system power quality is a standalone topic that is beyond the scope of this Study, and thus, the Company assumed this level of reliability wil be maintained. The difference between the CPS2 percentiles and the median of the bins represents the implied incremental load following service for operating reserve demand within that bin. As each respective bin also has an implied probability by the number of data points fallng within it, the volumetrc position over the study period was calculated as a simple weighted average. To fuer explain the calculation method for load following reserve demand, the following example follows from the ilustration in Figue 10. To assess the load following up reserve position for Bin 5, subtract the lower bound value (5,532 MW from the system load forecast of 5,687 MW to arrve at an estimate of 154 MW for the occurences within that bin. Integrating this process through all bins produced a composite load following up position for the East Balancing Authority Area in May, and the process was repeated for each month in the up and down directions. Wind generation was analyzed in exactly the same procedure, but with generation output representing the individual state variable. The wind and load reserve positions were combined using the root sum square calculation in each direction (up and down), assuming their variability in the short term is independent. ReservesLoadFollowing = LoadReserveSioadFoiiowíng 2 + WindReserveSioadFollowing 2 3.3 Determination of Wind Integration Cost 3.3.1 Overview Owing to the varabilty and uncertainty of wind generation, each hour of power system operations featues a need to set aside increased operating reserve (both spinning and non- spinning reserve), in addition to those set aside explicitly to cover load and contingency events which are inerent to the PacifiCorp system with or without wind. Additional costs are incured with daily system balancing practice that is influenced by the unpredictable natue of wind generation on a day-ahead basis. To derive how wind generation affects operating reserve costs and system balancing costs, the Study utilizes the PaR modeL. 201 PACIFICORP - 2011 IR . APPENIX I - WIN INGRATION STUY PacifiCorp's PaR model, developed and licensed by Venty Energy LLC, uses the PROSYM chronological unit commitment and dispatch production cost simulation engine and is confgued with a detailed representation of the PacifiCorp system. For this study, four different PaR simulations were developed for a range of wind penetration scenarios as defined in Table 7. By carefully designing the four simulations, we were able to isolate wind integration costs associated with operating reserves and to separately calculate wind integration costs. associated with system balancing practice. The former reflects integration cost that arises from short-term (within the hour and hour ahead) varabilty in wid generation and the latter reflects integration costs that arse from errors in forecasting load and wid generation on a day-ahead basis. Table 7. Wind penetration scenarios used in PaR, as a percentage of total fleet capacity. The four PaR simulations used for each penetration scenario in the Study are summarized in Table 8. The first two simulations are used to tabulate operating reserve wind integration costs, while the third and forth simulations support the calculation of system balancing wind integration costs. Table 8 identifies how key input variables change among the simulations. The simulations were ru over the 2011 to 2013 forward term (thee years), wherein 2007 wind generation and load data are used as inputs for 2011, 2008 wind generation and load data are used for 2012, and 2009 wid generation and load data ar used for 2013. This calculation method combînes the benefits of using actual system data available for the historic three-year Initial Term period with curent forward price curves pertent to setting the cost for wind integration service on a forward basis.24 PacifiCorp resources used in the simulations are based upon the 2008 IR Update resource portfolio.25 24 The Study uses the March 31, 2010 offcial forward price cure. 25 The 2008 Integrted Resource Update report, fied with the state utilty commssions on March 31, 2010. The report is available for downoad frorn PacifiCorp's IR Web page using the following hyperlin: htt://WV.W.pacificorp.com/content/dam/pacificoæ/doc/Energy Sources/Integrated Resource Plan/2008IRPU pdate! PacifiCorp-2008IRPUpdate 3-31-10.pdf 202 PACIFiCORP-20ll IR APPENDIX I - WIN INTEGRATION STUY Table 8. Wind integration cost simulations in PaR. 1 2011 - 2013 Actual Ideal Shape None None 2 2011 - 2013 Actual Actual Yes None Operating Resere Integrtion Cost = System Cost from PaR simulation 2 less system costs from PaR simulation 1 3 2011 - 2013 Day-ahead Day-ahead Forecast Yes NoneForecast Yes 4 2011 - 2013 Actual Actual Yes (Commtment frorn PaR Simulation 3 System Balancing Integrtion Cost = System Cost from PaR simulation 4 less system costs from PaR simulation 2 3.3.2 Calculating Operating Reserve Wind Integration Costs To assess the effects of various levels of wind capacity added to the Balancing Authority Areas on operating reserve costs, each penetration scenario was simulated in PaR using both ideal (Simulation l) and actual (Simulation 2) wind profies. Both the ideal and actul PaR simulations excluded System Balancing costs. The ideal wind profie is a "flattened" representation of the actual profile, where wind generation is averaged across on- and off-peak blocks. Such a profile requires no additional operating reserve to support wind generation variability, and as such, Simulation 1 only included an operating reserve needed for load variability. In summary, Simulation 1 included actul historical loads, ideal wind profies, and no incremental operating reserve to account for wind varability. Simulation 2 used the actual wind generation profiles, which reflect the 2007 to 2009 observed and developed Initial Term wind data as inputs for the 2011 to 2013 forward period. These actual wind generation profiles reflect the same variability used to derive the incremental operating reserve requirements needed to integrate wind generation. Thus, the second PaR simulation includes the incremental operating reserve demand created by the variable natue of wind generation as well as the actual, varable wind generation profies. The system cost differences between these two simulations were divided by the total volume of wind generation in each penetration scenario to derive the wind integration costs associated with having to hold incremental operating reserve on a per unit of wind production basis. 3.3.3 Calculating System Balancing Wind Integration Costs PacifiCorp conducted another series of PaR simulations to estimate daily system balancing wind integration costs consistent with the wind penetration scenarios studied. In this phase of the analysis, PacifiCorp generation assets were committed consistent with a day-ahead forecast of 203 PACIFiCORP-20ll IR APPENDIX I - WIN INTGRATION STUY wind and load, but dispatched against actual wid and load. To simulate this operational behavior, two additional PaR simulations were necessar for each wid penetration scenario. Simulation 3 was used to determine the unit commitment state of generation assets given the day-ahead forecast of wid generation and load. Simulation 4 used the unit commitment state from Simulation 3, but dispatches units based on actual wind generation and load. This actual wind and load data is pulled from the Initial Ter , and thus, is identical to the actual wind generation and load inputs used to derive operatig reserve wind integration costs as described above. In both of these PaR simulations, the amount of incremental reserve required for each penetration scenaro was applied. The change in system costs between Simulation 4 and the system costs from Simulation 2 already produced in the estimation of operating reserve integration costs isolates the wind integration cost due to system balancing. Dividing the change in system. costs by the volume of wind generation in each penetration scenario produced a system balancing integration costs on a per-unit of wind production basis. 3.3.4 Allocation of Operating Reserve Demand in PaR PaR Simulations 2 through 4 require operating reserve demand inputs that must be applied consistent with the ancilary services strctue native to the modeL. The PaR model distinguishes reserve types by the priority order for unit commitment scheduling, and optimizes them to minimize cost in response to demand changes and the quatity of reserve required on an hour-to- hour basis. The highest-priority reserve tyes are regulation up and re¡ilation down followed in order by spinning, non-spining, and fially, 30-minute non-spining. 6 Reserve requirements in the model need to be allocated into these PaR reserve categories and are expressed as a percentage of load. The regulation up and regulation down reserves in PaR are a tye of spinning reserve that must be met before traditional spinning and non-spining reserve demands are satisfied. The incremental operating reserve demand needed to integrate wind generation was assigned in PaR as regulation up and regulation down. The traditional spining and non-spinning reserve inputs are used for contingency reserve requirements, which remain unchanged among all PaR simulations in the Study. The 30-minute non-spinning reserve is not applicable to PacifiCorp's system, and thus it is not used in this Study. 26 In PaR, spinning reserve is defined as unoaded generation which is synchronized, ready to serve additional dernand and able to reach reserve amount within 10 miutes. Non-spining Resere is defined as unloaded generation which is non-synchronized and able to reach required generation amount within 10 minutes. 204 PACIFiCORP-2011 IR APPENDIX I - WIN INTEGRATION STUY Note that given the hourly granularity in PaR, there is no distinction between operating reserve categorized as regulation and load-following in terms of how the model optimizes their use. Thus both regulation reserve service demand and load following reserve servce demand are combined as a geometrc average and input in PaR as regulation up and regulation down. Furher, owing to the hourly granularty of PaR and the fact that PaR optimizes dispatch for each distinct hour, regulation reserves are effectively released for economic dispatch from one hour to the next. The PaR model requires separate inputs for spining operating reserve and non- spinning operating reserve. Table 9 summarizes how the services for operating reserves are applied in PaR. Table 9. Allocation of operating reserve demand to regulation, spinning and non-spinning reserve categories in PaR. 27 Reserve Service PaR Regulation Up PaR Regulation Down PaR Spinning Reserves PaR Non-5pin Reserves RegulationUP10..n RegulationUp, O"n 0 0 0 RegulationDown,o..n 0 RegulationDown,oMin 0 0 Load Following Up Load Following Up 0 0 0 Load Following Don 0 Load Following Down 0 0 0.5*(5% of Hydro and Wind 0.5*(5% of Hydro and Wind Contingency 0 0 Generation output + 7% of Generation output + 7% of Thennal generation output)Thennal generation output) Tolal Geometric A\Ærage of the abo\Æ Gemetric A\Ærage of the abo\Æ Sum of the abo\Æ Sum of the abo\Æ 3.3.5 Satisfying Reserve Service Demand in PaR PacifiCorp's thermal and hydro units are able to meet the reserve demand entered in PaR as shown in Table 10. Regulation reserve is tyically held by units operating in automatic generation control (AGe) mode. 27 Contingency Reserve is specified by the Nort American Energy Corporation in per http://w"\vw.nerc.com/fiesíBAL-S TD-002-0 .pdf . 205 PACIFiCORP-20ll IR APPENIX I - WIN INTGRATION STUY Table 10. Reserve servce capabilty of each generating unit in PaR. I Unit Name I Regulaton Up IRegulatiOn D~ Non-SpinBEAR RI No No No Yes.CARBN I No No Yes v_-CARBN 2 No No Yes Yes.CHliS Yes YesæOLL 4 I Yes I Yes Yes "CLRWATER I & 2 No No No YesCOLSTRI 3 & 4 No No No '"COPCO I & 2 No No Yes .. iesCRIG I & 2 No No No YesCUNT CR I I'" I . res YesDAVE JOHNSTON I No No . Yes . DAVE JOHNSTON 2 No No -t Yes.. DAVE JOHNSTON 3 No No . DA VEJOHNSTON 4 i YèS Yes YesFISH CR No No NoGADSBY I No No I Yes GADSBY 2 No No Yes GADSBY 3 i i= -_. GADSBY 4 I . · Yes .- YesGADSBY 5 I. Yes Yes YesGADSBY 6 . . I"S YesHAYDEN I & 2 No No NoHEISTON I I . v__ I Yes HEISTON 2 I Yes. I Yes I YesHUER I " Yes I _HU 2 I Yes Yes IHUER 3 I. Yes YesHUINGTON I Yes Yes . HUINGTON 2 ì'''b I Yes -JC BOYL No No JI BRI I i.. Yes . Yes - JI BRI 2 ... Yes Yes JIM BRIGE 3 res Yes - ~ Y""JIM BRI 4 Yes Yes i IAKE SIDE .. . Yes Yes. Yes .IEOW No NoUTTLMOUNAIN No NoMERWIN No No MID-CLUMBIA .: Yes !. NA UGHON I No NA UGHON 2 Yes NAUGHON 3 I YesSWIF Yes TOKESLIE NoWYODAK I . Yes . .YALE I. Yes /. Yes : .., .'1'" . -~:~ - Yes ..Yes + Yes . ,.. Yes:.No -- No No No No I Yès Yes I Yes - Yes I v...No No.,,,_ I . .. . -- "-- . Yes Yes .1 206 PACIFCORP-20ll IR APPENDIX I - WIN INTEGRATION STUY 3.3.6 Modeling gas plant utiization in PaR One of the objectives in calculating wind integration costs using PaR was to emulate observed real-time unit commitment and dispatch behavior of PacifiCorp's thermal plants durng the simulation period. A specific focus was placed on east-side gas plants capable of providing regulation reserve service. The commitment status of these gas plants, consisting of Curant Creek, Lake Side, and Gadsby units 4 through 6, was initially set to "must ru" in PaR to mirror recent utilization of these units. In the PaR framework, must ru status means that the unit is committed, but not ne.cessarily fully dispatched, at all times. PacifiCorp then compared the resulting simulated capacity factors for the simulation year 2013 against actual plant capacity factors for 2009 keeping in mind that 2009 wind generation and load data are used as inputs for the 2013 PaR simulation year. Differences in the capacity factors were reasonably small. Given these findigs, PacifiCorp concluded that PaR was reasonably aligned with actual operational characteristics of the east-side gas plants when setting Curent Creek and Gadsby units 4 through 6 as must run. Consequently, this must ru configuration was applied in PaR to circumvent the fact that PaR establishes unit commitment on price and not necessarily on operating reserve requirements. In this way, and consistent with recent operational practice, the Curent Creek and Gadsby units 4 through 6 are available for meetig operating reserve obligations even when out-of-the-money from a pure market dispatch perspective. The must ru setting on Curant Creek and Gadsby units 4 through six was applied in PaR Simulations 2 through 4. In each of these simulations, incremental operating reserve demand needed to integrate wind is applied in the model, and must..run configuation ensures that the select set of east-side gas units wil be available to meet the added reserve obligation even at times when they are out-of-the-money. In contrast, PaR Simulation 1 does not include any incremental operating reserve demand, and thus, the must-ru setting was not used. 3.3.7 Transmission Topology in PaR PacifiCorp used the PaR transmission topology consistent with the 2008 IRP Update as shown in Figure 13. 207 PACIFICORP - 2011 IR APPENIX I - WIN INTGRATION STUY Figure 13. PaR transmission topology. . iw Load .. Generation ~ PurchaselSale Mark ø= Co n tract/Exhanges .. PaCifiCorpTransn'sson-Owned/FirmR¡~Is"' .... Planned EnergyGatewyTransmissin " 3.3.8 Carbon Dioxide Cost Assumptions in PaR Given the 2011 to 2013 forward term used in the Study, there was no C02 cost applied to fossil- fired thermal generating resources. This assumption simplifies any comparson of the calculated wind integration cost among the thee forward simulation years and avoids the possibilty of disparity between plant dispatch costs and wholesale electrcity market forward prices used over the term. This is in contrast to the 2008 IRP Update, in which PacifiCorp assumed that federal cap and trade carbon dioxide (C02) allowance prices go into effect in 2013, with prices staing at $8.58/ton in 2013 dollars and escalating at 1.8 percent per year thereafter. 208 PACIFiCORP-20ll IRP APPENDIX I - WIN INTGRATION STUY 4. Results 4.1 Operating Reserve Demand Based upon historical and simulated wind generation data and historical load data, the Study shows that operating reserve demand for both regulation reserve service and load following reserve service increases with higher wind penetration levels. Table 11 sumarzes how operating reserve demand for both regulation and load following services increases as wind penetration levels grow from approximately 425 MW to approximately 1,833 MW. Table 11. Annual average operating reserve demand by penetration scenario. Load Only 425MW 1372MW 1833MW Regulation Up 97 105 137 137 West Regulation Down 72 84 120 120 Load Following Up 101 114 139 141 Load Following Down 106 113 132 133 Regulation Up 138 140 201 231 .. Regulation Down 107 110 185 222EastLoad Following Up . 139 144 207 245 Load FollowingDown 144 147 198 237 The increase in operating reserve necessar to support wind generation in grd operations is apparent in each of the penetration scenarios. For example, very little wind generation is added to the East Balancing Authority Area between the load-only and 425 MW scenaros, and understandably, there is little increase in the resultant incremental operating reserve demand. The same situation occurs between the 1,372 MW and 1,833 MW penetration scenaros on the West Balancing Authority Area, where again, there is little change to the calculated operating reserve demand. Additionally, as significant wind generation development impacts the East Balancing Authority Area between the 425 MW and 1,372 MW scenarios, and again between the 1,372 MW and 1,833 MW scenarios, there is clearly a proportionate growth of the operating reserve required to satisfy higher levels of wind penetration. Tabular monthly results for each Balancing Authority Area and for each tye of reserve service appear in Appendix C. For convenience, Figues 14 through 21 summarize monthly operating reserve demand results. In reviewing these figues, it is helpful to compare the growth of estimated reserve demand per MW of wind penetration recognizing that most of the wind capacity in the 425 MW penetration scenario is in the West Balancing Authority Area and that most of the incremental wind capacity in the 1,372 and 1,833 MW penetration scenarios is in the East Balancing Authority Area. 209 PACIFiCORP-20ll IR APPENDIX I - WIN INGRATION STUY Figure 14. Load following up operating reserve servce demand in the West Balancing Authority Area. r 200 180 160 140 120 :: 100:E 80 60 40 20 West Load Following Up 1 2 3 4 5 6 7 8 9 10 11 12 Month -Load -425MW -1372MW -1833MW '\ I Figure 15. Load following down operating reserve service demand in the West Balancing Authority Area. r 200 180 160 140 120 ~ 100 80 60 40 20 i I l,- West Load Following Down 1 2 3 4 5 6 7 8 9 10 11 12 Month -Load -425MW ØfE-1372MW -1833MW L i i i I I) 210 PACIFiCORP-20ll IRP APPENDIX I - WIN INTEGRATION STUY up operating reserve servce demand in the West BalancingFigure 16. Regulation Authority Area. r :: 120~ \,." West Regu lation Up 180 L i I I -1372MW I I -Load -425MW -1833MW I J 160 140 100 80 60 . 1 6 10 11 127892345 Month down operating reserve service demand in the West BalancingFigure 17. Regulation Authority Area. r ::~ West Regulation Down 160 140 120 100 80 60 40 20 -.'\ I i ! -Load -425MW ""~1372MW -1833MW 1 2 3 4 5 6 7 8 9 10 11 12 Month 211 PACIFiCORP-20ll IR APPENIX I - WIN INTGRATION STUY Figure 18. Load following up operating reserve service demand in the East Balancing Authority Area. I East Load Following Up 350 -~-./..-..~~ -.- ~--~ l ¡ -Load -425MW "-~1372MW I-1833MW I I ) 1 2 3 4 5 6 7 8 9 10 11 12 Month Figure 19. Load following down operatig reserve servce demand in the East Balancing Authority Area. f 250 200 3=~150 100 I 50 I 1 2 3 4 5 6 7 Month L East Load Following Down 350 l -Load -425MW 12 I I-1372MW r i I j 300 8 9 10 11 --1833MW 212 PACIFICORP - 2011 IRP APPENDIX I - WIN INTEGRATION STUY up operating reserve service demand in the East Balancing East Regulation Up 350 ì 250 i200 3=-Load I~150 I -425MW 100 -1372MW 50 -1833MW 1 2 3 4 5 6 --8 9 10 11 12 Month Figure 20. Regulation Authority Area. r I" 300 down operating reserve service demand in the East Balancing East Regulation Down 300 12 L I I -1372MW I i J Figure 21. Regulation Authority Area. r Ii 200 I ~ 150 250 100 50 1 2 6 8 9 11 ""Load -425MW -1833MW 10357 Figues 14 through 21 identify both the seasonal natue of the operating reserve required to cover wind integratìon services and the tendency for the services' demand to be increased in months where more wind energy is generated. The monthly variation in operating reserve demand is built into the costing of the services in PaR, considering that the allocation of operating reserve for wind generatìon is less in the months where there is less need. 4 Month 213 PACIFiCORP-20ll IRP APPENIX I - WIN INTGRATION STUY 4.2 Wind Integration Costs Tables 12 and 13 present the wind integration cost results for each wind penetration scenario. Costs are reported in both present value revenue requirement (PVR) dollars and dollars per megawatt-hour of wind generation for each year in the study period. Levelized costs across the three year study term are also included in the far right colum of each scenario table. Table 12. PaR simulation results for the load only scenario and the 425 MW wind penetration scenario. Wi;; I LeyellzedTotl vañable costs 2011 202 203 Base (No Wind) Simulation 1 $1,192,79 $1,311,178 $1,305n Simulation 2 N/A N/A N/A Simulation 3 1.188,90 $1,300,920 1,28,758 Simulation 4 1,201,530 1,322.3n 1,313,055 calculation of Integration Costs Operating Reserve L(Sim 2 less Sim 1)thousands $ System Balancing (Sim4IessSim2¡$$ Total thousands $$$ . Wind Generaion (Acual) East Wind GWh bWest Wind Total GWh Operaing Reserve $/MWh $$$b5ystem Balancing $$$Total Wind Intgraon $/MWh $$$$ . 425MW I Leyellzed201120122013 1,141,308 1,251,695 1,249,391 1.150,552 1.261.783 1,259,733 $1,145,876 1,251.190 1,241,73 1,152,34 1,264,907 l,264,2n 9,244 W,088 10,342 $25,830 $1,79 3,124 4,54 $8,09 $11,04 13,212 14,886 $ 33,924 534 603 520 1,446 754 794 66S 1,937 1,28 1,396 1,18 3,383 $7.8 $7.22 $&73 $7.64 $1.39 $2.24 $3.83 $2.39 $8.57 $9.46 $1256 $10.03 214 P ACIFICORP - 2011 IRP APPENDIX I - WIN INTGRATION STUY Table 13. PaR simulation results for the 1,372 MW and 1,833 MW wind penetration scenarios. Total variable co 1400MW 2011 2012 2013 I Levellzed 17S0MW 2011 2012 2013 i Levelized Base (No Wind) Operatng Reseive System Balancing Total Wind Integration thousands $1,04,895 $1,141,572 $1,148,139 $1,014,831 $1,103,397 $1,112,343 1,075.215 1,172,782 $1,180,728 $1,053,713 $1.145,954 $1,15,n4 1,08,733 1,179,114 $1,176,68 $1,06,86 $1,163,768 $1,163,482 $1.on,117 $1,175,126 $1,18,073 $1,057,08 $1,149,48 $1,162,164 thousands $28,320 $31,210 $32,58 $80,135 38,88 $42,557 $44,431 $109,512 $1,902 2,34 5345 $8,165 3,374 3,530 5,390 $10,60 thousands $30,222 33,554 37,934 $88.30 42,25 46,087 49,821 $120,121 GWh 2,319 2,520 2.232 6,175 3,230 3,483 3,106 8,576 1,462 1,556 1,332 3,805 1,46 1,556 1,332 380 GWh 3,781 4,076 3.564 9,980 4,692 5,04 4,438 12,38 $!MWh $7.49 7.66 $9.14 8.03 $8.29 8.44 $10.01 8.85 $0.5 0.58 $1.50 0.82 $0.72 0.70 $1.21 0.86 $/MWh $7.99 8.23 $1064 8.85 $9.01 9.14 $11.23 9.70 Simulation 1 Simulation 2 Simulation 3 Simulation 4 Calculation of Integraton Coss Operating Reserve (5im 2 less 5im 1) System Balancing ISim 4 less Sim 2) Total Wind Generaon (Actual) East Wind West Wind Total The PaR model results demonstrate interesting trends in the component costs. Most notable is the reduction of system balancing costs for the 1,372 MW and 1,833 MW wind capacity penetration scenarios when compared to the 425 MW wind capacity penetration scenario. This is due to the domination of load forecast error in the 425 MW scenario system balancing integration cost line item, where total system costs are divided by wind energy production to derive system costs on a per unit of wind generation basis. The system balancing costs stabilize as wind generation increases in the higher penetration scenaros. Additionally, the operating reserve integration costs increase with additional wind capacity penetration. The rate of increase in costs is outpacing the increased wind energy produced, resulting in a higher price per megawatt-hour of wind energy produced. Finally, it is noteworthy that the addition of wind generation capacity lowers overall system costs. Table 14 compares the results of the Study to integration costs developed for the 2008 IRP on a component by component basis using Levelized costs over the applicable terms. The primar differences in results are most apparent for inter-hour (2008 IRP)/system balancing (2010 Study) wid integration costs. This difference is explained by improvements in method. In the 2008 IR, market transaction costs were used to estimate inter-hour integration costs, whereas the curent Study calculates system. balancing integration costs derived from the operation of PacifiCorp resources. 215 PACIFICORP - 2011 IR APPENIX I - WIN INTGRATION STUY Table 14. Wind integration cost comparison to the 2008 IRP. Study Wind Capacity Penetration Tenor of Cost 20081RP 2734MW :zYear leve ii zed 2010 Wind Integration Study 1372MW 3-Year levelized 2010 Wind Integration Study 1833MW 3-Year levelized Expected to Day Ahead ($/MWh) Day Ahead to Hour Ahead ($/MWh) System Balancing ($/MWh) Subtotallnterhour / System Balancing $0.28 $2.17 $2.45 $0.82 $0.82 $0.86 $0.86 Intra Hour Reserves1 ($/MWh) 2010 Study Operating Reserves ($/MWh) $7.51 $8.03 $8.85 Total Wind Integration $9.96 $8.5 $9.70 Assumptions Forward Price Curve Oct 2008, $8C02 Mar 2010, No C02 Mar 2010, NoC02 1- IRP resources were available to meet Operating Reserve demand before the in-service year, which lowers wind integration cost 4.3 Application of Wind Integration Costs in the 2011 Integrated Resource Plan The start of portfolio development for PacifiCorp's 2011 IRP is scheduled for September 2010. Portfolio development relies on the Company's capacity expansion optimization model, called System Optimizer. (Note that wind integration impacts are treated as an increased resource cost in the System Optimizer modeL.) The high-end wind capacity penetration scenario wil not be completed until after portfolio development is well underway. Until costs are assessed for the high-end wind capacity penetration scenaro, PacifiCorp wil use the costs developed for the 1,833 MW penetrations scenario, totaling $9.70/M of wind generated power. 216 P ACIFICORP - 2011 IR APPENDIX I - WIN INTEGRATION STUY Simulation of Wind Generation Data A.I Detailed Discussion of Statistical Patterns of the Historical Wind Output Data From the available ten-minute interval historical wind generation data over the 2007 to 2009 Initial Term, there are four key observations. First, wid output has a seasonal pattern. Taking one plant as an example, Figue 1A shows capacity factor data for Leaning Juniper in 2009. The red markers in the figue indicate the median of the distrbution, and the wide bar delineates the 25th to 75th percentiles of the distrbution. Figue 1A shows the median, as well as the range of observed capacity factors in each month in 2009 for Leaning Juniper varies significantly. Second, . the monthly standard deviations for capacity factor output are very different across sites in most months. Figue 2A compares the output patterns across June, July, and August of 2009 for Leaning Junper ~ and Combine Hils and shows that non-normality is evident in. the data. Again, the red markers indicate the median of the distrbution, and the wide bar represents the 25th to 75th percentiles in the distrbution. Third, the commonly-accepted notion that wind output follows a pronounced diural pattern is only partially supported by the various historical profies in the dataset, as apparent in Figue 3A. In general, such recurng patterns are more easily found in average aggregate representations of the data on hourly level, rather than by examining higher resolution ten-minute data. Figure IA. Leaning Juniper 2009 monthly capacity factors. 217 PACIFiCORP-20ll IR APPENDIX I - WIN INTRATION STUY Figure 2A. Comparison of Leaning Juniper and Combine Hils capacity factors. onthly Capacit Factor Output Rang Combine Hils and Leaning Juniper (2009) Figure 3A. Daily generation patterns of several PacifCorp wind plants. 100%....---- leaun . ,,,. mago ".. -- wolver -Monthly Avere 90% 80% 70%.. ~ 60% '"~50%.0= ê' 40%U 30% 20% 10% 0% Actal Capacity Factrs....... glon ....... go .....'Jshfo ......._ g¿, g ~ ÒÌ Finally, Figues 4A and SA present the empircal distrbution of the 2009 capacity factor output of Leaning Juniper and Combine Hils, respectively. Both plants' hourly capacity factor data represent two key patterns to the study. One, that there are a very substantial number of zero generation hours for each station. Two, the output varies greatly though the potential capacity range of each generating station, implying the wid generation wil have the characteristic to vary from one time period to the next. This is different behavior than would be implied by a 218 PACIFiCORP-2011 IRP APPENDIX I - WIN INTEGRA nON STUDY strong bimodal diural pattern, which would imply very regular on/off behavior with and without wind. Figure 4A. Distribution of observed 2009 hourly capacity factors at Leaning Juniper. Figure SA. Distribution of observed 2009 hourly capacity factors at Combine Hils. A.2 Time Pattern of the Historical Wind Data The time-series properties of the wind generation data are also important to the Study. Initial data analysis revealed that the wind generation profies in the dataset were consistently 219 PACIFICORP - 2011 IR APPENIX I - WIN INRATION STUY characterized by a slowly decaying auto correlation process, while their parial autocorrelations are significant up to 6 period lags. In other words, the wind data in a ten-minute period is heavily consistent with the previous 10-mIute interval and, therefore, over time, the wind pattern could be described as influenced by its behavior in the previous time periods. Partial correlatîon measures the autocorrelation at a specific lagged time frame, while controlling for the effect of preceding lags. Paral autocorrelation is useful in deterrining the number of lagged terms to include as explanatory varables in a regression modeL. Figues 6A though 9A show the full and partial auto correlation factors for the Leang Juniper and Combine Hils wind plants. Figues 6A and 7 A show that the predictive power fades regularly over time lag. Figues 8A and 9A show that the oscilating natue of wind generation is more apparent in the negative predictive power of the 2nd and 4th lags. Figure 6A. Autocorrelation coeffcients for successive ten minute lags in capacity factor for Leaning Juniper. 220 PACIFiCORP-20ll IRP APPENIX I - WIN INTEGRATION STUDY Figure 7 A. Autocorrelation coeffcients for successive ten minute lags in capacity factor for Combine Hils. actor Outpu Figure 8A. Partal autocorrelation coeffcients for lags in capacity factor for Leaning Juniper. 221 PACIFICORP - 20 11 IR APPENDIX I - WIN INTGRATION STUY Figure 9 A. Partial autocorrelation coeffcients for lags in capacity factor for Combine Hils. Factor Output(2007 -2009) .. "~..W~~~~~H#"~~~~~~~. A.3 Data Clean-up and Verification The source wind generation data were characteried by a number of issues that needed data clean-up, verification and, in some cases, adjustments. The first observed issue is that for certain records over various periods of time, the historical wind output data were zero. Those observations covered varying lengths of time and, in some instances, up to a few months. However, we noticed that the zero-value data blocks consistently occured only at the beginning of a wind project's chronological energy output data and therefore it is suspected that those were probably periods when the plant had not yet been fully commissioned. Thus, those observations are treated as "missing" and excluded them from the historical data set. Next, through our source data review, we identified that the output of certin plants seemed to have much smaller capacity factors and increased over time. This trend seemed to have extended beyond the natual volatility of wind generation for those wind sites and showed up as a gradual increase over time and reaching a maximum after a number of months. This observation seemed to suggest that the historical data were captung the build-out of a wind site before it has reached its commercial operation date. As the maximum available capability through wind plant constrction on a daily basis was not documented, the decision was made to exclude wind output data for dates prior to the known commercial operation date for each wid site. As a result, the data set used for simulations was limited to include only date ranges that conform to the known commercial operation dates shown in Table lA. 222 P ACIFICORP - 2011 IRP APPENDIX I - WIN INTEGRATION STUY Table lA. Summary of wind plant start dates and nameplate capacity. Plant name Applied Commercial Operation Date Nominal Capacity (MW) Observed Max Output (MW) Dunlap I Goodnoe Hills Glenrock Glenrock III Rolling Hills High Plains McFadden Ridge I Leaning Juniper Marengo I Marengo II Seven Mile Hill I Seven Mile Hill II Combine Hills Wolverine Creek Mountain Wind I Mountain Wind II Three Buttes Top of the World Spanish Fork Foote Creek I Foote Creek II Foote Creek III Foote Creek IV Rock River 11/1/2010 5/31/2008 1/17/200 111 94 237 Data Unavailable 95 232 9/13/2009 99 148 10/10/2009 29 29 9/14/2006 101 103 6/26/2008 211 206 12/31/2008 119 123 6/17/2003 41 41 4/29/2005 65 65 9/29/2008 141 137 12/1/2009 99 Data Unavailable 12/31/2010 202 Data Unavailable 7/31/2008 19 22 4/1/1999 95 137 The sites that were affected by these revisions were: . Goodnoe Hils (observations were set to missing for November 2007 through May 2008), . Marengo (observations were set to missing for Februar 2007 through May 2008), . Spanish Fork (observations were set to missing for April 2008 through Jul 2008), . Mountain Wind (observations were set to missing for April 2008 through September 2008), . Seven Mile Hil (observation were set to missing for November 2008 through December 2008), . McFadden Ridge (observations were set to missing for June 2009 through September 2009), . High Plains (observations were set to missing for February 2009 through August 2009), . Glenrock (observations were set to missing for November 2008 though December 2008). 223 PACIFICORP - 20 11 IR APPENIX I - WIN INTGRATION STUY . That leaves five wind sites that were not affected by this adjustment -Leaning Juniper, Combine Hils, Stateline, Wolverie Creek, and Foote Creek. The second clean-up process involved understading the aggregation of data and the interpretation of the plant size. The data provided to the technical advisor contained single wind output data stream for sites that share the same pricipal name but are distinguished as individual projects--those include Marengo and Marengo II, Mountain Wind and Mountain Wind II, Seven Mile Hil and Seven Mile Hil II, Glenrock and Glenrock III. The wind output data, which were collected on-site, did not distinguish between separate sharng the same name. The third clean-up involved the fact that the maximum output levels observed in the wind output data sometimes exceed the capacity officially available to PacifiCorp. The Study team decided to use the maximum output found in. each wind profie data stream to be the de facto wind site megawatt capacity. We used this capacity level and converted each 10-minute output into a capacity factor value ranging from 0 to 1.28 A.4 Wind Data Simulation Methodology A.4.1 General Description The overall methodology centered on using available data to estimate the missing data. To do so, the statistical relationships between pairs of sites were studied and those relationships were used to derive or estimate the wind output for periods that historical data are incomplete or missing. For example, if there was afully available set of historical data for site A, but partially missing for site B, the overlapping periods durg which historical data are available for both sites A and B were used to estimate the statistical relationship using that data. Then the technical advisor employed that statistical relationship and used the available data from site A for the period when site B has missing data to estimate wind data for that period. If site B has completely missing data, the technical advisor applied NRL's simulated data (from 2004..2007) to establish the statistical relationship between sites A and B and then applied that estimated relationship to the historical data of site A and again, estimated site B' s wind output accordingly. AA.2 Wind Generation Estimation Model Specifcation In general, the modeling approach is based on the use of contemporaneously available ten- minute wind capacity factor data from fully available wind profies to simulate capacity factor data for profies with partially or completely missing wind output. As prior figues demonstrated, ten-minute wind output exhibited a generally volatile profie with several notable featues. First, output from previous periods is highly indicative of the curent level of output, with the partial autocorrelations significant up to as many as six lags. Second, the diural patterns were harder to discern on a consistent basis. Given these characteristics and our preliminary analysis, we chose to include six lagged terms in addition to the concurent wind output term in the model used to estimate the statistical relationship between pairs of sites. We have found that such 28 The capacity factor represents the output at a given point in time as a fraction of the maximum possible output for the wind project. For example, a capacity factor of 0.23 indicates tht curent output is 23% of the total capacity of the wind site. 224 PACIFiCORP-20ll IR APPENDIX I - WIN INTGRATION STUY specification allows us to captue the time-based behavior and time-dependence of the wind data used in the Study. This approach also captues some of the spatial relationship between the two sites-as wind moves from one site to the other, its impact on the other site is delayed in time. The equation below describes the general strctue of the mode¡29: S. A S' B S. B S' B S' B S' B S' B. S't Bitet = ao itet + ai itet_i + ai itet_i + a3 itet_3 + a4 itet_4 + as itet_S + a6 i et-6 + & A.4.3 Wind Generation Estimation Model for Constrained Output An importnt challenge in specifying this model is the natue of the capacity factor varables. Capacity factor is used instead of absolute wind output levels to translate between small and large wind plants. By such a constrction, the wind output measured in capacity factor terms can only take values between 0 and i (or, equivalently 0% and 100%). Attempting to predict a limited dependent variable using a standard linear ordinar least squares (OLS) approach resulted in estimated values for the dependent variable (or sites with partially missing and completely missing historical data) that are outside the possible value range. For example, for given mean values of the explanatory variables, the linear OLS model might result in a predicted mean dependent variable value greater than a capacity factor of 100%. This is due to the fact that a linear OLS model does not limit the outcome range for the dependent variable. In the literatue, a model whose dependent variable is limited at either one or both upper and lower ends of its range is called a "censored" model.3o A standard approach for estimating a censored model is to use the Tobit regression modeL. The Tobit model was originally developed by James Tobin (1958)31 and employs an estimation technique, which recognizes the limited ("censored") range of possible values that the observed dependent variable can take.32 As a result, predicted mean values for the dependent variable wil behave as expected and not exceed the natual capacity limits of 0 and l, as specified in our case. The Tobit model uses a maximum likelihood process, which takes into account the probability of obtaining an observation thàt lies inside the censoring interval. In other words, Tobit tyically is used to estimate the likelihood of a value to be equal to some expected quantity. The model assumes that the tre value of the dependent variable (y*) is explained by a number of independent variables, where the regression error term (epsilon) is normally distributed with a zero mean. In addition, if y* is between 0 and 1 we observe y*, however, if y*o:O we observe 0 and, similarly, ify*::l, we observe 1. The maximum likelihood estimation uses the Erobabilityof each individual observation being censored to estimate the regression coefficients. 3 In other words, the regression coefficients are determined to ensure that their value maximizes the likelihood of obtaining the observed values ofy*.34 29 We specify a regression model that has no constant term. 30 Greene, Wiliam H., "Econometrc Analysis", 5th Ed., Prentice Hall 2003, p. 764. 31 Gujarati, Damodar N., "Basic Econometrcs", McGraw Hil 2003, p. 616; Kenedy, Peter "A Guide to Econornetrcs," 5th Ed., MIT Press 2003, pp. 289-290. 32 Ibid. 33 For example, see "STATA Base Reference Manual Release 11", Stata Corp. pp. 1939-1948; Maddala, G. S., "Limited-Dependent and Qualitative Varables in Econometrcs.", Cambridge University Press 1986, pp.159-162.34 For more detailed description of the Tobit model, please see Maddala, G. S., "Limited-Dependent and Qualitative Varables in Econometrcs", Cambridge University Press 1986, pp.159-162. 225 PACIFICORP - 2011 IR APPENDIX I - WIN INTGRATION STUY In contrast to linear OLS regression, the Tobit regression model does not report an R-squared metrc, which tyically indicates the explanatory power of the regression model specification (with high R-squared value indicating stronger explanatory power). In other words, in the linear OLS regression, the adjusted R-squared measures the proporton of variance of the dependent variable that has been explained by the independent (right-hand-side) varables. There are a range of so-called "Pseudo R-Squaed" metrcs that have been proposed in the literatue for use with maximum likelihood models, such as the Tobit modeL. However, their interpretation is not equivalent to the R-Squared in OLS. This is because estimates derived using a Tobit model are calculated via an iterative process designed to maxime the likelihood of obtaining the observations of the dependent varable, rather than to minimize variance.35 The technical advisor used the statistical softare package STAT A(Ç to perform the regressions using the Tobit modeL. The model specification uses the chosen explanatory variables and generates a censored prediction of y* where the relevant upper and lower censoring limits are taken into account.36 An example of the six-lag model the technical advisor settled upon for significance is below: Goodnoe; = aoLeaningJun iper/ + a¡ LeaningJun ipert~¡ + aiLeaningJun ipert~i + + a3LeaningJun ipert~3 + a4LeaningJun iper'~4 + as LeaningJun ipert~S + a6LeaningJun ipert~6 + & A.4.4 Using NREL's Wind Data to Facilitate Wind Simulation for Sites without Historical Information To simulate wind data of sites with no historical information, the technical advisor used the NREL wind data to estimate the statistical relationship between pairs of sites and then used the estimated relationship to simulate the necessary wind data. For sites with completely missing historical wind data, NRL sites are chosen to serve as a proxy wind profies. NREL's Western Wind Dataset was created by 3TIER for use in NREL's Western Wind and Solar Integration Study. The dataset was synthesized using numerical weather prediction (NP) models "to recreate the historical weather for the western U.S. for 2004, 2005, and 2006. The modeled data were temporally sampled every i 0 minutes and spatially sampled every arc-minute (approximately 2 kilometers).'.3 We refer to this wind data set as the "NREL data". The first step in using the NREL Western Wind Dataset is to identify NREL-modeled sites that are the closest in geographical terms to the relevant PacifiCorp wind sites. These are called the "NRL proxies" for each corresponding PacifiCorp wind site. The technical advisor then estimated the statistical relationship between the pairs of NREL proxies (that correspond to PacifiCorp wind sites) and used the statistical relationship to carr out the rest of the simulation 35 For rnore information, please see: Long, 1. Scott. "Regression Models for Categorical and Limted Dependent Varables" Thousand Oak: Sage Publications, 1997; Freese, Jererny and 1. Scott Long. "Regression Models for Categorical Dependent Varables Using Stata", College Station: Stata Press, 2006.36 For more infonnation, please see: Baum, Chrstopher F., "An Introduction to Modem Econometrcs Using Stata", College Station: Stata Press, 2006, p. 264.37 http://vv'\vw.lUeLgov/wínd/integrationrlatasets/westernmethodologv;html#methodology (accessed July 1,2010) 226 PACIFiCORP-20ll IR APPENDIX I - WIN INTEGRATION STUDY described above. PacifiCorp staff provided the technical advisor with the geographical coordinates (latitude and longitude) for the PacifiCorp wid sites as sumarized in Table 2A. In addition, the NREL data contains comprehensive information on the geographical coordinates of all modeled sites.38 The technical advisor then determined the closest NREL proxy for each ofplant.39 Table 2A. NREL Proxies selected for pertnent PacifCorp plants. PacifiCorp Plant Name Closest NRL Site il Distance (kI) High Plains McFadden Rock River Rollng Hils Dunlap Three Buttes Top of the World 16676 0.516676 0.531422 0.423909 2.919280 0.823870 5.323803 4.8 Table 2A shows each PacifiCorp-NREL pair and the calculated distance between them. We should note that High Plains and McFadden Ridge share the same geographical location and, as a result, are paired with the same NREL-modeled site. As a result, High Plains and McFadden Ridge have identical simulated profies. (This is a fuction of the study's approach of simulating wind generation output based on geographical location rather than wind project name~for example, the same simulated profile is also used to represent the Mountain WindIountain Wind II pair of wind sites.) After determining the set of NREL sites to be used in the simulation analysis, NREL data were formatted, compiled by site, and labeled using their PacifiCorp counterpart's name. Similar to the earlier approach in formatting the PacifiCorp data, NREL wind output data were converted into capacity factor terms (using a 30 MW capacity value for each site as specified in the NRL description of the dataset).4o 38 The rnain web portal for the NRL Western Wind Dataset can be accessed at http://wind.nrel.goviWeb nrel 39 Geographical coordinates for two points on the earh's surface can be converted to a straight-line distance using a range of alternative algoriths, which take into consideration the shape of the eart and use trgonornetrc formulas to project and rneasure surface distances. For the puroses of this study, the Spherical Law of Cosines was used to calculate the distance between each relevant PacifiCorp wind site and every site in the Western Wind Dataset. Fore rnore information, please see: Weisstein, Eric W. "Spherical Trigonometr." From MathWorld -- A Wolfram Web Resource. litt:l/mathworld.wolfram.com/SphericalTrigonoinetrv.litmJ (accessed July 1, 2010) Distace (kI) == ArcCos( Sin(Latitude Pacificorp) * Sin(Latitude NRL) + Cos(Latitude Pacificorp) * Cos(Latitude NRL) * Cos(Longitude NRL - Longitude Pacificorp)) * 6371 kI 40 http://www.nreL.gov/windlintegrationdatasets/about.html (accessed July 1,2010) 227 PACIFICORP - 2011 IR APPENDIX I .. WIN INTEGRA nON STUY A.4.5 Pairing of Wind Profiles Usedfor Regression Recognizing the monthly seasonality of wid data, each modeled pair required twelve separate regression models per year, one for each month.41 To ensure the use of observed historical wind data is meaningful, we require that a full year of overlap between a fully available wind profie and a partially missing wind profile. This means that if the partially missing wind profile only had 11 months of historical data, it was treated as a completely missing dataset and used the NREL data to help simulate the data from the period without historical data. To simplify the rest of this explanation, the fully available wind profile was a predictor and a site with partially missing or completely missing wid profile was a predicted site (because the process effectively used the available profie to "predict" the missing profie). The Study focused on two methods in estiatig monthy regressions. First, for sites with partially missing historical wid data that have at least 12 months of historical data, the data from afully available site was employed as the predictor (such as Foote Creek, Combine Hils, or Leaning Juniper) to estimate monthly coeffcients. From the coefficients derived in the regression estimation, the Study estimated the wind data for all the missing months. Second, for sites with partially missing data (and with less than 12 months historical data available) and sites with completely missing data, the NRL closest neighbor set of wind profies was employed. The process estimated monthly regression models between the closest NREL site to the predictor and the closest NRL site to the predicted. Then the coefficients estimated in those regressions were applied to the PacifiCorp fully available predictor data to simulate 1O~minute output data for the predicted. This second approach implicitly assumed that the monthly relationships between the predictor and the predicted derived from the 2004-2006 period (using available NRL data) were applicable to the Initial Term as represented by the PacifiCorp data. Below in Figue lOA, a flow char depicts the steps described above. Table 3A depicts the pairs of wind sites with left colum containing the predictor and the right column containing the predicted. 41 For example, if overlapping data for the predictor and the predicted are available for all of2008 and 2009, we estimate a regression for January using data for that month from both 2008 and 2009. Then, the estimated coeffcients from the regression wil be used to predict the output for January of2007 using the predictor 2007 data for that rnonth. 228 PACIFICORP - 2011 IR APPENDIX I - WIN INTGRATION STUY Figure lOA. Wind generation data development flow chart. Methods of Wind Data Simulation Method B: Sit wih Completely Missing Data (or less than 12 montbs historical data)Method A: Site with PartaUy Missing Data (with at leat 12 months bitorica data) Table 3A. Pairs of wind projects used in data simulation. Predicted Data UsedPredictor High Plains McFadden Rock River Rolling Hils Dunap Three Buttes Top of the World Goodnoe Marengo Mountain Wind Seven Mile Hil Spanish Fork Glenrock Foote Creek Foote Creek Foote Creek Foote Creek Foote Creek Foote Creek Foote Creek Leaning Juniper Combine Hils Foote Creek Foote Creek Foote Creek Foote Creek NRLlPacifiCorp NRELlPacifiCorp NRL/PacifiCorp NRLlPacifiCorp NRLlPacifiCorp NRLlPacifiCorp NRLlPacifiCorp PacifiCorp PacifiCorp PacifiCorp PacifiCorp PacifiCorp PacifiCorp 229 P ACIFICORP - 2011 IR APPENIX I - WIN INRATION STUY A.4.6 Regression Analysis The estimation process of the Tobit regressions was identical across all sites-the six-lag model is applied to a predictor-predicted pair. After estimation, the resulting coefficients were used to generate data for the predicted profie for all missing time periods using the values of the predictor in those time periods.42 A sample of resulting regression coeffcients for one month for one pair of wind sites is shown in Table 4A below. Table 4A. Predictive capacity factor coeffcients for the simulation of Goodnoe Hils wind generation using Leaning Juniper actual generation data. Explanatory Varables Estimated Coeffcients Capacity Factor Leang Juniper 0.841 *** (0.0744) -0.321** (0.130) 0.0314 (0.135) 0.0631 (0.135) 0.0597 (0.135) 0.00342 (0.130) 0.267*** (0.0744) Capacity Factor Leaning Junper (t-l) Capacity Factor Leaning Junper (t-2) Capacity Factor Leaning Junper (t-3) Capacity Factor Leang Junper (t-4) Capacity Factor Leanig Junper (t-5) Capacity Factor Leaning Juniper (t-6) Observations 4,464 Not~: Stadad errors in parentheses. *** p-CO.Ol, ** p-c0.05, * p-CO.1 A.4. 7 Esnmate Mean Values of the Predicted In general, using the estimated regression coefficients to derive a prediction for the dependent varable is done by using the mean values of the explanatory variables to arrve at the predicted mean value of the dependent variable. In this case, however, we are interested in generating predicted values of the dependent variable (predicted) for all individually observed values of the independent varable (predictor). As a result, applying the estimated regression coefficients to each individual observation of the explanatory varables wil result in predìcted values of the predicted that are significantly less variable than the tre unobserved predicted series. This is due to the fact that the regression model assumes that the regression error is zero on average across the observations, but not in every individual instance. An ilustrative comparison of the predicted mean value to the historical actual of the same period is shown in Figue llA. 42 Again, all estimation procedures and simulations were conducted using the cornercially- available statistical softare package STATA(Ç (http://www.stata.com) 230 l: P ACIFICORP - 2011 IR APPENIX I - WIN INTEGRATION STUY Figure llA. Comparison of actual Goodnoe Hils capacity factors with predicted mean Goodnoe Hils capacity factors derived off of Leaning Juniper generation data. --~Goodne Acal .. . Goodnoe TOBIT 100% 90% 80% 70%i.=..r.600/0=~ È 50% r.=Q.40%=U 30% 20% 10% 0%N =GO..=...;0:.;..'"'"'"======N ~~õ'"~~~.- Actu and Prdicted Capaci F)ictors \C ..N =GO.-N ..=...;.;.;0:.; '"....'"'"=CO '"=======~==~!:=.~~..-~==~~.-~~.-.-.-.- A.4.8 Calculating the Regression Residuals To address the loss of variability by simply using the regression coefficients in the estimation, the technical advisor subtracted the predicted values of the dependent variable from their corresponding observed values over the overlapping subset of predicted/predictor data used for the regression estimation.43 This produced a set of regression residuals, which represent the amount by which predicted values for the known (historical) part of the data set were different from the actual observed values of the predicted. Then, each regression residual value was categorized according to the level of predicted output it was originally associated with. The predicted values are then grouped in bins of 10 percentage points to create 10 bins that cover the range of 0% to 100% capacity factor output. For example, all residuals that were associated with a predicted output between 10% and 20% are grouped together. As Figues 12A and 13A show, the distributions of those residuals var across bins. 43 In the case of the PacifiCorp sourced data, this is done over the rnonthly regression data. For the Hybrid approach where NRL data was required, this is done with the NRL data. 231 PACIFiCORP-20ll IRP APPENDIX I - WIN INRATION STUY Figure 12A. Highly non-normal residuals from bin 5 of the March regression of Goodnoe Hils capacity factor derived from observed Leaning Juniper data. bution of Regression Residuals Bin#S Goodnoe Predict by leaning Juniper (Marc Regresion) Figure 13A. Highly non-normal residuals from bin 7 of the March regression of Goodnoe Hills capacity factor derived from observed Leaning Juniper data. Residuals Bin Juniper (Marc Regr A.4.9 Sample of Residuals According to Simulated Output Ranges The next step involved randomly drawing residuals from the previously defined bins and "adding them back" to the simulated mean lO-minute wid output. The procedure of making random 232 PACIFiCORl., 2011 IR APPENDIX I - WIN INTEGRATION STUDY draws from an empircal distrbution of residuals is called "bootstrapping" residuals.44 In the context of this study, the technical advisor applied the bootstrapping procedure by randomly drawing 45 a residual from a corresponding bin and adding it to the predicted mean capacity factor value. For example, if a predicted capacity factor value for a missing data point falls within the i 0% to 20% interval, a residual value wil be randomly drawn from the bin that contains the residuals of the corresponding capacity factor of the historical data when compared with the simulated (or predicted) mean values. A.4.10 Application of a Non-Linear 3-Step Median Smoother to the Sampled Residuals After generating a time-series of bootstrapped residuals, the additional step of applying a non- linear smoother to the series, called the "span-3 median smoother" was taen. The span-3 median smoother is a process by which the median of the curent, previous, and next period value - in this case, it is calculated by takig the median of residual(t-l), residual(t), residual( t+ i )46 - and using that median as the residual for the current period. The purose of this approach is two-fold. Firstly, the median smoother ensures that the time-series of residuals resembles the time behavior of wind more closely, with lags affecting the instantaneous results. Secondly, the span-3 median smoother introduces a time-dependency to the data set, which is known to exist in the original wind data.47 The technical advisor then added the smoothed time-series of the randomly drawn residuals to the predicted mean capacity factor values for each ten-minute point; then checking the resulting data to make sure the estimates remained within the 0 ~ i 00%. capacity factor range. 44 This name alludes to the fact that, absent prior knowledge of the distrbution, the researcher has to pull herself by the bootstraps by drawing randomly frorn the empircally-derived residual data in order to generate residuals.45 Random drws are done with replacernent as irnplernented by the STATA(Ç bsample procedure. 46 For exarnple, see "STATA Base Reference Manual Release 11", Stata Corp. p. 1758; Mosteller, F. and Tukey, John W., "Data Analysis and Regression: A Second Course in Statistics", Addison-Wesley: 1977., pp. 52-58. 47 Although the non-linear srnoothing approach does not exactly replicate the auto~regressive behavior of the wind data, it introduces sorne similar dependency. 233 PACIFiCORP-2011 IR APPENDIX I - WIN INGRATION STUY Regression Coefficients and Relative Signifcance Regression Results by Month for Glenrock Predicted by Foo Creek Capacity Factor Foote Creek It) Capacity Factor Foote Crek (t-I) Capacity Factor Foote Crek It-2) Capacity Factor Foote Creek (t-3) Capacity Factor Foote Crek (t-4) Capacity Factor Foote Creek It-5) Capacity Factor Foote Crek It-6) Number of Observations Note: Standar errs in parentheses. u* p-CO.OI, ** p"'.05, * p"'.l Regression Results by Month for Spash Fork Preccte by Foo Creek lanatory Varbles Capacity Factor Foote Creek (t) Capacity Factor Foote Creek (t- i) Capacity Factor Foote Crek (t-2) Capacity Factor Foote Crek (t-3) Capacity Factor Foote Creek(t-4) Capacity Factor Foote Creek (t-5) Capacity Factor Foote Creek (t-6) Number of Observations Note: Standard errs in parentheses. *** p"'.Oi, ** p"'.05, * p-cO.i 234 P ACIFICORP - 20 11 IRP APPENDIX I - WIN INTEGRATION STUY Regression Res nits by Month for Se\en Mle mil Predcted by Foo Creek laato Vanables Capacity FactOr Foote Creek (t) Capacity Factor Foote Creek (t-J) Capacity Factor Foote Crek (t-2) Capacity Factor Foote Crk (t-3) Capacity Factor Foote Creek (t-4) Capacity Factor Foote Crek (t-5) Capacity Factor Foote Crek (t-6) Number of Observations Note: Standard errrs in parntheses. ... p"'.Oi, .. p"',05, · p"'O.1 Regression Res nits by Month for Monntain Wind Predicted by Fooe Creek Capacity Factor Foote Crek (t) Capacity Factor Foote Creek (t-J) Capacity Factor Foote Creek (t-2) Capacity Factor Foote Creek (t-3) Capacity Factor Foote Creek (t-4) Capacity Factor Foote Crek (t-5) Capacìty Factor Foote Creek (t-6) Numer of Observations Note: Standar errors in parentheses. ... p"'.Oi, .. p"'O..05, · p"'O.i 235 P ACIFICORP - 2011 IRP APPENDIX I - WIN INTGRATION STUY Regression Res u1ts by Minth for Maengo Predicted by Combne HiDs Ianato Variables Capacity Factor Coniine Hi (t) Capacity Factor Coniine Hi. (t-I) Capacit Factor Coniine Hi (t-2) Capacit Factor Coniine Hi (t-3) Capacity Factor Coniine Hi (t-4) Capacity Factor Coniine Hi (t-5J Capacit Factor Coniine Hi (t-6 NunierofObservations Note: Standar errs in parntheses. *** p4l.01. ** p4l.05. * p""O.1 Regress ion Res u1ts by Month for Gooe Predicted by Leanng J nnper Capacity Factor Leaning Juniper (t) Capacity Factor Leaning Juniper (t-I) Capacity Factor Leaning Juniper (t-2) Capacity Factor Leaning Juniper (t-3) Capacity Factor Leaning Juniper (t-4) Capacity Factor Leaning Juniper (t-5) Capacity Factor Leaning Juniper (t-6) Number of Observations Note: Standar errrs in parntheses. *** p""O.OI, ** p4l.05, * p4l.! 236 PACIFiCORP-201l IR APPENDIX I - WIN INTEGRATION STUDY Regression Results by.Month for Top of th World Predcted by Foote Creek Capacit Factor Foote Creek (t) Capacity Factor Foote Crek (t- i) Capacity Factor Foote Crek (t-2) Capacity Factor Foote Crek (t-3) Capacity Factor Foote Creek (t-4) Capacit Factor Foote Creek (t-5) Capacity Factor Foote Crek (t-6) Number of Observations Note: Standard erors in parntheses. ... p"Ü.Ol, .. p"Ü.05, . p"Ü.I Regression Results by Month for Three Butts Predcted by Foo Creek Capacity Factor Foote Creek (t) Capacity Factor Foote Creek (t-I) Capacity Factor Foote Crek (t-2) Capacity Factor Foote Crek (t-3) Capacity Factor Foote Crek (t-4) Capacity Factor Foote Crek (t-5) Capacity Factor Foote Crek (t-6 Numer of Observations Note: Standard errrs in parentheses. ... p"Ü.OI, .. p"Ü.05, . p"Ü.I 237 PACIFICORP - 2011 IR APPENDIX I - WIN INTGRATION STUY Reression Resolts by Mitl fur Duap Predcted by Fooe Creek Ianato Varbles Capacit Factor Foote Crek (t) Capacit Factor Foote Crek (t-1) Capacit Factor Foote Crek (t-2) Capacit Factor Foote Crek (t-3) Capacit Factor Foote Crek (t-4) Capacit Factor Foote Crek (t-5) Capacity Factor Foote Creek (t-6) Number of Observations Note: Standaid errrs in parntheses. ... p""O.OI... p4l.05,. p""O.1 Regression Results by Montl for Rollng Hills Predcted by Foote Creek laato Varbles Capacity Factor Foote Crek (t) Capacity Factor Foote Crek (t-IJ Capacity Factor Foote Crek (t-2) Capacity Factor Foote Creek (t-3) Capacity Factor Foote Crek (t-4) Capacity Factor Foote Crek (t-5) Capacity Factor Foote Crek (t-6) Number of Obserations Note: Standaid errrs in parntheses. ... p4l.01, .. p4l.05, . p4l. I 238 PACIFICORP - 2011 IR APPENIX I - WIN INTEGRATION STUY Regression Resnlts by Month for Rock rowr Predcted by Foote Creek Capacity Factor Foote Crek (t) Capacit Factor Foote Crek (t-IJ Capacity Factor Foote Crek (t-2) Capacity Factor Foote Crek (t-3) Capacity Factor Foote Creek (t-4) Capacity Faetor Foote Crek (t-5) Capacity Factor Foote Crek (t-6) Nutler orObservations Note: Standard errrs in parentheses. ... p"l.Ol. .. p"l.05, . p"O.\ Regression Resnlts by Month for McFadn Predicted by Foo Creek EJlaatory Varbles Capacity Factor Foote Crek (t) Capacity Factor Foote Crek (t-l) Capacity Factor Foote Crek (t-2) Capacity Factor Foote Crek (t-3) Capacity Factor Foote Crk (t-4) Capacity Factor Foote Crek (t-5) Capacity Factor Foote Crek (t-6) Nutler of Observations Note: Standard errrs in parentheses. ... p"l.OI, .. p"O.05, . p"l.\ 239 PACIFICORP - 20 11 IRP APPENIX I - WIN INGRA nON STUDY Regression Results by Month for Higb Plains Predicted by Foo Creek Capacit Factor Foote Crek (t) Capacity Factor Foote Crek (t-I) Capacity Factor Foote Creek (t-2) Capacity Factor Foote Crk (t-3) Capacity Factor Foote Crek (t-4) Capacity Factor Foote Crek (t-5) Capacity Factor Foote Crek (t-6) Number of Obseivations Note: Standar errrs in parntheses. ... p",O.OI, .. p.q.05, · p.q.i 240 PACIFCORP-20ll IRP APPENIX I - WIN INTEGRATION STUDY Operating Reserve Demand Seasonal Detail This Appendix presents the monthly component operating reserve service demand calculated for the PacifiCorp East and West Balancing Authority Areas in the Study. The 1,372 MW and 1,833 MW penetration scenarios include some simulated wind data; the load-only and 425 MW penetration scenarios do not. Table Cl.West Balancin~ Authority Area, Load 0 Load Following Regulationll.Q :Y Down January 127 129 125 82 February 93 103 111 73 March 114 115 109 77 April 84 87 103 65 May 93 101 95 72 June 82 83 78 63 July 93 96 69 64 August 79 84 65 60 September 96 104 88 64 October 83 83 98 62 November 149 166 127 95 December 125 116 101 86 nly Table C2.West Balancin2 Authority Area, 425 Load Following Regulation~Down :Y Down January 132 134 131 91 February 104 110 117 82 March 128 124 118 92 April 96 96 110 78 May 108 109 102 84 June 103 96 88 80 July 110 105 78 79 August 98 94 76 77 September 105 107 94 73 October 97 88 104 74 November 157 169 133 103 December 132 121 106 94 MW 241 PACIFICORP - 2011 IR APPENIX I - WIN INTEGRATION STUY Table C3. West Balancin2 Authority area, 1,372 load Following Regulation yg Down ~.Q January 153 150 171 139 February 122 122 152 129 March 160 152 152 140 April 133 122 150 121 May 135 131 136 123 June 131 123 127 118 July 128 122 110 104 August 118 113 103 104 September 125 121 118 101 October 124 105 126 104 November 181 180 152 131 December 159 138 142 131 MW Table C4. West Balancin2 Authority area, 1,833 load Following Regulation yg Down ~Down January 153 150 171 139 February 124 124 152 129 March 162 154 152 140 April 136 123 150 121 May 137 133 136 123 June 133 125 127 118 July 129 123 110 104 August 120 115 103 104 September 126 122 118 101 October 125 106 126 104 November 182 180 152 131 December 161 139 142 131 MW 242 PACIFiCORP-20ll1R APPENDIX I - WIN INTEGRATION STUY c nlyTable5. East Balancin~ Authority area, Load 0 Load Following Regulation ~Down ~Down January 127 131 150 110 February 117 122 131 98 March 135 138 122 102 April 105 103 145 95 May 146 145 133 114 June 143 152 134 114 July 157 155 130 112 August 162 162 122 111 September 144 162 127 105 October 139 146 116 97 November 154 164 161 110 December 145 149 182 112 Table C6. East Balancin2: Authority Area, 425 Load Following Regulation~Down ~Down January 132 135 152 113 February 120 125 134 101 March 139 142 124 105 April 112 107 148 99 May 151 148 137 118 June 148 155 137 118 July 161 157 132 115 August 165 164 124 114 September 149 165 130 109 October 143 150 119 101 November 158 168 163 113 December 150 154 185 116 MW 243 PACIFiCORP-2011 IRP APPENIX I - WIN INTGRATION STUDY Table C7. East Balancine Authority Area, 1,372 Load Following Regulation .I Down .I ~ January 187 193 201 175 February 201 195 210 189 March 212 2æ 207 200 April 193 174 212 182 May 204 184 183 179 June 205 192 189 185 July 205 177 170 172 August 204 187 164 166 September 219 203 185 177 October 218 211 202 192 November 230 227 232 197 December 212 228 253 207 MW TableC8. East Balancine Authority area, 1,833 Load Following Regulation .I Down .I Down January 240 262 250 241 February 256 262 264 247 March 247 247 235 236 April 236 213 243 223 May 228 205 203 202 June 232 210 204 202 July 220 185 177 183 August 216 197 176 179 September 245 222 201 199 October 257 251 235 230 November 276 290 279 259 December 291 299 300 266 MW 244 PACIFICORP - 2011 IR APPENDIX J - STOCHASTIC Loss OF LOAD STUY ApPENDIX J - STOCHASTIC Loss OF LOAD STUDY PacifiCorp evaluates the desired level of capacity planning reserves for each integrated resource plan. For the 2011 IRP, the Company conducted a stochastic loss of load study to help identify the taget capacity planning reserve margin (PRM) to use for resource portfolio development. This study utilized the Company's stochastic production cost simulation system, Planing and Risk (PaR), to determine the relationship between PRM and resource adequacy as measured by Loss of Load Probability (LOLP) index. Loss of load probability represents the probability that generation in a given hour is insufficient to serve load. Accumulating the number of hours for which the system experiences unserved load over a given period, tyically one year, yields the LOLP index. Once the relationship between LOLP and PRM is established for PacifiCorp's system, a target LOLP level is selected to determine the PRM for subsequent resource portfolio development. This report. describes the loss of load study and modeling assumptions, the selection of a target loss of load criterion, and the (ldoption of a PRM for portfolio development. The last comprehensive stochastic study conducted was for PacifiCorp's 2004 IRP.48 Major differences between this study and the last one include (1) significantly more wind resources and incorporation of incremental wind operating reserves in the resource portfolio simulations, (2) expansion of the transmission topology from two bubbles to 26, and (3) incorporation of energy efficiency programs as a resource with a reserve credit rather than a reduction to the load forecast. Note that while this study reports the incremental resource cost for achieving a given loss of load frequency and associated reserve margin level using a standard reliability resource tye, it does not assess the trade-off between reliabilty and cost or the optimal resource mix to achieve a given reliability leveL. PacifiCorp compares different resource portfolios based on the amount and cost of unserved load (megawatt-hours of "Energy Not Served" or ENS) resulting from stochastic simulations of many portfolios built to meet a given PRM leveL. This stochastic analysis reveals the reliabilty impacts and costs associated with different resource mixes. The metrc used to derive the LOLP index is Loss of Load Hours (LOLH). The PaR model records a LOLH event when load is not met for an hour. This condition results from unit outages that reduce available generation capacity in a load area below the load derived from the Monte Carlo draws conducted by the PaR modeL. The LOLH event also has an associated Energy Not Served value, which is the magnitude of the lost load for the hour. 48 See Appendix N of the 2004 IRP Technical Appendix Volume. 245 PACIFICORP - 2011 IRP APPENDIX J - STOCHASTIC Loss OF LOAD STUY The PaR model's reported LOLP index is the average number of LOLH events for PacifiCorp's 100-iterationMonte Carlo production cost simulation. This measure is thus a likelihood of experiencing a shortfall in any given hour for the stochastic Monte Carlo simulation.49 PacifiCorp selected 2014 as the simulation test year for the LOLP study. This year aligns with the start of the 2014-2016 resource acquisition period targeted by the Company's All Source RFP issued to the market on December 2, 16 2009. This year also aligns with major planned Energy Gateway transmission additions: the Mona-Oquirh segment of Energy Gateway Central by June 2013, and the Sigud-Red Butte segment by June 2014. The LOLP modeling approach entailed adding incremental reliability resource capacity to a starting point resource portfolio to reach increasingly higher target PRM levels. Loads and resources reflect those of the September 21, 2010 preliminar caJgacity load & resource balance, as presented at the October 5, 2010 IRP public input meeting. 0 This balance uses the annual system coincident peak load forecast prepared in September 2010 for use in the Company's 2011 business plan. The starting PRM level was 8.3 percent, which covers system operating reserve requirements (contingency and regulating reserves). Reliability resource capacity was then added to reach planning reserve margin levels of approximately 10 percent, 12 percent, 15 percent, and 18 percent. PacifiCorp conducted stochastic Monte Carlo simulations for each of the five resource portfolios built to achieve the taget PRMs. The stochastic simulations account for Western Electrcity Coordinating Council (WECC) operating reserve obligations plus incremental operating reserves for existing and forecasted wind additions as of year-end 2013. PacifiCorp then extracted LOLH and associated LOLP statistics from the portfolio simulations to characterize the reliabilty impacts of the incremental reliability resource capacity. PacifiCorp used an intercooled aeroderivative simple-cycle combustion tubine (IC aero SCCT) as the reliability resource for the loss of load study. Starting from a portfolio with approximately a zero PRM, IC aero SCCT capacity blocks were added to PacifiCorp's East and West Balancing Authority Areas-PacifiCorp East (PACE) and PacifiCorp West (PACW)-until reaching the desired PRM. The capacity build-up includes 77 MW of non-owned reserves held for other paries located in PacifiCorp's Balancing Authority Areas, and accounts for the treatment of dispatchable load control (Class 1 DSM), interrptible load contracts, and purchases in the 49 Calculating a probability using LOLH is a variant of the Loss of Load Expectation (LOLE) statistic. 50 The prelirninar 2011 IRP capacity load and resource balance is reported on page 45 of the meetig presentation, which can be downloaded at: htt://\\'Ww.pacificorp.comlcontent! dampacificorp/ doc/Energy Sources/lntegrated Resource Plan/20 11 IRP lPacifi Corp 20 i lIRP PIM4 1O-05-10.pdf 246 PACIFICORP - 2011 IR APPENDIX J - STOCHASTIC Loss OF LOAD STUY calculation of the reserve margin (See Chapter 5 for more details). Additionally, since the capacity balance uses a load forecast before energy effciency (Class 2 DSM) load reductions are applied (the "pre-DSM" load forecast), PacifiCorp included a reserve credit for the incremental 307 MW of Class 2 DSM capacity added by 2014. Modeled SCCT units were sized as follows by Balancing Authority Area: . PacifiCorp East Units - 93 MW (1 unit), 186 MW (2 Units), 279 MW (3 Units) . PacifiCorp West Units - 102 MW (1 unit), 205 MW (2 Units), 307 MW (3 Units) Regarding resource placement, PacifiCorp added SCCT capacity to transmission areas as dictated by PRM needs, with most resources placed in the West Main ("West Units") and Utah North ("East Units") transmission areas. Table 1.1 shows the megawatt capacity added to reach the taget PRM levels. Since capacity is added in blocks, the resulting PRM levels vary from the original target levels. Table J.1 - Resource Capacity Additions Needed to Reach PRM Target Levels East 3 Unit 837 1,116 1,116East 2 Unit 186 0 186East 1 Unit 0 0 0Goshen 186 186 186West 3 Unit 0 0 307West 2 Unit 0 205 0West 1 Unit 102 0 0Walla Walla 102 102 102 Total IC Aero SCCT Ca aci 1,413 1,609 1,897 DSM with Reserve Credit 332 338 344Total Ca aci Added* 1,745 1,947 2,241 * Excludes non-owned reserves held for other paries within PacifiCorp's servce terrtory. 1,395 o 93 186 307 o 102 102 2,185 353 2,539 1,674 o o 186 307 o 205 102 2,474 362 2,836 Figue 1.1 shows the relative magnitude of existing resources, the load obligation plus sales, and resources with incremental reserves required to reach the taget PRM. 247 P ACIFICORP - 2011 IR APPENDIX J - STOCHASTIC Loss OF LOAD STUY Figure J.t - Existing Resources, Loads & Sales, and Resources with Reserve Requirements 16,000 15,500 15,000 14,500 14,000 13.500 ~ 13,000 ~ 12,500m 12,000 gi 11,500 :i 11,00010,500 10,000 9,500 9,000 8,500 8,000 ..............._.........__._........._........-.............-.. ~r#/#//~~#~#//#ÆWÆfAØff#Æ'Æ'._...~__ 8.3%10.2%12.8%15.5%18.3% ~ Requirement with Planning Reserves ..Loads and Sales ..-Existing Resources For the loss of load study, the PaR model is configued to conduct 100 Monte Carlo simulation rus. Durng model execution, PaR makes tie-path-dependent Monte Carlo draws for each stochastic variable. The stochastic varables include regional loads, unit outages, hydro availabilty, commodity natual gas prices, and wholesale electrcity prices. In the case of natual gas prices, electrcity prices, and regional loads, PaR applies Monte Carlo draws on a daily basis. Figues 2 through 9 show. a sample of first-of-month daily loads by transmission area resulting from the Monte Carlo draws. In the case of hydroelectrc generation, Monte Carlo draws are applied on a weekly basis. ' Twelve representative weeks for each month, including the July system peak week, were modeled on an hourly b(lsis. This representative-week approach reduces the model ru-time requirements while ensurg that unit dispatch durg the critical capacity planning periods is captued in the system simulations. Since only one year was simulated, the stochastic model's long-term stochastic parameters were tued off. 248 P ACIFICORP - 2011 IRP APPENDIX J - STOCHASTIC Loss OF LOAD STUY Figure J.2 - Utah North Load Area Figure J.3 - Utah South Load Area Figure J.4 - Walla Walla, Washington Load Area 249 P ACIFICORP - 2011 IR APPENDIX J - STOCHASTIC Loss OF LOAD STUY Figure J.5 - West Main (Oregon, Northern Caliornia) Load Area Figure J.6 - Yakima Load Area Figure J.7 - Goshen Idaho Load Area 250 PACIFICORP - 2011 IR APPENDIX J - STOCHASTIC Loss OF LOAD STUY Figure J.8 - Northeast Wyoming Load Area Figure J.9 - Southwest Wyoming Load Area As par of the WECC, PacifiCorp is currently required to maintain at least 5 percent and 7 percent operating reserve margins on hydro and thermal load-serving resources, respectively. The Northwest Power Pool (NP) also requires a 5 percent operating reserve margin on wind. In the PaR model, operating reserves are modeled as a fuction of load. The maximum reserve amount that each generating unit can car is specified in the modeL. The PaR model also includes 1.6 percent ofloads to cover the WECCregulating reserves requirements. The operating reserve percentages, exclusive of wind, equate to 8.6 percent for the East Balancing Area and 8.1 percent for the West Balancing Area. These operating reserves are split into, roughly, 60-percent spining and 40-percent non-spining reserves to comply with WECC spinning and non- spining reserve requirements.51 An additional 14 percent incremental operating reserve 51 At least half of the operating reserves must be Spinning Reserve. Spining reserve is the margin of generating capacity available to replace 10st capacity and provide the regulatig rnargin to follow load; spining capacity rnust 251 PACIFICORP - 2011 IRP APPENDIX J - STOCHASTIC Loss OF LOAD STUY requirement is applied against nameplate wind capacity (211 MW to cover incremental operating reserves for wind as determned by PacifiCorp's 2010 wind integration study. The operating reserve modeling approach does not address the impact of resource tye (i.e., hydro, wind, or thermal) in determining required operating reserves. Operating reserves count toward the PRM, but the required percentages for the Balancing Authority Areas (8.6 percent and 8.1 percent) stay constant regardless of resource mix. All Balancing Authorities with the Nortwest Power Pool are also required to paricipate in the Contingency Reserve Sharg Progr. This progrm provides 60-minute recovery assistance following the loss of a generatig resource or transmission path, or failure of a generating unit to start up or increase output. This assistance is provided after the Balancing Authority uses up its Contingency Reserve Obligation (i.e., 7 percent ofload served by thermal resources; 5 percent of load served by hydro reserves). The reserve sharing program provides a benefit to the utility by coverig the first hour of an outage. For recording LOLH and calculating LOLP, the stochastic simulation. should omit the first hour of a forced outage event in order to captue reserve sharing benefits. Implementing this fuctionality in the PaR model requires that a "shadow" station be assigned to each unit with a capacity equal to the unit MW rating and energy equal to the full load output. The shadow station is called upon in the event of a unit outage, thereby contrbuting emergency generation for one hour durg the outage period. (The PaR model would determine that hour based on the marginal energy cost durg the outage period.) This modeling approach was judged to be too complex to implement and validate in time for use in the 2011 IRP. However, this approach was implemented for a loss of load study conducted by the PaR model vendor, Venty LLC, for Public Service Company of Colorado. The impact to the PRM of modeling reserve sharing rules of the Rocky Mountain Reserve Group (RMRG) was a reduction of 1.5 percentage pointS.52 While the RMRG reserve sharing rules provide for up to two hours of contingency reserve assistace as opposed to the one hour for the Northwest Power Pool's program, the RMG rules are more restrctive in other respects. For example, reserve support is targeted for units at least 200 MW in size, is provided only to the unit with the largest capacity in the event that two or more units experience simultaneous outages,. covers only one outage event per month, and covers less than the full unit capacity due to a smaller pool of member reserves available. Given these offsetting limitations, PacifiCorp assumes that a PRM reduction of 1.5 percentage points is a reasonable proxy for the NWP's reserve sharng benefit. Figue l10 reports the LOLH counts for the five PRM levels modeled, while Figue J.11 reports the resulting LOLE index values (the stochastic average for the 100 Monte Carlo iterations). be synchronized to the system and ready to provide power instantaeously. Non-spining reserve is generating capacity that is not synchronized to the system but can be available within a few hours - although some capacity may be ready imediately. 52 The 10ss of load report is available at: http:/í"'i\'v'W.xceJenergy.comlSiteCoJ JectionDocuments/ docs/CRPReserveMarginS tudy.pdf 252 PACIFICORP - 2011 IRP APPENDIX J - STOCHASTIC Loss OF LOAD STUY Fitted cures highlight the smooth relationship between the reliability statistics and the PRM leveL. Figure J.12 reports the total fixed cost of meeting each PRM level based on the incremental IC aero SCCT resource capacity required. The per-unit fixed cost is approximately $191/kW-year, which is grossed up to account for a 2.7 percent expected forced outage rate. Each percentage point increase in the PRM translates into an incremental fixed cost of about $42 milion. Figure J.I0 - System LOLH by Planning Reserve Margin Level 2014l0lH 20 5 15 , I :i ¡ 510.. o o 5 10 15 20 Reserve Margin (%) Figure J.lt - System LOLP Index by Planning Reserve Margin Level Loss of Load Probability 4.0000 3.5000 ------- 3.0000 _ 2.5000~;: 2.0000 5 1.5000.. 1.0000 0.5000 0.0000 o 5 10 15 20 Reserve Margin (%) 253 P ACIFICORP - 2011 IRP APPENDIX J - STOCHASTIC Loss OF LOAD STUY Figure J.12 - Reliabilty Resource Fixed Costs Associated with Meeting PRM Levels -$450,000..;.00 $400,0000~ c 'Q $350,000....:: GI $300,000:-..GIVIGIii $250,000bIc'ii..GI $200,000..u .=..$150,000.2 VI'I0 $100,000u .~...!$50,000:i E:iu $0 00 I-I-I- W 0 .... *'iv 00 :. *'*'w *' I-vi in *' I-00w*' Planning Reserve Margin Traditionally, the long-term reliabilty planning standard has been a one-day in ten year loss of load criterion: 24 hours I (8760 hours x 10 years) = 0.027 percent. PacifiCorp has thus adopted this standad for determination of its PRM for IRP portfolio development.53 Using a logarithmic fuctional form and regressing the PRM levels against the LOLE values, yielded a PRM of 14.8 percent to achieve a one-day in ten year loss ofload (Figue J.13). 53 Reliance on a one-in-ten loss of load criterion is being bolstered at the Federal leveL. The Federal Energy Regulatory Commission issued a Notice of Proposed Ru1emaking in October 2010 approving a regional resource adequacy standard for ReliabilityFirstCorporation (RFC) based on a one-in-ten loss ofload criterion. RFC is one of the nine Nort American Electrc Reliability Corporation's electrcity reliability councils, consisting of the former Mid-Atlantic Area Council (MAAC), the East Central Area Coordination Agreernent (ECAR), and the Mid- American Interconnected Network (MA. 254 P ACIFICORP - 2011 IR APPENDIX J - STOCHASTIC Loss OF LOAD STUY Figure J.13 - Relationship between Reserve Margin and LOLP 20 18 16 c: 14'ii~ 12 Q, 10 t= s: 8 ~ 6 4 2 o "~ . v = -1.086In(x) + 10.92 R2 = 0.9821 . - ,,,, 0.00 0.20 0.40 0.60 0.80 LOLP (%) 1.00 1.20 1.40 1.60 As noted previously, the loss of load study does not incorporate the benefit of the Northwest Power Pool reserve sharing program. As a result, the 14.8 percent PRM requires a downward adjustment. Applying the 1.5 percent RMRG reserve sharing impact estimated by Venty for Public Service Company of Colorado results in an adjusted PRM of 13.3 percent. Rounding to 13 percent yields the PRM that PacifiCorp selected for its 2011 IR portfolio development. Based on the loss of load study and an out-of-model planning reserve margin adjustment to reflect reliability benefits from the Northwest Power Pool's reserve sharig program, PacifiCorp selected a 13% PRM for 2011 IRP portfolio development. PacifiCorp's previous PRM was 12 percent. This study incorporated a one-year snapshot of the transmission topology and loads & resources situation, targeting 2014 as the representative study year. Since the study focused on the PRM needed to meet firm load and sales obligations, it did not incorporate the reliability benefits of accessing off-system generation with non-firm transmission capacity. PacifiCorp evaluated the reliabilty impact of different resource mixes using LOLP and Energy Not Served measures as par of its portfolio evaluation process. 255 PACIFICORP - 2011 IRP APPENDIX K - HYDROELECTRIC CAPACITY ACCOUNTING ApPENDIX K - HYDROELECTRIC CAPACITY ACCOUNTING The Utah Commission, in its 2008 IRPacknowledgment order, directed the Company to revisit its approach for estimating the capacity contrbution of hydroelectrc facilities for load & resource balance development puroses. Both the Utah Division of Public Utilities and Office of Consumer Services specifically recommended in their written comments on the 2008 IRP that the Company continue to investigate the hydro capacity accounting methodology adopted for regional resource adequacy reporting puroses by the Pacific Northwest Resource Adequacy Forum, an organization sponsored by the Nortwest Power and Conservation Council (NWPCC). This accounting methodology extends the one-hour sustained peaking period to the six highest load hours over three consecutive days of highest demand. The methodology was originally adopted in 2008, and continues to be investigated and refined. In this appendix, the Company first describes what hydro facilities are eligible for providing sustained hydro peaking capability under an 18-hour standard, and then reports its estimates of the 18-hour sustained hydro capability for the eligible facilities. The Company then discusses the applicability of this standard to PacifiCorp's hydroelectrc system. PacifiCorp evaluated its hydro resource portfolio according to the definitions and methodologies outlined by the curent standards established by the Pacific Northwest Resource Adequacy Forum. The following PacifiCorp hydroelectrc facilities apply with regard to supporting sustained capacity for the Nortwest: Lewis River . Swift-I . Swift-2 . Yale Other hydro facilties owned and operated by PacifiCorp that provide limited peaking . JC Boyle . Copco-I . Copco-2 . Lemolo-I . Lemolo- 2 . Toketee . Slide Creek . Oneida 257 P ACIFICORP - 2011 IR APPENDIX K - HYDROELECTRC CAPACITY ACCOUNTIG . Cutler This second group of hydro facilities was determned to be ineligible for providing sustained peaking capability as defined by the Pacific Nortwest Resource Adequacy Foru. For example, they lack sufficient storage for sustained peakig and are constrained in their dispatch by minimal inflow during the peak load period (July), have ramping regulations imposed within the operating license, restrctive minimum flow regulation and stage change downstream of the project, irrgation priority, and fisheries/recreation requirements. Only the Lewis River facilities listed above (Swift-I, Swift-2, and Yale) meet the criteria for providing 18-hour sustained peaking capabilty without extraordinar actions taken regarding adaptive policy decisions or waivers by the various governing agencies and priar staeholders of the project output. Sustained Hydro Peaking Capabilty for Lewis River Facilties Durng the July peak load period, the Swift and Yale reservoirs are maintained near full pool elevation in support of recreation. Historical median flow into the Swift reservoir in July is 1245- cubic feet per second (cfs). The median natual accretion between Swift and Yale reservoirs is 198 cfs. The median natual accretion between Yale and Merwin reservoirs is 198 cfs. Minimum flow below the re-regulating facility downstream of Swift and Yale, varies durng the month of July from 2,300 cfs in the fist ten days, 1900 cfs in the second ten days, and 1,500 cfs in the last ten days of the month. From July 31st to mid October, the minimum flow is 1,200 cfs. In a median water year, Swift and Yale reservoirs operate in the upper eight feet of the reservoir 100 percent of the time in July. Over a 15-year consecutive period, Swift and Yale reservoirs operate in the upper eight feet of the reservoir 93 percent of the time in July. In the upper eight feet of the reservoirs, Swift 1 and 2 and Yale are capable of 344 MW and 134 MW, respectively. The maximum sustained peak capacity for Swift 1 and 2 combined is 210 MW. At Yale, the maximum sustained peak capacity is 95 megawatts. The total combined sustained peak capacity is therefore 304 MW. The difference between the one-hour sustained peaking capacity and 18- hour sustained peaking capacity is a reduction of 164 MW as indicated in Table Table K.l - Peaking Capabilty Comparison for Lewis River Hydro Facilties Swift 1 and 2 Yale TOTAL 319 150 469 210 95 305 (l09) (55) (164) These estimates were determined assuming the critical event occurs in the first ten days of July when the minimum stream flow requirement is the highest. Given the median inflows and assuming the same 18-hour sustained peakig period, the available peak flow for Swift 1 and 2 is 5,000 cfs, whereas the peak flow for Yale is 5,800 cfs. The above stated sustained capacity pertains to these peak period flows. Under peak operation, reservoir levels remain approximately constant as normally required to support recreation. 258 PACIFiCORP-20ll IR APPENDIX K - HYDROELECTRIC CAPACITY ACCOUNTING The Pacific Northwest Resource Adequacy Forum's 18-hour sustained peaking period stadard is intended as a broad regional capacity planning guideline. The issue is whether it makes sense to adopt for PacifiCorp based on its hydro licensing provisions and operational protocols and practices. In practice, the Company would not adhere to reservoir level compliance or constat stream flow regulation below Merwin if there was an emergency need for generation to support critical load. In a real world situation, PacifiCorp would generate to maximum capacity of the units and make the necessary public announcements unless instrcted to provide the sustained capacity per a revised peaking period definition enforced by. the Western Electric Coordinating Councilor Northwest Power Pool. The Company has the ability to operate outside the normal boundaries of the operating license given emergency conditions, which means that the 18-hour sustained peaking stadard would hot be relevant for peak capacity planning as it relates to PacifiCorp's hydro system. Additionally, the choice of the length of the sustained peaking period has minimal consequences for capacity position reporting given that the sustained peaking period must be consistently applied to both hydro capacity and peak loads. It is also importnt to note that the NWPC characterizes the Resource Adequacy Forum's capacity adequacy stadard as being useful for informing hydro utilities' resource planning efforts, and not as a methodology that should be adopted in lieu of the utilties' own planning criteria and methodologies. 259 PACIFiCORP..2011 IRP APPENIX L - PLANT WATER CONSUMTION ApPENDIX L - PLANT WATER CONSUMPTION The information provide in this appendix is for PacifiCorp owned plants. Total water consumption and generation includes all owners for jointly-owned facilities 261 PA C I F i C O R P - 2 0 l l I R P Ap P E N D I X L - P L A N T W A T E R C O N S U M P T I O N Ta b l e L . l - P l a n t W a t e r C o n s u m p t i o n w i t h A c r e - F e e t P e r Y e a r Ac r e - F e e t P e r Y e a r Ca r b o n Ye s No 2, 3 8 0 2, 1 9 9 2, 3 4 9 2, 1 9 3 2, 2 8 0 1, 3 3 9 , 3 4 3 1, 2 0 4 , 9 8 2 1, 2 1 1 , 8 7 5 1, 2 9 6 , 0 0 4 58 8 9.8 1 Ch e h a l i * Ye s Ye s - 1, 7 4 7 , 2 5 2 1,2 8 8 , 2 5 6 - 0.0 1 Le r o Cu r a n t C r e e k * Di s c h a r g e Do e s n o t a p p l y 11 6 82 10 8 83 97 3, 6 0 5 , 0 7 1 2, 7 9 9 , 5 8 5 2, 4 6 4 , 4 6 3 2, 5 3 6 , 6 6 0 1 i . 0. 2 Da v e J o l m t o n Ye s No 7, 8 7 2 7, 7 4 6 6, 9 8 3 6, 6 0 4 7, 3 0 1 5, 6 9 6 , 8 6 0 5, 6 3 8 , 8 0 6 5, 0 1 7 , 7 9 6 4, 6 9 9 , 7 6 7 45 2 7. 5 Ga d s b y * * Ye s No 77 8 42 6 68 0 89 3 69 4 63 3 , 0 4 9 48 2 , 5 9 6 60 5 , 8 1 7 35 9 , 4 0 4 43 5 7. 2 Ze r o Hu n Di c h a r g e Do e s n o t a p p l y 19 , 1 5 7 19 , 3 8 0 19 , 3 0 0 19 , 2 0 0 19 , 2 5 9 9, 6 0 0 , 2 9 5 10 , 2 4 6 , 9 6 5 9, 4 3 8 , 6 8 3 8, 7 8 5 , 8 2 7 65 9 11 . 0 Le r o Hw i i n n Di s c h a r g e Do e s n o t a p p l y 11 , 7 3 7 11 , 3 8 5 10 , 9 2 2 9, 5 6 6 10 , 9 0 3 7, 1 2 7 , 0 8 4 7, 1 4 8 , 8 5 0 6, 7 5 3 , 7 6 4 6, 1 0 7 , 3 7 9 52 4 8. 7 Le r o Jim Br i g e r Di s c h a r g e Do e s n o t a p p l y 25 , 6 1 6 27 , 3 2 2 25 , 3 6 1 24 , 0 7 6 25 , 5 9 4 15 , 1 1 9 , 3 7 9 15 , 3 0 3 , 5 0 8 15 , 1 8 8 , 1 8 4 14 , 8 2 8 , 9 0 6 55 2 9. 2 La k e s i d e * * * Ye s Ye s 0 1, 8 2 1 1, 2 8 7 1,5 3 3 1,1 6 0 0 2, 8 6 1 , 7 2 2 2, 0 9 9 , 1 0 9 2, 5 3 7 , 0 4 6 20 2 3. 4 Na w m t o n Ye s No 9, 9 4 8 10 , 9 9 2 10 , 8 4 6 0 7, 9 4 7 5, 2 1 0 , 6 1 8 5, 1 1 4 , 4 0 9 4, 7 5 2 , 6 3 2 5, 3 3 9 , 6 0 3 68 7 11 . 4 * E q u i p e d w i t a i r c o o l e d c o n d e n s e r ** M i o f bo t h r a i n e s t e a m u n a n d p e a k i n g a s t u b i n e s * * * F i r t f u y e a r o f w a t e r c o n s m n t i o n o c c l l e d i n 2 0 0 8 1 a c r e - f o o t o f wa t e r i s e q u i v a l e n t t o : 3 2 5 , 8 5 1 G a l l o n s o r 4 3 , 5 6 0 C u b i c F e e t 26 2 P ACIFICORP - 2011 IR APPENDIX L - PLAN WATER CONSUMTION Table L.2 - Plant Water Consumption by State Hunter Huntin ton Carbon Curant Creek Lakeside Gadsb 19,157 11,737 2,380 116 19,380 11,385 2,199 82 1,821 426 19,300 10,922 2,349 108 1,287 680 Percent of total water consumption = 43.7% 2008 10,992 27,322 446 7746 2009 10,846 25,361 365 6,983 Percent of total water consumption = 56.3% Table L.3 - Plant Water Consumption by Fuel Type Hunter 19,157 19,380 19,300 1320 14.6 HuntIn on 11,737 11,385 10,922 895 12.7 Carbon 2,380 2,199 2,349 175 13.2 Nau hton 9,948 10,992 10,846 700 15.1 Jim Brid er 25,616 27,322 25,361 2120 12.3 W odak 405 446 365 335 1.2 Dave Johnston 7,872 7746 6983 762 9.9 Percent of total water consumption = 97.8% 263 Ei II . P ACIFICORP - 2011 IR APPENIX L - PLAN WATER CONSUMION Percent of total water consumption = 2.2% Table LA - Plant Water Consumption for Plants Located in the Upper Colorado River Basin 19,157 11,737 2,380 9,948 25,616 19,380 11,385 2,199 10,992 27,322 19,300 10,922 2,349 10,846 25,361 Percent of total water consumption = 87.8% 264