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20170404PacifiCorp 2017 IRP - Volume II.pdf
Volume II - Appendices April 4, 2017 2017 INTEGRATED RESOURCE PLAN This 2017 Integrated Resource Plan Report is based upon the best available information at the time of preparation. The IRP action plan will be implemented as described herein, but is subject to change as new information becomes available or as circumstances change. It is PacifiCorp’s intention to revisit and refresh the IRP action plan no less frequently than annually. Any refreshed IRP action plan will be submitted to the State Commissions for their information. For more information, contact: PacifiCorp IRP Resource Planning 825 N.E. Multnomah, Suite 600 Portland, Oregon 97232 (503) 813-5245 irp@pacificorp.com http://www.pacificorp.com This report is printed on recycled paper Cover Photos (Top to Bottom): Wind Turbine: Marengo Wind Project Solar: Pavant Solar Plant Transmission: Sigurd to Red Butte Transmission Line Demand-Side Management: Smart thermostat Pacific Power wattsmart Business Customer Meeting Thermal-Gas: Blundell Geothermal Plant PACIFICORP – 2017 IRP TABLE OF CONTENTS i TABLE OF CONTENTS TABLE OF CONTENTS ………………………………………………….….………….……..….. i INDEX OF TABLES ………..…………………………………………….….………………..….. vi INDEX OF FIGURES ….………………………………………………….….………………..….. x APPENDIX A – LOAD FORECAST DETAILS ……………………………….……………….. 1 INTRODUCTION ................................................................................................................................ 1 SUMMARY LOAD FORECAST ........................................................................................................... 1 LOAD FORECAST ASSUMPTIONS ...................................................................................................... 3 REGIONAL ECONOMY BY JURISDICTION .......................................................................................... 3 UTAH ............................................................................................................................................ 5 OREGON ....................................................................................................................................... 6 WYOMING ..................................................................................................................................... 7 WASHINGTON ................................................................................................................................ 7 IDAHO .......................................................................................................................................... 8 CALIFORNIA .................................................................................................................................. 8 WEATHER ........................................................................................................................................ 9 STATISTICALLY ADJUSTED END-USE (SAE) .................................................................................. 10 INDIVIDUAL CUSTOMER FORECAST .............................................................................................. 11 ACTUAL LOAD DATA ................................................................................................................... 11 SYSTEM LOSSES ........................................................................................................................... 13 FORECAST METHODOLOGY OVERVIEW ......................................................................................... 13 CLASS 2 DEMAND-SIDE MANAGEMENT (DSM) RESOURCES IN THE LOAD FORECAST ..................... 13 MODELING OVERVIEW ................................................................................................................. 13 SALES FORECAST AT THE CUSTOMER METER ................................................................................ 14 RESIDENTIAL ............................................................................................................................... 15 COMMERCIAL .............................................................................................................................. 15 INDUSTRIAL ................................................................................................................................ 15 STATE SUMMARIES ........................................................................................................................ 16 OREGON ..................................................................................................................................... 16 WASHINGTON .............................................................................................................................. 16 CALIFORNIA ................................................................................................................................ 17 UTAH .......................................................................................................................................... 17 IDAHO ........................................................................................................................................ 18 WYOMING ................................................................................................................................... 18 ALTERNATIVE LOAD FORECAST SCENARIOS.................................................................................. 18 APPENDIX B – IRP REGULATORY COMPLIANCE …………………………….………… 21 INTRODUCTION .............................................................................................................................. 21 GENERAL COMPLIANCE ................................................................................................................. 21 CALIFORNIA ................................................................................................................................ 22 IDAHO ........................................................................................................................................ 23 OREGON ..................................................................................................................................... 23 PACIFICORP – 2017 IRP TABLE OF CONTENTS ii UTAH .......................................................................................................................................... 23 WASHINGTON .............................................................................................................................. 23 WYOMING ................................................................................................................................... 24 APPENDIX C – PUBLIC INPUT PROCESS …………………………….………………..…... 57 PARTICIPANT LIST ......................................................................................................................... 57 COMMISSIONS ............................................................................................................................. 57 STAKEHOLDERS AND INDUSTRY EXPERTS ..................................................................................... 58 PUBLIC INPUT MEETINGS ............................................................................................................... 59 GENERAL MEETINGS ................................................................................................................... 59 June 21, 2016 – General Public Meeting ........................................................................................................... 59 July 20, 2016 – General Public Meeting ............................................................................................................ 59 August 25-26, 2016 – General Public Meeting .................................................................................................. 59 September 22-23, 2016 – General Public Meeting ............................................................................................ 59 November 17, 2016 – General Public Meeting .................................................................................................. 60 January 26-27, 2017 – General Public Meeting ................................................................................................. 60 March 2-3, 2017 – General Public Meeting ....................................................................................................... 60 STATE MEETINGS ........................................................................................................................ 60 June 6, 2016 – Washington State Stakeholder Meeting ..................................................................................... 60 June 10, 2016 – Oregon State Stakeholder Meeting .......................................................................................... 60 June 13, 2016 – Utah State Stakeholder Meeting............................................................................................... 60 June 14, 2016 – Wyoming State Stakeholder Meeting ...................................................................................... 60 STAKEHOLDER COMMENTS ............................................................................................................ 61 CONTACT INFORMATION ................................................................................................................ 62 APPENDIX D – DEMAND-SIDE MANAGEMENT RESOURCES ......................................... 63 INTRODUCTION .............................................................................................................................. 63 DEMAND-SIDE RESOURCE POTENTIAL ASSESSMENTS FOR 2017-2036 .......................................... 63 CURRENT DSM PROGRAM OFFERINGS BY STATE .......................................................................... 64 PREFERRED PORTFOLIO DSM RESOURCE SELECTIONS .................................................................. 67 STATE-SPECIFIC DSM PLANNING PROCESSES ............................................................................... 68 APPENDIX E – SMART GRID ..................................................................................................... 69 INTRODUCTION .............................................................................................................................. 69 TRANSMISSION SYSTEM EFFORTS ................................................................................................. 69 Dynamic Line Rating ............................................................................................................ 69 Thermal Replicating Relays .................................................................................................. 70 Synchrophasors ..................................................................................................................... 70 DISTRIBUTION SYSTEM EFFORTS .................................................................................................. 71 Distribution Automation ....................................................................................................... 71 CUSTOMER INFORMATION EFFORTS ............................................................................................. 72 Advanced Metering Infrastructure ........................................................................................ 72 FUTURE SMART GRID .................................................................................................................... 72 PACIFICORP – 2017 IRP TABLE OF CONTENTS iii APPENDIX F – FLEXIBLE RESERVE STUDY ........................................................................ 73 INTRODUCTION .............................................................................................................................. 73 EXECUTIVE SUMMARY ................................................................................................................. 75 FLEXIBLE RESOURCE REQUIREMENTS ........................................................................................... 76 CONTINGENCY RESERVE .............................................................................................................. 76 REGULATION RESERVE ................................................................................................................ 76 FREQUENCY RESPONSE RESERVE ................................................................................................. 77 DESCRIPTION OF DATA INPUTS ...................................................................................................... 78 OVERVIEW .................................................................................................................................. 78 LOAD DATA ................................................................................................................................ 79 WIND DATA ................................................................................................................................ 80 NON-VER DATA ......................................................................................................................... 80 DATA ANALYSIS AND ADJUSTMENT .............................................................................................. 81 OVERVIEW .................................................................................................................................. 81 LOAD BASE SCHEDULE DEVELOPMENT ........................................................................................ 81 BASE SCHEDULE RAMPING ADJUSTMENT ..................................................................................... 84 DATA CORRECTIONS.................................................................................................................... 84 NON-VER DEVIATION ADJUSTMENT ............................................................................................ 86 METHODOLOGY TO DETERMINE INITIAL REGULATION RESERVE REQUIREMENT ........................... 88 OVERVIEW .................................................................................................................................. 88 COMPONENTS OF OPERATING RESERVE METHODOLOGY .............................................................. 89 Operating Reserve: Reserve Categories ............................................................................................................. 89 Calculation of Regulation Reserve Need ........................................................................................................... 92 Balancing Authority ACE Limit: Allowed Deviations ...................................................................................... 94 Planning Reliability Target: Loss of Load Probability ....................................................................................... 96 Regulation Reserve Forecast: Amount Held ...................................................................................................... 96 2015 REGULATION RESERVE FORECAST ....................................................................................... 97 Wind ................................................................................................................................................................... 97 Non-VERs ........................................................................................................................................................ 100 Load ................................................................................................................................................................. 102 2015 PACIFICORP SYSTEM DIVERSITY AND EIM DIVERSITY BENEFITS....................................... 104 PACIFICORP SYSTEM-WIDE PORTFOLIO DIVERSITY BENEFIT ...................................................... 104 EIM INTRA-HOUR BENEFIT ....................................................................................................... 105 INCREMENTAL WIND REGULATION RESERVE REQUIREMENTS .................................................... 107 SOLAR REGULATION RESERVE REQUIREMENTS ........................................................................... 108 OVERVIEW ................................................................................................................................ 108 PROXY SOLAR BASE SCHEDULE DEVELOPMENT ......................................................................... 109 SOLAR DIVERSITY ...................................................................................................................... 111 SOLAR LOCATIONS .................................................................................................................... 112 SOLAR PORTFOLIO .................................................................................................................... 114 SOLAR REGULATION RESERVE FORECAST ................................................................................... 115 PORTFOLIO REGULATION RESERVE REQUIREMENTS .................................................................... 117 OVERVIEW ................................................................................................................................ 117 METHODOLOGY ........................................................................................................................ 117 RESULTS ................................................................................................................................... 118 REGULATION RESERVE COST ..................................................................................................... 119 DAY-AHEAD SYSTEM BALANCING COSTS .................................................................................... 121 TECHNICAL REVIEW COMMITTEE ................................................................................................ 123 FLEXIBLE RESOURCE NEEDS ASSESSMENT .................................................................................. 125 PACIFICORP – 2017 IRP TABLE OF CONTENTS iv OVERVIEW ................................................................................................................................ 125 FORECASTED RESERVE REQUIREMENTS ..................................................................................... 126 FLEXIBLE RESOURCE SUPPLY FORECAST ................................................................................... 128 FLEXIBLE RESOURCE SUPPLY PLANNING ................................................................................... 131 SUMMARY .................................................................................................................................... 132 REFERENCE TABLES ..................................................................................................................... 134 APPENDIX G – PLANT WATER CONSUMPTION ............................................................... 139 APPENDIX H – STOCHASTIC PARAMETERS ..................................................................... 143 INTRODUCTION ............................................................................................................................ 144 VOLATILITY ................................................................................................................................. 144 MEAN REVERSION ....................................................................................................................... 144 ESTIMATING SHORT-TERM PROCESS PARAMETERS ...................................................................... 146 STOCHASTIC PROCESS DESCRIPTION ............................................................................................ 146 DATA DEVELOPMENT .................................................................................................................. 147 PARAMETER ESTIMATION – AUTOREGRESSIVE MODEL ............................................................... 150 ELECTRICITY PRICE PROCESS ...................................................................................................... 151 REGIONAL LOAD PROCESS ........................................................................................................... 153 HYDRO GENERATION PROCESS .................................................................................................... 155 SHORT-TERM CORRELATION ESTIMATION ................................................................................... 156 CONCLUSION ................................................................................................................................ 158 APPENDIX I – PLANNING RESERVE MARGIN STUDY .................................................... 159 INTRODUCTION ............................................................................................................................ 159 METHODOLOGY ........................................................................................................................... 160 DEVELOPMENT OF RESOURCE PORTFOLIOS ............................................................................... 160 DEVELOPMENT OF RELIABILITY METRICS ................................................................................... 161 DEVELOPMENT OF SYSTEM VARIABLE PRODUCTION COSTS ........................................................ 161 RESULTS ...................................................................................................................................... 163 RESOURCE PORTFOLIOS ............................................................................................................ 163 RELIABILITY METRICS ................................................................................................................ 164 SYSTEM COSTS .......................................................................................................................... 167 INCREMENTAL COST OF RELIABILITY .......................................................................................... 168 CONCLUSION ................................................................................................................................ 169 APPENDIX J – WESTERN RESOURCE ADEQUACY EVALUATION .............................. 171 INTRODUCTION ............................................................................................................................ 171 WESTERN ELECTRICITY COORDINATING COUNCIL RESOURCE ADEQUACY ASSESSMENT ........... 171 PACIFIC NORTHWEST RESOURCE ADEQUACY FORUM’S ADEQUACY ASSESSMENT...................... 175 CUSTOMER VERSUS SHAREHOLDER RISK ALLOCATION ............................................................... 176 MARKET PURCHASES ................................................................................................................... 176 PACIFICORP – 2017 IRP TABLE OF CONTENTS v APPENDIX K – CAPACITY EXPANSION RESULTS DETAIL ........................................... 179 PORTFOLIO CASE BUILD TABLES ................................................................................................. 179 APPENDIX L – STOCHASTIC PRODUCTION COST SIMULATION RESULTS ............ 225 APPENDIX M – CASE STUDY FACT SHEETS ...................................................................... 263 CASE FACT SHEET OVERVIEW ..................................................................................................... 263 MASTER FACT SHEET .................................................................................................................. 267 REGIONAL HAZE CASE FACT SHEETS .......................................................................................... 269 CORE CASE FACT SHEETS ............................................................................................................ 276 SENSITIVITY FACT SHEETS .......................................................................................................... 287 FINAL SELECTION FACT SHEETS .................................................................................................. 309 APPENDIX N – WIND AND SOLAR CAPACITY CONTRIBUTION STUDY ................... 313 INTRODUCTION ............................................................................................................................ 313 METHODOLOGY ........................................................................................................................... 314 RESULTS ...................................................................................................................................... 315 CONCLUSION ................................................................................................................................ 318 APPENDIX O – PRIVATE GENERATION STUDY ............................................................... 319 APPENDIX P – ENERGY STORAGE STUDIES ..................................................................... 415 PACIFICORP – 2017 IRP TABLE OF CONTENTS vi INDEX OF TABLES TABLE A.1 – FORECASTED ANNUAL LOAD GROWTH, 2017 THROUGH 2026 (MEGAWATT-HOURS), AT GENERATION, PRE-DSM ..................................................................................................... 2 TABLE A.2 – FORECASTED ANNUAL COINCIDENT PEAK LOAD (MEGAWATTS) AT GENERATION, PRE-DSM ................................................................................................................................. 3 TABLE A.3 – ANNUAL LOAD GROWTH CHANGE: DECEMBER 2016 FORECAST LESS OCTOBER 2015 FORECAST (MEGAWATT-HOURS) AT GENERATION, PRE-DSM ................................................. 3 TABLE A.4 – ANNUAL COINCIDENT PEAK GROWTH CHANGE: JULY 2016 FORECAST LESS OCTOBER 2015 FORECAST (MEGAWATTS) AT GENERATION, PRE-DSM .................................................. 3 TABLE A.5 – WEATHER NORMALIZED JURISDICTIONAL RETAIL SALES 2000 THROUGH 2016 ....... 11 TABLE A.6 – NON-COINCIDENT JURISDICTIONAL PEAK 2000 THROUGH 2016 ............................... 12 TABLE A.7 – JURISDICTIONAL CONTRIBUTION TO COINCIDENT PEAK 2000 THROUGH 2016 ......... 12 TABLE A.8 – SYSTEM ANNUAL RETAIL SALES FORECAST 2017 THROUGH 2026, POST-DSM ....... 14 TABLE A. 9 – FORECASTED RETAIL SALES GROWTH IN OREGON, POST-DSM ............................... 16 TABLE A.10 – FORECASTED RETAIL SALES GROWTH IN WASHINGTON, POST-DSM .................... 16 TABLE A.11 – FORECASTED RETAIL SALES GROWTH IN CALIFORNIA, POST-DSM ....................... 17 TABLE A.12 – FORECASTED RETAIL SALES GROWTH IN UTAH, POST-DSM ................................. 17 TABLE A.13 – FORECASTED RETAIL SALES GROWTH IN IDAHO, POST-DSM ................................ 18 TABLE A.14 – FORECASTED RETAIL SALES GROWTH IN WYOMING, POST-DSM ........................... 18 TABLE B.1 – INTEGRATED RESOURCE PLANNING STANDARDS AND GUIDELINES SUMMARY BY STATE .................................................................................................................................... 25 TABLE B.2 – HANDLING OF 2015 IRP ACKNOWLEDGMENT AND OTHER IRP REQUIREMENTS ...... 30 TABLE B.3 – OREGON PUBLIC UTILITY COMMISSION IRP STANDARD AND GUIDELINES ............... 38 TABLE B.4 – UTAH PUBLIC SERVICE COMMISSION IRP STANDARD AND GUIDELINES .................. 47 TABLE B.5 – WASHINGTON UTILITIES AND TRANSPORTATION COMMISSION IRP STANDARD AND GUIDELINES (RCW 19.280.030 AND WAC 480-100-238) .................................................... 52 TABLE B.6 – WYOMING PUBLIC SERVICE COMMISSION GUIDELINES REGARDING ELECTRIC IRP . 56 TABLE D.1– CURRENT CLASS 1 AND 2 DSM PROGRAM SERVICES AND OFFERINGS BY SECTOR AND STATE .................................................................................................................................... 65 TABLE D.2 – CURRENT WATTSMART OUTREACH AND COMMUNICATIONS ACTIVITIES.................. 66 TABLE D.3 – INCREMENTAL AND CUMULATIVE CLASS 1 DSM RESOURCE SELECTIONS (2017 IRP PREFERRED PORTFOLIO) ........................................................................................................ 67 TABLE D.4 – INCREMENTAL CLASS 2 DSM RESOURCE SELECTIONS (2017 IRP PREFERRED PORTFOLIO) ........................................................................................................................... 67 TABLE F.1 – PORTFOLIO REGULATION RESERVE REQUIREMENTS, BY SCENARIO .......................... 75 TABLE F.2 – 2017 FRS FLEXIBLE RESOURCE COSTS AS COMPARED TO 2014 WIS COSTS, $/MWH ............................................................................................................................................... 75 TABLE F.3 – BAL-001-1 VS BAL-001-2 ....................................................................................... 91 TABLE F.4 – DEVIATION AND REGULATION RESERVE REQUIREMENT EXAMPLE ........................... 92 TABLE F.5 – RESULTS WITH PACIFICORP PORTFOLIO DIVERSITY ................................................ 105 TABLE F.6 – EIM FLEXIBLE RESERVE DIVERSITY BENEFIT APPLICATION EXAMPLE .................. 106 TABLE F.7 – 2015 RESULTS WITH PACIFICORP PORTFOLIO DIVERSITY AND EIM INTRA-HOUR BENEFIT ............................................................................................................................... 107 TABLE F.8 – EAST SOLAR CLUSTERS BY SCENARIO ..................................................................... 114 TABLE F.9 – WEST SOLAR CLUSTERS BY SCENARIO .................................................................... 114 PACIFICORP – 2017 IRP TABLE OF CONTENTS vii TABLE F.10 – SOLAR AND WIND STAND-ALONE REGULATION REQUIREMENTS, AS PERCENTAGE OF NAMEPLATE CAPACITY ........................................................................................................ 116 TABLE F.11 – PORTFOLIO REGULATION REQUIREMENT RESULTS, BY SCENARIO ........................ 118 TABLE F.12 – PORTFOLIO REGULATION REQUIREMENT RESULTS, PERCENT OF NAMEPLATE CAPACITY ............................................................................................................................ 119 TABLE F.13 – REGULATION RESERVE PAR SCENARIOS ............................................................... 119 TABLE F.14 – REGULATION RESERVE COST CALCULATIONS ....................................................... 120 TABLE F.15 – SYSTEM BALANCING COST SIMULATIONS IN PAR ................................................. 122 TABLE F.16 – DAY-AHEAD FORECAST SYSTEM BALANCING COST RESULTS ............................... 122 TABLE F.17 – DAY-AHEAD SYSTEM BALANCING COST COMPARISON ........................................ 123 TABLE F.18 – FRS TRC RECOMMENDATIONS ............................................................................. 124 TABLE F.19 – RESERVE REQUIREMENTS (MW) ........................................................................... 127 TABLE F.20 – FLEXIBLE RESOURCE SUPPLY FORECAST (MW) .................................................... 129 TABLE F.21 – PORTFOLIO REGULATION RESERVE REQUIREMENTS, BY SCENARIO ...................... 132 TABLE F.22 – 2017 FRS FLEXIBLE RESOURCE COSTS AS COMPARED TO 2014 WIS COSTS, $/MWH ............................................................................................................................................. 133 TABLE F.23 – WIND ..................................................................................................................... 134 TABLE F.24 – NON-VERS ............................................................................................................ 134 TABLE F.25 – SOLAR ................................................................................................................... 136 TABLE G.1 – PLANT WATER CONSUMPTION WITH ACRE-FEET PER YEAR .................................. 140 TABLE G.2 – PLANT WATER CONSUMPTION BY STATE (ACRE-FEET) ........................................... 141 TABLE G.3 – PLANT WATER CONSUMPTION BY FUEL TYPE (ACRE-FEET) ................................... 141 TABLE G.4 – PLANT WATER CONSUMPTION FOR PLANTS LOCATED IN THE UPPER COLORADO RIVER BASIN (ACRE-FEET) ................................................................................................... 142 TABLE H.1 – SEASONAL DEFINITION ........................................................................................... 147 TABLE H.2 – UNCERTAINTY PARAMETERS FOR NATURAL GAS ................................................... 151 TABLE H.3 – UNCERTAINTY PARAMETERS FOR ELECTRICITY REGIONS ...................................... 153 TABLE H.4 – UNCERTAINTY PARAMETERS FOR LOAD REGIONS .................................................. 155 TABLE H.5 – UNCERTAINTY PARAMETERS FOR HYDRO GENERATION ......................................... 156 TABLE H.6 – SHORT-TERM CORRELATIONS BY SEASON .............................................................. 157 TABLE I.1 – EXPANSION RESOURCE ADDITIONS BY PRM FOR SUMMER ...................................... 163 TABLE I.2 – EXPANSION RESOURCE ADDITIONS BY PRM FOR WINTER ....................................... 164 TABLE I.3 – EXPECTED RELIABILITY METRICS BY PRM .............................................................. 165 TABLE I.4 – FITTED RELIABILITY METRICS BY PRM ................................................................... 165 TABLE I.5 – SYSTEM VARIABLE, UP-FRONT CAPITAL, AND RUN-RATE FIXED COSTS BY PRM ... 168 TABLE I.6 – 10-YEAR NOMINAL LEVELIZED COST OF EUE RELATIVE TO 10 PERCENT PRM ......... 168 TABLE J.1 – 2016 WECC FORECASTED PLANNING RESERVE MARGINS (SUMMER) .................... 175 TABLE J.2 – 2016 WECC FORECASTED PLANNING RESERVE MARGINS (WINTER) ..................... 175 TABLE J.3 – MAXIMUM AVAILABLE FRONT OFFICE TRANSACTIONS BY MARKET HUB ............... 177 TABLE K.1– REGIONAL HAZE STUDY REFERENCE GUIDE ........................................................... 179 TABLE K.2 – CORE CASE STUDY REFERENCE GUIDE ................................................................... 179 TABLE K.3 – SENSITIVITY CASE STUDY REFERENCE GUIDE ........................................................ 180 TABLE K.4 – FINAL CASE STUDY REFERENCE GUIDE .................................................................. 180 TABLE K.5 – EAST SIDE RESOURCE NAME AND DESCRIPTION ..................................................... 181 TABLE K.6 – WEST-SIDE RESOURCE NAME AND DESCRIPTION ................................................... 182 TABLE L.1 – STOCHASTIC MEAN PVRR BY PRICE SCENARIO, REGIONAL HAZE CASES .............. 225 TABLE L.2 – STOCHASTIC MEAN PVRR BY PRICE SCENARIO, CORE CASES ............................... 226 TABLE L.3 – STOCHASTIC MEAN PVRR BY PRICE SCENARIO, SENSITIVITY CASES ..................... 226 TABLE L.4 – STOCHASTIC MEAN PVRR BY PRICE SCENARIO, FINAL SCREENING CASES ............ 227 PACIFICORP – 2017 IRP TABLE OF CONTENTS viii TABLE L.5 – STOCHASTIC RISK RESULTS, REGIONAL HAZE CASES – LOW GAS, MC A .............. 227 TABLE L.6 – STOCHASTIC RISK RESULTS, REGIONAL HAZE CASES – MEDIUM GAS, MC A ........ 227 TABLE L.7 – STOCHASTIC RISK RESULTS, REGIONAL HAZE CASES – HIGH GAS, MC A ............. 228 TABLE L.8 – STOCHASTIC RISK RESULTS, REGIONAL HAZE CASES – LOW GAS, MC B .............. 228 TABLE L.9 – STOCHASTIC RISK RESULTS, REGIONAL HAZE CASES – MEDIUM GAS, MC B ........ 228 TABLE L.10 – STOCHASTIC RISK RESULTS, REGIONAL HAZE CASES – HIGH GAS, MC B............ 229 TABLE L.11 – STOCHASTIC RISK RESULTS, CORE CASES – LOW GAS, MC A .............................. 229 TABLE L.12 – STOCHASTIC RISK RESULTS, CORE CASES – MEDIUM GAS, MC A ....................... 230 TABLE L.13 – STOCHASTIC RISK RESULTS, CORE CASES – HIGH GAS, MC A ............................. 230 TABLE L.14 – STOCHASTIC RISK RESULTS, CORE CASES – LOW GAS, MC B .............................. 231 TABLE L.15 – STOCHASTIC RISK RESULTS, CORE CASES – MEDIUM GAS, MC B ........................ 231 TABLE L.16 – STOCHASTIC RISK RESULTS, CORE CASES – HIGH GAS, MC B ............................. 232 TABLE L.17 – STOCHASTIC RISK RESULTS, SENSITIVITY CASES – LOW GAS, MC A ................... 232 TABLE L.18 – STOCHASTIC RISK RESULTS, SENSITIVITY CASES – MEDIUM GAS, MC A ............. 233 TABLE L.19 – STOCHASTIC RISK RESULTS, SENSITIVITY CASES – HIGH GAS, MC A .................. 233 TABLE L.20 – STOCHASTIC RISK RESULTS, SENSITIVITY CASES – LOW GAS, MC B ................... 234 TABLE L.21 – STOCHASTIC RISK RESULTS, SENSITIVITY CASES – MEDIUM GAS, MC B ............. 235 TABLE L.22 – STOCHASTIC RISK RESULTS, SENSITIVITY CASES – HIGH GAS, MC B .................. 236 TABLE L.23 – STOCHASTIC RISK RESULTS, FINAL SCREENING CASES, LOW GAS, MC A ............ 236 TABLE L.24 – STOCHASTIC RISK RESULTS, FINAL SCREENING CASES, MEDIUM GAS, MC A ..... 236 TABLE L.25 – STOCHASTIC RISK RESULTS, FINAL SCREENING CASES, HIGH GAS, MC A ........... 237 TABLE L.26 – STOCHASTIC RISK RESULTS, FINAL SCREENING CASES, LOW GAS, MC B ............ 237 TABLE L.27 – STOCHASTIC RISK RESULTS, FINAL SCREENING CASES, MEDIUM GAS, MC B ...... 237 TABLE L.28 – STOCHASTIC RISK RESULTS, FINAL SCREENING CASES, HIGH GAS, MC B ........... 238 TABLE L.29 – STOCHASTIC RISK ADJUSTED PVRR BY PRICE SCENARIO, REGIONAL HAZE CASES ............................................................................................................................................. 238 TABLE L.30 – STOCHASTIC RISK ADJUSTED PVRR BY PRICE SCENARIO, CORE CASES .............. 238 TABLE L.31 – STOCHASTIC RISK ADJUSTED PVRR BY PRICE SCENARIO, SENSITIVITY CASES ... 239 TABLE L.32 – STOCHASTIC RISK ADJUSTED PVRR BY PRICE SCENARIO, FINAL SCREENING CASES ............................................................................................................................................. 239 TABLE L.33 – CARBON DIOXIDE EMISSIONS BY PRICE SCENARIO, REGIONAL HAZE CASES ........ 240 TABLE L.34 – CARBON DIOXIDE EMISSIONS BY PRICE SCENARIO, CORE CASES ......................... 240 TABLE L.35 – CARBON DIOXIDE EMISSIONS BY PRICE SCENARIO, SENSITIVITY CASES .............. 241 TABLE L.36 – CARBON DIOXIDE EMISSIONS BY PRICE SCENARIO, FINAL SCREENING CASES ..... 241 TABLE L.37 – ENERGY NOT SERVED, REGIONAL HAZE CASES, LOW GAS .................................. 242 TABLE L.38 – ENERGY NOT SERVED, REGIONAL HAZE CASES, MEDIUM GAS ............................ 242 TABLE L.39 – ENERGY NOT SERVED, REGIONAL HAZE CASES, HIGH GAS .................................. 243 TABLE L.40 – ENERGY NOT SERVED, CORE CASES, LOW GAS .................................................... 243 TABLE L.41 – ENERGY NOT SERVED, CORE CASES, MEDIUM GAS .............................................. 244 TABLE L.42 – ENERGY NOT SERVED, CORE CASES, HIGH GAS ................................................... 244 TABLE L.43 – ENERGY NOT SERVED, SENSITIVITY CASES, LOW GAS ......................................... 245 TABLE L.44 – ENERGY NOT SERVED, SENSITIVITY CASES, MEDIUM GAS ................................... 246 TABLE L.45 – ENERGY NOT SERVED, SENSITIVITY CASES, HIGH GAS ........................................ 247 TABLE L.46 – ENERGY NOT SERVED, FINAL SCREENING CASES, LOW GAS ................................ 247 TABLE L.47 – ENERGY NOT SERVED, FINAL SCREENING CASES, MEDIUM GAS .......................... 248 TABLE L.48 – ENERGY NOT SERVED, FINAL SCREENING CASES, HIGH GAS ............................... 248 TABLE L.49 – PVRR COST COMPONENTS BY PRICE SCENARIO, REGIONAL HAZE CASES, MC A 249 TABLE L.50 – PVRR COST COMPONENTS BY PRICE SCENARIO, REGIONAL HAZE CASES, MC B 250 PACIFICORP – 2017 IRP TABLE OF CONTENTS ix TABLE L.51 – PVRR COST COMPONENTS BY PRICE SCENARIO, CORE CASES, MC A ................. 251 TABLE L.52 – PVRR COST COMPONENTS BY PRICE SCENARIO, CORE CASES, MC B ................. 252 TABLE L.53 – PVRR COST COMPONENTS BY PRICE SCENARIO, SENSITIVITY CASES, MC A ...... 254 TABLE L.54 – PVRR COST COMPONENTS BY PRICE SCENARIO, SENSITIVITY CASES, MC B....... 255 TABLE L.55 – PVRR COST COMPONENTS BY PRICE SCENARIO, FINAL SCREENING CASES, MC A ............................................................................................................................................. 257 TABLE L.56 – PVRR COST COMPONENTS BY PRICE SCENARIO, FINAL SCREENING CASES, MC B ............................................................................................................................................. 258 TABLE L.57 – 10-YEAR AVERAGE INCREMENTAL CUSTOMER RATE IMPACT, FINAL SCREENING CASES .................................................................................................................................. 259 TABLE L.58 – LOSS OF LOAD PROBABILITY, MAJOR (> 25,000 MWH) JULY EVENT, FINAL SCREENING CASES, MEDIUM GAS, MC B ............................................................................ 260 TABLE L.59 – SUMMER PEAK, AVERAGE LOSS OF LOAD PROBABILITY, FINAL SCREENING CASES, MEDIUM GAS, MC B ........................................................................................................... 261 TABLE N.1 – PEAK CAPACITY CONTRIBUTION VALUES FOR WIND AND SOLAR .......................... 315 PACIFICORP – 2017 IRP TABLE OF CONTENTS x INDEX OF FIGURES FIGURE A.1 – PACIFICORP SYSTEM ENERGY LOAD FORECAST CHANGE, AT GENERATION, PRE- DSM ........................................................................................................................................ 2 FIGURE A.2 – PACIFICORP ANNUAL RETAIL SALES 2000 THROUGH 2016 AND WESTERN REGION EMPLOYMENT .......................................................................................................................... 4 FIGURE A.3 – PACIFICORP ANNUAL RESIDENTIAL USE PER CUSTOMER 2001 THROUGH 2016 ........ 5 FIGURE A.4 – IHS GLOBAL INSIGHT UTAH HOUSEHOLD AND EMPLOYMENT FORECASTS FROM THE OCTOBER 2015 LOAD FORECAST AND THE DECEMBER 2016 LOAD FORECAST ......................... 6 FIGURE A.5 – IHS GLOBAL INSIGHT OREGON HOUSEHOLD AND EMPLOYMENT FORECASTS FROM THE OCTOBER 2015 LOAD FORECAST AND THE DECEMBER 2016 LOAD FORECAST .................. 6 FIGURE A.6 – IHS GLOBAL INSIGHT WYOMING HOUSEHOLD AND EMPLOYMENT FORECASTS FROM THE OCTOBER 2015 LOAD FORECAST AND THE DECEMBER 2016 LOAD FORECAST .................. 7 FIGURE A.7 – IHS GLOBAL INSIGHT WASHINGTON HOUSEHOLD AND EMPLOYMENT FORECASTS FROM THE OCTOBER 2015 LOAD FORECAST AND THE DECEMBER 2016 LOAD FORECAST ........ 8 FIGURE A.8 – IHS GLOBAL INSIGHT IDAHO HOUSEHOLD AND EMPLOYMENT FORECASTS FROM THE OCTOBER 2015 LOAD FORECAST AND THE DECEMBER 2016 LOAD FORECAST ......................... 8 FIGURE A.9 – IHS GLOBAL INSIGHT CALIFORNIA HOUSEHOLD AND EMPLOYMENT FORECASTS FROM THE OCTOBER 2015 LOAD FORECAST AND THE DECEMBER 2016 LOAD FORECAST ........ 9 FIGURE A.10 – COMPARISON OF UTAH 5, 10, AND 20 YEAR AVERAGE PEAK PRODUCING TEMPERATURES ..................................................................................................................... 10 FIGURE A.11 – LOAD FORECAST SCENARIOS FOR 1-IN-20 WEATHER, HIGH, BASE CASE AND LOW, PRE-DSM ............................................................................................................................... 19 FIGURE F.1 – EXPECTED LOAD CHANGE FROM PRIOR WEEK ......................................................... 82 FIGURE F.2 – PROXY LOAD BASE SCHEDULE ................................................................................ 83 FIGURE F.3 – BASE SCHEDULE RAMPING ADJUSTMENT ................................................................ 84 FIGURE F.4 – ORIGINAL PACW NON-VER DEVIATIONS ............................................................... 87 FIGURE F.5 – ADJUSTED PACW NON-VER DEVIATIONS .............................................................. 88 FIGURE F.6 – DEVIATION AND REGULATION RESERVE REQUIREMENT EXAMPLE .......................... 93 FIGURE F.7 – PROBABILITY DISTRIBUTION OF PACE COMBINED PORTFOLIO DEVIATIONS ........... 94 FIGURE F.8 – PROBABILITY OF EXCEEDING ALLOWED DEVIATION................................................ 95 FIGURE F.9 – WIND REGULATION RESERVE REQUIREMENTS BY FORECAST CAPACITY FACTOR ... 98 FIGURE F.10 – STAND-ALONE WIND REGULATION RESERVE FORECAST ....................................... 99 FIGURE F.11 – NON-VER REGULATION RESERVE REQUIREMENTS BY FORECAST CAPACITY FACTOR ................................................................................................................................ 100 FIGURE F.12 – NON-VER REGULATION RESERVE REQUIREMENTS BY HOUR OF THE DAY .......... 101 FIGURE F.13 – STAND-ALONE NON-VER REGULATION RESERVE FORECAST .............................. 102 FIGURE F.14 – STAND-ALONE LOAD REGULATION RESERVE REQUIREMENTS BY HOUR OF THE DAY ............................................................................................................................................. 103 FIGURE F.15 – STAND-ALONE LOAD REGULATION RESERVE FORECAST ..................................... 104 FIGURE F.16 – SOLAR CAPACITY ADDITIONS .............................................................................. 109 FIGURE F.17 – SOLAR REGULATION RESERVE REQUIREMENTS: PROXY VS EIM ......................... 111 FIGURE F.18 – SOLAR DIVERSITY ................................................................................................ 112 FIGURE F.19 – SOLAR RESOURCE LOCATIONS ............................................................................. 113 FIGURE F.20 – STAND-ALONE SOLAR REGULATION RESERVE REQUIREMENTS, BY CAPACITY..... 116 FIGURE F.21 – COMPARISON OF RESERVE REQUIREMENTS AND RESOURCES, EAST BALANCING AUTHORITY AREA (MW) ..................................................................................................... 130 PACIFICORP – 2017 IRP TABLE OF CONTENTS xi FIGURE F.22 – COMPARISON OF RESERVE REQUIREMENTS AND RESOURCES, WEST BALANCING AUTHORITY AREA (MW) ..................................................................................................... 131 FIGURE H.1 – STOCHASTIC PROCESSES ........................................................................................ 145 FIGURE H.2 – RANDOM WALK PRICE PROCESS AND MEAN REVERTING PROCESS ....................... 145 FIGURE H.3 – LOGNORMAL DISTRIBUTION AND CUMULATIVE LOGNORMAL DISTRIBUTION ....... 146 FIGURE H.4 – DAILY GAS PRICES FOR SUMAS BASIN ................................................................ 147 FIGURE H.5 – DAILY GAS PRICES FOR SUMAS BASIN WITH "EXPECTED" PRICES ....................... 149 FIGURE H.6 – GAS PRICE INDEX FOR SUMAS BASIN .................................................................. 149 FIGURE H.7 – REGRESSION FOR SUMAS GAS BASIN .................................................................. 150 FIGURE H.8 – DAILY ELECTRICITY PRICES FOR FOUR CORNERS .................................................. 152 FIGURE H.9 – PROBABILITY DISTRIBUTION FOR PORTLAND LOAD .............................................. 153 FIGURE H.10 – DAILY AVERAGE LOAD FOR PORTLAND .............................................................. 154 FIGURE H.11 – WEEKLY AVERAGE HYDRO GENERATION IN THE WEST ...................................... 156 FIGURE I.1 – WORKFLOW FOR PLANNING RESERVE MARGIN STUDY .......................................... 160 FIGURE I.2 – EXPECTED AND FITTED RELATIONSHIP OF EUE TO PRM ........................................ 166 FIGURE I.3 – EXPECTED AND FITTED RELATIONSHIP OF LOLH TO PRM ..................................... 166 FIGURE I.4 – SIMULATED RELATIONSHIP OF LOSS OF LOAD EPISODE TO PRM ............................ 167 FIGURE I.5 – INCREMENTAL COST OF RELIABILITY BY PRM ...................................................... 169 FIGURE J.1 – WECC FORECASTED POWER SUPPLY MARGINS, ISSUED 2009 TO 2016 (SUMMER) 173 FIGURE J.2 – 2016 LESS 2014 WECC PSA (FOR SUMMER PERIODS) ........................................... 174 FIGURE J.3 – PACIFICORP SUMMER PEAK MARKET PURCHASES 2009-2015 ............................... 178 FIGURE J.4 – PACIFICORP WINTER PEAK MARKET PURCHASES 2009-2015 ................................ 178 FIGURE N.1 – DAILY LOLP ......................................................................................................... 316 FIGURE N.2 – MONTHLY RESOURCE CAPACITY FACTORS AS COMPARED TO LOLP .................... 316 FIGURE N.3 – HOURLY RESOURCE CAPACITY FACTORS AS COMPARED TO LOLP FOR AN AVERAGE DAY IN JULY ........................................................................................................................ 317 PACIFICORP – 2017 IRP TABLE OF CONTENTS xii PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 1 APPENDIX A – LOAD FORECAST DETAILS Introduction This appendix reviews the load forecast used in the modeling and analysis of the 2017 Integrated Resource Plan (“IRP”), including scenario development for case sensitivities. The load forecast used in the IRP is an estimate of the energy sales, and peak demand over a 20-year period. The 20-year horizon is important to anticipate electricity demand in order to develop timely response of resources. In the development of its load forecast PacifiCorp employs econometric models that use historical data and inputs such as regional and national economic growth, weather, seasonality, and other customer usage and behavior changes. The forecast is divided into classes that use energy for similar purposes and at comparable retail rates. These separate customer classes include residential, commercial, industrial, irrigation, lighting, and public authority customer classes. The classes are modeled separately using variables specific to their usage patterns. For residential customers, typical energy uses include space heating, water heating, lighting, cooking, refrigeration, dish washing, laundry washing, televisions and various other end use appliances. Commercial and industrial customers use energy for production and manufacturing processes, space heating, air conditioning, lighting, computers and other office equipment. Jurisdictional peak load forecasts are developed using econometric equations that relate observed monthly peak loads, peak producing weather and the weather-sensitive loads for all classes. The system coincident peak forecast, which is used in portfolio development, is the maximum load required on the system in any hourly period and is extracted from the hourly forecast model. Summary Load Forecast The Company updated its load forecast in December 2016. The average annual energy growth rate for the 10-year period (2017 through 2026) is 0.91 percent. Relative to the load forecast prepared for the 2015 IRP update, PacifiCorp 2026 energy forecasted energy requirement decreased in all jurisdictions other than Idaho, while PacifiCorp system energy requirement decreased approximately 5.3 percent. Figure A.1 has a comparison of energy forecasts from the 2017 IRP compared to the 2015 IRP Update. PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 2 Figure A.1 - PacifiCorp System Energy Load Forecast Change, at Generation, pre-DSM Tables A.1 and A.2 show the annual load and coincident peak load forecast when not reducing load projections to account for new energy efficiency measures (Class 2 DSM).1 Tables A.3 and A.4 show the forecast changes relative to the 2015 IRP Update load forecast for loads and coincident system peak, respectively. Table A.1 – Forecasted Annual Load Growth, 2017 through 2026 (Megawatt-hours), at Generation, pre-DSM 1 Class 2 DSM load reductions are included as resources in the System Optimizer model. Me g a W a t t H o u r s ( M W h ) Comparison of System Energy Forecast Year Total OR WA CA UT WY ID SE-ID 2017 60,061,400 14,605,160 4,458,290 905,140 26,276,610 10,004,230 3,811,970 - 2018 60,670,450 14,736,700 4,497,430 904,220 26,637,690 10,050,920 3,843,490 - 2019 61,301,370 14,881,630 4,536,810 901,890 26,956,500 10,150,590 3,873,950 - 2020 61,863,300 14,951,780 4,563,240 897,830 27,260,420 10,292,840 3,897,190 - 2021 62,297,200 15,019,870 4,585,510 892,140 27,547,010 10,334,140 3,918,530 - 2022 63,007,030 15,144,810 4,615,090 889,900 27,962,140 10,445,060 3,950,030 - 2023 63,799,730 15,276,170 4,646,900 887,920 28,398,470 10,606,930 3,983,340 - 2024 64,610,360 15,448,030 4,692,480 888,010 28,896,420 10,663,800 4,021,620 - 2025 65,171,560 15,534,760 4,720,510 882,810 29,224,630 10,763,560 4,045,290 - 2026 65,182,980 15,634,920 4,753,180 879,280 28,894,200 10,947,860 4,073,540 - 2017 - 2026 0.91%0.76%0.71%-0.32%1.06%1.01%0.74% Average Annual Growth Rate for 2017-2026 PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 3 Table A.2 - Forecasted Annual Coincident Peak Load (Megawatts) at Generation, pre- DSM Table A.3 – Annual Load Growth Change: December 2016 Forecast less October 2015 Forecast (Megawatt-hours) at Generation, pre-DSM Table A.4 – Annual Coincident Peak Growth Change: July 2016 Forecast less October 2015 Forecast (Megawatts) at Generation, pre-DSM Load Forecast Assumptions Regional Economy by Jurisdiction The PacifiCorp electric service territory is comprised of six states and within these states the Company serves customers in a total of 88 counties. The level of retail sales for each state and county is correlated with economic conditions and population statistics in each state. The Company uses both economic data, such as employment, and population data, to forecast its Year Total OR WA CA UT WY ID SE-ID 2017 10,130 2,285 718 151 5,012 1,246 719 - 2018 10,225 2,308 724 151 5,071 1,248 724 - 2019 10,310 2,349 739 152 5,097 1,245 727 - 2020 10,403 2,359 742 152 5,152 1,267 731 - 2021 10,518 2,374 747 151 5,217 1,279 750 - 2022 10,624 2,391 752 151 5,281 1,292 756 - 2023 10,706 2,407 757 151 5,341 1,303 747 - 2024 10,804 2,425 763 151 5,409 1,305 752 - 2025 10,920 2,443 768 151 5,483 1,318 757 - 2026 10,931 2,457 773 150 5,446 1,343 762 - 2017 - 2026 0.85%0.81%0.82%-0.06%0.93%0.84%0.65% Average Annual Growth Rate for 2017-2026 Year Total OR WA CA UT WY ID SE-ID 2017 (2,207,700) (282,280) (216,490) 18,670 (1,306,230) (447,850) 26,480 - 2018 (2,711,610) (404,400) (213,910) 16,230 (1,595,750) (549,600) 35,820 - 2019 (3,080,850) (415,220) (210,950) 13,080 (1,914,340) (596,700) 43,280 - 2020 (3,219,990) (429,430) (214,930) 9,540 (2,136,110) (499,850) 50,790 - 2021 (3,275,870) (410,960) (204,530) 7,180 (2,246,040) (479,490) 57,970 - 2022 (3,231,080) (396,300) (200,300) 5,500 (2,309,120) (397,770) 66,910 - 2023 (3,104,490) (393,620) (193,660) 6,790 (2,351,250) (248,360) 75,610 - 2024 (3,150,500) (397,080) (186,540) 10,390 (2,400,790) (260,370) 83,890 - 2025 (3,065,130) (397,820) (168,980) 15,410 (2,451,900) (151,930) 90,090 - 2026 (3,674,160) (424,310) (161,420) 17,830 (3,226,920) 24,970 95,690 - Year Total OR WA CA UT WY ID SE-ID 2017 (153) (23) (25) 4 7 (111) (4) - 2018 (245) (29) (26) 4 (66) (125) (2) - 2019 (306) (6) (15) 4 (145) (143) (2) - 2020 (319) (11) (18) 6 (177) (126) 6 - 2021 (323) (9) (17) 5 (199) (118) 14 - 2022 (326) (6) (17) 5 (215) (108) 16 - 2023 (343) (5) (16) 4 (231) (99) 3 - 2024 (350) 1 (15) 6 (244) (104) 5 - 2025 (333) (5) (16) 10 (258) (91) 27 - 2026 (438) (7) (16) 12 (375) (67) 14 - PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 4 retail sales. Looking at historical sales and employment data for PacifiCorp’s service territory, 2000 through 2016, in Figure A.2, it is apparent that the Company’s retail sales generally follow economic conditions in its service territory, and most recently the 2008-2009 recession. Figure A.2 - PacifiCorp Annual Retail Sales 2000 through 2016 and Western Region Employment Sources: PacifiCorp and United States Department of Labor, Bureau of Labor Statistics As discussed below, although both the economic and demographic forecast is relatively unchanged from the 2015 IRP Update, the load forecast has decreased. There are two changes which are driving the 2017 IRP load and peak forecast down. First, the relationship between the economic variable and sales has “flattened”, meaning electric usage has become less responsive to the economic variable as seen in years 2015 and 2016 in Figure A.2 above. Second, there have been changes in expected sales to our customers due in large part to lower commodity prices. Figure A.3 shows the weather normalized average system residential use per customer. As illustrated, residential use per customer has been decreasing since 2010. 28 29 30 31 32 33 34 35 36 42,000 44,000 46,000 48,000 50,000 52,000 54,000 56,000 58,000 Em p l o y m e n t ( m i l l i o n s ) GW h Retail Sales and Service Territory Employment System Annual Sales Western Region Employment PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 5 Figure A.3 - PacifiCorp Annual Residential Use per Customer 2001 through 2016 Residential use per customer across all six of PacifiCorp’s states is changing due to increased energy efficiency driven primarily by lighting efficiency standards resulting from the 2007 Federal Energy legislation. In addition, there has been a shift from single-family and manufactured housing to multi-dwelling units and a trend of replacing older electric appliances with more energy efficient appliances. Utah PacifiCorp serves 25 of the 29 counties in the state of Utah, with Salt Lake City being the largest metropolitan area served by the Company within the state. Utah is expected to experience a 1.9 percent increase in non-farm employment over the next 10 years. Figure A.4 shows the change in population and employment forecasts between the 2015 IRP Update relative to the 2017 IRP forecast. This figure illustrates that the population forecast is slightly higher while the employment forecasts is slightly lower. Relative to the load forecast prepared for the 2015 IRP update, the Utah 2026 retail load forecast decreased approximately 6.7 percent. This decrease is attributable to the projected impact of additional private generation and the impact of a relatively less favorable economic outlook compared to the 2015 IRP Update. PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 6 Figure A.4 – IHS Global Insight Utah Household and Employment forecasts from the October 2015 load forecast and the December 2016 load forecast A risk to the Utah forecast is commodity prices, such as oil and natural gas, where volatility in prices and profitability can lead to swings in production and employment potentially translating to swings in the retail sales forecast. Oregon PacifiCorp serves 25 of the 36 counties in Oregon, but provided only 27.2 percent of ultimate electric retail sales in the state of Oregon in 2015.2 In 2014 and 2015, Oregon employment growth has outpaced national employment by approximately one percentage point.3 Figure A.5 shows the change in population and employment forecasts for the 2015 IRP Update relative to the 2017 IRP forecast. This figure illustrates that the Oregon forecast of population has increased slightly, while the employment forecast has decreased slightly. Relative to the load forecast prepared for the 2015 IRP Update, the Oregon 2026 retail load forecast has decreased approximately 2.6 percent. Figure A.5 – IHS Global Insight Oregon Household and Employment forecasts from the October 2015 load forecast and the December 2016 load forecast 2 Source: Oregon Public Utility Commission, 2015 Oregon Utility Statistics. 3 Source: Bureau of Labor Statistics. 3,000 3,200 3,400 3,600 3,800 4,000 Po p u l a t i o n ( t h o u s a n d s ) Utah Population Forecasts October 2015 December 2016 1,300 1,350 1,400 1,450 1,500 1,550 1,600 1,650 1,700 1,750 No n -fa r m E m p l o y m e n t ( t h o u s a n d s ) Utah Employment Forecasts October 2015 December 2016 1,100 1,150 1,200 1,250 1,300 Po p u l a t i o n ( t h o u s a n d s ) Oregon Population Forecasts October 2015 December 2016 400 450 500 550 600 No n -fa r m E m p l o y m e n t ( t h o u s a n d s ) Oregon Employment Forecasts October 2015 December 2016 PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 7 Wyoming The Company serves 15 of the 23 counties in Wyoming, with Casper being the largest metropolitan area served by the Company in the state. Industrial sales make up approximately 73 percent of the Company’s Wyoming sales. Figure A.6 shows the change in population and employment forecasts for the 2015 IRP Update relative to the 2017 IRP forecast. This figure illustrates that the Wyoming population forecast has decreased over the 2017 to 2022 timeframe, while it increased over the 2023 to 2026 period. The employment forecast has decreased. Relative to the load forecast prepared for the 2015 IRP Update, the Wyoming 2026 retail load forecast increased approximately 1.2 percent. Figure A.6 – IHS Global Insight Wyoming Household and Employment forecasts from the October 2015 load forecast and the December 2016 load forecast A risk to the Wyoming forecast is commodity prices, such as oil and natural gas, where volatility in prices and profitability can lead to swings in production and employment which translates to potential swings in the retail sales forecast. Washington PacifiCorp serves the following counties in Washington State: Benton, Columbia, Garfield, Klickitat, Walla Walla, and Yakima. Yakima is the most populated county that the Company serves in Washington State and has a large concentration of agriculture and food processing businesses. Residential and commercial sales are roughly equal in size each making up approximately 38 percent of the Company’s Washington sales. Figure A.7 shows the change in population and employment forecasts for the 2015 IRP Update relative to the 2017 IRP forecast. This figure illustrates that the population forecast is higher and the employment forecast has decreased. Relative to the load forecast prepared for the 2015 IRP Update, the Washington 2026 retail load forecast decreased approximately 1.3 percent. 270 275 280 285 290 Po p u l a t i o n ( t h o u s a n d s ) Wyoming Population Forecasts October 2015 December 2016 130 135 140 145 150 No n -fa r m E m p l o y m e n t ( t h o u s a n d s ) Wyoming Employment Forecasts October 2015 December 2016 PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 8 Figure A.7 – IHS Global Insight Washington Household and Employment forecasts from the October 2015 load forecast and the December 2016 load forecast Idaho The Company serves 13 of the 44 counties in the state of Idaho, with the majority of the Company’s service territory in rural Idaho. Industrial sales make up approximately 47 percent of the Company’s Idaho sales. Figure A.8 shows the change in population and employment forecasts for the 2015 IRP Update relative to the 2017 IRP forecast. This figure illustrates that the forecast for population has decreased, while the employment forecast has increased. Relative to the load forecast prepared for the 2015 IRP Update, the Idaho 2026 retail load forecast increased approximately 3.0 percent. Figure A.8 – IHS Global Insight Idaho Household and Employment forecasts from the October 2015 load forecast and the December 2016 load forecast California The four northern California counties served by PacifiCorp are largely rural, which include Del Norte, Modoc, Shasta and Siskiyou Counties. Crescent City is the largest metropolitan area served by the Company in California. Residential sales make up approximately 49 percent of the Company’s California sales. Figure A.9 shows the change in population and employment forecasts for the 2015 IRP Update relative to the 2017 IRP forecast. This figure illustrates that the population forecast has decreased, while the employment forecast had increased. Relative to 270 280 290 300 310 320 Po p u l a t i o n ( t h o u s a n d s ) Washington Population Forecasts October 2015 December 2016 80 85 90 95 100 105 110 No n -fa r m E m p l o y m e n t ( t h o u s a n d s ) Washington Employment Forecasts October 2015 December 2016 160 165 170 175 180 185 190 195 200 Po p u l a t i o n ( t h o u s a n d s ) Idaho Population Forecasts October 2015 December 2016 50 55 60 65 70 75 80 No n -fa r m E m p l o y m e n t ( t h o u s a n d s ) Idaho Employment Forecasts October 2015 December 2016 PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 9 the load forecast prepared for the 2015 IRP Update, the California 2026 retail load forecast increased approximately 6.5 percent. Figure A.9 – IHS Global Insight California Household and Employment forecasts from the October 2015 load forecast and the December 2016 load forecast Weather The Company’s load forecast is based on normal weather defined by the 20-year time period of 1996-2015. The Company updated its temperature spline models to the five-year time period of 2011-2015. The Company’s spline models are used to model the commercial and residential class temperature sensitivity at varying temperatures. The Company has reviewed the appropriateness of using the average weather from a shorter time period as its “normal” peak weather. Figure A.10 indicates that peak producing weather does not change significantly when comparing five, 10, or 20 year average weather. 70.0 72.0 74.0 76.0 78.0 80.0 Po p u l a t i o n ( t h o u s a n d s ) California Population Forecasts October 2015 December 2016 25.0 27.0 29.0 31.0 33.0 35.0 No n -fa r m E m p l o y m e n t ( t h o u s a n d s ) California Employment Forecasts October 2015 December 2016 PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 10 Figure A.10 - Comparison of Utah 5, 10, and 20 Year Average Peak Producing Temperatures Statistically Adjusted End-Use (SAE) The Company models sales per customer for the residential class using the SAE model, which combines the end-use modeling concepts with traditional regression analysis techniques. Major drivers of the SAE-based residential model are heating and cooling related variables, equipment shares, saturation levels and efficiency trends, and economic drivers such as household size, income and energy price. The Company uses ITRON for its load forecasting software and services, as well as SAE. To predict future changes in the efficiency of the various end uses for the residential class, an excel spreadsheet model obtained from ITRON was utilized; the model includes appliance efficiency trends based on appliance life as well as past and future efficiency standards. The SAE model reflects the US Department of Energy’s Energy Information Administration (EIA) assumptions for changes in energy efficiency of each appliance category, which are updated annually to take into consideration for new codes and standards including lighting standards from the Energy Independence and Security Act of 2007. The EIA estimates the efficiency of appliance stocks and the saturation of appliances at the national level and for individual Census Regions. The model embeds all currently applicable laws and regulations regarding appliance efficiency, along with life cycle models of each appliance. The life cycle models, based on the decay and replacement rate are necessary to estimate how fast the existing stock of any given appliance turns over, i.e. newer more efficient equipment replacing older less efficient equipment. 0 10 20 30 40 50 60 70 80 90 100 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec De g r e e s Utah Average Peak Producing Weather 20 Year Average 10 Year Average 5 Year Average PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 11 Individual Customer Forecast The Company updated its load forecast for a select group of large industrial customers, self- generation facilities of large industrial customers, and data center forecasts within the respective jurisdictions. Customer forecasts are provided by the customer to the Company through a regional business manager (RBM). Actual Load Data With the exception of the industrial class, the Company uses actual load data from January 2000 through February 2016. The historical data period used to develop the industrial monthly sales is from January 2000 through February 2016 in Utah and Wyoming, January 2002 through February 2016 in Idaho, and Washington, and January 2003 through February 2016 in California and Oregon. The following tables are the annual actual retail sales, non-coincident peak, and coincident peak by state used in calculating the 2017 IRP retail sales forecast. Table A.5 - Weather Normalized Jurisdictional Retail Sales 2000 through 2016 Year California Idaho Oregon Utah Washington Wyoming System 2000 776,665 3,077,264 14,194,244 18,793,616 4,091,310 7,347,453 48,280,553 2001 778,162 2,976,494 13,523,805 18,484,442 4,026,937 7,680,809 47,470,649 2002 799,939 3,232,113 13,085,474 18,620,633 4,013,855 7,406,900 47,158,914 2003 819,108 3,227,070 13,108,396 19,249,531 4,067,382 7,471,050 47,942,536 2004 844,582 3,304,254 13,156,747 19,832,347 4,100,463 7,814,422 49,052,814 2005 835,402 3,222,870 13,160,345 20,214,262 4,213,148 8,009,888 49,655,914 2006 859,303 3,344,385 13,910,585 21,079,795 4,126,393 8,254,237 51,574,698 2007 874,819 3,358,414 13,973,359 21,962,447 4,071,975 8,482,587 52,723,603 2008 867,587 3,402,821 13,775,175 22,636,955 4,064,372 9,213,810 53,960,720 2009 829,879 2,962,976 13,116,677 22,094,266 4,037,211 9,259,753 52,300,763 2010 840,479 3,395,472 13,122,473 22,570,702 4,051,355 9,664,607 53,645,087 2011 803,948 3,432,628 13,000,020 23,357,025 4,017,580 9,766,930 54,378,131 2012 785,803 3,494,537 13,024,670 23,814,679 4,046,167 9,479,742 54,645,597 2013 774,660 3,517,060 13,061,037 23,794,419 4,058,252 9,552,400 54,757,828 2014 774,113 3,524,860 13,123,680 24,352,495 4,113,824 9,589,358 55,478,330 2015 746,136 3,459,937 13,082,915 24,081,112 4,114,642 9,379,936 54,864,679 2016 757,816 3,475,328 13,019,288 23,782,480 4,055,425 9,195,353 54,285,689 2000-16 -0.15%0.76%-0.54%1.48%-0.06%1.41%0.74% *System retail sales do not include sales for resale System Retail Sales - Megawatt-hours (MWh)* Average Annual Growth Rate PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 12 Table A.6 - Non-Coincident Jurisdictional Peak 2000 through 2016 Table A.7 - Jurisdictional Contribution to Coincident Peak 2000 through 2016 Year California Idaho Oregon Utah Washington Wyoming System 2000 176 686 2,603 3,684 785 1,062 8,995 2001 162 616 2,739 3,480 755 1,124 8,876 2002 174 713 2,639 3,773 771 1,113 9,184 2003 169 722 2,451 4,004 788 1,126 9,260 2004 193 708 2,524 3,862 920 1,111 9,318 2005 189 753 2,721 4,081 844 1,224 9,811 2006 180 723 2,724 4,314 822 1,208 9,970 2007 187 789 2,856 4,571 834 1,230 10,466 2008 187 759 2,921 4,479 923 1,339 10,609 2009 193 688 3,121 4,404 917 1,383 10,705 2010 176 777 2,552 4,448 893 1,366 10,213 2011 177 770 2,686 4,596 854 1,404 10,486 2012 159 800 2,550 4,732 797 1,338 10,376 2013 182 814 2,980 5,091 886 1,398 11,351 2014 161 818 2,598 5,024 871 1,360 10,831 2015 157 843 2,598 5,226 837 1,326 10,986 2016 155 848 2,584 5,018 819 1,300 10,724 2000-16 -0.78%1.33%-0.05%1.95%0.27%1.28%1.11% *Non-coincident peaks do not include sales for resale Non-Coincident Peak - Megawatts (MW)* Average Annual Growth Rate Year California Idaho Oregon Utah Washington Wyoming System 2000 154 523 2,347 3,684 756 979 8,443 2001 124 421 2,121 3,479 627 1,091 7,863 2002 162 689 2,138 3,721 758 1,043 8,511 2003 155 573 2,359 4,004 774 1,022 8,887 2004 120 603 2,200 3,831 740 1,094 8,588 2005 171 681 2,238 4,015 708 1,081 8,895 2006 156 561 2,684 3,972 816 1,094 9,283 2007 160 701 2,604 4,381 754 1,129 9,730 2008 171 682 2,521 4,145 728 1,208 9,456 2009 153 517 2,573 4,351 795 987 9,375 2010 144 527 2,442 4,294 757 1,208 9,373 2011 143 549 2,187 4,596 707 1,204 9,387 2012 156 782 2,163 4,731 749 1,225 9,806 2013 156 674 2,407 5,091 797 1,349 10,474 2014 150 630 2,345 5,024 819 1,294 10,263 2015 152 805 2,472 5,081 833 1,259 10,601 2016 139 575 2,462 4,940 817 1,201 10,135 2000-16 -0.63%0.59%0.30%1.85%0.49%1.29%1.15% *Coincident peaks do not include sales for resale Average Annual Growth Rate Coincident Peak - Megawatts (MW)* PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 13 System Losses Line loss factors are derived using the five-year average of the percent difference between the annual system load by jurisdiction and the retail sales by jurisdiction. System line losses were updated to reflect actual losses for the five-year period ending December 31, 2015. Forecast Methodology Overview Class 2 Demand-side Management (DSM) 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 Optimizer. 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 curves, along with the economic screening provided by System Optimizer, determines the cost-effective mix of Class 2 DSM for a given scenario. Modeling overview The load forecast is developed by forecasting the monthly sales by customer class for each jurisdiction. The residential sales forecast is developed as a use-per-customer forecast multiplied by the forecast number of customers. The customer forecasts are based on a combination of regression analysis and exponential smoothing techniques using historical data from January 2000 to February 2016. For the residential class, the Company forecasts the number of customers using IHS Global Insight’s forecast of each state’s number of population as the major driver. The Company models sales per customer for the residential class using the SAE model discussed above, which combines the end-use modeling concepts with traditional regression analysis techniques. For the commercial class, the Company forecasts sales using regression analysis techniques with non-manufacturing employment and non-farm employment designated as the major economic drivers, in addition to weather-related variables. Monthly sales for the commercial class are forecast directly from historical sales volumes, not as a product of the use per customer and number of customers. 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 Company’s RBM’s. Although the scale is much smaller, the treatment of large commercial additions is similar to the methodology for large industrial customer sales, which is discussed below. Monthly sales for irrigation and street lighting are forecast directly from historical sales volumes, not as a product of the use per customer and number of customers. PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 14 The majority of industrial sales are modeled using regression analysis with trend and economic variables. Manufacturing employment is used as the major economic driver in all states with exception of Utah, in which an Industrial Production Index is used. For a small number of the very largest industrial customers, the Company prepares individual forecasts based on input from the customer and information provided by the RBM’s. After the Company develops the forecasts of monthly energy sales by customer class, a forecast of hourly loads is developed in two steps. First, monthly peak forecasts are developed for each state. The monthly peak model uses historical peak producing weather for each state, and incorporates the impact of weather on peak loads through several weather variables that drive heating and cooling usage. The weather variables include the average temperature on the peak day and lagged average temperatures from up to two days before the day of the forecast. The peak forecast is based on average monthly historical peak-producing weather for the 20-year period, 1996 through 2015. Second, the Company develops hourly load forecasts for each state using hourly load models that include state-specific hourly load data, daily weather variables, the 20-year average temperatures as identified above, a typical annual weather pattern, and day-type variables such as weekends and holidays as inputs to the model. The hourly loads are adjusted to match the monthly peaks from the first step above. Hourly loads are then adjusted so the monthly sum of hourly loads equals monthly sales plus line losses. After the hourly load forecasts are developed for each state, hourly loads are aggregated to the total system level. The system coincident peaks can then be identified, as well as the contribution of each jurisdiction to those monthly peaks. Sales Forecast at the Customer Meter This section provides total system and state-level forecasted retail sales summaries measured at the customer meter by customer class including load reduction projections from new energy efficiency measures from the 2017 IRP preferred portfolio. Table A.8 – System Annual Retail Sales Forecast 2017 through 2026, post-DSM Year Residential Commercial Industrial Irrigation Lighting Public Authority Total 2017 15,760,322 16,973,309 19,610,575 1,402,815 142,837 280,969 54,170,827 2018 15,665,011 17,100,676 19,507,344 1,392,957 143,073 280,959 54,090,019 2019 15,535,613 17,165,098 19,643,268 1,381,347 143,191 280,959 54,149,477 2020 15,362,775 17,233,844 19,795,688 1,369,343 143,651 281,715 54,187,017 2021 15,210,722 17,262,252 19,845,887 1,357,840 143,273 280,959 54,100,934 2022 15,217,032 17,346,947 19,968,520 1,347,604 143,286 280,959 54,304,348 2023 15,222,916 17,445,564 20,161,584 1,336,707 143,293 280,959 54,591,023 2024 15,313,009 17,579,119 20,252,811 1,322,691 143,701 281,715 54,893,047 2025 15,205,483 17,645,518 20,422,452 1,291,633 143,297 280,959 54,989,343 2026 15,213,345 17,741,890 19,943,873 1,243,850 143,298 280,959 54,567,215 2017-26 -0.4%0.5%0.2%-1.3%0.0%0.0%0.1% Average Annual Growth Rate System Retail Sales – Megawatt-hours (MWh) PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 15 Residential Over the 2017-2026 timeframe, the average annual growth of the residential class sales forecast declined from -0.1 percent in the 2015 IRP Update to -0.4 percent in the 2017 IRP. The number of residential customers across PacifiCorp’s system is expected to grow at an annual average rate of 1.0 percent, reaching approximately 1.8 million customers in 2026, with Rocky Mountain Power states adding 1.4 percent per year and Pacific Power states adding 0.4 percent per year. New customers on PacifiCorp’s system will also contribute to declining average use of the residential class. It is expected that new single-family homes are likely to use more efficient appliances and use gas instead of electricity for both space and water heating. Commercial Average annual growth of the commercial class sales forecast increased from 0.0 percent annual average growth in the 2015 IRP Update to 0.5 percent expected average annual growth. The number of commercial customers across PacifiCorp’s system is expected to grow at an annual average rate of 0.9 percent, reaching approximately 223,000 customers in 2026, with Rocky Mountain Power states adding 1.2 percent per year and Pacific Power states adding 0.4 percent per year. The Company lowered its commercial load expectations in Oregon, Wyoming and Washington in the 2017 IRP load forecast due to lower than expected loads and adverse economic conditions for particular commercial sectors. Industrial Average annual growth of the industrial class sales forecast declined from 0.5 percent annual average growth in the 2015 IRP Update to 0.2 percent expected annual growth. A portion of the Company’s industrial load is in the extractive industry in Utah and Wyoming; therefore, changes in commodity prices can impact the Company’s load forecast. The Company has seen several large industrial customers cancel expected new load when prices have fallen. The risk to the Company’s load forecast due to commodity price changes is reflected in the high and low economic growth scenarios discussed below. PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 16 State Summaries Oregon Table A.9 summarizes Oregon state forecasted retail sales growth by customer class. Table A. 9 – Forecasted Retail Sales Growth in Oregon, post-DSM Washington Table A.10 summarizes Washington state forecasted retail sales growth by customer class. Table A.10 – Forecasted Retail Sales Growth in Washington, post-DSM Year Residential Commercial Industrial Irrigation Lighting Total 2017 5,408,380 5,076,308 1,849,639 330,637 37,893 12,702,857 2018 5,393,855 5,115,251 1,769,573 327,078 37,923 12,643,680 2019 5,378,539 5,098,874 1,763,691 322,898 37,934 12,601,937 2020 5,293,038 5,103,759 1,762,377 318,439 38,046 12,515,659 2021 5,223,123 5,104,908 1,770,168 313,909 37,941 12,450,049 2022 5,229,132 5,103,511 1,774,498 309,780 37,941 12,454,862 2023 5,234,327 5,106,544 1,794,852 305,586 37,942 12,479,251 2024 5,263,095 5,136,531 1,803,903 300,173 38,049 12,541,752 2025 5,236,271 5,145,302 1,826,703 294,032 37,942 12,540,250 2026 5,230,030 5,155,635 1,844,084 287,757 37,942 12,555,448 2017-26 -0.37%0.17%-0.03%-1.53%0.01%-0.13% Oregon Retail Sales – Megawatt-hours (MWh) Average Annual Growth Rate Year Residential Commercial Industrial Irrigation Lighting Total 2017 1,575,461 1,415,068 772,436 157,910 10,231 3,931,105 2018 1,572,606 1,430,519 764,944 157,185 10,227 3,935,480 2019 1,568,255 1,449,111 754,477 156,282 10,228 3,938,353 2020 1,562,912 1,460,871 742,346 155,494 10,256 3,931,880 2021 1,549,095 1,476,203 726,969 154,890 10,227 3,917,385 2022 1,544,682 1,495,077 707,110 154,532 10,227 3,911,628 2023 1,539,012 1,517,008 689,349 154,010 10,227 3,909,606 2024 1,542,678 1,537,227 676,877 152,734 10,256 3,919,772 2025 1,531,595 1,557,097 666,360 151,066 10,227 3,916,346 2026 1,528,077 1,576,410 655,792 149,274 10,227 3,919,780 2017-26 -0.34%1.21%-1.80%-0.62%0.00%-0.03% Washington Retail Sales – Megawatt-hours (MWh) Average Annual Growth Rate PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 17 California Table A.11 summarizes California state forecasted sales growth by customer class. Table A.11 – Forecasted Retail Sales Growth in California, post-DSM Utah Table A.12 summarizes Utah state forecasted sales growth by customer class. Table A.12 – Forecasted Retail Sales Growth in Utah, post-DSM Year Residential Commercial Industrial Irrigation Lighting Total 2017 363,268 233,137 59,312 96,753 2,421 754,891 2018 361,543 228,011 59,389 96,523 2,415 747,882 2019 360,225 223,517 59,337 96,063 2,415 741,557 2020 360,738 216,437 58,516 95,553 2,422 733,666 2021 357,443 211,498 58,100 94,980 2,415 724,437 2022 356,265 207,254 57,817 94,489 2,415 718,240 2023 354,361 204,046 57,719 93,948 2,415 712,489 2024 354,910 200,624 57,479 93,239 2,422 708,674 2025 351,419 197,037 57,138 92,501 2,415 700,511 2026 349,167 193,931 56,803 91,810 2,415 694,126 2017-26 -0.44%-2.03%-0.48%-0.58%-0.03%-0.93% Average Annual Growth Rate California Retail Sales – Megawatt-hours (MWh) Year Residential Commercial Industrial Irrigation Lighting Public Authority Total 2017 6,696,419 8,402,810 8,329,787 199,895 77,765 280,969 23,987,646 2018 6,625,352 8,470,814 8,317,408 196,470 77,982 280,959 23,968,985 2019 6,526,580 8,528,238 8,422,789 192,466 78,087 280,959 24,029,121 2020 6,454,747 8,575,851 8,504,675 188,368 78,358 281,715 24,083,714 2021 6,410,141 8,588,882 8,572,928 184,763 78,164 280,959 24,115,838 2022 6,420,793 8,648,462 8,671,514 181,250 78,176 280,959 24,281,155 2023 6,433,763 8,713,821 8,773,258 177,495 78,182 280,959 24,457,479 2024 6,484,638 8,788,396 8,884,190 173,538 78,404 281,715 24,690,881 2025 6,440,021 8,839,447 8,984,607 154,147 78,186 280,959 24,777,368 2026 6,463,388 8,896,420 8,396,408 118,936 78,187 280,959 24,234,297 2017-26 -0.39%0.64%0.09%-5.61%0.06%0.00%0.11% Utah Retail Sales – Megawatt-hours (MWh) Average Annual Growth Rate PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 18 Idaho Table A.13 summarizes Idaho state forecasted sales growth by customer class. Table A.13 – Forecasted Retail Sales Growth in Idaho, post-DSM Wyoming Table A.14 summarizes Wyoming state forecasted sales growth by customer class. Table A.14 – Forecasted Retail Sales Growth in Wyoming, post-DSM Alternative Load Forecast Scenarios The purpose of providing alternative load forecast cases is to determine the resource type and timing impacts resulting from a change in the economy or system peaks as a result of higher than normal temperatures. The December 2016 forecast is the baseline scenario. For the high and low economic growth scenarios assumptions from IHS Global Insight were applied to the economic drivers in the Year Residential Commercial Industrial Irrigation Lighting Total 2017 690,259 474,749 1,735,017 594,801 2,634 3,497,459 2018 689,058 485,148 1,735,211 593,351 2,634 3,505,401 2019 686,683 495,579 1,735,443 591,908 2,634 3,512,247 2020 677,472 508,489 1,736,923 590,466 2,641 3,515,992 2021 672,104 516,761 1,736,760 589,043 2,634 3,517,301 2022 672,994 528,327 1,737,300 587,953 2,634 3,529,207 2023 675,008 541,033 1,737,637 586,913 2,634 3,543,225 2024 680,047 553,976 1,738,600 585,564 2,641 3,560,828 2025 678,023 562,833 1,737,847 584,140 2,634 3,565,476 2026 678,865 572,063 1,737,599 582,674 2,634 3,573,835 2017-26 -0.18%2.09%0.02%-0.23%0.00%0.24% Idaho Retail Sales – Megawatt-hours (MWh) Average Annual Growth Rate Year Residential Commercial Industrial Irrigation Lighting Total 2017 1,026,536 1,371,237 6,864,383 22,819 11,893 9,296,868 2018 1,022,597 1,370,933 6,860,818 22,349 11,893 9,288,592 2019 1,015,332 1,369,779 6,907,530 21,730 11,893 9,326,263 2020 1,013,869 1,368,436 6,990,851 21,023 11,928 9,406,107 2021 998,816 1,363,999 6,980,961 20,255 11,893 9,375,925 2022 993,165 1,364,316 7,020,281 19,600 11,893 9,409,255 2023 986,444 1,363,112 7,108,770 18,754 11,893 9,488,973 2024 987,641 1,362,366 7,091,762 17,442 11,928 9,471,139 2025 968,155 1,343,801 7,149,796 15,747 11,893 9,489,391 2026 963,818 1,347,430 7,253,188 13,399 11,893 9,589,729 2017-26 -0.70%-0.19%0.61%-5.74%0.00%0.35% Wyoming Retail Sales – Megawatt-hours (MWh) Average Annual Growth Rate PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 19 Company’s load forecasting models. These growth assumptions were extended for the entire forecast horizon. Recognizing the volatility associated with the oil and gas extraction industries, PacifiCorp applied additional assumptions for the Utah and Wyoming industrial class load forecasts in the high and low scenario. Specifically, the Company focused on the increased uncertainty of the industrial load forecast as it moves further out in time. In order to capture this increased uncertainty the Company modeled 1,000 possible annual loads for each year based on the standard error of the medium scenario regression equation. The 1,000 load values are then ranked and the Company selected the 95th percentile and 5th percentile of the Utah and Wyoming industrial loads for both the low and high growth scenarios. For the 1-in-20 year (5 percent probability) extreme weather scenario, the Company used 1-in-20 year peak weather for summer (July) months for each state. The 1-in-20 year peak weather is defined as the year for which the peak has the chance of occurring once in 20 years. Figure A.11 shows the comparison of the above scenarios relative to the base case scenario. Figure A.11 – Load Forecast Scenarios for 1-in-20 Weather, High, Base Case and Low, pre-DSM 0.0 2,000.0 4,000.0 6,000.0 8,000.0 10,000.0 12,000.0 14,000.0 Me g a w a t t s ( M W ) 1-in-20 Weather High Base Case Low PACIFICORP – 2017 IRP APPENDIX A – LOAD FORECAST 20 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE APPENDIX B – IRP REGULATORY COMPLIANCE Introduction This appendix describes how PacifiCorp’s 2017 IRP complies with (1) the various state commission IRP standards and guidelines, (2) specific analytical requirements stemming from acknowledgment orders for the Company’s last IRP (“2015 IRP”), and (3) state commission IRP requirements stemming from other regulatory proceedings. Included in this appendix are the following tables: ● Table B.1 – 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 2015 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 Oregon IRP guidelines. ● Table B.4 – Provides an explanation of how this plan addresses each of the items contained in the Public Service Commission of Utah 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 updated in March 2016. General Compliance PacifiCorp prepares the IRP on a biennial basis and files the IRP with 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 opportunity to contribute information and ideas in the planning process, and also serves to inform all parties on the planning issues and approach. The public input process for this IRP, described in Volume I, Chapter 2 (Introduction), as well as Volume II, Appendix C (Public Input Process) fully complies with IRP Standards and Guidelines. The IRP provides a framework and plan for future actions to ensure PacifiCorp continues to provide reliable and least-cost electric service to its customers. The IRP evaluates, over a twenty- year planning period, the future loads of PacifiCorp customers and the resources required to meet this load. To fill any gap between changes in loads and existing resources, while taking into consideration potential early retirement of existing coal units as an alternative to investments that achieve compliance with environmental regulations, the IRP evaluates a broad range of available resource 1 California guidelines exempt a utility with less than 500,000 customers in the state from filing an IRP. However, PacifiCorp files its IRP and IRP supplements with the California Public Utilities Commission to address the Company plan for compliance with the California RPS requirements. 21 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE options, as required by state commission rules. These resource alternatives include supply-side, demand-side, and transmission alternatives. The evaluation of the alternatives in the IRP, as detailed in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach) and Chapter 8 (Modeling and Portfolio Selection Results) meets this requirement and includes the impact to system costs, system operations, supply and transmission reliability, and the impacts of various risks, 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 rigorous testing of a reasonably broad range of commercially feasible resource alternatives available to PacifiCorp on a consistent and comparable basis. The analytical process, including the risk and uncertainty analysis, fully complies with IRP Standards and Guidelines, and is described in detail in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach). The IRP analysis is designed to define a resource plan that is least cost, after consideration of risks and uncertainties. To test resource alternatives and identify a least-cost, risk adjusted plan, portfolio resource options were developed and tested against each other. This testing included examination of various tradeoffs among the portfolios, such as average cost versus risk, reliability, customer rate impacts, and average annual CO2 emissions. This portfolio analysis and the results and conclusions drawn from the analysis are described in Volume I, Chapter 8 (Modeling and Portfolio Selection Results). Consistent with the IRP Standards and Guidelines of Oregon, Utah, and Washington, this IRP includes an Action Plan in Volume I, Chapter 9 (Action Plan). The Action Plan details near-term actions that are necessary to ensure PacifiCorp continues to provide reliable and least-cost electric service after considering risk and uncertainty. The Action Plan also provides a progress report on action items contained in the 2015 IRP and 2015 IRP Update. The 2017 IRP and related Action Plan are filed with each commission with a request for acknowledgment. Acknowledgment means that a commission recognizes the IRP as meeting all regulatory requirements at the time of acknowledgment. In the case where a commission acknowledges the IRP in part or not at all, PacifiCorp works with the commission to modify and re-file an IRP that meets their acknowledgment standards. State commission acknowledgment orders or letters typically stress that an acknowledgment does not indicate approval or endorsement of IRP conclusions or analysis results. Similarly, an acknowledgment does not imply that favorable ratemaking treatment for resources proposed in the IRP will be given. California Public Utilities Code Section 454.52, mandates that the California Public Utilities Commission (CPUC) adopt a process for load serving entities to file an IRP beginning in 2017. In February 2016, the CPUC opened a rulemaking to adopt an IRP process and address the scope of the IRP to be filed with the CPUC. As of the date PacifiCorp’s 2017 IRP was finalized, the CPUC has not adopted any IRP requirements. 22 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Idaho The Idaho Public Utilities Commission’s Order No. 22299, issued in January 1989, specifies integrated resource planning requirements. The Order mandates that PacifiCorp submit a Resource Management Report (RMR) on a biennial basis. The intent of the RMR is to describe the status of IRP efforts in a concise format, and cover the following areas: Each utility's RMR should discuss any flexibilities 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, availability, lead time, reliability, risk, etc.) as future events unfold. This IRP is submitted to the Idaho PUC as the Resource Management Report for 2017, and fully addresses the above report components. Oregon This IRP is submitted to the Oregon PUC in compliance with its planning guidelines issued in January 2007 (Order No. 07-002). The Commission’s IRP guidelines consist of substantive requirements (Guideline 1), procedural requirements (Guideline 2), plan filing, 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), reliability (Guideline 11), distributed generation (Guideline 12), resource acquisition (Guideline 13), and flexible resource capacity (Order No. 12-0132). Consistent with the earlier guidelines (Order 89-507), the Commission notes that acknowledgment does not guarantee favorable ratemaking treatment, only that the plan seems reasonable at the time acknowledgment is given. Table B.3 provides detail on how this plan addresses each of the requirements. Utah This IRP is submitted to the Public Service Commission of Utah in compliance with its 1992 Order on Standards and Guidelines for Integrated Resource Planning (Docket No. 90-2035-01, “Report and Order on Standards and Guidelines”). Table B.4 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) (as amended, January 2006). 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 filed plan.” The rule requires PacifiCorp to submit a work plan for informal commission review not later than 12 months prior to the due date of the plan. The work plan is to lay out the contents of the IRP, the 2 Public Utility Commission of Oregon, Order No. 12-013, Docket No. 1461, January 19, 2012. 23 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE resource assessment method, and timing and extent of public participation. PacifiCorp filed a work plan with the Commission on March 30, 2016, in Docket UE-160353. Table B.5 provides detail on how this plan addresses each of the rule requirements. Wyoming Wyoming Public Service Commission issued new rules that replaced the previous set of rules on March 21, 2016. Chapter 3, Section 33 outlines the requirements on filing IRPs for any utility serving Wyoming customers. The rule, shown below, went into effect in March 2016. Table B.6 provides detail on how this plan addresses the rule requirements. Section 33. Integrated Resource Plan (IRP). Each utility serving in Wyoming that files an IRP in another jurisdiction shall file that IRP with the Commission. The Commission may require any utility to file an IRP. 24 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Table B.1 – Integrated Resource Planning Standards and Guidelines Summary by State Order No. 07-002, Investigation Into Integrated Resource Planning, January 8, 2007, as amended by Order No. 07-047. Order No. 08-339, Investigation into the Treatment of CO2 Risk in the Integrated Resource Planning Process, June 30, 2008. Order No. 09-041, New Rule OAR 860-027-0400, implementing Guideline 3, “Plan Filing, Review, and Updates”. Order No. 12-013, “Investigation of Matters related to Electric Vehicle Charging”, January 19, 2012. Docket 90-2035-01 Standards and Guidelines for Integrated Resource Planning June 18, 1992. cost planning, May 19, 1987, and as amended from WAC 480-100-238 Least Cost Planning Rulemaking, January 9, 2006 (Docket # UE-030311) Electric Utility Conservation Standards and Practices January, 1989. and Water Utilities, Chapter 3, Section 33, March 21, 2016. Filing Requirements Least-cost plans must be filed with the Commission. Plan (IRP) is to be submitted to Commission. the Commission. Plan to be developed with consultation of Commission staff, and with public involvement. Management Report” (RMR) on planning status. Also file progress reports on conservation, low-income programs, lost opportunities and capability building. Wyoming that files and IRP in another jurisdiction, shall file the IRP with the Commission. 25 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Frequency within two years of its previous IRP acknowledgment order. An annual update to the most recently acknowledged IRP is required to be filed on or before the one-year anniversary of the acknowledgment order date. While informational only, utilities may request acknowledgment of proposed changes to the action plan. biennially. Conservation reports to be filed annually. Low income reports to be filed at least annually. Lost Opportunities reports to be filed at least annually. Capability building reports to be filed at least annually. require any utility to file an IRP. Commission Response Least-cost plan (LCP) acknowledged if found to comply with standards and guidelines. A decision made in the LCP process does not guarantee favorable rate- making treatment. The OPUC may direct the utility to revise the IRP or conduct additional analysis before an acknowledgment order is issued. Note, however, that Rate Plan legislation allows pre-approval of near-term resource investments. found to comply with standards and guidelines. Prudence reviews of new resource acquisitions will occur during rate making proceedings. considered, with other available information, when evaluating the performance of the utility in rate proceedings. WUTC sends a letter discussing the report, making suggestions and requirements and acknowledges the report. pre-approval of proposed resource acquisitions. Idaho sends a short letter stating that they accept the filing and acknowledge the report as satisfying Commission requirements. staff reviews the IRP as directed by the Commission and drafts a memo to report its findings to the Commission in an open meeting or technical conference. 26 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Process utilities are allowed significant involvement in the preparation of the plan, with opportunities to contribute and receive information. Order 07-002 requires that the utility present IRP results to the OPUC at a public meeting prior to the deadline for written public comments. Commission staff and parties should complete their comments and recommendations within six months after IRP filing. Competitive secrets must the public at all stages. IRP developed in consultation with the Commission, its staff, with ample opportunity for public input. Commission staff, develop and implement a public involvement plan. Involvement by the public in development of the plan is required. PacifiCorp is required to submit a work plan for informal commission review not later than 12 months prior to the due date of the plan. The work plan is to lay out the contents of the IRP, resource assessment method, and timing and extent of public participation. Commission staff when reviewing and updating RMRs. Regular public workshops should be part of process. conducted in accordance with guidelines set from time to time as conditions warrant. The Public Service in its Letter Order on PacifiCorp’s 2008 IRP (Docket No. 2000-346-EA-09) adopted Commission Staff’s recommendation to expand the review process to include a technical conference, an expanded public comment period, and filing of reply comments. Focus effects, and a short-term (two-year) action plan. The IRP process should result in the selection of that mix of options which yields, for society over the long run, the best combination of expected costs and variance of costs. term (four-year) action plan. Specific actions for the first two years and anticipated actions in the second two years to be detailed. The IRP process should result in the selection of the optimal set of resources given the expected combination of costs, risk and uncertainty. term (two-year) action plan. The plan describes mix of resources sufficient to meet current and future loads at “lowest reasonable” cost to utility and ratepayers. Resource cost, market volatility risks, demand-side resource uncertainty, resource dispatchability, ratepayer risks, policy impacts, and environmental risks, must be considered. obligations at least-cost, with equal consideration to demand side resources. Plan to address risks and uncertainties. Emphasis on clarity, understandability, resource capabilities and planning flexibility. cost/least-risk resources and discussion of deviations from least-cost resources or resource combinations. 27 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Elements • All resources evaluated on a consistent and comparable basis. • Risk and uncertainty must be considered. • The primary goal must be least cost, consistent with the long-run public interest. • The plan must be consistent with Oregon and federal energy policy. • External costs must be considered, and quantified where possible. OPUC specifies environmental adders (Order No. 93-695, Docket UM 424). • Multi-state utilities should plan their generation and transmission systems on an integrated- system basis. • Construction of resource portfolios over the range of identified risks and uncertainties. • Portfolio analysis shall include fuel transportation and • Range of forecasts of future load growth • Evaluation of all present and future resources, including demand side, supply side and market, on a consistent and comparable basis. • Analysis of the role of competitive bidding • A plan for adapting to different paths as the future unfolds. • A cost effectiveness methodology. • An evaluation of the financial, competitive, reliability and operational risks associated with resource options, and how the action plan addresses these risks. • Definition of how risks are allocated between ratepayers and shareholders • A range of forecasts of future demand using methods that examine the effect of economic forces on the consumption of electricity and that address changes in the number, type and efficiency of electrical end-uses. • An assessment of commercially available conservation, including load management, as well as an assessment of currently employed and new policies and programs needed to obtain the conservation improvements. • Assessment of a wide range of conventional and commercially available nonconventional generating technologies • An assessment of transmission system capability and reliability. • A comparative evaluation of energy supply resources (including transmission and distribution) and improvements in conservation using considered including: • Load forecast uncertainties; • Known or potential changes to existing resources; • Equal consideration of demand and supply side resource options; • Contingencies for upgrading, optioning and acquiring resources at optimum times; • Report on existing resource stack, load forecast and additional resource menu. Proposed Commission Staff guidelines issued July 2016 cover: • Sufficiency of the public comment process • Utility strategic goals, resource planning goals and preferred resource portfolio • Resource need over the near-term and long- term planning horizons • Types of resources considered • Changes in expected resource acquisitions and load growth from the previous IRP • Environmental impacts considered • Market purchase evaluation • Reserve margin analysis • Demand-side management and conservation options 28 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE requirements. • Plan includes conservation potential study, demand response resources, environmental costs, and distributed generation technologies. • Avoided cost filing required within 30 days of acknowledgment. cost” criteria. • Integration of the demand forecasts and resource evaluations into a long-range (at least 10 years) plan. • All plans shall also include a progress report that relates the new plan to the previously filed plan. 29 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Table B.2 – Handling of 2015 IRP Acknowledgment and Other IRP Requirements Idaho Case No. PAC-E-15-04, Order No. 33396 conducting a reasonable evaluation, similar to the Wind Integration Study previously commissioned, of the costs and benefits associated with the integration of integration as part of Volume II, Appendix H (Flexible Reserve Study) of the 2017 IRP. Oregon Order No. 14- 252, p. 3 PacifiCorp will appear before the Commission to provide quarterly updates on coal plant compliance requirements, legal proceedings, pollution control investments, and other major capital expenditures on its coal plants or transmission projects. PacifiCorp may provide a written report and need not appear if there are no significant changes between the quarterly updates. moving the date of the first meeting from the third quarter of 2014 to the fourth quarter of 2014. Order No. 16-071 further streamlined this requirement by requiring the company to continue to provide twice yearly updates on the status of DSM IRP acquisition goals at public meetings and include in these updates information on future coal plant and transmission investment decisions. Also include information on 111(d) rule compliance analysis; Environmental/coal and transmission expenditures quarterly presentations were made at Commission special public meetings on October 28, 2014 and March 16, 2015. Quarterly presentations via written reports were provided on June 30, 2015 and October 1, 2015. The 2015 fourth quarter presentation was made at the Commission special public meeting on December 17, 2015. A biannual DSM update was provided at the Commission public meetings on March 10, 2015 and December 15, 2015 Biannual presentations for both Environmental/coal and transmission expenditures/111(d) and DSM were provided on August 30, 2016 and December 20, 2016. Please see Commission website for public meeting history and Docket RE 163 for presentations and written reports provided. 252, p. 3 • Timelines and key decision points for expected pollution control options and transmission investments; and • Tables detailing major planned expenditures with estimated costs in each year for each plant or transmission project, under different modeled scenarios in its 2017 IRP. See case study fact sheets (Volume II, Appendix M (Case Study Fact Sheets) for discussion on specific Regional Haze assumptions. For modeling purposes PacifiCorp has included incremental transmission costs associated with specific resources. See Volume I, Chapter 6 30 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Reference IRP Requirement or Recommendation How the Requirement or Recommendation is Addressed in the 2017 IRP costs. Additional detail is provided on the data discs included with the 2017 IRP filing. 252, p. 13 Commission provided the following recommendation: As part of the 2015, 2017, and 2019 IRPs, PacifiCorp will provide an updated version of the screening tool spreadsheet model that was provided to participants in competing retirement scenarios. The variety of retirement scenarios represented by the Regional Haze cases and the addition of an endogenous retirement case in the 2017 IRP has made the use of this tool unnecessary. 252, p. 16 yearly Class 1 and Class 2 DSM acquisition targets in both GWh and MW for each year in the planning period, by Management Resources) for the breakdown by state and year for both energy and capacity selected for the preferred portfolio. 071, Appendix A, p.1 (action item 1a-1c) costs. Provide analysis of the system benefits of storage. Capacity Contribution Study), and two energy storage sensitivities (Storage – Battery, Storage – CAES) described in Volume I, Chapter 8 (Modeling 071, p. 4 enacted, PacifiCorp will revisit action item 1c, to conclude negotiations with shortlisted bids from the Company’s 2013 RFP seeking up to 7 MW of qualifying solar capacity, and bring forth its 071, p. 4 update its Clean Power Plan modeling in its 2015 IRP update or its next IRP (depending on when Oregon’s compliance plan is known) to correctly reflect the final rule and Oregon’s implementation plan. the Clean Power Plan, however, at the time of the 2017 IRP, the rule is stayed and Oregon has not issued a draft or final implementation plan therefore Oregon’s compliance plan is not known and not reflected in the 2017 IRP. The 2017 IRP does include two Clean Power Plan modeling assumptions (CPP(a) and CPP(b)) plus two Clean Power Plan sensitivities (Mass Cap C and Mass Cap D), described in Volume I, Chapter 8 (Modeling and 071, Appendix A, p.1 (action item 2a) Order No. 16- 071, p. 5 assumed levels of trading hub liquidity and depth. The Commission noted that the Company has committed to conducting a market reliance risk analysis and urge the Company to also address concerns about reliance on Front Office Transactions in Adequacy Evaluation). 071, Appendix A, p.1 (action item 3a) months of this order, potential demand response pilot programs including: a time- varying rate pilot, peak-time rebate, and direct load control programs for other Commission at the August 16, 2016 public meeting. Ongoing. The Company engaged stakeholders in the development of its proposed transportation 31 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Reference IRP Requirement or Recommendation How the Requirement or Recommendation is Addressed in the 2017 IRP demand bidding programs. Engage Oregon stakeholders in an informal process to address increased voluntary participation in time-of-use pricing and present the outcome of this informal process to the Portfolio Options vehicle owners. The Company plans to promote the benefits of time-of-use rates to customers through its proposed Outreach and Education program, if present initial strategies to promote time-of-use rates to current and potential electric vehicle owners to the POC. 071, p. 5 pilot program, the Commission directs PacifiCorp to design and present additional pilots. demand response pilot opportunities at the Commission’s August 16, 2016 public input meeting and explained that the 2017 IRP would inform whether the Company would propose 071, Appendix A, p.1 (action item 3b) on the status of DSM IRP acquisition goals at public meetings. Include in these updates information on future coal plant and transmission investment decisions, as a streamlined continuation of Order No. 14-288. Also include information on 111 (d) rule compliance analysis; Provide more risk analysis on portfolios that include accelerated energy efficiency as a resource; Include annual incremental summer and winter peak demand capacity (MW) corresponding to 2015 through 2018 Class 2 DSM annual energy savings targets; For the 2015 IRP Update, provide model run results of the preferred portfolio with base case DSM and with accelerated DSM for comparison purposes; Perform stochastic modeling on all acquisition goals to the Commission on August 30, 2016 and December 20, 2016. PacifiCorp did not conduct a sensitivity on accelerated DSM in the 2017 IRP. See Volume I, Chapter 8 (Modeling Portfolio Selection Results) for the annual summer and winter peak demand capacity (MW) for Class 2 DSM. PacifiCorp provided a portfolio comparison of its accelerated DSM study and the 2015 IRP Update preferred portfolio in Chapter 5 (Portfolio Development) of the 2015 IRP Update. See response to the second item above. PacifiCorp did not conduct a sensitivity on accelerated DSM in the 2017 IRP. 071, Appendix A, p.2 (action item 5a) and Order No. 16- 071, p. 9. Segments D, E, F, and H until PacifiCorp files its 2017 IRP. The Commission acknowledges this action item only to the extent of PacifiCorp’s permitting actions. The Commission expects to see updated analysis in the next IRP or before the Company makes significant commitments and Portfolio Evaluation Approach), Chapter 8 (Modeling and Portfolio Selection Results), and Chapter 9 (Action Plan) for updated analysis on the Company’s Energy Gateway transmission segments. 071, Appendix A, p.2 (action item 5b) of freed-up transmission due to plant closures; 2017 IRP, representing alternate retirement scenarios and accounting for the PVRR costs and benefits applicable to new resources 32 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Reference IRP Requirement or Recommendation How the Requirement or Recommendation is Addressed in the 2017 IRP capability between east and west balancing authority areas (BAAs) in modeling; 3. Incorporate an analysis of California Independent System Operator (CAISO) membership in the 2017 IRP as appropriate. freed- closures. 2. The transfer capability of west/east transmission availability (the ‘overlay’) is recognized in 2017 IRP modeling, consistent with the most current assumptions tied to operational practice. 3. California Senate Bill No. 350, which was passed in October 2015, authorizes the California legislature to consider making changes to current laws that would create an ISO up until the conclusion of the 2017 legislative session which ends September 15, 2017. In the event that legislation is passed, PacifiCorp will coordinate with its state regulatory authorities on evaluation of next steps. As such, an analysis of participation in a regional ISO is not included in the 2017 IRP. 071, Appendix A, p.2 (additional actions - modeling) regarding the west BAA winter peak load/resource balance and portfolios to meet this peak load; 2. Provide quantitative justification for the planning reserve margin of 13 percent; 3. Utilize the Balancing Authority's Area Control Error (ACE) Limit (BAAL) NERC standard in forthcoming wind integration studies, and confirm and demonstrate that the study is based on implementation of the BAAL standard; 4. Use the same regional haze assumptions when directly comparing Portfolio Selection Results) including winter and summer peak load and resource tables. 2. See Volume II, Appendix I (Planning Reserve Margin Study). The study concludes with a planning criteria that meets one day in 10 year planning targets at the lowest reasonable cost. 3. The Company’s Flexible Reserve Study (Appendix H) incorporates the specific requirements of the BAAL standard (BAL-001-2). 4. In the 2017 IRP, the least-cost, least-risk Regional Haze case is assumed for all subsequent portfolios. 071, Appendix A, p.3 (additional actions – Clean Power Plan Analysis) compliance paths, including mass-based solutions, with stochastic analysis for each; 2. Include the constraints needed for 111(d) rule compliance in all cost risk analysis (“PaR” analyses); 3. Estimate the effects of 111(d) rule compliance on western wholesale power prices; Power Plan modeling strategies (CPP(a) and CPP(b)) plus two Clean Power Plan sensitivities (Mass Cap C and Mass Cap D), described in Volume I, Chapter 8 (Modeling and Portfolio Selection Results) of the 2017 IRP. Portfolios are evaluated on the basis of stochastic modeling, analysis and metrics. 2. PaR uses optimized shadow prices to drive stochastic model behavior. Please refer to Volume I, Chapter 8 (Modeling and Portfolio 33 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Reference IRP Requirement or Recommendation How the Requirement or Recommendation is Addressed in the 2017 IRP update on 111 (d) rule compliance alternatives that do not double count Renewable Energy Credits (RECs) and the Emission Rate Credits (ERCs). 3. The price curves developed for CPP(a) and CPP(b) capture the effects of emissions policy on power prices. CO2 emissions, and therefore developed prices, are not significantly constrained by Clean Power Plan limits except under high gas price conditions. Please refer to Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach). 4. Clean Power Plan modeling for the 2017 IRP assumes a fixed cap on emissions, unaffected 071, p. 10. demonstrate that its upcoming wind integration study is based on implementation of the BAAL standard. H) incorporates the specific requirements of the BAAL standard (BAL-001-2). Utah Order, Docket No. 15-035-04, Benefit Tool type of transmission analytical tool in future IRPs, PacifiCorp should introduce and vet the tool in an IRP workshop setting prior to utilizing the IRP. -035-04, processes, to provide a stronger demonstration of the reasonableness of the range of renewable resource costs resource table and inputs at the August 25-26, 2016 public input meeting. The supply-side resource table was updated based on stakeholder feedback. -035-04, of distributed generation in the baseload forecast in its load and resource table, as it does for existing DSM and curtailment. Balance), which breaks out private generation in the same manner as DSM and interruptible load curtailment. -035-04, the depth of the western wholesale market, and to use sensitivity cases and acquisition path analysis, including development of a contingency plan, to monitor the feasibility of long-term reliance on Front Office Transactions to Adequacy Evaluation) for an evaluation of market depth, and also the Front Office Transaction sensitivity provided in Volume I, Chapter 8 (Modeling and Portfolio Selection Results). Also refer to acquisition path analysis for contingencies in Volume I, Chapter 9 (Action Plan). -035-04, planning reserve margin in future IRPs using results from both loss of load probability studies and analysis of the Margin Study). The study concludes with a planning criteria that meets one day in 10 year planning targets at the lowest reasonable cost. -035-04, Term Resource Acquisition Paths (Table 9.3 in the 2015 IRP) could be improved in terms of identifying potential exogenous changes that would cause a significant change in acquisition path. Encourage PacifiCorp in future IRPs to further define Volume I, Chapter 9 (Action Plan). 34 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Reference IRP Requirement or Recommendation How the Requirement or Recommendation is Addressed in the 2017 IRP would be required to potentially trigger movement to any of the different paths listed in the table. -035-04, the energy storage screening study in its 2017 IRP, update the storage cost assumptions, and consider modeling changes for energy storage following discussion with stakeholders. Request that PacifiCorp present the findings of the updated study, with the study authors accessible for stakeholder questions and Studies). PacifiCorp presented results of its updated Energy Storage Studies at the August 25-26, 2017 public input meeting with the study authors participating via phone. -035-04, examining the impact on Present Value Revenue Requirement and investment decisions of varying levels of Qualifying Facilities on the system. Direct PacifiCorp to develop a set of sensitivity runs addressing this issue following discussion with interested stakeholders. qualifying facility contracts, as of the time modeling assumptions are locked down, are considered in the resource mix when performing 2017 IRP analysis. Stakeholders did not request additional sensitivity cases to assess alternative qualifying facility penetration scenarios during the public input process. Such sensitivities would be difficult to produce, as it is not reasonably feasible to derive avoided cost pricing for hypothetical qualifying facility projects on the system as there is no information on project location or technology type. Without a sound avoided cost price estimate, which would significantly influence system costs under a qualifying facility sensitivity, PVRR cost -035-04, 2017 IRP how the effects of the federal standards on lighting technologies are Details). -035-04, future IRPs to present the Business Plan as a sensitivity case. If PacifiCorp has substantive objections to this requirement, PacifiCorp should file a motion for Commission action within 90 days of this order explaining the objection and presented in Volume I, Chapter 8 (Modeling and Portfolio Selection Results) consistent with the Order in Docket No. 15-035-04. Washington UE-140546, Acknowledgement Letter, practice of including data discs with the filing in future IRP filings. filing. Acknowledge ment Letter, p.2 evaluate how its method of developing capacity value of renewable resources compares to the effective load carrying capability method on which it was based, to ensure that the Company’s model is Capacity Contribution Study), analyzing updated hourly profiles and transmission availability impacts to determine effectiveness in meeting system load. The 2017 IRP also adds winter peak (in addition to summer peak) in its assumptions, allowing 35 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Reference IRP Requirement or Recommendation How the Requirement or Recommendation is Addressed in the 2017 IRP Acknowledge ment Letter, p.3 for both a trading system and carbon tax system in its 2017 IRP, and consult with commission staff regarding the appropriate assumptions and inputs. studies and an alternative CO2 price sensitivity. The CO2 price sensitivity reflects an alternative policy mechanism, without defining whether that policy is implemented as a tax or trading system, than what is contemplated in the Clean Power Plan. The effects of the policy (tax vs. trading system) would not influence the impacts on system variable costs. Under a CO2 tax, PacifiCorp would incur a direct cost for CO2 emissions. Under a CO2 trading system, presumably with some type of allowance allocation, PacifiCorp would be faced with either the direct cost of buying allowances from the market if its emissions were higher than its allowance allocation or the opportunity cost of not selling allowances into the market if its emissions were below its allowance allocation. Consequently, the impact on system dispatch and the associated variable costs is the same under a tax or trading Acknowledgement Letter, p.3 develop a supply curve of emissions abatement. This supply curve would identify, specific to Pacific Power, the available technologies and their associated costs that could reach a given emissions goal. This type of tool would lend increased transparency to the issue, and would allow the Company, regulators and stakeholders to engage in meaningful and informed conversations regarding the costs and benefits of reducing Pacific Power’s emissions. curve, as linear model optimizations are ideally suited to endogenously and simultaneously assess finely detailed and incremental trade-offs among resources, requirements and constraints to achieve least-cost least-risk outcomes influenced by dynamic market conditions. Emissions constraints are included in the simultaneous optimization of all resource (technology) selections, reflecting a PacifiCorp- specific marginal cost of compliance expressed in dollars per ton. In addition, six price-emissions scenarios were evaluated in each Regional Haze and core case. Variant CO2 sensitivities are also included in the 2017 IRP. Acknowledgement Letter, p.3 IRP S-15, but question approach in assuming the only compliance alternative would be to shut down Chehalis gas plant. It would be more appropriate to allow the model to conduct a full run to see if it can identify some other combination of compliance options consistent with the final CPP that would allow the Company to meet its obligations without have to double allocate renewable energy. Request that the Company provide such Update covering both Chehalis shutdown assumptions and the potential double-counting issue based on ERCs (2015 IRP Update, pages 61-62). ERCs are not explicitly included 2017 IRP analytics. Acknowledgement Letter, p.4 were on a system basis and the commission would like to see them on a balancing authority area basis. Requests the analysis be redone in the 2017 IRP and Selection Results) for a description regarding the West and East balancing authority area sensitivities and response to this request. 36 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Reference IRP Requirement or Recommendation How the Requirement or Recommendation is Addressed in the 2017 IRP explain why different inputs are more appropriate. Request that the Company incorporate the balancing area analysis in all future IRPs. Acknowledgement Letter, p.5 in-depth analysis of energy storage in its 2017 IRP. Analysis should include benefits associated with ancillary services such as frequency regulation and include batteries and other forms of storage. It should also value specific projects on Pacific Power’s system both at the transmission and distribution levels and ensure cost assumptions are based on and Storage – CAES) were conducted for the 2017 IRP, using updated cost assumptions. Please refer to Volume I, Chapter 8 (Modeling and Portfolio Selection Results) for a discussion of these sensitivity cases and energy storage. See also Volume II, Appendix P (Energy Storage Studies). Acknowledgement Letter, p.6 overall potential and levelized costs for demand response and add a sensitivity analysis that evaluates the portfolio impact of adding additional demand response resources. Encourage the Company to consider demand response along with traditional energy efficiency programs in the context of Clean Power Plan compliance planning. do not produce emissions, and with their selection in any portfolio, potentially defer emissions from alternative generating resources, are directly competitive with alternate strategies to keep total emissions below CPP limits. Also, in the 2017 IRP, core case DLC-1 includes the forced addition of Class 1 DSM resources equal to 5 percent of the incremental L&R balance estimated at the time the study was prepared. Please refer to Chapter 7 (Modeling and Portfolio Evaluation Approach) and Chapter 8 (Modeling and Portfolio Selection Acknowledgement Letter, p.7 compliance analysis in the 2015 IRP Update based on a more accurate projection of Washington’s future Update, page 57. Acknowledgement Letter, p.7 condition of the commission’s granting of the waivers requested in Docket UE- 151694, to conduct a market reliance risk assessment in conjunction with the 2017 IRP. Encourage the Company to work Resource Adequacy Evaluation) for an evaluation of market depth, and also the Front Office Transaction sensitivity provided in Volume I, Chapter 8 (Modeling and Portfolio Selection Results). Acknowledgement Letter, p.8 integrate the EIM into its IRP model, in particular to develop modeling capability to capture how different resources with different generation profiles would interact with the EIM, based on the Company’s experience with the market. Also expect the Company to work with staff on incorporating an analysis of CAISO membership in the 2017 IRP as appropriate. procurement diversity savings from the EIM in its Flexible Reserve Study. See Volume II, Appendix H (Flexible Reserve Study). California Senate Bill No. 350, which was passed in October 2015, authorizes the California legislature to consider making changes to current laws that would create an independent governance structure for a regional ISO up until the conclusion of the 2017 legislative session which ends September 15, 2017. In the event that legislation is passed, PacifiCorp will coordinate with its state regulatory 37 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Reference IRP Requirement or Recommendation How the Requirement or Recommendation is Addressed in the 2017 IRP included in the 2017 IRP. This is discussed further in Volume I, Chapter 3 (Planning Environment) of Wyoming The Wyoming Public Service Commission provided the following comment in its Letter Order (Docket No. 20000-474474-EA-15, record No. 14089, dated January 11, 2015) on PacifiCorp’s 2015 IRP: Pursuant to open meeting action taken on December 29, 2015, Rocky Mountain Power’s 2015 Integrated Resource Plan is hereby placed in the Commission’s files. No further action will be taken and this matter is closed. Table B.3 – Oregon Public Utility Commission IRP Standard and Guidelines 1.a.1 All resources must be evaluated on a consistent and comparable basis: All known resources for meeting the utility’s load should be considered, including supply- side options which focus on the generation, purchase and transmission of power – or gas purchases, transportation, and storage – and demand-side options which focus on conservation and demand response. including renewables, demand-side management, energy storage, power purchases, thermal resources, and transmission. Volume I, Chapter 4 (Transmission Planning), Chapter 6 (Resource Options), and Chapter 7 (Modeling and Portfolio 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 model based on load requirements, relative economics, resource size, and comparable basis: Utilities should compare different resource fuel types, technologies, lead times, in-service dates, durations and locations in portfolio risk modeling. subjected to Monte Carlo production cost simulation. These portfolios contained a variety of resource types with different fuel types (coal, gas, biomass, nuclear fuel, “no fuel” renewables), lead-times (ranging from front office transactions to nuclear plants), in-service dates, operational lives, and locations. See Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach), Chapter 8 (Modeling and Portfolio Selection Results), and Volume II, Appendix K (Detailed Capacity Expansion Results) and Appendix and comparable basis: Consistent assumptions and methods should be used for evaluation of all resources. company developed generic supply-side resource attributes based on a consistent characterization methodology. For demand-side resources, the company used the Applied Energy Group’s supply curve data developed for this IRP for representation of DSM resources. The study was based on a consistently applied methodology for determining technical, market, and achievable DSM potentials. All portfolio resources were evaluated using the same sets of price and load forecast inputs. These inputs are 38 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Guideline is Addressed in the 2017 IRP and Chapter 7 (Modeling and Portfolio Evaluation Approach) as well as Volume II, Appendix D (Demand-Side Management and Supplemental and comparable basis: The after-tax marginal weighted-average cost of capital (WACC) should be used to discount all future resource 6.57 percent to discount all cost streams. At a minimum, utilities should address the following sources of risk and uncertainty: 1. Electric utilities: load requirements, hydroelectric generation, plant forced outages, fuel prices, electricity prices, and costs to comply with any regulation of greenhouse gas 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 and evaluated via the 111(d) modeling approach. Additional scenario risk is used to evaluate load sensitivities. See Volume I, Chapter 7 (Modeling Utilities should identify in their plans any additional sources of risk and uncertainty. Chapter 9 (Action Plan). Regulatory and financial risks associated with resource and transmission investments are highlighted in several areas in the IRP document, including Volume I, Chapter 3 (The Planning Environment), Chapter 4 (Transmission), Chapter 7 (Modeling and Portfolio Evaluation Approach), and Chapter 8 (Modeling and Portfolio portfolio of resources with the best combination of expected costs and associated risks and uncertainties for the utility and its customers (“best cost/risk portfolio”). portfolios considered. See Volume I, Chapter 8 (Modeling and Portfolio Selection Results), Chapter 9 (Action Plan), and Volume II, Appendix K (Detailed Capacity Expansion Results) and Appendix L (Stochastic Production Cost Simulation Results) for the Company’s portfolio cost/risk analysis and 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 for portfolio modeling, and a real levelized revenue requirement methodology for treatment of end effects. requirement (PVRR) as the key cost metric. The plan should include analysis of current and estimated future costs for all long-lived resources such as power plants, gas storage facilities, and pipelines, as well as all short-lived resources such as gas supply and short- Evaluation Approach) provides a description of the PVRR methodology. minimum: production costs as the measure of cost variability. For 39 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Guideline is Addressed in the 2017 IRP measures the variability of costs and one that measures the severity of bad outcomes. PVRR (mean of highest three Monte Carlo iterations) and the 95th percentile stochastic production cost minimum: 2. Discussion of the proposed use and impact on costs and risks of physical and financial Chapter 9 (Action Plan). resource choices appropriately balance cost and risk. Selection Results) summarizes the results of PacifiCorp’s cost/risk tradeoff analysis, and describes what criteria the Company used to determine the best public interest as expressed in Oregon and federal energy policies. and federal energy/pollutant emission policies in portfolio modeling. Volume I, Chapter 7 describes the decision process used to derive portfolios, which includes consideration of state and federal resource policies and regulations that are summarized in Volume I, Chapter 3 (The Planning Environment). Volume I, Chapter 8 (Modeling and Portfolio Selection Results) provides the results. Volume I, Chapter 9 (Action Plan) presents an acquisition path analysis that describes resource strategies based on Guideline 2. Procedural Requirements should be allowed significant involvement in the preparation of the IRP. Involvement includes opportunities to contribute information and ideas, as well as to receive information. Parties must have an opportunity to make relevant inquiries of the utility formulating the plan. Disputes about whether information requests are relevant or unreasonably burdensome, or whether a utility is being properly responsive, may be submitted to the Volume I, Chapter 2 (Introduction) provides an overview of the public process, all public meetings held for the 2017 IRP, which are documented in Volume II, Appendix C (Public Input Process). PacifiCorp also made use of a Feedback Form for stakeholders to provide comments and offer suggestions. Feedback Forms along with the public meeting presentations and handouts are available on PacifiCorp’s webpage at: http://www.pacificorp.com/es/irp.html protected, the utility should make public, in its plan, 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 information the Company used for portfolio evaluation, as well as other data requested by stakeholders. PacifiCorp also provided stakeholders with non-confidential information to support public meeting discussions via email. Data discs will be available with public data. Additionally, data discs with confidential data will be protected through use of review and comment prior to filing a final plan with the Commission. review throughout the process prior to each of the public input meetings and solicited/and received feedback at various times when developing the 2017 40 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Guideline is Addressed in the 2017 IRP (Introduction), is consistent with materials presented in Volumes I and II of the 2017 IRP report. PacifiCorp requested and responded to comments from stakeholders in developing core case and sensitivity definitions. The Company considered comments received via Feedback Forms in developing Guideline 3: Plan Filing, Review, and Updates its previous IRP 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 may request an extension of its filing date from the plan to the Commission at a public meeting prior to the deadline for written public this IRP. their comments and recommendations within this IRP. recommendations on a utility’s plan at a public meeting before issuing an order on acknowledgment. The Commission may provide the utility an opportunity to revise the this IRP. utility regarding any additional analyses or actions that the utility should undertake in its update on its most recently acknowledged IRP. The update is due on or before the acknowledgment order anniversary date. Once a utility anticipates a significant deviation from its acknowledged IRP, it must file an update with the Commission, unless the utility is within six months of filing its next IRP. The utility must summarize the update at a Commission public meeting. The utility may request acknowledgment of changes in proposed this IRP. changes in proposed actions, the annual update is an informational filing that: • Describes what actions the utility has taken this IRP. 41 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Guideline is Addressed in the 2017 IRP • since the acknowledgment order that affects the action plan to select best portfolio of resources, including changes in such factors as load, expiration of resource contracts, supply-side and demand-side resource acquisitions, resource costs, and transmission availability; and • Justifies any deviations from the Guideline 4. Plan Components: in addition to stochastic load risk analysis with an explanation of major assumptions. temperature (one-in-twenty probability) load growth forecasts for scenario analysis using the System Optimizer model. Stochastic variability of loads was also captured in the risk analysis. See Volume I, Chapters 5 (Load and Resource Balance) and Chapter 7 (Modeling and Portfolio Evaluation Approach), and Volume II, Appendix A (Load Forecast) for load 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; modeling of all existing transmission rights, as well as future transmission additions associated with the on annual capacity and energy balances. Existing transmission rights are reflected in the IRP model topologies. Future transmission additions used in analyzing portfolios are summarized in Volume I, Chapter 4 (Transmission) and Chapter 7 (Modeling and Portfolio Evaluation Approach) side and demand side resource options, taking into account anticipated advances in technology. resources included in this IRP, and provides their detailed cost and performance attributes. Additional information on energy efficiency resource characteristics is available in Volume II, Appendix D (Demand-Side Management and Supplemental Resources) referencing additional information on PacifiCorp’s IRP Web, site see footnote 3 of this to provide reliable service, including cost-risk tradeoffs. reserve margin for all portfolios evaluated, as supported by an updated Stochastic Loss of Load Study in Volume II, Appendix I), the Company used several measures to evaluate relative portfolio supply reliability. These measures (Energy Not Served and Loss of Load Probability) are described in Volume I, Chapter 7 (Modeling and Portfolio Evaluation future (e.g., fuel prices and environmental Evaluation Approach) describes the key assumptions 42 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Guideline is Addressed in the 2017 IRP considered. summaries of assumptions used for each case portfolios to test various operating characteristics, resource types, fuels and sources, technologies, lead times, in-service dates, durations and general locations – system-wide or delivered to a specific portion of the portfolios designed to determine resource selection under a variety of input assumptions in Volume I, Chapters7 (Modeling and Portfolio Evaluation Approach) and Chapter 8 (Modeling and Portfolio Selection Results). portfolios over the range of identified risks and uncertainties. Selection Results) presents the stochastic portfolio modeling results, and describes portfolio attributes that explain relative differences in cost and risk portfolios by cost and risk metric, and Selection Results) provides tables and charts with combination of cost and risk for the utility and inconsistencies of the selected portfolio with any state and federal energy policies that may affect a utility’s plan and any barriers to state and federal energy policies therefore none are currently identified. utility intends to undertake over the next two to four years to acquire the identified resources, regardless of whether the activity was acknowledged in a previous IRP, with the key attributes of each resource specified as in IRP action plan. Guideline 5: Transmission utility for the fuel transportation and electric transmission required for each resource being considered. In addition, utilities should consider fuel transportation and electric transmission facilities as resource options, taking into account their value for making additional purchases and sales, accessing less costly resources in remote locations, acquiring alternative fuel supplies, and improving Gateway transmission project configurations on a consistent and comparable basis with respect to other resources. Where new resources would require additional transmission facilities the associated costs were factored into the analysis. Fuel transportation costs were factored into resource costs. Guideline 6: Conservation potential study is conducted periodically for its study was completed in 2017, and those results were 43 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Guideline is Addressed in the 2017 IRP funding for conservation programs in its service territory, the utility should include in its action plan all best cost/risk portfolio conservation resources for meeting projected resource needs, specifying annual savings targets. incorporate Oregon resource potential. Oregon potential estimates were provided by the Energy Trust of Oregon. See the demand-side resource section in Volume I, Chapter 6 (Resource Alternatives), the results in Volume I, Chapter 8 (Modeling and Portfolio Selection Results), the targeted amounts in Volume I, Chapter 9 (Action Plan) and the implementation steps outlined in Volume II, Appendix conservation programs in a utility’s service territory at a level of funding that is beyond the utility’s control, the utility should: 1. Determine 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 party’s projection of conservation acquisition. Guideline 7: Demand Response resources, including voluntary rate programs, on par with other options for meeting energy, capacity, and transmission needs (for electric utilities) or gas supply and transportation needs (Class 1 DSM) on a consistent basis with other resources. Guideline 8: Environmental Costs utility should construct a base-case scenario to reflect what it considers to be the most likely regulatory compliance future for carbon dioxide (CO2), nitrogen oxides, sulfur oxides, and mercury emissions. The utility should develop several compliance scenarios ranging from the present CO2 regulatory level to the upper reaches of credible proposals by governing entities. Each compliance scenario should include a time profile of CO2 compliance requirements. The utility should identify whether the basis of those requirements, or “costs,” would be CO2 taxes, a ban on certain types of resources, or CO2 caps (with or without flexibility mechanisms such as allowance or credit trading as a safety valve). The analysis should recognize significant and important upstream emissions that would likely have a significant impact on resource decisions. Each compliance scenario should maintain logical consistency, to the extent practicable, between the CO2 regulatory requirements and other key Evaluation Approach). For the 2017 IRP PacifiCorp used the EPA’s proposed 11(d) rule as the basis for future regulations. The proposed rules limit carbon emissions either through a state-level rate per MWh, or a hard cap amount. PacifiCorp looked at both approaches in determining portfolio selections. PacifiCorp examined compliance through EPA’s 111(d) along with a carbon tax adder. 44 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Guideline is Addressed in the 2017 IRP compliance scenarios: The utility should estimate, under each of the compliance scenarios, the present value revenue requirement (PVRR) costs and risk measures, over at least 20 years, for a set of reasonable alternative portfolios from which the preferred portfolio is selected. The utility should incorporate end-effect considerations in the analyses to allow for comparisons of portfolios containing resources with economic or physical lives that extend beyond the planning period. The utility should also modify projected lifetimes as necessary to be consistent with the compliance scenario under analysis. In addition, the utility should include, if material, sensitivity analyses on a range of reasonably possible regulatory futures for nitrogen oxides, sulfur oxides, and mercury to further inform the Simulation Results) provides the Stochastic mean PVRR versus upper tail mean less stochastic mean PVRR scatter plot diagrams that for a broad range of portfolios developed with a range of compliance scenarios as summarized in 8.a above. The Company considers end-effects in its use of Real Levelized Revenue Requirement Analysis, as summarized in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach) and uses a 20-year planning horizon. Early retirement and gas conversion alternatives to coal unit environmental investments were considered in the development of all resource portfolios. Alternate scenarios were applied in the 2017 IRP to capture the possibility of more stringent Regional identify at least one CO2 compliance “turning point” scenario, which, if anticipated now, would lead to, or “trigger” the selection of a portfolio of resources that is substantially different from the preferred portfolio. The utility should develop a substitute portfolio appropriate for this trigger-point scenario and compare the substitute portfolio’s expected cost and risk performance to that of the preferred portfolio – under the base case and each of the above CO2 compliance scenarios. The utility should provide its assessment of whether a CO2 regulatory future that is equally or more stringent that the identified trigger point will be Evaluation Approach) for a description of core case definitions. Regional Haze cases were developed to represent “triggered” portfolios with coal unit retirements and gas conversions that differ substantially from the preferred portfolio. PacifiCorp also performed CO2 price sensitivities showing portfolios that differ significantly from the preferred portfolio. Comparative analysis of these case results is included in Volume I, Chapter 8 (Modeling and Portfolio Selection Results). above portfolios is consistent with Oregon energy policies (including state goals for reducing greenhouse gas emissions) as those policies are applied to the utility, the utility should construct the best cost/risk portfolio that achieves that consistency, present its cost and risk parameters, and compare it to those in the state goals for reducing greenhouse gas emissions. These cases are summarized in Volume I, Chapter 8 (Modeling and Portfolio Selection Results). Guideline 9: Direct Access Loads should exclude customer loads that are effectively committed to service by an alternative electricity supplier. option for eligible PacifiCorp customers. Going forward PacifiCorp will cease planning for customers who elect direct-access service on a long-term basis Guideline 10: Multi-state Utilities 45 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Guideline is Addressed in the 2017 IRP and transmission systems, or gas supply and delivery, on an integrated system basis that achieves a best cost/risk portfolio for all their retail customers. approach as stated in Volume I, Chapter 2 under the section “The Role of PacifiCorp’s Integrated Resource Planning”. The Company notes the challenges in complying with multi-state integrated planning given differing state energy policies and resource Guideline 11: Reliability within the risk modeling of the actual portfolios being considered. Loss of load probability, expected planning reserve margin, and expected and worst-case unserved energy should be determined by year for top-performing portfolios. Natural gas utilities should analyze, on an integrated basis, gas supply, transportation, and storage, along with demand-side resources, to reliably meet peak, swing, and base-load system requirements. Electric and natural gas utility plans should demonstrate that the utility’s chosen portfolio achieves its (Modeling and Portfolio Selection Results) walks through the role of reliability, cost, and risk measures in determining the preferred portfolio. Scatter plots of portfolio cost versus risk at different CO2 cost levels were used to inform the cost/risk tradeoff analysis. Guideline 12: Distributed Generation generation technologies on par with other supply-side resources and should consider, and quantify where possible, the additional benefits of distributed generation. estimates of expected private generation penetration. The study was incorporated in the analysis as a deduction to load. Sensitivities looked at both high and low penetration rates for private generation. The study is included in Volume II, Appendix P (Energy Guideline 13: Resource Acquisition 1. Identify its proposed acquisition strategy for each resource in its action plan. 2. Assess the advantages and disadvantages of owning a resource instead of purchasing power from another party. 3. Identify any Benchmark Resources it plans to consider in competitive bidding. approaches for resources identified in the preferred portfolio. A discussion of the advantages and disadvantages of owning a resource instead of purchasing it is included in Chapter 9 (Action Plan). PacifiCorp has not at this time identified any specific benchmark resources it plans to consider in the competitive bidding process summarized in the 2017 Flexible Capacity Resources The electric utilities shall forecast the balancing reserves needed at different time intervals (e.g. ramping needed within 5 minutes) to respond to variation in load and intermittent renewable 46 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Guideline is Addressed in the 2017 IRP electric utilities shall forecast the balancing reserves available at different time intervals (e.g. ramping available within 5 minutes) from existing generating resources over the 20-year and Comparable Basis: In planning to fill any gap between the demand and supply of flexible capacity, the electric utilities shall evaluate all resource options, including the use of EVs, on a Table B.4 – Utah Public Service Commission IRP Standard and Guidelines 1 The Commission has the legal authority to promulgate Standards and Guidelines for of Utah responsibility. method for developing and implementing the IRP process. will occur during ratemaking proceedings. acknowledges that prudence reviews will occur during ratemaking proceedings, outside of the IRP will be open to the public at all stages. The Commission, its staff, the Division, the Committee, appropriate Utah state agencies, and other interested parties can participate. The Commission will pursue a more active-directive role if deemed necessary, after formal review of Chapter 2 (Introduction). A record of public meetings is provided in Volume II, Appendix C (Public Input Process). attendant costs must be included in the integrated resource planning analysis. with externality cost adders to model environmental externality costs. See Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach) for a description of the methodology employed, including how CO2 cost uncertainty is factored into the determination of supply-side and demand-side resources on a consistent and comparable basis. were evaluated on a comparable basis using PacifiCorp’s capacity expansion optimization model. consistent with the Company's Integrated determination of avoided costs in Utah will be 47 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Standards and Guidelines are Addressed in the 2017 IRP the needs of the Utah service area, but since coordination with other jurisdictions is important, must not ignore the rules governing the planning from all state jurisdictions, and meets all formal state IRP guidelines. directly related to its Integrated Resource Plan. linkage between the 2017 IRP preferred portfolio and fall 2016 business plan resources. Significant resource differences are highlighted. The business plan portfolio was run consistent with requirements outlined in the Order issued by the Utah Public Service Commission on September 16, 2016, Docket Standards and Guidelines utility planning process which evaluates all known resources on a consistent and comparable basis, in order to meet current and future customer electric energy services needs at the lowest total cost to the utility and its customers, and in a manner consistent with the long-run public interest. The process should result in the selection of the optimal set of resources given the expected combination of costs, risk and uncertainty. Evaluation Approach) outlines the portfolio performance evaluation and preferred portfolio selection process, while Chapter 8 (Modeling and Portfolio Selection Results) chronicles the modeling and preferred portfolio selection process. This IRP also addresses concerns expressed by Utah stakeholders and the Utah commission concerning comprehensiveness of resources considered, consistency in applying input assumptions for portfolio modeling, and explanation of PacifiCorp’s decision process for selecting top-performing Plan biennially. 2015, and filed this IRP on April 4, 2017 meeting the Commission, its staff, the Division of Public Utilities, the Committee of Consumer Services, appropriate Utah state agencies and interested parties. PacifiCorp will provide ample opportunity for public input and information exchange during Chapter 2 (Introduction). A record of public meetings is provided in Volume II, Appendix C (Public Input Process). include: a range of estimates or forecasts of load growth, including both capacity (kW) and energy (kWh) requirements. both capacity expansion optimization scenarios as well as for stochastic variability, covering both capacity and energy. Details concerning the load forecasts used in the 2017 IRP are provided in Volume I, Chapter 5 (Load and Resource Balance) general class and will differentiate energy and capacity requirements. The Company will include in its forecasts all on-system loads and those off-system loads which they have a contractual obligation to fulfill. Non-firm off-system sales are differentiate energy and capacity requirements. See Volume I, Chapter 5 (Load and Resource Balance) and Volume II, Appendix A (Load Forecast Details). Non-firm off-system sales are not incorporated into the load forecast. Off-system sales markets are 48 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Standards and Guidelines are Addressed in the 2017 IRP then plans to meet. However, the Plan must have some analysis of the off-system sales market to assess the impacts such markets will have on risks balancing purposes. demographic factors, including the prices of electricity and alternative energy sources, will affect the consumption of electric energy services, and how changes in the number, type and documents how demographic and price factors are used in PacifiCorp’s load forecasting methodology. including future market opportunities (both demand-side and supply-side), on a consistent and comparable basis. comparable basis using the System Optimizer model and Planning and Risk production cost model using both supply side and demand side alternatives. See explanation in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach) and the results in Volume I, Chapter 8 (Modeling and Portfolio Selection Results). Resource options are summarized effective improvements in the efficient use of electricity, including load management and conservation. (dispatchable/schedulable load control) and Class 2 DSM (energy efficiency measures) in its capacity expansion model. Details are provided in Volume I, generating technologies including: renewable resources, cogeneration, power purchases from other sources, and the construction of thermal resources. including renewables, cogeneration (combined heat and power), power purchases, thermal resources, energy storage, and Energy Gateway transmission configurations. Volume I, Chapters 6 (Resource Options) and 7 (Modeling and Portfolio Evaluation Approach) contain assumptions and describe the process under which PacifiCorp developed and expectancy of the resources, the recognition of whether the resource is replacing/adding capacity or energy, dispatchability, lead-time requirements, flexibility, efficiency of the resource and opportunities for customer participation. attributes in its IRP models. Resources are defined as providing capacity, energy, or both. The DSM supply curves used for portfolio modeling explicitly incorporate estimated rates of program and event participation. The private generation study, modeled as a reduction to load, also considered rates of participation. Replacement capacity is considered in the case of early coal unit retirements as evaluated in this IRP as an alternative to coal unit environmental investments. Dispatchability is accounted for in both IRP models used; however, the Planning and Risk model provides a more detailed representation of unit dispatch than System Optimizer, and includes modeling of unit 49 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Standards and Guidelines are Addressed in the 2017 IRP demand-side and supply-side resource other procurement methods is provided in Volume I, decisions intended to implement the integrated resource plan in a manner consistent with the Company's strategic business plan. The action plan will span a four-year horizon and will describe specific actions to be taken in the first two years and outline actions anticipated in the last two years. The action plan will include a status report of the specific actions contained in 9 (Action Plan). A status report of the actions outlined in the previous action plan (2015 IRP Update) is provided in Volume I, Chapter 9 (Action Plan). In Volume I, Chapter 9 (Action Plan) Table 9.1 identifies actions anticipated in the next two years and in the next four years. different economic circumstances with a decision mechanism to select among and modify these paths as the future unfolds. acquisition path analysis that presents broad resource strategies based on regulatory trigger events, change in load growth, extension of federal renewable 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 estimates of resource options. resource cost information in Volume I, Chapter 6 (Resource Options). The IRP document addresses the impact of social concerns on resource cost-effectiveness in the following ways: ● Portfolios were evaluated using a range of CO2 compliance methods, most included emissions rate targets, but there was examination of additional CO2 tax adders. ● A discussion of environmental policy status and impacts on utility resource planning is provided in Volume I, Chapter 3 (The Planning Environment). ● State and proposed federal public policy preferences for clean energy are considered for development of the preferred portfolio, which is documented in Volume I, Chapter 8 (Modeling and Portfolio Selection Results). ● Volume II, Appendix G (Plant Water Consumption) of reports historical water 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 will identify who should bear such risk, the ratepayer or the stockholder. Volume I, Chapter 9 (Action Plan), and covers managing environmental risk for existing plants, risk management and hedging and treatment of customer and investment risk. Transmission expansion risks are discussed in Chapter 4 (Transmission). Resource capital cost uncertainty and technological risk is addressed in Volume I, Chapter 6 (Resource Options). 50 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Standards and Guidelines are Addressed in the 2017 IRP incorporates stochastic volatility of forced outages for new thermal plants and hydro availability. These risks are factored into the comparative evaluation of portfolios and the selection of the preferred portfolio upon which the action plan is based. Identification of the classes of risk and how these risks are allocated to ratepayers and investors is planning process so that the Company can take advantage of opportunities and can prevent the is highlighted in Volume I, Chapter 9 (Action Plan), specifically, Table 9.1. such conditions of service as reliability and dispatchability and the acquisition of lowest cost resources. cost and risk, taking into consideration a broad range of resource alternatives defined with varying levels of dispatchability. This trade-off analysis is documented in Volume I, Chapter 8 (Modeling and Portfolio Selection Results), and highlighted through the use of scatter-plot graphs showing the relationship between stochastic mean and upper-tail quantification, of estimated external costs which may be intangible, in order to show how explicit consideration of them 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 costs for CO2 and costs for complying with current and proposed U.S. EPA regulatory requirements. For CO2 externality costs, the company used scenarios with various compliance requirements to capture a reasonable range of cost impacts. These modeling assumptions are described in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach). consistent with the Company's integrated resource planning goals and how changes in rate design might facilitate integrated resource planning objectives. Environment). The role of Class 3 DSM (price response programs) at PacifiCorp and how these resources are modeled in the IRP are described in Volume I, Chapter 6 (Resource Options). comment, review and acknowledgment. external review throughout the process prior to each of the public input meetings and solicited/and received feedback at various times when developing the 2017 IRP. The materials shared with stakeholders at these meetings, outlined in Volume I Chapter 2 (Introduction), is consistent with materials presented in Volumes I and II of the 2017IRP report. PacifiCorp requested and responded to comments from stakeholders in developing core case and sensitivity definitions. The Company also considered comments received via Feedback Forms in 51 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Standards and Guidelines are Addressed in the 2017 IRP parties will have the opportunity to make formal comment to the Commission on the adequacy of the Plan. The Commission will review the Plan for adherence to the principles stated herein, and will judge the merit and applicability of the public comment. If the Plan needs further work the Commission will return it to the Company with comments and suggestions for change. This process should lead more quickly to the Commission's acknowledgment of an acceptable Integrated Resource Plan. The Company will give an oral presentation of its report to the Commission and all interested public parties. Formal hearings on the acknowledgment of the Integrated Resource Plan might be appropriate but guarantee favorable ratemaking treatment of cases to evaluate the performance of the utility Table B.5 – Washington Utilities and Transportation Commission IRP Standard and Guidelines (RCW 19.280.030 and WAC 480-100-238) Requirements prior to IRP Filing (4) Work plan filed no later than 12 months before next IRP due date. Docket No. UE-160353, given an anticipated IRP filing date of March 31, 2017. PacifiCorp was granted approval in Docket No. assessing potential resources. (See anticipated resource analysis. of public participation. anticipated IRP schedule. PacifiCorp was granted approval in Docket No. UE-160353 on March 29, 2017 to file the IRP April 4, within two years of previous plan. Docket No. UE-070117, granting the Company permission to file its IRP on March 31 of each odd numbered year. PacifiCorp filed the 2015 IRP on March 31, 2015. PacifiCorp was granted approval in Docket No. UE-160353 on March 29, 2017 to file the IRP April 4, hearing after company files plan for 52 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Standards and Guidelines are Addressed in the 2017 IRP Requirements specific to IRP filing (2)(a) Plan describes the mix of energy supply resources. of existing resources, while Volume I, Chapter 8 (Modeling and Portfolio Selection Results) describes the 2015 IRP preferred how conservation supplies are represented and modeled, and Volume I, Chapter 8 (Modeling and Portfolio Selection Results) for conservation supply in the preferred portfolio. Additional information on energy efficiency resource characteristics is available current and future needs at the lowest reasonable cost to the utility and its ratepayers. assessment that accounted for forecasted load growth, expiration of existing power purchase contracts, resources under construction, contract, or reflected in the Company’s capital budget, as well as a capacity planning reserve margin. Details on PacifiCorp’s findings of resource need are described in Volume I, Chapter 5 (Load and (LRC) analysis to select the mix of resources. Present Value of Revenue Requirements (PVRR) methodology. See the section on portfolio performance measures in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach) and Volume I information on costs and other attributes for all resources analyzed volatility risks. Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach) resource uncertainties. development of numerous portfolios based on different sets of input dispatchability. existing and future resources based on such attributes as heat rate, availability, fuel cost, and variable O&M cost. The chronological production cost simulation model also incorporates unit commitment logic for handling start-up, shutdown, rtimes, and run up rates, and reserve holding characteristics of on system operation. reflecting dispatch/unit commitment, forced/unforced outages, access to markets, and system reliability and transmission on ratepayers. 2regulatory regimes, wholesale electricity and natural gas price escalation and volatility, load growth uncertainty, resource reliability, renewable portfolio standard requirement uncertainty, plant construction cost escalation, and resource affordability. These risks and uncertainties are handled through stochastic modeling and scenarios depicting alternative futures. In addition to risk modeling, the IRP discusses a number of resource risk topics not addressed in the IRP system simulation models. For 53 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Standards and Guidelines are Addressed in the 2017 IRP of owning vs. purchasing power, (3) purpose of hedging, (4) procurement delays and (5) treatment of customer and investor risks. Volume I, Chapter 4 (Transmission) covers similar risks associated regarding resource preference adopted by Washington state or federal government. modeling incorporates resource expansion constraints tied to renewable portfolio standards (RPS) currently in place for Washington. PacifiCorp also evaluated various CO2 regulatory schemes, and future Regional Haze compliance requirements. The I- 937 conservation requirements are also explicitly accounted for in associated with environmental effects including emissions of carbon dioxide. reduction in electric power consumption that results from increases in the efficiency of energy conservation is provided in Volume I, Chapter 6 (Resource Options). future demand. the load forecasts used in the 2017 IRP (high, low, and extreme peak temperature) are provided in Volume II, Appendix A (Load Forecast that examine the effect of economic forces on the consumption of electricity. forecasting techniques that include such economic variables as household income, employment, and population. See Volume II, Appendix A (Load Forecast Details) for a description of the load that address changes in the number, type and efficiency of electrical end-model that accounts for equipment saturation rates and efficiency. See Volume II, Appendix A (Load Forecast Details), for a commercially available conservation, including load management. potential study in the 2017 IRP, which served as the basis for developing DSM resource supply curves for resource portfolio modeling. The supply curves account for technical and achievable (market) potential, while the IRP capacity expansion model identifies a cost-effective mix of DSM resources based on these limits and other model inputs. The DSM potential study is included on the data disc, and available on PacifiCorp’s IRP website at: currently employed and new policies and programs needed to obtain the activities to implement current and new programs is provided in Volume I, Chapter 5 (Load and Resource Balance). range of conventional and commercially available nonconventional generating technologies. renewables, cogeneration (combined heat and power), customer standby generation, power purchases, thermal resources, energy storage, and transmission. Volume I, Chapters 6 (Resource Options and Chapter 7 (Modeling and Portfolio Evaluation Approach) document how PacifiCorp developed and assessed these 54 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE No. Requirement How the Standards and Guidelines are Addressed in the 2017 IRP transmission system capability and reliability; to the extent such information can be provided consistent with applicable laws. obligations, factoring in updates to the representation of major load and generation centers, regional transmission congestion impacts, import/export availability, external market dynamics, and significant transmission expansion plans explained in Volume I, Chapter 4 (Transmission) and Chapter 7 (Modeling and Portfolio Evaluation Approach). System reliability given transmission capability was analyzed using stochastic production cost simulation and measures of insufficient energy and capacity for a load area (Energy Not of energy supply resources (including transmission and distribution) and improvements in conservation using LRC. Optimizer) is designed to compare alternative resources—including transmission expansion options—for the least-cost resource mix. for comparative evaluation on the basis of cost, risk, reliability, and other performance attributes. Potential energy savings associated demand forecasts and resource evaluations into a long range integrated resource plan describing the mix of resources that is designated to meet current and project future needs at the lowest reasonable cost to the operations in the context of a system modeling framework described in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach). The portfolio evaluation covers a 20-year period (2017-2036). PacifiCorp developed its preferred portfolio of resources judged to be least-cost after considering load requirements, risk, uncertainty, supply adequacy/reliability, and government resource implementation of the previously filed plan. Volume I, Chapter 9 (Action Plan). commercially available technologies, or facilities for integrating renewable resources, and addressing overgeneration events, if applicable to in the 2017 IRP. Also see Volume II, Appendix H (Wind and Solar Integration Study). forecasts and resource evaluations into a long-range assessment describing the mix of supply side generating resources and conservation and efficiency resources that will meet current and projected needs, including mitigating overgeneration events, at the lowest reasonable cost and risk to the utility and its ratepayers; Supply-side and demand-side are discussed in Volume I, Chapter 6. Also included is a discussion of DSM in Volume II, Appendix D are included in Volume I, Chapters 7 and 8 go through the modeling methodology and discussion of selecting the preferred portfolio using least cost/least risk metrics. 55 PACIFICORP – 2017 IRP APPENDIX B – IRP REGULATORY COMPLIANCE Table B.6 – Wyoming Public Service Commission Guidelines Regarding Electric IRP A employed as part of the formulation of the utility’s IRP, including a description, timing and (Introduction) and in Volume II, Appendix C (Public Input Process). B resource planning goals and preferred resource portfolio; documents the preferred resource portfolio and rationale for selection. Volume I, Chapter 9 (Action Plan) constitutes the IRP action plan and the descriptions of resource strategies and risk C need over the near-term and long- D F acquisitions and load growth from that presented in the utility’s previous IRP; is presented in Volume I, Chapter 9 (Action Plan). A chart comparing the peak load forecasts for the 2015 IRP, 2015 IRP Update, and 2017 IRP is included in Volume II, Appendix A (Load Forecast Details). G considered; 2impacts are considered, including prospective early retirement and gas conversions of existing coal units as alternatives to environmental investments. See Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach) and Chapter 8 (Modeling and Portfolio Selection) as well as Volume II, Appendix L (Stochastic H I selection of a capacity planning reserve margin is in Volume I, J conservation options; discussion on DSM and conservation resource options. Additional information on energy efficiency resource characteristics is 56 PACIFICORP - 2017 IRP APPENDIX C – PUBLIC INPUT PROCESS APPENDIX C – PUBLIC INPUT PROCESS A critical element of this Integrated Resource Plan (IRP) is the public input process. PacifiCorp has pursued an open and collaborative approach involving the Commissions, customers and other stakeholders in PacifiCorp’s IRP prior to making resource planning decisions. Since these decisions can have significant economic and environmental consequences, conducting the IRP with transparency and full participation from interested and affected parties is essential. Stakeholders have been involved in the development of the 2017 IRP from the beginning. The public input meetings (PIM) held beginning in June 2016 were the cornerstone of the direct public input process. There were a total of seven PIM, with four lasting two days, the remainder being single days. Meetings were held jointly in both Salt Lake City, Utah and Portland, Oregon via video conference, with expanded video conference locations in Denver, Colorado and Cheyenne, Wyoming. One meeting was held via phone conference. For all meetings, attendees off-site for were able to conference in via phone. The IRP public input process also included state-specific stakeholder dialogue sessions held in June 2016. The goal of these sessions was to capture key IRP issues of most concern to each state, as well as discuss how to tackle these from a system planning perspective. PacifiCorp also wanted to ensure that stakeholders understood IRP planning principles. These meetings continued to enhance interaction with stakeholders in the planning cycle, and provided a forum to directly address stakeholder concerns regarding equitable representation of state interests during public input meetings. PacifiCorp solicited agenda item recommendations from the state stakeholders in advance of the state meetings. There was additional open time to ensure that participants had adequate time for dialogue. PacifiCorp’s comment website housed the feedback form discussed earlier in Chapter 2 - Introduction. This standardized form allowed stakeholders opportunities to provide comments, questions, and suggestions. Feedback forms can be found via the following link: (http://www.pacificorp.com/es/irp/irpcomments.html). Participant List PacifiCorp’s 2017 IRP was a robust process involving input from many parties throughout. Organizations actively participated in the development of material, modeling process, and public meetings. Participants included Commissions, stakeholders, and industry experts. Among the organizations that were represented and actively involved in this collaborative effort were: Commissions • Idaho Public Utilities Commission • Oregon Public Utilities Commission • Public Service Commission of Utah • Washington Utilities and Transportation Commission 57 PACIFICORP - 2017 IRP APPENDIX C – PUBLIC INPUT PROCESS • Wyoming Public Service Commission Stakeholders and Industry Experts • ABB Enterprise Software Inc. (formerly known as Ventyx Inc.) • Applied Energy Group • Avista Utilities • Black & Veatch • Blue Castle Holdings, Inc. • Citizen’s Utility Board of Oregon • Energy Trust of Oregon • DNV-GL • Idaho Conservation League • Idaho Power Company • Individual Customers • Industrial Customers of Northwest Utilities • Intermountain Wind • Interwest Energy Alliance • Mitsubishi • National Renewable Energy Laboratory • Natural Resources Defense Council • Navigant Consulting, Inc. • Northwest Power and Conservation Council • Northwest Pipeline GP • NW Energy Coalition • Oregon Department of Energy • Oregon Department of Environmental Quality • Portland General Electric • Powder River Basin Resource Council • Renewable Energy Coalition • Renewables Northwest • Sierra Club • Siemens • For Utah Association of Energy Users • Utah Clean Energy • Utah Division of Public Utilities • Utah Industrial Energy Consumers • Utah Office of Consumer Services • Utah Office of Energy Development • Western Clean Energy Campaign • Western Electricity Coordination Council • Western Resource Advocates • Wyoming Industrial Energy Consumers • Wyoming Office Of Consumer Advocate 58 PACIFICORP - 2017 IRP APPENDIX C – PUBLIC INPUT PROCESS PacifiCorp extends its gratitude for the time and energy participants have given to the IRP process. Their participation has contributed significantly to the quality of this plan, and their continued participation will help PacifiCorp as it strives to improve its planning efforts going forward. Public Input Meetings As mentioned above, PacifiCorp hosted seven public input meetings, as well as five state meetings during the public input process. During the 2017 IRP public input process presentations and discussions covered various issues regarding inputs, assumptions, risks, modeling techniques, and analytical results. Below are the agendas from the public input meetings; the presentations may be found on the PacifiCorp website at: http://www.pacificorp.com/es/irp.html. General Meetings June 21, 2016 – General Public Meeting • Introductions • 2017 IRP Timeline • 2015 IRP Update Highlights • Overview of Changes Since 2015 IRP • 2015 IRP Order Requirements • 2015 IRP Action Plan status updates July 20, 2016 – General Public Meeting Day One • Introductions • Environmental Policy • Transmission and Regional Integration • Renewable Portfolio Standards and Request for Proposals August 25-26, 2016 – General Public Meeting Day 1 • Introductions • Portfolio Development • Private Generation Study • Supply-Side Resources • Energy Storage Day 2 • Update on Renewable Portfolio Standards and Request for Proposals • Conservation Potential Assessment • Load Forecast September 22-23, 2016 – General Public Meeting Day 1 • Introductions • Portfolio Development • Stochastic Modeling & Portfolio Selection Process • Resource Adequacy and Front Office Transactions 59 PACIFICORP - 2017 IRP APPENDIX C – PUBLIC INPUT PROCESS • Loss of Load Probability and Planning Reserve Margin • Capacity Contribution Study Day 2 • Load and Resource Balance • Flexible Capacity Reserve Study • Smart Grid Update November 17, 2016 – General Public Meeting • Introductions • Updated Capacity Contribution Study • Official Forward Price Curve January 26-27, 2017 – General Public Meeting Day 1 • Portfolio Summaries Day 2 • Sensitivity Studies March 2-3, 2017 – General Public Meeting Day 1 • Draft Preferred Portfolio Overview • Market Price Scenarios • Regional Haze and Core Cases Day 2 • Sensitivity Studies • Preferred Portfolio Selection Process State Meetings June 6, 2016 – Washington State Stakeholder Meeting June 7, 2016 – Idaho State Stakeholder Meeting June 10, 2016 – Oregon State Stakeholder Meeting June 13, 2016 – Utah State Stakeholder Meeting June 14, 2016 – Wyoming State Stakeholder Meeting 60 PACIFICORP - 2017 IRP APPENDIX C – PUBLIC INPUT PROCESS Stakeholder Comments For the 2017 IRP, PacifiCorp provided a Feedback Form which offered stakeholders a direct opportunity to provide comments, questions, and suggestions outside the public input meetings. PacifiCorp recognizes the importance of stakeholder feedback to the IRP public input process. A blank form, as well as those submitted by stakeholders, is housed on the PacifiCorp website at the IRP comments webpage at: http://www.pacificorp.com/es/irp/irpcomments.html The Feedback Form allowed the Company to review and summarize issues by topic as well as identify specific recommendations that were provided. Information collected was used to inform issues included in the 2017 IRP, including, process improvements, and input assumptions, as well as responding directly to stakeholder questions. Feedback Forms were received from the following stakeholders: • HEAL Utah • Idaho Conservation League • Interwest Energy Alliance • Natural Resources Defense Council • NW Energy Coalition • Oregon Public Utility Commission • Powder River Basin Resource Council • Renewable Energy Coalition • Renewable Northwest • Sierra Club • Utah Clean Energy • Utah Division of Public Utilities • Western Clean Energy Campaign • Western Resource Advocates Some topics of note addressed in the forms include: • Modeling of EPA’s 111(d) rules • Supply-side resources • Demand Side Management • Energy Storage • Renewable Portfolio Standards • Load forecast • Renewable capacity values • Wholesale power availability • Portfolios and sensitivity cases • IRP Public Input Meeting Process 61 PACIFICORP - 2017 IRP APPENDIX C – PUBLIC INPUT PROCESS Contact Information PacifiCorp’s IRP website contains many of the documents and presentations that support recent Integrated Resource Plans. To access it, please visit the company’s website at http://www.pacificorp.com/es/irp.html PacifiCorp requests that any informal request be sent in writing to the following address or email address below. PacifiCorp IRP Resource Planning Department 825 N.E. Multnomah, Suite 600 Portland, Oregon 97232 Email Address: IRP@PacifiCorp.com Phone Number: (503) 813-5245 62 PACIFICORP – 2017 IRP APPENDIX D – DEMAND-SIDE MANAGEMENT RESOURCES APPENDIX D – DEMAND-SIDE MANAGEMENT RESOURCES Introduction Appendix D reviews the studies and reports used to support the demand-side management (DSM) resource information used in the modeling and analysis of the 2017 Integrated Resource Plan (IRP). In addition, it provides information on the economic DSM selections in the 2017 IRP’s Preferred Portfolio, a summary of existing DSM program services and offerings, and an overview of the DSM planning process in each of PacifiCorp’s service areas. Demand-Side Resource Potential Assessments for 2017-2036 Since 1989, PacifiCorp has developed biennial IRPs to identify an optimal mix of resources that balance considerations of cost, risk, uncertainty, supply reliability/deliverability, and long-run public policy goals. The optimization process accounts for capital, energy, and ongoing operation costs as well as the risk profiles of various resource alternatives, including: traditional generation and market purchases, renewable generation, and DSM resources such as energy efficiency, and demand response or capacity-focused resources. Since the 2008 IRP, DSM resources have competed directly against supply-side options, allowing the IRP model to guide decisions regarding resource mixes, based on cost and risk. The Demand-side Resource Potential Assessment for 2017-20361 study, conducted by Applied Energy Group (AEG), primarily seeks to develop reliable estimates of the magnitude, timing, and costs of DSM resources likely available to PacifiCorp over a 20-year planning horizon, beginning in 2017. The study focuses on resources realistically achievable during the planning horizon, given normal market dynamics that may hinder resource acquisition. Study results were incorporated into PacifiCorp’s 2017 IRP and will be used to inform subsequent DSM planning and program design efforts. This study serves as an update of similar studies completed in 2007, 2011, 2013 and 2015. For resource planning purposes, PacifiCorp classifies DSM resources into four classifications, differentiated by two primary characteristics: reliability and customer choice. These resources classifications can be defined as: Class 1 DSM (firm, capacity focused), Class 2 DSM (energy efficiency), Class 3 DSM (non-firm, capacity focused), and Class 4 DSM (educational). From a system-planning perspective, Class 1 DSM resources can be considered the most reliable, as they can be dispatched by the utility. In contrast, behavioral changes, resulting from voluntary educational programs included in Class 4 DSM, tend to be the least reliable. With respect to customer choice, Class 1 DSM and Class 2 DSM resources should be considered involuntary in that, once equipment and systems have been put in place, savings can be expected to occur over a certain period of time. Class 3 and Class 4 DSM activities involve greater customer choice and control. This assessment estimates potential from Class 1, 2, and 3 DSM. 1 PacifiCorp’s Demand-Side Resource Potential Assessment for 2017-2036, completed by AEG, can be found at: http://www.pacificorp.com/es/dsm.html 63 PACIFICORP – 2017 IRP APPENDIX D – DEMAND-SIDE MANAGEMENT RESOURCES This study excludes an assessment of Oregon’s Class 2 DSM resource potential, as this work is performed by the Energy Trust of Oregon, which provides energy-efficiency potential in Oregon to PacifiCorp for resource planning purposes. Current DSM Program Offerings by State Currently there are two Class 1 DSM programs running within PacifiCorp’s six-state service area; Utah’s “Cool Keeper” residential and small commercial air conditioner load control program and the irrigation load control program in Utah, Idaho, and Oregon.2 The two programs contribute approximately 308 MW of load reduction capability, helping the Company better manage demand during peak periods.3 In addition to the Class 1 DSM products, the Company offers a robust portfolio of distinct Class 2 DSM programs and initiatives, most of which are offered in multiple states, depending on size of opportunity and need. Table D.1 provides an overview of the breadth of Class 1 and 2 DSM program services and offerings available by Sector and State. Energy efficiency services listed for Oregon, except for low income weatherization services, are provided in collaboration with the Energy Trust of Oregon.4 2 The Oregon Irrigation Load Control Pilot was approved in May of 2016. 3 Actual reductions may vary by event (temperature and month and time dependent), cited load reduction represents the sum of the highest event performance available across the three states for the two programs and account for line losses (are “at generator” values). In addition to these two programs, the Company has additional interruptible load under contract with select Utah and Idaho special contract customers, see Table 5.12 in the 2015 IRP for additional detail. 4 Funds for low-income weatherization services are forwarded to Oregon Housing and Community Services. 64 PACIFICORP – 2017 IRP APPENDIX D – DEMAND-SIDE MANAGEMENT RESOURCES Table D.1– Current Class 1 and 2 DSM Program Services and Offerings by Sector and State The Company has numerous Class 3 DSM offerings currently available. They include metered time-of-day and time-of-use pricing plans (in all states, availability varies by customer class), residential seasonal inverted block rates (Idaho and Utah) and residential year-round inverted block rates (California, Oregon, Washington, and Wyoming). System-wide, approximately 18,700 customers were participating in metered time-of-day and time-of-use programs as of December 31, 2014.5 All of the Company’s residential customers not opting for a time-of-use rates are 5 Year-end 2014 participation data was used in the development of the 2017 DSM Potential Study. By the end of 2015, participation levels had declined slightly to approximately 18,300 participants. Program Services & Offerings by Sector and State California Oregon Washington Idaho Utah Wyoming √ √√√√√√ √√√√√ √√√√√√ √√√√√√ √√√√√√ √√√√√√ √√√√ √√√ √√√√√√ √ √√√√√√ √ √√√ √√√√√√ √√√√√√ √√√ √√√√√√ √√√√√√ √√√√√√ √√√√√√ √√√√√√ √√√√√ √√√√√√ √√√√√√ Residential Sector Non-Residential Sector 65 PACIFICORP – 2017 IRP APPENDIX D – DEMAND-SIDE MANAGEMENT RESOURCES currently subject to seasonal or year-round inverted block rate plans. Savings associated with these resources are captured within the Company’s load forecast and are thus captured in the integrated resource planning framework. PacifiCorp continues to evaluate Class 3 DSM programs for applicability to long-term resource planning. Educating customers regarding energy efficiency and load management opportunities is an important component of the Company’s long-term resource acquisition plan. A variety of channels are used to educate customers including television, radio, newspapers, bill inserts and messages, newsletters, school education programs, and personal contact. Load reductions due to Class 4 DSM activity will show up in Class 1 and Class 2 DSM program results and non-program reductions in the load forecast over time. Table D.2 provides an overview of DSM related wattsmart Outreach and Communication activities (Class 4 DSM activities) by state. Table D.2 – Current wattsmart Outreach and Communications Activities California Oregon Washington Idaho Utah Wyoming Advertising √√√√√ Sponsorships √√ Social Media √√√√√√ Contests (video)√ Public Relations (Habitat for Humanity, other)√√√√ Business Advocacy (awards at customer meetings, sponsorships, chamber partnership, university partnership) √√√√ wattsmart Workshops √ Rockin wattsmart Assemblies √ 66 PACIFICORP – 2017 IRP APPENDIX D – DEMAND-SIDE MANAGEMENT RESOURCES Preferred Portfolio DSM Resource Selections The following tables shows the economic DSM resource selections by state and year in the 2017 IRP preferred portfolio, OP_GW4b. Table D.3 – Incremental and Cumulative Class 1 DSM Resource Selections (2017 IRP Preferred Portfolio) Table D.4 – Incremental Class 2 DSM Resource Selections (2017 IRP Preferred Portfolio) For the 20-year assumed nameplate capacity contributions (MW impacts) by state and year associated with the Class 2 DSM resource selections above, see Table 8.7 – PacifiCorp’s 2017 IRP Preferred Portfolio, in Volume I of the 2017 IRP. State/Product by Year 2028 2029 2030 2032 2033 2034 2035 Total/Products (MW) Cumulative Total by Year (MW) 289.3 43.1 4.8 6.7 3.1 3.7 3.1 353.6 Energy Efficiency Energy (MWh) Selected by State and Year State 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 CA 7,450 7,340 5,130 5,250 5,190 5,070 4,800 4,590 4,420 4,000 OR 198,680 197,720 191,550 166,590 141,410 119,530 104,130 102,010 88,400 83,220 WA 44,600 34,300 36,170 33,650 38,370 35,970 34,060 34,300 31,830 28,860 UT 333,400 240,790 255,190 245,260 253,480 239,730 249,190 249,390 237,350 246,620 ID 17,570 22,950 23,060 19,200 19,920 18,630 18,160 19,280 18,640 19,220 WY 43,800 56,030 59,550 56,690 74,090 75,440 76,460 76,450 80,390 76,950 Total System 645,500 559,130 570,650 526,640 532,460 494,370 486,800 486,020 461,030 458,870 Energy Efficiency Energy (MWh) Selected by State and Year State 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 CA 4,880 4,320 3,880 4,190 3,830 3,080 2,690 2,200 1,240 1,060 OR 82,810 76,970 73,750 73,890 71,890 74,280 68,090 67,880 72,400 72,350 WA 27,160 24,780 22,300 20,360 19,630 15,260 12,870 9,860 8,590 6,760 UT 241,950 228,310 213,700 216,120 220,390 182,340 161,080 135,140 124,270 127,670 ID 18,120 17,080 16,590 16,000 15,510 13,010 12,190 9,970 8,910 9,180 WY 69,050 62,320 62,910 58,670 56,430 47,440 40,530 36,690 36,310 36,460 Total System 443,970 413,780 393,130 389,230 387,680 335,410 297,450 261,740 251,720 253,480 67 PACIFICORP – 2017 IRP APPENDIX D – DEMAND-SIDE MANAGEMENT RESOURCES State-Specific DSM Planning Processes PacifiCorp offers robust portfolios of DSM resource options in each of its state service areas. A summary of the DSM planning process in each state is provided below. Washington The Company is one of three investor-owned utilities required to comply with the Energy Independence Act (also referred to as I-937) approved in November 2006. The Act requires utilities to pursue all conservation that is cost-effective, reliable, and feasible. Every two years, each utility must identify its 10-year conservation potential and two-year acquisition target based on its IRP and using methodologies that are consistent with those used by the Northwest Power and Conservation Council. Each utility must maintain and use an external conservation stakeholder group to advise on a range of issues including conservation programs, development of conservation potential assessments, program marketing, incentive levels, budgets, adaptive management and the development of new and pilot programs. During 2017, the Company will be working with stakeholders to establish the conservation target for 2018-2019. California The Company has historically structured its energy efficiency programs on a multi-year cycle to align with the three large California investor-owned utilities’ portfolio and budget schedules when possible.6 In October 2015, the California Public Utility Commission (CPUC) issued Decision D.15-10-028, which imposes a new rolling portfolio review process on the large investor-owned utilities’ energy efficiency program. In addition to the Commission’s new review process, California Senate Bill (SB) 350 requires the California Energy Commission (CEC) to set annual targets for statewide energy efficiency savings that will cumulatively double energy efficiency by 2030. In 2016, the Company filed to extend its existing energy efficiency programs through 2017 and during 2017, the Company will file with the CPUC to transition into the new multi-year program cycle, incorporating components of SB 350, as appropriate. Utah, Wyoming and Idaho The Company’s biennial IRP and associated action plan provides the foundation for DSM acquisition targets in each state Where appropriate, the Company maintains and uses external stakeholder groups and vendors to advise on a range of issues including annual goals for conservation programs, development of conservation potential assessments, program marketing, incentive levels, budgets, adaptive management and the development of new and pilot programs. Oregon Energy efficiency programs for Oregon customers are planned and delivered by the Energy Trust of Oregon in collaboration with PacifiCorp. The Energy Trust’s planning process is comparable to PacifiCorp’s other states, including establishing resource acquisition targets based on resource assessment and integrated resource planning, developing programs based on local market conditions, and coordinating with stakeholders and regulators to ensure efficient and cost-effective delivery of energy efficiency resources. 6 In California, the company is considered to be a small multi-jurisdictional utility and is not typically required to comply with the energy efficiency requirements of the three large investor owned electric utilities. 68 PACIFICORP – 2017 IRP APPENDIX E – SMART GRID 69 APPENDIX E – SMART GRID Introduction The smart grid is the application of advanced communications and controls to the electric power system. Areas of installation include generation, transmission, distribution, and customer facilities. A wide array of applications can be defined under the smart grid umbrella. Smart grid includes technologies such as dynamic line rating, phasor measurement units (synchrophasors), energy storage, power line sensors, distribution automation, integrated volt/var optimization, advanced metering infrastructure, automated demand response, and smart renewable and/or distributed generation controls (e.g., smart inverters). PacifiCorp has reviewed relevant smart grid technologies for transmission, substation, and distribution systems. When considering smart grid technologies, the communications network is often the most critical infrastructure decision. This network must have high speed, reliability, and security. It must be interoperable for many device types, manufacturers, and generations of technology and must be scalable in order to support PacifiCorp’s entire service territory. PacifiCorp regularly evaluates integrating smart grid technologies and implements those that show a positive net benefit for its customers. PacifiCorp has tested or implemented smart grid devices and functions such as dynamic line rating, synchrophasors, and communicating faulted circuit indicators. Advanced metering infrastructure, distribution automation, and distributed energy resource systems (including electric vehicles) are also underway or under consideration. PacifiCorp will leverage smart grid technologies to align investments with the least-cost/least- risk goals of the Integrated Resource Plan (IRP). This will optimize the electrical grid when and where it is economically feasible, operationally beneficial, and in the best interest of customers. PacifiCorp is committed to consistently evaluating the value of emerging technologies and recommend them for demonstration or integration if they are found to be appropriate investments. PacifiCorp is working with state commissions to improve reliability, energy efficiency, customer service, and integration of renewable resources by analyzing the total cost of ownership, performing thorough cost-benefit analyses, and reaching out to customers concerning smart grid applications and technologies. As technology advances and development continues, PacifiCorp is able to improve estimates of the costs and benefits of smart grid technologies. Progressing large-scale deployments and demonstration projects will reveal the effect of large-scale rollouts and assist PacifiCorp in identifying the best suited technologies for implementation. Transmission System Efforts Dynamic Line Rating Dynamic line rating is the application of sensors to transmission lines to indicate the real-time current-carrying capacity of the lines in relation to thermal restrictions. Transmission line ratings are typically based on line loading calculations given a set of worst-case weather assumptions, PACIFICORP – 2017 IRP APPENDIX E – SMART GRID 70 such as high ambient temperatures and very low wind speeds. Dynamic line rating allows an increase in current-carrying capacity when more favorable weather conditions are present and the transmission path is not constrained by other operating elements. Two dynamic line rating projects were implemented in 2014, Miners-Platte and West-of-Populus. The Miners-Platte project uses a dynamic line rating system to determine the resulting cooling effect of the wind on the line. The current carrying capacity is then updated to a new weather dependent line rating. The Miners-Platte 230 kV transmission line was one of the limitations of the TOT4A transmission path with wind farms significantly impacting the loading of the line. As a result of this project, the TOT4A WECC non-simultaneous path rating was increased. The West-of-Populus project was the second dynamic line rating project in 2014. The dynamic line rating enabled lines experienced low line loading due to peak loads between Pacific Power and Rocky Mountain Power coinciding over time. As a result of this low loading, the thermal reading of the lines is dependent upon ambient weather conditions without being greatly affected by line loading. Until higher line loading is experienced from high flow scenarios or outages, conclusions concerning the dynamic line rating project in West-of-Populus are difficult to ascertain. PacifiCorp will continue to collect and analyze future data as high line loading is experienced. Dynamic line rating will be considered for all future transmission needs as a means for increasing capacity in relation to traditional construction methods. Dynamic line rating is only applicable for thermal constraints and only provides additional site-dependent capacity during finite time periods. It may or may not align with the expected transmission need of future projects. PacifiCorp will continue to look for opportunities to cost-effectively employ dynamic line rating systems. Thermal Replicating Relays PacifiCorp extensively considered a project to install thermal replicating relays to adhere to protection and control compliance standards in the Soda Springs area of Idaho. Thermal replicating relays utilize dynamic line rating to monitor the thermal properties of the line, then send a trip signal if the thermal limit has been exceeded. These relays may only be used where line tripping will not cause cascading outages. A remedial action scheme (RAS) was also analyzed as an alternative to thermal replicating relays for the Soda Springs area. In this particular case, because the remedial action scheme was deemed more cost-effective, the thermal replicating relay project alternative will not be employed. Synchrophasors Synchrophasors, also called phasor measurement units, can lead to a more reliable transmission network by comparing phase angles of certain network elements with a base element measurement. Phasor measurement units can also be used to increase reliability by relaying line condition data through the communication network quickly. Phasor measurement unit implementation may enable transmission operators to integrate variable resources and energy storage more effectively while minimizing service disruptions. PACIFICORP – 2017 IRP APPENDIX E – SMART GRID 71 PacifiCorp participated in the Western Interconnection Synchrophasor Project (WISP). The project resulted in eight phasor measurement units installed in eight PacifiCorp substations. These devices are currently collecting data and will support PacifiCorp’s and Peak Reliability’s1 goal of maintaining power system stability. The system of synchrophasors will be used to identify and analyze system vulnerabilities and disturbances. It will also assist in preventing system blackouts and provide historical data for the analysis of any future power system failure. Peak Reliability is continuing to develop data access for utility participants. PacifiCorp has discontinued sending data to Peak Reliability as part of their WISP program since they currently do not operationally utilize the data. Once Peak Reliability has their advanced application functionality enabled, which is expected in 2017, PacifiCorp expects to reinitiate data flow to Peak Reliability. Phasor measurement units will also be used to satisfy the validation requirements in NERC- MOD-033, a reliability standard proposed to improve accurate data collection and planning models. Planning models analyzing the transmission system reliability are required to compare model results to real-world values in order to meet model validation requirements. Distribution System Efforts Distribution Automation Distribution automation (DA) is a wide field of smart grid technology and applications, which focuses on using sensors and data collection on the distribution system, as well as automatically adjusting the system to optimize performance. It can also provide operational efficiency, peak load management, equipment failure prediction, and decreased restoration times after failure. PacifiCorp is working on several distribution automation initiatives. In Oregon, PacifiCorp has identified 40 circuits on which a DA cost benefit analysis will be performed. These 40 circuits were selected based on a set of criteria intended to minimize the cost of implementation and maximize the reliability benefit. The feasibility of utilizing an advanced metering infrastructure network for the communications of the distribution automation system will also be addressed. PacifiCorp has installed FusesaverTM devices and electronic reclosers with the capability of enabling communications through a retrofit in the future. A pilot project in Walla Walla, Washington is underway to demonstrate the feasibility and effectiveness of distribution automation, including a fault location isolation and restoration application. A feasibility study to determine the cost and benefit of retrofitting an existing source/transfer scheme to a distribution automation scheme is underway in Salt Lake City, Utah. PacifiCorp installed communicating faulted circuit indicators on five circuits in eastern Utah in March 2014. These devices have proven capable of improving reliability by reducing the time required to report and locate a fault. PacifiCorp is still evaluating the cost and feasibility of integrating these devices in its outage management system before further deployment. 1 Peak Reliability (Peak) is a company wholly independent of WECC that performs the Reliability Coordinator (RC) function in its RC Area in the Western Interconnection. PACIFICORP – 2017 IRP APPENDIX E – SMART GRID 72 Customer Information Efforts Advanced Metering Infrastructure A key effort for PacifiCorp in 2016 was the development of a detailed business case for advanced metering infrastructure in Oregon. Advanced metering infrastructure is an integrated system of smart meters, communications networks, and data management systems with two-way communication. PacifiCorp’s objectives were to identify a solution and strategy that would deliver tangible projected benefits to our customers and deliver economically-driven financial results while minimizing the impact on consumer rates. A request for information followed by a request for proposals was solicited to further evaluate the economics and impacts of an advanced metering infrastructure rollout in Oregon. The financial analysis of proposals indicated a positive business case due to decreasing costs of advance metering technology and increasing operations and maintenance costs. As a result, Pacific Power committed to proceed with deployment of an advanced metering infrastructure system in Oregon. The advanced metering infrastructure program in Oregon will replace 590,000 existing customer meters with smart meters and install an advanced metering system to remotely read and operate customer meters. The project will provide a web portal for customers, capture hourly meter data, perform on demand meter reads, remotely connect and disconnect power, verify outage inquiries, remotely reprogram meters, and collect data on power quality and tampering. This advanced metering infrastructure project will provide a network and metering infrastructure to improve customer service and enable future smart grid applications. Project benefits include reduced operations and maintenance costs, a platform for future smart grid applications, increased worker safety, reduced emissions, and increased data for efficient management of the network. Meter installations begin in 2017 and the project completion date is scheduled for the end of 2019. Future Smart Grid PacifiCorp is continuing to evaluate smart grid technologies and piloted projects that might benefit customers. PacifiCorp regularly develops smart grid reports to examine the quantifiable costs and benefits of individual components of the smart grid. While the net present value of implementing a comprehensive smart grid system throughout PacifiCorp is negative at this time, PacifiCorp has implemented specific projects and programs that have positive benefits for customers, and continues to explore pilot projects in other areas of interest. In order to reduce risks to the company, grid, customers, and supporting systems, it is essential to identify affordable leading technologies and implement industry best practices. PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY APPENDIX F – FLEXIBLE RESERVE STUDY Introduction This 2017 Flexible Reserve Study (“FRS”) estimates the regulation reserve required to maintain PacifiCorp’s system reliability and comply with North American Electric Reliability Corporation (“NERC”) reliability standards as well as the incremental cost of this regulation reserve. The FRS also compares PacifiCorp’s overall operating reserve requirements, including both regulation reserve and contingency reserve, to its flexible resource supply over the IRP study period. PacifiCorp operates two Balancing Authority Areas (“BAAs”) in the Western Electricity Coordinating Council (“WECC”) NERC region, PacifiCorp East (“PACE”) and PacifiCorp West (“PACW”). The PACE and PACW BAAs are interconnected by a limited amount of transmission across a third-party transmission system and the two BAAs are each required to comply with NERC standards. PacifiCorp must provide sufficient regulation reserve to remain within NERC’s balancing authority area control error (“ACE”) limit in compliance with BAL-001-2,1 as well as the amount of contingency reserve required in order to comply with NERC standard BAL-002-WECC-2.2 BAL-001-2 is a new regulation reserve standard that became effective July 1, 2016, and BAL-002-WECC-2 is a contingency reserve standard that became effective October 1, 2014. Regulation reserve and contingency reserve are components of operating reserve, which NERC defines as “the capability above firm system demand required to provide for regulation, load forecasting error, equipment forced and scheduled outages and local area protection.”3 Apart from disturbance events that are addressed through contingency reserve, regulation reserve is necessary to compensate for changes in load demand and generation output, so as to maintain ACE within mandatory parameters established by the BAL-001-2 standard. The FRS estimates the amount of regulation reserve required to manage variations in load, variable energy resources4 (“VERs”), and resources that are not VERs (“Non-VERs”) in each of PacifiCorp’s BAAs. Load, wind, solar, and Non-VERs were each studied because PacifiCorp’s data indicates that these components or customer classes place different regulation reserve burdens on PacifiCorp’s system due to differences in the magnitude, frequency, and timing of their variations from forecasted levels. Specifically, PacifiCorp’s calculations demonstrate that the regulation reserve burden associated with wind deviations from scheduled amounts are twice the amount associated with solar, three times the amount associated with load, and four times the amount associated with Non- 1 NERC Standard BAL-001-2, http://www.nerc.com/files/BAL-001-2.pdf, which became effective July 1, 2016. ACE is the difference between a BAA’s scheduled and actual interchange, and reflects the difference between electrical generation and Load within that BAA. 2 NERC Standard BAL-002-WECC-2, http://www.nerc.com/files/BAL-002-WECC-2.pdf, which became effective October 1, 2014. 3 NERC Glossary of Terms: http://www.nerc.com/files/glossary_of_terms.pdf, updated July 13, 2016. 4 VERs are resources that resources that: (1) are renewable; (2) cannot be stored by the facility owner or operator; and (3) have variability that is beyond the control of the facility owner or operator. Integration of Variable Energy Resources, Order No. 764, 139 FERC ¶ 61,246 at P 281 (2012) (“Order No. 764”); order on reh’g, Order No. 764-A, 141 FERC ¶ 61,232 (2012) (“Order No. 764-A”); order on reh’g and clarification, Order No. 764-B, 144 FERC ¶ 61,222 at P 210 (2013) (“Order No. 764-B”). 73 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY VERs. As a result, PacifiCorp attributes different levels of regulation reserve to load, wind, solar, and Non-VERs. The FRS is based on PacifiCorp operational data recorded from January 2015 through December 2015 for load, wind, and Non-VERs. Solar generation on PacifiCorp’s system was insignificant during that time period, but is expected to amount to over 1,000 MW by the end of 2017. PacifiCorp’s primary analysis, focuses on the variability of load, wind, and Non-VERs during 2015. A supplemental analysis discusses how the total variability of the PacifiCorp system changes with varying levels of wind and solar capacity. The estimated regulation reserve amounts determined in this study represent the incremental capacity needed to ensure compliance with BAL-001-2 for a particular operating hour. The regulation reserve requirement for the combined portfolio is the sum of the individual requirements for load, wind, solar, and Non-VERs, less the reserve “savings” associated with diversity between the different classes, including diversity benefits realized as a result of PacifiCorp’s participation in the Energy Imbalance Market (“EIM”) operated by the California Independent System Operator Corporation (“CAISO”). The methodology in the FRS differs in several ways from that employed in PacifiCorp’s previous regulation reserve requirement analyses.5,6,7 First, regulation reserve requirements are now tied directly to compliance with the BAL-001-2 standard. Second, the FRS uses a portfolio wide approach to determine the overall regulation reserve requirement, including the aggregated diversity benefits for all customer classes. Third, all customer classes that contribute to the overall regulation reserve requirement are now allocated a share of the diversity benefits resulting from aggregating their requirement with that of the system as a whole. Fourth, the FRS reflects updated data based on actual operational experience, including the data and benefits from PacifiCorp’s participation in the EIM. The FRS results produce an hourly forecast of the regulation reserve requirements for each of PacifiCorp’s BAAs that is sufficient to ensure the reliability of the transmission system and compliance with NERC and WECC standards. This regulation reserve forecast covers the combined deviations of the load, wind, solar and Non-VERs on PacifiCorp’s system and varies as a function of the wind and solar capacity on PacifiCorp’s system, as well as forecasted wind and solar output. The regulation reserve requirements produced by the FRS were applied in the Planning and Risk (PaR) production cost model to determine the cost of the reserve requirements associated with incremental wind and solar capacity. These costs are attributed to the integration of wind and solar generation resources in the 2017 Integrated Resource Plan (IRP). 5 2012 Wind Integration Study report, Appendix H in Volume II of PacifiCorp’s 2013 IRP report: http://www.pacificorp.com/content/dam/pacificorp/doc/Energy_Sources/Integrated_Resource_Plan/2013IRP/PacifiCorp-2013IRP_Vol2-Appendices_4-30-13.pdf 6 2013 PacifiCorp Schedule 3 and 3A Study, Exhibit PAC-8 in testimony of Greg Duvall, FERC Docket No. ER13-1206 (filed April 1, 2013). 7 2014 Wind Integration Study, Appendix H in Volume II of PacifiCorp’s 2015 IRP report: http://www.pacificorp.com/content/dam/pacificorp/doc/Energy_Sources/Integrated_Resource_Plan/2015IRP/Pacifi Corp_2015IRP-Vol2-Appendices.pdf 74 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Executive Summary The FRS first estimates the regulation reserve necessary to maintain compliance with NERC Standard BAL-001-2 given a specified portfolio of wind and solar resources. The FRS next calculates the cost of holding regulation reserve for incremental wind and solar resources and the cost of using day-ahead load, wind, and solar forecasts to commit gas units. Finally, the FRS compares PacifiCorp’s overall operating reserve requirements over the IRP study period, including both regulation reserve and contingency reserve, to its flexible resource supply. The FRS estimates regulation reserve based on the specific requirements of NERC Standard BAL-001-2. It also incorporates the current timeline for EIM market processes, as well as EIM resource deviations and flexibility reserve benefits based on actual results. The FRS also includes adjustments to regulation reserve requirements to account for the changing portfolio of solar and wind resources on PacifiCorp’s system and accounts for the diversity of using a single portfolio of regulation reserve resources to cover variations in load, wind, solar, and Non-VERs. The regulation reserve requirements for the various portfolios considered in this analysis including values from the 2014 Wind Integration Study for reference are shown in Table F.1. Table F.1 - Portfolio Regulation Reserve Requirements, by Scenario Two categories of flexible resource costs are estimated using the Planning and Risk (PaR) model: one for meeting intra-hour regulation reserve requirements, and one for inter-hour system balancing costs associated with committing gas plants using day-ahead forecasts of load, wind, and solar. Table F.2 provides the wind and solar costs on a dollar per megawatt-hour ($/MWh) of generation basis. The results of the 2014 Wind Integration Study are also included for reference. Table F.2 - 2017 FRS Flexible Resource Costs as Compared to 2014 WIS Costs, $/MWh The 2017 FRS results are applied in the 2017 IRP portfolio development process as a cost for wind Case Wind Capacity (MW) Solar Capacity (MW) Stand-alone Regulation Requirement (MW) Portfolio Diversity Credit (%) Regulation Requirement with Diversity (MW) Wind Wind Solar 2014 WIS 2017 FRS 2017 FRS (2014$)(2016$)(2016$) Total Flexible Resource Cost $3.06 $0.57 $0.60 75 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY and solar generation resources. Once candidate resource portfolios are developed using the SO model, the PaR model is used to evaluate portfolio risks. The PaR model inputs include regulation reserve requirements specific to the resource portfolio developed using the SO model. As a result, the IRP risk analysis using PaR includes the impact of differences in regulation reserve requirements between portfolios. Flexible Resource Requirements PacifiCorp’s flexible resource needs are the same as its operating reserve requirements over the planning horizon for maintaining reliability and compliance with the North American Electric Reliability Corporation (NERC) regional reliability standards. Operating reserve consists of three categories: (1) contingency reserve (i.e., spinning and supplemental reserve), (2) regulation reserve, and (3) frequency response reserve. Contingency reserve is capacity that PacifiCorp holds available to ensure compliance with the NERC regional reliability standard BAL-002-WECC-2.8 Regulation reserve is capacity that PacifiCorp holds available to ensure compliance with the NERC Control Performance Criteria in BAL-001-2.9 Frequency response reserve is capacity that PacifiCorp holds available to ensure compliance with NERC standard BAL-003-1.10 Each type of operating reserve is further defined below. Contingency Reserve NERC regional reliability standard BAL-002-WECC-2 specifies that each BAA must hold as contingency reserve an amount of capacity equal to three percent of load and three percent of generation in that BAA. Contingency reserve must be available within ten minutes, and at least half must be from “spinning” resources that are online and immediately responsive to system fluctuations. Contingency reserve may be deployed when unexpected outages of a generator or a transmission line occur. Contingency reserve may not be deployed to manage other system fluctuations such as changes in load or wind generation output. Regulation Reserve NERC standard BAL-001-2, which became effective July 1, 2016, does not specify a regulation reserve requirement based on a simple formula, but instead requires utilities to hold sufficient reserve to meet specified control performance standards. The primary requirement relates to area control error (“ACE”), which is the difference between a BAA’s scheduled and actual interchange, and reflects the difference between electrical generation and load within that BAA. Requirement 2 of BAL-001-2 defines the compliance standard as follows: Each Balancing Authority shall operate such that its clock-minute average of Reporting ACE does not exceed its clock-minute Balancing Authority ACE Limit 8 NERC Standard BAL-002-WECC-2 – Contingency Reserve: http://www.nerc.com/files/BAL-002-WECC-2.pdf 9 NERC Standard BAL-001-2 – Real Power Balancing Control Performance: http://www.nerc.com/files/BAL-001- 2.pdf 10 NERC Standard BAL-003-1 — Frequency Response and Frequency Bias Setting: http://www.nerc.com/pa/Stand/Reliability%20Standards/BAL-003-1.pdf 76 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY (BAAL) for more than 30 consecutive clock-minutes… In addition, Requirement 1 of BAL-001-2 specifies that PacifiCorp’s Control Performance Standard 1 (“CPS1”) score must be greater than equal to 100 percent for each preceding 12 consecutive calendar month period, evaluated monthly. The CPS1 score compares PacifiCorp’s ACE with interconnection frequency during each clock minute. A higher score indicates PacifiCorp’s ACE is helping interconnection frequency, while a lower score indicates it is hurting interconnection frequency. Because CPS1 is averaged and evaluated on a monthly basis, it does not require a response to each and every ACE event, but rather requires that PacifiCorp meet a minimum aggregate level of performance in each month. Regulation reserve is thus the capacity that PacifiCorp holds available to respond to changes in generation and load to manage ACE within the limits specified in BAL-001-2. Because Requirement 2 includes a 30 minute time limit for compliance, ramping capability that can be deployed within 30 minutes contributes to meeting PacifiCorp’s regulation reserve requirements. PacifiCorp has not specifically evaluated reserve needs for CPS1 compliance. The reserve for CPS1 is not expected to be incremental to the need for compliance with Requirement 2, but may require that a subset of resources held for Requirement 2 be able to make frequent rapid changes to manage ACE relative to interconnection frequency. Regulation reserve requirements are discussed in more detail later on in the study. Frequency Response Reserve NERC standard BAL-003-1 specifies that each BAA must arrest frequency deviations and support interconnection frequency when it drops below the scheduled level. When a frequency drop occurs, each BAA is expected to deploy resources that are at least equal to its Frequency Response Obligation. The incremental requirement is based on the size of the frequency drop and the BAA’s Frequency Response Obligation, expressed in MW/0.1Hz. The additional capacity must be deployed immediately, and performance is measured over a period of seconds, amounting to under a minute. To comply with the standard, a BAA’s median measured frequency response during a sampling of under-frequency events must be equal to or greater than its Frequency Response Obligation. PacifiCorp’s 2017 Frequency Response Obligation was 19.51 MW/0.1Hz for PACW, and 48.93 MW/0.1Hz for PACE. PacifiCorp’s combined obligation amounts to 68.44 MW for a frequency drop of 0.1 Hz, or 205.32 MW for a frequency drop of 0.3 Hz. Because the performance measurement for contingency reserve under the Disturbance Control Standard (BAL-002-1) is similar to that for BAL-003-1, frequency response capacity is effectively incremental to contingency reserve obligations. As Standard BAL-003-1 is based on median performance under selected WECC-wide events, while regulation reserve obligations under BAL-001-2 are based on minimum performance during BAA-specific events, frequency response capacity can be considered a subset of the BAL-001-2 obligation. Since median performance is adequate for BAL-003-1 compliance, BAL-001-2 compliance can take precedence, so long as the overlap is sufficiently low, i.e. BAL-001-2 events are rare and there don’t have a positive correlation with BAL-003-1 events. While frequency response reserve can meet regulation reserve requirements, the reverse is not necessarily true. Frequency response must occur very rapidly, and a generating unit’s capability is limited based on the unit’s size, governor controls, and available capacity, as well as the size of 77 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY the frequency drop. As a result, while a few resources could hold a large amount of regulation reserve, frequency response needs to be spread over a larger number of resources. Because PacifiCorp has excess spinning reserve capability compared to its contingency reserve obligation, the capacity and response time requirements for its frequency response obligations are expected to be met by drawing from its existing pool of regulation reserve resources. As a result, no incremental capacity requirements or resource constraints related to frequency response were included in the 2017 IRP analysis beyond those already included for contingency and regulation reserve. Description of Data Inputs Overview This section describes the data used to determine PacifiCorp’s regulation reserve requirements. In order to estimate PacifiCorp’s required regulation reserve amount, PacifiCorp must determine the difference between the expected load and resources and actual load and resources. The difference between load and resources is calculated every four seconds and is represented by the ACE. ACE must be maintained within the limits established by BAL-001-2, so PacifiCorp must estimate the amount of regulation reserve that is necessary in order to maintain ACE within these limits. To estimate the amount of regulation reserve that will be required in the future, the FRS identifies the scheduled use of the system as compared to the actual use of the system during the study term. For the baseline determination of scheduled use for load and resources, the FRS used hourly base schedules. Hourly base schedules are the power production forecasts used for imbalance settlement in the EIM and represent the best information available concerning the upcoming hour.11 The deviation from scheduled use was derived from data provided through participation in the EIM. The deviations of generation resources in EIM were measured on a five-minute basis, so the Regulation Reserve Study used five-minute intervals throughout the analysis. EIM base schedule and deviation data for each wind and Non-VER transaction point were downloaded using the Report Explorer application to query PacifiCorp’s nMarket Application database, which is populated with data provided by the CAISO. Since PacifiCorp’s implementation of EIM on November 1, 2014, PacifiCorp requires certain operational forecast data from all of its transmission customers pursuant to the provisions of Attachment T to 11 The CAISO, as the market operator for the EIM, requests base schedules at 75 minutes (“T-75”) prior to the hour of delivery. PacifiCorp’s transmission customers are required to submit base schedules by 77 minutes (“T-77”) prior to the hour of delivery – two minutes in advance of the EIM Entity deadline. This allows all transmission customer base schedules enough time to be submitted into the EIM systems before the overall deadline of T-75 for the entirety of PacifiCorp’s two BAAs. The base schedules are due again to CAISO at 55 minutes (“T-55”) prior to the delivery hour and can be adjusted up until that time by the EIM Entity (i.e., PacifiCorp Grid Operations). PacifiCorp’s transmission customers are required to submit updated, final base schedules no later than 57 minutes (“T-57”) prior to the delivery hour. Again, this allows all transmission customer base schedules enough time to be submitted into the EIM systems before the overall deadline of T-55 for the entirety of PacifiCorp’s two BAAs. Base schedules may be finally adjusted again, by the EIM Entity only, at 40 minutes (“T-40”) prior to the delivery hour in response to CAISO sufficiency tests. T-55 is the base schedule time point used throughout this study because it is the deadline which most closely corresponds to the final T-57 deadline for all transmission customers to submit final base schedules. 78 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY PacifiCorp’s Federal Energy Regulatory Commission (“FERC”)-approved Open Access Transmission Tariff (“OATT”). This includes EIM base schedule data (or forecasts) from all resources included in the EIM network model at transaction points. EIM base schedules are submitted by transmission customers with hourly granularity, and are settled using hourly data for load, and fifteen-minute and five-minute data for resources. A primary function of the EIM is to measure load and resource imbalance (or deviations) as the difference between the hourly base schedule and the actual metered values. A summary of the data gathered for this analysis is listed below, and a more detailed description of each type of source data is contained in the following subsections. Source data: - Load data o Five-minute interval actual Load o Proxy hourly base schedules developed from actual prior hour and prior week data - VER data o Five-minute EIM deviations o Hourly base schedules - Non-VER data o Five-minute EIM deviations o Hourly base schedules Load Data The Load class represents the aggregate firm demand of end users of power from the electric system. While the requirements of individual users vary, there are diurnal and seasonal patterns in aggregated demand. The Load class can generally be described to include three components: (1) average load, which is the base load during a particular scheduling period; (2) the trend, or “ramp,” during the hour and from hour-to-hour; and (3) the rapid fluctuations in load that depart from the underlying trend. The need for a system response to the second and third components is the function of regulation reserve in order to ensure reliability of the system. The PACE BAA includes several large industrial loads with unique patterns of demand. Each of these loads is either interruptible at short notice or includes behind the meter generation. Due to their large size, abrupt changes in their demand are magnified for these customers in a manner which is not representative of the aggregated demand of the large number of small customers which make up the majority of PacifiCorp’s loads. In addition, interruptible loads can be curtailed if their deviations are contributing to a resource shortfall. Because of these unique characteristics, these loads are excluded from the FRS. This treatment is consistent with that used in the CAISO load forecast methodology (used for PACE and PACW operations), which also nets these interruptible customer loads out of the PACE BAA. Actual average load data was collected separately for the PACE and PACW BAAs for each five- minute interval over the Study Term. Load data for the Study Term was downloaded from PacifiCorp’s Ranger PI system and has not been adjusted for transmission and distribution losses. Only actual load data is available from Ranger PI, not base schedule data that could be used to 79 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY determine the deviation associated with Load. Because of differences in the load defined in EIM and in the Ranger PI system, the EIM load base schedules are not consistent with the Ranger PI actual results. To address the inconsistency, PacifiCorp developed proxy load base schedules, as discussed below. Wind Data The Wind class includes resources that: (1) are renewable; (2) cannot be stored by the facility owner or operator; and (3) have variability that is beyond the control of the facility owner or operator.12 Wind, in comparison to load, often has larger upward and downward fluctuations in output that impose significant and sometimes unforeseen challenges when attempting to maintain reliability. For example, as recognized by FERC in Order No. 764, “Increasing the relative amount of [VERs] on a system can increase operational uncertainty that the system operator must manage through operating criteria, practices, and procedures, including the commitment of adequate reserves.”13 The data included in the FRS for the Wind class includes all wind resources in PacifiCorp’s BAAs, which includes: (1) third-party resources (OATT or legacy contract transmission customers); (2) PacifiCorp-owned resources; and (3) other PacifiCorp-contracted resources, such as qualifying facilities, power purchases, and exchanges. Appendix F.B, Table 1 contains the list of the wind plants included in the study. In total, the FRS includes 2,588 megawatts of wind. Non-VER Data The Non-VER class is a mix of thermal and hydroelectric resources and includes all resources which are not VERs, and which do not provide either contingency or regulation reserve. Non- VERs, in contrast to VERs, are often more stable and predictable. Non-VERs are thus easier to plan for and maintain within a reliable operating state. For example, in Order No. 764, FERC suggested that many of its rules were developed with Non-VERs in mind and that such generation “could be scheduled with relative precision.”14 The output of these resources is largely in the control of the resource operator, particularly when considered within the hourly timeframe of the FRS. The deviations by resources in the Non-VER class are thus significantly lower than the deviations by resources in the Wind class. The Non-VER class includes third-party resources (OATT or legacy transmission customers); many PacifiCorp-owned resources; and other PacifiCorp-contracted resources, such as qualifying facilities, power purchases, and exchanges. Appendix F.B, Table 2 contains the list of the Non-VERs included in the study. In total, the FRS includes 2,228 megawatts of Non-VERs. In the FRS, resources that provide contingency or regulation reserve are considered a separate, dispatchable resource class. The dispatchable resource class compensates for deviations resulting from other users of the transmission system in all hours. While non-dispatchable resources may offset deviations in loads and other resources in some hours, they are not in the control of the system operator and contribute to the overall requirement in other hours. Because the dispatchable resource class is a net provider rather than a user of regulation reserve service, its stand-alone regulation reserve requirement is zero (or negative), and its share of the system regulation reserve 12 Order No. 764 at P 281; Order No. 764-B at P 210. 13 Order No. 764 at P 20 (emphasis added). 14 Id. at P 92. 80 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY requirement is also zero. The allocation of regulation reserve requirements and diversity benefits is discussed in more detail later on in the study.. Data Analysis and Adjustment Overview This section provides details on adjustments made to the data to develop base schedules that correspond to the load data, align the ACE calculation with actual operations, and address data issues. Load Base Schedule Development Load deviations are settled using hourly imbalance data in EIM, whereas resource deviations are settled using fifteen-minute and five-minute imbalance data. As a result, the five-minute deviations necessary to assess the regulation reserve requirements associated with Load were not available through EIM. For the FRS, PacifiCorp used actual load data from its Ranger PI system, which can provide data at a five-minute granularity. The Ranger PI system does not have the associated base schedules necessary to calculate deviations, however, so PacifiCorp developed proxy load base schedules consistent with the measured actual loads. The load base schedule for each hour was calculated from actual load at 55 minutes prior to the hour (“T-55”) in question, with a scaling factor applied based on the change in load over that same interval in the prior week. The five-minute interval ending at T-55 is the last load data point available prior to base schedule submission to CAISO at hour T-55 and represents the current state of load in the PacifiCorp BAAs. Load follows different patterns depending on season and day of the week. Using data from one week prior ensures that recent conditions on a similar day are used in the calculation of the load base schedule. Figure F.1 below illustrates measurement of the expected load change between T-55 data and the hourly base schedule over three hours. The five-minute interval ending at 17:05 (first green column) has a load of 2,643 MW. The actual load in hour 18 averages 2,837 MW (middle solid horizontal line), an increase of 7.4 percent. Similarly, the expected load change from the five- minute interval ending at 18:05 to hour 19 is a decrease of 1.1 percent (difference between second green column and second horizontal line). Figure F.2 below shows how those load measurements are applied seven days later to determine the proxy load base schedules for hours 18 and 19. The proxy load base schedule for hour 18 is calculated as the actual load in the five-minute interval ending at 17:05, plus an additional 7.4 percent. The proxy load base schedule for hour 19 is calculated as the actual load in the five-minute interval ending at 18:05, minus 1.1 percent. Deviations are then calculated as the difference between the proxy load base schedule and actual five-minute loads over the hour. 81 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.1 - Expected Load Change from Prior Week 2,600 2,650 2,700 2,750 2,800 2,850 2,900 17 : 0 0 17 : 0 5 17 : 1 0 17 : 1 5 17 : 2 0 17 : 2 5 17 : 3 0 17 : 3 5 17 : 4 0 17 : 4 5 17 : 5 0 17 : 5 5 18 : 0 0 18 : 0 5 18 : 1 0 18 : 1 5 18 : 2 0 18 : 2 5 18 : 3 0 18 : 3 5 18 : 4 0 18 : 4 5 18 : 5 0 18 : 5 5 19 : 0 0 19 : 0 5 19 : 1 0 19 : 1 5 19 : 2 0 19 : 2 5 19 : 3 0 19 : 3 5 19 : 4 0 19 : 4 5 19 : 5 0 19 : 5 5 Actual Load (5-minute) Actual Load (Hourly) +7.4%, T-55 to next hour -1.1%, T-55 to next hour 82 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.2 - Proxy Load Base Schedule 2,600 2,650 2,700 2,750 2,800 2,850 2,900 17 : 0 0 17 : 0 5 17 : 1 0 17 : 1 5 17 : 2 0 17 : 2 5 17 : 3 0 17 : 3 5 17 : 4 0 17 : 4 5 17 : 5 0 17 : 5 5 18 : 0 0 18 : 0 5 18 : 1 0 18 : 1 5 18 : 2 0 18 : 2 5 18 : 3 0 18 : 3 5 18 : 4 0 18 : 4 5 18 : 5 0 18 : 5 5 19 : 0 0 19 : 0 5 19 : 1 0 19 : 1 5 19 : 2 0 19 : 2 5 19 : 3 0 19 : 3 5 19 : 4 0 19 : 4 5 19 : 5 0 19 : 5 5 Actual Load (5-minute) Base Schedule (Hourly) +7.4%, from prior week -1.1%, from prior week 83 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Base Schedule Ramping Adjustment In actual operations, PacifiCorp’s ACE calculation includes a linear ramp from the base schedule in one hour to the base schedule in the next hour, starting ten-minutes before the hour and continuing until ten-minutes past the hour. The hourly base schedules used in the study are adjusted to reflect this transition from one hour to the next. This adjustment step is important because, to the extent actual load or generation is transitioning to the levels expected in the next hour, the adjusted base schedules will result in reduced deviations during these intervals, potentially reducing the regulation reserve requirement. Figure F.3 below illustrates the hourly base schedule and the ramping adjustment. The same calculation applies to all base schedules: Load, Wind, Non-VERs, and the combined portfolio. Figure F.3 - Base Schedule Ramping Adjustment Data Corrections The raw data extracted from PacifiCorp’s systems for Load, Wind, and Non-VERs was reviewed to identify potentially spurious data points prior to performing the regulation reserve requirement calculations contained in the next section. Hourly intervals of data were excluded from the FRS results if any five-minute interval within that hour suffered from at least one of the data anomalies that are described further below: Ba s e S c h e d u l e ( M W ) Time (Interval Beginning) 84 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Load: • Stuck meter/flat meter reading • Telemetry spike/poor connection to meter Wind and Non-VERs: • Deviations missing in CAISO database • Base schedules missing in CAISO database • Generator trip events • Wind curtailment events Load in PacifiCorp’s BAAs changes continuously. While a BAA could potentially maintain the exact same load levels in two five-minute intervals in a row, it is extremely unlikely for the exact same load level to persist over longer time frames. When PacifiCorp’s energy management system (“EMS”) load telemetry fails, updated load values may not be logged, and the last available load measurement for the BAA will continue to be reported. For instance, in one observed example, PACW BAA load remained stuck at a single level for two days beginning at 2:00 PM on January 6, 2015. The change in load relative to the prior interval was calculated for the entire test period and instances where multiple successive intervals showed no change in load were excluded from the analysis since they are not indicative of actual operating conditions. Similarly, rapid spikes in load either up or down are also unlikely to be a result of conditions which require deployment of regulation reserve, particularly when they are transient. For example, a 637 MW drop in PACE BAA load occurred over one five-minute interval on May 15, 2015. Roughly one hour later, PACE BAA load increased by 849 MW over two five-minute intervals. Such events could be a result of a transmission or distribution outage, which would allow for the deployment of contingency reserve, and would not require deployment of regulation reserve. A similar spike on March 23, 2015, spanned just one five-minute interval, and was likely a result of a single bad load measurement. Load telemetry spike irregularities were identified by examining the intervals with the largest changes from one interval to the next, either up or down. Intervals with inexplicably large and rapid changes in load, particularly where the load reverts back within a short period, were assumed to have been covered through contingency reserve deployment or to reflect inaccurate load measurements. Because they don’t reflect periods that require regulation reserve deployment, such intervals are excluded from the analysis. The available Wind and Non-VER data also includes some data irregularities. PacifiCorp evaluated these irregularities and in some cases removed data that appears to be inaccurate. For instance, PACW wind deviation data is missing in 36 five-minute intervals out of the 105,108 intervals in the study. Deviations are directly tied to regulation reserve requirements, so the hours in which deviation data is missing are excluded from the analysis. Base schedules for PACE Non- VERs are missing in 75 hours, while the other wind and Non-VER categories have smaller amounts of missing data. While Wind base schedules are directly linked to the regulation requirement forecast, missing base schedule data in PacifiCorp’s database may be indicative of inconsistencies in deviation results, which may be calculated off of a stale or erroneous base. Given the limited frequency of such events, PacifiCorp has excluded from the analysis intervals where deviations or base schedules are missing. As with Load, certain Wind and Non-VER deviations are more likely to be a result of conditions that allow for the deployment of contingency reserve, rather than regulation reserve. In particular, 85 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY contingency reserve can be deployed to compensate for unexpected generator outages. For Non-VERs, these are relatively straightforward—namely, periods when generation drops to zero despite base schedules indicating otherwise. Certain Wind outages also qualify as contingency events. Notably, wind generators can be curtailed when wind speed exceeds the maximum rating of the equipment (sometimes referred to as “high speed cutout”). In such instances, generation is curtailed until wind speeds drop back into a safe operating range in order to protect the equipment. When wind speed oscillates above and below the cut-off point, generation may ramp down and up repeatedly. Because events which qualify for deployment of contingency reserve do not require deployment of regulation reserve they have been excluded from the analysis. As the regulation reserve requirements are calculated using a rolling thirty-minute timeline, data from the prior hour is necessary during the first several five-minute intervals of the next hour. An error in one hour thus results in the need to remove the following hour. This is relevant to error adjustments for both Wind and Non-VERs. For load, an hour of spurious data will prevent the calculation of the base schedule for the next hour, since the actual load at T-55 is not available. The spurious data also impacts the same two hours in the following week as the expected load change used to determine the base schedule for those hours utilizes the hour in question. For example, if the hour beginning at midnight on February 1, 2015, is found to be spurious, four hours are removed from the Study Term: the spurious hour (the hour ending midnight, February 1, 2015); the hour following the spurious hour (the hour ending 1:00 AM, February 1, 2015), which relies on the spurious hour to inform the regulation forecast; and the two corresponding hours in the following week (the hour ending at midnight, February 8, 2015 and the hour ending at 1:00 AM, February 8, 2015), each of which no longer has a valid prior-week hour from which to develop a proxy load base schedule. The description of “Load Base Schedule Development” above contains further discussion about this relationship and development of the base schedule. After review of the data for each of the above anomaly types, and out of 105,120 five-minute intervals in the Study Term, only 5.9 percent and 3.6 percent of the total FRS term hours were removed from PACW and PACE, respectively. The system-wide error rate was 9.1 percent, slightly lower than the sum of the PACW and PACE rates due to coincident hours. While cleaning up or replacing anomalous hours could yield a more complete data set, determining the appropriate conditions in those hours would be difficult and subjective. By removing anomalies, the FRS sample is smaller but remains reflective of the range of conditions PacifiCorp actually experiences, including the impact on regulation reserve requirements of weather events experienced during the Study Term. Non-VER Deviation Adjustment The deviations associated with the Non-VER class show a clear anomaly between January 2015 and April 14, 2015. The abrupt change is evident in the hourly data for PACW shown in Figure 4 below and a comparable anomaly was seen over the same time frame for PACE (not shown). The anomaly ends abruptly at midnight on April 14, 2015, in both BAAs. PacifiCorp has concluded that this issue is a result of errors in base schedule submission rather than an actual deviation. During the early stages of the EIM there were differences between the CAISO’s EIM model and PacifiCorp’s EMS. The modeling of Colstrip generation was one of those differences. Within the PacifiCorp EMS, 100 percent of Colstrip generation output is pseudo-tied into the PACW BAA. However, the EIM modeled 50 percent of Colstrip generation as being in the PACW BAA and the 86 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY other 50 percent of Colstrip generation as modeled in the PACE BAA. This mismatch between the two systems resulted in the measured deviation. The Colstrip EIM base schedule of 50 percent to PACE and 50 percent to PACW was compared to the EMS output of 100 percent to PACW to determine the deviation. This resulted in a positive deviation to base schedule for PACW. When the EIM model mismatch was discovered it was corrected to align to PacifiCorp’s EMS system. This eliminated the persistent deviation on April 14, 2015. For the purposes of the FRS, the regulation reserve requirement for this period was reduced by 58 MW such that the average requirement during this period is equal to the average in the remainder of 2015. The box in Figures F.4 and F.5 below shows the affected data before and after the adjustment is applied. Figure F.4 - Original PACW Non-VER Deviations The adjusted regulation reserve requirement is shown in Figure F.5 below. De v i a t i o n ( M W ) 87 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.5 - Adjusted PACW Non-VER Deviations Methodology to Determine Initial Regulation Reserve Requirement Overview This section presents the methodology used to determine the initial regulation reserve needed to manage the load and resource balance within PacifiCorp’s BAAs. The five-minute interval load and resource deviation data described above informs a regulation reserve forecast methodology that achieves the following goals: - Complies with NERC standard BAL-001-2; - Minimizes regulation reserve held; and - Uses data available at time of EIM base schedule submission at T-55.15 The components of the methodology are described below, and include: - Operating Reserve: Reserve Categories; - Calculation of Regulation Reserve Need; - Balancing Authority ACE Limit: Allowed Deviations; - Planning Reliability Target: Loss of Load Probability (“LOLP”); and 15 See footnote 11 above for explanation of PacifiCorp’s use of the T-55 base schedule time point in the FRS. De v i a t i o n ( M W ) 88 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY - Regulation Reserve Forecast: Amount Held. Following the explanation below of the components of the methodology, the next section details the forecasted amount of regulation reserve for: - Wind; - Non-VERs; and - Load. Components of Operating Reserve Methodology Operating Reserve: Reserve Categories Operating reserve consists of three categories: (1) contingency reserve (i.e., spinning and supplemental reserve), (2) regulation reserve, and (3) frequency response reserve. These requirements must be met by resources that are incremental to those needed to meet firm system demand. The purpose of the FRS is to determine the regulation reserve requirement. The contingency reserve requirement is defined formulaically by a regional reliability standard. Of the three categories of reserve referenced above, the FRS is primarily focused on the requirements associated with regulation reserve. Contingency reserve may not be deployed to manage other system fluctuations such as changes in load or wind generation output. Because deviations caused by contingency events are covered by contingency reserve rather than regulation reserve, they are excluded from the determination of the regulation reserve requirements. On the other hand, frequency response reserve can be considered a subset of the regulation reserve obligation, though it requires faster responding resources than those contemplated in the FRS. Because PacifiCorp has excess spinning reserve capability compared to its contingency reserve obligation, the capacity and response time requirements for its frequency response obligations are expected to be met by drawing from its existing pool of regulation reserve resources. As a result, no incremental capacity requirements or resource constraints related to frequency response were included in the FRS analysis. The types of operating reserve and relationship between them are further defined in in the Flexible Resource Requirements section above. Regulation reserve is capacity that PacifiCorp holds available to ensure compliance with the NERC Control Performance Criteria in BAL-001-2, which requires a BAA to carry regulation reserve incremental to contingency reserve to maintain reliability.16 The regulation reserve requirement is not defined by a simple formula, but instead is the amount of reserve required by each BAA to meet specified control performance standards. Requirement 2 of BAL-001-2 defines the compliance standard as follows: Each Balancing Authority shall operate such that its clock-minute average of Reporting ACE does not exceed its clock-minute Balancing Authority ACE Limit (BAAL) for more than 30 consecutive clock-minutes… The BAL-001-2 standard became effective as of July 1, 2016 and, upon its effectiveness, officially replaced the BAL-001-1 standard. The new BAL-001-2 standard is a fundamentally different 16 NERC Standard BAL-001-2, http://www.nerc.com/files/BAL-001-2.pdf 89 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY requirement than the prior standard, BAL-001-1, though it is intended to achieve a similar result. BAL-001-1 required ten-minute average ACE to be within the static L10 limit in at least 90 percent of non-overlapping ten-minute intervals in a month.17 The new BAL-001-2 standard requires average ACE to be within a dynamic limit for at least one minute in 100 percent of all rolling thirty-minute intervals. PacifiCorp has been operating under BAL-001-2 since March 1, 2010, as part of a NERC Reliability-Based Control field trial in the Western Interconnection, so PacifiCorp has experience operating under the new standard, even though it did not become effective until July 1, 2016. PacifiCorp’s 2012, 2013, and 2014 studies were all based on compliance with BAL-001-1. These studies utilized deviations over ten-minute intervals and allowed deviations up to the fixed L10 value.18,19 While these studies all used a 99.7 percent confidence interval, they did not necessarily achieve 99.7 percent compliance with the BAL-001-1 standard. For instance, the 2014 Wind Integration Study had a failure rate of 1.4 percent for PACE and 2.0 percent for PACW.20 This is higher than the 90 percent compliance requirement under BAL-001-1, but significantly lower than the 100 percent compliance requirement under BAL-001-2. In addition, prior studies separately distinguished between three categories of regulation reserve, all of which were intended to capture the total potential deviation over the ten-minute interval relevant under BAL-001-1: - Ramping – flexibility required to follow the change in actual net system Load from hour to hour; - Regulating – flexibility required to manage forecast uncertainty over ten-minute intervals; and - Following – flexibility required to manage forecast uncertainty over sixty-minute intervals. The FRS fundamentally differs from the 2012, 2013, and 2014 studies because it is based on compliance with BAL-001-2. The impacts of the changes in three key elements of the new BAL-001-2 standard relative to the old standard are summarized in Table F.3 below. The three key elements shown in Table F.3 include: (1) the length of time (or “interval”) used to measure compliance under the old versus new BAL standard; (2) the change in compliance threshold between the two standards, which represents the percentage of intervals that a BAA must be within the limits set in the standard; and (3) the bandwidth of acceptable deviation used under each standard to determine whether an interval is considered out of compliance. These changes are discussed in further detail below. 17 BAL-001-1 (R2) stated: Each Balancing Authority shall operate such that its average ACE for at least 90 percent of clock-ten-minute periods (6 non-overlapping periods per hour) during a calendar month is within a specific limit, referred to as L10. 18 L10 represents a bandwidth of acceptable deviation under BAL-001-1 prescribed by WECC between the net scheduled interchange and the net actual electrical interchange of PacifiCorp’s BAAs. 19 The L10 for PacifiCorp’s BAAs in 2015 were approximately 33.49 MW for PACW and 49.92 MW for PACE. For more information, please refer to: http://www.nerc.com/comm/OC/RS%20Landing%20Page%20DL/CPS2%20Bounds%20Reports/2015%20CPS2%2 0Bounds%20Report%20Final%2020150615.pdf 20 See Redacted Rebuttal Testimony of Brian S. Dickman, Wyoming Public Service Commission Docket No. 20000-469-ER-15 at p. 46:1-6 (filed Sept. 16, 2015). 90 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Table F.3 - BAL-001-1 vs BAL-001-2 The first change in Table F.3 is related to the length of time used to measure compliance. Under the prior standard, BAL-001-1, compliance was measured over six, non-overlapping ten-minute intervals within each hour. If ACE was within the allowed limits for all ten minutes of an interval, that interval was in compliance, and only the maximum deviation in that interval was considered in determining compliance. Compliance under BAL-001-2 is measured over rolling thirty-minute intervals, with sixty overlapping periods per hour, some of which include parts of two clock-hours. In effect, this means that every minute of every hour is the beginning of a new, thirty-minute compliance interval under the new BAL-001-2 standard. If ACE is within the allowed limits at least once in a thirty-minute interval, that interval was in compliance, and only the minimum deviation in each thirty-minute interval is considered in determining compliance. This change reduces regulation reserve requirements because PacifiCorp does not need to hold regulation reserve for deviations with duration less than 30 minutes. The second change in Table F.3 above is related to the compliance percentage, or the number of intervals where deviations are allowed to be outside the limits set in the standard. BAL-001-1 required 90 percent compliance, that is, 10 percent of ten minute intervals were allowed to have deviations in excess of the requirement in the standard. BAL-001-2 requires 100 percent compliance, so deviations must be maintained within the requirement set by the standard for all rolling thirty-minute intervals. Under the old standard, overall compliance could be achieved despite shortfalls in the intervals with the largest deviations. Because shortfalls are not permitted when the compliance requirement is 100 percent, this change increases regulation reserve requirements. The third change in Table F.3 is related to the bandwidth of acceptable deviation before an interval is considered out of compliance. Under BAL-001-1, the acceptable deviation for each BAA was set at a fixed value in all intervals, referred to as L10.21 Under BAL-001-2, the acceptable deviation for each BAA is dynamic, varying as a function of the frequency deviation for the entire interconnect. The impact of this change is mixed as the limits under BAL-001-2 are generally higher, but at times can be lower than the limits under BAL-001-1. In addition, the FRS identifies a single category of flexible capacity, rather than the three categories used in the prior studies performed in compliance with the old standard. Because deviations over ten-minute intervals are only relevant to the extent they exacerbate deviations over longer time 21 The L10 for PacifiCorp’s BAAs in 2015 were approximately 33.49 MW for PACW and 49.92 MW for PACE. For more information, please refer to: http://www.nerc.com/comm/OC/RS%20Landing%20Page%20DL/CPS2%20Bounds%20Reports/2015%20CPS2%2 0Bounds%20Report%20Final%2020150615.pdf . Interval (minutes)Compliance % Allowed Variance 91 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY frames, measuring three separate categories does not provide an accurate depiction of the requirements under BAL-001-2. In addition, while the following and regulating requirements in prior studies were statistically uncorrelated over the course of the year, the root sum square methodology used in the prior studies fails to account for the few random intervals when these components both show large requirements. Because the root sum square methodology underestimates the frequency of outlier events, it underestimates the capacity needed to cover them. The FRS eliminates complexity and distortion associated with combining multiple requirements by directly calculating a single component that allows for compliance with the BAL- 001-2 standard. Calculation of Regulation Reserve Need The next step of the operating reserve methodology is to calculate the amount of regulation reserve required to be held under BAL-001-2. Regulation reserve requirements were calculated from five- minute EIM deviation data in a manner that emulates the requirements of the BAL-001-2 standard. The same calculation applies to all types of imbalances: Load, Wind, Non-VERs, and the combined portfolio. First, the minimum five-minute imbalance was calculated for each thirty-minute rolling period in the Study Term. Second, for each hour, the maximum five-minute imbalance was selected from the values identified in the first step. An example is provided in the Table 2 and Figure 6 below. In the example in Table F.4 below, the minimum five-minute imbalance in the thirty minutes beginning at 0:15 is 40 MW. This is also the maximum five-minute imbalance in any thirty-minute period in this hour. Assuming 40 MW of regulation reserve was available in this hour and the allowable ACE deviation was zero, this hour would still be compliant with the BAL-001-2 requirement—even though the imbalance exceeds the regulation reserve available for five consecutive, five-minute intervals—because the allowable ACE deviation was exceeded for less than 30 minutes. Table F.4 - Deviation and Regulation Reserve Requirement Example Interval Base Schedule Actual 5-Minute Deviation 30-Minute Deviation Reserve Requirement 40 10 40 0:20 2550 50 10 40 0:25 2560 60 10 40 0:30 2570 70 20 40 0:35 2560 60 30 40 0:40 2550 50 40 40 0:45 2540 40 40 40 0:50 2530 30 30 40 0:55 2520 20 20 40 92 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY As shown in Figure F.6 below, if the ACE deviations were only allowed for a ten minute interval, the requirement would be higher. Figure F.6 - Deviation and Regulation Reserve Requirement Example Figure F.7 below illustrates the distribution of the combined five-minute deviations for Load, Wind, and Non-VERs in PACE during 2015, as well as the distribution of thirty-minute sustained deviations relevant to the BAL-001-2 standard. The effect for PACW was comparable (not shown). The thirty-minute window for compliance reduces the regulation reserve need. The thirty-minute window can be particularly helpful with deviations in the last few intervals of each hour. This period has the longest forecast horizon (i.e., the furthest out from T-55), so the potential deviations are expected to be larger. However, if the change resulting in the deviation is reflected in the base schedule for the next hour, PacifiCorp’s ACE will return to zero on its own a few minutes later. Thus, so long as the duration of the deviation is less than 30 minutes, the size of the deviation in the last few intervals is irrelevant for compliance with BAL-001-2. Me g a w a t t s ( M W ) Time (minutes) 93 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.7 - Probability Distribution of PACE Combined Portfolio Deviations Balancing Authority ACE Limit: Allowed Deviations Even if insufficient regulation reserve capability is available to compensate for a thirty-minute sustained deviation, a violation of BAL-001-2 does not occur unless the deviation also exceeds the Balancing Authority ACE Limit. The Balancing Authority ACE Limit is specific to each BAA and is dynamic, varying as a function of interconnection frequency. When WECC frequency is close to 60 Hz, the Balancing Authority ACE Limit is large and large deviations in ACE are allowed. As WECC frequency drops further and further below 60 Hz, ACE deviations are increasingly restricted for BAAs that are contributing to the shortfall, i.e. those BAAs with higher loads than resources. A BAA commits a BAL-001-2 reliability violation if in any thirty-minute interval it doesn’t have at least one minute when its ACE is within its Balancing Authority ACE Limit. While the specific Balancing Authority ACE Limit for a given interval cannot be known in advance, the historical probability distribution of Balancing Authority ACE Limit values is known. Figure 8 below shows the probability of exceeding the allowed deviation during a five-minute interval for a given level of ACE shortfall. For instance, a 47 MW ACE shortfall in PACE has a one percent chance of exceeding the Balancing Authority ACE Limit. The fixed value under the prior BAL-001-1 standard for L10 is also plotted for comparison. WECC-wide frequency can change rapidly and without notice, and this causes large changes in the Balancing Authority ACE De v i a t i o n ( M W ) Exceedance Probability 94 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Limit over short time frames. Maintaining ACE within the Balancing Authority ACE Limit under those circumstances can require rapid deployment of large amounts of operating reserve. To limit the size and speed of resource deployment necessitated by variation in the Balancing Authority ACE Limit, PacifiCorp’s operating practice caps permissible ACE at the lesser of the Balancing Authority ACE Limit or four times L10. This also limits the occurrence of transmission flows that exceed path ratings as result of large variations in ACE.22,23 This cap is reflected in Figure F.8. Figure F.8 - Probability of Exceeding Allowed Deviation In 2015, PacifiCorp’s deviations and Balancing Authority ACE Limits were uncorrelated, which indicates that PacifiCorp’s contribution to WECC-wide frequency is small. PacifiCorp’s deviations and Balancing Authority ACE Limits were also uncorrelated when periods with large deviations were examined in isolation. If PacifiCorp’s large deviations made distinguishable contributions to the Balancing Authority ACE Limit, ACE shortfalls would be more likely to exceed the Balancing Authority ACE Limit during large deviations. Since this is not the case, the probability of exceeding the Balancing Authority ACE Limit is lower, and less regulation reserve is necessary to comply with the BAL-001-2 standard. 22 “Regional Industry Initiatives Assessment.” NWPP MC Phase 3 Operations Integration Work Group. Dec. 31, 2014. Pg. 14. Available at: http://www.nwpp.org/documents/MC-Public/NWPP-MC-Phase-3-Regional-Industry-Initiatives-Assessment12-31-2014.pdf 23 “NERC Reliability-Based Control Field Trial Draft Report.” Western Electricity Coordinating Council. Mar. 25, 2015. Available at: https://www.wecc.biz/Reliability/RBC%20Field%20Trial%20Report%20Approved%203-25- 2015.pdf Pr o b a b i l i t y o f E x c e e d i n g Al l o w e d D e v i a t i o n ( % ) ACE Shortfall (MW) 95 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Planning Reliability Target: Loss of Load Probability When conducting resource planning, it is common to use a reliability target that assumes a specified LOLP. In effect, this is a plan to curtail firm load in rare circumstances, rather than acquiring resources for extremely unlikely events. The reliability target balances the cost of additional capacity against the benefit of incrementally more reliable operation. By planning to curtail firm load in the rare event of a regulation reserve shortage, PacifiCorp can maintain the required 100 percent compliance with the BAL-001-2 standard and the Balancing Authority ACE Limit. This balances the cost of holding additional regulation reserve against the likelihood of regulation reserve shortage events. PacifiCorp’s 2015 Integrated Resource Plan (“IRP”) utilized a planning reserve margin of 13 percent, which is intended to achieve 0.88 loss of load hours per year.24 This FRS assumes that 0.88 loss of load hours per year due to regulation reserve shortages is appropriate for planning and ratemaking purposes. This is in addition to any loss of load resulting from transmission or distribution outages, resource adequacy, or other causes. The FRS applies this reliability target as follows: • If the regulation reserve available is greater than the regulation reserve need for an hour, the LOLP is zero for that hour. • If the regulation reserve held is less than the amount needed, the LOLP is derived from the Balancing Authority ACE Limit probability distribution. As the magnitude of the shortfall increases, the probability of exceeding the Balancing Authority ACE Limit increases. For instance, as indicated above, a 47 MW ACE shortfall in PACE has a one percent chance of exceeding the Balancing Authority ACE Limit. A one percent probability of failing to meet the Balancing Authority ACE Limit in one hour is 0.01 loss of Load hours per year. A one percent probability of failing to meet the Balancing Authority ACE Limit in eighty- eight hours would be 0.88 loss of load hours per year and corresponds to the targeted level of reliability. Regulation Reserve Forecast: Amount Held As previously shown in Figure 7, the instances requiring the largest amounts of regulation reserve occur infrequently, and many hours have very low requirements. If periods when requirements are likely to be low can be distinguished from periods when requirements are likely to be high, less regulation reserve is necessary to achieve a given reliability target. As described above, the regulation reserve forecast is not intended to compensate for every potential deviation. Instead, when a shortfall occurs, the size of that shortfall determines the probability of exceeding the Balancing Authority ACE Limit and a reliability violation occurring. The forecast should achieve a cumulative LOLP that corresponds to the annual reliability target. PacifiCorp submits balanced base schedules to CAISO for its load and resources by T-55.25 Operating reserve is intended to cover demand in excess of the balanced load and resources submitted in base schedules. Capacity to be used as operating reserve needs to be identified and 24 2015 IRP, Appendix I, Table I.3 25 See footnote 9 for explanation of PacifiCorp’s use of the T-55 base schedule time point in the Regulation Reserve Study. 96 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY set aside so that it is not utilized in the base schedule submission. Likewise, the regulation reserve forecast identifying the quantity of operating reserve to be set aside for the upcoming hour needs to be finalized by T-55. The base schedule itself reflects the best, most up-to-date information about conditions in the upcoming hour. The next section describes how the information available can be used to forecast regulation reserve requirements for each of the regulation reserve classes while maintaining reliability. The portfolio regulation reserve requirement forecast incorporates each of the resource/load class forecasts and accounts for the reduced requirements resulting from diversity between the classes. All of these calculations are prepared separately for each of the PacifiCorp BAAs. 2015 Regulation Reserve Forecast Wind Figure F.9 illustrates the relationship between the observed regulation reserve requirements for wind during 2015 and the forecasted level of output, stated as a capacity factor (i.e., a percentage of the nameplate wind capacity). Three distinct patterns are apparent in the figure. First, for capacity factors from zero percent to approximately 20 percent, the regulation reserve requirement increases linearly. The linear relationship in this first range reflects the fact that the largest possible deviation is equal to the base schedule and a very small amount of negative generation (station service). Second, for capacity factors from approximately 20 percent to approximately 80 percent, the maximum requirement varies somewhat widely and does not exhibit significant trends. Third, as capacity factors increase above approximately 80 percent, the observed maximum requirement declines. 97 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.9 - Wind Regulation Reserve Requirements by Forecast Capacity Factor When evaluating the distribution of maximum requirements above an approximately 20 percent capacity factor, it is important to consider the characteristics of an observed maximum within a sample. The mean of a sample may be higher or lower than the mean of the population from which it is drawn, but it is not expected to vary systematically with sample size. This is not the case for the maximum of a sample, which will always be less than or equal to the maximum of the population from which it is drawn. In addition, the expected value of the sample maximum increases as the sample size increases. The sample size of each forecasted capacity factor varies, with very high capacity factors occurring less frequently. With this consideration in mind, the decline in observed maximum requirements at high capacity factors can be viewed as an artifact of the sample rather than a real trend related to the behavior of wind under those specific conditions. This view is reinforced by the fact that the average and standard deviation of the requirements are relatively constant at forecasted capacity factors above roughly 20 percent. Because the probability of a large deviation doesn’t vary for capacity factors above roughly 20 percent, a single regulation reserve requirement is a reasonable forecast for that range. Figure F.10 below presents the regulation reserve forecast for PACE and PACW wind, incorporating the two trends described above: (1) the linear increase in requirements at low capacity factors (i.e., below 20 percent); and (2) a uniform requirement at higher capacity factors (i.e., from 20 percent to 100 percent). As illustrated in Figure 10, PACW had 888 hours with forecasted capacity factors between 41 percent and 55 percent, while PACE had 1,115 hours in Re q u i r e m e n t a s a P e r c e n t o f N a m e p l a t e Forecast Capacity Factor 98 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY that range. PACW only had 64 hours with forecasted capacity factors of 85 percent or more, while PACE only had 109 hours in that range. The wind regulation reserve forecast is a fixed percentage of the wind nameplate capacity, but never more than the difference between minimum actual output and the base schedule. The fixed percentage of nameplate capacity is set at the minimum level that achieves the reliability target of 0.88 loss of load hours per year. The forecast resulted in the possibility of reliability violations in roughly one percent of the hours. While the forecast does not result in any potential reliability violations at high capacity factors, this is likely due to the small number of observations in this range, as described above. Using a forecast based on the hour-ahead base schedule results in a 2015 stand-alone regulation reserve requirement for wind of 384 MW, or approximately 14.8 percent of nameplate capacity. This forecast does not account for any diversity benefit from combining the reserve requirements for wind with the requirements of other classes. Diversity benefits are discussed later on in the study. Figure F.10 - Stand-alone Wind Regulation Reserve Forecast 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 0%5%10%15%20%25%30%35%40%45%50%55%60%65%70%75%80%85%90%95%100% Max Requirement PACW Max Requirement PACE Forecast Reserve PACW Forecast Reserve PACE 99 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Non-VERs Figure F.11 below illustrates the observed regulation reserve requirements for Non-VERs during 2015 as a function of the forecasted level of output, stated as a capacity factor (i.e., a percentage of the nameplate Non-VERs capacity). For Non-VERs, the forecasted capacity factors during 2015 fall within limited ranges and do not approach either zero or 100 percent. Since the distribution of errors appears to be essentially random, the base schedule provides limited forecasting value for Non-VERs, resulting in a single reserve value applied in all hours. Figure F.11 - Non-VER Regulation Reserve Requirements by Forecast Capacity Factor Figure F.12 below illustrates the observed regulation reserve requirements for Non-VERs during 2015 as a function of hour of the day. The average and standard deviation are very low compared to the maximum events, indicating the relative rarity of large deviation events. However, the maximum, average, and standard deviation all exhibit comparable trends, indicating that the characteristics of the maximum are also reflected in the rest of the data for those periods. While an overall diurnal pattern is noticeable, significant volatility in the observed maximum requirements is apparent from hour to hour. For example, consider the significant drop in the observed maximum requirement for PACW in hour 19 relative to hours 18 and 20. The average and standard deviation do not indicate that hour 19 is significantly different from hours 18 and 20. As a result, this drop is more likely to be from randomness in the sample, rather than a specific characteristic of hour 19 itself. Re q u i r e m e n t a s a Pe r c e n t o f N a m e p l a t e : P A C E Re q u i r e m e n t a s a Pe r c e n t o f N a m e p l a t e : P A C W Forecast Capacity Factor 100 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.12 - Non-VER Regulation Reserve Requirements by Hour of the Day Figure F.13 below presents the regulation reserve forecast for each hour of the day for PACE and PACW Non-VERs. The forecast is based on the rolling three-hour maximum of regulation reserve requirements from 2015. This produces a smoother forecast, reflecting realistic hourly variation rather than just aligning with the large events in the sampled data for 2015. The forecasted requirement is then reduced by a fixed percentage until it reaches the minimum level necessary to achieve the reliability target of 0.88 loss of load hours per year. This forecast resulted in the possibility of reliability violations roughly 1.1 percent of the time on PACW, and 2.6 percent of the time on PACE. Due to the lower probability of a reliability violation in each hour for PACE Non-VERs, more hours of potential violations are aggregated to reach the reliability target of 0.88 loss of load hours per year. Using a forecast based on the hour of the day results in a 2015 stand- alone regulation reserve requirement for Non-VERs of 83 MW, or approximately 3.7 percent of nameplate capacity. This forecast does not account for any diversity benefit from combining the regulation reserve requirements for Non-VERs with the requirements of other classes. Re q u i r e m e n t a s a Pe r c e n t o f N a m e p l a t e : P A C E Re q u i r e m e n t a s a Pe r c e n t o f N a m e p l a t e : P A C W Hour 101 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.13 - Stand-alone Non-VER Regulation Reserve Forecast Load Figure F.14 below illustrates the relationship between the observed regulation reserve requirements for load during 2015 and hour of the day. Similar to the results for Non-VERs, the average and standard deviation are very low compared to the maximum events, indicating the relative rarity of large deviation events. However, the maximum, average, and standard deviation all exhibit comparable trends, indicating that the characteristics of the maximum are also reflected in the rest of the data for those periods. Re q u i r e m e n t a s a Pe r c e n t o f N a m e p l a t e : P A C E Re q u i r e m e n t a s a Pe r c e n t o f N a m e p l a t e : P A C W Hour 102 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.14 - Stand-alone Load Regulation Reserve Requirements by Hour of the Day Figure F.15 below presents the regulation reserve forecast for each hour of the day for PACE and PACW load. The forecast is based on the rolling three-hour maximum of regulation reserve requirements from 2015. This produces a smoother forecast, reflecting realistic hourly variation rather than just aligning with the large events in the sampled data for 2015. The forecasted requirement is then reduced by a fixed percentage until it reaches the minimum level necessary to achieve the reliability target of 0.88 loss of load hours per year. This forecast resulted in the possibility of reliability violations roughly 0.7 percent of the time in both PACW and PACE. Using a forecast based on the hour of the day results in a 2015 stand-alone regulation reserve requirement for load of 433 MW, or approximately 4.5 percent of the 12CP. This forecast does not account for any diversity benefit from combining the reserve requirements for load with the requirements of other classes. Re q u i r e m e n t : P A C E Re q u i r e m e n t : P A C W Hour 103 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.15 - Stand-alone Load Regulation Reserve Forecast 2015 PacifiCorp System Diversity and EIM Diversity Benefits PacifiCorp System-Wide Portfolio Diversity Benefit The EIM is a voluntary energy imbalance market service through the CAISO where market systems automatically balance supply and demand for electricity every fifteen minutes, dispatching the least-cost resources every five minutes. PacifiCorp began full EIM operation on November 1, 2014. NV Energy began full operation in EIM on December 1, 2015. Puget Sound Energy and Arizona Public Service Company commenced EIM participation on October 1, 2016. Additionally, several other entities have announced their intention to begin participating over the next few years. PacifiCorp’s participation in the EIM results in improved power production forecasting and optimized intra-hour resource dispatch. This brings important benefits including reduced energy dispatch costs through automatic dispatch, enhanced reliability with improved situational awareness, better integration of renewable energy resources, and reduced curtailment of renewable energy resources EIM also direct effects related to regulation reserve requirements. First, as a result of EIM participation, PacifiCorp has improved granularity for data used in the analysis contained in this FRS. The data and control provided EIM allow PacifiCorp to achieve the portfolio diversity benefits described in this section. Second, the EIM’s intra-hour capabilities across the broader EIM Re q u i r e m e n t : P A C E Re q u i r e m e n t : P A C W Hour 104 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY footprint provide the opportunity to reduce the amount of regulation reserve necessary for PacifiCorp to hold, as further explained in the next section. The regulation reserve forecasts described above (384 MW for Wind, 83 MW for Non-VERs, and 433 MW for Load) independently ensure that the probability of a reliability violation for each class remains within the reliability target; however, the largest deviations in each class tend not to occur simultaneously, and in some cases deviations will occur in offsetting directions. Because the deviations are not occurring at the same time, the regulation reserve held can cover the expected deviations for multiple classes at once and a reduced total quantity of reserve is sufficient to maintain the desired level of reliability. This reduction in the reserve requirement is the diversity benefit from holding a single pool of reserve to cover deviations in Wind, Non-VERs, and Load. As a result, the regulation reserve forecast for the portfolio can be reduced while still meeting the reliability target. As shown in Table F.5 below, the sum of the stand-alone forecasts for each class results in a cumulative LOLP of 0.03 hours per year. This is significantly less than the target of 0.88 hours per year as a result of the diversity among the different classes. PacifiCorp then calculated the proportional reduction to the standalone requirement—the diversity benefit shown in the second column of values in Table 3—that could be applied such that the PacifiCorp system just achieves the reliability target for the Study Term. A total portfolio requirement of 654 MW is sufficient to achieve the reliability target, resulting in diversity benefits equal to 118 MW for Load, 105 MW for Wind, and 23 MW for Non-VERs. The last column of Table 3 shows the regulation requirements for each class that incorporates the proportional allocation of portfolio diversity benefits. The diversity benefits result in a 27 percent reduction from the total standalone requirement of 900 MW. Table F.5 - Results with PacifiCorp Portfolio Diversity EIM Intra-Hour Benefit In addition to the direct benefits from EIM’s increased system visibility and improved intra-hour operational performance described above, the participation of other entities in the broader EIM footprint—such as NV Energy, Puget Sound Energy, and Arizona Public Service Company— provides the opportunity to further reduce the amount of regulation reserve PacifiCorp must hold. By pooling variability in load, wind, and solar output, EIM entities reduce the quantity of reserve required to meet flexibility needs. The EIM also facilitates procurement of flexible ramping Stand-alone Regulation Forecast Diversity Benefit Portfolio Regulation Forecast Scenario (aMW)(aMW)(aMW) 105 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY capacity in the fifteen-minute market to address variability that may occur in the five-minute market. Because variability across different BAAs may happen in opposite directions, the flexible ramping requirement for the entire EIM footprint can be less than the sum of individual BAAs’ requirements. This difference is known as the “flexible ramping procurement diversity savings” in the EIM. This intra-hour benefit reflects offsetting variability and lower combined uncertainty. This flexibility reserve is in addition to the spinning and supplemental reserve carried against generation or transmission system contingencies under the NERC standards. The CAISO calculates the EIM intra-hour benefit by first calculating a flexible reserve requirement for each individual EIM BAA and then by comparing the sum of those requirements to the flexible reserve requirement for the entire EIM area. The latter amount is expected to be less than the sum of the flexible reserve requirements from the individual BAAs due to the portfolio diversification effect of forecasting a larger pool of load and resources using intra-hour scheduling and increased system visibility in the hypothetical, single-BAA EIM. Each EIM BAA is then credited with a share of the intra-hour benefit calculated by CAISO based on its share of the stand-alone requirement relative to the total stand-alone requirement. The EIM does not relieve participants of their reliability responsibilities. EIM entities are required to have sufficient resources to serve their load on a standalone basis each hour before participating in the EIM. Thus, each EIM participant remains responsible for all reliability obligations. Despite these limitations, EIM imports from other participating BAAs can help balance PacifiCorp’s loads and resources within an hour, reducing the size of reserve shortfalls and the likelihood of a Balancing Authority ACE Limit violation. While substantial EIM imports do occur in some hours, it is only appropriate to rely on PacifiCorp’s share of the intra-hour benefits associated with EIM, as these are derived from the structure of the EIM rather than resources contributed by other participants. Under the current EIM operational structure, the calculated EIM intra-hour benefit is not known to PacifiCorp prior to its base schedule submission at T-55. The CAISO does not finalize the intra- hour benefit until T-40, therefore making it too late to incorporate any of the benefit into PacifiCorp’s base schedule. Table F.6 below provides a numeric example of flexible reserve requirements for each EIM participating BAA and application of the calculated intra-hour benefit. Table F.6 - EIM Flexible Reserve Diversity Benefit Application Example While the intra-hour benefit is uncertain, that uncertainty is not significantly different from the uncertainty in the Balancing Authority ACE Limit described above. PacifiCorp proposes crediting its regulation reserve forecast with a probability distribution of calculated EIM intra-hour benefits CAISO req't. before benefit NEVP req't. before benefit PACE req't. before benefit PACW req't. before benefit Total req't. before benefit Total req't. after benefit Total diversity benefit PACE share PACE benefit PACE req't. after benefit Interval (MW)(MW)(MW)(MW)(MW)(MW)(MW)(%)(MW)(MW) 106 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY based on historical results. When a potential regulation shortfall occurs, the probability that the EIM intra-hour benefit would have exceeded that level can be calculated, and the LOLP associated with that event goes down. As a result, PacifiCorp’s regulation reserve requirements can be reduced until the reliability target is again just achieved. While this FRS considers regulation reserve requirements in 2015, the participation of NV Energy in the EIM starting in December 2015 has resulted in increased intra-hour benefits. To capture these additional benefits for this analysis, PacifiCorp has applied the probability distribution of EIM intra-hour benefits from January 2016 through June 2016 because it is a more reasonable representation of actual operations going forward than the 2015 results. Relatively small incremental EIM diversity benefits are expected going forward as additional entities participate in EIM; however, operational data on new participants was not available at the time the study was prepared. The inclusion of EIM intra-hour benefits in the 2015 regulation reserve analysis reduces the probability of reserve shortfalls and, in doing so, reduces the overall regulation reserve requirement. This allows PacifiCorp’s forecasted requirements to be reduced until the PacifiCorp system just achieves the reliability target for the 2015 Study Term. As shown in Table F.7 below, the resulting regulation reserve requirement is 562 MW, a 38 percent reduction (including the portfolio diversity benefit) compared to the stand-alone requirement for each class. The average regulation reserve requirement is reduced by 92 MW relative to the PacifiCorp portfolio reserve requirement without the EIM intra-hour benefit. Table F.7 - 2015 Results with PacifiCorp Portfolio Diversity and EIM Intra-Hour Benefit Incremental Wind Regulation Reserve Requirements Since 2015, 153 MW of wind resources have been added to PacifiCorp’s system. Furthermore, the IRP portfolio optimization process contemplates the addition of new wind capacity as part of its selection of future resources. As PacifiCorp’s portfolio of resources grows, the diversity of that portfolio is also expected to increase. As a result, incremental regulation reserve requirements are expected to be lower than the average requirement for a given portfolio. The need to develop realistic deviation data for a period during which resources did not exist makes measuring an incremental diversity effect a difficult proposition. Instead, PacifiCorp’s FRS evaluated the decremental diversity associated with reducing the size of PacifiCorp’s wind portfolio. Removing specific resources produces a similar change in the size of PacifiCorp’s Stand-alone Regulation Forecast Stand-alone Rate Portfolio Regulation Forecast with EIM Portfolio Rate with EIM 2015 Capacity Rate Determinant Scenario (aMW)(%)(aMW)(%)(MW) Total 900 562 107 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY portfolio without requiring the creation of any data points. Specifically, the PacifiCorp system-wide results described above were recalculated using only 90 percent of the available wind resources, by removing approximately 10 percent of the wind capacity from each geographic location. Regulation reserve requirements for PacifiCorp’s system-wide portfolio dropped by 6.1percent of the wind capacity removed. This is lower than the average requirement of 9.2 percent in the 2015 portfolio results shown in Table F.7 above. This indicates that diversity is increasing as the pool of requirements increases, as expected. These incremental wind regulation requirement results are incorporated in the forecasted portfolio regulation results discussed later on in the study. Solar Regulation Reserve Requirements Overview At the start of 2015, PacifiCorp had less than three megawatts of utility-scale solar generating capacity on its system. Over the course of 2015, an additional 165 MW was added but the majority was from two large resources which only came online in the second half of December. As shown in Figure F.16, solar capacity has increased rapidly in both PACE and PACW and by the end of 2017 is expected to total over 1,000 MW. Reference Table F.25 on page 64 contains the list of solar resources included in the study. Because solar resources have only recently been added to PacifiCorp’s system, the 2015 study period used for the regulation reserve requirements for load, wind, and Non-VERs does not have data suitable predict current and future solar regulation reserve requirements. 108 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.16 - Solar Capacity Additions Five-minute solar data was collected from PacifiCorp’s Ranger PI system for Jan. 1, 2016 through Aug. 23rd, 2016 for two large solar resources in southern Utah totaling 130 MW.26 PacifiCorp’s solar forecast service provider, DNV GL, provided generation forecasts for these resources during this timeframe, which were submitted to EIM. While EIM deviation data is available for a portion of this period, certain meteorological monitoring equipment was not in place for the entire timeframe, and the limited availability of historical results are expected to make the forecasts for these resources less accurate than what will be possible going forward. Instead, proxy solar base schedules were developed for these two resources, as described in the next section. To make the results easier to compare and apply elsewhere, the actual output of the resources was normalized by their capacity. The calculations described below were all carried out on a capacity factor basis. Proxy Solar Base Schedule Development Solar resource output is primarily a function of two attributes: the position of the sun, and the amount of cloud cover. The position of the sun is comparable from day to day at a given time, though over the course of weeks it changes by meaningful amounts. To estimate the maximum possible output for a particular date and time, the maximum output at that time from two weeks prior to two weeks following is calculated. The four week span helps ensure that at least one data point is likely to have very little cloud cover and maximum output, while limiting the effect of 26 Pavant I, 50 MW and Utah Red Hills, 80 MW. Cu m u l a t i v e S o l a r C a p a c i t y ( M W ) Pavant I Red Hills Available 5-min data 109 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY seasonal changes in the position of the sun. Identifying the maximum possible output for each interval allows the forecast to account for changes in output as the sun rises and sets. The following calculations were carried out independently for the two solar resources. To estimate the amount of cloud cover, the solar availability is calculated by dividing the actual output in each five-minute interval by the maximum output for that interval, as identified above. This removes the effect of the position of the sun, and the changes that remain should primarily be primarily associated with cloud cover. From day to day, cloud cover is expected to vary widely, but from T-55 when the solar resource forecast is submitted as an hourly base schedule to EIM through the course of that upcoming hour, it is reasonable to assume the prevailing cloud conditions will continue. To improve further upon the cloud cover forecast using the available data, the trend in cloud conditions leading up to the time of forecast submission was also accounted for. If it is less cloudy at T-55 than it was twenty minutes earlier, that trend is also extrapolated forward to the forecast period. The weighting of the trend versus the final measurement before the forecast is submitted was set to maximize the correlation between the actual solar output and the forecasted hourly base schedule, i.e. to produce the best achievable forecast. Due to the absence of generation output, cloud cover can’t be estimated from intervals prior to sunrise, so the forecasted output during the first hours after sunrise is set at the monthly average for those intervals. The proxy solar base schedules incorporate cloud cover data and solar position data as follows. The cloud cover measurement is the primary component in the forecast for the upcoming hour. The cloud cover trend over the preceding intervals, and the cloud cover in the last interval are locked in at the values measured just prior to base schedule submission. On the other hand the position of the sun, embedded in the maximum output for each interval, is assumed to be fixed and known in advance. The base schedule submission looks forward in time to the forecast hour and incorporate the expected solar position changes over each five-minute interval in the hour. While the forecast is created with a five-minute granularity, the base schedule submission to EIM at T-55 reflects an hourly average value in accordance with EIM operating procedures. The difference between this hourly average and the five-minute actual resource output (i.e. the original source data) is the deviation of the solar resource. Once base schedule and deviation data were prepared for the two solar resources, those deviations were applied in the same template used to calculate hourly regulation reserve requirements for load, wind, and Non-VERs, including the base schedule ramping adjustment described previously. This identifies the minimum hourly regulation reserve needed to guarantee compliance with BAL-001-2 with the resource in question viewed in isolation. As shown in Figure F.17, the proxy solar forecasts have less frequent large deviations, and thus produce fewer instances of large regulation reserve requirements than the available EIM deviation data from the same period. Note that while Pavant I become operational in 2015, EIM deviations only became available starting April 1, 2016. For comparability, the proxy and EIM results for each generator are shown for the overlapping time period only. Regulation reserve requirements in excess of approximately 15 percent of nameplate capacity occurred more frequently in the EIM data than the proxy data. Because the largest errors are most likely to cause a BAAL violation, they drive the majority of the reserve requirement. Future results will show whether the forecast accuracy that can be achieved in actual practice is higher or lower than that in the proxy data used in this analysis. 110 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.17 - Solar Regulation Reserve Requirements: Proxy vs EIM Solar Diversity When the hourly regulation reserve requirements of the two solar resources are measured independently, as described above, the results do not capture any of the potential for diversity in the intra-hour requirements. To identify the potential diversity between the two solar resources, the average of their base schedules and actual output was used in the hourly regulation reserve calculation. The difference between the requirements when measured independently and the requirements when measured in aggregate is the result of diversity. The results of this diversity measurement are shown in Figure F.18. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0%10%20%30%40%50%60%70%80%90%100% Red Hills EIM Proxy Red Hills Pavant I EIM Proxy Pavant I EIM has high reserve requirements more frequently than Proxy Red Hills data Jan. -Aug. 2016 Pavant I data Apr. -Aug. 2016 Frequency of 50% Reserve RequirementEIMProxy Red Hills 4.4%1.9%Pavant 3.0%1.9% 111 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.18 - Solar Diversity As shown in Figure F.18, diversity is not guaranteed to reduce hourly regulation reserve requirements. While this is not intuitive, it is a direct result of the 30 minute maximum time limit for deviations under BAL-001-2. If two resources each have deviations that are only 20 minutes long, the regulation reserve requirement is zero. If the deviations both started at the same time, then viewed together they will overlap perfectly, and the length of the deviation remains just 20 minutes with a regulation reserve requirement of zero. However, if one resource’s deviation starts 15 minutes earlier than the other, the length of the aggregate deviation will be 35 minutes, and the regulation reserve requirement will be greater than zero to ensure compliance with BAL-001-2. Despite the potential for increased aggregate requirements in some instances, on average the aggregate requirements are lower as a result of diversity. Because the regulation requirements are bounded by zero, the diversity benefit is limited to the size of the independent requirement. As a result, the diversity benefits increase as the independent requirements increase. Solar Locations The solar facilities on PacifiCorp’s system are concentrated in southeastern Utah and southern and central Oregon. As shown in Figure F.19, within these areas multiple facilities are also clustered within relatively close proximity. Five clusters were identified in Utah, while three were identified in Oregon. Because one of the Oregon clusters is relatively dispersed, it is treated as two independent clusters. So l a r D i v e r s i t y (C o m b i n e d R e q u i r e m e n t l e s s I n d e p e n d e n t ) Independent Solar Regulation Reserve Requirements 112 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.19 - Solar Resource Locations Southeastern Utah South/Central Oregon While all of the clusters identified are in close enough proximity to experience most of the same passing weather systems, different clusters experience different cloud cover at the time of forecast submission, and different cloud cover over the course of the operating hour. These differences are in turn reflected in their actual output and deviations. On the other hand, due to their proximity, facilities within a given cluster are expected to reflect more closely-related weather conditions in their forecasts and deviations. As a result, the aggregate capacity within a given cluster is not expected to experience offsetting deviations, i.e. diversity benefits, whereas the effect of capacity spread among multiple clusters should create opportunities for offsetting deviations. The IRP is focused not just on regulation reserve requirements for existing solar resources, but also on the requirements associated with incremental solar resources added in the future. Tables F.8 and F.9 present the solar capacity on PacifiCorp’s system in three scenarios. The base scenario reflects the contracted solar resources scheduled to be online in 2017, while two incremental scenarios reflect the addition of 500 MW and 1000 MW of new solar resources. The incremental solar capacity is split between the PACE and PACW BAAs, and among existing and new clusters. 113 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Table F.8 - East Solar Clusters by Scenario Table F.9 - West Solar Clusters by Scenario Solar Portfolio Data Red Hills and Pavant have proxy base schedules, hourly regulation reserve requirements, and diversity based on actual generation. It is reasonable to assume other solar resources within those two clusters would experience comparable conditions and results. Therefore, the Red Hills and Pavant results are scaled up to reflect any additional capacity within the cluster. At the time the study was prepared, actual data for the other clusters in PACE and all of the clusters in PACW was unavailable. While the varying geographic locations of these clusters impact the timing of weather conditions, they are all relatively sunny locations, and it is reasonable to assume that the likelihood of over-forecasting resource output, resulting in a regulation reserve requirement, is similar in all of the clusters. With this in mind, all of the hourly regulation reserve requirements for Red Hills and Pavant (measured independently) were taken as a single data set and hourly regulation reserve requirements for the other clusters were assigned randomly from this distribution. While the resulting hourly regulation reserve requirements vary from 0 percent to 95 percent of the solar nameplate capacity, 18.7 percent of the regulation reserve requirements are zero, and half of the regulation reserve requirements are less than 2 percent of the solar nameplate. Despite being predominantly random, there is a relatively small positive correlation (+0.2638) between the hourly regulation reserve requirements for Red Hills and Pavant. This may reflect weather conditions that occur at the same time over a broad area, such as afternoon thundercloud formation, rather than as a result of passing weather fronts. This relationship is assumed to be real effect and is reflected in each of the calculated clusters by blending a random regulation requirement and the simultaneous requirement for one of the two source clusters. The weighting East Cluster Base Incr. Solar 1 Incr. Solar 2 Total 855 1,255 1,655 % Change vs Base 47%94% West Cluster Base Incr. Solar 1 Incr. Solar 2 Total 163 263 363 % Change vs Base 61%123% 114 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY of the blend was set such that the average correlation between the new clusters and the existing clusters matches the correlation measured between the existing clusters. Because the hourly regulation reserve requirements described above reflect the independent regulation reserve requirements for Red Hills and Pavant, they do not capture the diversity between different clusters of solar resources. As discussed above, diversity is partly a linear function of the independent hourly regulation reserve requirements – the greater the requirement, the greater the diversity credit. However, much of the variation in diversity values appears to be unpredictable, i.e. largely random. In a similar manner to the regulation reserve requirements described above, the diversity results for Red Hills and Pavant were taken as a single data set and assigned randomly to each of the clusters. A weighted average diversity value was then calculated that takes into account the number of clusters since diversity requires two or more. In addition, because diversity benefits are bounded by a zero regulation reserve requirement, they may be truncated in manner that under-represents the potential diversity available. Instances when diversity leads to higher requirements are not bounded in this manner in the sample. With more than two clusters, it may be possible to utilize additional diversity benefits before hitting the zero bound. To help reflect this, whenever the sampled diversity components indicated an increase in requirements, the increase was reduced by half. The random assignment of regulation reserve requirements described above disregards the hour of the day, and can overstate requirements when little output is expected such as during the morning ramp. To compensate, the aggregate regulation reserve requirements are reduced during the morning ramp to align with the requirements seen for Pavant and Red Hills. Solar Regulation Reserve Forecast The solar regulation reserve forecast is comparable to that developed for wind, representing a fixed percentage of the solar nameplate capacity, but never more than the maximum output in that hour, including a portion of the ramp up across the hour in the morning and down across the hour in the afternoon. The fixed percentage of nameplate capacity is set at the minimum level that achieves the reliability target of 0.88 loss of load hours per year. The reserve requirement necessary to achieve the reliability target varies in PACE and PACW, and with changes in total solar capacity. The results of the solar regulation requirements in the various scenarios is shown in Table F.10 below, with the wind results shown for comparison. Note that while the fixed percentage of nameplate capacity (i.e. the maximum reserve held) for solar and wind in PACE is similar, ranging from 14.9 percent to 18.6 percent of nameplate capacity, the average requirement for solar is significantly lower than that for wind. This is because solar output is zero for half of the hours in the year, whereas PACE wind output drops below the maximum reserve held infrequently. PACW wind output is more strongly correlated and drops to zero more frequently than PACE wind. 115 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Table F.10 - Solar and Wind Stand-alone Regulation Requirements, as Percentage of Nameplate Capacity For solar, the fixed percentage of nameplate in the reserve requirement calculation varies with the size of the solar capacity. There are two offsetting trends related to increasing solar capacity. First, more diverse solar resources (i.e. more clusters) have lower requirements, but the incremental benefit declines as more diversity is added. Second, spreading the fixed allowable BAAL variation across more capacity increases requirements, and the incremental impact increases as capacity increases. Figure F.20 shows these relationships as well as fitted curves used to project the solar regulation reserve requirements as a function of capacity for PACE and PACW. The solar regulation reserve requirement in PACE is assumed to be related to capacity using a third-order polynomial. The solar regulation reserve requirement in PACW is assumed to be related to capacity using two linear extrapolations. Figure F.20 - Stand-alone Solar Regulation Reserve Requirements, by capacity Scenario East West East West Max Reserve HeldAverage Reserve Held Ma x i m u m R e s e r v e H e l d : % o f S o l a r N a m e p l a t e Solar Capacity (MW) 116 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Portfolio Regulation Reserve Requirements Overview A single pool of regulation reserve is held to cover deviations by load, wind, solar, and non- dispatchable generation. Simultaneous large deviations by all classes are unlikely – as a result, this pool of regulation reserve can be smaller than what these classes would require on their own. The reduction in regulation reserve is a result of the diversity of the portfolio of requirements. While the diversity of load, wind, and Non-VER generation was measured using 2015 data, the solar deviations are from 2016 and are extrapolated from a very limited sample. As such, it is not currently possible to measure the diversity of the PacifiCorp system, inclusive of requirements for solar. Instead, several characteristics of the diversity of PacifiCorp’s system were used to produce an estimate of the relationship between the amount of diversity and the portfolio of regulation requirements. These characteristics are discussed below. Methodology The most important element in PacifiCorp’s portfolio diversity estimate is the system diversity, including EIM benefits, associated with load, wind, and Non-VERs during 2015. The diversity in the 2015 portfolio reduced reserve requirements by 37.51 percent. This captures the vast majority of the regulation reserve requirements both today and in likely future scenarios over the near term. For example, approximately 1000 MW of solar capacity is expected to be on the PacifiCorp system in 2017, and no solar was included in the 2015 results. However, this additional solar increases the stand-alone regulation reserve requirement (before accounting for diversity) by less than 10 percent. Since diversity only occurs in intervals when two or more regulation reserve requirements exist, changes in diversity in 10 percent of the intervals will have relatively limited effects. In a portfolio without solar capacity, incremental wind generation was calculated to have reserve requirements of 6.1 percent of nameplate, after accounting for portfolio diversity, compared to an average requirement of 9.2 percent for the entire wind fleet. Much of the benefits are captured within the wind class – its stand-alone requirements increase by a limited amount; however, the diversity of the entire portfolio increases slightly when the reserve requirements for the incremental wind are added. This relationship between stand-alone reserve requirements and portfolio diversity is assumed to be linear - a small increase in diversity as the reserve requirements of the existing classes grows. As a starting point, solar regulation reserve requirements are assumed to create equivalent amounts of diversity as the components of the pre-solar portfolio, including the linear increase as requirements grow. In addition, incremental diversity as a result of solar is assumed to occur in relation to the size of the stand-alone solar regulation requirements. When the solar requirements are equivalent in size to the requirements for load, wind, and Non-VERs, the incremental diversity benefits are assumed to be maximized at 20 percent of the solar requirement. At lower levels of solar requirements (i.e. for less solar capacity), the incremental diversity benefits are smaller and are assumed to proportional to the size of the solar requirements relative to the other regulation requirements. With four categories of requirements (load, wind, solar, Non-VER), solar requirements would need to be 25 percent of the total to achieve the maximum level of diversity. In the base scenario, solar requirements are 81 MW out of 998 MW total, and result in incremental 117 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY diversity benefits of 5.3 MW, on top of approximately 30 MW of benefits based on the diversity in the pre-solar portfolio.27 Based on the above, hourly regulation requirements for PACE and PACW are calculated as a function of: wind and solar nameplate capacity, forecasted wind output and month/hour as a proxy for expected solar output, and static hourly regulation reserve requirements for load and non-VER generation. Diversity is a function of the total requirements and is calculated dynamically as described above. Results Table F.11 presents the portfolio regulation requirement results from the various scenarios described above. As the wind and solar capacity on PacifiCorp’s system increases, regulation requirements increase, but those requirements are partially offset by the increasing diversity of the portfolio. The 2017 Base Case regulation reserve requirements are 617 MW. By comparison, PacifiCorp’s 2014 Wind Integration Study identified requirements of 626 MW for a smaller amount of wind, and without any requirements for solar or Non-VERs. Table F.11 - Portfolio Regulation Requirement Results, by Scenario There are a significant number of changes between the PacifiCorp’s 2014 Wind Integration Study and the current study. First, the specific requirements of the BAL-001-2 standard are being applied, as previously discussed. Second, the updated requirements are based on an expanded portfolio of resources, including solar, Non-VERs, and additional wind capacity. Finally, diversity benefits are now shared among all requirements, rather than being allocated solely to wind resources as was done in the 2014 Study. Table F.12 presents a comparison of the regulation reserve requirement results in the current study and prior studies. 27 81 MW solar requirement / (998 MW total requirement / 4 classes) * 20% incremental diversity = 5.3 MW. 81 MW solar requirement * 37.6% pre-solar portfolio diversity = ~30 MW Scenario Wind capacity (MW) Solar capacity (MW) Stand-alone regulation requirement (MW) Portfolio diversity credit (%) Regulation requirement with diversity (MW) 118 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Table F.12 - Portfolio Regulation Requirement Results, Percent of Nameplate Capacity The 2012 and 2014 Wind Integration Studies calculated the regulation reserve requirement for load only, then the incremental requirement for the entire wind fleet, allocating all diversity to wind. The FRS calculates the regulation reserve requirement for the 2017 resource mix, allocating the diversity among all components. As compared to prior studies, the diversity allocation decreases the load requirement and increases the wind requirement, the changes in standards and methodology notwithstanding. In an additional step, the FRS also calculates incremental requirements for wind and solar which are more closely aligned with the obligations resulting from new resource additions contemplated in the IRP. While these requirements are lower than the average requirements in the base case, they will call on higher cost resources, as the least-cost regulation reserve resources are dispatched first. The cost of the regulation reserve obligation is discussed in more detail in the next section. Regulation Reserve Cost A series of PaR scenarios were prepared to isolate the regulation reserve cost associated with wind and solar generation. The scenarios are shown in Table F.13. These scenarios were based on 2017 and included the existing resources in the 2015 IRP Update. In the 2014 Wind Integration Study reserve requirements were modeled on both an hourly and monthly basis to reflect the timing differences of reserve requirements. While the requirements are calculated on an hourly basis, due to difficulties incorporating those requirements in the PaR model at that granularity, monthly requirements were used to calculate regulation reserve costs discussed herein. Where possible, it is recommended that hourly regulation requirements be modeled that are consistent with the resource capacity and generation profiles of the specific portfolio under evaluation. Table F.13 - Regulation Reserve PaR Scenarios Study Load Wind Non-VER Solar Method #Scenario Resources Regulation requirement 119 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY The regulation reserve cost results are shown in Table F.14. The 2014 Wind Integration Study identified regulation reserve costs for wind generation of $2.35/MWh. This value measured the incremental cost when regulation reserve for the existing wind fleet were added to the regulation reserve for load. The most comparable wind reserve cost from the FRS is $0.30/MWh. This represents the cost of the regulation reserve for existing wind, load, solar, and Non-VERs, relative to a scenario with no regulation reserve. The result is adjusted to account for the wind regulation reserve requirement relative to the total regulation reserve requirement. Table F.14 - Regulation Reserve Cost Calculations The change in regulation reserve costs is primarily attributable to the following factors: lower market prices, transmission congestion, and 30-minute regulation reserve capability. Assuming sufficient regulating capability is available within PacifiCorp’s portfolio, the cost of regulation reserve reflects the lost margin on resources that can provide the service, i.e. the difference between the market price or alternative generation cost and their fuel cost. Since the prior study, market prices have declined, which reduces this margin, and a 10 percent drop in market price can reduce the margin by more than 10 percent. In addition, transmission congestion has increased, primarily as a result of substantial additions of solar, which has reduced the ability of resources to get to market. If regulation-capable resources are already backed down due to transmission congestion there is no additional cost to count that capacity as regulation reserve. Finally, in the prior study the entire regulation reserve requirement was included in the spinning reserve category, which is limited to capacity available within 10 minutes. The FRS assumes that dispatchable capacity available within 30-minutes can be counted toward the regulation reserve requirement. This increases the supply of regulation resources and reduces costs when 30-minute capacity from the unit with the lowest-cost reserve can be used instead of being limited to only the 10-minute capacity of that unit. While the Base wind reserve rate is helpful for comparison with the 2014 Wind Integration Study, it is not representative of the incremental cost of regulation reserve for new wind resources. Instead, PacifiCorp’s FRS calculates regulation reserve requirements specific to the incremental resource additions contemplated in the IRP. As shown in Table F.14 above, the addition of 250 MW of wind capacity results in incremental regulation reserve costs of $0.43/MWh, while the addition of 1000 MW of solar capacity results in incremental regulation reserve costs of $0.46/MWh. It should be noted that the difference in reserve costs for wind and solar reflects timing differences. Per MWh of generation, the wind reserve obligation is 16 percent higher than #Value Calculation Units Results Base wind reserve rate [a] x [b] / [c]$/MWh $0.30 a'Incremental regulation reserve cost [Study W.2] - [Study W.1]$$389,890 b'Incremental wind generation [Study W.1] - [Study B.1]MWh 909,050 Incremental wind reserve rate [a'] / [b']$/MWh $0.43 a"Incremental regulation reserve cost [Study S2.2] - [Study S2.1]$$1,221,610 b"Incremental solar generation [Study S2.1] - [Study B.1]MWh 2,667,200 Incremental solar reserve rate [a"] / [b"]$/MWh $0.46 120 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY the solar obligation; however, the solar obligation is higher during the summer and during the day, when market prices and marginal reserve costs are higher. While incremental reserve costs generally increase with volume, the 500 MW solar scenario had a slightly higher cost than the 1000 MW scenario, likely due to lower transmission congestion. For simplicity, the 1000 MW result was used where a specific dollar value was required in the IRP. The 2017 FRS results are applied in the 2017 IRP portfolio development process as a cost for wind and solar generation resources. Once candidate resource portfolios are developed using the SO model, the PaR model is used to evaluate portfolio risks. The PaR model inputs include regulation reserve requirements specific to the resource portfolio developed using the SO model. As a result, the IRP risk analysis using PaR includes the impact of differences in regulation reserve requirements between portfolios. Ideally, the hourly regulation reserve requirements should be used to determine costs specific to the requirements of the resource and portfolio under consideration. This ensures regulation reserve costs reflect changes in market prices and fuel costs, transmission congestion, and regulation reserve capability relative to the IRP analysis. The corollary of a more accurate estimate of incremental regulation reserve cost is a more accurate estimate of the value of resources that supply regulation reserve, including energy storage and direct load control. Day-ahead System Balancing Costs In addition to using PaR for evaluating operating reserve cost, the PaR model is also used to estimate the costs associated with daily system balancing activities. These system balancing costs result from the unpredictable nature of load and 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 as they occur in real time. The methodology is comparable to that used in the 2014 Wind Integration Study, with modifications to account for solar and the allocation of costs between load, wind, and solar. The PaR model simulates production costs of a system by committing and dispatching resources to meet system load. For this study, PacifiCorp developed nine different PaR simulations as summarized in Table F.15. These simulations isolate the system balancing costs of load, wind, and solar, plus the system balancing costs of the overall portfolio. These simulations were run assuming operation in the 2017 calendar year, applying 2015 load, wind, and solar data collected from PacifiCorp’s wind forecast service provider, DNV GL. This calculation method combines the benefits of using actual system data with current forward price curves pertinent to calculating the costs for wind integration service on a forward basis, as well as the current resource portfolio.28 PacifiCorp resources used in the simulations are based upon its existing resource portfolio. 28 The Study uses the October 12, 2016 official forward price curve (OFPC). 121 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Table F.15 - System Balancing Cost Simulations in PaR Simulation 1 identifies the unit commitment using day-ahead forecasts of load, wind, and solar. Simulation 2 identifies the unit commitment using actual load, wind, and solar, and represents the optimal dispatch of the system. Simulation 3 uses the unit commitment from Simulation 1, along with the actual load, wind, and solar from Simulation 2. Since Simulation 2 and 3 both have identical load, wind, and solar, differences between them are solely due to unit commitment and Simulation 3 represents the achievable optimization of unit commitment using the information available on a day-ahead basis when unit commitment occurs. The difference in cost between Simulation 3 and Simulation 2 is the system balancing cost associated with changes between day- ahead load, wind, and solar forecasts and actual output. Simulations 4-9 isolate the total day-ahead forecast cost of the individual components. Simulations 4-6 each calculate unit commitment using one day-ahead forecast and two actual results. Simulations 7-9 calculate the costs of those day-ahead unit commitment decisions under actual output. The relative costs of Simulations 7-9 are used to determine the relative allocation of the portfolio among the individual components. The simulation results and day-ahead balancing cost for each category is shown in Table F.16. Table F.16 - Day-ahead Forecast System Balancing Cost Results As indicated in the Regulation Reserve section above, the actual solar on PacifiCorp’s system in 2015 was very limited, and the available solar generation averages just 21 megawatts, or roughly 3 percent of the available wind generation. Because unit commitment changes have low granularity (a unit is either on or off), small differences can sometimes have a large effect, and this appears to be the case for the solar results, which were far out of proportion with the measured volumes. In light of the limited solar data set, it is unlikely those results would scale up to the current level of solar on PacifiCorp’s system. In light of this, the day-ahead forecast cost for solar #Load Wind profile Solar profile Commitment Day-ahead forecast error Study 1 For Load/Wind/Solar 4 Day-ahead Actual Actual Study 4 n/a 5 Actual Day-ahead Actual Study 5 n/a 6 Actual Actual Day-ahead Study 6 n/a 7 Actual Actual Actual Study 4 For Load 8 Actual Actual Actual Study 5 For Wind 9 Actual Actual Actual Study 6 For Solar #Value Cost calculation Cost ($)Diversity calculation Rate w/ diversity ($/MWh) $0.09 c Wind Only [Study 8] - [Study 2]$1,053,530 [c] * ([a] / [e]) / [Actual Wind MWh]$0.14 d Solar Only [Adjusted]$31,111 [Set equal to wind result]$0.14 e Total One-off [b] + [c] + [d]$7,217,501 122 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY generation has been reduced to the level calculated for wind generation.29 Table F.16 above has been modified from what was presented in the 2014 Wind Integration Study. In that study, day-ahead system balancing costs associated with load were calculated first, and incremental day-ahead system balancing costs associated with wind were calculated second. In this analysis, the total day-ahead system balancing costs are calculated for the portfolio and are allocated among the components based on their individual contributions. This attributes diversity in the requirements to all of the components and avoids differences related to the order the studies are conducted. A comparison of the day-ahead system balancing costs in the FRS and 2014 Wind Integration Study is shown in Table F.17. Table F.17 - Day-Ahead System Balancing Cost Comparison The increase in the day-ahead system balancing costs associated with load do not appear to be a result of the portfolio allocation methodology, as load was previously calculated on a stand-alone basis, and the portfolio adjustment reduces the stand-alone day-ahead system balancing costs by 14 percent. Instead the difference appears to be related to market prices and the composition of the PacifiCorp’s system. Market prices influence the relative costs of PacifiCorp’s gas resources and determine how close they are to being economic or uneconomic. Resources generally only are faced with commitment changes when they have low margins. Because falling market prices have reduced margins, this occurs more frequently. In addition, transmission congestion has reduced the ability of resources to get to market. When resources are committed in anticipation of high load or low resources, there may not be sufficient transmission to get them to market if load is lower than expected or resources are higher. The costs of backing down economic resources due to transmission constraints is higher than the cost of forgone market sales, and thus contributes to higher day-ahead system balancing costs. Technical Review Committee As was done for its prior Wind Integration Studies, PacifiCorp engaged a Technical Review Committee (TRC) to review the study results from the FRS. PacifiCorp thanks each of the TRC members, identified below, for their participation and professional feedback. The members of the TRC are: • Andrea Coon - Director, Western Renewable Energy Generation Information System (WREGIS) for the Western Electricity Coordinating Council (WECC) • Michael Milligan - Principal Analyst at the National Renewable Energy Laboratory (NREL) • J. Charles Smith - Executive Director, Utility Variable-Generation Integration Group (UVIG) 29 The calculated Solar Only Day-Ahead Forecast Cost, [Study 9] – [Study 2], was $805k, or over $4/MWh. 2014 WIS 2017 FRS (2014$/MWh)(2016$/MWh) 123 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY • Robert Zavadil - Executive Vice President, EnerNex LLC In its technical review30 of PacifiCorp’s FRS, the TRC provided comments and questions on specific aspects of the analysis. Table F.18 - FRS TRC Recommendations 2016 FRS TRC Recommendations Response to TRC Recommendations The TRC feels that it might be useful to state the role of key assumptions generally - but specifically how key requirements of the EIM may have an impact on regulation reserve requirements and the calculations in the FRS. Specific details on the EIM market process On Slide page 8 of the presentation provided to the TRC, below the table: should that be 70 MW instead of 40 MW? The presentation stated: 40 MW is the maximum five-minute imbalance in any thirty-minute period in this hour. This is more accurately stated as: When the minimum imbalances in every rolling thirty-minute period are compared, 40 MW is the maximum five-minute imbalance in any thirty- Would be helpful to include a few sentences about the ACE cap of 4L10? “Balancing Authority ACE Limit: Allowed The use of what has traditionally been a resource adequacy metric – LOLH – use in long term capacity planning as a key criterion for estimating regulation reserve requirements is both interesting and a departure from previous studies – by Pacificorp as well as the general wind integration community in the U.S. This approach has been employed in a few recent integration analyses, but given the uniqueness, it would be good if it were more clearly called out/highlighted in the description of the analytical methodology. The discussion of 0.88 LOLH was helpful on the call. It would be useful to have a similar explanation in the report - something along the lines that the RA target resulted in 0.88 LOLH/year and that was judged to be an acceptable reliability level. Using the same target for operations, there are different drivers, but assuming resource adequacy is not the constraint, the 0.88 LOLH may instead result from UC errors that result in too little regulation being available when needed. “Planning Reliability Target: Loss of Load Probability.” The FRS identifies the “up” regulation reserve needed to maintain compliance with BAL-001-2. The 0.88 LOLH in the FRS assumes that resources are available to provide the identified hourly regulation requirements. To the extent resources are not available to meet the identified requirements, LOLH would increase. PacifiCorp’s Flexible Resource Needs Assessment in the FRS assesses the availability of resources to meet its reserve requirements over the long term. In addition, over the short term, maintaining adequate reserve can be dependent on the availability of hourly market balancing opportunities. While a single unit can provide reserve in each hour of for a multi-hour ramp, it can only do so to the extent alternate resources can be procured so that it can ramp back to its starting point. Potential market balancing constraints are an 30 PacifiCorp 2016 Wind Integration Study Technical Review, Dec. 12, 2016. Available at: http://www.pacificorp.com/es/irp/irpsupport.html 124 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY 2016 FRS TRC Recommendations Response to TRC Recommendations Would be useful to have discussion of how wind (and solar) are treated in the study - do they respond to AGC or dispatch or both? Impact of lost RECs vs. operational flexibility etc. to maintain compliance with BAL-001-2. The ability of wind or solar to provide “up” regulation reserve would impact the cost of meeting that need. Generally, the opportunity cost of foregone renewable resource output is higher than the variable cost of PacifiCorp’s regulation reserve resources. When considered relative to the cost of adding flexible resource capacity, in some circumstances providing regulation reserve with to allocate the diversity benefits for each EIM This is addressed in the FRS in the section entitled “EIM Intra-hour Benefit.” There is some remaining confusion on the part of the TRC regarding the assumptions and utilization of forecasting into the production simulations for calculating integration cost. Specifically, the forecast lead time is nearly one hour prior to the operating hour. The disconnect on the part of the TRC is likely driven by current operation in some larger RTOs, where very short term persistence forecasts (5 minutes ahead) are used to dispatch generators participating in the sub- hourly energy markets, which substantially reduces the remaining requirement for generators providing regulation. the start of an interval, it can only dispatch the resources made available by participants. Because of EIM operating timelines, balanced load and resource schedules with regulation reserve capacity identified have to be submitted by 55 minutes prior to the hour. Once a resource is deployed, for instance to cover increasing load or decreasing wind, PacifiCorp cannot restore that regulating capacity to its original levels without buying additional resources from a third party. Bilateral hourly markets in the West have historically been liquid enough for this purpose, whereas sub- hourly markets, other than EIM, have not. Because EIM is an Energy Imbalance Market, each participant is independently responsible for meeting its reliability obligations and it is inappropriate to rely upon the availability of resources from other participants, though they will be deployed in the EIM if it is economic to do so. As discussed in the section entitled “EIM Intra-hour Benefit”, the FRS incorporates benefits associated with the diversity of the EIM as data, especially for wind generation (rather than synthesized data from numerical weather simulations) has been a key feature of the Pacificorp integration studies dating back to 2012. Going forward, the TRC feels that future Pacificorp integration studies could benefit greatly by a thorough comparison of “study results vs. real world”, especially since a current year baseline is part of the analysis. This would provide perhaps the strongest validation of the analytical methodology or otherwise give strong clues to PacifiCorp agrees that the performance of the regulation reserve forecast developed in the FRS against future regulation reserve requirements would provide valuable feedback. This is an area for future work. Flexible Resource Needs Assessment Overview In its Order No. 12013 issued on January 19, 2012 in Docket No. UM 1461 on “Investigation of matters related to Electric Vehicle Charging”, the Oregon Public Utility Commission (OPUC) adopted the OPUC staff’s proposed IRP guideline: 125 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY 1. Forecast the Demand for Flexible Capacity: The electric utilities shall forecast the balancing reserves needed at different time intervals (e.g. ramping needed within 5 minutes) to respond to variation in load and intermittent renewable generation over the 20- year planning period; 2. Forecast the Supply of Flexible Capacity: The electric utilities shall forecast the balancing reserves available at different time intervals (e.g. ramping available within 5 minutes) from existing generating resources over the 20-year planning period; and 3. Evaluate Flexible Resources on a Consistent and Comparable Basis: In planning to fill any gap between the demand and supply of flexible capacity, the electric utilities shall evaluate all resource options including the use of electric vehicles (EVs), on a consistent and comparable basis. In this section, PacifiCorp first identifies its flexible resource needs for the IRP study period of 2017 through 2036, and the calculation method used to estimate those requirements. PacifiCorp then identifies its supply of flexible capacity from its generation resources, in accordance with the Western Electricity Coordinating Council (WECC) operating reserve guidelines, demonstrating that PacifiCorp has sufficient flexible resources to meet its requirements. Forecasted Reserve Requirements Since contingency reserve and regulation reserve are separate and distinct components, PacifiCorp estimates the forward requirements for each separately. The contingency reserve requirements are derived from stochastic simulations run using the Planning and Risk (PaR) model. The regulating reserve requirements are part of the inputs to the PaR model, and are calculated by applying the methods developed in the Portfolio Regulation Reserve Requirements section. The contingency and regulation reserve requirements include three distinct components and are modeled separately in the 2017 IRP: 10-minute spinning reserve requirements, 10-minute non-spinning reserve requirements, and 30-minute regulation reserve requirements. The reserve requirements for PacifiCorp’s two balancing authority areas are shown in Table F.19 below. 126 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Table F.19 - Reserve Requirements (MW) East Requirement West Requirement Year Spin (10-minute) Non-spin (10-minute) Regulation (30-minute) Spin (10-minute) Non-spin (10-minute) Regulation (30-minute) 127 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Flexible Resource Supply Forecast Requirements by NERC and the WECC dictate the types of resources that can be used to serve the reserve requirements. • 10-minute spinning reserve can only be provided by resources currently online and synchronized to the transmission grid; • 10-minute non-spinning reserve may be served by fast-start resources that are capable of being online and synchronized to the transmission grid within ten minutes. Interruptible load can only provide non-spinning reserve. Non-spinning reserve may be provided by resources that are capable of providing spinning reserve. • 30-minute regulation reserve can be provided by unused spinning or non-spinning reserve. Incremental 30-minute ramping capability beyond the 10-minute capability captured in the categories above also counts toward this requirement. The resources that PacifiCorp employs to serve its reserve requirements include owned hydro resources that have storage, owned thermal resources, and purchased power contracts that provide reserve capability. Hydro resources are generally deployed first to meet the spinning reserve requirements because of their flexibility and their ability to respond quickly. The amount of reserve that these resources can provide depends upon the difference between their expected capacities and their generation level at the time. The hydro resources that PacifiCorp may use to cover reserve requirements in the PacifiCorp West balancing authority area include its facilities on the Lewis River and the Klamath River as well as contracted generation from the Mid-Columbia projects. In the PacifiCorp East balancing authority area, PacifiCorp may use facilities on the Bear River to provide spinning reserve. Thermal resources are also used to meet the spinning reserve requirements when they are online. The amount of reserve provided by these resources is determined by their ability to ramp up within a 10-minute interval. For natural gas-fired thermal resources, the amount of reserve can be close to the differences between their nameplate capacities and their minimum generation levels. In the current IRP, PacifiCorp’s reserve are served not only from existing coal- and gas-fired resources, but also from new gas-fired resources selected in the preferred portfolio. Table F.20 lists the annual reserve capability from resources in PacifiCorp’s East and West balancing authority areas. All the resources included in the calculation are capable of providing all types of reserve. The non-spinning reserve resources under third party contracts are excluded in the calculations. The changes in the flexible resource supply reflect retirement of existing resources, addition of new preferred portfolio resources, and variation in hydro capability due to forecasted streamflow conditions, and expiration of contracts from the Mid-Columbia projects that are reflected in the preferred portfolio. 128 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Table F.20 - Flexible Resource Supply Forecast (MW) Figure F.21 and Figure F.22 graphically display the balances of reserve requirements and capability of spinning reserve resources in PacifiCorp’s East and West balancing authority areas respectively. The graphs demonstrate that PacifiCorp’s system has sufficient resources to serve its reserve requirements throughout the IRP planning period. Year East Supply (10-minute) West Supply (10-minute) East Supply (30-minute) West Supply (30-minute) 129 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.21 - Comparison of Reserve Requirements and Resources, East Balancing Authority Area (MW) MW 130 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Figure F.22 - Comparison of Reserve Requirements and Resources, West Balancing Authority Area (MW) Flexible Resource Supply Planning In actual operations, PacifiCorp has been able to serve its reserve requirements and has not experienced any incidents where it was short of reserve. PacifiCorp manages its resources to meet its reserve obligation in the same manner as meeting its load obligation – through long term planning, market transactions, utilization of the transmission capability between the two balancing authority areas, and operational activities that are performed on an economic basis. PacifiCorp and the California Independent System Operator Corporation implemented the energy imbalance market (EIM) on November 1, 2014, and participation has since expanded to include NV Energy, Arizona Public Service, and Puget Sound Energy, with several additional participants scheduled for entry between 2017 and 2019. By pooling variability in load and resource output, EIM entities reduce the quantity of reserve required to meet flexibility needs. Because variability across different BAAs may happen in opposite directions, the flexible ramping requirement for the entire EIM footprint can be less than the sum of individual BAAs’ requirements. This difference is known as the “flexible ramping procurement diversity savings” in the EIM. This intra-hour benefit reflects offsetting variability and lower combined uncertainty. PacifiCorp’s regulation reserve forecast includes a credit to account for the diversity benefits associated with its participation in EIM. MW 131 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY As indicated in the OPUC order, electric vehicle technologies may be able to meet flexible resource needs at some point in the future. However, the electric vehicle technology and market have not developed sufficiently to provide data for the current study. Since this analysis shows no gap between forecasted demand and supply of flexible resources over the IRP planning horizon, this IRP does not include whether electric vehicles could be used to meet future flexible resource needs. Summary The FRS first estimates the regulation reserve necessary to maintain compliance with NERC Standard BAL-001-2 given a specified portfolio of wind and solar resources. The FRS next calculates the cost of holding regulation reserve for incremental wind and solar resources and the cost of using day-ahead load, wind, and solar forecasts to commit gas units. Finally, the FRS compares PacifiCorp’s overall operating reserve requirements over the IRP study period, including both regulation reserve and contingency reserve, to its flexible resource supply. PacifiCorp incorporated a revised methodology in the FRS compared to its 2014 Wind Integration Study. The FRS now estimates regulation reserve based on the specific requirements of NERC Standard BAL-001-2. It also incorporates the current timeline for EIM market processes, as well as EIM resource deviations and flexibility reserve benefits based on actual results. The FRS also includes adjustments to regulation reserve requirements to account for the changing portfolio of solar and wind resources on PacifiCorp’s system and accounts for the diversity of using a single portfolio of regulation reserve resources to cover variations in load, wind, solar, and Non-VERs. The regulation reserve requirements for the various portfolios considered in the analysis and in the 2014 Wind Integration Study are shown in Table F.21. Table F.21 – Portfolio Regulation Reserve Requirements, by Scenario Case Wind Capacity Solar Capacity Stand-alone Regulation Requirement Portfolio Diversity Credit Regulation Requirement with Diversity 2,543 n/a n/a n/a 626 2,588 0 900 37.5% 562 2,757 1,050 998 38.2% 617 3,007 1,050 1,023 38.3% 631 2,757 1,550 1,033 38.6% 635 2,757 2,050 1,074 39.2% 653 Two categories of flexible resource costs are estimated using the Planning and Risk (PaR) model: one for meeting intra-hour regulation reserve requirements, and one for inter-hour system balancing costs associated with committing gas plants using day-ahead forecasts of load, wind, and solar. Table F.22 provides the wind and solar costs on a dollar per megawatt-hour ($/MWh) of generation basis. The results of the 2014 Wind Integration Study are also included for comparison. 132 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Table F.22 – 2017 FRS Flexible Resource Costs as Compared to 2014 WIS Costs, $/MWh 2014 WIS (2015$)2017 FRS (2017$)2017 FRS (2017$) Intra-hour Reserve $2.35 $0.43 $0.46 Inter-hour/System Balancing $0.71 $0.14 $0.14 The 2017 FRS results are applied in the 2017 IRP portfolio development process as a cost for wind and solar generation resources. Once candidate resource portfolios are developed using the SO model, the PaR model is used to evaluate portfolio risks. The PaR model inputs include regulation reserve requirements specific to the resource portfolio developed using the SO model. As a result, the IRP risk analysis using PaR includes the impact of differences in regulation reserve requirements between portfolios. 133 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Reference Tables Table F.23 - Wind Capacity (MW) DUNLAP_6_UNIT 111 PACE Wind FOOTECRE_7_UNITS 133.6 PACE Wind FREEZOUT_6_UNIT 118.5 PACE Wind GLENROCW_6_UNIT 138 PACE Wind HINSHAW_7_UNITS 144 PACE Wind HIPLAINS_7_UNITS 127.5 PACE Wind HORSEBU_7_UNIT 57.6 PACE Wind JOLLYHIL_1_GOSHEN 124.5 PACE Wind LATIGO_6_UNIT 99 PACE Wind MEADOWCR_6_UNIT 119.7 PACE Wind MOONSHIN_7_UNITS 45 PACE Wind MTWNDCOL_7_UNITS 140.7 PACE Wind RAWHIDE_6_UNIT 16.5 PACE Wind ROLLHILL_6_UNIT 99 PACE Wind SPNFKWND_7_UNIT 18.9 PACE Wind TOPWORLD_7_UNITS 200.2 PACE Wind WOLVERIN_7_UNITS 64.5 PACE Wind CAMPCOL_6_UNIT 98.9 PACW Wind COMBINEH_6_UNIT 41 PACW Wind DALREED_7_WIND 9.9 PACW Wind GOODNOEH_7_UNIT 94 PACW Wind HINKLE_6_UNIT 64.55 PACW Wind LEANJNPR_7_UNIT 100.5 PACW Wind MARENGO_6_UNITS 210.6 PACW Wind NINEMIL_7_UNIT 1 210 PACW Wind Table F.24 – Non-VERs Capacity (MW) BONANZA_7_UNIT 458 PACE Non-VER DALTONU_7_UNIT 4.6 PACE Non-VER EXXON_7_UNITS 107.4 PACE Non-VER GEMSTATE_1_UNIT 23.4 PACE Non-VER MILLCRK_7_UNIT 1 40 PACE Non-VER 134 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY 135 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Total 2227.65 Table F.25 - Solar Capacity (MW) Beryl Solar 3 PACE Solar Buckhorn 3 PACE Solar Cedar Valley 3 PACE Solar Enterprise Solar I QF 80 PACE Solar Escalante Solar I QF 80 PACE Solar Escalante Solar II QF 80 PACE Solar Escalante Solar III QF 80 PACE Solar Fiddler's Canyon 1 3 PACE Solar Fiddler's Canyon 2 3 PACE Solar Fiddler's Canyon 3 3 PACE Solar Granite Mountain East Solar QF 80 PACE Solar Granite Mountain West Solar QF 50.4 PACE Solar Granite Peak 3 PACE Solar Greenville 2.2 PACE Solar Iron Springs Solar QF 80 PACE Solar Laho #1 3 PACE Solar Milford 2 2.97 PACE Solar Milford Flat 3 PACE Solar 136 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY Total 1017.7 137 PACIFICORP – 2017 IRP APPENDIX F – FLEXIBLE RESERVE STUDY 138 PACIFICORP – 2017 IRP APPENDIX G – PLANT WATER CONSUMPTION 139 APPENDIX G – 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 PACIFICORP – 2017 IRP APPENDIX G – PLANT WATER CONSUMPTION 140 Table G.1 – Plant Water Consumption with Acre-Feet Per Year * Beginning in 2014, net water consumed reflects "Raw Water Consumed" instead of "Raw Water Diversion." ** Gadsby includes a mix of both Rankine steam units and peaking gas turbines. *** Lake Side 2 went commercial in May 30, 2014. The averages for Lake Side 2 are based only on 2014 and 2015 numbers. **** Naughton Unit 3 was rerated in September 2015 from 330 MW to 280 MW. The averages remain as 4-year averages. 1 acre-foot of water is equivalent to 325,851 Gallons or 43,560 Cubic Feet 4-year Average Plant Name Zero Discharge Cooling Media 2012 2013 2014 *2015 * 4-year Average 2012 2013 2014 2015 Gals/ MWH GPM/ MW Chehalis Air 55 86 150 93 96 849,938 1,674,194 2,543,785 1,095,433 20 0.3 Currant Creek Yes Air 90 84 92 78 86 2,132,523 2,359,924 2,498,058 2,257,106 12 0.2 Dave Johnston Water 7,721 8,941 9,474 9,736 8,968 4,906,422 5,295,081 5,183,347 5,140,970 569 9.5 Gadsby Water 1,059 610 367 1,022 764 214,739 339,592 325,677 123,795 993 16.5 Hunter Yes Water 18,266 17,001 16,662 16,386 17,079 9,118,876 9,546,313 9,098,918 9,630,419 595 9.9 Huntington Yes Water 10,423 10,643 10,240 9,888 10,299 6,744,160 6,768,625 6,300,558 5,988,318 520 8.7 Jim Bridger Yes Water 23,977 25,059 23,936 22,493 23,866 13,625,135 14,817,041 14,016,315 13,439,341 557 9.3 Lake Side ***Water 1,693 1,361 2,960 4,533 3,746 2,890,938 2,508,960 4,351,182 4,550,871 274 4.6 Naughton ****Yes Water 8,745 9,622 7,484 9,160 8,753 5,056,959 5,533,895 4,958,589 4,899,321 558 9.3 Wyodak Yes Air 322 319 332 228 300 2,526,307 2,518,120 2,625,183 2,563,421 38 0.6 72,351 73,726 71,695 73,616 72,591 48,065,997 51,361,745 51,901,612 49,688,995 472 7.9 Acre-Feet Per Year MWhs Per Year TOTAL PACIFICORP – 2017 IRP APPENDIX G – PLANT WATER CONSUMPTION 141 Table G.2 – Plant Water Consumption by State (acre-feet) Percent of total water consumption = 41.9% Percent of total water consumption = 58.1% Table G.3 – Plant Water Consumption by Fuel Type (acre-feet) Percent of total water consumption = 95.7% Percent of total water consumption = 4.4% UTAH PLANTS Plant Name 2010 2011 2012 2013 2014 2015 Currant Creek 82 78 90 84 92 78 Gadsby 893 864 1,059 610 367 1,022 Hunter 18,941 16,961 18,266 17,001 16,662 16,386 Huntington 9,549 9,069 10,423 10,643 10,240 9,888 Lake Side 1,533 1,154 1,693 1,361 2,960 4,533 TOTAL 30,998 28,125 31,531 29,699 30,320 31,906 WYOMING PLANTS Plant Name 2010 2011 2012 2013 2014 2015 Dave Johnston 6,604 7,233 7,721 8,941 9,474 9,736 Jim Bridger 20,757 22,282 23,977 25,059 23,936 22,493 Naughton 13,354 14,157 8,745 9,622 7,484 9,160 Wyodak 396 367 322 319 332 228 TOTAL 41111 44039 40765 43941 41225 41617 COAL FIRED PLANTS Plant Name 2010 2011 2012 2013 2014 2015 Dave Johnston 6,604 7,233 7,721 8,941 9,474 9,736 Hunter 18,941 16,961 18,266 17,001 16,662 16,386 Huntington 9,549 9,069 10,423 10,643 10,240 9,888 Jim Bridger 20,757 22,282 23,977 25,059 23,936 22,493 Naughton 13,354 14,157 8,745 9,622 7,484 9,160 Wyodak 396 367 322 319 332 228 TOTAL 69,601 70,069 69,454 71,585 68,127 67,891 Plant Name 2010 2011 2012 2013 2014 2015 Currant Creek 82 78 90 84 92 78 Chehalis 24 43 55 86 150 93 Gadsby 893 864 1,059 610 367 1,022 Lake side 1,533 1,154 1,693 1,361 2,960 4,533 Total 2,532 2,139 2,897 2,141 3,569 5,726 NATURAL GAS FIRED PLANTS PACIFICORP – 2017 IRP APPENDIX G – PLANT WATER CONSUMPTION 142 Table G.4 – Plant Water Consumption for Plants Located in the Upper Colorado River Basin (acre-feet) Percent of total water consumption = 83.9% Plant Name 2010 2011 2012 2013 2014 2015 Hunter 18,941 16,961 18,266 17,001 16,662 16,386 Huntington 9,549 9,069 10,423 10,643 10,240 9,888 Naughton 13,354 14,157 8,745 9,622 7,484 9,160 Jim Bridger 20,757 22,282 23,977 25,059 23,936 22,493 TOTAL 62,601 62,469 61,411 62,325 58,322 57,927 PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 143 APPENDIX H – STOCHASTIC PARAMETERS For this IRP, PacifiCorp updated and re-estimated the stochastic parameters provided in the 2015 IRP for use in the Planning and Risk (PaR) model runs. PaR, as used by PacifiCorp, develops portfolio cost scenarios via computational finance in concert with production simulation. The model stochastically shocks the case-specific underlying electricity price forecast as well as the corresponding case-specific key drivers (e.g., natural gas, loads, and hydro) and dispatches accordingly. Using exogenously calculated parameters (i.e., volatilities, mean reversions, and correlations), PaR develops scenarios that bracket the uncertainty surrounding a driver; statistical sampling techniques are then employed to limit the number of representative scenarios to 50. The stochastic model used in PaR is a two-factor (short- and long-run) short run mean reverting model. PacifiCorp used short-run stochastic parameters for this IRP; long-run parameters were set to zero since PaR cannot re-optimize its capacity expansion plan. This inability to re-optimize or add capacity can create a problem when dispatching to meet extreme load and/or fuel price excursions, as often seen in long-term stochastic modeling. Such extreme out-year price and load excursions can influence portfolio costs disproportionately while not reflecting plausible outcome. Thus, since long-term volatility is the year-on-year growth rate, only the expected yearly price and/or load growth is simulated over the forecast horizon1. Key drivers that significantly affect the determination of prices tend to fall into two categories: loads and fuels. Targeting only key variables from each category simplifies the analysis while effectively capturing sensitivities on a larger number of individual variables. For instance, load uncertainty can encompass the sensitivities of weather, transmission availability, unit outages, and evolving end-uses. Depending on the region, fuel price uncertainty (especially that of natural gas) can encompass the sensitivities of weather, load growth, emissions, and hydro availability. The following sections summarize the development of stochastic process parameters and describe how these uncertain variables evolve over time. 1Mean reversion is assumed to be zero in the long run. PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 144 Introduction Long-term planning demands specification of how important variables behave over time. For the case of PacifiCorp's long-term planning, important variables include natural gas and electricity prices, regional loads, and regional hydro generation. Modeling these variables involves not only a description of their expected value over time as with a traditional forecast, but also a description of the spread of possible future values. The following sections summarize the development of stochastic process parameters to describe how these uncertain variables evolve over time2. Volatility The standard measure of uncertainty for a stochastic variable is volatility: 𝑉𝑜𝑙𝑎𝑡𝑖𝑙𝑖𝑡𝑦=𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝐷𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 √𝑇𝑖𝑚𝑒 The standard deviation3 is a measure of how widely values are dispersed from the average value: 𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝐷𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛= √∑(𝑥𝑖−𝑎𝑣𝑒𝑟𝑎𝑔𝑒)2𝑛𝑖=1 (𝑛−1) Volatility incorporates a time component so a variable with constant volatility has a larger spread of possible outcomes two years in the future than one year in the future. Volatilities are typically quoted on an annual basis but can be specified for any desired time period. Suppose the annual volatility of load in Idaho is two percent. This implies that the standard deviation of the range of possible loads in Idaho a year from now is two percent, while the standard deviation four years from now is four percent. Mean Reversion If volatility were constant over the forecast period, then the standard deviation would increase linearly with the square root of time. This is described as a "Random Walk" process and often provides a reasonable assumption for long-term uncertainty. However, for energy commodities as well as many other variables in the short-term, this is not typically the case. Excepting seasonal effects, the standard deviation increases less quickly with longer forecast time. This is called a mean reverting process - variable outcomes tend to revert back towards a long-term mean after experiencing a shock: 2 A stochastic or random process is the counterpart to a deterministic process. Instead of dealing with only one possible reality of how the variables might evolve over time, there is some indeterminacy in the future evolution described by probability distributions. 3 "Standard Deviation" and "Variance" are standard statistical terms describing the spread of possible outcomes. The Variance equals the Standard Deviation squared. PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 145 Figure H.1 – Stochastic Processes For a random walk process, the distribution of possible future outcomes continues to increase indefinitely. While for a mean reverting process, the distribution of possible outcomes reaches a steady-state. Actual observed outcomes will continue to vary within the distribution, but the distribution across all possible outcomes does not increase: Figure H.2 – Random Walk Price Process and Mean Reverting Process The volatility and mean reversion rate parameters combine to provide a compact description of the distribution of possible variable outcomes over time. The volatility describes the size of a typical shock or deviation for a particular variable and the mean reversion rate describes how quickly the variable moves back towards the long-run mean after experiencing a shock. 0.0 0.5 1.0 1.5 2.0 2.5 0 10 20 30 40 50 60 Pr i c e I n d e x Time to Delivery Stochastic Processes Random Walk Expectation Mean-Reverting Expectation <----Observed Forecast --> 0.0 0.5 1.0 1.5 2.0 2.5 0 6 12 18 24 30 36 Pr i c e I n d e x Time to Delivery Random Walk Price Process 0.0 0.5 1.0 1.5 2.0 2.5 0 6 12 18 24 30 36 Li k e l i h o o d Time to Delivery Mean Reverting Price Process PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 146 Estimating Short-term Process Parameters Short-term uncertainty can best be described as a mean reverting process. The factors that drive uncertainty in the short-term are generally short-lived, decaying back to long-run average levels. Short-term uncertainty is mainly driven by weather (temperature, windiness, rainfall) but can also be driven by short-term economic factors, congestion, outages, etc. The process for estimating short-term uncertainty parameters is similar for most variables of interest. However, each of PacifiCorp's variables have characteristics that make their processes slightly different. The process for estimating short-term uncertainty parameters is described in detail below for the most straightforward variable -- natural gas prices. Each of the other variables is then discussed in terms of how they differ from the standard natural gas price parameter estimation process. Stochastic Process Description The first step in developing process parameter estimates for any uncertain variable is to determine the form of the distribution and time step for uncertainty. In the case of natural gas, and prices in general, the lognormal distribution is a good representation of possible future outcomes. A lognormal distribution is a continuous probability distribution of a random variable whose logarithm is normally distributed4. The lognormal distribution is often used to describe prices because it is bounded on the bottom by zero and has a long, asymmetric "tail" reflecting the possibility that prices could be significantly higher than the average: Figure H.3 – Lognormal Distribution and Cumulative Lognormal Distribution The time step for calculating uncertainty parameters depends on how quickly a variable can experience a significant change. Natural gas prices can change substantially from day to day and are reported on a daily basis, so the time step for analysis will be one day. 4 A normal distribution is the most common continuous distribution represented by a bell-shaped curve that is symmetrical about the mean, or average, value. 0 0 0.5 1 1.5 2 2.5 3 Lik e l i h o o d Price index Lognormal Distribution 90th Percentile 10th Percentile Expected Index 0 0 0.5 1 1.5 2 2.5 3 Lik e l i h o o d Price Index Cumulative Lognormal Distribution 90th Percentile10th Percentile Expected Index PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 147 All short-term parameters were calculated on a seasonal basis to reflect the different dynamics present during different seasons of the year. For instance, the volatility of gas prices is higher in the winter and lower in the spring and summer. Seasons were defined as follows: Table H.1 - Seasonal Definition Winter December, January, and February Spring March, April, and May Summer June, July, and August Data Development Basic Data Set: The natural gas price data were organized into a consistent dataset with one natural gas price for each gas delivery point reported for each delivery day. The data were checked to make sure that there were no missing or duplicate dates. If no price is reported for a particular date, the date is included but left blank to maintain a consistent 24 hour time step between all observed prices. Four years of daily data from 2012 to 2015 was used for this short-term parameter analysis. The following chart shows the resulting data set for the Sumas gas basin: Figure H.4 – Daily Gas Prices for SUMAS Basin Development of Price Index: Uncertainty parameters are estimated by looking at the movement, or deviation, in prices from one day to the next. However, some of this movement is due to expected factors, not uncertainty. For instance, gas prices are expected to be higher during winter or as we move towards winter. This expectation is already included in the gas price forecast and should not be considered a shock, or random event. In order to capture only the random or uncertain portion of price PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 148 movements, a price index is developed that takes into account the expected portion of price movements. There are three categories of price expectations that are calculated: Seasonal Average: The level of gas prices may be different from one year to the next. While this can be attributed to random movements or shocks in the gas markets, it is not a short-term event and should not be included in the short-term uncertainty process. In order to account for this possible difference in the level of gas prices, the average gas price for each season and year is calculated. For example, Sumas prices in the winter of 2012 average $3.02/MMBtu. Monthly Average: Within a season, there are different expected prices by month. For instance, within the fall season, November gas prices are expected to be much higher than September and October prices as winter is just around the corner. A monthly factor representing the ratio of monthly prices to the seasonal average price is calculated. For example, February prices in Sumas are 108 percent of the winter average price. Weekly Shape: Many variables exhibit a distinct shape across the week. For instance, loads and electricity prices are higher during the middle of the week and lower on the weekends. The expected shape of gas prices across the week was calculated but found to be insignificant (expected variation by weekday did not exceed two percent of the weekly average). These three components: seasonal average, monthly shape, and weekly shape, combine to form an expected price for each day. For example, the expected price of gas in Sumas in January of 2012 was $2.84/MMBtu, the product of the seasonal average and the monthly shape factor 𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝐺𝑎𝑠 𝑃𝑟𝑖𝑐𝑒 =𝑆𝑒𝑎𝑠𝑜𝑛𝑎𝑙 𝐴𝑣𝑔.𝑃𝑟𝑖𝑐𝑒∗𝑀𝑜𝑛𝑡ℎ𝑙𝑦 𝑆ℎ𝑎𝑝𝑒 𝑤𝑖𝑡ℎ𝑖𝑛 𝑡ℎ𝑒 𝑆𝑒𝑎𝑠𝑜𝑛 The chart below shows the comparison of the actual Sumas prices with the "expected" prices: PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 149 Figure H.5 – Daily Gas Prices for SUMAS Basin with "expected" prices Dividing the actual gas prices by the expected prices forms a price index that averages one. This index captures only the random component of price movements—the portion not explained by expected seasonal, monthly, and weekly shape. Figure H.6 – Gas Price Index for SUMAS Basin PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 150 Parameter Estimation – Autoregressive Model Uncertainty parameters are calculated for each variable by regressing the movement of each regions price index compared to the previous day's index. Step 1 - Calculate Log Deviation of Price Index Since gas prices are log normally distributed, the regression analysis is performed on the natural log of prices and their log deviations. The log deviations are simply the differences between the natural log of one day's price index and the natural log of the previous day's price index. Step 2 - Perform Regression The log deviations of price index are regressed against the previous day's logarithm of price index for each season as well as for the entire data set. The following chart shows the log of the price index versus the log deviations for Sumas gas for all seasons and the resulting regression equation: Figure H.7 – Regression for SUMAS Gas Basin Step 3 - Interpret the Results The INTERCEPT of the regression represents the log of the long-run mean. So in this case, the intercept is approximately zero, implying that the long-run mean is equal to one. This is consistent with the way in which the price index is formulated. The SLOPE of the regression is related to the auto correlation and mean reversion rate: 𝑎𝑢𝑡𝑜 𝑐𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑖𝑜𝑛=Ø =1 +𝑠𝑙𝑜𝑝𝑒 𝑀𝑒𝑎𝑛 𝑅𝑒𝑣𝑒𝑟𝑠𝑖𝑜𝑛 𝑅𝑎𝑡𝑒 𝛼= −ln(Ø) The autocorrelation measures how much of the price shock from the previous time period remains in the next time period. For instance, if the autocorrelation is 0.4 and gas prices PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 151 yesterday experienced a 10 percent jump over the norm, today's expected price would be four percent higher than normal. In addition, today's gas price will experience a shock today that may result in prices higher or lower than this expectation. The mean reversion rate expresses the same thing in a different manner. The higher the mean reversion rate, the faster prices revert to the long-run mean. The last component of the regression analysis is the STANDARD ERROR or STEYX. This measures the portion of the price movements not explained by mean reversion and is the estimate of the variable's volatility. Both the mean reversion rate and volatility calculated with this process are daily parameters and can be applied directly to daily movements in gas prices. Step 4 - Results The natural gas price parameters derived through this process are reported in the table below. Table H.2 - Uncertainty Parameters for Natural Gas Electricity Price Process For the most part, electricity prices behave very similar to natural gas prices. The lognormal distribution is generally a good assumption for electricity. While electricity prices do occasionally go below zero, this is not common enough to be worth using the Normal distribution assumption. And the distribution of electricity prices is often skewed upwards. In fact, even the lognormal assumption is sometimes inadequate for capturing the tail of the electricity price distribution. Similar to gas prices, electricity price can experience substantial change from one day to the next so a daily time step should be used. Basic Data Set: The electricity price data were organized into a consistent dataset with one price for each region reported for each delivery day similar to gas prices. Data covers the 2012 through 2015 time period. However, electricity prices are reported for "High Load Level" periods (16 hours for six days a week) and "Low Load Level" periods (eight hours for six days a week and 24 hours on Sunday & NERC holidays). In order to have a consistent price definition, a composite price calculated based on 16 hours of peak and eight hours of off-peak prices is used for Monday through Saturday. The Low Load Level price was used for Sundays since that already reflects the 24 hour price. Missing and duplicate data is handled in a fashion similar to gas prices. Illiquid delivery point prices are filled using liquid hub prices as reference. Mid-C is the most liquid market in PACW, so missing prices for COB are filled using latest available spread between COB and Mid-C markets. Similarly, Four Corner prices are filled using Palo Verde prices. Winter Spring Summer Fall KERN OPAL Daily Volatility 13.2%10.4%2.7%2.8% Daily Mean Reversion Rate 0.219 0.652 0.068 0.060 SUMAS Daily Volatility 14.0%10.0%4.2%6.0% Daily Mean Reversion Rate 0.197 0.537 0.125 0.157 PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 152 Development of Price Index: As with gas prices, an electricity price index was developed which accounts for the expected components of price movements. The "expected" electricity price incorporates all three possible adjustments: seasonal average, monthly shape and weekly shape. For instance, the expected price for January 2, 2012 in the Four Corners region was $24.28/MWh. This price incorporates the 2012 winter average price of $25.26/MWh times the monthly shape factor for January of 94 percent and the weekday index for Monday of 102 percent. The following chart shows the Four Corners actual and expected electricity prices over the analysis time period. Figure H.8 – Daily Electricity Prices for Four Corners Electricity Price Uncertainty Parameters Uncertainty parameters are calculated for each electric region similar to the process for gas prices. The electricity price parameters derived through this process are reported in the table below. PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 153 Table H.3 - Uncertainty Parameters for Electricity Regions Regional Load Process There are only two significant differences between the uncertainty analysis for regional loads and natural gas prices. The distribution of daily loads is somewhat better represented by a normal distribution rather than a lognormal distribution. And, similar to electricity prices, loads have a significant expected shape across the week. The chart below shows the distribution of historical load outcomes for the Portland area as well as normal and lognormal distribution functions representing load possibilities. Both distributions do a reasonable job of representing the spread of possible load outcomes but the tail of the lognormal distribution implies the possibility of higher loads than is supported by the historical data. Figure H.9 – Probability Distribution for Portland Load Winter Spring Summer Fall Four Corners Daily Volatility 10.57%8.68%10.51%6.55% Daily Mean Reversion Rate 0.129 0.466 0.270 0.372 CA-OR Border Daily Volatility 13.61%22.88%23.51%7.35% Daily Mean Reversion Rate 0.135 0.435 0.390 0.227 Mid-Columbia Daily Volatility 16.18%41.99%38.34%7.93% Daily Mean Reversion Rate 0.138 0.510 0.910 0.188 Palo Verde Daily Volatility 10.59%5.82%8.78%5.01% Daily Mean Reversion Rate 0.160 0.308 0.252 0.247 PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 154 Development of Load Index: As with electricity prices, a load index was developed which accounts for the expected components of load movements incorporating all three possible adjustments. For instance, the expected load for January 2, 2012 in Portland was 314 MW. This load incorporates the 2012 winter average load of 302 MW times the monthly shape factor for January of 101 percent and the weekday index for Monday of 102 percent. The following chart shows the Portland actual and expected loads over the analysis time period. Figure H.10 – Daily Average Load for Portland Load Uncertainty Parameters Uncertainty parameters are calculated for each load region similar to the process for gas and electricity prices. Since loads are modeled as normally, rather than log-normally distributed, deviations are simply calculated as the difference between the load index and the previous day's index. The uncertainty parameters for regional loads derived through this process are reported in the table below. PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 155 Table H.4 - Uncertainty Parameters for Load Regions Hydro Generation Process There are two differences between the uncertainty analysis for hydro generation and natural gas prices. Hydro generation varies on a slower time frame than other variables analyzed. As such, average hydro generation is calculated and analyzed on a weekly, rather than daily, basis. Generation is calculated as the average hourly generation across the 168 hour in a week. In addition, an extra year of data was analyzed for hydro generation. The hydro analysis covers the 2011 through 2015 time period. Development of Hydro Index: A hydro generation index was developed which accounts for the expected components of hydro movements incorporating seasonal and monthly adjustments. For instance, the expected hydro generation for the week of January 1, 2011 through January 7, 2011 in the Western Region was 596 MW. This generation incorporates the 2011 winter average generation of 562 MW times the monthly shape factor for January of 106 percent. The following chart shows the western hydro actual and expected generation over the analysis time period. Winter Spring Summer Fall California Daily Volatility 4.5%4.1%3.6%4.8% Daily Mean Reversion Rate 0.268 0.263 0.156 0.296 Idaho Daily Volatility 3.1%5.2%4.8%4.9% Daily Mean Reversion Rate 0.175 0.097 0.101 0.210 Portland Daily Volatility 3.3%2.9%3.9%3.4% Daily Mean Reversion Rate 0.237 0.204 0.294 0.268 Oregon Other Daily Volatility 4.4%3.4%3.8%4.1% Daily Mean Reversion Rate 0.206 0.279 0.200 0.212 Utah Daily Volatility 2.2%2.9%4.5%3.3% Daily Mean Reversion Rate 0.400 0.398 0.211 0.287 Washington Daily Volatility 4.9%3.8%4.8%4.4% Daily Mean Reversion Rate 0.202 0.250 0.184 0.184 Wyoming Daily Volatility 1.7%1.6%1.6%1.7% Daily Mean Reversion Rate 0.263 0.271 0.316 0.192 PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 156 Figure H.11 – Weekly Average Hydro Generation in the West Hydro Generation Uncertainty Parameters Uncertainty parameters are calculated for each hydro region similar to the process for gas and electricity prices. The uncertainty parameters for hydro generation derived through this process are reported in the table below. Table H.5 - Uncertainty Parameters for Hydro Generation Short-term Correlation Estimation Correlation is a measure of how much the random component of variables tend to move together. After the uncertainty analysis has been performed, the process for estimating correlations is relatively straight-forward. Winter Spring Summer Fall Daily Volatility 20.83%13.38%14.89%27.98% Daily Mean Reversion Rate 0.81 0.37 1.44 1.06 PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 157 Step 1 - Calculate Residual Errors Calculate the residual errors of the regression analysis for all of the variables. The residual error represents the random portion of the deviation not explained by mean reversion. It is calculated for each time period as the difference between the actual value and the value predicted by the linear regression equation: 𝐸𝑟𝑟𝑜𝑟=𝐴𝑐𝑡𝑢𝑎𝑙 𝐷𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛−(𝑆𝑙𝑜𝑝𝑒∗𝑃𝑟𝑒𝑣𝑖𝑜𝑢𝑠 𝐷𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛+𝐼𝑛𝑡𝑒𝑟𝑐𝑒𝑝𝑡) All of the residual errors are compiled by delivery date. Step 2 - Calculate Correlations Correlate the residual errors of each pair of variables: 𝐶𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑖𝑜𝑛(𝑋,𝑌)= ∑[(𝑥𝑖−𝑥𝑎𝑣𝑔.)∗(𝑦𝑖−𝑦𝑎𝑣𝑔.)]𝑛𝑖 √∑(𝑥𝑖−𝑥𝑎𝑣𝑔.)2 ∗𝑛𝑖∑(𝑦𝑖−𝑦𝑎𝑣𝑔.)2𝑛𝑖 There are a few things to note about the correlation calculations. First, correlation data must always be organized so that the same time period is being compared for both variables. So for instance, weekly hydro deviations cannot be compared to daily gas price deviations. Thus, a daily regression analysis was performed for the hydro variables. Also note that what is being correlated is the residual errors of the regression—only the uncertain portion of the variable movements. Variables may exhibit similar expected shapes—both loads and electricity prices are higher during the week than on the weekend. This coincidence is captured in the expected weekly shapes input into the planning model. The correlation calculated here captures the extent to which the shocks experienced by two different variables tend to have similar direction and magnitude. The resulting short-term correlations by season are reported below: Table H.6 - Short-term Correlations by Season SHORT-TERM WINTER CORRELATIONS K-O SUMAS 4C COB Mid-C PV CA ID Portland OR Other UT WA WY Hydro K-O 100%92%53%27%27%52%-4%7%14%6%2%13%6%1% SUMAS 92%100%46%28%28%45%-2%9%17%10%3%16%9%-1% 4C 53%46%100%54%53%78%11%21%35%27%25%34%22%6% COB 27%28%54%100%96%71%14%17%35%37%18%45%22%7% Mid-C 27%28%53%96%100%68%14%18%36%37%18%46%23%5% PV 52%45%78%71%68%100%10%16%30%25%22%31%16%9% CA -4%-2%11%14%14%10%100%27%40%73%32%37%18%6% ID 7%9%21%17%18%16%27%100%31%33%34%37%31%-6% Portland 14%17%35%35%36%30%40%31%100%70%51%66%35%6% OR Other 6%10%27%37%37%25%73%33%70%100%43%65%33%8% UT 2%3%25%18%18%22%32%34%51%43%100%44%48%0% WA 13%16%34%45%46%31%37%37%66%65%44%100%33%15% WY 6%9%22%22%23%16%18%31%35%33%48%33%100%5% Hydro 1%-1%6%7%5%9%6%-6%6%8%0%15%5%100% PACIFICORP – 2017 IRP APPENDIX H – STOCHASTIC PARAMETERS 158 Conclusion For the continuous, stochastic variables that drive PacifiCorp's electricity environment short-term volatility and mean reversion, complete with corresponding correlations, provide a robust picture of the spread of future outcome. The standard parameters developed here can be used within the PaR model to develop PacifiCorp's Integrated Resource Plan. SHORT-TERM SPRING CORRELATIONS K-O SUMAS 4C COB Mid-C PV CA ID Portland OR Other UT WA WY Hydro K-O 100%87%13%9%6%18%-1%-1%-2%0%-3%-6%3%-2% SUMAS 87%100%12%9%6%14%-2%-2%2%1%-3%-1%6%-3% 4C 13%12%100%42%35%64%9%9%12%10%20%11%5%-2% COB 9%9%42%100%86%46%14%2%30%28%15%33%13%3% Mid-C 6%6%35%86%100%33%16%7%28%26%22%30%9%0% PV 18%14%64%46%33%100%12%13%24%19%30%19%9%1% CA -1%-2%9%14%16%12%100%23%25%45%16%31%4%3% ID -1%-2%9%2%7%13%23%100%9%16%47%14%12%-11% Portland -2%2%12%30%28%24%25%9%100%73%29%63%24%10% OR Other 0%1%10%28%26%19%45%16%73%100%33%69%19%11% UT -3%-3%20%15%22%30%16%47%29%33%100%27%35%-11% WA -6%-1%11%33%30%19%31%14%63%69%27%100%19%22% WY 3%6%5%13%9%9%4%12%24%19%35%19%100%2% Hydro -2%-3%-2%3%0%1%3%-11%10%11%-11%22%2%100% SHORT-TERM SUMMER CORRELATIONS K-O SUMAS 4C COB Mid-C PV CA ID Portland OR Other UT WA WY Hydro K-O 100%56%7%10%5%11%-4%8%12%12%4%11%-1%0% SUMAS 56%100%10%13%5%13%-1%3%16%12%-8%11%-6%3% 4C 7%10%100%45%34%84%21%8%19%20%25%12%10%5% COB 10%13%45%100%66%53%16%15%35%34%12%27%-1%24% Mid-C 5%5%34%66%100%37%19%9%35%34%16%30%2%8% PV 11%13%84%53%37%100%16%6%19%21%20%10%11%12% CA -4%-1%21%16%19%16%100%30%26%49%24%37%9%4% ID 8%3%8%15%9%6%30%100%14%19%38%21%20%9% Portland 12%16%19%35%35%19%26%14%100%78%18%63%-4%22% OR Other 12%12%20%34%34%21%49%19%78%100%27%75%-2%19% UT 4%-8%25%12%16%20%24%38%18%27%100%26%43%2% WA 11%11%12%27%30%10%37%21%63%75%26%100%-1%15% WY -1%-6%10%-1%2%11%9%20%-4%-2%43%-1%100%-3% Hydro 0%3%5%24%8%12%4%9%22%19%2%15%-3%100% SHORT-TERM FALL CORRELATIONS K-O SUMAS 4C COB Mid-C PV CA ID Portland OR Other UT WA WY Hydro K-O 100%35%14%7%4%17%9%11%8%14%8%10%8%12% SUMAS 35%100%6%3%4%1%7%7%9%16%6%11%17%7% 4C 14%6%100%45%38%73%16%13%22%24%28%23%10%-18% COB 7%3%45%100%85%50%7%6%21%22%20%24%1%-12% Mid-C 4%4%38%85%100%37%9%9%24%25%13%26%0%-10% PV 17%1%73%50%37%100%12%14%20%20%26%19%8%-16% CA 9%7%16%7%9%12%100%26%43%66%27%54%19%5% ID 11%7%13%6%9%14%26%100%22%27%35%24%7%-11% Portland 8%9%22%21%24%20%43%22%100%77%40%71%32%9% OR Other 14%16%24%22%25%20%66%27%77%100%37%82%31%8% UT 8%6%28%20%13%26%27%35%40%37%100%36%37%-2% WA 10%11%23%24%26%19%54%24%71%82%36%100%31%9% WY 8%17%10%1%0%8%19%7%32%31%37%31%100%13% Hydro 12%7%-18%-12%-10%-16%5%-11%9%8%-2%9%13%100% PACIFICORP – 2017 IRP APPENDIX I – PLANNING RESERVE MARGIN STUDY 159 APPENDIX I - PLANNING RESERVE MARGIN STUDY Introduction The planning reserve margin (PRM), measured as a percentage of coincident system peak load, is a parameter used in resource planning to ensure there are adequate resources to meet forecasted load over time. PacifiCorp selects a PRM for use in its resource planning by studying the relationship between cost and reliability among ten different PRM levels, accounting for variability and uncertainty in load and generation resources.1 Costs include capital and run-rate fixed costs for new resources required to achieve ten different PRM levels, ranging from 11 percent to 20 percent, along with system production costs (fuel and non-fuel variable operating costs, contract costs, and market purchases). In analyzing reliability, PacifiCorp performed a stochastic loss of load study using the Planning and Risk (PaR) production cost simulation model to calculate the following reliability metrics for each PRM level: Expected Unserved Energy (EUE): Measured in gigawatt-hours (GWh), EUE reports the expected (mean) amount of load that exceeds available resources over the course of a given year. EUE measures the magnitude of reliability events, but does not measure frequency or duration. Loss of Load Hours (LOLH): LOLH is a count of the expected (mean) number of hours in which load exceeds available resources over the course of a given year. A LOLH of 2.4 hours per year equates to one day in 10 years, a common reliability target in the industry. LOLH measurs the duration of reliability events, but does not measure frequency or magnitude. Loss of Load Events (LOLE): LOLE is a count of the expected (mean) number of reliability events over the course of a given year. A LOLE of 0.1 events per year equates to one event in 10 years, a common reliability target in the industry. LOLE measures the frequency of reliability events, but does not measure magnitude or duration. PacifiCorp’s loss of load study results reflect its participation in the Northwest Power Pool (NWPP) reserve sharing agreement. This agreement allows a participant to receive energy from other participants within the first hour of a contingency event, defined as an event when there is an unexpected failure or outage of a system component, such as a generator, transmission line, circuit breaker, switch, or other electrical element. PacifiCorp’s participation in the NWPP reserve sharing agreement improves reliability at a given PRM level. Upon evaluating the relationship between cost and reliability in its PRM study, PacifiCorp will continue to use a 13 percent target PRM in its resource planning. 1 Costs and reliability metrics are calculated for eleven different PRM levels, ranging from 10 percent to 20 percent. Comparative analysis among each PRM is performed for 10 different PRM levels by comparing the cost and reliability results from PRM levels ranging between 11 percent and 20 percent to those from the 10 percent PRM. PACIFICORP – 2017 IRP APPENDIX I – PLANNING RESERVE MARGIN STUDY 160 Methodology Figure I.1 shows the workflow used in PacifiCorp’s PRM study. The four basic modeling steps in the workflow include: (1) using the System Optimizer (SO) model, produce resource portfolios among eleven different PRM levels ranging between 10 percent and 20 percent; (2) using the Planning and Risk model (PaR), produce reliability metrics for each resource portfolio; (3) using PaR, produce system stochastic variable production costs with full market access for each resource portfolio; (4) produce the marginal cost of reliabability using outcomes of different PRM levels, (5) select PRM level. Figure I.1 - Workflow for Planning Reserve Margin Study Development of Resource Portfolios The SO model is used to produce resource portoflios assuming PRM levels ranging between 10 percent and 20 percent. The SO model optimizes expansion resources over a 20-year planning horizon to meet peak load inclusive of the PRM applicable to each case. An improvement was made in the study to meet the PRM in both summer and winter. As the PRM level is increased from 10 percent to 20 percent, additional resources are added to the portfolio. Resource options used in this step of the workflow include demand side management (DSM), gas-fired combined cycle combustion turbines (CCCT), gas-fired simple cycle combustion turbines (SCCT), renewable resources and front office transactions (FOTs). FOTs are considered as a resource expansion option in this phase of the workflow. FOTs are proxy resources used in the IRP portfolio development process that represent firm forward short- term market purchases for summer and winter on-peak delivery, which coincides with the time PACIFICORP – 2017 IRP APPENDIX I – PLANNING RESERVE MARGIN STUDY 161 of year and time of day in which PacifiCorp observes its coincident system peak load. These proxy resources are a reasonable representation of firm market purchases when performing comparative analysis of different resource portfolios to arrive at a preferred portfolio in the IRP. Upfront capital and run-rate fixed costs from each portfolio are recorded and used later in the workflow where the relationship between cost and reliability is analyzed. Resources from each portfolio are used in the subsequent workflow steps where reliability metrics and production costs are produced in PaR. Development of Reliability Metrics PaR is used to produce reliability metrics for each of the resource portfolios developed assuming PRM levels ranging between 10 percent and 20 percent. PaR is a production cost simulation model, configured to represent PacifiCorp’s integrated system, that uses Monte Carlo random sampling of stochastic variables to produce a distribution of system operation. For this step in the workflow, reliability metrics are produced from a 500-iteration PaR simulation with Monte Carlo draws of stochastic variables that affect system reliability—load, hydro generation, and thermal unit outages. As discussed above, system balancing hourly purchases are enabled to capture the contribution of firm market purchases to system reliability. The PaR reliability studies are used to report instances where load exceeds available resources, including system balancing hourly purchases. Reported EUE measures the stochastic mean volume of instances where load exceeds available resources, and is mesasured in GWh. EUE measures the magnitude of reliability events. Reported LOLH is a count of the stochastic mean hours in which load exceeds available resources. LOLH measures the duration of reliability events. Reported LOLE is a count of the stochastic mean events in which load exceeds available resources. LOLE is a measure of the frequency of reliability events. Each of the reliability metrics described above is adjusted to account for PacifiCorp’s participation in the NWPP reserve sharing agreement, which allows a participant to receive energy from other participants within the first hour of a contingency event. The NWPP adjustments are made to EUE by reducing the stochastic mean volume of instances where load exceeds available resources for the first hour of a reliability event. For example, if the stochastic mean volume of EUE for a reliability event is 120 MWh, equal to 40 MWh in three consecutive hours, then the adjusted EUE is 80 MWh after removing the first hour of the event. Using this same example, LOLH would be adjusted from three to two hours, and LOLE would not be adjusted. The LOLE is only adjusted inasmuch as a given reliability event has a one hour duration. For PaR, the contribution of firm market purchases are removed and instead include system balancing hourly purchases that cover the firm market purchases, limited by transmission and market depth limits, for the reliability metrics. Development of System Variable Production Costs In addition to using PaR to develop reliability metrics, PaR is also used to produce system variable production operating costs for each of the resource portfolios developed assuming PRM levels ranging between 10 percent and 20 percent. For PaR’s system variable production cost runs, its Monte Carlo sampling of stochastic variables is expanded to include natural gas and PACIFICORP – 2017 IRP APPENDIX I – PLANNING RESERVE MARGIN STUDY 162 wholesale market prices in addition to load, hydro generation, and thermal unit outages. At this step, the stochastic treatment of market prices is key given its influence on the economic dispatch of system resources, cost of system balancing purchases, and revenues from system balancing sales. In this step, full market access is included for the simulation. The stochastic mean of system variable costs is added to the upfront capital and run-rate fixed costs from each portfolio so that total portfolio costs are captured for each PRM level. Marginal Cost of Reliability The marginal cost of reliability compares costs and reliabability outcomes across different PRM levels for 2020 through 2030. The use of a 10-year test period was an improvement to that of earlier IRPs which used a one-year test period. The marginal cost of reliability for each PRM, vis-a-vis that of the 10-percent PRM, is calculated as the difference in total production costs divided by the change in EUE. Correspondingly, for a 10 year period, the average marginal cost of reliability is the 10-year nominal levelized cost of yearly marginal reliability costs. The average ten-year marginal cost of reliability is calculated for all PRM levels ranging between 11 percent and 20 percent. Selection of PRM Level Using the marginal cost of reliability analysis, the PRM level is selected for use in the 2017 IRP. PACIFICORP – 2017 IRP APPENDIX I – PLANNING RESERVE MARGIN STUDY 163 Results Resource Portfolios Table I.1 shows new resources added to the portfolio for the summer at PRM levels ranging between 10 and 20 percent. Each portfolio includes high load hour (HLH) front office transactions (FOTs) ranging from 550 to 1,136 MWs and flat FOTs of 176 MW in all PRMs. A 454 MW CCCT is added for the 19 percent and 20 percent PRM studies. DSM resource additions range between 374 MW and 431 MW. An improvement, to prior IRPs, was the inclusion of DSM Class 1 to the resource selection. As the PRM increases, system capacity is largely met with FOTs. Because new CCCT resources are added in blocks indicative of a typical plant size (i.e. the model cannot add a 2 MW CCCT plant), the addition of new DSM resources does not always follow an increase in the PRM. Table I.1 - Expansion Resource Additions by PRM for Summer Summer PRM (%) DSM Capacity at System Peak DSM Class 1 FOT FOT Flat SCCT CCCT Total 10 380 0 550 176 0 0 1,107 11 374 0 651 176 0 0 1,201 12 380 0 738 176 0 0 1,294 13 384 0 828 176 0 0 1,388 14 394 0 912 175 0 0 1,481 15 400 0 1,000 175 0 0 1,575 16 382 0 1,112 176 0 0 1,670 17 425 25 1,134 174 0 0 1,759 18 431 113 1,136 172 0 0 1,852 19 396 0 982 175 0 454 2,007 20 380 0 1,093 176 0 454 2,103 PACIFICORP – 2017 IRP APPENDIX I – PLANNING RESERVE MARGIN STUDY 164 Table I.2 shows new resources added to the portfolio for the winter at PRM levels ranging between 10 percent and 20 percent. The winter resource rating are difference from summer due to temperative variations and contribution to system peak. Table I.2 - Expansion Resource Additions by PRM for Winter Reliability Metrics Table I.3 shows EUE, LOLH, and LOLE reliability results before and after adjusting these reliability metrics for PacifiCorp’s participation in the NWPP reserve sharing agreement. Each of the reliability metrics generally improve as the PRM increases and after accounting for benefits associated with PacifiCorp’s participation in the NWPP reserve sharing agreement. After accounting for its participation in the NWPP reserve sharing agreement, all PRM levels meet a one day in ten year planning criteria (LOLH at or below 2.4), and PRM levels of between 19 and 20 percent meet a one event in ten year planning criteria (LOLE at or above 0.1). Winter PRM (%) DSM Capacity at System Peak DSM Class 1 FOT FOT Flat SCCT CCCT Total 10 240 0 26 176 0 0 442 11 237 0 34 176 0 0 447 12 240 0 41 176 0 0 456 13 243 0 48 176 0 0 467 14 250 0 55 175 0 0 480 15 253 0 70 175 0 0 497 16 241 0 86 176 0 0 502 17 259 25 101 174 0 0 559 18 266 113 93 172 0 0 643 19 248 0 133 175 0 454 1,010 20 239 0 149 176 0 454 1,018 PACIFICORP – 2017 IRP APPENDIX I – PLANNING RESERVE MARGIN STUDY 165 Table I.3 - Expected Reliability Metrics by PRM The reliability metrics do not montonically improve with each incremental increase in the PRM. This is influenced by the physical location of new resources within PacifiCorp’s system at varying PRM levels and the ability of these resources to serve load in all load pockets when Monte Carlo sampling is applied to load, hydro generation, and thermal unit outages. Considering that the reliability metrics are measuring very small magnitudes of change among the different PRM levels, the PaR outputs are fit to a logarithmic function to report the overall trend in reliability improvements as the PRM level increases. Table I.4 shows the fitted EUE LOLH, and LOLE results. Figure I.2, Figure I.3 and Figure I.4 show a plot of the fitted trend for EUE, LOLH, and LOLE, respectively, after accounting for PacifiCorp’s participation in the NWPP reserve sharing agreement. Table I.4 - Fitted Reliability Metrics by PRM Before NWPP Adjustment After NWPP Adjustment PRM (%) Simulated Energy Not Served (GWh) LOLH (<2.4 target year) (Hour) Loss of Load Episodes EUE (GWh) LOLH (Hour) Modeled Loss of Load Episodes 10 79 0.94 0.69 21 0.25 0.15 11 80 0.93 0.68 21 0.25 0.15 12 79 0.94 0.69 21 0.25 0.15 13 78 0.92 0.68 20 0.24 0.15 14 76 0.90 0.66 20 0.24 0.15 15 75 0.90 0.66 20 0.24 0.15 16 78 0.94 0.69 21 0.25 0.15 17 72 0.92 0.68 19 0.24 0.15 18 71 0.91 0.68 18 0.23 0.14 19 33 0.78 0.60 8 0.18 0.10 20 34 0.76 0.58 8 0.19 0.10 Before NWPP Adjustment After NWPP Adjustment PRM (%) EUE (GWh) LOLH (<2.4 target year) (Hour) Modeled Loss of Load Episodes EUE (GWh) LOLH (Hour) Modeled Loss of Load Episodes 10 91 0.97 0.71 24 0.26 0.16 11 81 0.94 0.69 22 0.25 0.15 12 76 0.92 0.68 20 0.24 0.15 13 72 0.90 0.67 19 0.23 0.14 14 68 0.89 0.66 18 0.23 0.14 15 66 0.88 0.66 17 0.23 0.14 16 64 0.87 0.65 16 0.22 0.14 17 62 0.87 0.65 16 0.22 0.13 18 60 0.86 0.65 15 0.22 0.13 19 58 0.86 0.64 15 0.22 0.13 20 57 0.85 0.64 14 0.21 0.13 PACIFICORP – 2017 IRP APPENDIX I – PLANNING RESERVE MARGIN STUDY 166 Figure I.2 - Expected and Fitted Relationship of EUE to PRM Figure I.3 - Expected and Fitted Relationship of LOLH to PRM y = -4.14ln(x) + 24.411 R² = 0.3826 0 5 10 15 20 25 30 10 11 12 13 14 15 16 17 18 19 20 EU E ( G W h ) PRM (%) EUE ln (EUE) y = -0.021ln(x) + 0.2636R² = 0.3756 0.00 0.05 0.10 0.15 0.20 0.25 0.30 10 11 12 13 14 15 16 17 18 19 20 LO L H ( H o u r ) PRM (%) LOLH ln(LOLH) PACIFICORP – 2017 IRP APPENDIX I – PLANNING RESERVE MARGIN STUDY 167 Figure I.4 - Simulated Relationship of Loss of Load Episode to PRM System Costs For the 2020 reference year, Table I.5 shows the stochastic mean of system variable production costs and the upfront capital and run-rate fixed costs, including the cost of new DSM resources, for each portfolio developed at PRM levels ranging between 10 percent and 20 percent. The fixed costs associated with these new resource additions drive total costs higher as PRM levels increase. DSM run-rate costs vary depending on resource additions for DSM Class 1 and new resources where a CCCT was added in 19 percent and 20 percent. y = -0.015ln(x) + 0.1645 R² = 0.2937 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20 10 11 12 13 14 15 16 17 18 19 20 LO L E ( E v e n t s / Y e a r ) PRM (%) LOLE ln(LOLE) PACIFICORP – 2017 IRP APPENDIX I – PLANNING RESERVE MARGIN STUDY 168 Table I.5 – System Variable, Up-front Capital, and Run-rate Fixed Costs by PRM Incremental Cost of Reliability Table I.6 shows the incremental cost of reliability, stated as the 10-year nominal levelized cost of EUE relative to 10 percent PRM, at PRM levels ranging between 11 percent and 20 percent. Figure I.5 depicts this same information graphically. The incremental cost of reliability rises modestly at the 14 percent to 15 percent PRM, then rises dramatically as PRM levels increase from 16 percent to 20 percent. Table I.6 - 10-year nominal levelized cost of EUE relative to 10 percent PRM PRM (%) System Production Costs ($m) Class 2 DSM ($m) Class 1 DSM ($m) Existing Resource Fixed Costs ($m) New Resource Fixed Cost ($m) Total Costs ($m) 10 10,969 437 0 6,093 183 $17,681 11 11,003 404 0 6,093 197 $17,698 12 10,966 437 2 6,093 203 $17,701 13 10,958 463 9 6,093 193 $17,715 14 10,906 514 12 6,093 198 $17,723 15 10,892 553 28 6,093 181 $17,747 16 10,923 440 2 6,093 382 $17,840 17 10,882 522 18 6,093 354 $17,869 18 10,865 535 63 6,093 371 $17,927 19 10,835 527 26 6,093 581 $18,061 20 10,870 429 7 6,093 745 $18,144 PRM Reduction in EUE Reliability from 10% PRM (GWh) Reduction in Total Cost from 10% PRM ($ Million)$/MWh 10 - - $0 11 930 16 $17 12 1,475 19 $13 13 1,861 34 $18 14 2,160 41 $19 15 2,405 66 $27 16 2,612 155 $59 17 2,791 185 $66 18 2,949 243 $82 19 3,091 375 $121 20 3,219 455 $141 PACIFICORP – 2017 IRP APPENDIX I – PLANNING RESERVE MARGIN STUDY 169 Figure I.5 - Incremental Cost of Reliability by PRM Conclusion PacifiCorp will continue to use a 13 percent target PRM in its resource planning after evaluating the relationship between cost and reliability in the PRM study. A PRM below 13 percent would not sufficiently cover the need to carry short-term operating reserve needs (contingency and regulating margin) and longer-term uncertainties such as extended outages and changes in customer load.2 A PRM above 15 percent improves reliability above a one event in ten year planning level, though with a 300 percent to 700 percent increase in the incremental cost per megawatt-hour of reduced EUE when compared to a 13 percent PRM. With these considerations, the selected 13 percent PRM level ensures PacifiCorp can reliably meet customer loads while maintaining operating reserves, with a planning criteria that meets one day in 10 year planning targets, at the lowest reasonable cost. 2 PacifiCorp must hold approximately six percent of its resources in reserve to meet contingency reserve requirements and an estimated additional 4.5 percent to 5.5 percent of its resources in reserve, depending upon system conditions at the time of peak load, as regulating margin. This sums to 10.5 percent to 11.5 percent of operating reserves before even considering longer-term uncertainties such as extended outages (transmission or generation) and customer load growth. $0 $20 $40 $60 $80 $100 $120 $140 $160 10% PRM 11% PRM 12% PRM 13% PRM 14% PRM 15% PRM 16% PRM 17% PRM 18% PRM 19% PRM 20% PRM 10 ‐Ye a r No m . Le v . Co s t of EU E Re l a t i v e to 10 % PR M ($ / M W h ) PACIFICORP – 2017 IRP APPENDIX I – PLANNING RESERVE MARGIN STUDY 170 PACIFICORP – 2017 IRP APPENDIX J – WESTERN RESOURCE ADEQUACY EVALUATION APPENDIX J – WESTERN RESOURCE ADEQUACY EVALUATION Introduction The Public Service Commission of Utah, in its 2008 IRP Order, directed the Company to conduct two analyses pertaining to the Company’s ability 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 Office [of Consumer Services], the WECC is a reasonable source for this evaluation. We direct the Company to identify whether customers or shareholders will 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 meeting for inclusion in the next IRP or IRP update.1 To fulfill the first requirement, PacifiCorp evaluated the Western Electricity Coordinating Council (WECC) Power Supply Assessment (PSA) 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. Western Electricity Coordinating Council Resource Adequacy Assessment The WECC 2016 PSA, issued in December 2016, shows a planning reserve margin (PRM) calculated as a percentage of resources (generation and transfers) and load, and is the percentage of capacity greater than demand. The PRM indicates that there are sufficient resources when the PRM is equal to or greater than the target planning reserve margin. The 2016 PSA shows WECC in total not needing additional resources throughout the entire period of the study, which ends in 2026 (see Figure J.1). In WECC’s PSAs, the region and sub-region target planning reserve margins are calculated using a building block methodology established by WECC. As such, they do not reflect a criteria-based margin determination process and do not reflect any balancing authority area or load serving entity level requirements that may have been established through other processes (e.g., state regulatory authorities). They are not intended to supplant any of those requirements. 1 Public Service Commission of Utah, PacifiCorp 2008 Integrated Resource Plan, Report and Order, Docket No. 09- 2035-01, p. 30. 171 PACIFICORP – 2017 IRP APPENDIX J – WESTERN RESOURCE ADEQUACY EVALUATION The WECC building block methodology is comprised of four elements2: 1. Contingency Reserves – An amount of operating reserves sufficient to reduce area control error to zero in ten minutes following loss of generating capacity, which would result from the most severe single contingency. 2. Regulating Reserves – The amount of spinning reserves responsive to automatic generation control that is sufficient to provide the normal regulating margin. The regulating component of this guideline was calculated using data provided in WECC’s annual loads and resources data request responses. 3. Reserves for Generation Forced Outages – The capacity lost to forced outages for both the summer (July) and winter (December) is added by sub-region and divided by the total capacity reported for each sub-region. The seasonal forced out rates are then averaged across five years to give the forced outage portion of the reserve margin. 4. Temperature Adders – a MW/degree Celsius coefficient is determined by WECC staff based on five years of daily peak demand regressed on daily maximum temperature for every weekday in the season. Fifty years of seasonal extremes in daily peak temperature are used to estimate the difference between a 1-in-2 and 1-in-10 observation. The MW/degree Celsius number is multiplied by the 1-in-10 temperature to yield a 90/10 extreme weather demand forecast. As seen in Figure J.1, the 2016 PSA shows the WECC as having a positive summer power supply margin (PSM) in all years. The PSM is a measure of a region’s ability to meet total load requirements, including its target reserve margin. As such, a PSM of zero or more indicates that demand plus the target reserve margin was met. 2 Further details of building block elements can be found on the WECC website at the following location: https://www.wecc.biz/Reliability/2016LAR_MethodsAssumptions%20(002).pdf 172 PACIFICORP – 2017 IRP APPENDIX J – WESTERN RESOURCE ADEQUACY EVALUATION Figure J.1 - WECC Forecasted Power Supply Margins, Issued 2009 to 2016 (Summer) Note: WECC Power Supply Assessments include Class 1 Planned Resources Only The 2016 PSA shows no deficit for the study period. Figure J.2 shows the difference between the 2016 and 2014 PSA studies. For all years the load forecasts (net internal demand) and capacity resources decreased. The target reserve margins change from year to year, though for the most part are not a major contributor to the PSA deviations between the 2016 and 2014 PSAs. 173 PACIFICORP – 2017 IRP APPENDIX J – WESTERN RESOURCE ADEQUACY EVALUATION Figure J.2 - 2016 less 2014 WECC PSA (for Summer Periods) Tables J.1 and J.2 show both the target summer and winter planning reserve margins calculated in the 2016 WECC PSA report, along with the forecasted yearly results. These results are based on the following elements: • Monthly and annual peak demand and energy forecasts: • Expected generation availability; • Annual energy for energy limited resources; • Coincident hourly-shaping data for loads and energy-limited resources; and • A simplified transmission configuration that reflects nominal power transfer capability limits. 174 PACIFICORP – 2017 IRP APPENDIX J – WESTERN RESOURCE ADEQUACY EVALUATION Table J.1 - 2016 WECC Forecasted Planning Reserve Margins (Summer) Table J.2 – 2016 WECC Forecasted Planning Reserve Margins (Winter) The 2016 WECC planning reserve margin results show that there is no resource need through 2026 on a WECC total basis. However, the planning reserve margin for the CA/MX sub-region falls below the target reserve margin beginning in summer period 2024. Northwest Power Pool (NWPP) is a winter peaking WECC sub-region comprised of Washington, Oregon, Idaho, Montana, Nevada, Utah, western Wyoming, Alberta, British Columbia and the Balancing Authority of Northern California. The target summer reserve margin for this region is 15.2 percent, which is slightly below the WECC Total forecasted planning reserve margin for 2017-2026 (15.37 percent). The target winter reserve margin for this region is 16.70 percent, which is above the WECC Total forecasted planning reserve margin for 2017-2026 (14.27 percent). Market depth refers to a market’s ability to accept individual transactions without a perceptible change in market price. While different from market liquidity3 the two are linked in that a deep market tends to be a liquid market. Electricity market depth is a function of the number of economic agents, market period, generating capacity, transmission capability, transparency, and institutional and/or physical constraints. Based on the 2016 PSA, WECC maintains a positive power supply margin (PSM) through 2026. All of the WECC’s sub-regions also are forecasted to maintain sufficient PSM through 2026, with the exception of the CA/MX sub-region. In total, known market transactions, generation resources, load requirements, and the optimization of transfers within WECC show adequate market depth to maintain target reserve margins for several years. Pacific Northwest Resource Adequacy Forum’s Adequacy Assessment The Pacific Northwest Resource Adequacy Forum (later replaced by the Resource Adequacy Advisory Committee) issued resource adequacy standards in April 2008, which were 3 Market liquidity refers to having ready and willing buyers and sellers for large transactions. Subregion Target Reserve Margin 2017 (S)2018 (S)2019 (S)2020 (S)2021 (S)2022 (S)2023 (S)2024 (S)2025 (S)2026 (S) 15.20%27.7%26.5%28.3%27.9%26.6%25.4%24.7%22.8%20.0%18.9% 14.14%27.0%24.3%22.1%20.1%19.7%19.7%19.6%16.7%16.5%16.5% SRSG 15.82%23.4%21.2%21.1%17.6%17.5%17.5%17.4%17.4%17.4%17.3% CA/MX 16.16%19.1%20.3%20.1%21.3%19.7%18.8%17.4%16.0%16.0%15.6% WECC Total 15.37%24.1%23.6%23.2%22.5%21.0%20.0%18.9%17.3%16.1%15.5% Planning Reserve Margin Subregion Target Reserve Margin 2017-18 (W) 2018-19 (W) 2019-20 (W) 2020-21 (W) 2021-22 (W) 2022-23 (W) 2023-24 (W) 2024-25 (W) 2025-26 (W) 2026-27 (W) 16.70%24.9%24.9%24.1%23.1%22.4%21.3%20.8%19.9%17.7%17.1% 11.65%59.5%51.8%48.4%44.6%41.6%39.5%37.4%35.1%33.3%31.2% SRSG 12.11%101.6%101.0%96.5%94.2%89.8%85.0%80.9%77.1%73.3%69.7% CA/MX 13.50%19.3%19.9%20.8%22.2%18.8%20.3%19.6%17.9%18.2%18.6% WECC Total 14.27%35.3%34.9%34.2%33.5%31.7%29.9%28.8%27.5%26.2%25.3% Planning Reserve Margin 175 PACIFICORP – 2017 IRP APPENDIX J – WESTERN RESOURCE ADEQUACY EVALUATION subsequently adopted by the Northwest Power and Conservation Council. The standard calls for assessments three and five years out, conducted every year, and including only existing resources and planned resources that are already sited and licensed. The Resource Adequacy Advisory Committee issued a Pacific Northwest Power Supply Adequacy Assessment for 2021 on August 10, 2016. 4 This assessment concluded that power supply is expected to be adequate through 2020. However, with the planned retirements of four Northwest coal plants by July of 2022, 1,400 megawatts of new capacity will be needed to maintain the Council’s adequacy standard. 5 In 2021, with the loss of 1,330 megawatts of capacity from the retirements of the Boardman and Centralia 1 coal plants, the likelihood of a power supply shortfall (also referred to as the loss of load probability) rises to 10 percent. In this scenario, the region will need more than 1,000 megawatts of new capacity to maintain adequacy. Northwest utilities show about 550 megawatts of planned generating capacity for 2021, yet this capacity was not included in the August 10, 2016 assessment because it was not yet sited and licensed. Customer versus Shareholder Risk Allocation 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, efficient RFPs and ability to capture opportunistic procurement opportunities when they arise. Market Purchases As described in Volume I, Chapter 6 (Resource Options), PacifiCorp, other utilities, and power marketers who own and operate generation engage in market purchases and sales of electricity on an ongoing basis to balance the system and maximize the economic efficiency of power system operations. In addition to reflecting spot market purchase activity and existing long-term purchase contracts in the IRP portfolio analysis, PacifiCorp models front office transactions (FOT). FOTs are proxy resources, assumed to be firm, that represent procurement activity made on an on-going forward basis to help the Company cover short positions. Solicitations for FOTs can be made years, quarters or months in advance, however, most transactions made to balance PacifiCorp’s system are made on a balance of month, day-ahead, hour-ahead, or intra-hour basis. Annual transactions can be available three or more years in advance. Seasonal transactions are typically delivered during quarters and can be available from one to three years or more in advance. The terms, points of delivery, and products will all vary by individual market point. 4 Pacific Northwest Power Supply Adequacy Assessment for 2021, at https://www.nwcouncil.org/media/7150504/2021-adequacy-assessment-final-aug_9_2016.pdf 5 The standard deems the power supply to be inadequate if the likelihood of a power supply shortfall is higher than 5 percent. 176 PACIFICORP – 2017 IRP APPENDIX J – WESTERN RESOURCE ADEQUACY EVALUATION In developing FOT limits for the 2017 IRP, PacifiCorp reviewed the studies described in the sections above as part of its assessment of western resource adequacy in addition to consideration of its active participation in wholesale power markets, its view of physical delivery constraints, and market liquidity and market depth. For the 2017 IRP, PacifiCorp held its FOT limits consistent with the prior IRP as shown in Table J.3. Table J.3 – Maximum Available Front Office Transactions by Market Hub In determining FOT limits for the 2017 IRP planning cycle, PacifiCorp reviewed historical market purchases from 2009 to 2015 in both the summer peak and winter peak periods. As shown in Figures J.3 and J.4 below, PacifiCorp reviewed its hourly purchases during peak load times in the summer and in the winter when market purchases may be more likely to be constrained by market depth or physical delivery constraints. The review showed that in 34 percent of summer hours and 17 percent of winter hours, PacifiCorp purchased more than its IRP FOT limit of 1,575 MW. 177 PACIFICORP – 2017 IRP APPENDIX J – WESTERN RESOURCE ADEQUACY EVALUATION Figure J.3 - PacifiCorp Summer Peak Market Purchases 2009-2015 Figure J.4 - PacifiCorp Winter Peak Market Purchases 2009-2015 PacifiCorp believes based on its historical market transactions and review of western resource adequacy discussed above that its FOT limits for the 2017 IRP, unchanged from the 2015 IRP, continue to be a reasonable assumption. 34.1 16.7 17.5 >= 1,575 MW 1,575 MW - 2,000 MW > 2,000 MW Pe r c e n t a g e MW Purchased 17.0 8.2 8.8 >= 1,575 MW 1,575 MW - 2,000 MW > 2,000 MW Pe r c e n t a g e MW Purchased 178 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 179 APPENDIX K – CAPACITY EXPANSION RESULTS DETAIL Portfolio Case Build Tables This section provides the System Optimizer portfolio build tables for each of the case scenarios as described in the portfolio development section of Chapter 7. There are seven Regional Haze cases, eleven core cases, twenty sensitivity cases, and four final cases. Table K.1 – Regional Haze Study Reference Guide Case Description Benchmark Load Private Gen CO2 Policy FOTs Gateway 1st Year of New Thermal SO PVRR. ($m) Ref. Reference Case - Base Base Mass Cap B Base None 2032 $24,219 RH-1 Regional Haze 1 - Base Base Mass Cap B Base None 2030 $23,159 RH-2 Regional Haze 2 - Base Base Mass Cap B Base None 2029 $23,482 RH-3 Regional Haze 3 - Base Base Mass Cap B Base None 2029 $23,398 RH-4 Regional Haze 4 - Base Base Mass Cap B Base None 2030 $23,663 RH-5 Regional Haze 5 - Base Base Mass Cap B Base None 2029 $23,177 RH-6 Regional Haze 6 - Base Base Mass Cap B Base None 2028 $23,986 Table K.2 – Core Case Study Reference Guide Case Description Benchmark Load Private Gen CO2 Policy FOTs Gateway 1st Year of New Thermal SO PVRR ($m) OP-1 Optimized Portfolio RH5 Base Base Mass Cap B Base None 2029 $23,177 OP-NT3 Optimized Naughton 3 OP-1 Base Base Mass Cap B Base None 2029 $23,052 OP-REP Wind Repower OP-NT3 Base Base Mass Cap B Base None 2029 $22,984 OP-GW4 Energy Gateway + Repower OP-REP Base Base Mass Cap B Base Segment D2 2029 $23,123 FR-1 Flexible Resource OP-NT3 Base Base Mass Cap B Base None 2021 $23,585 FR-2 Flexible Resource OP-NT3 Base Base Mass Cap B Base None 2021 $24,319 RE-1a OR RPS Just in Time OP-NT3 Base Base Mass Cap B Base None 2029 $23,082 RE-1b WA RPS Just in Time OP-NT3 Base Base Mass Cap B Base None 2029 $23,091 RE-1c OR & WA RPS Just in Time OP-NT3 Base Base Mass Cap B Base None 2029 $23,154 RE-2 OR RPS Early OP-NT3 Base Base Mass Cap B Base None 2029 $23,098 DLC1 Direct Load Control OP-NT3 Base Base Mass Cap B Base None 2030 $23,103 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 180 Table K.3 – Sensitivity Case Study Reference Guide Case Description Benchmark Load Private Gen CO2 Policy FOTs Gateway 1st Year of New Thermal SO PVRR w/ Trans. ($m) RH2a Regional Haze OP-1 Base Base Mass Cap B Base None 2029 $23,404 LD-1 1 in 20 Loads OP-1 1 in 20 Base Mass Cap B Base None 2029 $23,364 LD-2 Low Load OP-1 Low Base Mass Cap B Base None 2030 $21,567 LD-3 High Load OP-1 High Base Mass Cap B Base None 2028 $24,818 PG-1 Low Private Gen OP-1 Base Low Mass Cap B Base None 2029 $23,304 PG-2 High Private Gen OP-1 Base High Mass Cap B Base None 2030 $22,899 CPP-C CPP Mass Cap C OP-1 Base Base Mass Cap C Base None 2029 $23,268 CPP-D CPP Mass Cap D OP-1 Base Base Mass Cap D Base None 2029 $23,102 FOT-1 Limited FOT OP-1 Base Base Mass Cap B Restricted None 2029 $23,347 CO2-1 CO2 Price OP-1 Base Base Tax, No CPP Base None 2030 $26,401 NO-CO2 No CO2 OP-NT3 Base Base No Tax, No CPP Base None 2028 $22,891 BP Business Plan OP-NT3 Base Base Mass Cap D Base None 2030 $23,198 GW1 Gateway 1 OP-NT3 Base Base Mass Cap B Base Segment D 2029 $23,593 GW2 Gateway 2 OP-NT3 Base Base Mass Cap B Base Segment F 2029 $24,054 GW3 Gateway 3 OP-NT3 Base Base Mass Cap B Base Segment D&F 2029 $24,627 GW4 Gateway 4 OP-NT3 Base Base Mass Cap B Base Segment D2 2029 $23,159 Battery Battery Storage FS-GW4 Base Base Mass Cap B Base Segment D2 2029 $23,162 CAES CAES Storage FS-GW4 Base Base Mass Cap B Base Segment D2 2029 $23,121 WCA WCA FS-REP Base Base Mass Cap B Base None 3033 $7,542 WCA-RPS WCA RPS FS-REP Base Base Mass Cap B Base None 3033 $7,557 Table K.4 – Final Case Study Reference Guide Description Benchmark Load Private Gen CO2 Policy FOTs Gateway 1st Year of New Thermal SO PVRR ($m) FS-REP Wind Repower OP-NT3 Base Base Mass Cap B Base Segment D2 2029 $23,042 FS-GW4 Gateway 4 FS-REP Base Base Mass Cap B Base Segment D2 2029 $22,990 FS-1c OR & WA RPS Just in Time FS-GW4 Base Base Mass Cap B Base Segment D2 2029 $23,006 FS-2 OR RPS Early FS-GW4 Base Base Mass Cap B Base Segment D2 2029 $22,995 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 181 Table K.5 – East Side Resource Name and Description Resource List Detailed Description CCCT - DJohns - J 1x1 Combine Cycle Combustion Turbine J-Machine 1x1 with Duct Firing - Dave Johnston Brownfield CCCT - Utah-S - J 1x1 Combine Cycle Combustion Turbine J-Machine 1x1 with Duct Firing - Utah South CCCT - Utah-S - G 1x1 Combine Cycle Combustion Turbine G-Machine 1x1 with Duct Firing - Utah South IC Aero UN Inter-cooled Simple Cycle Combustion Turbine Aero - Utah North SCCT Aero UN Simple Cycle Combustion Turbine Aero - Utah North SCCT Frame DJ Simple Cycle Combustion Turbine Frame - Dave Johnston Brownfield SCCT Frame UTN Simple Cycle Combustion Turbine Frame - Utah North SCCT Frame UTS Simple Cycle Combustion Turbine Frame - Utah North Battery Storage - East Battery Storage – East CAES - East Compressed Air Energy Storage Wind, DJohnston Wind, Wyoming After DJ Retirement Wind, GO Wind, Goshen Idaho Wind, UT Wind, Utah Wind, WYAE Wind, Wyoming Aeolus Utility Solar - PV - Utah-S Utility Solar - Photovoltaic - Utah South DSM, Class 1, ID-Cool/WH Direct Load Control-Cooling & Water Heating-Residential, Commercial & Industrial - Idaho DSM, Class 1, ID-Curtail Curtailment - Idaho DSM, Class 1, ID-Irrigate Direct Load Control-Irrigation -Idaho DSM, Class 1, UT-Cool/WH Direct Load Control-Cooling & Water Heating-Residential, Commercial & Industrial - Utah DSM, Class 1, UT-Curtail Curtailment - Utah DSM, Class 1, UT-ICE storage Ice Energy Storage - Utah DSM, Class 1, UT-Irrigate Direct Load Control-Irrigation -Utah DSM, Class 1, UT-Smart APPl Direct Load Control-Smart Appliance-Residential - Utah DSM, Class 1, UT-Thermostat Direct Load Control-Smart Thermostat-Residential - Utah DSM, Class 1, WY-Cool/WH Direct Load Control-Cooling & Water Heating-Residential, Commercial & Industrial - Wyoming DSM, Class 1, WY-Curtail Curtailment - Wyoming DSM, Class 1, WY-Irrigate Direct Load Control-Irrigation -Wyoming DSM, Class 2, ID DSM, Class 2 - Idaho DSM, Class 2, UT DSM, Class 2 - Utah DSM, Class 2, WY DSM, Class 2 - Wyoming FOT Mona - SMR Front Office Transaction - Summer HLH Product - Mona PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 182 Table K.6 – West-Side Resource Name and Description Resource List Detailed Description CCCT - SOregonCal - J 1x1 Combine Cycle Combustion Turbine J-Machine 1x1 with Duct Firing - Southern Oregon CCCT - WillamValcc - G 1x1 Combine Cycle Combustion Turbine G-Machine 1x1 with Duct Firing - Willamette Valley, Oregon CCCT - WillamValcc - J 1x1 Combine Cycle Combustion Turbine J-Machine 1x1 with Duct Firing - Willamette Valley, Oregon CCCT - Yakima - G 1x1 Combine Cycle Combustion Turbine G-Machine 1x1 with Duct Firing - Yakima, Washington IC Aero PO Inter-cooled Simple Cycle Combustion Turbine Aero - Portland-North Coast, Oregon IC Aero SO Inter-cooled Simple Cycle Combustion Turbine Aero - Southern Oregon IC Aero WV Inter-cooled Simple Cycle Combustion Turbine Aero - Willamette Valley, Oregon IC Aero WW Inter-cooled Simple Cycle Combustion Turbine Aero - Walla Walla, Washington SCCT Frame SO Simple Cycle Combustion Turbine Frame - Southern Oregon Battery Storage - West Battery Storage – West Wind, SO Wind, Southern Oregon Wind, YK Wind, Yakima, Washington Utility Solar - PV - S-Oregon Utility Solar - Photovoltaic - Southern Oregon Utility Solar - PV - Yakima Utility Solar - Photovoltaic - Yakima, Washington Geothermal, Greenfield - West Geothermal, Greenfield - West DSM, Class 1, CA-Cool/WH Direct Load Control-Cooling & Water Heating-Residential, Commercial & Industrial - California DSM, Class 1, CA-Curtail Curtailment - California DSM, Class 1, CA-Irrigate Direct Load Control-Irrigation -California DSM, Class 1, OR-Cool/WH Direct Load Control-Cooling & Water Heating-Residential, Commercial & Industrial - Oregon DSM, Class 1, OR-Curtail Curtailment - Oregon DSM, Class 1, OR-Irrigate Direct Load Control-Irrigation -Oregon DSM, Class 1, OR-Thermostat Direct Load Control-Smart Thermostat-Residential - Oregon DSM, Class 1, WA-Cool/WH Direct Load Control-Cooling & Water Heating-Residential, Commercial & Industrial - Washington DSM, Class 1, WA-Curtail Curtailment - Washington DSM, Class 1, WA-Irrigate Direct Load Control-Irrigation -Washington DSM, Class 1, WA-Thermostat Direct Load Control-Smart Thermostat-Residential - Washington DSM, Class 2, CA DSM, Class 2 - California PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 183 Table K.6 – West-Side Resource Name and Description (Continued) Resource List Detailed Description DSM, Class 2, OR DSM, Class 2 - Oregon DSM, Class 2, WA DSM, Class 2 - Washington FOT COB - SMR Front Office Transaction - Summer HLH Product - California Oregon Border FOT COB - WTR Front Office Transaction - Winter HLH Product - California Oregon Border FOT MidColumbia - SMR Front Office Transaction - Summer HLH Product - Mid Columbia FOT MidColumbia - SMR - 2 Front Office Transaction - Summer HLH Product - Mid Columbia FOT MidColumbia - WTR Front Office Transaction - Winter HLH Product - Mid Columbia FOT MidColumbia - WTR2 Front Office Transaction - Winter HLH Product - Mid Columbia FOT NOB - SMR Front Office Transaction - Summer HLH Product - Nevada Oregon Border FOT NOB - WTR Front Office Transaction - Winter HLH Product - Nevada Oregon Border PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 184 Table K.7 – Regional Haze Cases, Detailed Capacity Expansion Portfolios Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - - - - - (387) - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_AZ - Gas RePower - - - - - - - - 387 - - - - - - - - - - - 387 387 Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources SCCT Frame UTN - - - - - - - - - - - - - - - 200 - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - 617 145 - - - - - - 762 Wind, WYAE - - - - 299 - - - - - - - - - - - 1 - - - 299 300 Total Wind - - - - 299 - - - - - - - - 617 145 - 1 - - - 299 1,062 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - - - - 226 155 - 381 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - 3.4 - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - - 14.9 - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - - - 68.4 - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - - 80.0 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - - 3.1 - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - - 4.8 - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - - 40.7 - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - - - 219.0 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 5 7 6 6 5 5 5 5 5 5 5 5 4 4 4 3 3 2 2 54 92 DSM, Class 2, UT 84 58 56 59 62 58 57 66 63 65 61 57 57 57 56 47 42 35 33 33 627 1,106 DSM, Class 2, WY 8 10 11 10 11 13 14 14 14 14 12 11 10 10 10 9 8 7 7 7 119 210 DSM, Class 2 Total 97 73 74 75 78 77 76 85 82 84 78 73 72 72 71 60 53 45 42 42 801 1,409 FOT Mona - SMR - - - - - - - - - - - 29 98 300 300 248 300 300 300 300 - 109 West Expansion Resources Utility Solar - PV - S-Oregon - - - - - - - - - - - - - - 110 - 295 - - - - 405 Utility Solar - PV - Yakima - - - - - - - - - - - - - - - - 344 55 73 - - 471 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - - 2.4 - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - - 1.2 - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - - - 3.7 - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - - 36.1 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - - 35.0 - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - - - 12.8 - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - - 13.0 - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - - 9.1 - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - - 4.8 - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - - - 118.1 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 6 5 4 3 3 2 2 87 130 DSM, Class 2 Total 57 53 52 46 41 37 33 33 29 27 26 24 23 23 22 22 20 19 19 19 409 626 Geothermal, Greenfield - West - - - - - - - - - - - - - 30 - - - - - - - 30 FOT COB - SMR - - - - - - - - - - - 400 400 400 400 400 400 400 400 400 - 180 FOT MidColumbia - SMR 399 400 400 400 378 400 360 341 400 400 400 400 400 400 400 400 400 400 400 400 388 394 FOT MidColumbia - SMR - 2 - 276 112 46 - 23 - - 64 - 65 375 375 375 375 375 375 375 375 375 52 198 FOT NOB - SMR 100 100 100 100 - 9 7 67 100 100 100 100 100 100 100 100 100 100 100 100 68 84 FOT MidColumbia - WTR 281 - 275 - 323 311 309 - - 300 - 292 - 400 46 - 395 400 62 384 180 189 FOT MidColumbia - WTR2 - 331 - 310 - - - 290 298 - 292 - 301 57 375 319 - 35 375 375 123 168 FOT NOB - WTR - - - - - - - - 53 54 8 10 15 100 100 97 100 100 100 100 11 42 Existing Plant Retirements/Conversions - - 5 - - - - - - (82) - (762) - (642) (78) - (358) - (82) - Annual Additions, Long Term Resources 154 126 126 122 418 114 109 117 112 111 105 97 95 1,080 350 284 716 122 364 228 Annual Additions, Short Term Resources 779 1,107 887 856 701 743 676 698 915 854 865 1,606 1,689 2,132 2,096 1,939 2,070 2,110 2,112 2,434 Total Annual Additions 933 1,234 1,013 978 1,119 857 784 815 1,027 965 970 1,703 1,784 3,212 2,447 2,224 2,786 2,232 2,476 2,662 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. REF PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 185 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - - - - - (387) - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- (280) - - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - - - - - - - - - - - - - - - - - - - - - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 CCCT - Utah-S - J 1x1 - - - - - - - - - - - - - - - - - - - 477 - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - 477 - 953 SCCT Frame UTN - - - - - - - - - - - - - 200 - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - 35 - - 165 86 - - - - 285 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 300 - - - - - - - 35 - - 165 86 - - - 300 585 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - - 321 41 291 46 - 699 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - 40.7 - - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 205.0 9.2 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 6 6 5 5 5 5 4 4 3 3 3 3 57 96 DSM, Class 2, UT 84 58 62 59 62 68 66 66 68 65 65 61 57 57 58 49 44 37 34 35 656 1,152 DSM, Class 2, WY 8 10 11 10 13 13 14 15 14 14 12 13 11 11 11 9 8 7 7 7 122 218 DSM, Class 2 Total 97 74 79 75 81 86 85 86 89 84 82 78 73 73 73 62 55 47 43 44 835 1,465 FOT Mona - SMR - - - - - - - - - 27 27 300 300 108 195 300 300 300 300 300 3 123 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (354) - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - - - - (359) - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - S-Oregon - - - - - - - - - - - 15 - - - - - - - - - 15 Utility Solar - PV - Yakima - - - - - - - - - - - - - - - - 217 7 - - - 224 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - 11.4 24.7 - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - 13.0 - - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 93.5 24.7 - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 22 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 9 9 8 10 9 9 9 8 8 7 7 6 6 5 4 3 3 2 2 89 134 DSM, Class 2 Total 57 54 52 46 42 37 34 33 29 27 27 25 24 23 22 22 20 19 19 18 412 630 Geothermal, Greenfield - West - - - - - - - - - - - - 30 - - - - - - - - 30 FOT COB - SMR - - - - - - - - 279 188 249 400 400 400 400 400 400 400 400 364 47 214 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 275 375 310 56 167 95 135 375 375 375 375 375 375 375 375 375 375 375 375 216 296 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 - - 310 - 289 297 - - 400 91 249 290 352 - 16 394 400 178 199 FOT MidColumbia - WTR2 - - - 310 322 - 308 - - 299 290 21 375 - - - 351 375 - 251 124 145 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 86 97 100 100 100 100 100 11 50 Existing Plant Retirements/Conversions - (280) - - - - - - (387) (82) - (762) - (357) (78) - (712) - (82) (359) Annual Additions, Long Term Resources 154 128 131 122 423 123 118 119 118 112 109 417 195 737 98 252 1,178 117 356 597 Annual Additions, Short Term Resources 779 1,106 1,150 1,119 877 976 903 924 1,503 1,442 1,449 2,096 2,141 1,717 1,857 2,027 2,026 2,066 2,069 2,290 Total Annual Additions 933 1,234 1,281 1,241 1,300 1,100 1,021 1,042 1,621 1,554 1,558 2,513 2,336 2,454 1,955 2,278 3,204 2,184 2,425 2,887 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. RH-1 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 186 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - (82) - - - - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Hunter 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - (418) - - - - - (418) Hunter 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - (269) - - - - - (269) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - - - - - - (330) - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_CO - Gas RePower - - - - - - 82 - - - - - - - - - - - (82) - 82 - Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 CCCT - Utah-S - G 1x1 - - - - - - - - - - - - - - - - 389 - - - - 389 CCCT - Utah-S - J 1x1 - - - - - - - - - - - - - - - 477 - - - - - 477 Total CCCT - - - - - - - - - - - - - 477 - 477 389 - - - - 1,342 SCCT Frame DJ - - - - - - - - - - - - - - - 200 - - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - - - 200 - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - 85 - - - - - - 85 Wind, GO - - - - - - - - - - - - - - - - - - - 593 - 593 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 300 - - - - - - - - - 85 - - - - 593 300 979 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - - 383 48 315 54 - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - 3.4 - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - 14.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - 75.3 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - 3.1 - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - 4.8 - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 68.4 140.6 10.0 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 6 6 5 5 5 4 4 4 3 3 3 3 57 96 DSM, Class 2, UT 84 58 62 59 62 64 66 66 68 65 65 61 57 57 58 47 44 37 34 35 653 1,146 DSM, Class 2, WY 8 10 11 10 13 13 14 15 14 14 12 13 10 10 11 8 8 7 7 7 122 215 DSM, Class 2 Total 97 74 79 75 81 83 85 86 89 84 82 78 72 72 73 59 55 47 43 44 832 1,457 FOT Mona - SMR - - - - - - - - - - - 300 71 272 300 279 300 300 300 300 - 121 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - (354) - - - - - - - - - - - (354) (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (359) - - - - - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - 436 - - - - - - - - 436 Total CCCT - - - - - - - - - - - - 436 - - - - - - - - 436 Utility Solar - PV - S-Oregon - - - - - - - - - - - - - - 54 - - - - - - 54 Utility Solar - PV - Yakima - - - - - - - - - - - - - - - - 244 - - - - 244 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - 2.4 - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - 1.2 - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - - 3.7 - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 11.4 17.7 3.3 - - - - - - 32.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - 35.0 - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - - 12.8 - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - 9.1 - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - 4.8 - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - - 93.5 17.7 3.3 - - - - - - 114.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 20 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 5 5 4 3 3 2 2 87 131 DSM, Class 2 Total 57 53 52 46 41 37 34 33 29 27 26 25 23 23 22 21 20 19 19 18 410 625 FOT COB - SMR - - - - - - - - 347 283 344 400 400 400 400 400 400 400 400 367 63 227 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 276 107 41 153 266 194 234 375 375 375 375 375 375 375 375 375 375 375 375 202 288 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 - 275 - - - - 290 298 - - - 300 375 368 - - 317 319 400 114 161 FOT MidColumbia - WTR2 - 331 - 310 323 311 309 - - 300 292 291 - - - 306 276 - - 210 188 163 FOT NOB - WTR - - - - - - - - 53 54 8 10 - 100 100 45 100 100 100 100 11 38 Existing Plant Retirements/Conversions - - 5 - (387) - - - (354) - - (432) (359) (642) (78) (687) (688) - (164) - Annual Additions, Long Term Resources 154 128 131 122 421 120 118 119 118 111 109 171 765 599 237 960 1,094 117 381 721 Annual Additions, Short Term Resources 779 1,106 882 851 975 1,077 1,003 1,024 1,572 1,512 1,520 1,876 1,647 2,022 2,043 1,904 1,951 1,992 1,994 2,252 Total Annual Additions 933 1,234 1,013 973 1,397 1,196 1,122 1,143 1,690 1,623 1,628 2,047 2,412 2,621 2,280 2,864 3,046 2,108 2,375 2,974 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. RH-2 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 187 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - - - - - (387) - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- (280) - - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 Total CCCT - - - - - - - - - - - - - 477 - - - - - - - 477 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame ID - - - - - - - - - - - - - - - - - - - 200 - 200 SCCT Frame UTN - - - - - - - - - - - - 200 - - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - - - 85 - - - - 85 Wind, GO - - - - - - - - - - - - - - - - - - 800 - - 800 Wind, WYAE - - - - 235 - - - - - - - - - - - 65 - - - 235 300 Total Wind - - - - 235 - - - - - - - - - - - 151 - 800 - 235 1,185 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - - 712 33 60 - - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - 3.4 - - - - - - - - - 3.4 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - - - 1.9 - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 - - - 7.3 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - - - 4.8 - 3.7 - - - 83.7 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - - - 3.1 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1, WY-Curtail - - - - - - - - - - - 40.7 - - - - 3.1 - - - - 43.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 208.4 - - - 14.0 3.1 3.7 3.1 - - 232.2 DSM, Class 2, ID 5 7 7 6 6 6 6 6 6 6 5 5 5 5 5 4 4 3 3 2 58 98 DSM, Class 2, UT 84 62 62 59 70 68 66 67 72 69 65 65 57 60 59 51 45 40 48 24 679 1,192 DSM, Class 2, WY 8 10 11 12 13 13 15 15 14 14 13 13 12 11 11 10 9 8 9 5 125 227 DSM, Class 2 Total 97 78 79 77 89 87 86 88 92 88 83 83 74 76 75 65 58 51 60 31 862 1,517 Battery Storage - East - - - - - - - - - - - - - - - - - 8.0 - - - 8 FOT Mona - SMR - - - - - - - - - 27 27 300 127 91 188 300 300 300 300 272 3 112 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - 436 - - - - - - - - 436 Total CCCT - - - - - - - - - - - - 436 - - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - - - - - - 286 13 19 - - 318 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - 36.1 - - - 3.3 - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - 3.8 - - - 9.2 - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 108.9 - - - 12.6 - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 9 9 8 9 9 9 9 8 8 7 6 5 5 5 4 3 3 2 2 88 130 DSM, Class 2 Total 57 54 52 46 41 37 34 33 29 27 26 25 23 22 22 21 20 19 19 18 410 625 Geothermal, Greenfield - West - - - - - - - - - - - 30 - - - - - - - - - 30 FOT COB - SMR - - 17 - - - - - 311 221 286 400 400 400 400 400 400 400 400 360 55 220 FOT MidColumbia - SMR 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 4 284 375 330 83 196 126 166 375 375 375 375 375 375 375 375 375 375 375 375 231 303 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 - 322 311 - 290 298 - - 42 - - 292 306 292 - - 400 211 172 FOT MidColumbia - WTR2 - - - 310 - - 309 - - 301 292 375 301 251 - - - 327 330 152 92 147 FOT NOB - WTR - - - - - - - - 54 55 10 100 9 - - 76 100 100 100 100 11 35 Existing Plant Retirements/Conversions - (280) - - - - - - (387) (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 132 131 124 365 124 120 121 122 115 110 455 733 575 96 113 1,429 128 960 249 Annual Additions, Short Term Resources 784 1,115 1,167 1,139 906 1,007 934 956 1,538 1,479 1,490 2,092 1,711 1,617 1,756 1,957 1,967 2,002 2,005 2,160 Total Annual Additions 938 1,247 1,299 1,263 1,271 1,131 1,054 1,077 1,659 1,594 1,599 2,547 2,443 2,192 1,852 2,070 3,396 2,130 2,966 2,409 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. RH-3 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 188 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - - - - - (387) - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 SCCT Frame UTN - - - - - - - - - - - - - 200 - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - - 285 - - - - - 285 Wind, GO - - - - - - - - - - - - - - - - - - - 364 - 364 Wind, WYAE - - - - 288 - - - - - - - - - - 12 - - - - 288 300 Total Wind - - - - 288 - - - - - - - - - - 297 - - - 364 288 950 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - - 347 41 291 121 - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - 3.4 - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - 14.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 61.9 6.4 - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - - 80.0 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - 3.1 - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - 4.8 - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - - 40.7 - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 61.9 31.0 126.0 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 4 4 3 3 3 3 56 95 DSM, Class 2, UT 84 58 62 59 62 58 66 66 68 65 63 61 57 57 58 49 44 37 34 35 647 1,141 DSM, Class 2, WY 8 10 11 10 13 13 14 15 14 14 12 11 11 11 11 9 8 7 7 7 122 216 DSM, Class 2 Total 97 74 79 75 81 77 85 86 88 84 80 77 73 73 73 62 55 47 43 44 826 1,453 FOT Mona - SMR - - - - - - - - - - 24 298 300 140 228 300 300 300 300 300 - 124 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (354) - - - - (354) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - - - - - 25 213 7 - - - 246 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - 2.4 - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - 1.2 - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - - 3.7 - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - - 36.1 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - 7.7 27.3 - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - - 12.8 - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - - 13.0 - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - - 9.1 - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - 4.8 - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - - 32.7 85.4 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 6 5 4 3 3 2 2 87 131 DSM, Class 2 Total 57 53 52 46 41 37 34 33 29 27 26 25 24 23 22 22 20 19 19 18 410 626 Geothermal, Greenfield - West - - - - - - - - - - - - - 30 - - - - - - - 30 FOT COB - SMR - - - - - - - - 25 - - 400 400 400 400 400 400 400 400 364 2 179 FOT MidColumbia - SMR 399 400 400 400 378 400 359 340 400 400 400 400 400 400 400 400 400 400 400 400 388 394 FOT MidColumbia - SMR - 2 - 276 107 41 - 23 - - 375 336 375 375 375 375 375 375 375 375 375 375 116 245 FOT NOB - SMR 100 100 100 100 - - - 40 100 100 100 100 100 100 100 100 100 100 100 100 64 82 FOT MidColumbia - WTR 281 - 275 - - 311 - 290 - - - 291 300 264 - 349 - 388 15 400 116 158 FOT MidColumbia - WTR2 - 331 - 310 323 - 309 - 298 300 292 - - - 316 - 348 - 375 277 187 174 FOT NOB - WTR - - - - - - - - 53 54 8 10 54 100 100 100 100 100 100 100 11 44 Existing Plant Retirements/Conversions - - 5 - - - - - (387) (82) - (762) - (642) (78) - (712) - (82) - Annual Additions, Long Term Resources 154 128 131 122 410 114 118 119 117 111 107 163 160 973 98 409 1,115 117 356 560 Annual Additions, Short Term Resources 779 1,106 882 851 701 734 668 671 1,250 1,190 1,199 1,875 1,929 1,779 1,918 2,024 2,023 2,063 2,065 2,316 Total Annual Additions 933 1,234 1,013 973 1,110 848 787 789 1,368 1,301 1,306 2,038 2,090 2,752 2,016 2,433 3,137 2,180 2,422 2,876 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. RH-4 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 189 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 Total CCCT - - - - - - - - - - - - - 477 - - - - - - - 477 IC Aero UN - - - - - - - - - - - - - - - - - - 182 - - 182 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - - - - 200 - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - - 85 - - - - - 85 Wind, GO - - - - - - - - - - - - - - - - - - - 485 - 485 Wind, WYAE - - - - 229 - - - - - - - - - - 51 20 - - - 229 300 Total Wind - - - - 229 - - - - - - - - - - 137 20 - - 485 229 871 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - 17 654 44 - 85 - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - 14.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 65.2 3.2 - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - 75.3 - - 4.8 - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - 3.1 - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - 4.8 - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 21.7 - - 19.0 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 65.2 130.0 - - 27.1 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 4 4 4 3 3 2 3 56 94 DSM, Class 2, UT 84 58 62 59 62 58 66 66 68 65 63 61 57 57 56 49 44 37 33 35 647 1,138 DSM, Class 2, WY 8 10 11 10 13 13 14 15 14 14 12 11 11 9 10 9 8 7 6 7 122 213 DSM, Class 2 Total 97 74 79 75 81 77 85 86 88 84 80 77 73 71 71 62 55 47 41 44 826 1,446 FOT Mona - SMR - - - - - - - - - - - 300 299 173 260 300 300 300 300 300 - 127 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 SCCT Frame SO - - - - - - - - - - - - 216 - - - - - - - - 216 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - 2.4 - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - 1.2 - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - - 3.7 - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 4.0 - - - 7.4 - - - - 11.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - 35.0 - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - - 12.8 - - - - - - - - 12.8 DSM, Class 1, WA-Curtail - - - - - - - - - - - - 9.1 - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - 4.8 - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - - 73.0 - - - 7.4 - - - - 80.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 13 19 DSM, Class 2, OR 46 40 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 306 470 DSM, Class 2, WA 10 8 9 8 9 8 9 9 8 8 7 6 6 5 4 4 3 3 2 2 85 126 DSM, Class 2 Total 57 50 52 46 41 35 33 33 29 27 26 24 23 22 21 21 19 18 18 18 404 616 FOT COB - SMR - - - - - - - - 30 - 29 400 400 357 362 398 398 400 400 366 3 177 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 277 108 43 165 282 210 250 375 341 375 375 375 375 375 375 375 375 375 375 205 290 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 - 275 - 323 - - - - 301 - 293 8 - - - - - 314 224 118 101 FOT MidColumbia - WTR2 - 331 - 310 - 312 310 291 299 - 293 - 375 253 294 308 310 320 - 375 185 219 FOT NOB - WTR - - - - - - - - 54 56 10 12 100 1 13 59 68 100 95 100 11 33 Existing Plant Retirements/Conversions - - 5 - (387) - - - - (82) - (762) (354) (642) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 124 131 122 350 113 118 119 117 111 106 166 515 1,005 92 263 1,159 113 244 644 Annual Additions, Short Term Resources 779 1,108 884 853 988 1,094 1,021 1,042 1,258 1,198 1,207 1,880 2,057 1,658 1,804 1,941 1,951 1,995 1,984 2,239 Total Annual Additions 933 1,232 1,015 974 1,338 1,206 1,139 1,160 1,375 1,309 1,313 2,046 2,572 2,664 1,896 2,204 3,109 2,108 2,228 2,883 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. RH-5 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 190 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - - - - - (387) - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- (280) - - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 Total CCCT - - - - - - - - - - - - - 477 - - - - - - - 477 SCCT Frame UTN - - - - - - - - - - - - - - 200 - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - - - 285 - - - - 285 Wind, GO - - - - - - - - - - - - - - - - - - - 526 - 526 Wind, WYAE - - - - 179 - - - - - - - - - - - 121 - - - 179 300 Total Wind - - - - 179 - - - - - - - - - - - 407 - - 526 179 1,111 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - - 391 41 291 78 - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - - - - 3.4 - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - - - - 4.8 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 164.3 46.6 - - 3.4 11.2 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 4 4 4 3 3 3 3 56 95 DSM, Class 2, UT 84 58 62 59 62 58 66 66 63 65 62 61 57 56 56 49 44 37 34 35 642 1,132 DSM, Class 2, WY 8 10 11 10 13 13 14 14 14 14 12 11 11 9 10 9 8 7 7 7 121 213 DSM, Class 2 Total 97 74 79 75 81 77 85 85 82 84 80 77 73 70 71 62 55 47 44 45 819 1,441 FOT Mona - SMR - - - - - - - - 264 200 264 300 300 261 171 300 300 300 300 300 46 163 West Existing Plant Retirements/Conversions JimBridger 2 (Coal Early Retirement/Conversions)- - - - - (356) - - - - - - - - - - - - - - (356) (356) Expansion Resources CCCT - SOregonCal - J 1x1 - - - - - - - - - - - 509 - - - - - - - - - 509 Total CCCT - - - - - - - - - - - 509 - - - - - - - - - 509 Utility Solar - PV - Yakima - - - - - - - - - - - - - - - - 110 7 - - - 117 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 7.4 - - - 32.0 - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 69.1 20.4 - - - 32.0 - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 20 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 5 5 4 3 3 2 2 87 130 DSM, Class 2 Total 57 53 52 46 41 37 33 33 29 27 26 25 23 22 22 21 20 19 19 18 409 624 Geothermal, Greenfield - West - - - - - - - - - - - - - - - - 30 - - - - 30 FOT COB - SMR - - - - - 173 101 142 400 400 400 400 400 400 400 400 400 400 400 364 122 259 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 276 375 310 90 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 293 334 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 - 323 311 309 290 298 - - 321 399 - - 319 - 9 11 298 242 189 FOT MidColumbia - WTR2 - - - 310 - - - - - 300 292 - - 327 341 - 343 375 375 375 61 152 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 - 55 100 100 100 100 11 43 Existing Plant Retirements/Conversions - (280) - - - (356) - - (387) (82) - (762) - (357) (78) - (358) - (82) - Annual Additions, Long Term Resources 154 128 131 122 300 114 118 118 112 111 106 843 163 569 292 87 1,055 117 356 678 Annual Additions, Short Term Resources 779 1,106 1,150 1,120 913 1,359 1,286 1,307 1,890 1,830 1,839 1,996 2,074 1,963 1,787 1,949 2,018 2,059 2,061 2,312 Total Annual Additions 933 1,234 1,281 1,242 1,213 1,473 1,404 1,425 2,002 1,941 1,945 2,839 2,237 2,532 2,079 2,036 3,073 2,176 2,418 2,990 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. RH-6 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 191 Table K.8 – Core Cases, Detailed Capacity Expansion Portfolio Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 Total CCCT - - - - - - - - - - - - - 477 - - - - - - - 477 IC Aero UN - - - - - - - - - - - - - - - - - - 182 - - 182 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - - - - 200 - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - - 85 - - - - - 85 Wind, GO - - - - - - - - - - - - - - - - - - - 485 - 485 Wind, WYAE - - - - 229 - - - - - - - - - - 51 20 - - - 229 300 Total Wind - - - - 229 - - - - - - - - - - 137 20 - - 485 229 871 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - 17 654 44 - 85 - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - 14.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 65.2 3.2 - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - 75.3 - - 4.8 - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - 3.1 - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - 4.8 - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 21.7 - - 19.0 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 65.2 130.0 - - 27.1 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 4 4 4 3 3 2 3 56 94 DSM, Class 2, UT 84 58 62 59 62 58 66 66 68 65 63 61 57 57 56 49 44 37 33 35 647 1,138 DSM, Class 2, WY 8 10 11 10 13 13 14 15 14 14 12 11 11 9 10 9 8 7 6 7 122 213 DSM, Class 2 Total 97 74 79 75 81 77 85 86 88 84 80 77 73 71 71 62 55 47 41 44 826 1,446 FOT Mona - SMR - - - - - - - - - - - 300 299 173 260 300 300 300 300 300 - 127 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 SCCT Frame SO - - - - - - - - - - - - 216 - - - - - - - - 216 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - 2.4 - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - 1.2 - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - - 3.7 - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 4.0 - - - 7.4 - - - - 11.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - 35.0 - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - - 12.8 - - - - - - - - 12.8 DSM, Class 1, WA-Curtail - - - - - - - - - - - - 9.1 - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - 4.8 - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - - 73.0 - - - 7.4 - - - - 80.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 13 19 DSM, Class 2, OR 46 40 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 306 470 DSM, Class 2, WA 10 8 9 8 9 8 9 9 8 8 7 6 6 5 4 4 3 3 2 2 85 126 DSM, Class 2 Total 57 50 52 46 41 35 33 33 29 27 26 24 23 22 21 21 19 18 18 18 404 616 FOT COB - SMR - - - - - - - - 30 - 29 400 400 357 362 398 398 400 400 366 3 177 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 277 108 43 165 282 210 250 375 341 375 375 375 375 375 375 375 375 375 375 205 290 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 - 275 - 323 - - - - 301 - 293 8 - - - - - 314 224 118 101 FOT MidColumbia - WTR2 - 331 - 310 - 312 310 291 299 - 293 - 375 253 294 308 310 320 - 375 185 219 FOT NOB - WTR - - - - - - - - 54 56 10 12 100 1 13 59 68 100 95 100 11 33 Existing Plant Retirements/Conversions - - 5 - (387) - - - - (82) - (762) (354) (642) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 124 131 122 350 113 118 119 117 111 106 166 515 1,005 92 263 1,159 113 244 644 Annual Additions, Short Term Resources 779 1,108 884 853 988 1,094 1,021 1,042 1,258 1,198 1,207 1,880 2,057 1,658 1,804 1,941 1,951 1,995 1,984 2,239 Total Annual Additions 933 1,232 1,015 974 1,338 1,206 1,139 1,160 1,375 1,309 1,313 2,046 2,572 2,664 1,896 2,204 3,109 2,108 2,228 2,883 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. OP-1 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 192 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 SCCT Frame DJ - - - - - - - - - - - - - - - 200 - - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - 200 - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - 85 - - - - - - - 85 Wind, GO - - - - 150 - - - - - - - - - - - - - 407 393 150 950 Wind, UT - - - - - - - - - - - - - - - - - - - 460 - 460 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 450 - - - - - - - - 85 - - - - 407 853 450 1,796 Utility Solar - PV - Utah-S - - - - - - - - - - - - - 58 151 - 380 41 171 5 - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - 3.4 - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 - 3.9 - - 3.4 - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - 40.7 - - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 205.0 - 14.0 - - 6.5 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 6 6 6 6 5 5 5 5 5 4 3 3 3 3 57 97 DSM, Class 2, UT 84 62 62 59 62 68 66 71 68 69 65 61 57 60 59 47 44 37 34 35 670 1,168 DSM, Class 2, WY 8 10 11 12 13 13 14 15 14 14 12 13 12 11 11 9 8 7 7 7 124 221 DSM, Class 2 Total 97 78 79 77 81 87 85 91 89 88 82 79 74 76 74 60 55 47 44 44 851 1,486 FOT Mona - SMR - - - - - - - - - 27 27 299 236 300 300 252 300 300 300 300 3 132 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - SOregonCal - J 1x1 - - - - - - - - - - - - 509 - - - - - - - - 509 Total CCCT - - - - - - - - - - - - 509 - - - - - - - - 509 Utility Solar - PV - Yakima - - - - - - - - - - - - - 76 3 - 31 7 13 - - 130 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - 4.0 - 32.1 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - - 13.0 - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 73.0 - 45.1 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 20 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 5 5 4 3 3 2 2 87 130 DSM, Class 2 Total 57 53 52 46 41 37 34 33 29 27 26 25 23 23 22 21 20 19 19 18 410 625 Geothermal, Greenfield - West - - - - - - - - - - - - - - - - 30 - - - - 30 FOT COB - SMR - - - - 19 130 58 95 249 156 217 400 400 400 400 400 400 400 400 357 71 224 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 8 372 305 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 294 334 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 310 - 311 - 290 298 - - 27 317 400 17 - - 378 380 286 210 195 FOT MidColumbia - WTR2 - - - - 323 - 309 - - 300 292 375 - 27 375 287 337 - - 375 93 150 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 132 131 124 572 123 119 124 118 115 109 382 605 577 253 280 998 117 657 933 Annual Additions, Short Term Resources 779 839 1,148 1,115 1,217 1,316 1,242 1,260 1,475 1,412 1,420 2,075 1,928 2,102 2,067 1,914 2,012 2,053 2,055 2,293 Total Annual Additions 933 971 1,279 1,239 1,789 1,440 1,361 1,385 1,593 1,527 1,528 2,457 2,533 2,679 2,320 2,195 3,010 2,170 2,712 3,226 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. OP-NT3 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 193 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 CCCT - Utah-S - J 1x1 - - - - - - - - - - - - - - - - - - - 477 - 477 Total CCCT - - - - - - - - - - - - - 477 - - - - - 477 - 953 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - - - - 200 - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - - - 85 - - - - 85 Wind, GO - - - - 128 - - - - - - - - - - - - - 516 - 128 644 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 428 - - - - - - - - - - - 85 - 516 - 428 1,030 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - - 617 40 142 - - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - - - 3.4 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - - - 83.7 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - - - 3.1 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1, WY-Curtail - - - - - - - - - - - 40.7 - - - - 3.1 - - - - 43.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 205.0 9.2 4.8 - 3.4 3.1 3.7 3.1 - - 232.2 DSM, Class 2, ID 5 7 7 6 6 5 6 6 6 6 5 5 5 5 4 4 3 3 3 2 57 95 DSM, Class 2, UT 84 58 62 59 62 68 66 66 68 67 65 61 57 57 58 49 44 37 34 24 658 1,144 DSM, Class 2, WY 8 10 11 10 13 13 14 15 14 14 12 13 10 10 11 9 8 7 7 5 122 214 DSM, Class 2 Total 97 74 79 75 81 87 85 86 89 86 82 78 72 72 73 62 55 47 44 31 838 1,453 FOT Mona - SMR - - - - - - - - - 27 27 300 282 236 300 300 300 300 300 29 3 120 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - 436 - - - - - - - - 436 Total CCCT - - - - - - - - - - - - 436 - - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - - - - 53 247 37 8 13 - - 357 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - 11.4 - - - 3.3 - - - - - 14.7 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 80.5 13.0 - - 3.3 - - - - - 96.8 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 10 9 9 9 8 8 7 7 6 5 5 4 3 3 2 2 88 132 DSM, Class 2 Total 57 53 52 46 42 37 33 33 29 27 27 25 23 23 22 22 20 19 19 18 410 627 FOT COB - SMR - - - - 24 135 64 103 258 165 227 400 400 400 400 400 400 400 400 342 75 226 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 11 375 307 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 294 335 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 273 307 - 308 - 287 295 - - 35 397 - 348 312 314 - 357 - 208 192 FOT MidColumbia - WTR2 - - - - 319 - 306 - - 297 289 375 - 323 - - - 355 - 308 92 129 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 550 123 118 119 118 113 109 388 553 576 148 337 1,217 117 737 526 Annual Additions, Short Term Resources 779 842 1,148 1,115 1,219 1,318 1,245 1,266 1,480 1,418 1,425 2,085 2,053 1,934 2,023 1,987 1,989 2,030 2,032 1,654 Total Annual Additions 933 970 1,279 1,236 1,769 1,441 1,363 1,384 1,598 1,532 1,535 2,473 2,607 2,510 2,171 2,325 3,206 2,147 2,770 2,180 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. OP-REP PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 194 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 IC Aero UN - - - - - - - - - - - - - - - - - - - 182 - 182 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - 200 - - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - 72 - 9 5 - - - 85 Wind, WYAE - - - - 1,200 - - - - - - - - - - - - - - - 1,200 1,200 Total Wind - - - - 1,200 - - - - - - - - - 72 - 9 5 - - 1,200 1,285 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - 59 167 208 40 279 - - 752 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 34.8 40.5 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 123.8 90.5 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 4 4 3 3 3 3 56 95 DSM, Class 2, UT 84 58 62 59 62 58 66 66 63 65 65 61 57 57 59 49 44 37 34 35 642 1,139 DSM, Class 2, WY 8 10 11 10 11 13 14 14 14 14 12 11 11 11 11 9 8 7 7 7 119 214 DSM, Class 2 Total 97 74 79 75 78 77 85 85 82 84 82 77 73 73 74 62 55 47 44 44 817 1,448 FOT Mona - SMR - - - - - - - - - 27 27 293 300 291 300 300 300 300 300 263 3 135 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - - 82 - 64 70 16 8 13 - - 253 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 36.1 - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 69.1 49.1 - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 10 9 9 9 8 8 7 7 6 5 5 4 3 3 2 2 88 132 DSM, Class 2 Total 57 53 52 46 42 37 33 33 29 27 27 25 23 23 22 21 20 19 19 18 410 627 Geothermal, Greenfield - West - - - - - - - - - - - - 30 - - - - - - - - 30 FOT COB - SMR - - - - - 27 - - 154 63 124 400 400 400 400 400 400 400 400 357 24 196 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 11 375 307 286 375 331 372 375 375 375 375 375 375 375 375 375 375 375 375 281 328 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 273 307 - - - 287 295 - - - 400 41 390 351 - 377 4 236 177 179 FOT MidColumbia - WTR2 - - - - 319 308 306 - - 297 289 305 51 375 - - 337 - 375 375 123 167 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 1,321 114 118 118 112 111 109 295 548 536 296 323 986 121 358 256 Annual Additions, Short Term Resources 779 842 1,148 1,115 1,105 1,210 1,137 1,159 1,376 1,316 1,323 1,973 2,126 2,081 2,065 2,026 2,012 2,052 2,054 2,206 Total Annual Additions 933 970 1,279 1,236 2,426 1,324 1,255 1,276 1,488 1,427 1,432 2,267 2,674 2,618 2,361 2,349 2,998 2,173 2,412 2,462 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. OP-GW4 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 195 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 IC Aero UN - - - - 182 - - - - - - - - - - - - - - - 182 182 SCCT Frame UTN - - - - - - - - - - - - - 200 - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - 52 234 - - - - - - 285 Wind, GO - - - - 150 - - - - - - - - - - - - - 401 399 150 950 Wind, UT - - - - - - - - - - - - - - - - - - - 455 - 455 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 450 - - - - - - - - 52 234 - - - 401 853 450 1,990 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - 52 534 41 173 5 - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - 3.4 - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - 14.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - - 68.4 - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - 15.0 65.0 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - 3.1 - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - - 4.8 - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - - 40.7 - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - - 103.2 115.7 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 5 4 3 3 3 3 56 96 DSM, Class 2, UT 84 58 62 59 62 58 66 66 68 65 65 61 57 60 59 49 44 37 34 35 647 1,148 DSM, Class 2, WY 8 10 11 10 13 13 14 15 14 14 12 13 12 11 11 9 8 7 7 7 122 218 DSM, Class 2 Total 97 74 79 75 81 77 85 86 88 84 82 78 74 76 74 62 55 47 44 44 826 1,462 Battery Storage - East - - - - 3.0 - - - - - - - - - - - - - - - 3 3 FOT Mona - SMR - - - - - - - - - - - 67 296 300 300 300 300 300 300 300 - 123 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources IC Aero SO - - - - 393 - - - - - - - - - - - - - - - 393 393 Utility Solar - PV - S-Oregon - - - - - - - - - - - - - - 84 163 - - - - - 247 Utility Solar - PV - Yakima - - - - - - - - - - - - - - - - 16 8 13 - - 36 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - 2.4 - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - - 1.2 - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - - 3.7 - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 24.7 11.4 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - 27.3 7.7 - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - - 3.8 9.1 - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - - 13.0 - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - 4.7 4.4 - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - - 4.8 - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - - 66.5 51.6 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 22 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 6 5 4 3 3 2 2 87 131 DSM, Class 2 Total 57 53 52 46 41 37 34 33 29 27 26 25 24 23 22 22 20 19 19 18 410 627 Battery Storage - West - - - - 1 - - - - - - - - - - - - - - - 1 1 Geothermal, Greenfield - West - - - - - - - - - - - - - 30 - - - - - - - 30 FOT COB - SMR - - - - - - - - - - - 400 400 400 400 400 400 400 400 357 - 178 FOT MidColumbia - SMR 399 400 400 400 378 400 359 355 400 400 400 400 400 400 400 400 400 400 400 400 389 395 FOT MidColumbia - SMR - 2 - 11 375 310 - 23 - - 109 45 106 375 375 375 375 375 375 375 375 375 87 218 FOT NOB - SMR 100 100 100 100 - 63 56 100 100 100 100 100 100 100 100 100 100 100 100 100 82 91 FOT MidColumbia - WTR 281 331 275 310 - - 309 290 298 300 - 291 300 400 5 - 339 5 382 400 239 226 FOT MidColumbia - WTR2 - - - - 323 311 - - - - 292 - - 15 375 340 - 375 - 263 63 115 FOT NOB - WTR - - - - - - - - - - - - 57 100 100 100 100 100 100 100 - 38 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 1,150 114 118 119 117 112 109 103 267 548 417 303 1,105 117 653 933 Annual Additions, Short Term Resources 779 842 1,150 1,120 701 798 724 745 907 845 898 1,633 1,928 2,090 2,055 2,015 2,014 2,055 2,057 2,295 Total Annual Additions 933 970 1,281 1,242 1,851 912 842 863 1,024 957 1,007 1,735 2,195 2,637 2,472 2,318 3,119 2,172 2,710 3,228 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. FR-1 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 196 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 IC Aero UN - - - - 182 - - - - - - - - - - - - - - - 182 182 SCCT Aero UN - - - - 121 - - - - - - - - - - - - - - - 121 121 SCCT Frame UTN - - - - - - - - - - - - - - 200 - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - 39 - - 247 - - - - 285 Wind, GO - - - - 46 - - - - - - - - - - - - - - 800 46 846 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 346 - - - - - - - - 39 - - 247 - - 800 346 1,432 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - - 466 41 279 19 - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - 3.4 - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - - - - 1.9 - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - - 14.9 - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - - - 68.4 - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - - 80.0 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - - 3.1 - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - - 4.8 - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - - 40.7 - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - - - 217.1 - 3.4 5.0 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 5 7 6 6 5 5 5 5 5 5 5 5 5 4 4 3 3 3 3 54 93 DSM, Class 2, UT 84 58 56 59 62 58 57 66 63 65 61 57 57 57 56 47 44 37 34 35 627 1,112 DSM, Class 2, WY 8 10 11 10 11 13 14 14 14 14 12 11 10 10 10 9 8 7 7 7 119 211 DSM, Class 2 Total 97 73 74 75 78 77 76 85 82 84 78 73 72 72 71 60 55 47 43 44 801 1,415 Battery Storage - East - - - - 7.0 - - - - - - - - - - - - - - - 7 7 FOT Mona - SMR - - - - - - - - - - - - 140 300 204 300 300 300 300 300 - 107 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources IC Aero PO - - - - 221 - - - - - - - - - - - - - - - 221 221 IC Aero SO - - - - 196 - - - - - - - - - - - - - - - 196 196 IC Aero WV - - - - 208 - - - - - - - - - - - - - - - 208 208 IC Aero WW - - - - 221 - - - - - - - - - - - - - - - 221 221 DSM, Class 2, CA 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 12 18 DSM, Class 2, OR 46 40 39 34 29 26 23 23 20 18 18 17 16 16 16 17 15 15 16 16 297 461 DSM, Class 2, WA 10 7 7 8 8 8 7 7 7 7 6 6 5 5 4 3 3 2 2 2 76 114 DSM, Class 2 Total 57 48 47 43 38 35 32 31 27 27 25 23 22 22 21 21 19 18 18 18 384 592 Battery Storage - West - - - - 2 - - - - - - - - - - - - - - - 2 2 FOT COB - SMR - - 11 - - - - - - - - - 251 261 270 303 311 316 322 279 1 116 FOT MidColumbia - SMR 399 400 400 400 138 117 116 97 97 97 97 400 400 400 400 400 400 400 400 400 226 298 FOT MidColumbia - SMR - 2 - 15 375 322 - - - - - - - 363 375 375 372 375 375 375 375 375 71 204 FOT NOB - SMR 100 100 100 100 - - - - 25 - 26 100 100 100 100 100 100 100 100 100 43 68 FOT MidColumbia - WTR 281 332 278 313 108 98 97 79 70 68 83 83 92 124 - - 100 127 - 400 172 137 FOT MidColumbia - WTR2 - - - - - - - - - - - - - - 84 98 - - 136 16 - 17 FOT NOB - WTR - - - - - - - - - - - - - 100 - 74 82 100 100 100 - 28 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 121 120 118 1,620 113 107 115 110 110 104 96 94 349 292 83 1,268 109 344 894 Annual Additions, Short Term Resources 779 847 1,164 1,135 246 215 213 176 192 165 206 945 1,358 1,660 1,431 1,650 1,669 1,718 1,733 1,971 Total Annual Additions 933 968 1,284 1,253 1,867 327 320 292 302 275 310 1,042 1,452 2,010 1,722 1,734 2,936 1,826 2,078 2,864 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. FR-2 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 197 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - 477 - - - - - - - - 477 Total CCCT - - - - - - - - - - - - 477 - - - - - - - - 477 IC Aero UN - - - - - - - - - - - - - - - - 182 - - - - 182 SCCT Frame UTN - - - - - - - - - - - - - - - - 200 - - - - 200 Wind, Djohnston - - - - - - - - - - - - - 85 200 - - - - - - 285 Wind, GO - - - - 150 - - - - - - - - - - - - - 407 393 150 950 Wind, UT - - - - - - - - - - - - - - - - - - - 460 - 460 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 450 - - - - - - - - 85 200 - - - 407 853 450 1,996 Utility Solar - PV - Utah-S - - - - - - - - - - - - - 58 151 - 380 41 171 5 - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - 3.4 - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 - 3.9 - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - 40.7 - - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 205.0 - 14.0 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 6 6 6 6 5 5 5 5 5 4 3 3 3 3 57 97 DSM, Class 2, UT 84 62 62 59 62 68 66 71 68 69 65 61 57 60 59 47 44 37 34 35 670 1,168 DSM, Class 2, WY 8 10 11 12 13 13 14 15 14 14 12 13 12 11 11 9 8 7 7 7 124 221 DSM, Class 2 Total 97 78 79 77 81 87 85 91 89 88 82 79 74 76 74 60 55 47 44 44 851 1,486 FOT Mona - SMR - - - - - - - - - 27 27 299 265 300 257 300 300 300 300 287 3 133 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources Wind, YK - - - - 1 - - - - - - - - - - - - - - - 1 1 Wind, SO - - - - - - - - - - - - - - 153 - - - - - - 153 Total Wind - - - - 1 - - - - - - - - - 153 - - - - - 1 154 Utility Solar - PV - S-Oregon - - - - - - - - - - - - - 305 - - 56 - - - - 361 Utility Solar - PV - Yakima - - - - - - - - - - - - - 126 3 166 235 7 13 - - 550 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - 4.0 - 32.1 - 3.3 - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - - 13.0 - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 73.0 - 45.1 - 3.3 - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 20 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 5 5 4 3 3 2 2 87 130 DSM, Class 2 Total 57 53 52 46 41 37 34 33 29 27 26 25 23 23 22 21 20 19 19 18 410 625 Geothermal, Greenfield - West - - - - - - - - - - - - - - - - 30 - - - - 30 FOT COB - SMR - - - - 19 130 58 95 249 156 217 400 400 400 400 400 400 400 400 370 71 225 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 8 372 305 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 294 334 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 310 - - - 290 - - 292 400 - 67 361 - 370 400 400 318 149 205 FOT MidColumbia - WTR2 - - - - 323 311 309 - 298 300 - - 348 375 - 367 - 10 13 375 154 151 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 132 131 124 573 123 119 124 118 115 109 382 573 732 602 253 1,160 117 657 933 Annual Additions, Short Term Resources 779 839 1,148 1,115 1,217 1,316 1,242 1,260 1,475 1,412 1,419 2,074 1,988 2,117 1,993 2,042 2,045 2,085 2,088 2,325 Total Annual Additions 933 971 1,279 1,239 1,789 1,439 1,361 1,384 1,592 1,527 1,528 2,455 2,561 2,849 2,595 2,295 3,205 2,203 2,744 3,258 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. RE-1a PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 198 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 Total CCCT - - - - - - - - - - - - - 477 - - - - - - - 477 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - - - 200 - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - 85 - - - - - - - 85 Wind, GO - - - - 150 - - - - - - - - - - - - - 407 393 150 950 Wind, UT - - - - - - - - - - - - - - - - - - - 460 - 460 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 450 - - - - - - - - 85 - - - - 407 853 450 1,796 Utility Solar - PV - Utah-S - - - - - - - - - - - - - 58 151 - 380 41 171 5 - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - 37.6 3.1 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 201.9 12.3 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 6 6 6 6 5 5 5 5 5 4 3 3 3 3 57 97 DSM, Class 2, UT 84 62 62 59 62 68 66 71 68 69 65 61 57 60 59 47 44 37 34 35 670 1,168 DSM, Class 2, WY 8 10 11 12 13 13 14 15 14 14 12 13 12 11 11 9 8 7 7 7 124 221 DSM, Class 2 Total 97 78 79 77 81 87 85 91 89 88 82 79 74 76 74 60 55 47 44 44 851 1,486 FOT Mona - SMR - - - - - - - - - 27 27 299 289 156 160 105 300 300 300 300 3 113 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - 436 - - - - - - - - 436 Total CCCT - - - - - - - - - - - - 436 - - - - - - - - 436 Wind, YK - - - - 80 - - - - - - - - - - - - - - - 80 80 Total Wind - - - - 80 - - - - - - - - - - - - - - - 80 80 Utility Solar - PV - Yakima - - - - - - - - - - - - - 76 3 - 245 7 13 - - 344 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - - - - 3.3 - - - - - 3.3 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 67.8 - - - 3.3 - - - - - 71.2 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 20 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 5 5 4 3 3 2 2 87 130 DSM, Class 2 Total 57 53 52 46 41 37 34 33 29 27 26 25 23 23 22 21 20 19 19 18 410 625 Geothermal, Greenfield - West - - - - - - - - - - - - - - - - 30 - - - - 30 FOT COB - SMR - - - - 10 121 50 86 241 147 208 400 400 400 400 400 400 400 400 357 66 221 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 8 372 305 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 294 334 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 310 - - - 281 - - 283 393 3 - - 257 290 - 333 238 148 164 FOT MidColumbia - WTR2 - - - - 314 302 300 - 289 291 - - 375 219 242 - - 330 - 375 150 152 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 42 - 100 100 100 100 11 43 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 132 131 124 651 123 119 124 118 115 109 373 545 799 250 287 932 117 657 933 Annual Additions, Short Term Resources 779 839 1,148 1,115 1,199 1,299 1,225 1,243 1,457 1,394 1,402 2,066 2,042 1,751 1,720 1,636 1,965 2,005 2,008 2,245 Total Annual Additions 933 971 1,279 1,239 1,851 1,422 1,343 1,367 1,575 1,509 1,510 2,440 2,588 2,550 1,969 1,923 2,897 2,123 2,664 3,178 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. RE-1b PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 199 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - 477 - - - - - - - - 477 Total CCCT - - - - - - - - - - - - 477 - - - - - - - - 477 IC Aero UN - - - - - - - - - - - - - - - - 182 - - - - 182 SCCT Frame UTN - - - - - - - - - - - - - 200 - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - 279 6 - - - - - - 285 Wind, GO - - - - 150 - - - - - - - - - - - - - 407 393 150 950 Wind, UT - - - - - - - - - - - - - - - - - - - 460 - 460 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 450 - - - - - - - - 279 6 - - - 407 853 450 1,996 Utility Solar - PV - Utah-S - - - - - - - - - - - - - 58 151 - 380 41 171 5 - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - 3.4 - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - - - 1.9 - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 - 3.9 - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - 37.6 - 3.1 - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 201.9 - 15.1 - 5.3 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 6 6 6 6 5 5 5 5 5 4 3 3 3 3 57 97 DSM, Class 2, UT 84 62 62 59 62 68 66 71 68 69 65 61 57 60 59 47 44 37 34 35 670 1,168 DSM, Class 2, WY 8 10 11 12 13 13 14 15 14 14 12 13 12 11 11 9 8 7 7 7 124 221 DSM, Class 2 Total 97 78 79 77 81 87 85 91 89 88 82 79 74 76 74 60 55 47 44 44 851 1,486 FOT Mona - SMR - - - - - - - - - 27 27 297 263 300 258 300 287 287 287 287 3 131 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - - - - 436 - - - - 436 Total CCCT - - - - - - - - - - - - - - - - 436 - - - - 436 Wind, YK - - - - 81 - - - - - - - - - 186 - - - 39 - 81 306 Wind, SO - - - - - - - - - - - - - - 212 - - - - - - 212 Total Wind - - - - 81 - - - - - - - - - 398 - - - 39 - 81 518 Utility Solar - PV - Yakima - - - - - - - - - - - - - 105 3 124 31 7 13 - - 282 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - - 14.8 - 24.6 - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - - 13.0 - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 69.1 - 27.9 - 24.6 - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 20 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 5 5 4 3 3 2 2 87 130 DSM, Class 2 Total 57 53 52 46 41 37 34 33 29 27 26 25 23 23 22 21 20 19 19 18 410 625 Geothermal, Greenfield - West - - - - - - - - - - - - - - - - 30 - - - - 30 FOT COB - SMR - - - - 10 121 49 86 240 147 208 400 400 400 400 400 335 335 331 288 65 208 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 8 372 305 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 294 334 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 310 - - - 281 - - 283 393 - 31 - - - - - 209 148 120 FOT MidColumbia - WTR2 - - - - 314 302 300 - 289 291 - - 339 375 326 354 265 306 304 375 150 207 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 132 131 124 652 123 119 124 118 115 109 374 573 783 654 234 1,136 117 696 933 Annual Additions, Short Term Resources 779 839 1,148 1,115 1,199 1,298 1,224 1,242 1,457 1,394 1,402 2,065 1,978 2,081 1,959 2,029 1,863 1,903 1,897 2,134 Total Annual Additions 933 971 1,279 1,239 1,851 1,422 1,343 1,367 1,575 1,509 1,510 2,439 2,551 2,864 2,614 2,263 2,998 2,020 2,593 3,067 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. RE-1c PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 200 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - 477 - - - - - 477 Total CCCT - - - - - - - - - - - - - - - 477 - - - - - 477 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - 200 - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - 85 - - - - - - - 85 Wind, GO - - - - 150 - - - - - - - - - - - - - 407 393 150 950 Wind, UT - - - - - - - - - - - - - - - - - - - 460 - 460 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 450 - - - - - - - - 85 - - - - 407 853 450 1,796 Utility Solar - PV - Utah-S - - - - - - - - - - - - - 58 151 - 380 41 171 5 - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 71.3 4.0 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 160.4 53.9 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 6 6 6 6 5 5 5 5 5 4 3 3 3 3 57 97 DSM, Class 2, UT 84 62 62 59 62 68 66 71 68 69 65 61 57 60 59 47 44 37 34 35 670 1,168 DSM, Class 2, WY 8 10 11 12 13 13 14 15 14 14 12 13 12 11 11 9 8 7 7 7 124 221 DSM, Class 2 Total 97 78 79 77 81 87 85 91 89 88 82 79 74 76 74 60 55 47 44 44 851 1,486 FOT Mona - SMR - - - - - - - - - 27 27 300 198 300 300 - 300 300 300 300 3 118 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - 436 - - - - - - - - 436 Total CCCT - - - - - - - - - - - - 436 - - - - - - - - 436 Wind, YK - - - - 296 - - - - - - - - - - - - - - - 296 296 Total Wind - - - - 296 - - - - - - - - - - - - - - - 296 296 Utility Solar - PV - S-Oregon - - - - - - - - - - - 24 - 16 - - - - - - - 41 Utility Solar - PV - Yakima - - - - - - - - - - - - - 92 10 - 31 7 13 - - 153 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 36.1 - - - - - - - - 36.1 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 69.1 49.1 - - - - - - - - 118.1 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 20 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 5 5 4 3 3 2 2 87 130 DSM, Class 2 Total 57 53 52 46 41 37 34 33 29 27 26 25 23 23 22 21 20 19 19 18 410 625 Geothermal, Greenfield - West - - - - - - - - - - - - - - - - 30 - - - - 30 FOT COB - SMR - - - - - 97 25 62 216 123 184 400 400 400 400 396 400 400 400 357 52 213 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 8 372 305 361 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 292 334 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 310 - - - 257 - - 259 354 - 56 392 221 338 3 381 400 145 193 FOT MidColumbia - WTR2 - - - - 290 278 276 - 265 267 - - 339 375 - - - 375 - 261 138 136 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 - 100 100 100 100 11 46 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 132 131 124 867 123 119 124 118 115 109 357 636 555 257 560 718 117 657 933 Annual Additions, Short Term Resources 779 839 1,148 1,115 1,151 1,250 1,177 1,195 1,409 1,346 1,354 2,029 1,912 2,106 2,067 1,491 2,013 2,053 2,056 2,293 Total Annual Additions 933 971 1,279 1,239 2,019 1,374 1,295 1,319 1,527 1,461 1,462 2,386 2,548 2,661 2,325 2,052 2,731 2,171 2,712 3,226 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. RE-2 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 201 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 SCCT Aero UN - - - - - - - - - - - - - - - 121 - - - - - 121 SCCT Frame UTN - - - - - - - - - - - - - 200 - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - 285 - - - - - - - 285 Wind, GO - - - - 150 - - - - - - - - - - - - - 407 393 150 950 Wind, UT - - - - - - - - - - - - - - - - 13 - - 460 - 473 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 450 - - - - - - - - 285 - - 13 - 407 853 450 2,008 Utility Solar - PV - Utah-S - - - - - - - - - - - - - 58 151 - 380 41 171 5 - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - 3.4 - - - - - - - 11.5 - - 3.4 - - 3.1 - 3.4 21.3 DSM, Class 1, UT-Cool/WH - - - - 45.8 - - - - - - - 22.5 - - - - - - - 45.8 68.4 DSM, Class 1, UT-Curtail - - - - 71.3 - - - - - - - 4.0 4.8 - - - 3.7 - 2.2 71.3 85.9 DSM, Class 1, UT-ICE storage - - - - - - - - - - - - - - - - 3.3 - - - - 3.3 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - 3.1 - - - - - - 3.3 - 6.3 DSM, Class 1, UT-Smart APPl - - - - - - - - - - - - - - - - 4.5 - - - - 4.5 DSM, Class 1, UT-Thermostat - - - - 23.4 - - - - - - - - - - - - - - - 23.4 23.4 DSM, Class 1, WY-Cool/WH - - - - 4.8 - - - - - - - - - - - - - - 2.9 4.8 7.7 DSM, Class 1, WY-Curtail - - - - 37.6 - - - - - - - 3.1 - - - 3.1 - - 2.0 37.6 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1 Total - - - - 186.4 - - - - - - - 51.3 4.8 - 3.4 10.8 3.7 3.1 11.6 186.4 274.9 DSM, Class 2, ID 5 7 7 6 6 5 6 6 6 6 5 5 5 5 5 4 3 3 3 3 57 97 DSM, Class 2, UT 84 62 62 59 62 68 66 71 68 69 65 61 57 60 59 47 44 37 34 35 670 1,168 DSM, Class 2, WY 8 10 11 12 13 13 14 15 14 14 12 13 12 11 11 9 8 7 7 7 124 221 DSM, Class 2 Total 97 78 79 77 81 87 85 91 89 88 82 79 74 76 74 60 55 47 44 44 851 1,486 Battery Storage - East - - - - - - - - - - - - - - - - 10.0 - - - - 10 FOT Mona - SMR - - - - - - - - - - - 281 300 300 300 300 300 300 300 300 - 134 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources Wind, YK - - - - 81 - - - - - - - - - - - - - - - 81 81 Total Wind - - - - 81 - - - - - - - - - - - - - - - 81 81 Utility Solar - PV - S-Oregon - - - - - - - - - - - - 405 - - - - - - - - 405 Utility Solar - PV - Yakima - - - - - - - - - - - - 101 254 3 41 94 7 13 - - 514 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - 2.4 - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - 1.2 - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - 3.7 - - - - - - - - - - - - - - - 3.7 3.7 DSM, Class 1, OR-Cool/WH - - - - 24.7 - - - - - - - 11.4 - 3.3 - - - - - 24.7 39.4 DSM, Class 1, OR-Curtail - - - - 35.0 - - - - - - - - - - - - - - - 35.0 35.0 DSM, Class 1, OR-Irrigate - - - - 9.1 - - - - - - - 3.8 - - - - - - - 9.1 12.8 DSM, Class 1, OR-Thermostat - - - - 4.4 - - - - - - - 5.2 - - - - - - - 4.4 9.6 DSM, Class 1, WA-Cool/WH - - - - 8.9 - - - - - - - 4.1 - - - - - - - 8.9 13.0 DSM, Class 1, WA-Curtail - - - - 9.1 - - - - - - - - - - - - - - - 9.1 9.1 DSM, Class 1, WA-Irrigate - - - - 4.8 - - - - - - - - - - - - - - - 4.8 4.8 DSM, Class 1, WA-Thermostat - - - - 3.5 - - - - - - - - - - - - - - - 3.5 3.5 DSM, Class 1 Total - - - - 103.1 - - - - - - - 28.1 - 3.3 - - - - - 103.1 134.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 20 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 5 5 4 3 3 2 2 87 130 DSM, Class 2 Total 57 53 52 46 41 37 34 33 29 27 26 25 23 23 22 21 20 19 19 18 410 625 Geothermal, Greenfield - West - - - - - - - - - - - - - - - - 30 - - - - 30 FOT COB - SMR - - - - - - - - - - - 400 400 400 400 400 400 400 400 357 - 178 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 8 372 305 96 207 135 172 326 259 321 375 375 375 375 375 375 375 375 375 188 279 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 310 - - - 281 - - 283 393 130 119 85 36 400 400 400 366 148 205 FOT MidColumbia - WTR2 - - - - 314 302 300 - 289 291 - - 375 375 375 375 18 59 61 375 150 175 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 132 131 124 942 123 119 124 118 115 109 103 682 900 253 246 1,088 117 657 933 Annual Additions, Short Term Resources 779 839 1,148 1,115 910 1,009 935 953 1,168 1,105 1,112 2,048 2,180 2,169 2,135 2,086 2,093 2,134 2,136 2,373 Total Annual Additions 933 971 1,279 1,239 1,851 1,132 1,054 1,077 1,285 1,220 1,221 2,152 2,862 3,070 2,388 2,332 3,182 2,251 2,793 3,306 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. DLC-1 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 202 Table K.9 – Sensitivity Cases, Detailed Capacity Expansion Portfolios Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Hunter 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - (418) - - - - - (418) Hunter 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - (269) - - - - - (269) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - - - - - - (330) - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- (280) - - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - 477 - - - - - 477 CCCT - Utah-S - G 1x1 - - - - - - - - - - - - - - - - 389 - - - - 389 Total CCCT - - - - - - - - - - - - - - - 477 389 - - - - 865 IC Aero UN - - - - - - - - - - - - - - - - 182 - - - - 182 SCCT Aero UN - - - - - - - - - - - - - - - - - - 121 - - 121 SCCT Frame DJ - - - - - - - - - - - - - 200 - - - - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - - - 200 - - - - - 200 SCCT Frame UTS - - - - - - - - - - - - - - - - - - - 200 - 200 Wind, Djohnston - - - - - - - - - - - - - 85 - - - - - - - 85 Wind, GO - - - - - - - - - - - - - - - - 88 152 314 - - 555 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 300 - - - - - - - - 85 - - 88 152 314 - 300 940 Utility Solar - PV - Utah-S - - - - - - - - - - - - - 122 150 219 309 - - - - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - 3.4 - - - - - - - - - 3.4 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - - - 83.7 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - - - 3.1 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1, WY-Curtail - - - - - - - - - - - 40.7 - - - - 3.1 - - - - 43.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 208.4 3.9 6.7 - 3.4 3.1 3.7 3.1 - - 232.2 DSM, Class 2, ID 5 7 7 6 6 6 6 6 6 6 5 5 5 5 5 4 4 3 3 2 58 97 DSM, Class 2, UT 84 62 62 59 70 68 66 71 70 69 65 64 60 60 59 49 44 37 34 24 681 1,178 DSM, Class 2, WY 8 10 11 12 13 13 15 15 14 14 14 13 12 11 11 9 8 7 7 5 125 222 DSM, Class 2 Total 97 78 79 77 89 87 86 92 91 88 84 82 77 76 75 62 55 47 43 31 864 1,497 FOT Mona - SMR - - - - - - - - 197 130 191 300 300 300 300 300 300 300 300 267 33 159 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - (354) - - - - - - - - - - - (354) (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (359) - - - - - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - 436 - - - - - - - - 436 Total CCCT - - - - - - - - - - - - 436 - - - - - - - - 436 Utility Solar - PV - S-Oregon - - - - - - - - - - - - 1 121 2 58 8 - - - - 190 Utility Solar - PV - Yakima - - - - - - - - - - - - - - - - 6 7 13 - - 26 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - 21.8 - 14.2 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - 8.9 - 4.1 - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 99.8 - 18.3 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 22 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 9 9 8 10 9 9 9 8 8 7 7 6 6 5 4 3 3 2 2 89 134 DSM, Class 2 Total 57 54 52 46 42 37 34 33 29 27 27 25 24 23 22 22 20 19 19 18 412 630 Geothermal, Greenfield - West - - - - - - - - - - - - - 30 - - - - - - - 30 FOT COB - SMR - - - - 35 146 74 110 400 400 400 400 400 400 400 400 400 400 400 357 117 256 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 272 372 305 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 320 347 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 - 322 310 308 - - 299 290 400 52 62 400 - - - 348 400 212 204 FOT MidColumbia - WTR2 - - - 310 - - - 289 297 - - 38 375 375 - 320 313 353 - 167 90 142 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - (280) - - (387) - - - (354) (82) - (432) (359) (357) (78) (687) (688) - (82) - Annual Additions, Long Term Resources 154 132 131 124 432 124 120 125 120 116 110 415 542 683 253 1,041 1,060 229 513 249 Annual Additions, Short Term Resources 779 1,103 1,147 1,114 1,232 1,331 1,256 1,274 1,821 1,758 1,764 2,113 2,102 2,112 2,075 1,995 1,988 2,028 2,023 2,166 Total Annual Additions 933 1,235 1,278 1,238 1,664 1,455 1,376 1,399 1,941 1,873 1,874 2,529 2,644 2,794 2,328 3,036 3,048 2,258 2,536 2,416 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. RH2a PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 203 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 CCCT - Utah-S - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - 477 - - 477 - - - - 953 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - 200 - - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - 85 - - - - - - 85 Wind, GO - - - - - - - - - - - - - - - - - - - 695 - 695 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 300 - - - - - - - - - 85 - - - - 695 300 1,080 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - 20 179 216 41 297 47 - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - 40.7 - - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 205.0 9.2 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 6 6 6 6 5 5 5 5 4 4 3 3 3 3 57 97 DSM, Class 2, UT 84 62 62 59 62 68 66 71 68 69 65 61 57 60 59 49 44 37 34 35 670 1,170 DSM, Class 2, WY 8 10 11 12 13 13 14 15 14 14 12 13 11 11 11 9 8 7 7 7 124 220 DSM, Class 2 Total 97 78 79 77 81 87 85 92 89 88 82 79 73 76 74 62 55 47 44 44 852 1,488 FOT Mona - SMR - - - - - - - - - 27 27 300 84 300 300 300 300 300 300 300 3 127 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - 436 - - - - - - - - 436 Total CCCT - - - - - - - - - - - - 436 - - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - 151 - 16 130 70 16 8 - - - 391 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - 11.4 24.7 - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - 7.9 5.1 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 88.3 29.8 - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 9 9 8 10 9 9 9 8 8 7 7 6 6 5 4 3 3 2 2 89 134 DSM, Class 2 Total 57 54 52 46 42 37 34 33 29 27 27 25 23 23 22 21 20 19 19 18 412 629 FOT COB - SMR - 209 44 - 96 210 138 177 334 244 311 400 400 400 400 400 400 400 400 364 145 266 FOT MidColumbia - SMR 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 306 375 375 354 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 366 371 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT COB - WTR - - - - - - - - - - - - - - - - - - - 11 - 1 FOT MidColumbia - WTR 380 71 400 120 400 76 74 60 312 400 203 400 383 400 400 400 92 400 127 400 229 275 FOT MidColumbia - WTR2 - 375 7 375 59 375 375 375 375 287 375 193 - 180 176 85 375 106 375 375 260 242 FOT NOB - WTR - 3 - 45 88 86 91 77 100 100 100 100 100 100 100 100 100 100 100 100 59 79 Existing Plant Retirements/Conversions - - 5 - (387) - - - - (82) - (762) (354) (642) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 132 131 124 423 123 119 125 118 116 109 548 772 596 335 336 987 118 363 816 Annual Additions, Short Term Resources 1,186 1,532 1,325 1,394 1,518 1,623 1,553 1,564 1,996 1,933 1,891 2,268 1,842 2,255 2,251 2,160 2,142 2,181 2,177 2,425 Total Annual Additions 1,340 1,664 1,456 1,518 1,941 1,746 1,671 1,688 2,114 2,048 2,000 2,816 2,614 2,852 2,585 2,496 3,128 2,298 2,540 3,241 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. LD-1 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 204 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 SCCT Frame UTN - - - - - - - - - - - - - - - - 200 - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - - - 285 - - - - 285 Wind, WYAE - - - - - - - - - - - - - - - - 36 102 162 - - 300 Total Wind - - - - - - - - - - - - - - - - 321 102 162 - - 585 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - - - - 209 83 - 292 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - 3.4 - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - - 14.9 - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - - - 68.4 - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - - 80.0 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - - 3.1 - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - - 4.8 - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - - 40.7 - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - - - 219.0 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 5 7 6 6 5 5 5 5 5 5 5 5 4 4 4 3 3 2 2 53 91 DSM, Class 2, UT 84 58 56 53 62 58 57 57 63 60 61 57 57 57 56 47 43 36 33 34 607 1,088 DSM, Class 2, WY 8 10 11 10 11 11 14 14 14 14 12 11 10 10 10 9 8 7 7 7 116 208 DSM, Class 2 Total 97 73 74 69 78 75 76 76 81 79 78 73 72 72 71 60 54 46 42 43 777 1,387 FOT Mona - SMR - - - - - - - - - - - 27 276 144 194 298 300 300 300 300 - 107 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - - - - - - 76 - - - - 76 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - - 2.4 - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - - 1.2 - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - - - 3.7 - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - - 36.1 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - - 35.0 - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - - - 12.8 - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - - 13.0 - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - - 9.1 - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - - 4.8 - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - - - 118.1 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 20 DSM, Class 2, OR 46 40 42 37 31 26 23 23 20 18 18 17 17 16 16 17 15 15 16 16 306 470 DSM, Class 2, WA 10 8 8 8 9 9 9 8 8 8 7 6 6 5 5 4 3 3 2 2 86 129 DSM, Class 2 Total 57 50 52 46 41 37 33 32 29 27 26 24 23 23 22 21 20 19 19 18 404 619 Geothermal, Greenfield - West - - - - - - - - - - - - - 30 - - - - - - - 30 FOT COB - SMR - - - - - - - - - - - 276 400 400 400 400 400 400 400 400 - 174 FOT MidColumbia - SMR 280 400 400 368 369 400 349 329 400 330 377 400 400 400 400 400 400 400 400 400 362 380 FOT MidColumbia - SMR - 2 - 69 15 - - 13 - - 14 - - 375 375 375 375 375 375 375 375 375 11 174 FOT NOB - SMR 61 100 - - 18 62 26 50 100 100 100 100 100 100 100 100 100 100 100 100 52 76 FOT MidColumbia - WTR 280 - 274 - 321 - - - - 291 - 289 - 290 - - 377 393 400 353 116 163 FOT MidColumbia - WTR2 - 329 - 308 - 309 307 288 289 - 289 - 334 - 310 372 - - 2 375 183 176 FOT NOB - WTR - - - - - - - - 42 42 - - 100 100 100 100 100 100 100 100 8 44 Existing Plant Retirements/Conversions - - 5 - (387) - - - - (82) - (762) (354) (642) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 123 126 115 119 112 109 108 110 105 104 97 95 898 96 84 1,151 170 436 156 Annual Additions, Short Term Resources 621 898 688 676 707 783 682 667 845 763 767 1,467 1,985 1,809 1,879 2,045 2,052 2,068 2,077 2,403 Total Annual Additions 774 1,021 814 791 827 895 790 775 956 868 870 1,564 2,079 2,707 1,975 2,129 3,202 2,238 2,513 2,559 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. LD-2 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 205 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 CCCT - Utah-S - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - 477 - - 477 - - - - 953 IC Aero UN - - - - - - - - - - - - - - - - 182 - - - - 182 SCCT Frame DJ - - - - - - - - - - - - - 200 - - - - - - - 200 SCCT Frame UTN - - - - - - - - - - - 200 - - - - - - - - - 200 SCCT Frame UTS - - - - - - - - - - - - - - - - - - - 200 - 200 Wind, Djohnston - - - - - - - - - - - 85 - - - - - - - - - 85 Wind, GO - - - - - - - - - - - - - - - - - - 630 - - 630 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 300 - - - - - - 85 - - - - - - 630 - 300 1,015 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - 74 238 270 62 155 - - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - 3.4 - - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 - 3.9 - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - 40.7 - - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 208.4 - 10.6 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 6 6 6 6 5 5 5 5 5 4 3 3 3 3 57 97 DSM, Class 2, UT 84 62 62 59 66 68 66 71 68 69 65 61 57 60 59 49 44 37 34 35 674 1,174 DSM, Class 2, WY 8 12 13 12 14 14 15 15 15 16 14 14 13 11 11 9 8 7 7 7 134 234 DSM, Class 2 Total 97 80 81 77 85 87 86 92 89 90 84 79 74 76 74 62 55 47 44 45 865 1,506 FOT Mona - SMR - - - - - - - - 22 - 52 300 252 300 300 300 300 300 300 265 2 135 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - SOregonCal - J 1x1 - - - - - - - - - - - - 509 - - - - - - - - 509 Total CCCT - - - - - - - - - - - - 509 - - - - - - - - 509 Utility Solar - PV - S-Oregon - - - - - - - - - - - - - 21 55 48 - - - - - 124 Utility Solar - PV - Yakima - - - - - - - - - - - - - - - 15 18 11 18 - - 62 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - 36.1 - - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - 13.0 - - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 118.1 - - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 0 0 14 22 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 9 9 8 10 10 9 9 8 8 7 7 6 6 5 4 3 3 2 2 90 135 DSM, Class 2 Total 57 54 52 46 42 37 34 33 30 27 27 25 23 23 22 22 20 19 19 18 413 631 Geothermal, Greenfield - West - - - - - - - - - - - - - - 30 - - - - - - 30 FOT COB - SMR - 95 - - 66 215 162 223 400 371 400 400 400 400 400 400 400 400 400 360 153 275 FOT MidColumbia - SMR 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 151 375 341 297 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 341 358 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 282 - 277 - 324 - - - - 308 - 400 - 359 351 322 - 319 - 400 119 167 FOT MidColumbia - WTR2 - 332 - 312 - 312 310 292 305 - 294 25 359 - - - 318 - 316 140 186 166 FOT NOB - WTR - - - - - - - - 63 65 27 100 100 100 93 70 51 89 97 100 13 48 Existing Plant Retirements/Conversions - - 5 - (387) - - - - (82) - (762) (354) (642) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 134 133 124 427 125 120 125 119 117 111 716 606 807 258 388 1,024 143 870 275 Annual Additions, Short Term Resources 932 1,302 1,118 1,109 1,264 1,402 1,347 1,390 1,666 1,620 1,648 2,100 1,986 2,034 2,019 1,967 1,944 1,983 1,988 2,140 Total Annual Additions 1,086 1,436 1,251 1,232 1,692 1,527 1,467 1,515 1,785 1,737 1,759 2,816 2,592 2,841 2,277 2,355 2,969 2,126 2,857 2,415 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. LD-3 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 206 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 Total CCCT - - - - - - - - - - - - - 477 - - - - - - - 477 IC Aero UN - - - - - - - - - - - - - - - - - - 182 - - 182 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - 200 - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - 83 3 - - - - - 85 Wind, GO - - - - - - - - - - - - - - - - 62 212 - 526 - 800 Wind, UT - - - - - - - - - - - - - - - - - - - 347 - 347 Wind, WYAE - - - - 211 - - - - - - - - - - - 89 - - - 211 300 Total Wind - - - - 211 - - - - - - - - - 83 3 152 212 - 873 211 1,532 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - - 800 - - 5 - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - - - 3.4 - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - - - - 1.9 - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 - 3.9 - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - - - 39.5 40.5 - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - - 4.8 - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - - - - 40.7 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 82.4 - 10.6 39.5 88.0 5.0 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 4 4 3 3 3 3 56 95 DSM, Class 2, UT 84 58 62 59 62 58 66 66 68 65 63 61 57 57 56 49 44 37 34 35 647 1,140 DSM, Class 2, WY 8 10 11 10 13 13 14 14 14 14 12 11 10 10 11 9 8 7 7 7 121 214 DSM, Class 2 Total 97 74 79 75 81 77 85 85 88 84 80 77 72 72 71 62 55 47 44 44 825 1,450 FOT Mona - SMR - - - - - - - - - - - 296 249 300 300 300 300 300 300 300 - 132 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - SOregonCal - J 1x1 - - - - - - - - - - - - 509 - - - - - - - - 509 Total CCCT - - - - - - - - - - - - 509 - - - - - - - - 509 Utility Solar - PV - Yakima - - - - - - - - - - - - - - 15 - 141 14 16 - - 186 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - - 1.2 - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - - - - 39.4 - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - - - 35.0 - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - - - - 13.0 - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - - - 9.1 - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 23.7 - 1.2 44.1 52.4 - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 5 5 4 3 3 2 2 87 130 DSM, Class 2 Total 57 53 52 46 41 37 33 33 29 27 26 25 23 23 22 21 20 19 19 18 409 625 Geothermal, Greenfield - West - - - - - - - - - - - - - - - - 30 - - - - 30 FOT COB - SMR - - - - - - - - 54 - 64 400 400 400 400 400 400 400 400 365 5 184 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 281 115 50 178 298 228 270 375 372 375 375 375 375 375 375 375 375 375 375 217 296 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 - 275 - 323 - - - - 301 - 292 - - 334 313 259 291 - 180 118 142 FOT MidColumbia - WTR2 - 331 - 310 - 311 309 291 298 - 293 - 301 269 - - - - 274 375 185 168 FOT NOB - WTR - - - - - - - - 53 54 9 11 - - - 38 100 100 100 100 11 28 Existing Plant Retirements/Conversions - - 5 - (387) - - - - (82) - (762) (354) (642) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 332 114 118 118 117 111 107 208 603 783 275 227 1,403 295 264 952 Annual Additions, Short Term Resources 780 1,112 891 860 1,001 1,109 1,037 1,061 1,281 1,227 1,240 1,874 1,825 1,844 1,909 1,926 1,934 1,966 1,949 2,194 Total Annual Additions 934 1,240 1,022 982 1,333 1,223 1,155 1,178 1,398 1,338 1,347 2,082 2,428 2,627 2,185 2,153 3,337 2,262 2,213 3,146 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. PG-1 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 207 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 SCCT Frame UTN - - - - - - - - - - - - - 200 - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - 285 - - - - - - 285 Wind, GO - - - - - - - - - - - - - - - - - - 503 297 - 800 Wind, UT - - - - - - - - - - - - - - - - - - - 463 - 463 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 300 - - - - - - - - - 285 - - - 503 760 300 1,849 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - 33 150 502 - 115 5 - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - 3.4 - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - 14.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - - 68.4 - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - 75.3 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - 3.1 - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - 4.8 - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - - 209.0 10.0 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 4 4 3 3 3 3 56 95 DSM, Class 2, UT 84 58 62 59 62 58 66 66 68 65 63 61 57 57 58 49 44 37 34 35 647 1,141 DSM, Class 2, WY 8 10 11 10 13 13 14 14 14 14 12 11 11 11 11 9 8 7 7 7 121 216 DSM, Class 2 Total 97 74 79 75 81 77 85 85 88 84 80 77 73 73 73 62 55 47 44 44 825 1,452 FOT Mona - SMR - - - - - - - - - - - 249 300 300 300 300 300 299 300 300 - 132 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - S-Oregon - - - - - - - - - - - - 12 - - - - - - - - 12 Utility Solar - PV - Yakima - - - - - - - - - - - - 28 5 17 33 - - - - - 82 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - 2.4 - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - 1.2 - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - - 3.7 - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 11.4 24.7 - 3.3 - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - 35.0 - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - - 12.8 - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - 9.1 - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - 4.8 - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - - 93.5 24.7 - 3.3 - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 5 5 4 3 2 2 2 87 130 DSM, Class 2 Total 57 53 52 46 41 37 33 33 29 27 26 25 23 23 22 21 20 18 19 18 409 624 Geothermal, Greenfield - West - - - - - - - - - - - - - 30 - - - - - - - 30 FOT COB - SMR - - - - - - - - - - - 400 400 400 400 400 400 400 400 353 - 178 FOT MidColumbia - SMR 395 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 268 97 27 133 245 172 207 354 281 320 375 375 375 375 375 375 375 375 375 178 274 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT COB - WTR - - - - - - - - - - - - - - - - - - - 86 - 4 FOT MidColumbia - WTR 281 - 275 - 323 - - - - 300 - 291 144 400 121 400 400 400 198 400 118 197 FOT MidColumbia - WTR2 - 331 - 310 - 311 309 290 298 - 292 - 375 121 375 78 95 154 375 375 185 204 FOT NOB - WTR - - - - - - - - 52 53 4 5 100 100 100 100 100 100 100 100 10 46 Existing Plant Retirements/Conversions - - 5 - (387) - - - - (82) - (762) (354) (642) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 422 114 118 118 117 111 107 101 439 801 431 272 1,056 68 684 839 Annual Additions, Short Term Resources 776 1,099 873 837 955 1,056 981 997 1,204 1,133 1,116 1,820 2,194 2,196 2,171 2,153 2,170 2,228 2,248 2,489 Total Annual Additions 930 1,227 1,004 959 1,377 1,170 1,099 1,115 1,321 1,245 1,223 1,921 2,632 2,997 2,602 2,425 3,226 2,296 2,932 3,328 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. PG-2 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 208 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 CCCT - Utah-S - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - 477 - - 477 - - - - 953 SCCT Frame UTN - - - - - - - - - - - - - - - - 200 - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - 285 - - - - - - 285 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 300 - - - - - - - - - 285 - - - - - 300 585 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - - 196 49 293 212 - 750 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - - 3.4 - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - - - 1.9 - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - - 14.9 - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - - 80.0 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - - 3.1 - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - - 4.8 - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - - 37.6 3.1 - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 68.4 - 142.3 6.4 5.3 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 4 4 3 3 2 2 56 94 DSM, Class 2, UT 84 58 56 59 62 58 57 66 63 65 61 61 57 57 56 48 43 36 33 34 627 1,114 DSM, Class 2, WY 8 10 11 10 13 13 14 14 14 14 12 11 10 10 11 9 8 7 7 7 121 213 DSM, Class 2 Total 97 74 74 75 81 77 76 85 82 84 78 77 72 72 71 61 54 46 42 43 805 1,421 FOT Mona - SMR - - - - - - - - - - - 299 284 298 300 300 300 300 300 300 - 134 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - Yakima - G 1x1 - - - - - - - - - - - - 458 - - - - - - - - 458 Total CCCT - - - - - - - - - - - - 458 - - - - - - - - 458 Utility Solar - PV - S-Oregon - - - - - - - - - - - - - - 20 124 27 - - - - 171 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - - 2.4 - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - - 1.2 - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - - - 3.7 - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - - - 14.7 24.7 - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - - 35.0 - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - - - 12.8 - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - - - 13.0 - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - - 9.1 - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - - 4.8 - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - - - 69.1 27.8 24.7 - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 8 8 8 8 8 7 6 5 5 5 4 3 2 2 2 83 123 DSM, Class 2 Total 57 53 52 46 41 35 32 31 29 27 26 24 23 22 22 21 19 18 19 18 406 617 Geothermal, Greenfield - West - - - - - - - - - - - - - - - 30 - - - - - 30 FOT COB - SMR - - - - - - - - 31 - 32 400 400 400 400 400 400 400 400 368 3 182 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 276 111 45 157 274 208 249 375 342 375 375 375 375 375 375 375 375 375 375 204 289 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 - 275 - 323 - - - - 303 - 294 - 343 341 - - - - 271 118 122 FOT MidColumbia - WTR2 - 331 - 310 - 312 311 293 301 - 295 - 147 - - 328 313 354 356 375 186 201 FOT NOB - WTR - - - - - - - - 53 54 8 10 100 100 100 100 100 100 100 100 11 46 Existing Plant Retirements/Conversions - - 5 - (387) - - - - (82) - (762) (354) (642) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 126 122 422 113 108 116 112 111 105 169 552 782 432 265 976 117 357 285 Annual Additions, Short Term Resources 779 1,106 886 855 979 1,085 1,019 1,042 1,259 1,199 1,209 1,879 1,806 2,016 2,016 2,003 1,988 2,029 2,031 2,289 Total Annual Additions 933 1,234 1,012 977 1,401 1,198 1,127 1,158 1,371 1,310 1,314 2,048 2,359 2,798 2,448 2,268 2,965 2,145 2,387 2,574 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. CPP-C PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 209 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - 477 - - - - - - - - 477 Total CCCT - - - - - - - - - - - - 477 - - - - - - - - 477 IC Aero UN - - - - - - - - - - - - - - - - - - - 182 - 182 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - - - 200 - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - - - 85 - - - - 85 Wind, GO - - - - - - - - - - - - - - - - - - 768 - - 768 Wind, WYAE - - - - 9 - - - - - - - - - - - 291 - - - 9 300 Total Wind - - - - 9 - - - - - - - - - - - 377 - 768 - 9 1,154 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - - 684 40 75 - - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - - 3.4 - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - - 1.9 - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 - 3.9 - - 3.4 - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - - 80.0 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - - 4.8 - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - - 18.6 22.1 - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 82.4 - 109.3 27.4 - 6.5 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 4 4 3 3 3 3 56 95 DSM, Class 2, UT 84 58 56 59 62 58 66 66 63 65 63 61 57 57 58 47 44 37 34 35 637 1,128 DSM, Class 2, WY 8 10 11 10 13 13 14 14 14 14 12 11 10 10 11 9 8 7 7 7 121 215 DSM, Class 2 Total 97 74 74 75 81 77 85 85 82 84 80 77 72 72 73 60 55 47 44 44 814 1,438 FOT Mona - SMR - - - - - - - - - 4 27 300 267 300 281 233 300 300 300 263 0 129 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - SOregonCal - J 1x1 - - - - - - - - - - - - - 509 - - - - - - - 509 Total CCCT - - - - - - - - - - - - - 509 - - - - - - - 509 Utility Solar - PV - Yakima - - - - - - - - - - - - - 12 - - 98 8 13 - - 130 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - - 1.2 - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - - - 39.4 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - - 35.0 - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - - - 13.0 - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - - 9.1 - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - - 4.8 - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 18.9 - 50.1 52.4 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 9 9 9 9 8 8 7 6 6 5 5 4 3 3 2 2 87 130 DSM, Class 2 Total 57 53 52 46 41 37 33 33 29 27 26 25 23 23 22 21 20 19 19 18 409 625 Geothermal, Greenfield - West - - - - - - - - - - - - - - 30 - - - - - - 30 FOT COB - SMR - - - - - - - - 68 - 40 400 400 400 400 400 400 400 400 357 7 183 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 276 111 45 200 316 245 286 375 375 375 375 375 375 375 375 375 375 375 375 223 299 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 - 275 - 323 - - - - 300 - 292 - 325 - 313 329 370 - 228 118 152 FOT MidColumbia - WTR2 - 331 - 310 - 311 309 290 298 - 292 - 301 - 349 - - - 372 375 185 177 FOT NOB - WTR - - - - - - - - 53 54 8 28 15 100 100 31 100 100 100 100 11 39 Existing Plant Retirements/Conversions - - 5 - (387) - - - - (82) - (762) (354) (642) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 126 122 130 114 118 118 112 111 107 203 571 775 204 281 1,440 117 923 256 Annual Additions, Short Term Resources 779 1,106 886 855 1,023 1,127 1,054 1,076 1,294 1,233 1,243 1,894 1,858 2,000 2,005 1,852 2,004 2,045 2,047 2,198 Total Annual Additions 933 1,234 1,012 977 1,153 1,241 1,172 1,194 1,405 1,345 1,349 2,097 2,429 2,775 2,210 2,133 3,444 2,162 2,970 2,454 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. CPP-D PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 210 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 CCCT - Utah-S - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - 477 - - 477 - - - - 953 IC Aero UN - - - - - - - - - - - - - - - - - - 182 - - 182 SCCT Frame UTN - - - - - - - - - - - - 200 - - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - 285 - - - - - - 285 Wind, GO - - - - - - - - - - - - - - - - - - - 387 - 387 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 300 - - - - - - - - - 285 - - - - 387 300 973 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - 115 535 40 - 111 - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - 3.4 - - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - 40.7 - - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 210.3 3.9 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 6 6 6 6 5 5 5 5 5 4 3 3 3 3 57 97 DSM, Class 2, UT 84 62 62 59 62 68 66 71 68 69 65 61 60 60 59 49 44 37 34 35 670 1,174 DSM, Class 2, WY 8 10 11 12 13 13 15 15 14 14 12 13 12 11 11 9 8 7 7 7 125 222 DSM, Class 2 Total 97 78 79 77 81 87 86 92 89 88 82 79 77 76 74 62 55 47 44 44 853 1,493 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources SCCT Frame SO - - - - - - - - - - - - 216 - - - - - - - - 216 Utility Solar - PV - S-Oregon - - - - - - - - - - - 115 24 173 - - - - - - - 311 Utility Solar - PV - Yakima - - - - - - - - - - - - - 225 86 127 16 7 - - - 462 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - 36.1 - - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - 13.0 - - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 118.1 - - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 9 9 8 10 9 9 9 8 8 7 7 6 6 5 4 3 3 2 2 89 134 DSM, Class 2 Total 57 54 52 46 42 37 34 33 29 27 27 25 24 23 22 21 20 19 19 18 412 629 Geothermal, Greenfield - West - - - - - - - - - - - 30 - - - - - - - - - 30 FOT COB - SMR - - - - - - - - 101 34 96 400 400 400 400 400 400 400 398 364 14 190 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 272 103 36 247 358 285 322 375 375 375 375 375 375 375 375 375 375 375 375 237 306 FOT NOB - SMR 100 100 100 100 - - - - - - - - - - - - - - - - 40 20 FOT MidColumbia - WTR 281 - 275 - 322 310 - 289 349 - 298 289 298 - 180 - 91 - 98 - 182 154 FOT MidColumbia - WTR2 - 331 - 310 - - 308 - - 353 - - - 151 - 94 - 93 - 358 130 100 Existing Plant Retirements/Conversions - - 5 - (387) - - - - (82) - (762) (354) (642) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 132 131 124 423 123 120 125 118 116 109 577 544 978 471 329 1,105 117 247 572 Annual Additions, Short Term Resources 779 1,103 878 846 968 1,068 993 1,011 1,225 1,162 1,169 1,464 1,473 1,326 1,355 1,269 1,266 1,268 1,270 1,497 Total Annual Additions 933 1,235 1,009 969 1,391 1,191 1,113 1,135 1,343 1,277 1,278 2,041 2,017 2,304 1,826 1,598 2,371 1,385 1,518 2,069 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. FOT-1 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 211 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - Utah-S - G 1x1 - - - - - - - - - - - - - - - - 389 - - - - 389 CCCT - Utah-S - J 1x1 - - - - - - - - - - - - - - - - - - 477 - - 477 Total CCCT - - - - - - - - - - - - - - - - 389 - 477 - - 865 SCCT Frame UTN - - - - - - - - - - - - - 200 - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - 366 396 - - - - - - - 762 Wind, GO - - - - - - - - - - - - - - 70 673 57 - - - - 800 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 300 - - - - - - - 366 396 70 673 57 - - - 300 1,862 Utility Solar - PV - Utah-S - - - - - - - - - - - - - 50 - - 628 40 - - - 717 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - 14.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 3.3 65.0 - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - 75.3 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - 3.1 - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 8.1 206.1 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 6 6 6 6 5 5 5 5 5 4 3 3 3 3 57 98 DSM, Class 2, UT 84 62 62 59 70 68 66 71 70 69 65 61 60 60 59 49 44 37 34 37 681 1,187 DSM, Class 2, WY 8 10 11 12 13 13 15 15 14 15 14 13 12 11 11 9 8 8 7 8 126 226 DSM, Class 2 Total 97 78 79 77 89 87 86 92 90 89 84 80 77 76 74 62 56 47 43 48 865 1,511 FOT Mona - SMR - - - - - - - - - - - 300 300 300 300 300 300 300 86 149 - 117 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources Wind, YK - - - - - - - - - - - - - - - - - 33 - - - 33 Total Wind - - - - - - - - - - - - - - - 259 241 33 - - - 533 Utility Solar - PV - S-Oregon - - - - - - - - - - - - - 405 - - - - - - - 405 Utility Solar - PV - Yakima - - - - - - - - - - - - - 272 149 - - - - - - 421 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - 2.4 - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - 1.2 - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - - 3.7 - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 36.1 - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 7.7 27.3 - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - - 12.8 - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 4.7 4.4 - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - 4.8 - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 12.4 105.7 - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 0 0 14 22 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 19 16 21 310 483 DSM, Class 2, WA 10 9 9 8 10 10 9 9 8 8 7 7 6 6 5 4 3 3 2 2 90 135 DSM, Class 2 Total 57 54 52 46 42 37 34 33 30 27 27 25 24 23 22 22 20 22 19 24 413 640 Geothermal, Greenfield - West - - - - - - - - - - - - 30 - - - - - - - - 30 FOT COB - SMR - - - - - - - - - - - 400 400 400 400 400 400 400 342 363 - 175 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 272 103 36 142 252 180 216 369 301 362 375 375 375 375 375 375 375 375 375 187 280 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 - 275 - 322 - - - - 352 - 289 98 187 400 400 118 156 386 263 123 176 FOT MidColumbia - WTR2 - 331 - 310 - 309 307 288 348 - 290 - 375 375 127 88 375 375 - 375 189 214 FOT NOB - WTR - - - - - - - - - - 7 9 100 - - - - - - - - 6 Existing Plant Retirements/Conversions - - 5 - (387) - - - - (82) - (762) (354) (642) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 132 131 124 432 124 120 125 120 117 110 126 809 1,426 319 1,020 1,393 146 541 83 Annual Additions, Short Term Resources 779 1,103 878 846 963 1,062 987 1,005 1,217 1,153 1,159 1,873 2,148 2,137 2,102 2,063 2,068 2,106 1,690 2,025 Total Annual Additions 933 1,235 1,009 969 1,395 1,186 1,107 1,130 1,337 1,270 1,269 1,999 2,957 3,563 2,421 3,083 3,460 2,253 2,231 2,108 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. C02-1 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 212 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - 477 - - - - - - - 477 Total CCCT - - - - - - - - - - - - - 477 - - - - - - - 477 SCCT Aero UN - - - - - - - - - - - - - - - - - - - 121 - 121 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - - - - 200 - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - - 85 - - - - - 85 Wind, GO - - - - - - - - - - - - - - - - - - 682 112 - 795 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 300 - - - - - - - - - - 85 - - 682 112 300 1,180 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - 6 658 40 95 - - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - - - 3.4 - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - - - 1.9 - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - 14.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - - 68.4 - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - 75.3 - 4.8 - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - 3.1 - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - 4.8 - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - - 209.0 - 8.1 5.3 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 5 4 3 3 3 3 56 96 DSM, Class 2, UT 84 58 62 59 62 58 66 66 63 65 64 61 57 57 59 49 44 37 36 37 642 1,143 DSM, Class 2, WY 8 10 11 10 13 13 14 14 14 14 12 13 12 11 11 9 8 7 7 7 121 219 DSM, Class 2 Total 97 74 79 75 81 77 85 85 82 84 82 78 74 73 74 62 55 47 46 47 819 1,458 FOT Mona - SMR - - - - - - - - - 27 27 208 300 259 300 300 300 300 300 300 3 131 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - Yakima - G 1x1 - - - - - - - - - - - 458 - - - - - - - - - 458 Total CCCT - - - - - - - - - - - 458 - - - - - - - - - 458 Utility Solar - PV - S-Oregon - - - - - - - - - - - - - - 3 159 13 6 11 - - 192 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - 2.4 - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - 1.2 - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - - 3.7 - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 14.8 - 10.3 14.2 - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - 35.0 - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - - 12.8 - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - 9.1 - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - 4.8 - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - - 96.9 - 10.3 14.2 - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 40 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 306 471 DSM, Class 2, WA 10 7 9 8 9 8 7 8 8 8 7 6 5 5 5 4 3 2 2 2 81 121 DSM, Class 2 Total 57 49 52 46 41 35 32 31 29 27 26 24 23 22 22 21 19 18 19 18 400 613 Geothermal, Greenfield - West - - - - - - - - - - - - - - 30 - - - - - - 30 FOT COB - SMR - - 3 - 49 166 95 136 293 202 264 400 400 400 400 400 400 400 400 357 94 238 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 14 375 312 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 295 335 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 332 276 311 - - - 294 302 - - - 36 337 - 336 338 3 382 280 180 175 FOT MidColumbia - WTR2 - - - - 324 313 312 - - 304 296 - 375 - 359 - - 375 - 375 125 152 FOT NOB - WTR - - - - - - - - 54 56 10 99 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 123 131 122 422 113 116 116 112 111 108 560 403 571 147 353 1,149 116 857 310 Annual Additions, Short Term Resources 779 846 1,154 1,123 1,247 1,354 1,282 1,305 1,525 1,464 1,472 1,582 2,086 1,971 2,034 2,011 2,013 2,053 2,057 2,287 Total Annual Additions 933 969 1,285 1,245 1,669 1,466 1,399 1,422 1,636 1,575 1,580 2,142 2,488 2,542 2,181 2,364 3,162 2,169 2,913 2,597 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. NO-C02 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 213 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Coal Ret_WY - Gas RePower - - 285 - - - - - - - - - - (285) - - - - - - 285 - Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 CCCT - Utah-S - J 1x1 - - - - - - - - - - - - - - - - - - - 477 - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - 477 - 953 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - 200 - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - 85 - - - - - - - 85 Wind, GO - - - - 150 - - - - - - - - - - - - - 269 - 150 419 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 450 - - - - - - - - 85 - - - - 269 - 450 804 Utility Solar - PV - Utah-S - - - - - - - - - - - - - 23 153 167 210 40 208 - - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - - 1.9 - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - - 14.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 3.3 65.0 - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - 75.3 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - - 3.1 - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - - 4.8 - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 3.3 209.0 6.7 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 5 5 6 6 5 5 6 6 6 5 5 5 5 4 4 3 3 3 3 54 93 DSM, Class 2, UT 84 86 80 59 62 58 66 66 68 65 65 61 57 58 58 49 44 37 34 35 694 1,191 DSM, Class 2, WY 8 8 8 10 13 13 14 15 14 14 12 13 11 11 11 9 8 7 7 7 118 213 DSM, Class 2 Total 97 99 94 75 81 77 85 86 89 84 82 78 73 73 73 62 55 47 44 44 865 1,497 FOT Mona - SMR - - - - - - - - - - - 275 300 300 300 300 300 300 300 29 - 120 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - S-Oregon - - - - - - - - - - - - 87 22 - - - - - - - 109 Utility Solar - PV - Yakima - - - - - - - - - - - - - - 3 70 16 7 13 - - 109 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - - 2.4 - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - - 1.2 - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - - 3.7 - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 29.1 7.0 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - - 35.0 - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - - 12.8 - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - 9.1 - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - - 4.8 - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - - 111.1 7.0 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 14 22 DSM, Class 2, OR 50 46 41 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 315 479 DSM, Class 2, WA 10 10 11 8 9 9 9 9 8 8 7 6 6 5 5 4 3 3 2 2 92 135 DSM, Class 2 Total 62 58 55 46 41 37 33 33 29 27 26 25 23 23 22 21 20 19 19 18 421 637 Geothermal, Greenfield - West - - - - - - - - - - - - - 30 - - - - - - - 30 FOT COB - SMR - - - - - - - - - - - 400 400 400 400 400 400 400 400 321 - 176 FOT MidColumbia - SMR 400 400 400 393 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 399 400 FOT MidColumbia - SMR - 2 10 274 117 - 82 198 127 166 321 257 318 375 375 375 375 375 375 375 375 375 155 262 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 - 270 - 318 - - - - 296 - 287 103 400 400 374 360 25 400 - 116 176 FOT MidColumbia - WTR2 - 329 - 305 - 306 304 285 293 - 287 - 375 49 13 - - 375 3 347 182 164 FOT NOB - WTR - - - - - - - - 51 52 6 9 100 100 100 100 100 100 100 100 10 46 Existing Plant Retirements/Conversions - - 5 - (387) - - - - (82) - (762) (354) (642) (78) - (717) - (82) - Annual Additions, Long Term Resources 158 157 148 122 572 114 118 119 118 111 109 106 503 906 254 323 980 117 555 551 Annual Additions, Short Term Resources 791 1,103 887 798 899 1,004 931 952 1,165 1,104 1,112 1,845 2,153 2,124 2,088 2,049 2,035 2,075 2,078 1,673 Total Annual Additions 949 1,260 1,036 919 1,471 1,118 1,049 1,071 1,282 1,216 1,221 1,951 2,657 3,030 2,342 2,372 3,015 2,192 2,633 2,224 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. BP PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 214 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 SCCT Frame DJ - - - - - - - - - - - - - - - - - - 200 - - 200 SCCT Frame UTN - - - - - - - - - - - - 200 - - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - 85 - - - - - - 85 Wind, GO - - - - 150 - - - - - - - - - - - 46 152 - 602 150 950 Wind, UT - - - - - - - - - - - - - - - - - - - 91 - 91 Wind, WYAE - - - - 300 440 - - - - - - - - - - - - - - 740 740 Total Wind - - - - 450 440 - - - - - - - - 85 - 46 152 - 693 890 1,867 Utility Solar - PV - Utah-S - - - - - - - - - - - - 2 - 112 166 524 - - - - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - 6.9 33.9 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 171.2 43.1 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 6 6 5 5 5 5 4 4 3 3 3 3 57 96 DSM, Class 2, UT 84 58 62 59 62 68 66 66 68 65 65 61 57 58 59 49 44 37 34 35 656 1,155 DSM, Class 2, WY 8 10 11 10 13 13 14 15 14 14 12 13 12 11 11 9 8 7 7 7 122 219 DSM, Class 2 Total 97 74 79 75 81 87 85 86 89 84 82 78 74 74 74 62 55 47 44 44 835 1,470 FOT Mona - SMR - - - - - - - - - 27 27 281 300 291 300 300 300 300 281 300 3 135 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - - 150 - - 70 16 7 - - - 244 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 36.1 - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 69.1 49.1 - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 9 9 8 10 9 9 9 8 8 7 7 6 5 5 4 3 3 2 2 89 134 DSM, Class 2 Total 57 54 52 46 42 37 34 33 29 27 27 25 23 23 22 21 20 19 19 18 411 629 Geothermal, Greenfield - West - - - - - - - - - - - - 30 - - - - - - - - 30 FOT COB - SMR - - - - 23 69 - 37 191 100 161 400 400 399 400 400 400 400 400 364 42 207 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 11 375 310 375 375 372 375 375 375 375 375 375 375 375 375 375 375 375 375 294 335 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 310 322 310 - - 297 - 290 - 78 400 18 - - 393 363 294 212 198 FOT MidColumbia - WTR2 - - - - - - 308 289 - 299 - 343 375 17 375 353 352 - - 375 90 154 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 573 563 118 119 118 111 109 343 572 538 298 323 1,140 229 266 768 Annual Additions, Short Term Resources 779 842 1,150 1,119 1,220 1,253 1,180 1,201 1,415 1,355 1,362 2,000 2,128 2,082 2,068 2,028 2,027 2,068 2,019 2,307 Total Annual Additions 933 970 1,281 1,241 1,792 1,817 1,298 1,319 1,533 1,466 1,471 2,343 2,699 2,620 2,365 2,351 3,167 2,297 2,284 3,075 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. GW-1 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 215 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 SCCT Frame DJ - - - - - - - - - - - - - - - - - - 200 - - 200 SCCT Frame UTN - - - - - - - - - - - - 200 - - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - 85 - - - - - - 85 Wind, GO - - - - 150 - - - - - - - - - - - 46 152 - 602 150 950 Wind, UT - - - - - - - - - - - - - - - - - - - 91 - 91 Wind, WYAE - - - - 300 - 440 - - - - - - - - - - - - - 740 740 Total Wind - - - - 450 - 440 - - - - - - - 85 - 46 152 - 693 890 1,867 Utility Solar - PV - Utah-S - - - - - - - - - - - - 2 - 112 166 524 - - - - 805 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - 6.9 33.9 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 171.2 43.1 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 6 6 5 5 5 5 4 4 3 3 3 3 57 96 DSM, Class 2, UT 84 58 62 59 62 68 66 66 68 65 65 61 57 58 59 49 44 37 34 35 656 1,155 DSM, Class 2, WY 8 10 11 10 13 13 14 15 14 14 12 13 12 11 11 9 8 7 7 7 122 219 DSM, Class 2 Total 97 74 79 75 81 87 85 86 89 84 82 78 74 74 74 62 55 47 44 44 835 1,470 FOT Mona - SMR - - - - - - - - - 27 27 281 300 291 300 300 300 300 281 300 3 135 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - - 150 - - 70 16 7 - - - 244 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 36.1 - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 69.1 49.1 - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 9 9 8 10 9 9 9 8 8 7 7 6 5 5 4 3 3 2 2 89 134 DSM, Class 2 Total 57 54 52 46 42 37 34 33 29 27 27 25 23 23 22 21 20 19 19 18 411 629 Geothermal, Greenfield - West - - - - - - - - - - - - 30 - - - - - - - - 30 FOT COB - SMR - - - - 23 134 - 37 191 100 161 400 400 399 400 400 400 400 400 364 49 210 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 11 375 310 375 375 372 375 375 375 375 375 375 375 375 375 375 375 375 375 294 335 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 310 322 310 - - 297 - 290 - 78 42 18 353 352 18 - 294 212 178 FOT MidColumbia - WTR2 - - - - - - 308 289 - 299 - 343 375 375 375 - - 375 363 375 90 174 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 573 123 558 119 118 111 109 343 572 538 298 323 1,140 229 266 768 Annual Additions, Short Term Resources 779 842 1,150 1,119 1,220 1,319 1,180 1,201 1,415 1,355 1,362 2,000 2,128 2,082 2,068 2,028 2,027 2,068 2,019 2,307 Total Annual Additions 933 970 1,281 1,241 1,792 1,442 1,738 1,319 1,533 1,466 1,471 2,343 2,699 2,620 2,365 2,351 3,167 2,297 2,284 3,075 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. GW-2 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 216 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - 200 - - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - - - - 85 - - - 85 Wind, GO - - - - - - - - - - - - - - - - - - - 376 - 376 Wind, WYAE - - - - 300 440 760 - - - - - - - - - - - - - 1,500 1,500 Total Wind - - - - 300 440 760 - - - - - - - - - - 85 - 376 1,500 1,961 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - 163 210 18 291 118 - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - 75.3 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 89.0 125.2 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 4 4 3 3 3 3 56 95 DSM, Class 2, UT 84 58 62 59 62 58 66 66 63 65 65 61 57 57 59 49 44 37 34 35 642 1,139 DSM, Class 2, WY 8 10 11 10 13 13 14 14 14 14 12 11 11 11 11 9 8 7 7 7 121 215 DSM, Class 2 Total 97 74 79 75 81 77 85 85 82 84 82 77 73 73 74 62 55 47 43 44 819 1,450 FOT Mona - SMR - - - - - - - - - 27 27 300 295 286 300 300 300 300 300 300 3 137 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - 5 - - 142 74 16 7 - - - 244 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 36.1 - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 24.7 10.3 - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - 9.1 - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 49.7 68.4 - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 10 9 9 9 8 8 7 7 6 6 5 4 3 3 2 2 89 134 DSM, Class 2 Total 57 54 52 46 42 37 34 33 29 27 27 25 23 23 22 21 20 19 19 18 411 628 Geothermal, Greenfield - West - - - - - - - - - - - - 30 - - - - - - - - 30 FOT COB - SMR - - - - 46 97 - - 110 19 80 400 400 400 400 400 400 400 400 364 27 196 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 11 375 310 375 375 287 327 375 375 375 375 375 375 375 375 375 375 375 375 281 328 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 310 322 310 - - 297 - 291 - 71 35 15 350 - - 4 291 212 159 FOT MidColumbia - WTR2 - - - - - - 308 289 - 299 - 287 375 375 375 - 336 375 375 375 90 188 FOT NOB - WTR - - - - - - - - 53 54 8 71 100 100 100 100 100 100 100 100 11 49 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 423 554 878 118 112 111 109 245 520 537 241 324 980 180 356 568 Annual Additions, Short Term Resources 779 842 1,150 1,120 1,243 1,282 1,095 1,116 1,334 1,274 1,281 1,933 2,116 2,071 2,065 2,025 2,011 2,050 2,054 2,305 Total Annual Additions 933 970 1,281 1,241 1,665 1,836 1,973 1,234 1,446 1,385 1,390 2,179 2,636 2,608 2,306 2,349 2,991 2,230 2,410 2,873 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. GW-3 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 217 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 IC Aero UN - - - - - - - - - - - - - - - - - - - 182 - 182 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - 200 - - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - 85 - - - - - - 85 Wind, WYAE - - - - 1,200 - - - - - - - - - - - - - - - 1,200 1,200 Total Wind - - - - 1,200 - - - - - - - - - 85 - - - - - 1,200 1,285 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - 53 167 210 41 279 - - 749 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 34.8 40.5 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 123.8 90.5 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 4 4 3 3 3 3 56 95 DSM, Class 2, UT 84 58 62 59 62 58 66 66 63 65 65 61 57 57 59 49 44 37 34 35 642 1,139 DSM, Class 2, WY 8 10 11 10 13 13 14 14 14 14 12 11 11 11 11 9 8 7 7 7 121 216 DSM, Class 2 Total 97 74 79 75 81 77 85 85 82 84 82 77 73 73 74 62 55 47 44 44 819 1,450 FOT Mona - SMR - - - - - - - - - 27 27 293 300 291 300 300 300 300 300 263 3 135 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - - 83 - 68 70 16 7 13 - - 257 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 36.1 - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 69.1 49.1 - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 10 9 9 9 8 8 7 7 6 6 5 4 3 3 2 2 89 134 DSM, Class 2 Total 57 54 52 46 42 37 34 33 29 27 27 25 23 23 22 21 20 19 19 18 411 628 Geothermal, Greenfield - West - - - - - - - - - - - - 30 - - - - - - - - 30 FOT COB - SMR - - - - - 28 - - 154 63 125 400 400 400 400 400 400 400 400 357 25 196 FOT MidColumbia - SMR 399 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 11 375 310 287 375 332 372 375 375 375 375 375 375 375 375 375 375 375 375 281 328 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 331 275 310 - 310 - 289 297 - - - 400 40 390 350 - 377 4 235 209 194 FOT MidColumbia - WTR2 - - - - 322 - 308 - - 299 291 305 50 375 - - 336 - 375 375 93 152 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 1,323 114 118 118 112 111 109 295 549 537 306 323 980 117 358 256 Annual Additions, Short Term Resources 779 842 1,150 1,120 1,108 1,213 1,139 1,161 1,379 1,319 1,326 1,974 2,125 2,081 2,065 2,025 2,011 2,052 2,054 2,205 Total Annual Additions 933 970 1,281 1,241 2,431 1,327 1,258 1,279 1,491 1,430 1,435 2,268 2,675 2,617 2,371 2,349 2,991 2,169 2,412 2,461 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. GW-4 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 218 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 IC Aero UN - - - - - - - - - - - - - - - - - - - 182 - 182 SCCT Frame UTN - - - - - - - - - - - - 200 - - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - - 113 25 147 - - - 285 Wind, GO - - - - - - - - - - - - - - - - - - 448 - - 448 Wind, WYAE - - - - 1,100 - - - - - - - - - - - - - - - 1,100 1,100 Total Wind - - - - 1,100 - - - - - - - - - - 113 25 147 448 - 1,100 1,833 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - 110 528 2 161 - - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - 75.3 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 89.0 125.2 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 4 4 3 3 3 3 56 95 DSM, Class 2, UT 84 58 62 59 62 58 66 66 63 65 65 61 57 57 58 49 44 37 34 35 642 1,137 DSM, Class 2, WY 8 10 11 10 11 13 14 14 14 14 12 11 11 11 11 9 8 7 7 7 119 214 DSM, Class 2 Total 97 74 79 75 78 77 85 85 82 84 82 77 73 73 73 62 55 47 44 44 817 1,446 Battery Storage - East - - - - 80.0 - - - - - - - - - - - - - - - 80 80 FOT Mona - SMR - - - - - - - - - 27 27 300 278 269 300 300 300 300 300 263 3 133 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - 6 - - 111 100 16 8 13 - - 253 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 36.1 - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 7.7 27.3 - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - 9.1 - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 32.7 85.4 - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 10 9 9 9 8 8 7 7 6 5 5 4 3 3 2 2 88 132 DSM, Class 2 Total 57 53 52 46 42 37 33 33 29 27 27 25 23 23 22 21 20 19 19 18 410 627 Geothermal, Greenfield - West - - - - - - - - - - - - 30 - - - - - - - - 30 FOT COB - SMR - - 3 - - - - - 93 2 64 400 400 400 400 400 400 400 400 357 10 186 FOT MidColumbia - SMR 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 21 375 307 225 342 270 311 375 375 375 375 375 375 375 375 375 375 375 375 260 318 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 332 273 307 - - - 287 295 - - 284 400 19 390 350 - 15 392 248 178 194 FOT MidColumbia - WTR2 - - - - 319 308 306 - - 297 289 - 29 375 - - 349 375 - 375 123 151 FOT NOB - WTR - - - - - - - - 53 54 8 57 100 100 100 100 100 100 100 100 11 49 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 1,301 114 118 118 112 111 109 230 537 536 209 410 1,123 225 687 256 Annual Additions, Short Term Resources 781 853 1,151 1,115 1,045 1,149 1,076 1,098 1,316 1,256 1,263 1,916 2,082 2,038 2,065 2,025 2,024 2,065 2,067 2,218 Total Annual Additions 935 981 1,282 1,236 2,345 1,264 1,194 1,216 1,428 1,367 1,372 2,146 2,619 2,574 2,273 2,435 3,147 2,290 2,754 2,474 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. Battery PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 219 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 IC Aero UN - - - - - - - - - - - - - - - - - - - 182 - 182 SCCT Frame UTN - - - - - - - - - - - - 200 - - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - - 151 28 107 - - - 285 Wind, GO - - - - - - - - - - - - - - - - - - 447 - - 447 Wind, WYAE - - - - 1,100 - - - - - - - - - - - - - - - 1,100 1,100 Total Wind - - - - 1,100 - - - - - - - - - - 151 28 107 447 - 1,100 1,833 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - - 100 527 12 161 - - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - - 75.3 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 89.0 125.2 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 4 4 3 3 3 3 56 95 DSM, Class 2, UT 84 58 62 59 62 58 66 66 63 65 65 61 57 57 58 49 44 37 34 35 642 1,137 DSM, Class 2, WY 8 10 11 10 11 13 14 14 14 14 12 11 11 11 11 9 8 7 7 7 119 214 DSM, Class 2 Total 97 74 79 75 78 77 85 85 82 84 82 77 73 73 73 62 55 47 44 44 817 1,446 CAES - East - - - - 80.0 - - - - - - - - - - - - - - - 80.0 80.0 FOT Mona - SMR - - - - - - - - - 27 27 300 278 269 300 300 300 300 300 263 3 133 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - 6 - - 111 100 16 8 13 - - 253 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 36.1 - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 7.7 27.3 - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - - 9.1 - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 32.7 85.4 - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 10 9 9 9 8 8 7 7 6 5 5 4 3 3 2 2 88 132 DSM, Class 2 Total 57 53 52 46 42 37 33 33 29 27 27 25 23 23 22 21 20 19 19 18 410 627 Geothermal, Greenfield - West - - - - - - - - - - - - 30 - - - - - - - - 30 FOT COB - SMR - - 3 - - - - - 93 2 64 400 400 400 400 400 400 400 400 357 10 186 FOT MidColumbia - SMR 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 21 375 307 225 342 270 311 375 375 375 375 375 375 375 375 375 375 375 375 260 318 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 332 273 307 319 308 - - 295 - - - 400 19 390 350 349 390 17 400 211 221 FOT MidColumbia - WTR2 - - - - - - 306 287 - 297 289 284 29 375 - - - - 375 223 89 123 FOT NOB - WTR - - - - - - - - 53 54 8 57 100 100 100 100 100 100 100 100 11 49 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 1,301 114 118 118 112 111 109 230 537 536 209 437 1,125 196 687 256 Annual Additions, Short Term Resources 781 853 1,151 1,115 1,045 1,149 1,076 1,098 1,316 1,256 1,263 1,916 2,082 2,038 2,065 2,025 2,024 2,065 2,067 2,218 Total Annual Additions 935 981 1,282 1,236 2,345 1,264 1,194 1,216 1,427 1,367 1,372 2,146 2,619 2,574 2,273 2,462 3,149 2,261 2,754 2,474 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. CAES PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 220 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Expansion Resources West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - - - - 436 - - - - 436 Total CCCT - - - - - - - - - - - - - - - - 436 - - - - 436 Wind, SO - - - - - - - - - - - - - - - - - - - 500 - 500 Total Wind - - - - - - - - - - - - - - - - - - - 500 - 500 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 13 19 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 7 7 8 9 8 7 7 7 8 7 6 5 5 4 3 3 2 2 2 77 116 DSM, Class 2 Total 57 52 50 46 41 35 32 31 27 27 26 24 22 22 21 21 19 18 18 18 399 609 FOT COB - SMR - - - - - 58 180 193 182 188 207 206 400 400 400 400 333 340 348 250 80 204 FOT MidColumbia - SMR 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 162 160 306 204 368 375 170 164 198 182 177 187 338 345 352 359 375 375 375 375 229 277 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT COB - WTR - - - - - - 241 - 238 390 305 267 400 400 400 400 400 400 242 189 87 214 FOT MidColumbia - WTR 400 246 400 400 400 320 400 332 94 400 400 400 400 296 400 306 227 236 400 400 339 343 FOT MidColumbia - WTR2 146 375 177 164 301 375 55 375 375 20 24 58 269 375 276 375 375 375 375 375 236 262 FOT NOB - WTR 100 100 100 100 100 100 100 100 100 - 86 100 100 100 100 100 100 100 100 100 90 94 Existing Plant Retirements/Conversions - - - - - - - - - - - - (354) - - - (359) - - - Annual Additions, Long Term Resources 57 52 50 46 41 35 32 31 27 27 26 24 22 22 21 21 455 18 18 518 Annual Additions, Short Term Resources 1,308 1,382 1,483 1,368 1,670 1,729 1,646 1,664 1,687 1,681 1,700 1,717 2,406 2,416 2,428 2,439 2,310 2,326 2,340 2,189 Total Annual Additions 1,365 1,434 1,533 1,414 1,711 1,764 1,678 1,695 1,714 1,708 1,725 1,741 2,429 2,438 2,449 2,460 2,765 2,343 2,359 2,708 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. WCA Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - - - - 436 - - - - 436 Total CCCT - - - - - - - - - - - - - - - - 436 - - - - 436 Wind, YK - - - - 11 59 - - - - - - - - - - - - - - 70 70 Wind, SO - - - - - - - - - - - - - - - - - - - 500 - 500 Total Wind - - - - 11 59 - - - - - - - - - - - - - 500 70 570 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 13 19 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 7 7 8 9 8 7 7 7 7 7 6 5 5 4 3 3 2 2 2 77 116 DSM, Class 2 Total 57 52 50 46 41 35 32 31 27 27 26 24 22 22 21 21 19 18 18 18 399 608 FOT COB - SMR - - - - - 51 180 193 182 188 207 206 400 400 400 400 325 332 341 242 79 202 FOT MidColumbia - SMR 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 162 160 306 204 367 375 162 156 190 175 169 179 330 338 345 351 375 375 375 375 226 273 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT COB - WTR - - - - - - 241 - 238 390 291 267 400 400 400 400 400 400 235 182 87 212 FOT MidColumbia - WTR 171 246 202 400 400 313 72 324 400 38 42 75 400 400 400 400 400 228 400 400 257 286 FOT MidColumbia - WTR2 375 375 375 164 300 375 375 375 61 375 375 375 261 264 268 273 195 375 375 375 315 314 FOT NOB - WTR 100 100 100 100 100 100 100 100 100 - 100 100 100 100 100 100 100 100 100 100 90 95 Existing Plant Retirements/Conversions - - - - - - - - - - - - (354) - - - (359) - - - Annual Additions, Long Term Resources 57 52 50 46 52 94 32 31 27 27 26 24 22 22 21 21 455 18 18 518 Annual Additions, Short Term Resources 1,308 1,382 1,483 1,368 1,667 1,713 1,631 1,648 1,671 1,666 1,685 1,702 2,391 2,401 2,413 2,424 2,295 2,311 2,325 2,174 Total Annual Additions 1,365 1,434 1,533 1,414 1,719 1,807 1,662 1,679 1,699 1,692 1,710 1,726 2,414 2,423 2,434 2,445 2,750 2,328 2,344 2,693 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. WCA-RPS PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 221 Table K.10 – Final Screening Cases, Detailed Capacity Expansion Portfolios Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Wind - Repower Existing resource - - - - - - - - - - - - - - - - - - - - - - Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 CCCT - Utah-S - J 1x1 - - - - - - - - - - - - - - - - - - - 477 - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - 477 - 953 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - - 200 - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - 85 - - - - - - - 85 Wind, GO - - - - 103 - - - - - - - - - - - - - 512 - 103 615 Wind, WYAE - - - - 300 - - - - - - - - - - - - - - - 300 300 Total Wind - - - - 403 - - - - - - - - 85 - - - - 512 - 403 1,001 Utility Solar - PV - Utah-S - - - - - - - - - - - - - 88 153 167 209 40 143 - - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - - - 3.4 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 75.3 - 4.8 - - - 3.7 - - - 83.7 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - - - 3.1 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1, WY-Curtail - - - - - - - - - - - 40.7 - - - - 3.1 - - - - 43.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 205.0 9.2 4.8 - 3.4 3.1 3.7 3.1 - - 232.2 DSM, Class 2, ID 5 7 7 6 6 5 6 6 6 6 5 5 5 5 4 4 3 3 3 2 57 96 DSM, Class 2, UT 84 58 62 59 62 68 66 66 68 67 65 61 57 60 58 49 44 37 34 24 658 1,147 DSM, Class 2, WY 8 10 11 10 13 13 14 15 14 14 12 13 12 11 11 9 8 7 7 5 122 217 DSM, Class 2 Total 97 74 79 75 81 87 85 86 89 86 82 78 74 76 73 62 55 47 44 31 838 1,459 FOT Mona - SMR - - - - - - - - - 27 27 300 231 300 300 300 300 300 300 29 3 121 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Wind - Repower Existing resource - - - - - - - - - - - - - - - - - - - - - - West Wind-Repower - - - - - - - - - - - - - - - - - - - - - - Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - 436 - - - - - - - - 436 Total CCCT - - - - - - - - - - - - 436 - - - - - - - - 436 Utility Solar - PV - S-Oregon - - - - - - - - - - - - - 36 - - - - - - - 36 Utility Solar - PV - Yakima - - - - - - - - - - - - - 101 10 62 16 8 13 - - 210 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - 11.4 24.7 - - 3.3 - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - 3.8 9.2 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 84.2 33.9 - - 3.3 - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 10 9 9 9 8 8 7 6 6 5 5 4 3 3 2 2 88 132 DSM, Class 2 Total 57 53 52 46 42 37 33 33 29 27 27 25 23 23 22 22 20 19 19 18 410 627 Geothermal, Greenfield - West - - - - - - - - - - - - 30 - - - - - - - - 30 FOT COB - SMR - - 3 - 28 139 67 107 261 169 230 400 400 400 400 400 400 400 400 342 77 227 FOT MidColumbia - SMR 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 21 375 307 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 375 295 335 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 332 273 307 - 308 - 287 295 - - 38 - 54 15 - 340 381 383 334 208 181 FOT MidColumbia - WTR2 - - - - 319 - 306 - - 297 289 375 371 375 375 354 - - - - 92 153 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 526 123 118 119 118 113 109 392 606 613 258 319 980 117 734 526 Annual Additions, Short Term Resources 781 853 1,151 1,115 1,222 1,322 1,248 1,269 1,484 1,422 1,429 2,088 1,977 2,104 2,065 2,029 2,015 2,056 2,058 1,680 Total Annual Additions 935 981 1,282 1,236 1,748 1,445 1,367 1,388 1,601 1,535 1,538 2,480 2,583 2,717 2,323 2,349 2,995 2,173 2,792 2,206 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. FS-REP PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 222 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - 200 - - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - 85 - - - - - - 85 Wind, GO - - - - - - - - - - - - - - - - - - - 774 - 774 Wind, WYAE - - - - 1,100 - - - - - - - - - - - - - - - 1,100 1,100 Total Wind - - - - 1,100 - - - - - - - - - 85 - - - - 774 1,100 1,959 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - 79 167 210 41 291 13 - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - 3.1 - - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 34.8 40.5 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 123.8 90.5 4.8 - 3.4 3.1 3.7 3.1 11.6 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 4 4 3 3 3 3 56 95 DSM, Class 2, UT 84 58 62 59 62 58 66 66 63 65 65 61 57 57 59 49 44 37 34 35 642 1,139 DSM, Class 2, WY 8 10 11 10 13 13 14 14 14 14 12 11 11 11 11 9 8 7 7 7 121 216 DSM, Class 2 Total 97 74 79 75 81 77 85 85 82 84 82 77 73 73 74 62 55 47 44 44 819 1,450 FOT Mona - SMR - - - - - - - - - 27 27 300 300 291 300 300 300 300 300 300 3 137 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Utility Solar - PV - Yakima - - - - - - - - - - - 11 97 - 38 70 16 8 - - - 240 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 36.1 - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 69.1 49.1 - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 10 9 9 9 8 8 7 7 6 5 5 4 3 3 2 2 88 132 DSM, Class 2 Total 57 53 52 46 42 37 33 33 29 27 27 25 23 23 22 21 20 19 19 18 410 627 Geothermal, Greenfield - West - - - - - - - - - - - - 30 - - - - - - - - 30 FOT COB - SMR - - 3 - - 41 - 10 167 76 137 400 400 400 400 400 400 400 400 364 30 200 FOT MidColumbia - SMR 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 21 375 307 299 375 344 375 375 375 375 375 375 375 375 375 375 375 375 375 285 330 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 332 273 307 - 308 - 287 295 - - - 400 41 390 351 - 377 4 291 208 197 FOT MidColumbia - WTR2 - - - - 319 - 306 - - 297 289 312 51 375 - - 337 - 375 375 92 152 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 1,223 114 118 118 112 111 109 306 563 536 303 323 980 117 356 861 Annual Additions, Short Term Resources 781 853 1,151 1,115 1,118 1,223 1,150 1,172 1,390 1,329 1,336 1,987 2,126 2,081 2,065 2,026 2,012 2,052 2,054 2,305 Total Annual Additions 935 981 1,282 1,236 2,341 1,337 1,268 1,289 1,501 1,440 1,445 2,293 2,688 2,618 2,368 2,349 2,992 2,169 2,411 3,166 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. FS-GW4 PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 223 Capacity (MW)Resource Totals 1/ 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 10-year 20-year East Existing Plant Retirements/Conversions Craig 1 (Coal Early Retirement/Conversions)- - - - - - - - - (82) - - - - - - - - - - (82) (82) Craig 2 - - - - - - - - - - - - - - - - - - (82) - - (82) Hayden 1 - - - - - - - - - - - - - - (45) - - - - - - (45) Hayden 2 - - - - - - - - - - - - - - (33) - - - - - - (33) Cholla 4 (Coal Early Retirement/Conversions)- - - - (387) - - - - - - - - - - - - - - - (387) (387) DaveJohnston 1 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 2 - - - - - - - - - - - (106) - - - - - - - - - (106) DaveJohnston 3 - - - - - - - - - - - (220) - - - - - - - - - (220) DaveJohnston 4 - - - - - - - - - - - (330) - - - - - - - - - (330) Naughton 1 - - - - - - - - - - - - - (156) - - - - - - - (156) Naughton 2 - - - - - - - - - - - - - (201) - - - - - - - (201) Naughton 3 (Coal Early Retirement/Conversions)- - (280) - - - - - - - - - - - - - - - - - (280) (280) Gadsby 1-6 - - - - - - - - - - - - - - - - (358) - - - - (358) Expansion Resources CCCT - DJohns - J 1x1 - - - - - - - - - - - - - - - - 477 - - - - 477 Total CCCT - - - - - - - - - - - - - - - - 477 - - - - 477 SCCT Frame DJ - - - - - - - - - - - - - - - - 200 - - - - 200 SCCT Frame UTN - - - - - - - - - - - - 200 - - - - - - - - 200 Wind, Djohnston - - - - - - - - - - - - - - 85 - - - - - - 85 Wind, GO - - - - - - - - - - - - - - - - - - - 774 - 774 Wind, WYAE - - - - 1,100 - - - - - - - - - - - - - - - 1,100 1,100 Total Wind - - - - 1,100 - - - - - - - - - 85 - - - - 774 1,100 1,959 Utility Solar - PV - Utah-S - - - - - - - - - - - - - - 79 167 210 41 291 13 - 800 DSM, Class 1, ID-Cool/WH - - - - - - - - - - - - 3.4 - - - - - - 1.3 - 4.7 DSM, Class 1, ID-Curtail - - - - - - - - - - - - 1.9 - - - - - - - - 1.9 DSM, Class 1, ID-Irrigate - - - - - - - - - - - 10.9 3.9 - - 3.4 - - - 3.1 - 21.3 DSM, Class 1, UT-Cool/WH - - - - - - - - - - - 68.4 - - - - - - - - - 68.4 DSM, Class 1, UT-Curtail - - - - - - - - - - - 34.8 40.5 4.8 - - - 3.7 - 2.2 - 85.9 DSM, Class 1, UT-Irrigate - - - - - - - - - - - 3.1 - - - - - - - 3.3 - 6.3 DSM, Class 1, WY-Cool/WH - - - - - - - - - - - 4.8 - - - - - - - 2.9 - 7.7 DSM, Class 1, WY-Curtail - - - - - - - - - - - - 40.7 - - - 3.1 - - 2.0 - 45.8 DSM, Class 1, WY-Irrigate - - - - - - - - - - - 1.9 - - - - - - - - - 1.9 DSM, Class 1 Total - - - - - - - - - - - 123.8 90.5 4.8 - 3.4 3.1 3.7 - 14.7 - 243.8 DSM, Class 2, ID 5 7 7 6 6 5 5 6 5 6 5 5 5 5 4 4 3 3 3 3 56 95 DSM, Class 2, UT 84 58 62 59 62 58 66 66 63 65 65 61 57 57 59 49 44 37 34 35 642 1,139 DSM, Class 2, WY 8 10 11 10 13 13 14 14 14 14 12 11 11 11 11 9 8 7 7 7 121 216 DSM, Class 2 Total 97 74 79 75 81 77 85 85 82 84 82 77 73 73 74 62 55 47 44 44 819 1,450 FOT Mona - SMR - - - - - - - - - 27 27 294 294 284 300 300 300 300 297 300 3 136 West Existing Plant Retirements/Conversions JimBridger 1 (Coal Early Retirement/Conversions)- - - - - - - - - - - - (354) - - - - - - - - (354) JimBridger 2 (Coal Early Retirement/Conversions)- - - - - - - - - - - - - - - - (359) - - - - (359) Expansion Resources CCCT - WillamValcc - G 1x1 - - - - - - - - - - - - - 436 - - - - - - - 436 Total CCCT - - - - - - - - - - - - - 436 - - - - - - - 436 Wind, YK - - - - 57 - - - - - - - - - - - - - 239 128 57 423 Wind, SO - - - - - - - - - - - - - - - - - - 45 193 - 238 Total Wind - - - - 57 - - - - - - - - - - - - - 284 322 57 662 Utility Solar - PV - Yakima - - - - - - - - - - - 11 97 - 38 70 16 8 - - - 240 DSM, Class 1, CA-Cool/WH - - - - - - - - - - - 2.4 - - - - - - - - - 2.4 DSM, Class 1, CA-Curtail - - - - - - - - - - - 1.2 - - - - - - - - - 1.2 DSM, Class 1, CA-Irrigate - - - - - - - - - - - 3.7 - - - - - - - - - 3.7 DSM, Class 1, OR-Cool/WH - - - - - - - - - - - - 36.1 - 3.3 - - - - - - 39.4 DSM, Class 1, OR-Curtail - - - - - - - - - - - 35.0 - - - - - - - - - 35.0 DSM, Class 1, OR-Irrigate - - - - - - - - - - - 12.8 - - - - - - - - - 12.8 DSM, Class 1, WA-Cool/WH - - - - - - - - - - - - 13.0 - - - - - - - - 13.0 DSM, Class 1, WA-Curtail - - - - - - - - - - - 9.1 - - - - - - - - - 9.1 DSM, Class 1, WA-Irrigate - - - - - - - - - - - 4.8 - - - - - - - - - 4.8 DSM, Class 1 Total - - - - - - - - - - - 69.1 49.1 - 3.3 - - - - - - 121.5 DSM, Class 2, CA 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 13 21 DSM, Class 2, OR 46 44 42 37 31 26 23 23 20 19 18 17 17 16 16 17 15 15 16 16 310 474 DSM, Class 2, WA 10 8 9 8 10 9 9 9 8 8 7 7 6 5 5 4 3 3 2 2 88 132 DSM, Class 2 Total 57 53 52 46 42 37 33 33 29 27 27 25 23 23 22 21 20 19 19 18 410 627 Geothermal, Greenfield - West - - - - - - - - - - - - 30 - - - - - - - - 30 FOT COB - SMR - - 3 - - 34 - 3 161 70 131 400 400 400 394 394 394 394 369 290 27 192 FOT MidColumbia - SMR 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 FOT MidColumbia - SMR - 2 - 21 375 307 293 375 338 375 375 375 375 375 375 375 375 375 375 375 375 375 283 329 FOT NOB - SMR 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 FOT MidColumbia - WTR 281 332 273 307 313 301 - - 288 - 282 306 69 34 9 - 330 371 342 218 210 203 FOT MidColumbia - WTR2 - - - - - - 300 281 - 291 - - 375 375 375 344 - - - 375 87 136 FOT NOB - WTR - - - - - - - - 53 54 8 100 100 100 100 100 100 100 100 100 11 51 Existing Plant Retirements/Conversions - - (280) - (387) - - - - (82) - (762) (354) (357) (78) - (717) - (82) - Annual Additions, Long Term Resources 154 128 131 122 1,280 114 118 118 112 111 109 306 563 536 303 323 980 117 637 1,186 Annual Additions, Short Term Resources 781 853 1,151 1,115 1,106 1,211 1,137 1,159 1,377 1,317 1,324 1,975 2,113 2,069 2,053 2,013 1,999 2,039 1,982 2,158 Total Annual Additions 935 981 1,282 1,236 2,385 1,325 1,255 1,277 1,489 1,428 1,433 2,281 2,676 2,605 2,355 2,336 2,979 2,157 2,619 3,343 1/ Front office transaction amounts reflect one-year transaction periods, are not additive, and are reported as a 10/20-year annual average. FS-R1c PACIFICORP – 2017 IRP APPENDIX K – DETAIL CAPACITY EXPANSION RESULTS 224 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 225 APPENDIX L – STOCHASTIC PRODUCTION COST SIMULATION RESULTS Introduction This appendix reports additional results for the Monte Carlo production cost simulations conducted with the Planning and Risk (PaR) model for the core, sensitivity and final screening cases. These results supplement the data presented in Volume I, Chapter 8 (Modeling and Portfolio Selection Results) of the IRP document. The results presented include the following: Statistics of the stochastic simulation results Components of portfolios’ present value revenue requirements (PVRR) Energy-not-served Customer rate impact of portfolios in the final screen as compared with the preferred portfolio Loss of load probability of the preferred portfolio There are seven Regional Haze cases, eleven core cases, twenty sensitivity cases, and four final screening cases. Table L.1 – Stochastic Mean PVRR by Price Scenario, Regional Haze Cases PVRR ($m) Low Gas, MC A Med Gas, MC A High Gas, MC A Low Gas, MC B Med Gas, MC B High Gas, MC B Ref. 23,979 24,553 26,760 24,048 24,559 26,833 RH-1 22,840 23,453 25,654 22,931 23,477 25,827 RH-2 22,934 23,671 26,346 22,898 23,655 26,366 RH-3 22,953 23,593 25,956 22,981 23,593 26,046 RH-4 23,342 23,949 26,126 23,429 23,970 26,274 RH-5 22,762 23,446 26,088 22,730 23,430 26,059 RH-6 23,624 24,278 26,642 23,626 24,266 26,670 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 226 Table L.2 – Stochastic Mean PVRR by Price Scenario, Core Cases PVRR ($m) Low Gas, MC A Med Gas, MC A High Gas, MC A Low Gas, MC B Med Gas, MC B High Gas, MC B OP-1 22,763 23,444 25,988 22,730 23,430 26,020 OP-NT3 22,761 23,407 25,716 22,724 23,388 25,722 OP-REP 22,719 23,350 25,573 22,686 23,333 25,590 OP-GW4 23,069 23,608 25,400 23,035 23,584 25,413 FR-1 23,257 23,892 26,251 23,220 23,873 26,239 FR-2 23,820 24,485 27,003 23,783 24,467 26,995 RE-1a 22,819 23,431 25,651 22,783 23,449 25,656 RE-1b 22,772 23,395 25,632 22,737 23,413 25,650 RE-1c 22,868 23,462 25,613 22,832 23,444 25,627 RE-2 22,828 23,422 25,567 22,795 23,410 25,588 DLC-1 22,878 23,475 25,673 22,842 23,458 25,667 Table L.3 – Stochastic Mean PVRR by Price Scenario, Sensitivity Cases PVRR ($m) Low Gas, MC A Med Gas, MC A High Gas, MC A Low Gas, MC B Med Gas, MC B High Gas, MC B RH2a 22,842 23,558 26,149 22,806 23,542 26,167 CPP-C 22,813 23,513 26,274 22,777 23,505 26,490 CPP-D 22,699 23,364 25,667 22,661 23,330 25,663 FOT-1 23,048 23,681 26,061 23,011 23,663 26,067 CO2-1 23,791 24,306 25,620 23,748 24,261 25,667 GW1 23,321 23,890 25,841 23,283 23,867 25,846 GW2 23,667 24,236 26,194 23,629 24,212 26,199 GW3 24,214 24,723 26,440 24,176 24,696 26,449 GW4 23,055 23,611 25,480 23,020 23,587 25,489 WCA 6,767 7,090 8,261 6,739 7,066 8,225 WCA-RPS 6,789 7,102 8,241 6,762 7,079 8,207 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 227 Table L.4 – Stochastic Mean PVRR by Price Scenario, Final Screening Cases PVRR ($m) Low Gas, MC A Med Gas, MC A High Gas, MC A Low Gas, MC B Med Gas, MC B High Gas, MC B Ref. 23,979 24,553 26,760 24,048 24,559 26,833 RH-1 22,840 23,453 25,654 22,931 23,477 25,827 RH-2 22,934 23,671 26,346 22,898 23,655 26,366 RH-3 22,953 23,593 25,956 22,981 23,593 26,046 RH-4 23,342 23,949 26,126 23,429 23,970 26,274 RH-5 22,762 23,446 26,088 22,730 23,430 26,059 RH-6 23,624 24,278 26,642 23,626 24,266 26,670 Table L.5 – Stochastic Risk Results, Regional Haze Cases – Low Gas, MC A Low Gas, MC A PVRR ($m) Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs Ref. 123 23,818 24,097 24,272 15,464 RH-1 118 22,688 22,959 23,134 15,584 RH-2 128 22,771 23,052 23,225 15,638 RH-3 119 22,809 23,107 23,244 15,646 RH-4 121 23,199 23,467 23,629 15,598 RH-5 119 22,614 22,882 23,051 15,681 RH-6 123 23,460 23,738 23,902 15,659 Table L.6 – Stochastic Risk Results, Regional Haze Cases – Medium Gas, MC A Medium Gas, MC A PVRR ($m) Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs Ref. 138 24,375 24,682 24,869 16,086 RH-1 134 23,282 23,606 23,770 16,246 RH-2 145 23,482 23,804 23,987 16,421 RH-3 135 23,444 23,751 23,922 16,335 RH-4 136 23,784 24,086 24,262 16,253 RH-5 136 23,272 23,596 23,758 16,412 RH-6 140 24,119 24,425 24,605 16,386 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 228 Table L.7 – Stochastic Risk Results, Regional Haze Cases – High Gas, MC A High Gas, MC A PVRR ($m) Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs Ref. 205 26,438 26,990 27,130 18,376 RH-1 197 25,383 25,882 26,036 18,562 RH-2 210 26,014 26,568 26,730 19,199 RH-3 201 25,703 26,193 26,380 18,822 RH-4 199 25,860 26,437 26,500 18,551 RH-5 199 25,790 26,259 26,478 19,161 RH-6 206 26,390 27,019 27,059 18,890 Table L.8 – Stochastic Risk Results, Regional Haze Cases – Low Gas, MC B Low Gas, MC B PVRR ($m) Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs Ref. 123 23,893 24,174 24,347 15,525 RH-1 121 22,776 23,064 23,220 15,687 RH-2 127 22,737 23,007 23,188 15,598 RH-3 118 22,845 23,135 23,275 15,673 RH-4 123 23,287 23,576 23,721 15,697 RH-5 118 22,585 22,854 23,018 15,643 RH-6 121 23,487 23,755 23,921 15,675 Table L.9 – Stochastic Risk Results, Regional Haze Cases – Medium Gas, MC B Medium Gas, MC B PVRR ($m) Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs Ref. 137 24,384 24,698 24,878 16,078 RH-1 132 23,315 23,622 23,818 16,260 RH-2 144 23,469 23,790 23,969 16,399 RH-3 134 23,432 23,758 23,936 16,329 RH-4 133 23,795 24,104 24,289 16,258 RH-5 135 23,259 23,571 23,743 16,393 RH-6 139 24,108 24,412 24,593 16,366 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 229 Table L.10 – Stochastic Risk Results, Regional Haze Cases – High Gas, MC B High Gas, MC B PVRR ($m) Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs Ref. 195 26,517 27,168 27,220 18,424 RH-1 189 25,531 26,175 26,240 18,724 RH-2 208 26,094 26,577 26,751 19,219 RH-3 195 25,806 26,251 26,481 18,893 RH-4 190 26,002 26,597 26,674 18,676 RH-5 198 25,743 26,239 26,449 19,127 RH-6 202 26,435 26,929 27,091 18,912 Table L.11 – Stochastic Risk Results, Core Cases – Low Gas, MC A PVRR ($m) Low Gas, MC A Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs OP-1 119 22,615 22,883 23,051 15,681 OP-NT3 121 22,606 22,885 23,054 15,557 OP-REP 118 22,573 22,843 23,002 15,395 OP-GW4 120 22,924 23,196 23,363 14,891 FR-1 119 23,107 23,391 23,547 15,528 FR-2 97 23,668 23,930 23,978 15,459 RE-1a 118 22,671 22,948 23,103 15,318 RE-1b 116 22,628 22,892 23,051 15,360 RE-1c 117 22,716 22,996 23,154 15,254 RE-2 117 22,680 22,955 23,108 15,246 DLC-1 122 22,715 23,014 23,169 15,318 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 230 Table L.12 – Stochastic Risk Results, Core Cases – Medium Gas, MC A PVRR ($m) Medium Gas, MC A Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs OP-1 136 23,270 23,593 23,756 16,414 OP-NT3 137 23,234 23,558 23,730 16,255 OP-REP 133 23,185 23,500 23,659 16,074 OP-GW4 135 23,440 23,753 23,919 15,473 FR-1 135 23,721 24,037 24,203 16,211 FR-2 114 24,300 24,624 24,669 16,167 RE-1a 133 23,269 23,581 23,741 15,978 RE-1b 131 23,239 23,547 23,701 16,031 RE-1c 132 23,293 23,620 23,772 15,894 RE-2 132 23,255 23,577 23,728 15,888 DLC-1 138 23,292 23,624 23,787 15,964 Table L.13 – Stochastic Risk Results, Core Cases – High Gas, MC A PVRR ($m) High Gas, MC A Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs OP-1 201 25,695 26,191 26,370 19,067 OP-NT3 201 25,419 25,933 26,104 18,678 OP-REP 195 25,266 25,776 25,943 18,414 OP-GW4 198 25,146 25,660 25,778 17,373 FR-1 198 25,971 26,474 26,627 18,677 FR-2 189 26,704 27,209 27,361 18,833 RE-1a 196 25,379 25,861 26,030 18,306 RE-1b 196 25,346 25,858 25,999 18,375 RE-1c 195 25,313 25,820 25,992 18,154 RE-2 195 25,294 25,776 25,938 18,144 DLC-1 203 25,388 25,880 26,059 18,273 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 231 Table L.14 – Stochastic Risk Results, Core Cases – Low Gas, MC B PVRR ($m) Low Gas, MC B Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs OP-1 118 22,585 22,854 23,018 15,643 OP-NT3 119 22,575 22,842 23,016 15,516 OP-REP 116 22,535 22,810 22,967 15,357 OP-GW4 119 22,894 23,161 23,327 14,854 FR-1 118 23,068 23,346 23,507 15,487 FR-2 96 23,632 23,885 23,938 15,418 RE-1a 116 22,643 22,920 23,066 15,276 RE-1b 115 22,600 22,856 23,015 15,321 RE-1c 115 22,691 22,953 23,117 15,212 RE-2 115 22,655 22,927 23,072 15,207 DLC-1 121 22,684 22,977 23,131 15,278 Table L.15 – Stochastic Risk Results, Core Cases – Medium Gas, MC B PVRR ($m) Medium Gas, MC B Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs OP-1 135 23,259 23,571 23,743 16,393 OP-NT3 136 23,219 23,538 23,709 16,226 OP-REP 132 23,164 23,470 23,641 16,053 OP-GW4 134 23,424 23,722 23,898 15,448 FR-1 134 23,696 24,017 24,188 16,187 FR-2 113 24,296 24,600 24,649 16,146 RE-1a 133 23,289 23,595 23,760 15,989 RE-1b 131 23,260 23,551 23,719 16,041 RE-1c 131 23,280 23,598 23,755 15,869 RE-2 131 23,248 23,557 23,714 15,868 DLC-1 138 23,283 23,606 23,773 15,943 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 232 Table L.16 – Stochastic Risk Results, Core Cases – High Gas, MC B PVRR ($m) High Gas, MC B Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs OP-1 199 25,708 26,224 26,399 19,093 OP-NT3 197 25,410 25,934 26,104 18,666 OP-REP 191 25,329 25,790 25,957 18,408 OP-GW4 197 25,155 25,669 25,787 17,378 FR-1 196 25,952 26,447 26,608 18,663 FR-2 187 26,705 27,232 27,360 18,819 RE-1a 192 25,396 25,858 26,024 18,296 RE-1b 191 25,363 25,868 26,010 18,375 RE-1c 192 25,356 25,831 25,996 18,155 RE-2 192 25,306 25,793 25,959 18,149 DLC-1 201 25,389 25,874 26,044 18,265 Table L.17 – Stochastic Risk Results, Sensitivity Cases – Low Gas, MC A PVRR ($m) Low Gas, MC A Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs RH2a 119 22,982 23,284 23,420 15,854 CPP-C 121 22,661 22,956 23,082 15,585 CPP-D 122 22,532 22,832 22,992 15,739 FOT-1 117 22,894 23,185 23,322 15,496 CO2-1 134 23,637 23,968 24,075 15,913 GW1 118 23,165 23,449 23,611 15,091 GW2 124 23,513 23,815 23,963 15,150 GW3 116 24,065 24,342 24,493 14,719 GW4 119 22,906 23,182 23,344 14,993 WCA 82 6,678 6,871 6,972 4,970 WCA-RPS 81 6,700 6,899 6,991 4,910 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 233 Table L.18 – Stochastic Risk Results, Sensitivity Cases – Medium Gas, MC A PVRR ($m) Medium Gas, MC A Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs RH2a 136 24,015 24,352 24,499 16,954 CPP-C 139 23,332 23,652 23,808 16,333 CPP-D 138 23,186 23,505 23,679 16,449 FOT-1 133 23,502 23,844 23,990 16,177 CO2-1 138 24,167 24,472 24,584 16,422 GW1 133 23,721 24,050 24,202 15,689 GW2 140 24,058 24,400 24,561 15,737 GW3 130 24,554 24,878 25,022 15,258 GW4 134 23,439 23,766 23,928 15,523 WCA 95 6,981 7,220 7,300 5,312 WCA-RPS 94 6,996 7,231 7,309 5,241 Table L.19 – Stochastic Risk Results, Sensitivity Cases – High Gas, MC A PVRR ($m) High Gas, MC A Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs RH2a 200 28,092 28,631 28,768 21,249 CPP-C 207 26,025 26,458 26,630 19,197 CPP-D 209 25,358 25,991 26,074 18,868 FOT-1 199 25,780 26,271 26,450 18,670 CO2-1 193 25,348 25,847 25,996 17,802 GW1 196 25,565 26,079 26,235 17,767 GW2 202 25,912 26,504 26,578 17,824 GW3 191 26,179 26,667 26,804 17,090 GW4 197 25,224 25,764 25,893 17,581 WCA 119 8,118 8,431 8,458 6,495 WCA-RPS 117 8,113 8,403 8,433 6,391 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 234 Table L.20 – Stochastic Risk Results, Sensitivity Cases – Low Gas, MC B PVRR ($m) Low Gas, MC B Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs RH2a 118 22,985 23,275 23,415 15,847 CPP-C 120 22,584 22,872 22,992 15,489 CPP-D 120 22,496 22,789 22,951 15,698 FOT-1 116 22,858 23,141 23,283 15,455 CO2-1 134 23,526 23,848 23,960 15,796 GW1 117 23,134 23,413 23,571 15,051 GW2 123 23,481 23,769 23,921 15,108 GW3 115 24,034 24,309 24,453 14,679 GW4 118 22,876 23,148 23,307 14,956 WCA 82 6,644 6,841 6,944 4,941 WCA-RPS 81 6,688 6,870 6,965 4,882 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 235 Table L.21 – Stochastic Risk Results, Sensitivity Cases – Medium Gas, MC B PVRR ($m) Medium Gas, MC B Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs RH2a 135 23,360 23,701 23,856 16,296 LD-1 133 23,534 23,827 23,997 16,270 LD-2 124 21,490 21,801 21,940 15,210 LD-3 146 25,016 25,382 25,559 17,690 PG-1 136 23,417 23,745 23,919 16,416 PG-2 133 22,985 23,300 23,458 16,042 CPP-C 138 23,276 23,576 23,739 16,253 CPP-D 137 23,146 23,476 23,654 16,418 FOT-1 132 23,489 23,822 23,972 16,155 CO2-1 138 24,046 24,344 24,472 16,309 NO-CO2 143 23,010 23,333 23,510 16,164 BP 140 23,316 23,643 23,816 16,407 GW1 132 23,696 24,021 24,182 15,677 GW2 139 24,041 24,376 24,540 15,730 GW3 129 24,532 24,850 24,995 15,244 GW4 133 23,422 23,740 23,911 15,567 Battery 132 23,322 23,629 23,795 15,344 CAES 131 23,274 23,598 23,749 15,334 WCA 93 6,961 7,178 7,279 5,285 WCA-RPS 92 6,997 7,197 7,289 5,215 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 236 Table L.22 – Stochastic Risk Results, Sensitivity Cases – High Gas, MC B PVRR ($m) High Gas, MC B Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs RH2a 199 28,368 28,904 29,036 21,521 CPP-C 200 26,161 26,589 26,774 19,256 CPP-D 207 25,349 25,982 26,071 18,855 FOT-1 196 25,799 26,272 26,441 18,668 CO2-1 191 25,307 25,906 25,971 17,774 GW1 195 25,557 26,083 26,238 17,771 GW2 201 25,929 26,511 26,583 17,825 GW3 189 26,189 26,676 26,808 17,093 GW4 196 25,213 25,745 25,876 17,568 WCA 117 8,083 8,397 8,420 6,456 WCA-RPS 116 8,080 8,373 8,398 6,353 Table L.23 – Stochastic Risk Results, Final Screening Cases, Low Gas, MC A PVRR ($m) Low Gas, MC A Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs FS-REP 121 22,586 22,868 23,026 15,424 FS-GW4 121 22,671 22,964 23,107 14,852 FS-R1c 118 22,697 22,971 23,141 14,754 FS-R2 121 22,675 22,958 23,107 14,793 Table L.24 – Stochastic Risk Results, Final Screening Cases, Medium Gas, MC A PVRR ($m) Medium Gas, MC A Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs FS-REP 136 23,198 23,514 23,682 16,105 FS-GW4 136 23,182 23,510 23,660 15,433 FS-R1c 134 23,190 23,511 23,677 15,318 FS-R2 136 23,184 23,500 23,652 15,364 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 237 Table L.25 – Stochastic Risk Results, Final Screening Cases, High Gas, MC A PVRR ($m) High Gas, MC A Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs FS-REP 201 25,337 25,832 25,975 18,460 FS-GW4 199 24,865 25,388 25,524 17,323 FS-R1c 197 24,830 25,435 25,476 17,153 FS-R2 199 24,822 25,346 25,478 17,221 Table L.26 – Stochastic Risk Results, Final Screening Cases, Low Gas, MC B PVRR ($m) Low Gas, MC B Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs FS-REP 119 22,556 22,831 22,987 15,385 FS-GW4 120 22,642 22,919 23,070 14,816 FS-R1c 117 22,668 22,941 23,105 14,718 FS-R2 120 22,645 22,926 23,070 14,756 Table L.27 – Stochastic Risk Results, Final Screening Cases, Medium Gas, MC B PVRR ($m) Medium Gas, MC B Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs FS-REP 135 23,184 23,484 23,662 16,081 FS-GW4 136 23,164 23,486 23,639 15,409 FS-R1c 133 23,172 23,483 23,657 15,300 FS-R2 136 23,163 23,472 23,631 15,341 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 238 Table L.28 – Stochastic Risk Results, Final Screening Cases, High Gas, MC B PVRR ($m) High Gas, MC B Standard Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Costs FS-REP 197 25,361 25,837 25,988 18,450 FS-GW4 198 24,876 25,391 25,532 17,326 FS-R1c 196 24,842 25,442 25,487 17,163 FS-R2 198 24,831 25,350 25,484 17,222 Table L.29 – Stochastic Risk Adjusted PVRR by Price Scenario, Regional Haze Cases PVRR ($m) Low Gas MC A Med Gas MC A High Gas MC A Low Gas MC B Med Gas MC B High Gas MC B Ref. 25,192 25,797 28,117 25,265 25,803 28,194 RH-1 23,997 24,642 26,956 24,092 24,668 27,139 RH-2 24,095 24,871 27,683 24,058 24,853 27,703 RH-3 24,116 24,789 27,275 24,145 24,789 27,370 RH-4 24,523 25,162 27,451 24,615 25,185 27,607 RH-5 23,915 24,634 27,412 23,881 24,618 27,382 RH-6 24,819 25,508 27,995 24,822 25,496 28,025 Table L.30 – Stochastic Risk Adjusted PVRR by Price Scenario, Core Cases PVRR ($m) Low Gas MC A Med Gas MC A High Gas MC A Low Gas MC B Med Gas MC B High Gas MC B OP-1 23,915 24,632 27,306 23,881 24,618 27,339 OP-NT3 23,913 24,593 27,021 23,875 24,573 27,028 OP-REP 23,870 24,533 26,870 23,834 24,515 26,888 OP-GW4 24,238 24,804 26,689 24,201 24,779 26,702 FR-1 24,434 25,103 27,582 24,395 25,083 27,570 FR-2 25,019 25,718 28,371 24,980 25,699 28,363 RE-1a 23,974 24,618 26,953 23,937 24,637 26,958 RE-1b 23,924 24,580 26,932 23,887 24,599 26,950 RE-1c 24,026 24,650 26,913 23,988 24,632 26,927 RE-2 23,984 24,609 26,864 23,948 24,595 26,886 DLC-1 24,036 24,664 26,976 23,998 24,647 26,969 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 239 Table L.31 – Stochastic Risk Adjusted PVRR by Price Scenario, Sensitivity Cases PVRR ($m) Low Gas MC A Med Gas MC A High Gas MC A Low Gas MC B Med Gas MC B High Gas MC B RH2a 24,013 24,783 27,588 23,976 24,735 27,619 LD-1 24,896 LD-2 22,757 LD-3 26,507 PG-1 24,794 PG-2 24,330 CPP-C 23,967 24,703 27,605 23,926 24,691 27,829 CPP-D 23,848 24,548 26,971 23,809 24,513 26,966 FOT-1 24,215 24,881 27,384 24,176 24,862 27,389 CO2-1 24,994 25,535 26,919 24,946 25,484 26,966 NO-CO2 24,369 BP 24,686 GW1 24,501 25,100 27,153 24,462 25,076 27,158 GW2 24,865 25,464 27,523 24,825 25,439 27,528 GW3 25,439 25,974 27,780 25,399 25,946 27,789 GW4 24,223 24,808 26,775 24,185 24,783 26,782 Battery 24,672 CAES 24,628 WCA 7,116 7,456 8,684 7,087 7,430 8,646 WCA-RPS 7,139 7,468 8,662 7,110 7,443 8,627 Table L.32 – Stochastic Risk Adjusted PVRR by Price Scenario, Final Screening Cases PVRR ($m) Low Gas MC A Med Gas MC A High Gas MC A Low Gas MC B Med Gas MC B High Gas MC B FS-REP 23,892 24,556 26,915 23,854 24,536 26,928 FS-GW4 23,976 24,538 26,418 23,939 24,513 26,428 FS-R1c 24,005 24,549 26,369 23,969 24,525 26,383 FS-R2 23,977 24,531 26,372 23,940 24,506 26,383 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 240 Table L.33 – Carbon Dioxide Emissions by Price Scenario, Regional Haze Cases Thousand tons Low Gas MC A Med Gas MC A High Gas MC A Low Gas MC B Med Gas MC B High Gas MC B Ref. 777,629 792,139 822,316 746,112 771,917 807,893 RH-1 778,296 796,129 832,155 747,953 770,068 810,428 RH-2 740,349 760,516 789,876 731,639 746,202 782,057 RH-3 765,552 784,124 815,564 741,886 765,080 800,197 RH-4 778,761 797,502 833,982 748,802 772,180 814,146 RH-5 761,055 778,905 794,102 750,003 763,392 791,235 RH-6 769,111 790,454 823,815 750,212 774,962 815,909 Table L.34 – Carbon Dioxide Emissions by Price Scenario, Core Cases Thousand tons Low Gas MC A Med Gas MC A High Gas MC A Low Gas MC B Med Gas MC B High Gas MC B OP-1 761,704 779,805 807,022 750,003 763,392 797,073 OP-NT3 752,088 770,091 805,130 742,449 755,898 798,248 OP-REP 751,414 770,912 808,128 740,165 756,131 800,948 OP-GW4 729,100 754,628 799,689 720,898 742,897 796,752 FR-1 748,949 767,334 797,491 740,031 752,705 791,557 FR-2 758,938 776,901 803,494 749,934 761,926 796,269 RE-1a 744,406 762,430 795,949 734,788 748,177 789,525 RE-1b 752,346 771,202 806,636 742,328 756,734 799,467 RE-1c 747,267 766,006 800,317 737,728 751,818 793,791 RE-2 751,162 769,348 804,314 741,245 755,066 797,294 DLC-1 743,323 761,665 792,462 734,533 747,387 787,203 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 241 Table L.35 – Carbon Dioxide Emissions by Price Scenario, Sensitivity Cases Thousand tons Low Gas MC A Med Gas MC A High Gas MC A Low Gas MC B Med Gas MC B High Gas MC B RH2a 736,327 755,384 784,856 727,604 740,985 776,869 LD-1 761,575 LD-2 753,141 LD-3 768,550 PG-1 760,451 PG-2 756,276 CPP-C 762,993 772,981 791,975 750,783 753,561 770,192 CPP-D 772,053 793,785 832,451 763,993 783,373 829,399 FOT-1 754,305 772,805 800,512 745,459 758,254 793,920 CO2-1 611,462 669,010 797,827 604,190 660,142 791,631 NO-CO2 790,322 BP 767,893 GW1 741,560 764,748 806,382 733,200 752,041 802,801 GW2 742,726 765,925 807,538 734,339 752,954 803,467 GW3 728,679 754,860 801,057 720,557 743,122 798,561 GW4 732,726 757,439 801,200 724,538 745,567 798,313 Battery 744,571 CAES 744,830 WCA 186,112 201,116 220,945 183,590 198,186 220,099 WCA-RPS 185,814 200,791 220,609 183,288 197,860 219,764 Table L.36 – Carbon Dioxide Emissions by Price Scenario, Final Screening Cases Thousand tons Low Gas MC A Med Gas MC A High Gas MC A Low Gas MC B Med Gas MC B High Gas MC B FS-REP 751,656 770,177 806,095 742,090 756,079 799,221 FS-GW4 731,108 756,103 800,457 722,965 744,328 797,681 FS-R1c 730,427 755,499 799,914 722,284 743,734 797,140 FS-R2 729,953 755,491 800,937 721,857 743,727 798,200 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 242 Table L.37 – Energy Not Served, Regional Haze Cases, Low Gas GWh Low Gas, MC A Low Gas, MC B Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Ref. 13.7 33.4 14.2 33.4 RH-1 11.5 31.2 12.4 32.4 RH-2 11.9 34.4 12.2 34.5 RH-3 11.2 30.5 11.4 30.3 RH-4 11.5 30.4 12.3 31.1 RH-5 11.5 30.2 11.7 30.3 RH-6 12.0 30.9 12.3 30.9 Table L.38 – Energy Not Served, Regional Haze Cases, Medium Gas GWh Medium Gas, MC A Medium Gas, MC B Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Ref. 13.3 33.4 13.9 33.8 RH-1 11.1 31.0 11.6 31.3 RH-2 11.5 34.0 12.0 34.3 RH-3 10.8 30.2 11.3 30.6 RH-4 11.1 30.2 11.6 30.5 RH-5 11.1 30.1 11.6 30.5 RH-6 11.7 30.7 12.3 31.1 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 243 Table L.39 – Energy Not Served, Regional Haze Cases, High Gas GWh High Gas, MC A High Gas, MC B Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Ref. 14.5 33.8 14.9 34.4 RH-1 12.3 31.6 12.5 31.8 RH-2 12.6 35.1 12.9 35.8 RH-3 11.9 30.8 12.1 30.9 RH-4 12.2 30.6 12.5 30.9 RH-5 12.2 30.7 12.4 30.8 RH-6 12.9 31.3 13.3 31.8 Table L.40 – Energy Not Served, Core Cases, Low Gas GWh Low Gas MC A Low Gas, MC B Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 OP-1 11.5 30.2 11.7 30.3 OP-NT3 12.1 31.4 12.4 31.3 OP-REP 11.0 30.9 11.3 30.9 OP-GW4 11.0 30.3 11.3 30.5 FR-1 12.4 31.4 12.7 31.5 FR-2 2.8 8.2 3.0 8.3 RE-1a 12.1 31.2 12.4 31.4 RE-1b 10.9 29.8 11.2 29.9 RE-1c 11.2 30.6 11.5 30.5 RE-2 11.2 30.2 11.5 30.2 DLC-1 12.8 32.1 13.1 32.1 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 244 Table L.41 – Energy Not Served, Core Cases, Medium Gas GWh Medium Gas, MC A Medium Gas, MC B Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 OP-1 11.1 30.1 11.6 30.5 OP-NT3 11.8 31.0 12.3 31.4 OP-REP 10.7 30.7 11.2 31.0 OP-GW4 10.8 30.0 11.3 30.5 FR-1 12.0 31.1 12.6 31.5 FR-2 2.8 8.1 3.1 8.2 RE-1a 11.7 31.0 12.3 31.4 RE-1b 10.6 29.7 11.1 30.1 RE-1c 10.8 30.2 11.4 30.5 RE-2 10.8 29.9 11.4 30.3 DLC-1 12.5 31.7 13.0 32.1 Table L.42 – Energy Not Served, Core Cases, High Gas GWh High Gas, MC A High Gas, MC B Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 OP-1 12.2 30.7 12.4 30.8 OP-NT3 13.0 31.5 13.2 31.6 OP-REP 11.8 31.3 12.1 31.4 OP-GW4 12.0 30.7 12.2 30.8 FR-1 13.1 31.8 13.2 31.7 FR-2 3.1 8.4 3.1 8.5 RE-1a 12.9 31.7 13.1 32.0 RE-1b 11.7 30.1 12.0 30.3 RE-1c 12.0 30.7 12.2 30.8 RE-2 12.0 30.4 12.2 30.6 DLC-1 13.7 32.3 13.8 32.5 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 245 Table L.43 – Energy Not Served, Sensitivity Cases, Low Gas GWh Low Gas, MC A Low Gas, MC B Average Annual Energy Not Served 2017 - 2036 Upper Tail Mean Energy Not Served Cumulative Total 2017 - 2036 Average Annual Energy Not Served 2017 - 2036 Upper Tail Mean Energy Not Served Cumulative Total 2017 - 2036 RH2a 11.2 30.5 11.5 30.5 CPP-C 13.3 32.0 13.4 32.0 CPP-D 12.3 31.9 12.6 31.9 FOT-1 11.9 30.9 12.2 31.0 CO2-1 14.8 38.4 14.8 38.4 GW1 11.2 30.4 11.5 30.5 GW2 11.7 30.6 11.9 30.9 GW3 10.9 30.3 11.2 30.6 GW4 11.0 31.0 11.3 31.3 WCA 15.6 39.2 15.9 39.4 WCA-RPS 15.6 39.2 15.9 39.4 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 246 Table L.44 – Energy Not Served, Sensitivity Cases, Medium Gas GWh Medium Gas, MC A Medium Gas, MC B Average Annual Energy Not Served 2017 - 2036 Upper Tail Mean Energy Not Served Cumulative Total 2017 - 2036 Average Annual Energy Not Served 2017 - 2036 Upper Tail Mean Energy Not Served Cumulative Total 2017 - 2036 RH2a 10.8 30.1 11.4 30.5 LD-1 11.8 31.4 LD-2 9.9 27.5 LD-3 16.1 36.6 PG-1 13.3 32.9 PG-2 10.5 28.3 CPP-C 12.8 31.8 13.1 32.0 CPP-D 12.1 31.5 12.6 31.9 FOT-1 11.5 30.6 12.1 31.0 CO2-1 13.1 34.1 13.2 34.0 NO-CO2 9.9 29.2 BP 12.1 31.4 GW1 11.0 30.1 11.5 30.5 GW2 11.4 30.3 11.9 30.7 GW3 10.7 30.1 11.3 30.6 GW4 10.8 30.7 11.3 31.3 Battery 11.6 31.7 CAES 11.5 31.2 WCA 14.8 38.9 15.8 39.6 WCA-RPS 14.8 38.8 15.8 39.6 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 247 Table L.45 – Energy Not Served, Sensitivity Cases, High Gas GWh High Gas, MC A High Gas, MC B Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Average Annual Energy Not Served 2017 - 2036 Upper Tail Mean Energy Not Served Cumulative Total 2017 - 2036 RH2a 12.1 30.9 12.2 31.1 CPP-C 13.9 32.1 14.1 32.7 CPP-D 13.2 32.1 13.3 32.3 FOT-1 12.7 31.2 12.8 31.3 CO2-1 14.2 34.1 14.8 34.2 GW1 12.1 30.8 12.3 30.9 GW2 12.5 31.3 12.7 31.8 GW3 11.9 30.7 12.1 30.8 GW4 11.9 31.4 12.2 31.7 WCA 15.3 39.1 15.3 39.0 WCA-RPS 15.3 39.1 15.3 39.0 Table L.46 – Energy Not Served, Final Screening Cases, Low Gas GWh Low Gas MC A Low Gas, MC B Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 FS-REP 11.5 30.5 11.7 30.6 FS-GW4 11.3 30.0 11.6 30.3 FS-R1c 11.0 30.2 11.3 30.3 FS-R2 11.2 30.0 11.5 30.4 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 248 Table L.47 – Energy Not Served, Final Screening Cases, Medium Gas GWh Medium Gas, MC A Medium Gas, MC B Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 FS-REP 11.1 30.3 11.6 30.5 FS-GW4 11.1 29.7 11.6 30.3 FS-R1c 10.7 29.8 11.3 30.3 FS-R2 11.0 29.7 11.5 30.3 Table L.48 – Energy Not Served, Final Screening Cases, High Gas GWh High Gas, MC A High Gas, MC B Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 Average Annual Energy Not Served, 2017-2036 Upper Tail Mean Energy Not Served Cumulative Total, 2017-2036 FS-REP 12.3 30.8 12.5 30.9 FS-GW4 12.2 30.5 12.4 30.7 FS-R1c 11.9 30.5 12.1 30.6 FS-R2 12.2 31.0 12.4 31.2 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 249 Table L.49 – PVRR Cost Components by Price Scenario, Regional Haze Cases, MC A Low Gas MC A Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR Ref. 11,256 479 428 2,510 857 (2,202) 1,804 8,847 23,979 RH-1 11,430 525 427 2,502 915 (2,096) 1,562 7,575 22,840 RH-2 11,193 505 428 2,486 904 (1,877) 1,631 7,665 22,934 RH-3 11,380 561 427 2,501 961 (2,094) 1,582 7,634 22,953 RH-4 11,435 517 427 2,500 899 (2,086) 1,574 8,076 23,342 RH-5 11,269 524 428 2,482 888 (1,892) 1,660 7,404 22,762 RH-6 11,408 578 428 2,489 886 (2,079) 1,625 8,289 23,624 Medium Gas MC A Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR Ref. 11,862 524 434 2,510 857 (2,573) 2,093 8,847 24,553 RH-1 12,097 575 434 2,502 915 (2,448) 1,804 7,575 23,453 RH-2 11,995 553 435 2,486 904 (2,205) 1,840 7,665 23,671 RH-3 12,085 608 434 2,501 961 (2,449) 1,818 7,634 23,593 RH-4 12,105 563 434 2,500 899 (2,437) 1,809 8,076 23,949 RH-5 11,970 571 434 2,482 888 (2,195) 1,892 7,404 23,446 RH-6 12,151 631 435 2,489 886 (2,443) 1,840 8,289 24,278 High Gas MC A Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR Ref. 13,626 587 457 2,510 857 (3,874) 3,750 8,847 26,760 RH-1 14,029 651 457 2,502 915 (3,606) 3,132 7,575 25,654 RH-2 14,222 627 455 2,486 904 (3,242) 3,230 7,665 26,346 RH-3 14,058 679 457 2,502 961 (3,573) 3,237 7,634 25,956 RH-4 14,017 631 457 2,500 899 (3,596) 3,141 8,076 26,126 RH-5 13,687 638 459 2,482 888 (3,107) 3,637 7,404 26,088 RH-6 14,215 716 458 2,489 886 (3,594) 3,183 8,289 26,642 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 250 Table L.50 – PVRR Cost Components by Price Scenario, Regional Haze Cases, MC B Low Gas MC B Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR Ref. 10,891 478 424 2,510 857 (2,055) 2,096 8,847 24,048 RH-1 11,080 526 424 2,502 915 (1,946) 1,857 7,575 22,931 RH-2 11,016 504 425 2,486 904 (1,801) 1,701 7,665 22,898 RH-3 11,077 558 423 2,501 961 (1,967) 1,792 7,634 22,981 RH-4 11,088 515 424 2,500 899 (1,937) 1,864 8,076 23,429 RH-5 11,074 522 424 2,482 888 (1,813) 1,749 7,404 22,730 RH-6 11,144 577 424 2,489 886 (1,968) 1,784 8,289 23,626 Medium Gas MC B Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR Ref. 11,468 518 429 2,510 857 (2,388) 2,318 8,847 24,559 RH-1 11,649 568 429 2,502 915 (2,237) 2,077 7,575 23,477 RH-2 11,692 548 430 2,486 904 (2,059) 1,989 7,665 23,655 RH-3 11,711 603 429 2,501 961 (2,262) 2,014 7,634 23,593 RH-4 11,667 556 429 2,500 899 (2,229) 2,073 8,076 23,970 RH-5 11,654 564 429 2,482 888 (2,052) 2,061 7,404 23,430 RH-6 11,823 626 430 2,489 886 (2,276) 2,000 8,289 24,266 High Gas MC B Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR Ref. 13,104 571 459 2,510 857 (3,639) 4,124 8,847 26,833 RH-1 13,445 634 458 2,502 915 (3,361) 3,659 7,575 25,827 RH-2 13,927 615 457 2,486 904 (3,112) 3,425 7,665 26,366 RH-3 13,581 664 458 2,502 961 (3,360) 3,605 7,634 26,046 RH-4 13,456 614 459 2,500 899 (3,367) 3,637 8,076 26,274 RH-5 13,475 626 459 2,482 888 (3,018) 3,743 7,404 26,059 RH-6 13,882 701 459 2,489 886 (3,451) 3,415 8,289 26,670 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 251 Table L.51 – PVRR Cost Components by Price Scenario, Core Cases, MC A Low Gas MC A Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR OP-1 11,277 524 427 2,482 888 (1,893) 1,654 7,404 22,763 OP-NT3 11,103 545 427 2,497 937 (1,918) 1,636 7,534 22,761 OP-REP 11,145 544 426 2,489 911 (1,974) 1,535 7,643 22,719 OP-GW4 10,695 518 425 2,543 890 (1,991) 1,486 8,503 23,069 FR-1 10,974 492 427 2,506 906 (1,869) 1,777 8,045 23,257 FR-2 11,168 452 427 2,488 829 (1,909) 1,775 8,590 23,820 RE-1a 10,944 534 427 2,502 937 (1,946) 1,607 7,814 22,819 RE-1b 11,141 536 427 2,499 937 (1,990) 1,499 7,722 22,772 RE-1c 11,021 532 427 2,503 937 (2,020) 1,544 7,923 22,868 RE-2 11,088 530 427 2,503 937 (2,080) 1,525 7,898 22,828 DLC-1 10,867 505 427 2,506 937 (1,959) 1,709 7,886 22,878 Medium Gas MC A Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR OP-1 11,984 571 434 2,482 888 (2,199) 1,881 7,404 23,444 OP-NT3 11,772 598 433 2,497 937 (2,228) 1,864 7,534 23,407 OP-REP 11,837 594 433 2,489 911 (2,297) 1,741 7,643 23,350 OP-GW4 11,386 569 431 2,543 890 (2,342) 1,628 8,503 23,608 FR-1 11,647 541 433 2,506 906 (2,176) 1,991 8,045 23,892 FR-2 11,908 489 434 2,488 829 (2,234) 1,982 8,590 24,485 RE-1a 11,588 588 433 2,502 937 (2,260) 1,829 7,814 23,431 RE-1b 11,823 585 433 2,499 937 (2,315) 1,710 7,722 23,395 RE-1c 11,682 584 433 2,503 937 (2,349) 1,749 7,923 23,462 RE-2 11,755 580 433 2,503 937 (2,418) 1,734 7,898 23,422 DLC-1 11,510 557 433 2,506 937 (2,277) 1,923 7,886 23,475 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 252 High Gas MC A Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR OP-1 13,936 641 455 2,482 888 (3,196) 3,377 7,404 25,988 OP-NT3 13,725 677 454 2,497 937 (3,290) 3,181 7,534 25,716 OP-REP 13,852 672 454 2,489 911 (3,407) 2,960 7,643 25,573 OP-GW4 13,354 648 452 2,543 890 (3,556) 2,567 8,503 25,400 FR-1 13,493 611 454 2,506 906 (3,200) 3,436 8,045 26,251 FR-2 13,817 529 454 2,488 829 (3,267) 3,562 8,590 27,003 RE-1a 13,456 670 454 2,503 937 (3,339) 3,155 7,814 25,651 RE-1b 13,804 661 454 2,499 937 (3,414) 2,969 7,722 25,632 RE-1c 13,598 662 454 2,504 937 (3,466) 3,002 7,923 25,613 RE-2 13,698 657 454 2,503 937 (3,551) 2,971 7,898 25,567 DLC-1 13,288 633 454 2,506 937 (3,345) 3,314 7,886 25,673 Table L.52 – PVRR Cost Components by Price Scenario, Core Cases, MC B Low Gas MC B Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR OP-1 11,074 522 424 2,482 888 (1,813) 1,749 7,404 22,730 OP-NT3 10,918 543 423 2,497 937 (1,841) 1,714 7,534 22,724 OP-REP 10,947 542 423 2,489 911 (1,893) 1,624 7,643 22,686 OP-GW4 10,528 516 421 2,543 890 (1,919) 1,552 8,503 23,035 FR-1 10,795 490 423 2,506 906 (1,796) 1,849 8,045 23,220 FR-2 10,988 451 424 2,488 829 (1,836) 1,849 8,590 23,783 RE-1a 10,758 532 423 2,502 937 (1,870) 1,685 7,814 22,783 RE-1b 10,952 534 423 2,499 937 (1,912) 1,581 7,722 22,737 RE-1c 10,837 531 423 2,503 937 (1,943) 1,621 7,923 22,832 RE-2 10,900 528 423 2,503 937 (1,999) 1,605 7,898 22,795 DLC-1 10,690 503 423 2,506 937 (1,885) 1,781 7,886 22,842 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 253 Medium Gas MC B Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR OP-1 11,654 564 429 2,482 888 (2,052) 2,061 7,404 23,430 OP-NT3 11,476 591 428 2,497 937 (2,090) 2,014 7,534 23,388 OP-REP 11,533 587 428 2,489 911 (2,155) 1,898 7,643 23,333 OP-GW4 11,130 562 426 2,543 890 (2,216) 1,745 8,503 23,584 FR-1 11,347 536 429 2,506 906 (2,039) 2,143 8,045 23,873 FR-2 11,604 486 429 2,488 829 (2,097) 2,138 8,590 24,467 RE-1a 11,290 581 428 2,502 937 (2,121) 2,016 7,814 23,449 RE-1b 11,522 579 428 2,499 937 (2,173) 1,898 7,722 23,413 RE-1c 11,386 577 428 2,503 937 (2,208) 1,898 7,923 23,444 RE-2 11,458 574 428 2,503 937 (2,271) 1,882 7,898 23,410 DLC-1 11,212 550 428 2,506 937 (2,137) 2,074 7,886 23,458 High Gas MC B Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR OP-1 13,590 627 457 2,482 888 (3,057) 3,629 7,404 26,020 OP-NT3 13,437 663 456 2,497 937 (3,174) 3,372 7,534 25,722 OP-REP 13,546 657 456 2,489 911 (3,283) 3,171 7,643 25,590 OP-GW4 13,194 637 452 2,543 890 (3,463) 2,657 8,503 25,413 FR-1 13,230 595 456 2,506 906 (3,095) 3,596 8,045 26,239 FR-2 13,507 512 457 2,488 829 (3,137) 3,749 8,590 26,995 RE-1a 13,171 656 456 2,503 937 (3,222) 3,341 7,814 25,656 RE-1b 13,503 647 456 2,499 937 (3,288) 3,174 7,722 25,650 RE-1c 13,309 648 456 2,504 937 (3,341) 3,192 7,923 25,627 RE-2 13,404 643 456 2,503 937 (3,416) 3,163 7,898 25,588 DLC-1 13,055 620 456 2,506 937 (3,239) 3,446 7,886 25,667 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 254 Table L.53 – PVRR Cost Components by Price Scenario, Sensitivity Cases, MC A Low Gas MC A Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR RH2a 11,004 514 427 2,501 964 (1,888) 1,710 7,610 22,842 CPP-C 11,337 535 427 2,496 864 (2,032) 1,626 7,560 22,813 CPP-D 11,432 542 427 2,486 878 (1,926) 1,575 7,287 22,699 FOT-1 11,138 478 427 2,509 948 (1,928) 1,617 7,861 23,048 CO2-1 9,890 508 426 2,520 966 (1,555) 2,759 8,276 23,791 GW1 10,864 525 426 2,524 916 (1,969) 1,472 8,546 23,305 GW2 10,894 527 426 2,523 916 (1,967) 1,479 8,850 23,648 GW3 10,632 515 425 2,549 896 (1,986) 1,372 9,799 24,202 GW4 10,746 519 426 2,543 896 (1,971) 1,448 8,380 22,986 WCA 2,989 353 (44) 70 225 (373) 1,514 2,034 6,767 WCA-RPS 2,983 351 (44) 71 225 (398) 1,489 2,112 6,789 Medium Gas MC A Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR RH2a 11,758 570 433 2,501 964 (2,204) 1,925 7,610 23,558 CPP-C 11,975 583 434 2,496 864 (2,319) 1,921 7,560 23,513 CPP-D 12,183 589 433 2,486 878 (2,250) 1,760 7,287 23,364 FOT-1 11,827 513 433 2,509 948 (2,233) 1,823 7,861 23,681 CO2-1 10,879 555 431 2,520 966 (1,970) 2,649 8,276 24,306 GW1 11,549 578 431 2,524 916 (2,308) 1,637 8,546 23,874 GW2 11,582 579 432 2,523 916 (2,306) 1,640 8,850 24,217 GW3 11,311 565 430 2,549 896 (2,339) 1,499 9,799 24,710 GW4 11,438 570 431 2,543 896 (2,316) 1,599 8,380 23,542 WCA 3,359 436 (44) 70 225 (505) 1,515 2,034 7,090 WCA-RPS 3,352 433 (44) 71 225 (536) 1,488 2,112 7,102 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 255 High Gas MC A Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR RH2a 13,856 659 454 2,502 964 (3,235) 3,341 7,610 26,149 CPP-C 13,962 656 455 2,496 864 (3,308) 3,590 7,560 26,274 CPP-D 14,377 663 455 2,486 878 (3,375) 2,898 7,287 25,667 FOT-1 13,737 566 455 2,510 948 (3,271) 3,257 7,861 26,061 CO2-1 13,326 621 453 2,521 966 (3,447) 2,903 8,276 25,620 GW1 13,507 659 452 2,525 916 (3,476) 2,698 8,546 25,826 GW2 13,539 660 452 2,523 916 (3,470) 2,704 8,850 26,176 GW3 13,270 645 451 2,549 896 (3,557) 2,376 9,799 26,429 GW4 13,405 650 452 2,544 896 (3,508) 2,594 8,380 25,412 WCA 4,095 584 (44) 70 225 (755) 2,053 2,034 8,261 WCA-RPS 4,086 580 (44) 71 225 (800) 2,010 2,112 8,240 Table L.54 – PVRR Cost Components by Price Scenario, Sensitivity Cases, MC B Low Gas MC B Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR RH2a 10,829 514 423 2,501 964 (1,815) 1,779 7,610 22,806 CPP-C 11,127 533 424 2,496 864 (1,945) 1,719 7,560 22,777 CPP-D 11,263 540 423 2,486 878 (1,855) 1,640 7,287 22,661 FOT-1 10,960 476 423 2,509 948 (1,855) 1,688 7,861 23,011 CO2-1 9,735 507 422 2,520 966 (1,487) 2,809 8,276 23,748 GW1 10,694 524 422 2,524 916 (1,898) 1,539 8,546 23,268 GW2 10,723 525 422 2,523 916 (1,895) 1,546 8,850 23,610 GW3 10,465 513 421 2,549 896 (1,915) 1,437 9,799 24,165 GW4 10,579 517 422 2,543 896 (1,900) 1,514 8,380 22,951 WCA 2,930 351 (44) 70 225 (364) 1,537 2,034 6,739 WCA-RPS 2,924 349 (44) 71 225 (389) 1,513 2,112 6,762 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 256 Medium Gas MC B Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR RH2a 11,456 566 429 2,501 964 (2,063) 2,080 7,610 23,542 LD-1 11,681 667 429 2,487 943 (2,185) 1,889 7,787 23,696 LD-2 11,262 504 426 2,485 824 (2,189) 1,567 6,782 21,660 LD-3 11,994 641 432 2,498 973 (1,875) 2,648 7,917 25,229 PG-1 11,636 574 429 2,490 894 (2,047) 2,081 7,542 23,598 PG-2 11,459 564 429 2,503 896 (2,103) 1,931 7,478 23,157 CPP-C 11,623 577 430 2,496 864 (2,160) 2,115 7,560 23,505 CPP-D 11,931 583 427 2,486 878 (2,130) 1,869 7,287 23,330 FOT-1 11,527 506 429 2,509 948 (2,094) 1,978 7,861 23,663 CO2-1 10,663 550 425 2,520 966 (1,860) 2,720 8,276 24,261 NO-CO2 12,108 605 425 2,497 884 (2,395) 1,612 7,423 23,160 BP 11,690 556 429 2,502 1,003 (2,035) 1,842 7,476 23,464 GW1 11,278 571 427 2,524 916 (2,178) 1,766 8,546 23,850 GW2 11,305 573 428 2,523 916 (2,175) 1,773 8,850 24,193 GW3 11,054 559 426 2,549 896 (2,214) 1,614 9,799 24,683 GW4 11,178 564 427 2,543 896 (2,189) 1,719 8,380 23,517 Battery 11,154 558 426 2,541 889 (2,221) 1,618 8,499 23,464 CAES 11,156 558 427 2,541 889 (2,222) 1,613 8,461 23,423 WCA 3,262 432 (44) 70 225 (486) 1,573 2,034 7,066 WCA-RPS 3,255 429 (44) 71 225 (515) 1,545 2,112 7,078 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 257 High Gas MC B Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR RH2a 13,572 646 457 2,502 964 (3,115) 3,532 7,610 26,167 CPP-C 13,473 642 457 2,496 864 (3,057) 4,056 7,560 26,490 CPP-D 14,194 651 455 2,486 878 (3,285) 2,997 7,287 25,663 FOT-1 13,464 554 457 2,509 948 (3,158) 3,432 7,861 26,067 CO2-1 13,077 609 453 2,521 966 (3,324) 3,090 8,276 25,667 GW1 13,322 646 455 2,525 916 (3,381) 2,803 8,546 25,831 GW2 13,343 648 456 2,523 916 (3,374) 2,819 8,850 26,181 GW3 13,120 634 451 2,549 896 (3,469) 2,458 9,799 26,438 GW4 13,244 638 452 2,544 896 (3,417) 2,684 8,380 25,420 WCA 4,065 575 (44) 70 225 (740) 2,041 2,034 8,225 WCA-RPS 4,056 571 (44) 71 225 (783) 1,998 2,112 8,206 Table L.55 – PVRR Cost Components by Price Scenario, Final Screening Cases, MC A Low Gas MC A Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR FS-REP 11,102 536 427 2,504 916 (1,947) 1,560 7,643 22,741 FS-GW4 10,714 520 426 2,539 895 (1,989) 1,421 8,292 22,817 FS-R1c 10,703 517 426 2,541 895 (2,036) 1,390 8,410 22,844 FS-R2 10,698 519 425 2,540 878 (1,995) 1,400 8,352 22,818 Medium Gas MC A Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR FS-REP 11,777 589 433 2,504 916 (2,263) 1,774 7,643 23,372 FS-GW4 11,400 571 431 2,539 895 (2,338) 1,566 8,292 23,356 FS-R1c 11,387 567 431 2,541 895 (2,394) 1,528 8,410 23,366 FS-R2 11,387 571 431 2,540 878 (2,347) 1,538 8,352 23,349 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 258 High Gas MC A Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR FS-REP 13,739 668 454 2,505 916 (3,350) 3,042 7,643 25,616 FS-GW4 13,361 652 452 2,539 895 (3,544) 2,518 8,292 25,165 FS-R1c 13,342 646 452 2,541 895 (3,626) 2,458 8,410 25,119 FS-R2 13,351 651 451 2,541 878 (3,562) 2,459 8,352 25,122 Table L.56 – PVRR Cost Components by Price Scenario, Final Screening Cases, MC B Low Gas MC B Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR FS-REP 10,917 535 423 2,504 916 (1,871) 1,637 7,643 22,705 FS-GW4 10,547 518 422 2,539 895 (1,918) 1,487 8,292 22,782 FS-R1c 10,537 515 422 2,541 895 (1,965) 1,456 8,410 22,810 FS-R2 10,533 518 421 2,540 878 (1,924) 1,465 8,352 22,783 Medium Gas MC B Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR FS-REP 11,482 582 428 2,504 916 (2,125) 1,922 7,643 23,353 FS-GW4 11,143 565 427 2,539 895 (2,212) 1,684 8,292 23,333 FS-R1c 11,130 561 427 2,541 895 (2,266) 1,646 8,410 23,343 FS-R2 11,130 564 426 2,540 878 (2,221) 1,655 8,352 23,326 High Gas MC B Stochastic PVRR ($ millions) Thermal Fuel Variable O&M incl. FOT Long Term Contracts Renewable DSM System Balancing Sales System Balancing Purchases Capital and Fixed O&M Cost Total PVRR FS-REP 13,453 654 456 2,505 916 (3,231) 3,233 7,643 25,629 FS-GW4 13,203 640 452 2,539 895 (3,452) 2,606 8,292 25,175 FS-R1c 13,185 635 452 2,541 895 (3,529) 2,545 8,410 25,133 FS-R2 13,194 639 451 2,541 878 (3,470) 2,547 8,352 25,133 PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 259 Table L.57 – 10-year Average Incremental Customer Rate Impact, Final Screening Cases $ Millions 10-year Average Incremental Customer Rate Impact (2017 - 2026) Low Gas, MC B Medium Gas, MC B High Gas, MC B Average Difference from Preferred Portfolio Rank Difference from Preferred Portfolio Rank Difference from Preferred Portfolio Rank Difference from Preferred Portfolio Rank FS-GW4 0.0 3 0.0 3 0.0 3 0.0 3 FS-REP 4.3 4 12.6 4 43.6 4 20.2 4 FS-R1c (0.1) 2 (0.3) 2 (0.7) 2 (0.4) 2 FS-R2 (0.4) 1 (0.6) 1 (1.2) 1 (0.7) 1 $ Millions 10-year Average Incremental Customer Rate Impact (2017 - 2036) Low Gas, MC B Medium Gas, MC B High Gas, MC B Average Difference from Preferred Portfolio Rank Difference from Preferred Portfolio Rank Difference from Preferred Portfolio Rank Difference from Preferred Portfolio Rank FS-GW4 0.0 3 0.0 3 0.0 3 0.0 3 FS-REP 3.8 4 12.1 4 46.7 4 20.9 4 FS-R1c (0.1) 2 (0.3) 2 (0.8) 2 (0.4) 2 FS-R2 (0.4) 1 (0.5) 1 (1.3) 1 (0.7) 1 PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 260 Table L.58 – Loss of Load Probability, Major (> 25,000 MWh) July Event, Final Screening Cases, Medium Gas, MC B Year FS-REP Preferred Portfolio FS-GW4 FS-R1c FS-R2 2017 0% 0% 0% 0% 2018 8% 8% 8% 8% 2019 0% 0% 0% 0% 2020 0% 0% 0% 0% 2021 2% 2% 2% 2% 2022 4% 4% 4% 4% 2023 0% 0% 0% 0% 2024 6% 6% 6% 6% 2025 4% 4% 4% 4% 2026 6% 6% 6% 6% 2027 4% 4% 4% 4% 2028 2% 2% 2% 2% 2029 4% 4% 4% 4% 2030 8% 6% 6% 8% 2031 2% 2% 2% 2% 2032 8% 8% 8% 8% 2033 14% 12% 12% 14% 2034 8% 10% 10% 8% 2035 4% 2% 2% 2% 2036 8% 8% 8% 8% PACIFICORP - 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 261 Table L.59 – Summer Peak, Average Loss of Load Probability, Final Screening Cases, Medium Gas, MC B Event Size (MWh) Average for operating years 2017 through 2026 (10 Year) FS-REP Preferred Portfolio FS-GW4 FS-R1c FS-R2 > 0 94% 94% 94% 94% > 1,000 78% 78% 78% 78% > 10,000 10% 10% 10% 10% > 25,000 3% 3% 3% 3% > 50,000 0% 0% 0% 0% > 100,000 0% 0% 0% 0% > 500,000 0% 0% 0% 0% Event Size (MWh) Average for operating years 2017 through 2036 (20 Year) FS-REP Preferred Portfolio FS-GW4 FS-R1c FS-R2 > 0 96% 96% 96% 96% > 1,000 82% 81% 81% 81% > 10,000 12% 12% 12% 12% > 25,000 5% 4% 4% 5% > 50,000 1% 1% 1% 1% > 100,000 0% 0% 0% 0% > 500,000 0% 0% 0% 0% > 1,000,000 0% 0% 0% 0% PACIFICORP – 2017 IRP APPENDIX L – STOCHASTIC SIMULATION RESULTS 262 PacifiCorp – 2017 IRP Appendix M- Case Fact Sheets 263 APPENDIX M – CASE STUDY FACT SHEETS Case Fact Sheet Overview This appendix documents the 2017 Integrated Resource Plan modeling assumptions used for the regional haze, core case, sensitivity and final screening studies. Case Fact Sheets - Overview - 264 - Case Overview Regional Haze Case Fact Sheets The following Regional Haze Case Fact Sheets summarize key assumptions and portfolio results for each portfolio being developed for the 2017 IRP. All cases produce resource portfolios capable of meeting state renewable portfolio standard requirements. Similarly, in addition to the Regional Haze compliance requirements specified for each case, all cases include costs to meet known and assumed compliance obligations for Mercury and Air Toxics (MATS), coal combustion residuals (CCR) under subtitle D of the Resource Conservation and Recovery Act (RCRA), cooling water intake structures under §316(b) of the Clean Water Act, and effluent guidelines. Quick Reference Guide Case Description Benchmark Load Private Gen CO2 Policy FOTs Gateway 1st Year of New Thermal SO PVRR w/o Trans. ($m) SO PVRR w/ Trans. ($m) Ref. Reference Case - Base Base Mass Cap B Base None 2032 $24,156 $24,219 RH-1 Regional Haze 1 - Base Base Mass Cap B Base None 2030 $23,066 $23,159 RH-2 Regional Haze 2 - Base Base Mass Cap B Base None 2029 $23,313 $23,482 RH-3 Regional Haze 3 - Base Base Mass Cap B Base None 2029 $23,315 $23,398 RH-4 Regional Haze 4 - Base Base Mass Cap B Base None 2030 $23,582 $23,663 RH-5 Regional Haze 5 - Base Base Mass Cap B Base None 2029 $23,081 $23,177 RH-6 Regional Haze 6 - Base Base Mass Cap B Base None 2028 $23,891 $23,986 Core Case Fact Sheets The following Core Case Fact Sheets summarize key assumptions and portfolio results for each portfolio being developed for the 2017 IRP. All cases produce resource portfolios capable of meeting state renewable portfolio standard requirements. As with the regional haze cases, all core cases comply with the environmental obligations. Quick Reference Guide Case Description Benchmark Load Private Gen CO2 Policy FOTs Gateway 1st Year of New Thermal SO PVRR w/o Trans. ($m) SO PVRR w/ Trans. ($m) OP-1 Optimized Portfolio RH5 Base Base Mass Cap B Base None 2029 $23,081 $23,177 OP-NT3 Optimized Naughton 3 OP-1 Base Base Mass Cap B Base None 2029 $22,913 $23,052 OP-REP Wind Repower OP-NT3 Base Base Mass Cap B Base None 2029 $22,890 $22,984 OP-GW4 Energy Gateway + Repower OP-REP Base Base Mass Cap B Base Segment D2 2029 $22,612 $23,123 FR-1 Flexible Resource OP-NT3 Base Base Mass Cap B Base None 2021 $23,463 $23,585 FR-2 Flexible Resource OP-NT3 Base Base Mass Cap B Base None 2021 $24,136 $24,319 RE-1a OR RPS Just in Time OP-NT3 Base Base Mass Cap B Base None 2029 $22,945 $23,082 RE-1b WA RPS Just in Time OP-NT3 Base Base Mass Cap B Base None 2029 $22,962 $23,091 RE-1c OR & WA RPS Just in Time OP-NT3 Base Base Mass Cap B Base None 2029 $23,016 $23,154 RE-2 OR RPS Early OP-NT3 Base Base Mass Cap B Base None 2029 $22,967 $23,098 DLC-1 Direct Load Control OP-NT3 Base Base Mass Cap B Base None 2030 $22,942 $23,103 Sensitivity Fact Sheets The following Sensitivity Fact Sheets summarize key assumptions and portfolio results for each sensitivity being developed for the 2017 IRP. All sensitivities produce resource portfolios capable of meeting state Case Fact Sheets - Overview - 265 - Case Overview renewable portfolio standard requirements. As with the regional haze cases, all sensitivities comply with the environmental obligations. Quick Reference Guide Case Description Benchmark Load Private Gen CO2 Policy FOTs Gateway 1st Year of New Thermal SO PVRR w/o Trans. ($m) SO PVRR w/ Trans. ($m) RH2a Regional Haze OP-1 Base Base Mass Cap B Base None 2029 $23,237 $23,404 LD-1 1 in 20 Loads OP-1 1 in 20 Base Mass Cap B Base None 2029 $23,207 $23,364 LD-2 Low Load OP-1 Low Base Mass Cap B Base None 2030 $21,512 $21,567 LD-3 High Load OP-1 High Base Mass Cap B Base None 2028 $24,629 $24,818 PG-1 Low Private Gen OP-1 Base Low Mass Cap B Base None 2029 $23,203 $23,304 PG-2 High Private Gen OP-1 Base High Mass Cap B Base None 2030 $22,782 $22,899 CPP-C CPP Mass Cap C OP-1 Base Base Mass Cap C Base None 2029 $23,129 $23,268 CPP-D CPP Mass Cap D OP-1 Base Base Mass Cap D Base None 2029 $23,010 $23,102 FOT-1 Limited FOT OP-1 Base Base Mass Cap B Restricted None 2029 $23,189 $23,347 CO2-1 CO2 Price OP-1 Base Base Tax, No CPP Base None 2030 $26,222 $26,401 NO-CO2 No CO2 OP-NT3 Base Base No Tax, No CPP Base None 2028 $22,787 $22,891 BP Business Plan OP-NT3 Base Base Mass Cap D Base None 2030 $23,053 $23,198 GW1 Gateway 1 OP-NT3 Base Base Mass Cap B Base Segment D 2029 $22,803 $23,593 GW2 Gateway 2 OP-NT3 Base Base Mass Cap B Base Segment F 2029 $22,841 $24,054 GW3 Gateway 3 OP-NT3 Base Base Mass Cap B Base Segment D&F 2029 $22,706 $24,627 GW4 Gateway 4 OP-NT3 Base Base Mass Cap B Base Segment D2 2029 $22,648 $23,159 Battery Battery Storage FS-GW4 Base Base Mass Cap B Base Segment D2 2029 $22,735 $23,162 CAES CAES Storage FS-GW4 Base Base Mass Cap B Base Segment D2 2029 $22,659 $23,121 WCA WCA FS-REP Base Base Mass Cap B Base None 3033 $7,539 $7,542 WCA-RPS WCA RPS FS-REP Base Base Mass Cap B Base None 3033 $7,554 $7,557 Case Fact Sheets - Overview - 266 - Case Overview Final Case Fact Sheets The following Final Case Fact Sheets summarize key assumptions and portfolio results for each portfolio being developed for the 2017 IRP. All cases produce resource portfolios capable of meeting state renewable portfolio standard requirements. As with the regional haze cases, all final cases comply with the environmental obligations. Quick Reference Guide Case Description Benchmark Load Private Gen CO2 Policy FOTs Gateway 1st Year of New Thermal SO PVRR w/o Trans. ($m) SO PVRR w/ Trans. ($m) FS-REP Wind Repower OP-NT3 Base Base Mass Cap B Base Segment D2 2029 $22,907 $23,042 FS-GW4 Gateway 4 FS-REP Base Base Mass Cap B Base Segment D2 2029 $22,549 $22,990 FS-R1c OR & WA RPS Just in Time FS-GW4 Base Base Mass Cap B Base Segment D2 2029 $22,561 $23,006 FS-R2 OR RPS Early FS-GW4 Base Base Mass Cap B Base Segment D2 2029 $22,554 $22,995 Master Fact Sheet - 267 - Master Fact Sheet Master Fact Sheet CASE ASSUMPTIONS - MASTER Description The following assumptions are applicable to all cases, except where otherwise specified. Federal CO2 Policy/Price Signal The Clean Power Plan is reflected in all Regional Haze, core cases, final selections and sensitivities, with the exception of the CO2 Price and No CO2 sensitivities. Forward Price Curve Gas and power prices utilize medium natural gas price assumptions consistent with the Company’s October 12, 2016 OFPC through October 2022. After October 2022, prices are followed by a 12-month blend that segues into a pure fundamentals forecast. Prices reflect Mass Cap B total allocation cap. Federal Tax Incentives PTCs phase out beginning in 2017 and expire entirely end of 2019. To achieve the PTC, projects must be under construction by the end of 2019. ITC of 30 percent steps down to 26 percent in 2020 and 22 percent for 2021 through 2023, thereafter it continues in perpetuity at 10 percent. Load Forecast The figure below shows the base system coincident peak load forecast applicable to core cases before accounting for any potential contribution from DSM. Loads include private generation resources. 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 $/ M m b t u Nominal Average Henry Hub Gas Prices October 12, 2016 OFPC 9,000 9,500 10,000 10,500 11,000 11,500 12,000 12,500 13,000 13,500 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 MW Coincident System Peak Load Base Master Fact Sheet - 268 - Master Fact Sheet Energy Efficiency (Class 2 DSM) Core case studies uses base supply curves with economic resource selections up to the achievable potential. Class 2 resources that are not selected in any given year are not available for selection in future years. Achievable potential by state and year are summarized below. Private Generation Base case private generation penetration by state and year are summarized in the following figure, which is included in the load forecast. System CO2 Emissions (System Optimizer) System CO2 emissions from System Optimizer are shown in the figure below. Emissions reflect Mass Cap B total allocation cap. 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 MW Class 2 DSM Cumulative Achievable Potential UT OR WA WY ID CA - 500 1,000 1,500 2,000 2,500 3,000 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 MW Distributed Generation - Base Penetration Case UT OR WA WY ID CA 0.00 10.00 20.00 30.00 40.00 50.00 60.00 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 Mi l l i o n T o n s System CO2 Emissions (System Optimizer) Mass Cap B Regional Haze Case: Ref. - 269 - Regional Haze Case: Ref. Regional Haze Case Fact Sheets CASE ASSUMPTIONS Description Refer to Volume I, Chapter 7 (Regional Haze Case Definitions). PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $24,156 Transmission Integration $51 Transmission Reinforcement $12 Total Cost $24,219 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Regional Haze Regional Haze assumptions are summarized in the following table. SCR = selective catalytic reduction (4)(3)(2)(1)01234567891011 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Coal Unit Description Cholla 4 Gas Conversion by Dec 2025, Retire Dec 2042 Colstrip 3 Retire Dec 2046 Colstrip 4 Retire Dec 2046 Craig 1 Retire Dec 2025 Craig 2 SCR by Dec 2017, Retire Dec 2034 Dave Johnston 1 Retire Dec 2027 Dave Johnston 2 Retire Dec 2027 Dave Johnston 3 Retire Dec 2027 Dave Johnston 4 Retire Dec 2027 Hayden 1 Retire Dec 2030 Hayden 2 SCR by Dec 2016, Retire Dec 2030 Hunter 1 SCR by 2021, Retire Dec 2042 Hunter 2 SCR by 2021, Retire Dec 2042 Hunter 3 Retire Dec 2042 Huntington 1 SCR by 2021, Retire Dec 2036 Huntington 2 SCR by 2021, Retire Dec 2036 Jim Bridger 1 SCR by 2022, Retire Dec 2037 Jim Bridger 2 SCR by 2021, Retire Dec 2037 Jim Bridger 3 Retire Dec 2037 Jim Bridger 4 SCR by Dec 2016, Retire Dec 2037 Naughton 1 Retire Dec 2029 Naughton 2 Retire Dec 2029 Naughton 3 Gas Conversion by Dec 2019, Retire Dec 2029 Wyodak Retire Dec 2039 Regional Haze Case: RH-1 - 270 - Regional Haze Case: RH-1 Regional Haze Case Fact Sheets CASE ASSUMPTIONS Description Refer to Volume I, Chapter 7 (Regional Haze Case Definitions). PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,066 Transmission Integration $81 Transmission Reinforcement $12 Total Cost $23,159 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Regional Haze Regional Haze assumptions are summarized in the following table. SCR = selective catalytic reduction NOx = Low NOx burner (4)(3)(2)(1)01234567891011 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Coal Unit Description Cholla 4 Retire Apr 2025 Colstrip 3 Retire Dec 2046 Colstrip 4 Retire Dec 2046 Craig 1 Retire Dec 2025 Craig 2 SCR by Dec 2017, Retire Dec 2034 Dave Johnston 1 Retire Dec 2027 Dave Johnston 2 Retire Dec 2027 Dave Johnston 3 Retire Dec 2027 Dave Johnston 4 Retire Dec 2027 Hayden 1 Retire Dec 2030 Hayden 2 SCR by Dec 2016, Retire Dec 2030 Hunter 1 NOx by 2021, Retire Dec 2042 Hunter 2 NOx by 2021, Retire Dec 2042 Hunter 3 Retire Dec 2042 Huntington 1 Retire Dec 2036 Huntington 2 Retire Dec 2036 Jim Bridger 1 Retire Dec 2032 Jim Bridger 2 Retire Dec 2035 Jim Bridger 3 Retire Dec 2037 Jim Bridger 4 SCR by Dec 2016, Retire Dec 2037 Naughton 1 Retire Dec 2029 Naughton 2 Retire Dec 2029 Naughton 3 Retire Dec 2017 Wyodak Retire Dec 2039 Regional Haze Case: RH-2 - 271 - Regional Haze Case: RH-2 Regional Haze Case Fact Sheets CASE ASSUMPTIONS Description Refer to Volume I, Chapter 7 (Regional Haze Case Definitions). PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,313 Transmission Integration $157 Transmission Reinforcement $12 Total Cost $23,482 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Regional Haze Regional Haze assumptions are summarized in the following table. SCR = selective catalytic reduction (5)(4)(3)(2)(1)01234567891011 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Coal Unit Description Cholla 4 Retire Dec 2020 Colstrip 3 Retire Dec 2046 Colstrip 4 Retire Dec 2046 Craig 1 Gas Conversion by Dec 2023, Retire Dec 2034 Craig 2 SCR by Dec 2017, Retire Dec 2034 Dave Johnston 1 Retire Dec 2027 Dave Johnston 2 Retire Dec 2027 Dave Johnston 3 Retire Dec 2027 Dave Johnston 4 Retire Dec 2032 Hayden 1 Retire Dec 2030 Hayden 2 SCR by Dec 2016, Retire Dec 2030 Hunter 1 Retire Dec 2031 Hunter 2 Retire Dec 2031 Hunter 3 Retire Dec 2042 Huntington 1 Retire Dec 2036 Huntington 2 Retire Dec 2036 Jim Bridger 1 Retire Dec 2024 Jim Bridger 2 Retire Dec 2028 Jim Bridger 3 Retire Dec 2037 Jim Bridger 4 SCR by Dec 2016, Retire Dec 2037 Naughton 1 Retire Dec 2029 Naughton 2 Retire Dec 2029 Naughton 3 Gas Conversion by Dec 2019, Retire Dec 2029 Wyodak Retire Dec 2039 Regional Haze Case: RH-3 - 272 - Regional Haze Case: RH-3 Regional Haze Case Fact Sheets CASE ASSUMPTIONS Description Refer to Volume I, Chapter 7 (Regional Haze Case Definitions). PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,315 Transmission Integration $70 Transmission Reinforcement $12 Total Cost $23,398 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Regional Haze Regional Haze assumptions are summarized in the following table. SCR = selective catalytic reduction NOx = Low NOx burner (4)(3)(2)(1)01234567891011 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Coal Unit Description Cholla 4 Retire Apr 2025 Colstrip 3 Retire Dec 2046 Colstrip 4 Retire Dec 2046 Craig 1 Retire Dec 2025 Craig 2 SCR by Dec 2017, Retire Dec 2034 Dave Johnston 1 Retire Dec 2027 Dave Johnston 2 Retire Dec 2027 Dave Johnston 3 Retire Dec 2027 Dave Johnston 4 Retire Dec 2027 Hayden 1 Retire Dec 2030 Hayden 2 SCR by Dec 2016, Retire Dec 2030 Hunter 1 NOx by Dec 2026, Retire Dec 2042 Hunter 2 NOx by Dec 2027, Retire Dec 2042 Hunter 3 Retire Dec 2042 Huntington 1 NOx by Dec 2026, Retire Dec 2036 Huntington 2 NOx by Dec 2027, Retire Dec 2036 Jim Bridger 1 Retire Dec 2028 Jim Bridger 2 Retire Dec 2032 Jim Bridger 3 Retire Dec 2037 Jim Bridger 4 SCR by Dec 2016, Retire Dec 2037 Naughton 1 Retire Dec 2029 Naughton 2 Retire Dec 2029 Naughton 3 Retire Dec 2017 Wyodak Retire Dec 2039 Regional Haze Case: RH-4 - 273 - Regional Haze Case: RH-4 Regional Haze Case Fact Sheets CASE ASSUMPTIONS Description Refer to Volume I, Chapter 7 (Regional Haze Case Definitions). PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,582 Transmission Integration $69 Transmission Reinforcement $12 Total Cost $23,663 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Regional Haze Regional Haze assumptions are summarized in the following table. SCR = selective catalytic reduction NOx = Low NOx burner (4)(3)(2)(1)01234567891011 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Coal Unit Description Cholla 4 Retire Apr 2025 Colstrip 3 Retire Dec 2046 Colstrip 4 Retire Dec 2046 Craig 1 Retire Dec 2025 Craig 2 SCR by Dec 2017, Retire Dec 2034 Dave Johnston 1 Retire Dec 2027 Dave Johnston 2 Retire Dec 2027 Dave Johnston 3 Retire Dec 2027 Dave Johnston 4 Retire Dec 2027 Hayden 1 Retire Dec 2030 Hayden 2 SCR by Dec 2016, Retire Dec 2030 Hunter 1 SCR by Dec 2021, Retire Dec 2042 Hunter 2 NOx by Dec 2027, Retire Dec 2042 Hunter 3 Retire Dec 2042 Huntington 1 SCR by Dec 2021, Retire Dec 2036 Huntington 2 NOx by Dec 2027, Retire Dec 2036 Jim Bridger 1 NOx by Dec 2022, Retire Dec 2032 Jim Bridger 2 SCR by Dec 2021, Retire Dec 2037 Jim Bridger 3 Retire Dec 2037 Jim Bridger 4 SCR by Dec 2016, Retire Dec 2037 Naughton 1 Retire Dec 2029 Naughton 2 Retire Dec 2029 Naughton 3 Gas Conversion by Dec 2019, Retire Dec 2029 Wyodak Retire Dec 2039 Regional Haze Case: RH-5 - 274 - Regional Haze Case: RH-5 Regional Haze Case Fact Sheets CASE ASSUMPTIONS Description Refer to Volume I, Chapter 7 (Regional Haze Case Definitions). This Regional Haze case became core case OP-1. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,081 Transmission Integration $84 Transmission Reinforcement $12 Total Cost $23,177 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Regional Haze Core case OP-1 Regional Haze assumptions are summarized in the following table. SCR = selective catalytic reduction NOx = Low NOx burner (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Coal Unit Description Cholla 4 Retire Dec 2020 Colstrip 3 Retire Dec 2046 Colstrip 4 Retire Dec 2046 Craig 1 Retire Dec 2025 Craig 2 SCR by Dec 2017, Retire Dec 2034 Dave Johnston 1 Retire Dec 2027 Dave Johnston 2 Retire Dec 2027 Dave Johnston 3 Retire Dec 2027 Dave Johnston 4 Retire Dec 2027 Hayden 1 Retire Dec 2030 Hayden 2 SCR by Dec 2016, Retire Dec 2030 Hunter 1 NOx by Dec 2021, Retire Dec 2042 Hunter 2 NOx by Dec 2021, Retire Dec 2042 Hunter 3 Retire Dec 2042 Huntington 1 Retire Dec 2036 Huntington 2 Retire Dec 2036 Jim Bridger 1 Retire Dec 2028 Jim Bridger 2 Retire Dec 2032 Jim Bridger 3 Retire Dec 2037 Jim Bridger 4 SCR by Dec 2016, Retire Dec 2037 Naughton 1 Retire Dec 2029 Naughton 2 Retire Dec 2029 Naughton 3 Gas Conversion by Dec 2019, Retire Dec 2029 Wyodak Retire Dec 2039 Regional Haze Case: RH-6 - 275 - Regional Haze Case: RH-6 Regional Haze Case Fact Sheets CASE ASSUMPTIONS Description Refer to Volume I, Chapter 7 (Regional Haze Case Definitions). PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,891 Transmission Integration $83 Transmission Reinforcement $12 Total Cost $23,986 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Regional Haze Regional Haze assumptions are summarized in the following table. SCR = selective catalytic reduction (4)(3)(2)(1)01234567891011 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Coal Unit Description Cholla 4 Retire Apr 2025 Colstrip 3 Retire Dec 2046 Colstrip 4 Retire Dec 2046 Craig 1 Retire Dec 2025 Craig 2 SCR by Dec 2017, Retire Dec 2034 Dave Johnston 1 Retire Dec 2027 Dave Johnston 2 Retire Dec 2027 Dave Johnston 3 Retire Dec 2027 Dave Johnston 4 Retire Dec 2027 Hayden 1 Retire Dec 2030 Hayden 2 SCR by Dec 2016, Retire Dec 2030 Hunter 1 SCR by 8/4/2021 or Retire by 7/31/2021 Hunter 2 SCR by 8/4/2021 or Retire by 7/31/2021 Hunter 3 Retire Dec 2042 Huntington 1 SCR by 8/4/2021 or Retire by 7/31/2021 Huntington 2 SCR by 8/4/2021 or Retire by 7/31/2021 Jim Bridger 1 SCR by 12/31/2022 or Retire by 12/30/2022 Jim Bridger 2 SCR by 12/31/2022 or Retire by 12/30/2022 Jim Bridger 3 Retire Dec 2037 Jim Bridger 4 SCR by Dec 2016, Retire Dec 2037 Naughton 1 Retire Dec 2029 Naughton 2 Retire Dec 2029 Naughton 3 Retire Dec 2017 Wyodak Retire Dec 2039 Case: OP-1 - 276 - Core Case OP-1 Core Case Fact Sheets CASE ASSUMPTIONS Description This case is the least-cost-least-risk Regional Haze case emerging from screening stage 1 (RH-5). The Regional Haze case with the best cost-risk metrics is promoted to become core case 1, and serves as the basis for further studies, including the remaining core cases and sensitivities. Therefore, as with the underlying Regional Haze case, all resources have been optimized (selected endogenously by System Optimizer), and valued in the Planning and Risk model. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,081 Transmission Integration $84 Transmission Reinforcement $12 Total Cost $23,177 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Regional Haze Core case OP-1 Regional Haze assumptions are summarized in the following table. SCR = selective catalytic reduction NOx = Low NOx burner (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Coal Unit Description Cholla 4 Retire Dec 2020 Colstrip 3 Retire Dec 2046 Colstrip 4 Retire Dec 2046 Craig 1 Retire Dec 2025 Craig 2 SCR by Dec 2017, Retire Dec 2034 Dave Johnston 1 Retire Dec 2027 Dave Johnston 2 Retire Dec 2027 Dave Johnston 3 Retire Dec 2027 Dave Johnston 4 Retire Dec 2027 Hayden 1 Retire Dec 2030 Hayden 2 SCR by Dec 2016, Retire Dec 2030 Hunter 1 NOx by Dec 2021, Retire Dec 2042 Hunter 2 NOx by Dec 2021, Retire Dec 2042 Hunter 3 Retire Dec 2042 Huntington 1 Retire Dec 2036 Huntington 2 Retire Dec 2036 Jim Bridger 1 Retire Dec 2028 Jim Bridger 2 Retire Dec 2032 Jim Bridger 3 Retire Dec 2037 Jim Bridger 4 SCR by Dec 2016, Retire Dec 2037Naughton 1 Retire Dec 2029 Naughton 2 Retire Dec 2029 Naughton 3 Gas Conversion by Dec 2019, Retire Dec 2029 Wyodak Retire Dec 2039 Case: Optimized Naughton 3 (OP-NT3) - 277 - Core Case: Optimized Naughton 3 (OP-NT3) Core Case Fact Sheets CASE ASSUMPTIONS Description Case OP-NT3 is the optimal Regional Haze case selected as core case 1 and includes enhancements of full PTC value and Naughton 3 retirement by December 31, 2018. All resources optimized (selected endogenously by System Optimizer), and valued in the Planning and Risk model. This case is a variant of core case OP-1. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,913 Transmission Integration $127 Transmission Reinforcement $12 Total Cost $23,052 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Regional Haze Core case OP-NT3 Regional Haze assumptions are summarized in the following table. SCR = selective catalytic reduction NOx = Low NOx burner (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Coal Unit Description Cholla 4 Retire Dec 2020 Colstrip 3 Retire Dec 2046 Colstrip 4 Retire Dec 2046 Craig 1 Retire Dec 2025 Craig 2 SCR by Dec 2017, Retire Dec 2034 Dave Johnston 1 Retire Dec 2027 Dave Johnston 2 Retire Dec 2027 Dave Johnston 3 Retire Dec 2027 Dave Johnston 4 Retire Dec 2027 Hayden 1 Retire Dec 2030 Hayden 2 SCR by Dec 2016, Retire Dec 2030 Hunter 1 NOx by Dec 2021, Shut Down Dec 2042 Hunter 2 NOx by Dec 2021, Shut Down Dec 2042 Hunter 3 Retire Dec 2042 Huntington 1 Retire Dec 2036 Huntington 2 Retire Dec 2036 Jim Bridger 1 Retire Dec 2028 Jim Bridger 2 Retire Dec 2032 Jim Bridger 3 Retire Dec 2037 Jim Bridger 4 SCR by Dec 2016, Retire Dec 2037 Naughton 1 Retire Dec 2029 Naughton 2 Retire Dec 2029 Naughton 3 Retire Dec 2018 Wyodak Retire Dec 2039 Case: Wind Repower (OP-REP) - 278 - Core Case: Wind Repower (OP-REP) Core Case Fact Sheets CASE ASSUMPTIONS Description Core case OP-REP assumes 905 MW of existing wind resources are repowered by the end of 2020 (Glenrock, Rolling Hills, Seven Mile Hill, High Plains, McFadden Ridge, Dunlap, Marengo and Leaning Juniper). The repower projects provide significant customer benefits among all market price and Clean Power Plan scenarios. The 20-year planning horizon used for the IRP is insufficient to capture the incremental wind generation associated with the extended life of the repowered wind facilities: incremental annual energy production is in excess of 500 GWh over the existing life of the wind projects and incremental annual energy production beyond the current existing life exceeds 3,100 GWh. This case is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,890 Transmission Integration $81 Transmission Reinforcement $12 Total Cost $22,984 Total Cost thru 2050 $22,638 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Case: Energy Gateway + Repower (OP-GW4) - 279 - Core Case: Energy Gateway + Repower (OP-GW4) Core Case Fact Sheets CASE ASSUMPTIONS Description Core case OP-GW4 assumes 905 MW of existing wind resources are repowered by the end of 2020 and Gateway segment D2 – Aeolus to Anticline (assumed in-service year- end 2020). In addition to the 300 MW of Wyoming wind in case OP-NT3, the additional transmission enables 900 MW of Wyoming wind additions in 2021 (proxy for year-end 2020). This case is a variant of core case OP-REP. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,612 Transmission Integration $94 Transmission Reinforcement $12 Gateway Transmission $405 Total Cost $23,123 Total Cost thru 2050 $22,777 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Transmission Path (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Case: Flexible Resource (FR-1) - 280 - Core Case: Flexible Resource (FR-1) Core Case Fact Sheets CASE ASSUMPTIONS Description In core case FR-1, fast ramp resources are added with a capacity of at least 10 percent of the system L&R need. Fast-ramp resources available for selection include: SCCT Aero (i.e., LM6000); Intercooled SCCT Aero (i.e., LMS100); IC Reciprocating Engines; pumped storage, compressed air energy storage, and battery storage. This case is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,463 Transmission Integration $110 Transmission Reinforcement $12 Total Cost $23,585 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Case: Flexible Resource (FR-2) - 281 - Core Case: Flexible Resource (FR-2) Core Case Fact Sheets CASE ASSUMPTIONS Description In core case FR-2 fast ramp resources are added with a capacity of at least 20 percent of the system L&R need. Fast-ramp resources available for selection include: SCCT Aero (i.e., LM6000); Intercooled SCCT Aero (i.e., LMS100); IC Reciprocating Engines; pumped storage, compressed air energy storage, and battery storage. This case is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $24,136 Transmission Integration $170 Transmission Reinforcement $12 Total Cost $24,319 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Case: OR RPS Just in Time (RE-1a) - 282 - Core Case: Oregon RPS Just in Time (RE-1a) Core Case Fact Sheets CASE ASSUMPTIONS Description Case RE-1a retains endogenous renewables from core case 1 (OP-1) and includes additional renewables added to physically comply with Oregon RPS. Additions are made beginning the first year in which there is a projected compliance shortfall (just-in-time compliance). This case is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,945 Transmission Integration $126 Transmission Reinforcement $12 Total Cost $23,082 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Case: WA RPS Just in Time (RE-1b) - 283 - Core Case: WA RPS Just in Time (RE-1b) Core Case Fact Sheets CASE ASSUMPTIONS Description Case RE-1b retains endogenous renewables from core case 1 (OP-1) and includes additional renewables added to physically comply with Washington RPS. West Control Area renewable resource additions only. Additions are made beginning the first year in which there is a projected compliance shortfall (just-in-time compliance). This case is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,962 Transmission Integration $116 Transmission Reinforcement $12 Total Cost $23,091 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Case: OR & WA RPS Just in Time (RE-1c) - 284 - Core Case: OR & WA RPS Just in Time (RE-1c) Core Case Fact Sheets CASE ASSUMPTIONS Description Case RE-1c retains endogenous renewables from core case 1 (OP-1) and includes additional renewables added to physically comply with Oregon and Washington RPS. Additions are made beginning the first year in which there is a projected compliance shortfall (just-in-time compliance). This case is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,016 Transmission Integration $126 Transmission Reinforcement $12 Total Cost $23,154 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Case: OR RPS Early (RE-2) - 285 - Core Case: OR RPS Early (RE-2) Core Case Fact Sheets CASE ASSUMPTIONS Description Case RE-2 retains endogenous renewables from core case 1 and includes additional renewables to physically comply with projected Oregon RPS requirements. Additions are also made in 2021 (proxy for year-end 2020) to meet requirements throughout the planning period (early compliance). This case is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,967 Transmission Integration $119 Transmission Reinforcement $12 Total Cost $23,098 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Core Case: Direct Load Control (DLC-1) - 286 - Core Case: Direct Load Control (DLC-1) Core Case Fact Sheets CASE ASSUMPTIONS Description Case DLC-1 is a reference case with additional Direct Load Control (DLC) added to core case 1 in the first year (2021). Added DLC capacity is at least five percent of the system L&R need. Renewable resource assumptions are consistent with Case 4 (RE-1c), assuming Oregon and Washington physical RPS just-in-time compliance. This case is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,942 Transmission Integration $149 Transmission Reinforcement $12 Total Cost $23,103 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Sensitivity: Regional Haze (RH-2a) - 287 - Sensitivity: Regional Haze (RH-2a) Sensitivity Fact Sheets CASE ASSUMPTIONS Description In response to stakeholder feedback, Case RH-2a examines the impact of a Naughton 3 retirement year-end 2017 and a Craig 1 retirement year-end 2025 as an alternative to Case RH-2. This sensitivity is a variant of core case RH2. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,237 Transmission Integration $154 Transmission Reinforcement $12 Total Cost $23,404 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Regional Haze Sensitivity RH-2a Regional Haze assumptions are summarized in the following table. SCR = selective catalytic reduction (5) (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Coal Unit Description Cholla 4 Retire Dec 2020 Colstrip 3 Retire Dec 2046 Colstrip 4 Retire Dec 2046 Craig 1 Retire Dec 2025 Craig 2 SCR by Dec 2017, Retire Dec 2034 Dave Johnston 1 Retire Dec 2027 Dave Johnston 2 Retire Dec 2027 Dave Johnston 3 Retire Dec 2027 Dave Johnston 4 Retire Dec 2032 Hayden 1 Retire Dec 2030 Hayden 2 SCR by Dec 2016, Retire Dec 2030 Hunter 1 Retire Dec 2031 Hunter 2 Retire Dec 2031 Hunter 3 Retire Dec 2042 Huntington 1 Retire Dec 2036 Huntington 2 Retire Dec 2036 Jim Bridger 1 Retire Dec 2024 Jim Bridger 2 Retire Dec 2028 Jim Bridger 3 Retire Dec 2037 Jim Bridger 4 SCR by Dec 2016, Retire Dec 2037 Naughton 1 Retire Dec 2029 Naughton 2 Retire Dec 2029 Naughton 3 Retire Dec 2017 Wyodak Retire Dec 2039 Sensitivity: 1 in 20 Load Growth (LD-1) - 288 - Sensitivity: 1in 20 Load Growth (LD-1) Sensitivity Fact Sheets CASE ASSUMPTIONS Description The 1-in-20 peak load sensitivity is a five percent probability extreme weather scenario. The 1-in-20 year peak weather is defined as the year for which the peak has the chance of occurring once in 20 years. This sensitivity is based on 1-in-20 peak weather for July in each state. This sensitivity is a variant of core case OP-1. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,207 Transmission Integration $144 Transmission Reinforcement $12 Total Cost $23,364 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Load Forecast The figure below shows the base system coincident peak load forecast applicable to this case before accounting for any potential contribution from DSM alongside Base Case forecast. Loads include private generation resources. Energy load forecast is identical to Base Case. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement 9,000 9,500 10,000 10,500 11,000 11,500 12,000 12,500 13,000 13,500 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 MW Coincident System Peak Load Base 1 in 20 Sensitivity: Low Load (LD-2) - 289 - Sensitivity: Low Load (LD-2) Sensitivity Fact Sheets CASE ASSUMPTIONS Description The low load forecast sensitivity reflects pessimistic economic growth assumptions from IHS Global Insight and low Utah and Wyoming industrial loads. The low and high industrial load forecasts focus on increased uncertainty in industrial loads further out in time. To capture this uncertainty, PacifiCorp modeled 1,000 possible annual loads for each year based on the standard error of the medium scenario regression equation. The low industrial load forecast is taken from 5th percentile. This sensitivity is a variant of core case OP-1. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $21,512 Transmission Integration $42 Transmission Reinforcement $12 Total Cost $21,567 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Load Forecast The figure below shows the base system coincident peak load forecast applicable to this case before accounting for any potential contribution from DSM alongside Base Case forecast. Loads include private generation resources. The figure below shows the base energy load forecast applicable to this case before accounting for any potential contribution from DSM alongside Base Case forecast. Loads include private generation resources. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement 9,000 9,500 10,000 10,500 11,000 11,500 12,000 12,500 13,000 13,500 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 MW Coincident System Peak Load Base Low Load 55,000 60,000 65,000 70,000 75,000 80,000 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW h System Energy Load Base Low Load Sensitivity: High Load (LD-3) - 290 - Sensitivity: High Load (LD-3) Sensitivity Fact Sheets CASE ASSUMPTIONS Description The high load forecast sensitivity reflects optimistic economic growth assumptions from IHS Global Insight and low Utah and Wyoming industrial loads. The low and high industrial load forecasts focus on increased uncertainty in industrial loads further out in time. To capture this uncertainty, PacifiCorp modeled 1,000 possible annual loads for each year based on the standard error of the medium scenario regression equation. The high industrial load forecast is taken from 95th percentile. This sensitivity is a variant of core case OP-1. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $24,629 Transmission Integration $177 Transmission Reinforcement $12 Total Cost $24,818 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Load Forecast The figure below shows the base system coincident peak load forecast applicable to this case before accounting for any potential contribution from DSM alongside Base Case forecast. Loads include private generation resources. The figure below shows the base energy load forecast applicable to this case before accounting for any potential contribution from DSM alongside Base Case forecast. Loads include private generation resources. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement 9,000 9,500 10,000 10,500 11,000 11,500 12,000 12,500 13,000 13,500 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 MW Coincident System Peak Load Base High Load 55,000 60,000 65,000 70,000 75,000 80,000 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW h System Energy Load Base High Load Sensitivity: Low Private Gen (PG-1) - 291 - Sensitivity: Low Private Gen (PG-1) Sensitivity Fact Sheets CASE ASSUMPTIONS Description The low private generation sensitivity reflects reductions in technology costs, reduced technology performance levels, and lower retail electricity rates, compared to base penetration levels incorporating annual reductions in technology costs. This sensitivity is a variant of core case OP-1. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,203 Transmission Integration $89 Transmission Reinforcement $12 Total Cost $23,304 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Load Forecast The figure below shows the base system coincident peak load forecast applicable to this case before accounting for any potential contribution from DSM alongside Base Case forecast. Loads include private generation resources. The figure below shows the base energy load forecast applicable to this case before accounting for any potential contribution from DSM alongside Base Case forecast. Loads include private generation resources. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement 9,000 9,500 10,000 10,500 11,000 11,500 12,000 12,500 13,000 13,500 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 20 3 7 MW Coincident System Peak Load Base Low PG 55,000 60,000 65,000 70,000 75,000 80,000 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW h System Energy Load Base Low PG Sensitivity: Low Private Gen (PG-1) - 292 - Sensitivity: Low Private Gen (PG-1) Private Generation Scenario private generation penetration by state and year are summarized in the following figure. 0 500 1,000 1,500 2,000 2,500 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 MW Distributed Generation - Low Penetration Case UT OR WA WY ID CA Sensitivity: High Private Gen (PG-2) - 293 - Sensitivity: High Private Gen (PG-2) Sensitivity Fact Sheets CASE ASSUMPTIONS Description The high private generation sensitivity reflects more aggressive technology cost reduction assumptions, higher technology performance levels, and higher retail electricity rates, compared to base penetration levels incorporating annual reductions in technology costs. This sensitivity is a variant of core case OP-1. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,782 Transmission Integration $105 Transmission Reinforcement $12 Total Cost $22,899 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Load Forecast The figure below shows the base system coincident peak load forecast applicable to this case before accounting for any potential contribution from DSM alongside Base Case forecast. Loads include private generation resources. The figure below shows the base energy load forecast applicable to this case before accounting for any potential contribution from DSM alongside Base Case forecast. Loads include private generation resources. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement 9,000 9,500 10,000 10,500 11,000 11,500 12,000 12,500 13,000 13,500 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 MW Coincident System Peak Load Base High PG 55,000 60,000 65,000 70,000 75,000 80,000 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW h System Energy Load Base High PG Sensitivity: High Private Gen (PG-2) - 294 - Sensitivity: High Private Gen (PG-2) Private Generation Scenario private generation penetration by state and year are summarized in the following figure. 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 MW Distributed Generation - High Penetration Case UT OR WA WY ID CA Sensitivity: CPP Mass Cap C (CPP-C) - 295 - Sensitivity: CPP Mass Cap C (CPP-C) Sensitivity Fact Sheets CASE ASSUMPTIONS Description The CPP Mass Cap C scenario reflects the mass based compliance approach with pro-rata allowance allocation based on historical generation with no new source complement less the CEIP (Clean Energy Incentive Program), renewable and output-based set-asides. PacifiCorp does not receive any allocation of set-asides. New resources are not restricted by the CPP cap. (the CEIP is an optional “matching fund” program that states may choose to use to incentivize wind or solar power generation in all communities and energy efficiency measures in low-income communities.) This sensitivity is a variant of core case OP-1. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,129 Transmission Integration $126 Transmission Reinforcement $12 Total Cost $23,268 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. System CO2 Emissions (System Optimizer) System CO2 Emissions from System Optimizer are shown alongside those from Base Case in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement 20.0 22.5 25.0 27.5 30.0 32.5 35.0 37.5 40.0 42.5 45.0 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 Mi l l i o n T o n s Mass Cap Mass Cap B Mass Cap C Sensitivity: CPP Mass Cap D (CPP-D) - 296 - Sensitivity: CPP Mass Cap D (CPP-D) Sensitivity Fact Sheets CASE ASSUMPTIONS Description The CPP Mass Cap D scenario reflects the mass based compliance approach with no set-aside program, but does benefit from the new source complement, which assumes that the mass-based limit grows to accommodate new resources needed to meet load growth. This sensitivity is a variant of core case OP-1. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,010 Transmission Integration $79 Transmission Reinforcement $12 Total Cost $23,102 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. System CO2 Emissions (System Optimizer) System CO2 Emissions from System Optimizer are shown alongside those from Base Case in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement 20.0 22.5 25.0 27.5 30.0 32.535.037.540.042.545.047.550.0 52.5 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 Mi l l i o n T o n s Mass Cap Mass Cap B Mass Cap D Sensitivity: Limited FOTs (FOT-1) - 297 - Sensitivity Limited FOTs (FOT-1) Sensitivity Fact Sheets CASE ASSUMPTIONS Description PacifiCorp develops FOT limits based on its active participation in wholesale power markets; its view of physical delivery constraints, market liquidity, and market depth; and with consideration of regional resource supply. Alternative FOT limit assumptions applied during the portfolio development process eliminates the availability of FOTs at the NOB (100 MW) and Mona (300 MW) market hubs in summer and winter beginning 2021. This sensitivity is a variant of core case OP-1. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,189 Transmission Integration $145 Transmission Reinforcement $12 Total Cost $23,347 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Sensitivity: CO2 Price, No CPP (CO2-1) - 298 - Sensitivity: CO2 Price, No CPP (CO2-1) Sensitivity Fact Sheets CASE ASSUMPTIONS Description The CO2 Price sensitivity examines the impact of replacing the Clean Power Plan (currently stayed by the U.S. Supreme Court) with an CO2 proxy price beginning in the year 2025, based on the assumption that even if the CPP is not in effect, there will be some carbon-based policy in place by this time. CO2 prices applied to each ton of CO2 emissions from new and existing resources, beginning in 2025 at $4.75/ton and reaching $38.02/ton by 2036. This sensitivity is a variant of core case OP-1. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $26,222 Transmission Integration $166 Transmission Reinforcement $12 Total Cost $26,401 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. System CO2 Emissions (System Optimizer) System CO2 Emissions from System Optimizer are shown in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement 0.00 10.00 20.00 30.00 40.00 50.00 60.00 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 Mi l l i o n T o n s System CO2 Emissions (System Optimizer) Mass Cap B Sensitivity: No CO2 Policy (No-CO2) - 299 - Sensitivity: No CO2 Policy (No-CO2) Sensitivity Fact Sheets CASE ASSUMPTIONS Description The No CO2 sensitivity is a response to a stakeholder request and examines the impact of having no incremental state or federal CO2 emissions policy in place through the 2017 – 2036 study period. This sensitivity is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,787 Transmission Integration $91 Transmission Reinforcement $12 Total Cost $22,891 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Sensitivity: Business Plan (BP) - 300 - Sensitivity: Business Plan (BP) Sensitivity Fact Sheets CASE ASSUMPTIONS Description The Business Plan sensitivity complies with the Utah requirement to perform a business plan sensitivity consistent with the commission’s order in Docket No. 15-035-04. Over the first three years, resources align with those assumed in PacifiCorp’s Fall 2016 Business Plan. Beyond the first three years of the study period, unit retirement assumptions are aligned with the draft preferred portfolio selected from the second screening stage. All other resources are optimized. Note that initially, these assumptions were expected to align with core case 1. Due to the timing of this sensitivity, the study was modeled based on the outcome of a later screening stage. This serves to make the business plan sensitivity closer to the eventual preferred portfolio selection, and therefore a more indicative comparison. This sensitivity is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $23,053 Transmission Integration $133 Transmission Reinforcement $12 Total Cost $23,198 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Sensitivity: Energy Gateway 1 (GW1) - 301 - Sensitivity: Energy Gateway 1 (GW1) Sensitivity Fact Sheets CASE ASSUMPTIONS Description Sensitivity GW1 includes segment D – Windstar to Anticline (assumed in-service 2022). In addition to the 300 MW of Wyoming wind in case OP-NT3, the additional transmission enables 440 MW of Wyoming wind additions. This sensitivity is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,803 Transmission Integration $125 Transmission Reinforcement $12 $652 Total Cost $23,593 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Transmission Transmission path is shown in the map below (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Sensitivity: Energy Gateway 2 (GW2) - 302 - Sensitivity: Energy Gateway 2 (GW2) Sensitivity Fact Sheets CASE ASSUMPTIONS Description Sensitivity GW2 includes Segment F – Windstar to Mona/Clover (assumed in-service 2023). In addition to the 300 MW of Wyoming wind in case OP-NT3, the additional transmission enables 440 MW of Wyoming wind additions. This sensitivity is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,841 Transmission Integration $132 Transmission Reinforcement $12 Gateway Transmission $1,068 Total Cost $24,054 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Transmission Transmission path is shown in the map below (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Sensitivity: Energy Gateway 3 (GW3) - 303 - Sensitivity: Energy Gateway 3 (GW3) Sensitivity Fact Sheets CASE ASSUMPTIONS Description Sensitivity GW3 includes segments D & F – Windstar to Anticline and Aeolus to Mona/Clover (assumed in-service 2022 and 2023, respectively). In addition to the 300 MW of Wyoming wind in case OP-NT3, the additional transmission enables 1,200 MW of Wyoming wind additions. This sensitivity is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,706 Transmission Integration $96 Transmission Reinforcement $12 $1,813 Total Cost $24,627 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Transmission Transmission path is shown in the map below (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Sensitivity: Energy Gateway 4 (GW4) - 304 - Sensitivity: Energy Gateway (GW4) Sensitivity Fact Sheets CASE ASSUMPTIONS Description Sensitivity GW4 includes segment D2 – Aeolus to Anticline (assumed in-service year-end 2020). In addition to the 300 MW of Wyoming wind in case OP-NT3, the additional transmission enables 900 MW of Wyoming wind additions in 2021 (proxy for year-end 2020). This sensitivity is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,648 Transmission Integration $94 Transmission Reinforcement $12 Gateway Transmission $405 Total Cost $23,159 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Transmission Transmission path is shown in the map below (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Sensitivity: Energy Storage 1 (Battery) - 305 - Sensitivity: Energy Storage 1 (Battery) Sensitivity Fact Sheets CASE ASSUMPTIONS Description The battery storage sensitivity is the first of two storage sensitivities that force large scale energy storage resources into the resource portfolio, but allow the models to optimize their usage. This sensitivity forces 80 MW of battery storage capacity also in PacifiCorp’s east BAA (Wyoming). The site was based on a qualitative assessment of locations best suited for storage to provide support for added renewables, in the expectation that storage plants have the ability to mitigate the non-dispatchable nature of wind and solar energy production. Study includes Gateway segment D2 – Aeolus to Anticline (assumed in-service year-end 2020). In addition to the 300 MW of Wyoming wind in case OP-NT3, the additional transmission enables 800 MW of Wyoming wind additions in 2021 (proxy for year-end 2020), reflecting a refinement of the initial Gateway 4 analysis (OP-GW4). This sensitivity is a variant of core case FS-GW4. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,735 Transmission Integration $81 Transmission Reinforcement $12 Gateway Transmission $334 Total Cost $23,162 Total Cost thru 2050 $22,901 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Sensitivity: Energy Storage 2 (CAES) - 306 - Sensitivity: Energy Storage 2 (CAES) Sensitivity Fact Sheets CASE ASSUMPTIONS Description The CAES storage sensitivity is the second of two storage sensitivities that force large scale energy storage resources into the resource portfolio, but allow the models to optimize their usage. This sensitivity forces an 80 MW compressed air storage plant (CAES) sited in PacifiCorp’s east BAA (Utah South). The site was based on a qualitative assessment of locations best suited for storage to provide support for added renewables, in the expectation that storage plants have the ability to mitigate the non-dispatchable nature of wind and solar energy production. Study includes Gateway segment D2 – Aeolus to Anticline (assumed in-service year-end 2020). In addition to the 300 MW of Wyoming wind in case OP-NT3, the additional transmission enables 800 MW of Wyoming wind additions in 2021 (proxy for year-end 2020), reflecting a refinement of the initial Gateway 4 analysis (OP-GW4). This sensitivity is a variant of core case FS-GW4. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,659 Transmission Integration $116 Transmission Reinforcement $12 Gateway Transmission $334 Total Cost $23,121 Total Cost thru 2050 $22,860 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Sensitivity: WCA - 307 - Sensitivity: WCA Sensitivity Fact Sheets CASE ASSUMPTIONS Description The WCA sensitivity assumes separate balancing authority areas (BAA) for the Company’s East and West territory and produces standalone resource portfolios for the WCA, as required by the Washington Utilities and Transportation Commission. Key assumptions include maintaining a 13 percent reserve margin applicable to summer and winter peak; allowing on-peak FOT’s with limits at Mid-C (775 MW), COB (400 MW) and NOB (100 MW); including all of Jim Bridger in the west BAA; including Colstrip in the west BAA up to transmission limits; and applying Mass Cap B and CAR emission limits. This sensitivity is a variant of core case FS-REP. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $7,539 Transmission Integration $4 Transmission Reinforcement $0 Total Cost $7,542 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Sensitivity: WCA RPS - 308 - Sensitivity: WCA RPS Sensitivity Fact Sheets CASE ASSUMPTIONS Description The WCA RPS sensitivity assumes separate balancing authority areas (BAA) for the Company’s East and West territory and produces standalone resource portfolios for the WCA, as required by the Washington Utilities and Transportation Commission. In addition, the sensitivity assumes compliance with Washington RPS requirements. Key assumptions include maintaining a 13 percent reserve margin applicable to summer and winter peak; allowing on-peak FOT’s with limits at Mid-C (775 MW), COB (400 MW) and NOB (100 MW); including all of Jim Bridger in the west BAA; including Colstrip in the west BAA up to transmission limits; and applying Mass Cap B and CAR emission limits. This sensitivity is a variant of core case FS-REP. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $7,554 Transmission Integration $4 Transmission Reinforcement $0 Total Cost $7,557 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Final Selection: Wind Repower (FS-REP) - 309 - Final Selection: Wind Repower (FS-REP) Final Selection Fact Sheets CASE ASSUMPTIONS Description Final screening case FS-REP assumes 905 MW of existing wind resources are repowered by the end of 2020 (Glenrock, Rolling Hills, Seven Mile Hill, High Plains, McFadden Ridge, Dunlap, Marengo and Leaning Juniper) and was updated with more current wind shape information. This case is a variant of core case OP-NT3. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,907 Transmission Integration $123 Transmission Reinforcement $12 Total Cost $23,042 Total Cost thru 2050 $22,781 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. (4)(3)(2)(1)01234567891011 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Final Selection: Gateway 4 (FS-GW4) - 310 - Final Selection: Gateway 4 (FS-GW4) Final Selection Fact Sheets CASE ASSUMPTIONS Description Final screening case FS-GW4 assumes 905 MW of existing wind resources are repowered by the end of 2020. Study includes Gateway segment D2 – Aeolus to Anticline (assumed in-service year-end 2020). In addition to the 300 MW of Wyoming wind in case OP-NT3, the additional transmission enables 800 MW of Wyoming wind additions in 2021 (proxy for year-end 2020), reflecting a refinement of the initial Gateway 4 analysis (OP-GW4). This case is a variant of final selection FS-REP. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,549 Transmission Integration $95 Transmission Reinforcement $12 Gateway Transmission $334 Total Cost $22,990 Total Cost thru 2050 $22,729 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Transmission Path (4) (3) (2) (1) - 1 2 3 4 5 6 7 8 9 10 11 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Final Selection: OR & WA RPS Just in Time (FS-R1c) - 311 - Final Selection: OR & WA RPS Just in Time (FS-R1c) Final Selection Fact Sheets CASE ASSUMPTIONS Description Final screening case FS-R1c assumes 905 MW of existing wind resources are repowered by the end of 2020. Study includes Gateway segment D2 – Aeolus to Anticline (assumed in-service year-end 2020). In addition to the 300 MW of Wyoming wind in case OP-NT3, the additional transmission enables 800 MW of Wyoming wind additions in 2021 (proxy for year-end 2020), reflecting a refinement of the initial Gateway 4 analysis (OP-GW4). This study also includes additional renewables added to physically comply with Oregon and Washington RPS. Renewable additions are made beginning the first year in which there is a projected compliance shortfall (just-in-time compliance). This case is a variant of final selection FS-GW4. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,561 Transmission Integration $99 Transmission Reinforcement $12 Gateway Transmission $334 Total Cost $23,006 Total Cost thru 2050 $22,745 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Transmission Transmission path is shown in the map below (4)(3)(2)(1)01234567891011 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement Final Selection: OR RPS Early (FS-R2) - 312 - Final Selection: OR RPS Early (FS-R2) Final Selection Fact Sheets CASE ASSUMPTIONS Description Final screening case FS-R2 assumes 905 MW of existing wind resources are repowered by the end of 2020. Study includes Gateway segment D2 – Aeolus to Anticline (assumed in- service year-end 2020). In addition to the 300 MW of Wyoming wind in case OP-NT3, the additional transmission enables 800 MW of Wyoming wind additions in 2021 (proxy for year-end 2020), reflecting a refinement of the initial Gateway 4 analysis (OP-GW4). This study includes additional renewables added to physically comply with projected Oregon RPS requirements. Renewable additions are made in 2021 (proxy for year-end 2020) to meet requirements throughout the planning period (early compliance). This case is a variant of final selection FS-GW4. PORTFOLIO SUMMARY System Optimizer PVRR ($m) System Cost without Transmission Upgrades $22,554 Transmission Integration $95 Transmission Reinforcement $12 Gateway Transmission $334 Total Cost $22,995 Total Cost thru 2050 $22,734 Resource Portfolio Cumulative changes to the resource portfolio (new resource additions and resource retirements), represented as nameplate capacity, are summarized in the figure below. Transmission Transmission path is shown in the map below (4)(3)(2)(1)01234567891011 20 1 7 20 1 8 20 1 9 20 2 0 20 2 1 20 2 2 20 2 3 20 2 4 20 2 5 20 2 6 20 2 7 20 2 8 20 2 9 20 3 0 20 3 1 20 3 2 20 3 3 20 3 4 20 3 5 20 3 6 GW Cumulative Nameplate Capacity DSM FOTs GasRenewableGas Conversion OtherEarly Retirement End of Life Retirement PACIFICORP – 2017 IRP APPENDIX N – WIND AND SOLAR CAPACITY CONTRIBUTION STUDY 313 APPENDIX N – WIND AND SOLAR CAPACITY CONTRIBUTION STUDY Introduction The capacity contribution of wind and solar resources, represented as a percentage of resource capacity, is a measure of the ability for these resources to reliably meet demand. For purposes of this report, PacifiCorp defines the peak capacity contribution of wind and solar resources as the availability among hours with the highest loss of load probability (LOLP). PacifiCorp calculated peak capacity contribution values for wind and solar resources using the capacity factor approximation method (CF Method) as outlined in a 2012 report produced by the National Renewable Energy Laboratory (NREL Report)1. The capacity contribution of wind and solar resources affects PacifiCorp’s resource planning activities. PacifiCorp conducts its resource planning to ensure there is sufficient capacity on its system to meet its load obligation at the time of system coincident peak inclusive of a planning reserve margin. To ensure resource adequacy is maintained over time, all resource portfolios evaluated in the integrated resource plan (IRP) have sufficient capacity to meet PacifiCorp’s net coincident peak load obligation inclusive of a planning reserve margin throughout a 20-year planning horizon. Consequently, planning for the coincident peak drives the amount and timing of new resources, while resource cost and performance metrics among a wide range of different resource alternatives drive the types of resources that can be chosen to minimize portfolio costs and risks. PacifiCorp derives its planning reserve margin from a LOLP study. The study evaluates the relationship between reliability across all hours in a given year, accounting for variability and uncertainty in load and generation resources, and the cost of planning for system resources at varying levels of planning reserve margin. In this way, PacifiCorp’s planning reserve margin LOLP study is the mechanism used to transform hourly reliability metrics into a resource adequacy target at the time of system coincident peak. This same LOLP study was utilized for calculating the peak capacity contribution using the CF Method. Error! Reference source not found., summarizes the peak capacity contribution results for PacifiCorp’s East and West balancing authority areas (BAAs). The CF Method ignores transmission constraints that can prevent resource output in a location from reaching an area location where loss of load events occur. If transmission constraints prevent resources from reaching areas with loss of load events, additional capacity in those areas may not provide an adequate planning reserve margin or contribute to reliability. At the January 26-27, 2017 public input meeting PacifiCorp identified the potential for transmission constraints to impact 1 Madaeni, S. H.; Sioshansi, R.; and Denholm, P. “Comparison of Capacity Value Methods for Photovoltaics in the Western United States.” NREL/TP-6A20-54704, Denver, CO: National Renewable Energy Laboratory, July 2012 (NREL Report). http://www.nrel.gov/docs/fy12osti/54704.pdf PACIFICORP – 2017 IRP APPENDIX N - CAPACITY CONTRIBUTION STUDY 314 the effective capacity contribution from resources in Wyoming Northeast, Oregon, and Utah South.2 In light of the inclusion of Energy Gateway transmission segment D2 described in Volume I, Chapter 4 (Transmission) in the 2017 IRP preferred portfolio, the Wyoming Northeast transmission area is less constrained. This is particularly evident during summer months when LOLP is highest, as wind output in that area is relatively low in the summer. The 2017 IRP preferred portfolio also includes significant expansion resources in the 2030 timeframe in Oregon and Utah South. By the time additional capacity is required and new resources are added, transmission congestion in these areas is reduced, relative to the 2020 sample year used in the capacity contribution analysis, as a result of load growth, expiring contracts, and retiring resources. Methodology The NREL Report summarizes several methods for estimating the capacity value of renewable resources that are broadly categorized into two classes: 1) reliability-based methods that are computationally intensive; and 2) approximation methods that use simplified calculations to approximate reliability-based results. The NREL Report references a study from Milligan and Parsons that evaluated capacity factor approximation methods, which use capacity factor data among varying sets of hours, relative to the more computationally intensive reliability-based effective load carrying capability (ELCC) metric. As discussed in the NREL Report, the CF Method was found to be the most dependable technique in deriving capacity contribution values that approximate those developed using the ELCC Method. As described in the NREL Report, the CF Method “considers the capacity factor of a generator over a subset of periods during which the system faces a high risk of an outage event.” When using the CF Method, hourly LOLP is calculated and then weighting factors are obtained by dividing each hour’s LOLP by the total LOLP over the period. These weighting factors are then applied to the contemporaneous hourly capacity factors for a wind or solar resource to produce a weighted average capacity contribution value. The weighting factors based on LOLP are defined as: 𝑤𝑖=𝐿𝑂𝐿𝑃𝑖 ∑𝐿𝑂𝐿𝑃𝑗𝑇𝑗=1 where wi is the weight in hour i, LOLPi is the LOLP in hour i, and T is the number of hours in the study period, which is 8,760 hours for the current study. These weights are then used to calculate the weighted average capacity factor as an approximation of the capacity contribution as: 𝐶𝑉=∑𝑤𝑖𝐶𝑖 𝑇 𝑖=1 , 2 2017 IRP: Public Input Meeting 7. January 26-27, 2017. Presentation available at http://www.pacificorp.com/content/dam/pacificorp/doc/Energy_Sources/Integrated_Resource_Plan/2017_IRP/Pacifi Corp_2017_IRP_PIM07_1-26-17_Presentation.pdf PACIFICORP – 2017 IRP APPENDIX N – WIND AND SOLAR CAPACITY CONTRIBUTION STUDY 315 where Ci is the capacity factor of the resource in hour i, and CV is the weighted capacity value of the resource. To determine the capacity contribution using the CF method, PacifiCorp implemented the following two steps: 1. A 500-iteration hourly Monte Carlo simulation of PacifiCorp’s system was produced using the Planning and Risk (PaR) model to simulate the dispatch of the Company’s system for a sample year (calendar year 2020). This PaR study is based on the Company’s 2017 IRP planning reserve margin study using a 13 percent target planning reserve margin level. The LOLP for each hour in the year is calculated by counting the number of iterations in which system load could not be met with available resources and dividing by 500 (the total number iterations). For example, if in hour 9 on January 12th there are two iterations with Energy Not Served (ENS) out of a total of 500 iterations, then the LOLP for that hour would be 0.4 percent.3 2. Weighting factors were determined based upon the LOLP in each hour divided by the sum of LOLP among all hours. In the example noted above, the sum of LOLP among all hours is 143 percent.4 The weighting factor for hour 9 on January 12th would be 0.2797 percent.5 The hourly weighting factors are then applied to the capacity factors of wind and solar resources in the corresponding hours to determine the weighted capacity contribution value in those hours. Extending the example noted, if a resource has a capacity factor of 41.0 percent in hour 9 on January 12th, its weighted annual capacity contribution for that hour would be 0.1146 percent.6 Results Table N.1 summarizes the resulting annual capacity contribution using the CF Method described above as compared to capacity contribution values assumed in the 2015 IRP. In implementing the CF Method, PacifiCorp used actual wind project data from wind resources operating in its system to derive hourly wind capacity factor inputs. For solar resources, PacifiCorp used solar profiles from signed solar projects to apply to the 2017 IRP, differentiated between single axis tracking and fixed tilt projects. Separate solar and wind capacity contribution values were calculated using profiles corresponding to the East and West BAAs. 3 0.4 percent = 2 / 500. 4 For each hour, the hourly LOLP is calculated as the number of iterations with ENS divided by the total of 500 iterations. There are 715 ENS iteration-hours out of total of 8,760 hours. As a result, the sum of LOLP is 715 / 500 = 143 percent. 5 0.2797 percent = 0.4 percent / 143 percent, or simply 0.2797 percent = 2 / 715. 6 0.1146 percent = 0.2797 percent x 41.0 percent. PACIFICORP – 2017 IRP APPENDIX N - CAPACITY CONTRIBUTION STUDY 316 Table N.1 – Peak Capacity Contribution Values for Wind and Solar East BAA West BAA Wind Fixed Tilt Solar PV Single Axis Tracking Solar PV Wind Fixed Tilt Solar PV Single Axis Tracking Solar PV 2017 IRP Results 15.8% 37.9% 59.7.8% 11.8% 53.9% 64.8% 2015 IRP Results 14.5% 34.1% 39.1% 25.4% 32.2% 36.7% Figure N.1 presents daily average LOLP results from the PaR simulation, which shows that loss of load events are most likely to occur during the summer when load peaks in July. Figure N.1 – Daily LOLP Figure N.2 presents the relationship between monthly capacity factors among wind and solar resources (primary y-axis) and average monthly LOLP from the PaR simulation (secondary y- axis) in PacifiCorp’s CF Method analysis. As noted above, the average monthly LOLP is most prominent in summer (July peak loads). 0.00% 0.50% 1.00% 1.50% 2.00% 2.50% 3.00% 3.50% 4.00% Pe r c e n t a g e PACIFICORP – 2017 IRP APPENDIX N – WIND AND SOLAR CAPACITY CONTRIBUTION STUDY 317 Figure N.2 – Monthly Resource Capacity Factors as Compared to LOLP Figure N.3 presents the average hourly capacity factors for wind and solar resources (primary y- axis) as compared to the average hourly LOLP (secondary y-axis) for the month of July. In July, LOLP events peak during higher load hours and during the evening ramp. 0.00% 0.05% 0.10% 0.15% 0.20% 0.25% 0.30% 0% 10% 20% 30% 40% 50% 60% 1 2 3 4 5 6 7 8 9 10 11 12 Lo s s o f L o a d P r o b a b i l i t y Ca p a c i t y F a c t o r Month Wind, West Wind, East East Single Tracking Solar East Fixed Tilt Solar West Single Tracking Solar West Fixed Tilt Solar Loss of Load Probability PACIFICORP – 2017 IRP APPENDIX N - CAPACITY CONTRIBUTION STUDY 318 Figure N.3 – Hourly Resource Capacity Factors as Compared to LOLP for an Average Day in July Conclusion PacifiCorp conducts its resource planning by ensuring there is sufficient capacity on its system to meet its net load obligation at the time of system coincident peak inclusive of a planning reserve margin. The peak capacity contribution of wind and solar resources, represented as a percentage of resource capacity, is the weighted average capacity factor of these resources during periods when load cannot be met with available resources. The peak capacity contribution values developed using the CF Method are based on a LOLP study that aligns with PacifiCorp’s 13 percent planning reserve margin, and therefore represent the expected contribution that wind and solar resources make toward achieving PacifiCorp’s target resource planning criteria. 0.00% 0.20% 0.40% 0.60% 0.80% 1.00% 1.20% 1.40% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Lo s s o f L o a d P r o b a b i l i t y Ca p a c i t y F a c t o r / L o a d Hour Hourly Resource Capacity Factor Compared to Loss of Load Probability for Average Day in July Wind, West Wind, East East Single Tracking Solar East Fixed Tilt Solar West Single Tracking Solar West Fixed Tilt Solar Loss of Load Probability PACIFICORP – 2017 IRP APPENDIX O – PRIVATE GENERATION STUDY APPENDIX O - INTRODUCTION 319 APPENDIX O – PRIVATE GENERATION STUDY Introduction Navigant Consulting, Inc. prepared the Private Generation Long-Term Resource Assessment (2017-2036) for PacifiCorp. A key objective of this research is to assist PacifiCorp in developing private generation resource penetration forecasts to support its 2017 Integrated Resource Plan. The purpose of this study is to project the level of private generation resources PacifiCorp’s customers might install over the next twenty years. PACIFICORP – 2017 IRP APPENDIX O – PRIVATE GENERATION STUDY 320 ©2016 Navigant Consulting, Inc. Private Generation Long-Term Resource Assessment (2017-2036) Prepared for: PacifiCorp Prepared by: Karin Corfee Shalom Goffri Andrea Romano July 29th, 2016 Corrected: December 22nd, 2016 Navigant Consulting, Inc. One Market Street Spear Street Tower, Suite 1200 San Francisco, CA 94105 415.356.7100 navigant.com Reference No.: 184060 Private Generation Long-Term Resource Assessment (2017-2036) Page ii ©2016 Navigant Consulting, Inc. TABLE OF CONTENTS Executive Summary ...................................................................................................... 1 Key Findings ........................................................................................................................................ 2 Report Organization ............................................................................................................................ 5 Private Generation Market Penetration Methodology ................................................ 1 1.1 Methodology .................................................................................................................................. 1 1.2 Market Penetration Approach ....................................................................................................... 1 1.3 Assess Technical Potential ........................................................................................................... 2 1.4 Simple Payback ............................................................................................................................. 2 1.5 Payback Acceptance Curves ........................................................................................................ 3 1.6 Market Penetration Curves ........................................................................................................... 3 1.7 Key Assumptions ........................................................................................................................... 5 1.7.1 Technology Assumptions ................................................................................................. 5 1.7.2 Scenario Assumptions .................................................................................................... 13 1.7.3 Incentives ....................................................................................................................... 13 Results ......................................................................................................................... 17 1.8 PacifiCorp Territories ................................................................................................................... 17 1.8.1 California ........................................................................................................................ 18 1.8.2 Idaho ............................................................................................................................... 20 1.8.3 Oregon ............................................................................................................................ 23 1.8.4 Utah ................................................................................................................................ 26 1.8.5 Washington ..................................................................................................................... 28 1.8.6 Wyoming ......................................................................................................................... 31 Customer Data ................................................................................... A-1 System Capacity Assumptions ........................................................ B-3 Storage Evaluation ............................................................................ C-7 C.1 Drivers....................................................................................................................................... C-7 C.2 Challenges ................................................................................................................................ C-8 C.3 Policy ........................................................................................................................................ C-8 Federal and State ............................................................................................................................ C-8 C.4 Storage Customer Applications ................................................................................................ C-9 Non-Residential Solar + Storage ................................................................................................... C-10 Residential Solar + Storage .......................................................................................................... C-10 Wind + Storage .............................................................................................................................. C-10 Hydro + Storage ............................................................................................................................ C-11 CHP + Storage .............................................................................................................................. C-11 Washington high-efficiency cogeneration Levelized Costs ........ D-12 D.1 Key Assumptions .................................................................................................................... D-12 D.2 Results .................................................................................................................................... D-13 Private Generation Long-Term Resource Assessment (2017-2036) Page iii ©2016 Navigant Consulting, Inc. Comparison of 2016 and 2014 Study .............................................. E-14 Detailed Numeric Results ................................................................. F-16 F.1 Utah ......................................................................................................................................... F-16 F.2 Oregon .................................................................................................................................... F-22 F.3 Washington ............................................................................................................................. F-28 F.4 Idaho ....................................................................................................................................... F-34 F.5 California ................................................................................................................................. F-40 F.6 Wyoming ................................................................................................................................. F-46 Private Generation Long-Term Resource Assessment (2017-2036) Page iv ©2016 Navigant Consulting, Inc. DISCLAIMER This report was prepared by Navigant Consulting, Inc. (Navigant) for PacifiCorp and/or its affiliates or subsidiaries. The work presented in this report represents Navigant’s professional judgment based on the information available at the time this report was prepared. Navigant is not responsible for the reader’s use of, or reliance upon, the report, nor any decisions based on the report. NAVIGANT MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESSED OR IMPLIED. Readers of the report are advised that they assume all liabilities incurred by them, or third parties, as a result of their reliance on the report, or the data, information, findings and opinions contained in the report. July 29th, 2016 Private Generation Long-Term Resource Assessment (2017-2036) Page 1 ©2016 Navigant Consulting, Inc. EXECUTIVE SUMMARY Navigant Consulting, Inc. (Navigant) prepared this Long-term Private Generation Resource Assessment on behalf of PacifiCorp. Private generation sources provide customer-sited energy generation and are generally of relatively small size, generating less than the amount of energy used at a particular location. The purpose of this study is to support PacifiCorp’s 2017 Integrated Resource Plan (IRP) by projecting the level of private generation resources PacifiCorp’s customers might install over the next twenty years under base, low, and high penetration scenarios. This study builds on Navigant’s previous assessment 1 which supported PacifiCorp’s 2015 IRP, incorporating updated load forecasts, market data, technology cost and performance projections. Navigant evaluated five private generation resources in detail in this report: 1. Photovoltaic (Solar) Systems 2. Small Scale Wind 3. Small Scale Hydro 4. Combined Heat and Power Reciprocating Engines 5. Combined Heat and Power Micro-turbines Project sizes were determined based on average customer load across four customer classes including commercial, irrigation, industrial and residential. Navigant also evaluated the future potential of energy storage, evaluating the drivers, challenges and applications of energy storage today. Summary findings are detailed in APPENDIX C. Private generation technical potential2 and expected market penetration3 for each technology was estimated for each major customer class in each state in PacifiCorp’s service territory. Shown in Figure 1, PacifiCorp serves customers in California, Idaho, Oregon, Utah, Washington, and Wyoming. 1 Navigant, Distributed Generation Resource Assessment for Long-Term Planning Study, http://www.pacificorp.com/content/dam/pacificorp/doc/Energy_Sources/Integrated_Resource_Plan/2015IRP/2015IRPStudy/Naviga nt_Distributed-Generation-Resource-Study_06-09-2014.pdf. 2 Total resource potential factoring out resources that cannot be accessed due to non-economic reasons (i.e. land use restrictions, siting constraints and regulatory prohibitions), including those specific to each technology. Technical potential does not vary by scenario. 3 Based on economic potential (technical potential that can be developed because it’s not more expensive than competing options), estimates the timeline associated with the diffusion of the technology into the marketplace, considering the technology’s relative economics, maturity, and development timeline. Private Generation Long-Term Resource Assessment (2017-2036) Page 2 ©2016 Navigant Consulting, Inc. Figure 1 PacifiCorp Service Territory4 Key Findings Using PacifiCorp-specific information on customer size and retail rates in each state and public data sources for technology costs and performance, Navigant conducted a Fisher-Pry5 payback analysis to determine likely market penetration for private generation technologies from 2017 to 2036. This analysis was performed for typical commercial, irrigation, industrial and residential PacifiCorp customers in each state. In the base case scenario, Navigant estimates approximately 1.4 GW AC6 of private generation capacity will be installed in PacifiCorp’s territory from 2017-2036.7 As shown in Figure 2, the low and high scenarios project a cumulative installed capacity of 1.0 GW AC and 2.1 GW AC, respectively. The main drivers between the different scenarios include variation in technology costs, system performance, and electricity rate escalation assumptions. These assumptions are provided in Table 7. Figure 3 indicates that Utah and Oregon will drive the majority of private generation installations over the next two decades, largely because these two states are PacifiCorp’s largest markets in terms of customers and sales. Reference APPENDIX A for detailed state-specific customer data. In both of these 4 http://www.pacificorp.com/content/dam/pacificorp/doc/About_Us/Company_Overview/Service_Area_Map.pdf. 5 Fisher-Pry are researchers who studied the economics of “S-curves”, which describe how quickly products penetrate the market. They codified their findings based on payback period, which measures how long it takes to recoup initial high first costs with energy savings over time. 6 Alternating current (AC) is an electric current in which the flow of electric charge periodically reverses direction, whereas in direct current (DC) the flow of electric charge is only in one direction. AC is the form in which electric power is transmitted on the grid. 7 All capacity numbers across all five resources are projected in MW AC. Figures throughout the report are all in MW AC. Private Generation Long-Term Resource Assessment (2017-2036) Page 3 ©2016 Navigant Consulting, Inc. states private generation installations are also driven by local tax credits and incentives. As displayed in Figure 4, solar represents the highest market penetration potential across the five technologies examined, with residential solar development leading the way, followed by non-residential solar (commercial, industrial, and irrigation). The Results section of the report contains results by state and technology for the high, base, and low scenarios. Figure 2 Cumulative Market Penetration Results (MW AC), 2017 – 2036 Private Generation Long-Term Resource Assessment (2017-2036) Page 4 ©2016 Navigant Consulting, Inc. Figure 3 Cumulative Market Penetration Results by State (MW AC), 2017 – 2036, Base Case Figure 4 Cumulative Market Penetration Results by Technology (MW AC), 2017 – 2036, Base Case Private Generation Long-Term Resource Assessment (2017-2036) Page 5 ©2016 Navigant Consulting, Inc. Report Organization The report is organized as follows: Private Generation Market Penetration Methodology Results APPENDIX A: Customer Data APPENDIX B: System Capacity Assumptions APPENDIX C: Storage Evaluation APPENDIX D: Detailed Numeric Results APPENDIX E: Washington Levelized Costs APPENDIX F: Comparison of 2016 and 2014 Study Private Generation Long-Term Resource Assessment (2017-2036) Page 1 ©2016 Navigant Consulting, Inc. PRIVATE GENERATION MARKET PENETRATION METHODOLOGY This section provides a high-level overview of the study methodology. 1.1 Methodology In assessing the technical and market potential of each private generation resource and opportunity in PacifiCorp’s service area, the study considered a number of key factors, including: Technology maturity, costs, and future cost projections Industry practices, current and expected Net metering Federal and state tax incentives Utility or third-party incentives O&M costs Historical performance, and expected performance projections Hourly private generation Consumer behavior and market penetration 1.2 Market Penetration Approach The following five-step process was used to estimate the market penetration of private generation resources in each scenario: 1. Assess a Technology’s Technical Potential: Technical potential is the amount of a technology that can be physically installed without considering economics or other barriers to customer adoption. For example, technical potential assumes that photovoltaic systems are installed on all suitable residential roofs. 2. Calculate Simple Payback Period for Each Year of Analysis: From past work in projecting the penetration of new technologies, Navigant has found that Simple Payback Period is a key indicator of customer uptake. Navigant used all relevant federal, state, and utility incentives in its calculation of paybacks, incorporating their projected reduction and/or discontinuation over time, where appropriate. 3. Project Ultimate Adoption Using Payback Acceptance Curves: Payback Acceptance Curves estimate the percentage of a market that will ultimately adopt a technology, but do not factor in how long adoption will take. 4. Project Market Penetration Using Market Penetration Curves: Market penetration curves factor in market and technology characteristics, projecting the adoption timeline. 5. Project Market Penetration under Different Scenarios. In addition to the base case scenario, high and low case scenarios were created by varying cost, performance, and retail rate projections. Private Generation Long-Term Resource Assessment (2017-2036) Page 2 ©2016 Navigant Consulting, Inc. These five steps are explained in detail in the following sections. 1.3 Assess Technical Potential Each technology considered has its own characteristics and data sources that influence the technical potential assessment; the amount of a technology that can be physically installed within PacifiCorp’s service territory without considering economics or other barriers to customer adoption. Navigant escalated technical potentials at the same rate PacifiCorp projects its sales will change over time. 1.4 Simple Payback For each customer class (i.e., residential, commercial, irrigation and industrial), technology, and state, Navigant calculated the simple payback period using the following formula: Simple Payback Period = (Net Initial Costs) / (Net Annual Savings) Net Initial Costs = Installed Cost – Federal Incentives – Capacity-Based Incentives*(1 – Tax Rate) Net Annual Savings = Annual Energy Bills Savings + (Performance Based Incentives – O&M Costs – Fuel Costs)*(1 – Tax Rate) Federal tax credits can be taken against a system’s full value if other (i.e. utility or state supplied) capacity-based or performance-based incentives are considered taxable. Navigant’s Market Penetration model calculates first year simple payback assuming new installations for each year of analysis. For electric bills savings, Navigant conducted an 8,760 hourly analysis to take into account actual rate schedules, actual output profiles, and demand charges. System performance assumptions are listed in Section 1.3 above. Solar performance and wind performance profiles were calculated for representative locations within each state based on the National Renewable Energy Laboratory (NREL) Solar Advisory Model (SAM), which now also models wind. Building load profiles were provided by PacifiCorp, and were scaled to match the average electricity usage for each customer class based on billing data. Private Generation Long-Term Resource Assessment (2017-2036) Page 3 ©2016 Navigant Consulting, Inc. 1.5 Payback Acceptance Curves For private resources, Navigant used the following payback acceptance curves to model market penetration of private generation sources from the retail customer’s perspective. Figure 5 Payback Acceptance Curves These payback curves are based upon work for various utilities, federal government organizations, and state local organizations. They were developed from customer surveys, mining of historical program data, and industry interviews.8 Given a calculated payback period, the curve predicts the level of maximum market penetration. For example, if the technical potential is 100 MW, the 3-year commercial payback predicts that 15% of this technical potential, or 15 MW, will ultimately be achieved over the long term. 1.6 Market Penetration Curves To determine the future private generation market penetration within PacifiCorp’s territory, the team modeled the growth of private generation technologies from 2017 thru 2036. The model is a Fisher-Pry based technology adoption model that calculates the market growth of private generation technologies. It uses a lowest-cost approach to consumers to develop expected market growth curves based on maximum achievable market penetration and market saturation time, as defined below.9 8 Payback acceptance curves are based on a broad set of data from across the United States and may not predict customer behavior in a specific market (e.g. Utah customers may install solar at a faster rate than the rate indicated by the payback acceptance curves due to market specific reasons). 9 Michelfelder and Morrin, “Overview of New Product Diffusion Sales Forecasting Models” provides a summary of product diffusion models, including Fisher-Pry. Available: law.unh.edu/assets/images/uploads/pages/ipmanagement-new-product- diffusion-sales-forecasting-models.pdf Source: Navigant Consulting based upon work for various utilities, federal government organizations, and state/local organizations. The curves were developed from customer surveys, mining of historical program data, and industry interviews. Private Generation Long-Term Resource Assessment (2017-2036) Page 4 ©2016 Navigant Consulting, Inc. Market Penetration – The percentage of a market that purchases or adopts a specific product or technology. The Fisher-Pry model estimates the achievable market penetration based on the simple payback period of the technology. Market penetration curves (sometimes called S- curves) are well established tools for estimating diffusion or penetration of technologies into the market. Navigant applies the market penetration curve to the payback acceptance curve shown in Figure 5 Payback Acceptance Curves. Market Saturation Time – The duration in years for a technology to increase market penetration from around 10% to 80%. The Fisher-Pry model estimates market saturation time based on 12 different market input factors; those with the most substantial impact include: Payback Period – Years required for the cumulative cost savings to equal or surpass the incremental first cost of equipment. Market Risk – Risk associated with uncertainty and instability in the marketplace, which can be due to uncertainty regarding cost, industry viability, or even customer awareness, confidence, or brand reputation. An example of a high market risk environment is a jurisdiction lacking long- term, stable guarantees for incentives. Technology Risk – Measures how well-proven and the availability of the technology. For example, technologies that are completely new to the industry have a higher risk, whereas technologies that are only new to a specific market (or application) and have been proven elsewhere have lower risk. Government Regulation – Measure of government involvement in the market. A government-stated goal is an example of low government involvement, whereas a government mandated minimum efficiency requirement is an example of high involvement, having a significant impact on the market. The model uses these factors to determine market growth instead of relying on individual assumptions about annual market growth for each technology or various supply and/or demand curves that may sometimes be used in market penetration modeling. With this approach, the model does not account for other more qualitative limiting market factors, such as the ability to train quality installers or manufacture equipment at a sufficient rate to meet the growth rates. Corporate sustainability, and other non-economic growth factors, are also not modeled. The Fisher-Pry market growth curves have been developed and refined over time based on empirical adoption data for a wide range of technologies.10 The model is an imitative model that uses equations developed from historical penetration rates of real products for over two decades. It has been validated in this industry via comparison to historical data for solar photovoltaics, a key focus of this study. Navigant Consulting has used gathered market data on the adoption of technologies over the past 120 years and fit the data using Fisher-Pry curves. A key parameter when using market penetration curves is the assumed year of introduction. For the market penetration curves used in this study, Navigant assumed that the first year introduction occurred when the simple payback period was less than 25 years (per the pay-back acceptance curves used, this is the highest pay-back period that has any adoption). 10 Fisher, J. C. and R. H. Pry, "A Simple Substitution Model of Technological Change", Technological Forecasting and Social Change, 3 (March 1971), 75-88. Private Generation Long-Term Resource Assessment (2017-2036) Page 5 ©2016 Navigant Consulting, Inc. When the above payback period, market risk, technology risk, and government regulation factors above are analyzed, our general Fisher-Pry based method gives rise to the following market penetration curves used in this study: Figure 6 Market Penetration Curves 11 The model is designed to analyze the adoption of a single technology entering a market, and assumes that the private generation market penetration analyzed for each technology is additive because the underlying resources limiting installations (sun, wind, water, high thermal loads) are generally mutually exclusive, and because current levels of market penetration are relatively low (plenty of customers exist for each technology). 1.7 Key Assumptions The following section details the key technology-specific and base, low and high scenario assumptions. 1.7.1 Technology Assumptions Assumptions including costs and performance were decided for each technology evaluated. 11 Realized market penetration is applied to the maximum market penetration (Figure 6) for each technology, customer payback, and point in time. For example a residential customer with a five-year payback would have a maximum market penetration of around 35 percent, as indicated by the residential payback acceptance curve (Figure 5). A technology that was introduced 10 years ago will have realized about 20 percent of its maximum market penetration (Figure 6), having a market penetration of about seven percent of the technical potential. Source: Navigant Consulting, November 2008 as taken from Fisher, J.C. and R.H. Pry, A Simple Substitution Model of Technological Change, Technological Forecasting and Social Change, Vol 3, Pages 75 – 99, 1971. Private Generation Long-Term Resource Assessment (2017-2036) Page 6 ©2016 Navigant Consulting, Inc. 1.7.1.1 CHP: Reciprocating Engines A reciprocating engine uses one or more reciprocating pistons to convert pressure into rotating motion. In a combined heat and power (CHP) application, a small CHP source will burn a fuel to produce both electricity and heat. In many applications, the heat is transferred to water, and this hot water is then used to heat a building. Navigant sized the system to meet the minimum customer load, assuming the reciprocating engine system would function to meet the customer’s base load. Based on system size, CHP reciprocating engines were assumed a reasonable technology for commercial and industrial customers. Assumptions on system capacity sizes in each state are detailed in APPENDIX B. Table 1 Reciprocating Engine Assumptions provides the cost and performance assumptions used in the analysis and the source for each. Table 1 Reciprocating Engine Assumptions12 Private Generation Resource Costs Units 2015 Baseline Sources Installed Cost – 100kW $/kW $2,900 EPA, Catalog of CHP Technologies, March 2015, pg. 2-15 Change in Annual Installed Cost % 0.4% ICF International Inc., Combined Heat and Power: Policy Analysis and 2011-2030 Market Assessment, pg. 92 Variable O&M $/MWh $20 ICF International Inc., Combined Heat and Power: Policy Analysis and 2011-2030 Market Assessment, pg. 92 Fuel Cost $/MWh PacifiCorp Gas Forecast Private Generation Performance Assumptions Electric Heat Rate (HHV) Btu/kWh 12,637 EPA, Catalog of CHP Technologies, March 2015, pg. 2-10 1.7.1.2 CHP: Micro-turbines Micro-turbine use natural gas to start a combustor, which drives a turbine. The turbine in turn drives an AC generator and compressor, and the waste heat is exhausted to the user. The device therefore produces electrical power from the generator, and waste heat to the user. Navigant sized the system to meet the minimum customer load, assuming the reciprocating engine system would function to meet the customer’s base load. Based on system size, CHP reciprocating engines were assumed a reasonable technology for commercial and industrial customers. Assumptions 12 EPA, Catalog of CHP Technologies: www.epa.gov/sites/production/files/2015-07/documents/catalog_of_chp_technologies.pdf; ICF, Combined Heat and Power Policy Analysis, www.energy.ca.gov/2012publications/CEC-200-2012-002/CEC-200-2012-002.pdf Private Generation Long-Term Resource Assessment (2017-2036) Page 7 ©2016 Navigant Consulting, Inc. on system capacity sizes in each state are detailed in APPENDIX B. Table 2 Micro-turbines Assumptions provides the cost and performance assumptions used in the analysis and the source for each. Table 2 Micro-turbines Assumptions13 Private Generation Resource Costs Units 2015 Baseline Sources Installed Cost – 30kW $/kW $2,690 EPA, Catalog of CHP Technologies, March 2015, pg. 5- 7 Change in Annual Installed Cost % -0.3% ICF International Inc., Combined Heat and Power: Policy Analysis and 2011-2030 Market Assessment, pg. 97 Variable O&M $/MWh $23 ICF International Inc., Combined Heat and Power: Policy Analysis and 2011-2030 Market Assessment, pg. 97 Fuel Cost $/MWh PacifiCorp Gas Forecast Private Generation Performance Assumptions Electric Heat Rate (HHV) Btu/kWh 15,535 EPA, Catalog of CHP Technologies, March 2015, pg. 5-6 1.7.1.3 Small Hydro Small hydro is the development of hydroelectric power on a scale serving a small community or industrial plant. The detailed national small hydro studies conducted by the Department of Energy (DOE) from 2004 to 2013,14 formed the basis of Navigant’s small hydro technical potential estimate. In the Pacific Northwest Basin, which covers WA, OR, ID, and WY, a detailed stream-by-stream analysis was performed in 2013, and DOE provided these data to Navigant directly. For these states, Navigant combined detailed GIS PacifiCorp service territory data with detailed GIS data on each stream / water source. Using this method, Navigant was able to sum the technical potentials of only those streams located in PacifiCorp’s service territory. For the other two states, Utah and California, Navigant relied on an older 2006 national analysis, and multiplied the given state figures by the area served by PacifiCorp within that state. Table 3 Small Hydro Assumptions provides the cost and performance assumptions used in the analysis and the source for each. 13 EPA, Catalog of CHP Technologies: www.epa.gov/sites/production/files/2015-07/documents/catalog_of_chp_technologies.pdf; ICF, Combined Heat and Power Policy Analysis, www.energy.ca.gov/2012publications/CEC-200-2012-002/CEC-200-2012-002.pdf 14 Navigant used the same methodology and sources as in the 2014 study. Private Generation Long-Term Resource Assessment (2017-2036) Page 8 ©2016 Navigant Consulting, Inc. Table 3 Small Hydro Assumptions15 Private Generation Resource Costs Units 2017 Baseline Sources Installed Cost $/kW $4,000 Double average plant costs in "Quantifying the Value of Hydropower in the Electric Grid: Plant Cost Elements." Electric Power Research Institute, November 2011; this accounts for permitting/project costs Change in Annual Installed Cost % 0.00% Mature technology, consistent with other mature technologies in the IRP. Fixed O&M $/kW-yr. $52 Renewable Energy Technologies: Cost Analysis Series. "Hydropower." International Renewable Energy Agency, June 2012. Private Generation Performance Assumptions Capacity Factor % 50% ±5% Average capacity factor variance will be reflected in the low and high penetration scenarios. 1.7.1.4 Solar Photovoltaics Solar photovoltaic (solar) systems convert sunlight to electricity. Navigant applied a 20% discount factor to account for system sizing less than 100% of annual load and Direct Current (DC) to Alternating Current (AC) conversion. System size was then multiplied by the number of customers and the roof access factor. Assumptions on system capacity sizes in each state are detailed in APPENDIX B and access factors remained consistent with the 2014 study. Table 4 Solar Assumptions provides the cost and performance assumptions used in the analysis and the source for each. 15 Note: No change from 2014 study. Private Generation Long-Term Resource Assessment (2017-2036) Page 9 ©2016 Navigant Consulting, Inc. Table 4 Solar Assumptions Installed Cost – Res $/kW DC UT: $3,000 Other: $3,500 Navigant Forecast validated by NREL, U.S. Photovoltaic Prices and Cost Breakdowns: Q1 2015 Benchmarks for Residential, Commercial and Utility-Scale Systems Installed Cost – Non-Res $/kW DC All Markets: $2,300 Average Change in Annual Installed Cost (2015-2034) % -2.4% (Res) -2.2% (Non-Res) Fixed O&M – Res $/kW-yr. $25 National Renewable Energy Laboratory, U.S. Residential Photovoltaic (PV) System Prices, Q4 2013 Benchmarks: Cash Purchase, Fair Market Value, and Prepaid Lease Transaction Prices, Oct. 2014;National Renewable Energy Laboratory, Distributed Generation Renewable Energy Estimate of Costs, Accessed February 1, 2016 Fixed O&M – Non-Res $/kW-yr. $23 As shown in Figure 7 and Figure 8, the rapid decline in solar costs over the past decade has driven private solar adoption across the country for all customer classes. In the past, these cost declines were primarily due to reduction in the cost of equipment (e.g. panels, inverters and balance of system components) driven by economies of scale and improvements in efficiency. Solar costs are expected to continue to decline over the next decade as system efficiencies continue to increase, although these declines are expected to occur at a slower rate than what occurred in recent years. In the long term, Navigant expects price reductions to decline as the industry matures and efficiency gains become harder to achieve. Navigant’s national solar cost forecast includes a low, base and high forecast. For this project, Navigant developed a PacifiCorp forecast which is the average between the national base and high forecast. Navigant decided to use for California, Idaho, Oregon, Washington and Wyoming, as all of those states currently have relatively small solar markets in PacifiCorp’s territory, resulting in less competition and economies of scale to drive down local solar costs. For Utah, Navigant used the base cost forecast, as Utah has a larger and more mature private solar market. Private Generation Long-Term Resource Assessment (2017-2036) Page 10 ©2016 Navigant Consulting, Inc. Figure 7. Non-Residential Solar System Costs, 2015-2036 Figure 8 Residential Solar System Costs, 2015-2036 Private Generation Long-Term Resource Assessment (2017-2036) Page 11 ©2016 Navigant Consulting, Inc. The solar capacity factors (Table 5) were calculated using NREL’s System Advisory Model for each state territory. Table 5 Solar Capacity Factors16 Performance Assumptions (kW-DC/kWh AC) (kW-AC/kWh AC) Capacity Factor UT 16.3% 20.4% WY 16.8% 21.0% WA 14.0% 17.5% CA 16.6% 20.8% ID 16.0% 20.0% OR 12.4% 15.5% 1.7.1.5 Small Wind Wind power is the use of air flow through wind turbines to mechanically power generators for electricity. Navigant sized the wind systems at 80% of customer load to reduce the chance that the wind system will produce more than the customer’s electric load in a given year. System size was then multiplied by the number of customers and the access factor. The 2014 study access factors were used for this study. The following cost and performance assumptions were used in the analysis. 16 NREL, System Advisory Model (SAM) for specific state locations, consistent with 2014 study. Navigant used the default system configuration in SAM, which has a DC to AC derate factor of about 80%. Private Generation Long-Term Resource Assessment (2017-2036) Page 12 ©2016 Navigant Consulting, Inc. Table 6 Wind Assumptions Private Generation Resource Costs Units 2014 Baseline Sources Installed Cost – Res (2.5-10kW) $/kW $7,200 Department of Energy, 2014 Distributed Wind Market Report, August 2015 Installed Cost – Com (11-100kW) $/kW $6,000 Change in Annual Installed Cost % 0.0% Mature technology, consistent with other mature technologies in the IRP. Fixed O&M $/kW-yr. $40 Department of Energy, 2014 Distributed Wind Market Report, August 2015 Change in Annual O&M Cost % -1.0% Private Generation Performance Assumptions Capacity Factor % 20% (2013) - 25% (2034) Small scale wind hub heights are lower, with shorter turbine blades, relative to 30% capacity factor large scale turbines. Private Generation Long-Term Resource Assessment (2017-2036) Page 13 ©2016 Navigant Consulting, Inc. 1.7.2 Scenario Assumptions Navigant used the market penetration model to analyze three scenarios, capturing the impact of major changes that could affect market penetration. For the low and high penetration cases, Navigant varied technology costs, system performance, and electricity rate assumptions. Table 7 Scenario Variable Modifications See technology and cost section As modeled Increase at inflation rate, assumed at 1.9% PV: Same as Base Case Other: Mature technologies. Same as base case PV: Same as Base Case Other: 5% worse Increases at 1.4%, 0.5%/year lower than the Base Case PV: 2X steeper cost reduction/year Other: Mature technologies. Same as base case Reciprocating Engines: 0.5% better (mature) Micro-turbines: 2% better Hydro: 5% better (reflecting wide performance distribution uncertainty) PV/Wind: 1% better (relatively mature) Increases at 2.4%, 0.5%/year higher than the Base Case Technology cost reduction is the variable having the largest impact on market penetration over the next 20 years. Average technology performance assumptions are relatively constant across states and sites. Changes in electricity rates are modeled conservatively, reflecting the long-term stability of electricity rates in the United States. Navigant expects short-term volatility for all variables but when averaged over the 20-year IRP period, long-term trends show less variation. 1.7.3 Incentives Federal and state incentives are a very important private generation market penetration driver, as they can reduce a customer’s payback period significantly. 1.7.3.1 Federal The Federal Business Energy Investment Tax Credit (ITC) allows the owner of the system to claim a tax credit for a certain percentage of the installed private generation system price.17 The ITC, originally set to expire in 2016 for commercial solar systems and reduce to 10% for residential solar systems, was extended for solar PV systems in December 2015 through the end of 2021, with step downs occurring in 17 Business Energy Investment Tax Credit, http://energy.gov/savings/business-energy-investment-tax-credit-itc. Private Generation Long-Term Resource Assessment (2017-2036) Page 14 ©2016 Navigant Consulting, Inc. 2020 through 2022. The 2014 Navigant Distributed Generation Resource Assessment for Long-Term Planning Study assumed that the ITC would expire for commercial solar PV systems at the end of 2016 and step down to 10% for residential PV systems, per the legislation in place at the time of the analysis. The table below details how the ITC applies to the technologies evaluated in this study, however, this schedule may change in the future. Table 8 Federal Tax Incentives Technology 2016 2017 2018 2019 2020 2021 >2021 1.7.3.2 State State incentives drive the local market and are an important aspect promoting private generation market penetration. Currently, all states evaluated have full retail rate net energy metering (NEM) in place for all customer classes considered in this analysis. The study assumes that NEM policy remains constant, although future uncertainty exists surrounding NEM policy. Longer-term uncertainty also exists regarding other state incentives. Idaho also has a local state residential personal tax deduction for solar and wind projects. Currently, state incentives do not exist in California18 or Wyoming. The following tables detail the assumptions made regarding local state incentives. 18 In 2007, California launched the California Solar Initiative, however, incentives no longer remain in most utility territories, http://csi-trigger.com/. Private Generation Long-Term Resource Assessment (2017-2036) Page 15 ©2016 Navigant Consulting, Inc. Table 9 Oregon Incentives Technology 2016 2017 2018 2019 2020 2021 >2021 – – – – Table 10 Utah Incentives Technology 2016 2017 2018 2019 2020 2021 >2021 – – – – * Energy Trust of Oregon Solar Incentive (capped at $2M/year for residential and $1.6M/year for non-residential). Energy Trust of Oregon incentives after 2016 are estimated based on assumed system cost trends. ** Residential Energy Tax Credit - $6,000 over the life of the system, distributed $1,500/yr. http://programs.dsireusa.org/system/program/detail/638 ***The Residential Energy Tax Credit (RETC), in its current legislative form, is set to expire at the end of 2017. It is not yet known whether the Oregon Legislature will extend the RETC beyond 2017. Similarly, should the RETC be extended beyond 2017, it is not known if it would have the same value or eligibility criteria. However, for purposes of this analysis, it was assumed that the RETC will be extended beyond 2017 with the same value and eligibility criteria as exists as of the date of this report. *Renewable Energy Systems Tax Credit, Program Cap: Residential cap = $2,000; commercial systems <660kW, no limit **The Utah Renewable Energy Systems Tax Credit is assumed for the purpose of this report to continue at its current incentive level. The timing and value of any possible changes to the state tax credit remain unclear. Private Generation Long-Term Resource Assessment (2017-2036) Page 16 ©2016 Navigant Consulting, Inc. Table 11 Washington Incentives Technology 2016 2017 2018 2019 2020 2021 >2021 – – – – Table 12 Idaho Incentives Technology 2016 2017 2018 2019 2020 2021 >2021 –40,20,20,20 40,20,20,20 40,20,20,20 40,20,20,20 40,20,20,20 40,20,20,20 40,20,20,20 – –40,20,20,20 40,20,20,20 40,20,20,20 40,20,20,20 40,20,20,20 40,20,20,20 40,20,20,20 * Feed-in Tariff: $/kWh for all kWh generated through mid-2020; annually capped at $5,000/year, http://programs.dsireusa.org/system/program/detail/5698 * Residential Alternative Energy Income Tax Deduction: 40% in the first year and 20% for the next three years, http://programs.dsireusa.org/system/program/detail/137. Private Generation Long-Term Resource Assessment (2017-2036) Page 17 ©2016 Navigant Consulting, Inc. RESULTS Navigant estimates approximately 1.4 GW of private generation capacity will be installed in PacifiCorp’s territory from 2017-2036 in the base case scenario. As shown in Figure 9, the low and high scenarios project a cumulative installed capacity of 1.00 GW and 2.10 GW by 2036, respectively. The main drivers between the different scenarios include variation in technology costs, system performance, and electricity rate assumptions. Figure 9. Cumulative Market Penetration Results (MW AC), 2017 – 2036 1.8 PacifiCorp Territories The following sections report the results by state, providing high, base and low scenario installation projections. Results for each scenario are also broken out by technology. The solar sector exhibits the highest adoption across all states. Generally non-residential solar adoption is less sensitive to high and low scenario adjustments when compared the residential sector. This is because the residential customer payback is more sensitive to scenario changes (e.g. technology costs, performance, electricity rates) when compared to non-residential sectors. 19 Solar capacity is projected in DC, while the capacity for all other resources is projected in AC. Figures throughout the report that include all resources forecasted, reflect a combination of AC and DC. Private Generation Long-Term Resource Assessment (2017-2036) Page 18 ©2016 Navigant Consulting, Inc. 1.8.1 California PacifiCorp’s customers in northern California are projected to install about 22 MW of capacity over the next two decades in the base case, averaging about 1.1 MW annually. California does not currently have any state incentives promoting the installation of private generation and the ratcheting down of the Federal ITC from 2020 to 2022 has a negative impact on annual capacity installations after 2020. The main driver of private generation in California is its high electricity rates relative to other states. Over time, the increase in private generation installation capacity is driven by escalating electricity rates and declining technology costs. Both residential and non-residential solar installations are responsible for the majority of private generation growth over the horizon of this study. While the low and high scenarios follow similar market trends as the base case, the cumulative installations over the planning horizon differ significantly, as shown in Figure 10. The 22 MW from the base case decreases by 32% to 15 MW in the low case and increases by 55% to 34 MW in the high case. Figure 10. Cumulative Capacity Installations by Scenario (MW AC), California Private Generation Long-Term Resource Assessment (2017-2036) Page 19 ©2016 Navigant Consulting, Inc. Figure 11. Cumulative Capacity Installations by Technology (MW AC), California Base Case Figure 12. Cumulative Capacity Installations by Technology (MW AC), California High Case Private Generation Long-Term Resource Assessment (2017-2036) Page 20 ©2016 Navigant Consulting, Inc. Figure 13. Cumulative Capacity Installations by Technology (MW AC), California Low Case 1.8.2 Idaho PacifiCorp’s Idaho customers are projected to install about 39 MW of capacity over the next two decades in the base case, averaging about 1.9 MW annually. Idaho currently has a Residential Alternative Energy Income Tax Deduction for residential solar and wind installations20, although this incentive seems to have minimal impact on the market, as non-residential solar installations are responsible for the majority of private generation growth in the early years due to a combination of technical potential and escalating electric rates. The ratcheting down of the Federal ITC from 2020 to 2022 has a negative impact on annual capacity installations in the short term and overtime the increase in private generation installation capacity is driven by escalating electricity rates and declining technology costs. While the low and high scenarios follow similar market trends as the base case, the cumulative installations over the planning horizon differ significantly, as shown in Figure 14. The 38 MW from the base case decreases by 39% to 23 MW in the low case and increases by 82% to 69 MW in the high case. 20 Residential Alternative Energy Income Tax Deduction: 40% in the first year and 20% for the next three years, http://programs.dsireusa.org/system/program/detail/137. Private Generation Long-Term Resource Assessment (2017-2036) Page 21 ©2016 Navigant Consulting, Inc. Figure 14. Cumulative Capacity Installations by Scenario (MW AC), Idaho Private Generation Long-Term Resource Assessment (2017-2036) Page 22 ©2016 Navigant Consulting, Inc. Figure 15. Cumulative Capacity Installations by Technology (MW AC), Idaho Base Case Figure 16. Cumulative Capacity Installations by Technology (MW AC), Idaho High Case Private Generation Long-Term Resource Assessment (2017-2036) Page 23 ©2016 Navigant Consulting, Inc. Figure 17. Cumulative Capacity Installations by Technology (MW AC), Idaho Low Case 1.8.3 Oregon PacifiCorp’s Oregon customers are projected to install about 331 MW of private generation capacity over the next two decades in the base case, averaging about 16.6 MW annually. Solar is responsible for all of the private generation growth over the horizon of this study. Although the solar resource in Oregon is not as strong as the majority of other states in PacifiCorp’s territory, the Energy Trust of Oregon’s Solar Incentive and the state Residential Energy Tax Credit, assumed to extend through 2036, drive solar market adoption. The ratcheting down of the Federal ITC from 2020 to 2022 results in a relatively flat market in the short term but overtime the increase in solar capacity installation is driven by escalating electricity rates and declining technology costs. While the low and high scenarios follow similar market trends as the base case, the cumulative installations over the planning horizon differ significantly, as shown in Figure 18. The 331 MW from the base case decreases by 30% to 232 MW in the low case and increases by 72% to 568 MW in the high case. Private Generation Long-Term Resource Assessment (2017-2036) Page 24 ©2016 Navigant Consulting, Inc. Figure 18. Cumulative Capacity Installations by Scenario (MW AC), Oregon Figure 19. Cumulative Capacity Installations by Technology (MW AC), Oregon Base Case Private Generation Long-Term Resource Assessment (2017-2036) Page 25 ©2016 Navigant Consulting, Inc. Figure 20. Cumulative Capacity Installations by Technology (MW AC), Oregon High Case Figure 21 Cumulative Capacity Installations by Technology (MW AC), Oregon Low Case Private Generation Long-Term Resource Assessment (2017-2036) Page 26 ©2016 Navigant Consulting, Inc. 1.8.4 Utah PacifiCorp’s Utah customers are projected to install about 919 MW of private generation capacity over the next two decades in the base case, averaging around 45 MW annually. Solar is responsible for the majority of private generation installations over the horizon of this study, with CHP reciprocating engines being installed in small numbers in future years. Utah has the strongest solar resource in PacifiCorp’s territory and system costs are lower than in other states due to Utah’s larger and more mature market. The projection in the early years is dominated by residential customers adopting solar. The state Renewable Energy Systems Tax Credit applies to all technologies evaluated and has an impact on solar adoption. Solar adoption declines dramatically in 2020 as the ITC ratchets down. In 2025 projected capacity installation increases as solar prices continue to decline and utility rates escalate. While the low and high scenarios follow similar market trends as the base case, the cumulative installations over the planning horizon differ significantly, as shown in Figure 22. The 919 MW from the base case decreases by 25% to 688 MW in the low case and increases by 47% to 1351 MW in the high case. Figure 22. Cumulative Capacity Installations by Scenario (MW AC), Utah Private Generation Long-Term Resource Assessment (2017-2036) Page 27 ©2016 Navigant Consulting, Inc. Figure 23. Cumulative Capacity Installations by Technology (MW AC), Utah Base Case Figure 24. Cumulative Capacity Installations by Technology (MW AC), Utah High Case Private Generation Long-Term Resource Assessment (2017-2036) Page 28 ©2016 Navigant Consulting, Inc. Figure 25. Cumulative Capacity Installations by Technology (MW AC), Utah Low Case 1.8.5 Washington PacifiCorp’s Washington customers are expected to install about 23.9 MW of private generation capacity over the next two decades in the base case, averaging 1.2 MW annually. Solar is responsible for the majority of private generation installations over the horizon of this study, with CHP reciprocating engines being installed in small numbers in future years. Washington does not have a very strong solar resource, yet the lucrative Feed-In-Tariff in Washington, which extends through 2020, props up the solar market in the near term. The solar market is driven by non-residential solar installations, most likely due to the lower cost of installing larger systems. Solar adoption declines dramatically in 2020 as the ITC ratchets down. In 2025, installation capacity increases as solar prices continue to decline and utility rates escalate. While the low and high scenarios follow similar market trends as the base case, the cumulative installations over the planning horizon differ significantly, as shown in Figure 26. The 24 MW from the base case decreases by 29% to 17 MW in the low case and increases by 96% to 47 MW in the high case. Private Generation Long-Term Resource Assessment (2017-2036) Page 29 ©2016 Navigant Consulting, Inc. Figure 26. Cumulative Capacity Installations by Scenario (MW AC), Washington Figure 27. Cumulative Capacity Installations by Technology (MW AC), Washington Base Case Private Generation Long-Term Resource Assessment (2017-2036) Page 30 ©2016 Navigant Consulting, Inc. Figure 28. Cumulative Capacity Installations by Technology (MW AC), Washington High Case Figure 29. Cumulative Capacity Installations by Technology (MW AC), Washington Low Case Private Generation Long-Term Resource Assessment (2017-2036) Page 31 ©2016 Navigant Consulting, Inc. 1.8.6 Wyoming PacifiCorp’s Wyoming customers are projected to install about 44 MW of capacity over the next two decades in the base case, averaging about 2.2 MW annually. Solar is responsible for the majority of private generation installations over the horizon of this study, with CHP reciprocating engines, small hydro, and small wind being installed in small numbers in future years. Wyoming does not have any state incentives promoting the installation of private generation. Similar to other states, the ratcheting down of the Federal ITC from 2020 to 2022 has a negative impact on annual capacity installations but in 2023 the market begins to grow at a faster pace, driven by escalating electricity rates and declining technology costs. Both residential and non-residential solar installations are responsible for the majority of private generation growth over the horizon of this study. While the low and high scenarios follow similar market trends as the base case, the cumulative installations over the planning horizon differ significantly, as shown in Figure 30. The 44 MW from the base case decreases by 48% to 26 MW in the low case and increases by 86% to 82 MW in the high case. Figure 30. Cumulative Capacity Installations by Scenario, Wyoming Private Generation Long-Term Resource Assessment (2017-2036) Page 32 ©2016 Navigant Consulting, Inc. Figure 31. Cumulative Capacity Installations by Technology (MW AC), Wyoming Base Case Figure 32. Cumulative Capacity Installations by Technology, Wyoming High Case Private Generation Long-Term Resource Assessment (2017-2036) Page 33 ©2016 Navigant Consulting, Inc. Figure 33. Cumulative Capacity Installations by Technology (MW AC), Wyoming Low Case Private Generation Long-Term Resource Assessment (2017-2036) Page A-1 ©2016 Navigant Consulting, Inc. CUSTOMER DATA Table 13 California 35,461 369,076 0.138 7,179 235,760 0.132 125 48,336 0.099 1,835 97,790 0.132 Table 14 Idaho 61,788 690,071 0.109 8,478 468,291 0.083 592 1,728,411 0.068 4,947 592,595 0.091 Table 15 Oregon 493,990 5,387,920 0.102 65,287 5,104,499 0.090 1,446 2,192,338 0.071 7,713 338,450 0.096 Private Generation Long-Term Resource Assessment (2017-2036) Page A-2 ©2016 Navigant Consulting, Inc. Table 16 Utah 776,356 6,840,892 0.110 82,889 8,581,242 0.085 5,095 8,870,838 0.065 3,117 216,410 0.077 Table 17 Washington 107,382 1,585,732 0.100 15,561 1,539,732 0.081 500 798,140 0.065 5,091 162,150 0.087 Table 18 Wyoming 114,763 1,042,938 0.119 22,856 1,510,255 0.086 2,073 7,010,964 0.063 743 23,840 0.092 Private Generation Long-Term Resource Assessment (2017-2036) Page B-3 ©2016 Navigant Consulting, Inc. SYSTEM CAPACITY ASSUMPTIONS Table 19 Access Factors (%) Technology CA ID OR UT WA WY Recip. Engines Micro Turbines Small Hydro PV - Com PV - Res Wind - Com Wind - Res Table 20 California (kW AC) 2 0 0 28 2 0 0 28 500 0 0 500 18 29 0 212 0 0 6 0 10 16 0 113 0 0 3 0 Private Generation Long-Term Resource Assessment (2017-2036) Page B-4 ©2016 Navigant Consulting, Inc. Table 21 Idaho (kW AC) 4 0 0 185 4 0 0 185 500 0 0 500 31 68 0 250 0 0 6 0 29 62 0 1515 0 0 6 0 Table 22 Oregon (kW AC) 6 0 0 110 6 0 0 110 500 0 0 500 25 32 0 100 0 0 6 0 30 17 0 584 0 0 4 0 Private Generation Long-Term Resource Assessment (2017-2036) Page B-5 ©2016 Navigant Consulting, Inc. Table 23 Utah (kW AC) 7 0 0 150 7 0 0 150 500 0 0 500 58 39 0 130 0 0 5 0 56 0 0 938 0 0 5 0 Table 24 Washington (kW AC) 6 0 0 88 6 0 0 88 500 0 0 500 65 21 0 250 0 0 10 0 41 13 0 655 0 0 6 0 Private Generation Long-Term Resource Assessment (2017-2036) Page B-6 ©2016 Navigant Consulting, Inc. Table 25 Wyoming (kW AC) 150 0 0 150 150 0 0 150 500 0 0 500 25 17 0 150 0 0 5 0 23 11 0 1192 0 0 3 0 Private Generation Long-Term Resource Assessment (2017-2036) Page C-7 ©2016 Navigant Consulting, Inc. STORAGE EVALUATION Navigant evaluated the future potential of energy storage, evaluating the drivers, challenges and applications of energy storage today. C.1 Drivers Changes in the electric sector are increasing the need for storage and changes in the storage sector are increasing the viability. Figure 17 details the external and internal drivers driving the expansion of the energy storage market. Figure 34. Internal and External Storage Drivers Sector specific drivers include: Commercial and Industrial o Most commercial customers face demand charges and/or time-of-use (TOU) pricing. This makes storage extremely useful for energy cost management. o Storage may also provide additional reliability by smoothing out short term power fluctuations (similar to a large uninterruptible power supply (UPS)), and can provide reactive power to help reduce reactive power charges. o Consistent and predictable loads for sub-sets of commercial sites (restaurants, retail, office), will allow for some standardization in terms of product offering. o Market may begin to focus on larger scale longer, duration Li-ion battery storage coupled with demand response technology to meet emerging capacity market drivers. Private Generation Long-Term Resource Assessment (2017-2036) Page C-8 ©2016 Navigant Consulting, Inc. Residential o Residential market is currently very small and driven by the back-up power application. It is expected to remain that way in the near term since conventional backup power is still more cost effective. C.2 Challenges Storage requires high electricity prices, high demand charges and in many cases a subsidy to make economic sense (e.g. SGIP in California). Sector-specific challenges include: Commercial and Industrial Limited short-term demand spike facilities with high demand charge o Given the current cost of batteries, power conversion technology, software and controls and system integrator services, most projects still require incentives, high demand charge tariffs and emerging financing structures. Customer acquisition and project development costs are high o Each specific building load pattern must be analyzed to determine project viability, increasing the cost of customer acquisition. Lack of project finance at scale o C&I storage projects, like solar PV, typically do not offer paybacks that meet conventional host return on investment criteria, thereby requiring financing. o Despite battery manufacturer’s efforts to provide performance guarantees and warranties, financing capital is not available at scale and remains limited. Dispatch algorithm o Difficult to design the algorithms correctly so storage discharges at the correct time. Residential Most residential customers do not pay demand charges or TOU rates. As such, a standalone storage system only provides a reliability benefit. Without regulatory changes, the business case for residential solar + storage will remain NPV negative in all but a few select geographies (e.g. Hawaii). C.3 Policy Federal and state policy promoting energy storage remains one of the most important market drivers. Federal The predominant federal energy storage policies include the Investment Tax Credit, MACRS, USEPA Clean Power Plan and FERC Rules 792, 755, and 784. The Investment Tax Credit (ITC) is a federal government established 30 percent tax credit for residences and businesses that invest in solar photovoltaics and other qualifying renewable energy technologies. o ITC is applicable for energy storage system coupled with renewable energy. Private Generation Long-Term Resource Assessment (2017-2036) Page C-9 ©2016 Navigant Consulting, Inc. o PLR allows 10%-30% ITC depending on RE technology if 75% of energy to battery is renewable. o Recapture risk if renewable < 75% to battery in a single year. Federal Modified Accelerated Cost Recovery System (MACRS), which classifies photovoltaics (and other technologies) as a five-year property for investment recovery through depreciation deductions. Energy storage systems coupled with RE eligible. USEPA Clean Power Plan released August 2015 which mandates that utilities reduce carbon emissions. Implementation will be on a state by state basis, with plans due by 2018. Storage may be co-located with fuel assets to improve carbon efficiency, or with renewables or as DR assets to reduce carbon during peak demand or grid stabilization events. FERC Rules 792, 755, and 784 have created a pay for performance structure for frequency regulation which has enabled storage to compete in these markets. State The energy storage market is currently driven by a handful of states with high electricity prices, demand charges and supportive policy. Some of the most notable policies currently include the following: California: o Self-Generation Incentive Program (SGIP) allows up to $1620/kW for advanced energy storage technologies with a maximum eligible capacity of 3MW. It is budgeted for $83m/year through 2019. o AB 2514 requires 1325MW of storage procurement by 2020 for the large IOUs, including a carve-out of 199MW for behind-the-meter storage. New York REV has suggested methods of reforming the electricity sector in order to facilitate energy storage installations and controls. Oregon HB-2193-B which defines the value of storage, and allows utilities to submit rate- recoverable energy storage procurements through to 2017. Massachusetts state government has allocated $10 million for demonstration projects. Connecticut SB 1078 requires that resources solicited for the Integrated Resource Plan be done through an RFP, and storage may participate in those RFPs. C.4 Storage Customer Applications Current Applications • Demand charge reduction • Retail rate management • Energy arbitrage - renewable energy shifting • Power quality • Backup power Future Applications • Operating Reserves • Capacity (currently only in PJM and CAISO territories via IOUs) Private Generation Long-Term Resource Assessment (2017-2036) Page C-10 ©2016 Navigant Consulting, Inc. Non-Residential Solar + Storage Current Applications • Demand charge reduction – Reduce demand charges by eliminating spikes in demand. Solar coincides with peak but doesn’t effectively reduce demand charges due to intermittent production profile. • Retail rate management - Aid with tariff switching by eliminating consistent spikes in demand, minutes long that could be responsible for unfavorable tariff rates. • Energy arbitrage – Storing energy when it is inexpensive and discharging when electricity is expensive. This requires a large price differential ($/kWh) between different periods of the day. Requires a smart inverter in NEM states. • Power quality – Increasing power quality at the facility, ideal for protecting sensitive equipment. Future Applications • Back-up power – Provide backup power during grid failure. Currently, battery storage is cost prohibitive to serve this application and cannot compete with gas fired back-up generators for non-residential customers. • Load shifting – With the potential future elimination of NEM, storage could allow customers to store excess electricity during daylight hours and discharge during times of high load. Residential Solar + Storage The bulk of the residential storage market will be storage tied to solar PV. Current Applications Back-up power – Provide back-up power in an outage. Future Applications Demand response - Reduce demand charges by eliminating spikes in power demand. o Most residential customers do not pay demand charges or TOU rates (AZ only state with demand charges). Many utilities are considering moving toward time of use pricing although only a few have made the move. Energy arbitrage – Storing energy when it is inexpensive and discharging when electricity is expensive. This requires a large price differential ($/kWh) between different periods of the day. Load shifting – With the potential future elimination of NEM, storage could allow customers to store excess electricity during daylight hours and discharge during times of high load. Wind + Storage Current Applications • Demand charge reduction - Reduce demand charges by eliminating spikes in demand. • Retail rate management - Aid with tariff switching by eliminating consistent spikes in demand, minutes long that could be responsible for unfavorable tariff rates. • Energy arbitrage – Storing wind energy when it is inexpensive and discharging when electricity is expensive. This requires a large price differential ($/kWh) between different periods of the day. • Power quality – Increasing power quality at the facility, ideal for protecting sensitive equipment. Private Generation Long-Term Resource Assessment (2017-2036) Page C-11 ©2016 Navigant Consulting, Inc. Future Applications • Back-up power– Provide backup power during grid failure. Currently, battery storage is cost prohibitive to serve this application and cannot compete with gas fired back-up generators for non-residential customers. • Load shifting – With the potential future reduction or elimination of NEM benefits, storage could allow customers to store excess electricity during times of high wind and discharge during times of high load. • Interconnection costs – If utility plans to charge large interconnection costs to integrate the variable wind, energy storage could mitigate those impacts. Hydro + Storage Small hydro should have an even electricity generation profile throughout a 24 hour period, so coupling storage with hydro has minimal impact compared with intermittent renewables (e.g. solar and wind). Did not make the short list of storage for renewables integration applications in recent Navigant Research report. To a lesser degree, storage can still provide the following benefits when coupled with hydro: o Demand charge reduction o Retail rate management o Power quality o Back-up power o Load shifting CHP + Storage Availability of storage will likely not impact forecasts for CHP. Both reciprocating engines and micro-turbines are load following technologies for customers with high thermal loads. Load following technologies already help customers manage energy and demand charges. Customers with high thermal load will chose CHP over energy storage because CHP reduces thermal and electricity costs, simultaneously. Private Generation Long-Term Resource Assessment (2017-2036) Page D-12 ©2016 Navigant Consulting, Inc. WASHINGTON HIGH-EFFICIENCY COGENERATION LEVELIZED COSTS Section 480.109.100 of the Washington Administrative Code21 establishes high-efficiency cogeneration as a form of conservation that electric utilities must assess when identifying cost-effective, reliable, and feasible conservation for the purpose of establishing 10-year forecasts and biennial targets. To supplement the analysis in the main body of this report addressing reliability and feasibility, this appendix, analyzes the levelized cost of energy (LCOE) of these resources, for use in cost-effectiveness analysis. Key assumptions for the analysis are presented in Table 26 and Table 27. It is worth noting that the LCOE calculation is for the electrical generation component only and the cost of the heat recapture and recovery was taken out of the total installed system cost. PacifiCorp provided the natural gas pricing and the weighted average cost of capital (WACC) assumptions. D.1 Key Assumptions Table 26 Reciprocating Engines LCOE – Key Assumptions22 private generation Resource Costs Units 2017 2026 2036 Notes Installed System Cost $/W $2.61/W $2.71/W $2.82/W EPA, Catalog of CHP Technologies, March 2015, pg. 2-15 Assumed cost for electrical generation only, system cost was reduced by 10% to exclude heating generation costs. Asset Life Years 25 25 25 Capacity Factor % 85% 85% 85% Navigant Assumption Variable O&M $/MWh $20 $20 $20 ICF International Inc., Combined Heat and Power: Policy Analysis and 2011-2030 Market Assessment, pg. 92 Fuel Cost $/MMBtu PacifiCorp Gas Forecast PacifiCorp Gas Forecast PacifiCorp Gas Forecast Provided by PacifiCorp WACC % 6.57% 6.57% 6.57% Provided by PacifiCorp 21 http://apps.leg.wa.gov/WAC/default.aspx?cite=480-109-100 22 EPA, Catalog of CHP Technologies: www.epa.gov/sites/production/files/2015-07/documents/catalog_of_chp_technologies.pdf; ICF, Combined Heat and Power Policy Analysis, www.energy.ca.gov/2012publications/CEC-200-2012-002/CEC-200-2012-002.pdf Private Generation Long-Term Resource Assessment (2017-2036) Page D-13 ©2016 Navigant Consulting, Inc. Table 27 Micro-turbines LOE – Key Assumptions23 private generation Resource Costs Units 2017 2026 2036 Notes Installed System Cost $/W $2.561/W $2.55/W $2.54/W EPA, Catalog of CHP Technologies, March 2015, pg. 2-15 Assumed cost for electrical generation only, system cost was reduced by 5% to exclude heating generation costs. Asset Life Years 25 25 25 Assumption Capacity Factor % 85% 85% 85% Assumption Variable O&M $/MWh $20 $20 $20 ICF International Inc., Combined Heat and Power: Policy Analysis and 2011-2030 Market Assessment, pg. 92 Fuel Cost $/MMBtu PacifiCorp Gas Forecast PacifiCorp Gas Forecast PacifiCorp Gas Forecast Provided by PacifiCorp WACC % 6.57% 6.57% 6.57% Provided by PacifiCorp D.2 Results The results of the LCOE analysis are presented in Table 28, with levelized costs estimated to range from $88/MWh to $111/MWh over the forecast period, varying by year and technology. Table 28 LCOE Results – Electric Component Only Technology Units 2017 2026 2036 Reciprocating Engines $/MWh 98.0 99.7 108.7 Microturbines $/MWh 87.5 99.6 110.9 23 EPA, Catalog of CHP Technologies: www.epa.gov/sites/production/files/2015-07/documents/catalog_of_chp_technologies.pdf; ICF, Combined Heat and Power Policy Analysis, www.energy.ca.gov/2012publications/CEC-200-2012-002/CEC-200-2012-002.pdf Private Generation Long-Term Resource Assessment (2017-2036) Page E-14 ©2016 Navigant Consulting, Inc. COMPARISON OF 2016 AND 2014 STUDY The growth of the solar industry is the main driver in the difference between the 2014 and 2016 study results across PacifiCorp’s territory. Cumulative solar market penetration for the combined residential and non-residential sectors is expected to increase at about six times the rate projected in 2014. This increase in penetration is driven by the ITC extension and the continued decline of solar installation costs. The ITC, originally set to expire in 2016 for commercial solar systems and reduce to 10 percent for residential solar systems, was extended for solar PV systems in December 2015 through the end of 2021, with step downs occurring from 2020 through 2022. The 2014 Study assumed that the ITC would expire for commercial solar PV systems at the end of 2016 and step down to 10 percent for residential PV systems, per the legislation in place at the time of the analysis. Additionally, solar costs have continued to rapidly decline at a faster rate than expected the last few years, with 2017 residential and non-residential solar costs declining by 15 and 25 percent, respectively between the 2014 and 2016 studies. Another difference between the market penetration results is the adoption of CHP micro-turbines and reciprocating engines. Based on the latest references, the cost of installing a micro-turbine remained relatively constant to the assumptions made in 2014, yet CHP reciprocating engines increased by about 30 percent. Additionally, in the 2014 study, technology costs were expected to decline aggressively at 1.4 percent annually over the next 20 years, while the 2016 study expects the equipment costs of these fairly mature technologies to stay relatively flat. All other technologies evaluated had minimal cumulative market penetration in both the 2014 and 2016 studies. Figure 35. Cumulative Market Penetration Results by Technology (MW AC), 2017 – 2036, Base Case (Current Study) Private Generation Long-Term Resource Assessment (2017-2036) Page E-15 ©2016 Navigant Consulting, Inc. Figure 36. Cumulative Market Penetration Results by Technology (MW AC), 2013 – 2034, Base Case (2014 Study) Private Generation Long-Term Resource Assessment (2017-2036) Page F-16 ©2016 Navigant Consulting, Inc. DETAILED NUMERIC RESULTS F.1 Utah Table 29. Utah – Incremental Annual Market Penetration (MW AC) – Base Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.1 0.2 0.2 0.3 0.4 0.4 0.5 0.6 0.7 0.9 0.9 1.2 1.1 1.2 1.4 1.1 1.2 1.0 1.0 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 55.4 82.0 77.7 20.2 19.5 8.3 8.4 9.3 7.4 7.9 8.0 10.5 53.0 42.6 46.1 51.4 52.3 57.8 45.2 47.0 PV Commercial 1.8 2.0 2.4 2.2 1.8 2.1 2.1 2.3 19.3 20.0 19.9 15.0 13.9 13.8 12.5 12.7 11.2 11.3 5.4 2.5 PV Industrial 0.1 0.1 0.3 0.5 0.5 0.1 0.1 0.5 0.8 0.7 0.9 0.6 0.6 0.7 0.6 0.9 1.6 1.3 2.8 1.9 PV Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.3 0.4 0.4 0.4 0.5 0.4 0.4 0.4 0.4 0.2 0.2 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-17 ©2016 Navigant Consulting, Inc. Table 30. Utah – Incremental Annual Market Penetration (MWh) – Base Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 17 1090 1551 1767 2379 2657 3128 4076 4265 4987 7044 6664 9214 8485 8665 10487 8562 8652 7690 7411 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 99113 146737 139036 36123 34960 14844 15007 16617 13279 14202 14234 18753 94911 76192 82487 91991 93634 103402 80897 84212 PV Commercial 3200 3651 4357 3879 3292 3734 3775 4180 34562 35862 35657 26883 24894 24753 22367 22737 19995 20245 9657 4460 PV Industrial 177 202 448 865 971 250 253 939 1476 1325 1570 987 1150 1214 1163 1588 2954 2338 4981 3325 PV Irrigation 53 60 72 64 78 62 63 260 264 532 773 676 677 966 671 690 637 641 395 352 Wind Residential 0 1 1 1 0 1 1 1 0 0 0 1 0 1 1 1 0 1 0 0 Wind Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-18 ©2016 Navigant Consulting, Inc. Table 31. Utah – Incremental Annual Market Penetration (MW AC) – Low Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 50.6 62.7 80.5 18.4 6.8 7.1 7.1 7.9 6.3 6.8 6.8 7.8 6.4 22.3 37.1 41.4 25.4 45.7 36.9 38.7 PV Commercial 1.7 1.9 2.3 2.0 1.7 2.0 2.0 2.2 1.7 10.7 20.1 15.4 9.3 15.4 14.7 9.8 14.1 14.2 4.5 8.3 PV Industrial 0.1 0.1 0.1 0.3 0.4 0.1 0.1 0.2 0.7 0.7 0.8 0.5 0.5 0.6 0.5 0.5 0.6 0.5 0.3 0.3 PV Irrigation 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.3 0.4 0.4 0.4 0.2 0.3 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-19 ©2016 Navigant Consulting, Inc. Table 32. Utah – Incremental Annual Market Penetration (MWh) – Low Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 7 12 19 13 7 11 11 15 6 8 8 13 5 10 11 16 8 12 0 0 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 90623 112341 144056 32940 12169 12653 12791 14164 11318 12105 12133 13974 11535 39933 66480 74086 45520 81816 66117 69300 PV Commercial 2999 3422 4085 3637 3086 3500 3539 3918 3131 19117 35909 27611 16732 27625 26238 17557 25265 25404 8050 14804 PV Industrial 172 196 234 528 750 224 227 413 1207 1254 1503 918 861 1147 864 949 1144 972 524 524 PV Irrigation 47 54 64 81 156 58 59 203 218 261 224 289 375 396 535 709 708 739 288 555 Wind Residential 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 Wind Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-20 ©2016 Navigant Consulting, Inc. Table 33. Utah – Incremental Annual Market Penetration (MW AC) – High Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.2 0.3 0.3 0.6 0.7 0.9 1.2 1.4 1.6 1.6 1.7 1.7 1.8 2.7 3.8 6.5 5.4 6.2 4.4 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.4 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 71.2 86.1 85.7 35.5 22.6 10.0 10.1 11.2 8.9 11.0 75.6 67.7 71.4 57.5 85.1 69.9 96.2 77.6 56.6 57.7 PV Commercial 1.9 2.2 2.6 2.9 14.4 2.6 2.6 18.3 23.5 22.0 19.6 15.1 10.7 10.7 11.6 10.4 9.7 11.1 6.0 7.2 PV Industrial 0.1 0.1 0.5 0.5 0.6 0.2 0.2 1.0 1.0 1.0 1.2 2.0 2.4 3.0 2.9 2.9 2.7 2.6 1.1 1.5 PV Irrigation 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.3 0.6 0.6 0.7 0.5 0.3 0.4 0.3 0.4 0.2 0.3 0.2 0.1 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-21 ©2016 Navigant Consulting, Inc. Table 34. Utah – Incremental Annual Market Penetration (MWh) – High Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocatin g Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocatin g Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocatin g Engine Industrial 263 1527 1979 2529 4623 5190 7009 8666 10053 11582 11847 12878 13006 13440 20087 28503 48346 39904 46391 33085 Reciprocatin g Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7483 10723 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 127507 154195 153509 63551 40508 17892 18087 20029 16005 19661 135315 121192 127912 102994 152448 125061 172300 138896 101378 103387 PV Commercial 3385 3862 4609 5224 25777 4575 4625 32747 42125 39369 35037 27103 19088 19151 20771 18628 17286 19877 10791 12971 PV Industrial 184 210 970 944 1040 276 364 1770 1762 1834 2160 3602 4363 5314 5243 5276 4832 4623 2046 2640 PV Irrigation 59 67 80 71 109 70 71 602 1097 1140 1333 853 588 736 502 635 440 462 304 211 Wind Residential 0 1 1 1 0 1 1 1 0 0 0 1 0 1 1 1 1 1 0 0 Wind Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 113 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-22 ©2016 Navigant Consulting, Inc. F.2 Oregon Table 35. Oregon – Incremental Annual Market Penetration (MW AC) – Base Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 4.4 5.4 5.8 4.4 4.6 4.3 4.4 4.5 5.1 5.5 5.6 11.7 15.2 18.2 21.2 18.1 26.6 22.1 30.2 23.2 PV Commercial 2.5 2.7 3.4 3.2 3.4 2.6 3.5 4.5 4.5 4.7 4.6 4.5 4.4 4.5 4.5 4.5 4.1 4.5 5.5 5.1 PV Industrial 0.0 0.0 0.1 0.0 0.0 0.0 0.0 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 PV Irrigation 0.1 0.2 0.2 0.1 0.2 0.0 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.3 0.5 0.4 0.5 1.0 0.7 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-23 ©2016 Navigant Consulting, Inc. Table 36. Oregon – Incremental Annual Market Penetration (MWh) – Base Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 0 0 0 0 0 0 0 0 0 170 667 819 788 967 869 824 919 955 822 703 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 5946 7341 7853 6031 6273 5863 5961 6080 6991 7538 7663 15924 20755 24760 28945 24615 36228 30123 41169 31558 PV Commercial 3388 3730 4630 4345 4659 3600 4787 6095 6132 6419 6324 6140 6053 6119 6137 6194 5641 6163 7430 6982 PV Industrial 39 55 69 51 63 6 66 100 100 117 114 110 96 153 158 200 198 171 172 132 PV Irrigation 92 215 287 195 263 26 278 397 384 454 430 399 378 329 381 665 593 639 1321 905 Wind Residential -1 0 0 0 0 0 0 0 0 0 0 20 30 31 31 32 31 32 25 25 Wind Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 127 152 163 168 172 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 0 0 0 0 0 0 0 0 1 8 9 10 11 12 10 12 10 Private Generation Long-Term Resource Assessment (2017-2036) Page F-24 ©2016 Navigant Consulting, Inc. Table 37. Oregon – Incremental Annual Market Penetration (MW AC) – Low Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 4.1 5.2 5.7 4.2 4.6 4.3 4.4 4.4 4.5 5.5 5.6 5.1 5.3 5.1 9.3 11.4 12.7 19.3 15.5 16.7 PV Commercial 2.5 2.7 3.1 3.0 3.3 2.6 3.0 4.1 4.3 4.3 4.5 4.3 4.3 4.1 4.4 4.1 4.3 4.1 3.7 3.6 PV Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 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 PV Irrigation 0.1 0.1 0.2 0.1 0.2 0.0 0.1 0.2 0.3 0.3 0.3 0.3 0.2 0.2 0.3 0.2 0.2 0.2 0.1 0.1 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-25 ©2016 Navigant Consulting, Inc. Table 38. Oregon – Incremental Annual Market Penetration (MWh) – Low Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 5628 7113 7766 5771 6207 5843 5939 6054 6162 7487 7615 6945 7174 6992 12636 15583 17377 26370 21109 22733 PV Commercial 3353 3679 4249 4109 4516 3583 4080 5639 5895 5902 6081 5907 5856 5561 5946 5609 5897 5582 4976 4941 PV Industrial 35 50 65 40 53 5 35 90 91 99 105 92 78 90 79 92 74 90 128 127 PV Irrigation 91 170 259 178 222 23 201 332 352 380 397 367 298 300 355 300 274 286 180 172 Wind Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 25 Wind Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Private Generation Long-Term Resource Assessment (2017-2036) Page F-26 ©2016 Navigant Consulting, Inc. Table 39. Oregon – Incremental Annual Market Penetration (MW AC) – High Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.3 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 4.8 5.5 5.8 4.6 4.8 4.3 4.4 5.0 11.7 26.5 36.7 25.9 36.6 33.2 41.4 36.6 38.6 42.8 40.0 29.7 PV Commercial 2.5 2.9 3.6 3.4 3.7 2.7 4.1 4.8 4.9 5.1 5.3 4.8 5.5 6.6 7.7 11.6 9.7 8.0 8.4 7.8 PV Industrial 0.0 0.0 0.1 0.0 0.1 0.0 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.1 0.1 PV Irrigation 0.1 0.2 0.2 0.2 0.2 0.0 0.3 0.3 0.4 0.4 0.5 0.7 0.8 1.0 1.1 1.1 1.0 0.9 0.5 0.6 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-27 ©2016 Navigant Consulting, Inc. Table 40. Oregon – Incremental Annual Market Penetration (MWh) – High Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 0 0 0 0 0 350 566 726 772 996 1037 1173 1163 1235 1455 2279 2305 2401 2028 2011 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 6497 7468 7962 6308 6558 5892 5992 6759 15981 36114 50073 35265 49878 45265 56411 49921 52575 58317 54574 40466 PV Commercial 3410 3956 4917 4603 4975 3624 5594 6607 6679 7012 7255 6490 7496 8975 10456 15821 13264 10884 11468 10593 PV Industrial 43 56 79 57 74 7 99 125 127 163 293 206 237 250 224 232 224 236 181 177 PV Irrigation 129 241 289 250 265 33 411 471 502 501 627 960 1155 1399 1437 1434 1321 1263 641 772 Wind Residential -1 0 0 0 0 0 0 0 28 37 38 38 38 38 32 45 47 48 47 37 Wind Commercial -1 0 0 0 0 0 0 0 0 0 0 97 173 174 191 207 213 192 189 189 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 0 0 0 0 0 0 8 9 11 12 14 13 15 11 14 13 13 Private Generation Long-Term Resource Assessment (2017-2036) Page F-28 ©2016 Navigant Consulting, Inc. F.3 Washington Table 41. Washington – Incremental Annual Market Penetration (MW AC) – Base Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 0.6 0.0 0.1 0.1 0.1 0.0 0.1 0.1 0.1 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.0 PV Commercial 0.4 0.5 0.7 0.4 0.4 0.0 0.6 1.0 1.1 1.2 1.1 1.0 1.0 1.0 1.0 0.8 1.0 1.2 1.9 1.4 PV Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 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 PV Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.3 0.3 0.3 0.3 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-29 ©2016 Navigant Consulting, Inc. Table 42. Washington – Incremental Annual Market Penetration (MWh) – Base Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 0 39 88 101 141 142 163 247 207 342 331 232 350 336 193 392 305 290 274 260 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 961 69 82 77 93 69 86 87 105 75 92 93 113 82 100 98 96 96 0 0 PV Commercial 657 794 1012 550 647 69 976 1577 1758 1826 1742 1557 1602 1500 1529 1240 1471 1811 2996 2121 PV Industrial 40 54 68 50 61 5 76 93 109 105 110 140 147 175 183 154 154 190 125 122 PV Irrigation 18 10 11 11 13 10 94 170 204 189 198 177 182 143 291 269 458 462 412 401 Wind Residential 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Commercial 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-30 ©2016 Navigant Consulting, Inc. Table 43. Washington – Incremental Annual Market Penetration (MW AC) – Low Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Commercial 0.4 0.5 0.6 0.3 0.3 0.0 0.4 0.8 1.1 1.0 1.0 0.9 0.8 0.7 0.9 0.7 0.7 0.9 0.5 0.5 PV Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.0 0.1 0.1 0.1 0.1 0.1 PV Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 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 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-31 ©2016 Navigant Consulting, Inc. Table 44. Washington – Incremental Annual Adoption (MWh) – Low Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 0 26 45 41 63 38 42 59 45 94 48 0 25 8 0 10 30 0 0 0 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 707 51 60 57 68 51 63 64 77 55 68 68 83 61 74 72 71 71 0 0 PV Commercial 628 761 901 405 462 61 637 1296 1615 1508 1603 1430 1247 1146 1413 1136 1106 1365 757 724 PV Industrial 38 50 63 43 52 4 53 86 88 97 94 86 79 73 73 137 139 107 119 118 PV Irrigation 12 9 11 10 12 9 23 157 173 176 185 142 144 157 133 129 124 122 82 214 Wind Residential 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-32 ©2016 Navigant Consulting, Inc. Table 45. Washington – Incremental Annual Market Penetration (MW AC) – High Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 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 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 1.5 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 0.0 0.0 PV Commercial 0.5 0.6 0.7 0.5 0.5 0.1 1.1 1.2 1.4 1.4 1.4 1.3 2.2 2.2 4.9 4.0 3.9 2.8 3.0 2.6 PV Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.2 0.2 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.2 PV Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 0.1 0.3 0.3 0.4 0.4 0.4 0.4 0.4 0.3 0.2 0.1 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-33 ©2016 Navigant Consulting, Inc. Table 46. Washington – Incremental Annual Market Penetration (MWh) – High Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial -1 88 128 176 225 248 297 377 397 509 512 477 551 458 449 496 471 445 714 980 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 209 240 220 336 277 285 262 263 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 2272 114 135 128 153 114 142 145 173 124 153 154 187 136 165 163 160 160 0 0 PV Commercial 696 898 1150 725 762 79 1623 1912 2129 2209 2147 1974 3387 3451 7525 6136 6029 4298 4640 4022 PV Industrial 42 59 75 59 68 7 103 122 142 259 261 197 236 202 209 210 210 176 167 369 PV Irrigation 67 28 13 12 15 11 107 204 241 228 435 442 622 628 634 607 563 399 376 230 Wind Residential 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Commercial 0 0 0 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 51 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 3 6 6 6 Private Generation Long-Term Resource Assessment (2017-2036) Page F-34 ©2016 Navigant Consulting, Inc. F.4 Idaho Table 47. Idaho – Incremental Annual Market Penetration (MW AC) – Base Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 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 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 0.2 0.2 0.2 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 1.0 1.0 1.8 1.5 2.3 1.8 PV Commercial 0.2 0.3 0.3 0.2 0.3 0.0 0.3 0.3 0.3 0.4 0.4 0.6 0.5 0.8 1.1 0.8 0.8 0.8 0.6 0.5 PV Industrial 0.1 0.1 0.1 0.1 0.1 0.0 0.1 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.3 PV Irrigation 0.3 0.4 0.4 0.3 0.4 0.1 0.4 0.5 0.9 0.9 1.3 1.4 1.0 1.0 1.0 1.0 0.9 0.9 0.3 0.4 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-35 ©2016 Navigant Consulting, Inc. Table 48. Idaho – Incremental Annual Market Penetration (MWh) – Base Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 0 144 177 236 295 324 406 503 529 621 621 645 797 994 1013 1032 1000 1003 944 690 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 366 384 407 98 152 43 44 48 41 45 45 134 136 189 1774 1750 3143 2584 4121 3090 PV Commercial 371 439 542 431 464 63 523 595 600 615 709 1071 849 1355 1944 1458 1417 1418 1064 894 PV Industrial 99 123 219 157 196 22 108 279 295 313 325 255 248 251 250 208 246 256 126 505 PV Irrigation 505 624 723 574 657 102 779 821 1540 1659 2297 2415 1805 1796 1738 1700 1558 1511 558 765 Wind Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-36 ©2016 Navigant Consulting, Inc. Table 49. Idaho – Incremental Annual Market Penetration (MW AC) – Low Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 0.2 0.2 0.2 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.2 0.8 PV Commercial 0.2 0.2 0.3 0.2 0.2 0.0 0.2 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.4 0.5 0.5 0.5 0.7 0.7 PV Industrial 0.1 0.1 0.1 0.1 0.1 0.0 0.0 0.1 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 PV Irrigation 0.3 0.3 0.4 0.3 0.4 0.0 0.3 0.4 0.4 0.4 0.8 0.6 0.8 1.0 1.0 0.7 1.0 1.0 0.4 0.7 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-37 ©2016 Navigant Consulting, Inc. Table 50. Idaho – Incremental Annual Market Penetration (MWh) – Low Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial -1 0 0 0 0 0 0 30 35 116 92 2 153 49 43 172 176 182 106 103 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 356 344 397 90 109 39 40 43 38 41 41 44 38 125 138 194 143 153 428 1444 PV Commercial 342 425 527 379 401 59 367 557 566 516 585 446 418 415 788 818 831 824 1239 1179 PV Industrial 92 120 170 125 157 19 45 194 270 290 265 233 185 232 186 238 182 188 174 103 PV Irrigation 469 607 704 509 629 86 606 780 704 711 1318 1075 1390 1749 1799 1163 1805 1816 761 1233 Wind Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-38 ©2016 Navigant Consulting, Inc. Table 51. Idaho – Incremental Annual Market Penetration (MW AC) – High Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.4 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 0.2 0.2 0.2 0.1 0.2 0.0 0.0 0.0 0.0 0.0 1.7 2.2 2.1 2.5 4.0 2.4 3.9 5.2 3.8 2.6 PV Commercial 0.2 0.3 0.3 0.3 0.3 0.0 0.4 0.4 0.7 1.0 1.6 1.1 1.0 0.8 0.9 0.7 0.8 0.6 0.4 0.2 PV Industrial 0.1 0.1 0.2 0.1 0.1 0.0 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.4 0.4 0.6 0.6 0.6 0.5 0.4 PV Irrigation 0.3 0.4 0.5 0.5 0.6 0.1 0.5 1.3 1.8 1.6 1.5 1.0 1.1 0.9 1.0 0.8 0.7 0.7 0.5 0.3 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-39 ©2016 Navigant Consulting, Inc. Table 52. Idaho – Incremental Annual Market Penetration (MWh) – High Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 33 183 229 306 369 416 786 978 1055 1331 1358 1320 1498 1544 1355 1540 1257 1447 2125 2618 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 759 1044 1052 897 911 850 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 379 427 385 177 406 53 54 59 51 55 2919 3929 3740 4466 6959 4281 6768 9116 6608 4635 PV Commercial 386 482 567 458 533 68 689 696 1275 1739 2727 1899 1810 1354 1622 1208 1346 1022 776 400 PV Industrial 102 156 285 177 217 25 235 341 394 383 358 327 275 632 617 1081 1104 1111 903 761 PV Irrigation 524 647 836 868 976 109 834 2281 3202 2818 2713 1766 1972 1508 1679 1326 1189 1202 928 575 Wind Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-40 ©2016 Navigant Consulting, Inc. F.5 California Table 53. California – Incremental Annual Market Penetration (MW AC) – Base Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 0.1 0.1 0.8 0.3 0.3 0.0 0.0 0.0 0.0 0.0 0.2 0.6 0.7 1.2 0.9 1.0 1.1 1.2 1.2 1.6 PV Commercial 0.2 0.3 0.3 0.3 0.3 0.2 0.4 0.4 0.4 0.4 0.4 0.4 0.3 0.3 0.4 0.3 0.3 0.3 0.2 0.4 PV Industrial 0.0 0.0 0.1 0.0 0.1 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0 PV Irrigation 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.1 0.1 0.2 0.1 0.1 0.1 0.1 0.2 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-41 ©2016 Navigant Consulting, Inc. Table 54. California – Incremental Annual Market Penetration (MWh) – Base Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 11 33 45 56 67 74 91 97 108 108 117 111 100 106 87 83 66 63 58 76 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 4 13 17 20 26 31 41 69 90 94 129 140 114 113 130 100 84 77 68 59 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 192 204 1489 565 577 49 46 57 39 49 388 1118 1240 2112 1639 1847 1956 2175 2102 2904 PV Commercial 440 484 529 534 580 393 676 753 678 684 674 701 546 541 678 561 501 539 382 725 PV Industrial 31 56 108 74 103 6 41 154 193 170 166 111 123 118 108 104 68 87 54 32 PV Irrigation 183 201 220 222 241 163 280 313 281 284 280 291 226 224 281 233 208 223 158 301 Wind Residential -1 -1 -1 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Commercial 0 0 0 3 4 6 7 9 9 11 12 13 11 13 10 12 9 9 8 10 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 Wind Irrigation 0 0 0 1 1 2 3 4 4 4 5 5 4 5 4 5 4 4 4 3 Private Generation Long-Term Resource Assessment (2017-2036) Page F-42 ©2016 Navigant Consulting, Inc. Table 55. California – Incremental Annual Market Penetration (MW AC) – Low Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 0.1 0.1 0.4 0.1 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.5 0.6 0.6 0.7 0.4 0.8 0.9 PV Commercial 0.2 0.3 0.3 0.3 0.3 0.2 0.4 0.4 0.4 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.1 0.1 PV Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.1 0.0 0.0 0.0 PV Irrigation 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-43 ©2016 Navigant Consulting, Inc. Table 56. California – Incremental Annual Market Penetration (MWh) – Low Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial -1 8 26 34 41 51 60 87 79 87 91 95 90 88 82 79 39 62 57 51 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 1 6 7 8 14 17 21 22 27 27 29 35 30 30 29 28 25 24 23 15 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 176 198 705 140 399 28 27 34 23 29 29 38 238 862 1008 1178 1307 778 1455 1584 PV Commercial 414 489 530 527 537 345 673 700 666 661 636 569 490 476 542 463 394 417 262 260 PV Industrial 30 41 84 65 75 5 14 113 153 168 173 106 132 95 123 88 105 74 71 38 PV Irrigation 172 203 220 218 223 143 279 290 276 274 264 236 203 197 225 192 164 173 109 108 Wind Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Commercial 0 0 0 2 3 4 5 5 6 6 6 7 10 8 8 8 7 7 7 7 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 1 1 2 2 2 2 2 2 3 4 3 3 3 3 3 3 3 Private Generation Long-Term Resource Assessment (2017-2036) Page F-44 ©2016 Navigant Consulting, Inc. Table 57. California – Incremental Annual Market Penetration (MW AC) – High Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 0.1 0.5 1.4 0.5 0.8 0.0 0.0 0.1 0.0 0.7 1.7 1.5 1.1 2.2 1.8 1.4 1.4 2.2 1.4 1.5 PV Commercial 0.2 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.4 0.4 0.5 0.5 0.4 0.6 0.4 0.7 0.5 0.8 0.4 0.4 PV Industrial 0.0 0.0 0.1 0.0 0.1 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.1 PV Irrigation 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.2 0.3 0.2 0.2 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-45 ©2016 Navigant Consulting, Inc. Table 58. California – Incremental Annual Market Penetration (MWh) – High Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 14 41 47 58 69 82 93 106 113 122 118 133 130 113 132 109 94 139 98 96 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 6 16 27 42 68 88 94 110 118 126 128 129 109 116 98 97 85 89 93 100 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 198 890 2563 850 1375 90 84 106 71 1334 3102 2796 2076 3990 3265 2533 2548 4036 2565 2689 PV Commercial 435 479 553 548 596 460 731 787 806 787 963 939 715 1020 767 1233 821 1465 772 804 PV Industrial 32 75 139 84 111 7 122 211 162 179 165 127 111 108 101 105 95 106 83 94 PV Irrigation 180 199 229 227 247 191 303 326 334 326 399 389 297 423 318 512 341 608 320 334 Wind Residential -1 -1 -1 0 -1 0 0 0 -1 0 0 0 0 0 0 0 0 0 5 5 Wind Commercial 0 0 0 4 5 7 8 11 11 12 13 14 14 14 14 14 10 12 9 26 Wind Industrial 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 Wind Irrigation 0 0 0 2 2 3 3 4 5 5 5 6 6 6 6 6 4 5 4 11 Private Generation Long-Term Resource Assessment (2017-2036) Page F-46 ©2016 Navigant Consulting, Inc. F.6 Wyoming Table 59. Wyoming – Incremental Annual Market Penetration (MW AC) – Base Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 0.1 0.2 0.3 0.2 0.2 0.0 0.0 0.0 0.1 0.2 0.2 0.2 0.1 0.1 1.4 1.4 2.4 1.9 2.1 3.5 PV Commercial 0.2 0.3 0.3 0.3 0.4 0.2 0.6 0.7 1.0 1.4 1.9 1.7 1.8 2.3 1.8 1.7 1.6 1.5 0.8 1.0 PV Industrial 0.0 0.1 0.1 0.1 0.1 0.0 0.1 0.2 0.3 0.3 0.3 0.4 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.2 PV Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-47 ©2016 Navigant Consulting, Inc. Table 60. Wyoming – Incremental Annual Market Penetration (MWh) – Base Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1410 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 44 55 74 85 103 132 145 170 180 226 286 308 375 467 472 471 440 267 418 384 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 258 381 531 397 427 38 36 47 240 336 340 278 253 203 2562 2486 4437 3558 3816 6454 PV Commercial 357 481 628 629 715 360 1055 1257 1782 2506 3538 3193 3249 4281 3323 3221 2919 2737 1457 1922 PV Industrial 86 114 161 172 237 16 250 440 513 643 607 658 584 612 596 592 555 449 456 435 PV Irrigation 9 12 21 18 29 2 26 44 81 81 90 80 77 78 72 68 59 55 30 36 Wind Residential 0 0 0 0 0 0 0 26 36 36 36 30 34 28 34 27 29 39 41 41 Wind Commercial 1 1 1 0 0 0 0 0 0 0 0 0 -1 228 247 266 226 282 295 246 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 0 0 0 0 0 0 0 3 4 4 4 4 5 4 5 4 3 Private Generation Long-Term Resource Assessment (2017-2036) Page F-48 ©2016 Navigant Consulting, Inc. Table 61. Wyoming – Incremental Annual Market Penetration (MW AC) – Low Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 0.1 0.2 0.3 0.2 0.2 0.0 0.0 0.0 0.0 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.3 1.1 PV Commercial 0.2 0.3 0.3 0.3 0.4 0.1 0.5 0.6 0.7 0.8 1.0 1.1 1.1 1.6 1.2 1.7 1.7 1.7 0.9 1.4 PV Industrial 0.0 0.1 0.1 0.1 0.1 0.0 0.1 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.3 0.2 0.2 PV Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-49 ©2016 Navigant Consulting, Inc. Table 62. Wyoming – Incremental Annual Market Penetration (MWh) – Low Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 36 47 60 73 89 107 125 147 143 165 175 180 146 167 152 117 121 146 241 144 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 232 362 480 367 357 34 32 43 27 216 324 264 177 192 183 257 176 183 610 2056 PV Commercial 333 466 609 572 681 267 999 1117 1208 1401 1933 1982 2020 3035 2124 3200 3131 3104 1654 2550 PV Industrial 81 110 146 132 165 59 232 277 352 523 536 517 516 464 533 535 413 504 330 311 PV Irrigation 8 11 17 14 20 5 25 32 44 58 82 56 74 77 75 54 68 46 53 31 Wind Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 15 27 27 27 20 27 20 Wind Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 3 4 Private Generation Long-Term Resource Assessment (2017-2036) Page F-50 ©2016 Navigant Consulting, Inc. Table 63. Wyoming – Incremental Annual Market Penetration (MW AC) – High Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Reciprocating Engine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.2 Reciprocating Engine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Micro Turbine Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Commercial 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 Small Hydro Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Small Hydro Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PV Residential 0.2 0.2 0.3 0.3 0.3 0.0 0.0 0.1 0.3 0.2 2.5 2.3 3.8 3.5 4.0 4.6 3.4 5.5 6.3 3.5 PV Commercial 0.2 0.3 0.4 0.4 0.6 0.0 0.8 1.4 2.0 2.3 2.8 1.9 2.1 1.8 1.9 1.5 1.3 1.4 0.9 0.9 PV Industrial 0.0 0.1 0.1 0.1 0.2 0.0 0.2 0.3 0.4 0.4 0.5 0.4 0.4 0.4 0.6 0.9 1.2 1.3 1.2 1.1 PV Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Residential 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Commercial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.1 0.1 Wind Industrial 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Wind Irrigation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Private Generation Long-Term Resource Assessment (2017-2036) Page F-51 ©2016 Navigant Consulting, Inc. Table 64. Wyoming – Incremental Annual Market Penetration (MWh) – High Case Technology Sector 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Reciprocating Engine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Reciprocating Engine Industrial 0 0 0 0 0 0 0 0 0 0 0 1821 2133 2097 2258 2026 2035 2063 1953 1743 Reciprocating Engine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Commercial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Micro Turbine Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Residential 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Commercial 49 64 83 101 116 203 219 378 397 449 601 531 510 511 468 428 360 316 303 197 Small Hydro Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Small Hydro Irrigation 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 PV Residential 277 428 567 469 467 43 40 191 493 421 4644 4271 6966 6501 7442 8499 6287 10160 11676 6473 PV Commercial 373 501 681 825 1039 77 1491 2618 3661 4224 5164 3563 3880 3321 3473 2786 2408 2637 1683 1592 PV Industrial 89 122 244 199 293 19 409 592 694 741 833 700 753 791 1082 1643 2217 2302 2118 1969 PV Irrigation 9 13 30 29 31 2 52 79 90 96 99 80 82 73 66 62 64 55 32 44 Wind Residential 1 1 1 0 0 21 49 47 47 39 45 31 52 53 51 51 48 38 41 51 Wind Commercial 1 1 1 0 0 0 0 0 -1 47 252 266 298 332 305 364 314 316 328 326 Wind Industrial 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Wind Irrigation 0 0 0 0 0 0 0 1 4 4 5 5 6 5 5 6 5 5 5 5 PACIFICORP – 2017 IRP APPENDIX O – PRIVATE GENERATION STUDY 414 PACIFICORP – 2017 IRP APPENDIX P – ENGERY STORAGE STUDIES APPENDIX P – ENERGY STORAGE STUDIES To support PacifiCorp’s 2017 Integrated Resource Plan (IRP) two energy storage studies, initiated for previous IRPs, were updated including a battery energy storage study that focused on battery technologies and a bulk energy storage study that focused on pumped hydro and compressed air energy storage (CAES). DNV-GL’s Battery Energy Storage Study provided PacifiCorp with a catalog of commercially available and emerging battery energy storage technologies with forecasts and estimates for both performance and costs. To further support PacifiCorp’s bi-annual IRP, DNV GL produced probabilistic cost graphs for each of the proposed technologies, broken out by technology, energy conversion system, controls, and the remaining balance of system. The Bulk Energy Storage Study prepared by Black and Veatch (B&V) is an update to work HDR Navigant performed to support the 2015 IRP, incorporating updated information on three pumped hydro energy storage projects and a compressed air energy storage project within PacifiCorp’s territory. The study provides an update to information on commercially available utility-scale energy storage technologies, as well as their applications, performance characteristics, and estimated capital and operating costs. The estimates and information in the studies was used to inform the 2017 IRP and may be used to develop alternative applications to traditional utility transmission and distribution issues. 415 PACIFICORP – 2017 IRP APPENDIX O – PRIVATE GENERATION STUDY 416 the 2017 IRP : Battery Energy Storage Study for IRP 2016 SOW No.: 128197#-P-01-A Date of this Issue: 8/22/2016 7/27/2016 KEMA, Inc. Customer Details Customer Name: Pacificorp Customer Address: DNV GL Company Details DNV GL Legal Entity: KEMA, Inc. DNV GL Organization Unit: Advisory Americas DNV GL Address: 4377 County Line Road, Chalfont, PA 18914 DNV GL Telephone. No.: -997-4500 About this document Report Title: Energy Storage Technology Review Date of this issue: 2016-08-22 Date of last revision: 2016-07-27 Validity of Report: 30 days from date of issue Document Classification (see key below): Customer’s Discretion KEY TO DOCUMENT CLASSIFICATION Strictly Confidential: organization. Private and Confidential: matter of the document within the Customer’s organization. Commercial in Confidence: DNV GL only: Customer’s Discretion: to the above Important Notice and Disclaimer and the terms of DNV GL’s written agreement with the Customer). Published: Important Notice and Disclaimer). KEMA, Inc. Page ii Important Notice and Disclaimer This Report was prepared and issued for the sole use of the Customer. Neither this Report, nor any Report shall form a contract or GL) entering into a written agreement with DNV GL in accordance GL’s standard terms and conditions, which may be contained or referenced in this Report or ed by DNV GL upon request. Report has been created and produced using information available as of the date of this Report and, Report. There are no rights Report or Report may be subject to change at the sole GL and the provision of this Report does not assure or imply otherwise. Confidentiality and Copyright Protection Copyright © 2016 DNV GL. This Report and the information contained herein, is the exclusive, confidential and proprietary property of DNV GL and is protected under the trade secret and copyright laws of the U.S. and other international laws, treaties and conventions. No part of this Report may be disclosed to any third party or used, reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying and recording, or by any information storage or retrieval system, without first receiving the express written permission of DNV GL. Except as otherwise noted, all trademarks appearing herein are proprietary to DNV GL. For KEMA, Inc. KEMA, Inc. Page iii Table of contents 1 INTRODUCTION ............................................................................................................................. 1 1.1 Objective and Scope of Work ........................................................................................................ 1 1.2 Background and Materials ............................................................................................................ 1 2 STAGE OF COMMERCIAL DEVELOPMENT ........................................................................................... 3 2.1 Lithium-Ion Batteries ................................................................................................................... 3 2.2 Sodium Sulfur Batteries ............................................................................................................... 5 2.3 Vanadium Redox Batteries ............................................................................................................ 6 2.4 Zinc Redox Batteries .................................................................................................................... 7 2.5 Zinc Hybrid Cathode Batteries ....................................................................................................... 8 2.6 Commercialization Data ............................................................................................................... 9 3 PERFORMANCE CHARACTERISTICS .................................................................................................10 3.1 Power Capability ........................................................................................................................10 3.2 Energy Capacity .........................................................................................................................10 3.3 Recharge Rates ..........................................................................................................................11 3.4 Round Trip Efficiency ..................................................................................................................11 3.5 Availability ................................................................................................................................11 3.6 Degradation ...............................................................................................................................11 3.7 Expected Life .............................................................................................................................13 3.8 Environmental Effect Upon Disposal ..............................................................................................13 3.9 Technical Parameters Data ..........................................................................................................15 4 COST ESTIMATES AND TRENDS ......................................................................................................16 4.1 Energy Storage Equipment Costs .................................................................................................16 4.2 Power Conversion System Equipment Costs ...................................................................................16 4.3 Power Control System Costs ........................................................................................................17 4.4 Balance of System ......................................................................................................................17 4.5 Installation ................................................................................................................................17 4.6 Fixed O&M .................................................................................................................................17 4.7 Total System Cost Estimates ........................................................................................................19 4.8 Example Installed Cost Calculation ...............................................................................................20 4.9 System 10-Year Cost Trends ........................................................................................................21 5 UTILITY APPLICATIONS AND VALUE STREAM ....................................................................................25 5.1 Considered Applications ..............................................................................................................25 5.2 PacifiCorp Territory Regulatory Concerns and Application Drivers .....................................................28 5.3 Application Ranking Methodology and Results ................................................................................31 6 CONCLUSION ...............................................................................................................................34 KEMA, Inc. Page iv List of tables Table 1 Li-Ion Battery Manufacturers ................................................................................................... 5 Table 2 NaS Battery Manufacturers ..................................................................................................... 6 Table 3 VRB Manufacturers ................................................................................................................ 7 Table 4 ZnBr Battery Manufacturers .................................................................................................... 8 Table 5 Zinc-Hybrid Cathode Battery Manufacturer ............................................................................... 8 Table 6 Installation and Commercialization Data ................................................................................... 9 Table 7 Combustion Byproducts of Commercially Available Batteries ..................................................... 14 Table 8 Technical Parameters and Performance Characteristics Data, from Both Cell and Project-Scale Perspectives ................................................................................................................................... 15 Table 9 Energy storage system cost estimates .................................................................................... 19 Table 10 Example Installed Capital Cost Calculation for 10 MW, 20 MWh NCM Li-Ion Energy Storage System .................................................................................................................................................... 20 Table 11 Application Rankings in Current Market Rules Scenario ........................................................... 32 Table 12 Application Rankings for CAISO Market Rules Scenario ........................................................... 33 List of figures Figure 1 General Schematic and Components of a Cell-Based Battery Energy Storage System .................... 4 Figure 2 General Schematic and Components of a Redox Flow Battery Energy Storage System .................. 6 Figure 3 Projected DC System Cost Trends for Various Technologies, From 2016 to 2026 ........................ 21 Figure 4 Projected PCS Cost Trends for Various Technologies, From 2016 to 2026 .................................. 23 Figure 5 Projected Controls Cost Trends for Various Technologies, From 2016 to 2026 ............................ 23 Figure 6 Projected Balance of System Cost Trends for Various Technologies, From 2016 to 2026 .............. 24 KEMA, Inc. Page v 1 INTRODUCTION 1.1 Objective and Scope of Work At the behest of PacifiCorp, DNV GL has provided a status report and assessment of future potential applications for battery energy storage. DNV GL understands that PacifiCorp’s objective is to compile and maintain a catalog of engineering estimates of costs and performance metrics for utility scale battery energy storage technology, both demonstrated for currently commercially available technology as well as forecasted for emerging technology. The 2017 PacifiCorp Integrated Resource Plan (IRP) will include a portfolio of generating resources and energy storage options for evaluation. The provided estimates and information is intended for PacifiCorp’s use when preparing their upcoming and future IRPs and assessing energy storage applications for traditional utility transmission and distribution planning issues. The scope of work is divided between cataloging technology updates and cost trends. The technology updates are broken down by current stage of commercialization, utility applications with associated value streams, and a detailed list of technology performance metrics. The cost analysis includes current system costs for the battery, PCS, controls, installation and O&M, as well as 10-year cost trends for each listed technology. PacifiCorp has specifically requested the scope to include NCM, LiFePO4, and LTO Lithium-Ion (Li-Ion) batteries, Sodium Sulfur (NaS) batteries, Vanadium Redox (VRB) and Zinc Redox (ZnBr) flow batteries, as well as Zinc Hybrid Cathode (also known as Zinc-air) batteries. The report scope does not include application modeling or costs related to a specific vendor, but instead aims to cover the broader energy storage industry as it applies to applications being pursued by PacifiCorp. The final report provides PacifiCorp with a catalog of commercially available and emerging battery energy storage technologies with forecasts and estimates for both performance and costs. DNV GL has compiled this catalog through the proposed scope of work. To further support PacifiCorp’s bi-annual IRP, DNV GL has produced probabilistic cost graphs for each of the proposed technologies, broken out by technology, energy conversion system, controls, and the remaining balance of system. 1.2 Background and Materials In 2013, PacifiCorp hired HDR Engineering to prepare an energy storage screening study, examining utility- scale storage potential, which was updated by HDR for PacifiCorp’s 2015 IRP. This study covered operating and cost data for various energy storage technologies, with a section dedicated to batteries, including details on system size and lifecycle, comparing them to other storage options. The HDR study considers specific manufacturer’s products and reference cases under standard operating conditions. PacifiCorp utilized the information from the HDR research to contribute to the modeling of future energy consumption, and how various technologies impact load profiles, costs, and CO2 emissions. This and other previous energy storage studies performed for PacifiCorp are available at www.pacificorp.com/es/irp.html. Energy storage continues to be of interest to stakeholders – and options for advanced large batteries (one megawatt or larger) are detailed in the IRP as quoted from the HDR study, including the battery types DNV GL has been requested to explore. To the extent possible, DNV GL has built upon and utilized existing studies and reports, to expand and update a battery catalog to include a deeper dive into battery technologies, costs, and applications for PacifiCorp’s use in their 2017 IRP. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 1 www.dnvgl.com As a global advisory, classification, certification, and technical assurance company, DNV GL has served the energy sector as well as maritime and oil & gas industries for over 150 years. DNV GL is a leading authority on consulting, implementation, research, testing, and certification of solutions for the energy sector. Recognized as a global leader in the area of energy storage, DNV GL provides strategic advisory services, innovative modeling tools, and independent testing and certification of energy storage products to clients across various sectors. DNV GL operates as an independent entity without ties to any vendor, with no investments, affiliations, or financial interest with any equipment or service providers. Most notably related to this effort, DNV GL has been actively involved in supporting multiple energy storage procurement efforts in the US. Our models for energy storage cost-effectiveness have been employed by state energy commissions, system operators, electric utilities, and project developers to assess the application value of energy operating the grid for a variety of current and future applications. DNV GL has performed independent bid evaluation for utility wholesale and distribution connected energy storage RFOs. This work involved processing energy storage offers from project developers and providing a ranking and bid evaluation on the capital and O&M costs as well as an assessment of the proposed warranty and performance guarantees. Finally, DNV GL is the industry leader in providing independent engineering analysis and technical due diligence to support third-party financing of energy storage deployments. As part of this work, DNV GL has gained significant insight into the costs, technical characteristics, and life-time performance guarantees of energy storage projects being developed in the US. For this report, DNV GL leveraged their experience with battery technology and the broader energy industry to develop reasonable average values for technology parameters, as well as how these parameters affect the cost and feasibility of a particular technology for an application. Additionally, this study draws on a recommended practice (RP) document called GRIDSTOR (DNVGL-RP- 0043), which was developed by DNV GL in partnership with members of the energy storage industry, including technology vendors, grid service providers, energy consultants, and universities. The GRIDSTOR RP provides a breadth of actionable information for deploying safe and reliable grid-connected energy storage systems, offering a blueprint for an independent quality guarantee of the safe implementation and operation of energy storage systems. This guideline draws on DNV GL experience, credible industry insight, and globally accepted regulations and best practices (such as IEC, ISO, and IEE standards), and was utilized as a reference for this report. GRIDSTOR is publicly available for free download at www.dnvgl.com/energy/brochures/download/gridstor.html. Finally, under the scope of this effort, DNV GL also conducted current market research. This research included a review of published reports from consulting and energy-related clearinghouses, such as Navigant and IRENA, publicly available specification sheets and pricing for reviewed systems, and university and government sponsored research. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 2 www.dnvgl.com 2 STAGE OF COMMERCIAL DEVELOPMENT In this chapter, DNV GL provides an overview of the commercial development of each battery technology requested by PacifiCorp. DNV GL understands the importance of assessing the commercial viability of technologies which are intended to be procured as 10 to 20 year critical assets. With this consideration, DNV GL has provided definitions and basic information surrounding each considered technology and the associated system, followed by a sample of technology providers and sample products available on the market. This is followed by a summary of data available on current industry installation rates, including additional insight into some of the drivers behind the recent trends on installations. 2.1 Lithium-Ion Batteries Lithium-Ion (Li-Ion) batteries utilize the exchange of Lithium ions between electrodes to charge and discharge the battery. Li-ion is a highly attractive material for batteries because it has high reduction potential, i.e., a tendency to acquire electrons (‐3.04 Volt versus a standard hydrogen electrode), and it is lightweight. Li-Ion batteries are typically characterized as power devices capable of short durations (approximately 15 minutes to 1 hour) or stacked to form longer durations (but increasing costs). Rechargeable Li‐ion batteries are commonly found in consumer electronic products, such as cell phones and laptops, and are the standard battery found in electric vehicles. In recent years this technology has developed and expanded its portfolio of applications considerably into utility-scale applications. Today, Li-Ion batteries have been implemented for applications relating to ancillary services in grid connected storage. Because of its characteristics, Li-Ion technology is well suited for fast-response applications like frequency regulation, frequency response, and short-term (30-minutes or less) spinning reserve applications. Li-Ion batteries do carry some safety and environmental risk. Toxic or reactive gases may be released both during creation of the battery cells, as well as in case of thermal runaway within an operating system. However, this risk is being managed across the industry. During cell manufacture, effluent gases can be scrubbed and captured, to be disposed of safely. Once fully constructed, Li-Ion battery systems come with various methods of cooling, not only to help prevent thermal runaway but also to provide the most beneficial operating temperatures for the battery cells. This risk is being managed from a broader perspective, too; local authorities are preparing to appropriately address any fire concerns. The New York Fire Department (FDNY) and their stakeholders in the National Fire Protection Association (NFPA) have worked with DNV GL to develop ventilation, extinguishing, and cooling requirements for battery fires. Similar types of precautions have been taken industry-wide, in coordination with local communities. Figure 1 provides a schematic showing what is entailed in a general Li-Ion battery system. This includes monitoring, control, and management systems, power converter/inverter, and the batteries themselves. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 3 www.dnvgl.com Figure 1 General Schematic and Components of a Cell-Based Battery Energy Storage System Li-ion technology varies between chemistries. This report will focus on three of the most prominent and promising chemistries, Lithium Nickel Manganese Cobalt Oxide (LiNiMnCoO2 or NCM), Lithium Iron Phosphate (LiFePO4), and Lithium Titanate (Li4Ti5O12 or LTO), and compare and contrast their attributes. NCM is one of the most commonly used chemistries in grid-scale energy systems. This technology demonstrates balanced performance characteristics in terms of energy, power, cycle life, and cost. NCM chemistry is very common due to these features – it provides an engineering compromise. LiFePO4, on the other hand, can be purchased at a low cost for a high power density, and its chemistry is considered one of the safest available within Li-Ion batteries. Further, due to its very constant discharge voltage, the cell can deliver essentially full power to 100% DOD. However, LiFePO4 batteries are typically applicable to a more limited set of applications due to its low energy capacity and elevated self-discharge levels. Finally, LTO offers a stable Li-Ion chemistry, one of the highest cycle lifetimes reported, and a high power density. Further, it is the fastest charging Li-Ion chemistry of those reviewed here. However, in balance, it has a much lower energy density and much higher average cost. These systems are manufactured widely, but there is relatively high turn-over in manufacturers. Some of the more prominent or market-tested systems are included below, in Table 1. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 4 www.dnvgl.com Table 1 Li-Ion Battery Manufacturers Technology Manufacturer Cell or System Product NCM Enerdel Hitachi LeClanche LG Chem Panasonic PBES Samsung XALT Graphite/NMC JH2 NCR18650A 25R 31,40, 53, 75Ah HE; 31, 40, 63, 75Ah HP; 31, 37Ah UHP 4 BYD K2 Energy Microvast Saft Sony Thundersky APR18650 LFP123A VL10Fe, VL25Fe IJ1001M WB-LYP, TS-LYP LaClanche Microvast Toshiba LTO LpTO (Gen 1) SCiB 2.9, 20, 23Ah 2.2 Sodium Sulfur Batteries Sodium-sulfur (NaS) batteries are a type of molten-salt battery. The systems have high energy density, fast response times, and long cycle lives. They also have some of the longest durations available on the market. The inclusion of the term “molten” alludes to the battery operating temperature. NaS batteries store electricity through a chemical reaction which operates at 300 °C or above. At lower temperatures the chemicals become solid and reactions cannot occur. The high operating temperature makes the NaS batteries suitable for larger applications supporting the electric grid, but not personal electronic devices or vehicles. Further, due to the high temperature and natural reactivity of pure Sodium when exposed to water, the system can present a safety hazard if damaged. Figure 1 above provides a schematic showing what is entailed in a general NaS battery system, which is parallel in its architecture to Li-Ion systems. This includes monitoring, control, and management systems, power converter/inverter, and the batteries themselves. NaS batteries are a mature technology, and the system cost has generally leveled off. Although manufactured by more than one company, the market-share, and thus proven performance, of the company listed in Table 2 represents the majority of installations. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 5 www.dnvgl.com Table 2 NaS Battery Manufacturers Technology Manufacturer Cell or System Product Description NaS NGK NAS 2.3 Vanadium Redox Batteries Vanadium Redox batteries (VRB), or Vanadium flow batteries, are based on the redox reaction between the two electrolytes in the system. “Redox” is the abbreviation for “reduction-oxidation” reaction. These reactions include all chemical processes in which atoms have their oxidation number changed. In a redox flow cell, the two electrolytes are separated by a semi-permeable membrane. This membrane permits ion flow but prevents mixing of the liquids. Electrical contact is made through inert conductors in the liquids. As the ions flow across the membrane, an electrical current is induced in the conductors to charge the battery. This process is reversed during the discharge cycle. Figure 2 below provides a schematic showing what is entailed in a general VRB system. This includes monitoring, control, and management systems, power converter/inverter, and the electrolyte tanks and stack of the batteries themselves. Figure 2 General Schematic and Components of a Redox Flow Battery Energy Storage System DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 6 www.dnvgl.com In VRBs, the liquid electrolyte used for charge-discharge reactions is stored externally and pumped through the cell. This allows the energy capacity of the battery to be increased at a low cost. Energy and power are decoupled since energy content depends on the amount of electrolyte stored. VRB systems are unique in that they use one common electrolyte, which provides opportunities for increased cycle life. These large, liquid solution containers do however limit the VRB to stationary storage applications. An important advantage of VRB technology is that it can be “stopped” without any concern about maintaining a minimum operating temperature or state of charge. This is a key point to most flow batteries in that the batteries can actually be “turned off.” This technology can be left uncharged essentially indefinitely without significant capacity degradation. These systems are relatively new to the battery industry but are solidifying their place in the market. Some of the more prominent or market-tested systems are included below, in Table 3. Table 3 VRB Manufacturers Technology Manufacturer Cell or System Product Description VRB American Vanadium Imergy UET/UniEnergy ESP5, 50, 250 UniSystem, ReFlex 2.4 Zinc Redox Batteries The Zinc Bromine (ZnBr) battery utilizes similar flow battery technology as the previously discussed VRB. Due to this, it shares many of the same advantages: little to no claimed degradation over time (both in use and in the fully-discharged state), high energy density, 100% DOD, and easily scalable. The ZnBr consists of a zinc-negative electrode and a bromine-positive electrode, separated by a micro-porous separation. Solutions of zinc and a bromine complex compound are circulated through the two compartments. In a ZnBr the electrodes (Zn- and Br+) serve as substrates for the reaction. During charging, the Zinc is electroplated at the anode and bromine is evolved at the cathode. When not cycled, there is a potential for the Zinc to form dendrites that can degrade capacity or damage the battery components. To prevent this, the battery must be regularly and fully discharged. Figure 2 above provides a schematic showing what is entailed in a general ZnBr system, which is of similar physical structure to VRB, though differing completely in chemistry at the core of energy storage. This includes monitoring, control, and management systems, power converter/inverter, and the electrolyte tanks and stack of the batteries themselves. The response time for this technology is thought to be inadequate for fast-response applications; this should be verified on a case by case basis as new system designs may be able to improve on this limitation. ZnBr is a promising technology for balancing low-frequency power generation and consumption. However, cycle life tends to be less than that of VRBs. These systems are in the early stages of commercialization but are being produced by multiple manufacturers. Some of the more prominent or market-tested systems are included below, in Table 4. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 7 www.dnvgl.com Table 4 ZnBr Battery Manufacturers Technology Manufacturer Cell or System Product Description ZnBr Enphase (Previously ZBB) Primus Power Flow EnergyCell 2.5 Zinc Hybrid Cathode Batteries Zinc hybrid cathode (Zinc-air) batteries are a type of metal-air battery which uses an electropositive metal in an electrochemical couple with oxygen from the air to generate electricity. Zinc-air batteries take oxygen from the surrounding air to generate current. The oxygen serves as an electrode while the battery construction includes an electrolyte and a zinc electrode that channels air inside the battery. Zinc-air batteries have power densities similar to Li-ion batteries, but lower energy density. On the other hand, Zinc-air batteries in comparison to flow batteries can have both higher power and energy densities. Unlike Li-Ion, however, Zinc-air batteries are generally claimed to be benign, though their electrolytes – like those of other battery technologies – contain acidic or alkaline compounds and could produce SO2 if burned. The main Zinc-air battery material, zinc-oxide, is theoretically fully recyclable, though this has yet to be demonstrated at scale. In addition, the metals used or proposed in most metal-air designs are low cost. Zinc-air systems appear attractive for utility applications if their ability to charge and recharge can be improved. The challenge for researchers has been to devise a method where the air electrolyte is not deactivated in the recharging cycle to the point where the oxidation reaction is slowed or stopped. The cessation of the oxidation reaction reduces the number of times that a Zinc-air battery can be recharged. Some of the newest emerging technology, as created by Eos, claims to have addressed these issues by implementing a near-neutral, non-dendritic, and self-healing electrolyte solutions. This, Eos claims, prevents air electrode clogging, rupture of the membrane due to dendrites, and the drying out of the electrolyte, along with other innovations that have prepared the system for commercial launch. Potential applications include integrating renewable assets, peak shifting and load balancing, and frequency regulation. Consolidated Edison (ConEd) is currently pursuing one of the first utility-scale systems for demonstration with Eos technology. These systems are in the early stages of commercialization and, as such, manufacturing is limited. Although being researched by more than one company, the earliest product being actively used in demonstration projects is produced by the manufacturer listed in Table 5. Table 5 Zinc-Hybrid Cathode Battery Manufacturer Technology Manufacturer Product name (if available) Zinc-air Eos Znyth cell in Aurora 1000, 4000 DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 8 www.dnvgl.com 2.6 Commercialization Data Commercialization and installation data are based on DNV GL’s research and publicly available information. This data excludes projects that have been decommissioned for any reason, or construction has not yet started. Table 6 Installation and Commercialization Data System Attributes Li-Ion NCM Li-Ion LiFePO4 Li-Ion LTO NaS VRB ZnBr Zinc-air1 Typical project size (kW)2 6,500 5,000 2,000 6,000 4,000 1,000 3,500 Typical project size (kWh) 15,000 3,100 1,300 40,000 14,000 2,000 13,000 Largest project size installed (kW)3 30,000 31,500 40,000 50,000 15,000 1,000 250 Largest project size installed (kWh) 60,000 12,000 40,000 300,000 60,000 2,000 1,000 Current total power capacity installed (MW)4 77 142 31 186 66 5 0.25 Current total energy capacity installed (MWh) 30 220 19 1,254 226 25 1 1 Zinc-air is an emerging technology. Due to this, the majority of the projects DNV GL cited are publicly announced but not yet installed and operational. This clarification is provided to give context to the typical system size being larger than the largest installed system size. 2 Typical project size, both kW and kWh, are based on averages of publicly known projects that are operational, under construction, contracted, and announced. Decommissioned projects have been excluded from these counts. 3 Largest project size, both kW and kWh, is based on projects that are currently operational, under construction, or contracted. Announced and decommissioned projects have been excluded from these counts. 4 Current total power and energy capacity installed are based on publicly known projects that are operational, under construction, or contracted. Announced and decommissioned projects have been excluded from these counts. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 9 www.dnvgl.com 3 PERFORMANCE CHARACTERISTICS This chapter of the report provides a summary of technical parameters for each of the proposed storage technologies in a number of requested fields identified by PacifiCorp as useful for consideration within their 2017 IRP. The specific technology parameters of interest, as identified by PacifiCorp, are as follows: 1. Power Capacity 2. Energy Capacity 3. Recharge Rates 4. Roundtrip Efficiency 5. Availability 6. Degradation 7. Expected Life 8. Environmental Impact upon disposal Each of the specified parameters are first defined and discussed below followed by a summary of values for each technology. Further, these characteristics are utilized later in this report, in Chapter 5, in determining the appropriateness of a technology for a particular application. 3.1 Power Capability In composing this analysis, a variety of values were available given DNV GL’s experience in the field, depending on operating conditions as well as marketing versus as-built specs. In all cases, all technologies in the study were available down to at least the 1 MW power capacity level, with many having wide use at smaller sizes, for commercial and industrial, residential or non-stationary storage applications. The maximum values were based on the largest installed or proposed and contracted systems to date. The minimum size of 1 MW was based on feedback from PacifiCorp based on their IRP planning needs. DNV GL notes that all of these technologies are available in sizes smaller than 1 MW and can be installed as customer-sited, behind-the-meter resources. Storage is emerging as a technology being considered to provide utility services from aggregated behind-the-meter resources. Most notably, in 2014 Southern California Edison awarded two (2) capacity contracts to aggregated behind-the-meter energy storage. 3.2 Energy Capacity The energy capacity DNV GL has compiled is what has been quoted by manufacturing specs as the optimal charge pattern of the entire capacity of the battery as designed. However, in many cases, these units are sold and marketed at a capacity reduced from the system’s true total capacity. As such, useable or nameplate system capacity values are provided specified so that the system operates at a usable 0-100% SOC range. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 10 www.dnvgl.com 3.3 Recharge Rates All batteries have certain tolerances with regard to the rate at which they are charged or discharged. The current rating determines the C-rate for the battery, i.e., the rate at which a battery is discharged relative to its maximum energy capacity. Some batteries are more tolerant than others to high discharge rates. On the manufacturer specification sheets that accompany batteries, C-rates that are less than 1 are typically conservative, and may be recommended by the manufacturer to attain longer cycle lifetimes. Typically, discharge rates are higher than charge rates. 3.4 Round Trip Efficiency Efficiency data provided in this report is the full energy storage system round trip efficiency (RTE). Full system RTE includes the losses from the power conversion system, HVAC equipment loads, control system losses, and self-consumption. Often a manufacturer will provide battery efficiency rather than RTE when promoting their technology. However, there can be a 5-10% difference between these efficiency ratings, when conversion equipment, air conditioning, and other “parasitic” balance of plant devices from the full system are taken into consideration. Auxiliary losses like air conditioning or heating vary considerably according to the technology and the specific application it must perform. For example, the heating requirement for a NaS battery is about 3 percent of its rating but heating is not needed if the battery is discharged daily because heat released during discharge will keep it warm. In this case, typically RTE values are reported based on the system performed a minimum amount of cycling per day. 3.5 Availability The availability that DNV GL notes is based on guarantees being offered by manufacturers and distributors. Aside from these availability guarantees, annual planned maintenance carve-outs are typically included which do not contribute to these availability figures. Data here is provided based on currently observed guarantees being offered along with utility-scale energy storage systems, however, it should be noted that longer term operation experience will be required before these values are fully verified in practice. 3.6 Degradation Storage is a unique technology in that its performance characteristics are significantly influenced by degradation. Degradation is highly dependent on system operation. System operation is in turn affected by location, power and energy capacity, applications, and how frequently those applications are utilized. Typically, manufacturer packaging, control and management systems, and environmental considerations are in place to ensure these parameters stay within safe and non-destructive ranges. However, outside influences and one-time events resulting from environmental control failure, BMS failures, or dispatch control error can lead to significant degradation of the device. The degradation ranges that DNV GL has provided are given at year 10 after installation, based upon the average system operation, segmented by application type. The most common energy applications include electric time shift, electric supply capacity, spinning and non-spinning reserves, and T&D congestion relief. The Power applications include regulations, voltage support, load following and ramping support, and frequency response. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 11 www.dnvgl.com As noted previously, battery performance deteriorates as a result of various degradation mechanisms. The complexity and interactions of these mechanisms are given in detail below. • Temperature: All batteries have an ideal temperature operating range; most batteries control their operation to 30oC or less. High temperatures (generally above 30-40oC) tend to degrade capacity severely. Many battery chemistries will indicate operational temperature ranges between 0-60oC, however operation at or near these limits can severely impact efficiency of the cell as well as lifetime. • Charge and Discharge Rates: For many batteries, high charge/discharge rates lead to higher temperature, compounding the degradation effect. • High or Low Average State of Charge: If a battery spends a significant amount of time at a high state of charge, it will degrade faster than if it is left and maintained at a mid-level state of charge. Some batteries are more sensitive to this than others, but generally it is known that the higher the average state of charge (SOC) over the battery life, the faster it will degrade. Similarly, if a battery is kept at very low average SOC, it will also degrade quickly. This phenomenon has been studied extensively and it has been shown that battery capacity and average SOC are inversely proportional. • Depth of Discharge: Generally, the greater the average depth of discharge (DOD), the faster the battery capacity will fade. In most cases, battery spec sheets will list the lifetime of the battery as number of cycles until 80% of capacity is reached at 100% DOD at 25 C. These conditions are considered nominal and if cycle life of the battery is mentioned without these additional specifications, it is important to verify the DOD, final capacity, and temperature of the tests. Unfortunately, these conditions are often unlike what the battery may experience in an actual application. It is often not noted whether long rest times between charge and discharge were implemented (allowing the battery to cool). Longer rest times can inflate the total cycle life. • Calendar Life: The calendar life of the battery can affect its capacity as much or more than the cycling effects, but it is largely dependent on temperature. Assessing the time the battery is left at rest as a function of temperature is relevant to assessing its state of health. For this reason, most state of health predictions includes both calendar and cycling components. • Maintenance: It is assumed that batteries will not operate completely autonomously. This Maintenance ensures unit operate optimally, given product specific operating constraints. Some manufacturers will further offer capacity maintenance agreements wherein systems are provided with maintenance, supplemental units integrated into the system, or refreshed electrolyte solutions in order to ensure capacity does not degrade past agreed to trigger points. • Compounding and Consequential Effects: It is not possible to list the degradation factors from greatest to least without caveat considerations for specific chemistries, environment and duty cycle, but within the conservative limits established on a battery specification sheet, it may generally be assumed that abuse factors from least to greatest are: Temperature > Depth of Discharge > C- Rates . All of these factors are linked, however, and therefore have compounding effects depending on the battery duty cycle. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 12 www.dnvgl.com 3.7 Expected Life Most systems have not been available at a commercially mature stage for long enough to provide meaningful field data on lifetime performance, so the expected life is currently based on vendor projections, accelerated life-testing (ALT) on cells or modules and limited field results. Cell life tests are typically a good representation of the maximum possible lifetime under ideal conditions, and validation of these results is recommended on a case-by-case basis. With these caveats in mind, the expected life based on standardized cycling and disregarding extenuating circumstances is at least 10 years in all cases. Many manufacturers claim longer calendar lives; these claims assume periodic maintenance, including integrating new modules or adding new electrolyte. The number of cycles that these claims cover varies from technology to technology, based on the applications expected for use. As with calendar life claims, vendors typically claim cycle life in excess of 3,000 cycles. These claims are tied to the same periodic maintenance as previously mentioned. Further, all of the mechanisms discussed above that cause degradation are related to expected life and the system’s ability to continue to meet the needs of the customer. 3.8 Environmental Effect Upon Disposal While batteries claim advantages over traditional energy sources, including the ability to provide energy and power essentially instantaneously and without emission, the components will eventually require disposal. Disposal or recycling, however, comes with consequences. The United States Environmental Protection Agency states that no rechargeable electrochemical cells may lawfully be disposed of to be taken to a landfill. Li-ion and nickel-based electrochemical cells are classified as toxic due to the presence of lead, as well as cobalt, copper, nickel, chromium, thorium, and silver. The majority of energy storage technologies covered in this report have yet to see adoption rates, much less decommissioning rates, high enough that significant research has been conducted on opportunities and limitations to recycling. While the US Department of Energy has pursued research on the subject, even producing functional Li-Ion cells from recycled materials, the process is so far limited to small pilot operations. For this reason, when decommissioning, disposing of, or pursuing potential recycling of batteries, the manufacturer of the energy storage system should be consulted for guidance. As energy storage systems are deployed in greater numbers, decommissioning and recycling are rising as important facets to financing agreements, contributing to the total cost of ownership. Lead-acid battery repurposing and recycling activities are a well-established and extremely successful system. The policy has not addressed lithium and nickel-based battery recycling the same way it has lead- acid, and this is due to a number of challenges. The construction materials used in these systems are similar to the advanced technologies covered in this report (alloy and mild steel, aluminum alloys, copper, titanium, HPDE, etc.) and thus the majority of the challenge faced has to do with disassembly, destruction, sorting and any potential contamination. These batteries are mechanically varied between manufacturers and technologies, and packs are very sophisticated relative to lead-acid. In addition, there is a much larger range of materials in each battery, as well as a wide range of chemistries between batteries. Mined Lithium itself is low cost so although recycling is feasible, at present it is not economical. Instead, the primary components of interest are nickel and cobalt (and copper), and not all Li-ion batteries contain them in sufficient quantities. In many cases, the metals involved may just be sent to slag, to be burned for process heat (with the appropriate emission scrubbing). Materials can be recovered from this slag, but they must be DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 13 www.dnvgl.com in high enough quantity, quality, and demand to merit the additional effort. NCM batteries, for instance, contain a high enough percentage of valuable constituents (nickel and cobalt) to be recyclable. Beyond the potential for emissions from burning slag, the chemicals have additional properties that affect disposal options. A universal issue for Li-Ion battery recycling is Lithium’s high reactivity, creating a risk of fire if handled incorrectly. Otherwise, DNV GL’s own research indicates that the materials within Li-Ion batteries are individually not exotic – for instance, Iron Phosphate is used as a non-toxic pesticide – but their destruction or combustion can create flammable gases such as ethylene, methane, and carbon monoxide. Toxic gases are also created, such as hydrogen fluoride, hydrogen chloride, and hydrogen cyanide. It should be noted that all of these gases are also created during the burning of plastics. To provide perspective as to Li-Ion battery toxicity, on a mass and volume equivalence, plastics are equally or more toxic than the by-products of Li-ion battery combustion. As to redox flow batteries, electrolytes such as Zinc bromide and Vanadium solutions can typically be reused, sometimes for the life of the battery. However, contaminants or impurities may occur, requiring monitoring and removal. Additionally, upon decommissioning, the Vanadium and Zinc from these batteries may be recycled. It should be noted, however, that several materials commonly found in redox flow batteries are environmentally hazardous and regulated and thus should be disposed of according to regional government requirements. VRB electrolytes can dry or evaporate to form V2O5 dust as well as sulfate salts, while ZnBr electrolytes can evolve bromine at temperatures above 50oC. Finally, Zinc-air batteries, upon decommissioning, have similar overall construction materials that can be recycled via standard processes. Further, the aqueous electrolyte is non-flammable and non-hazardous (both non-toxic to humans and the environment). This electrolyte solution contains salts that are mildly corrosive but are not uniquely different or more hazardous than competing chemistries. The main component of Zinc-air batteries is Zinc-oxide, which is theoretically fully recyclable, although this has not yet been demonstrated on a large scale. Properties of potential byproducts of battery decomposition are shown in Table 7. Table 7 Combustion Byproducts of Commercially Available Batteries Chemical Formula LEL (Lower Explosion Limit) IDLH (Immediately Dangerous to Life and Health) Solubility in Water (mg/L) Autoignition Temp (degC) Thermal Instability Threshold (deg C) NFPA Flammability NFPA Health NFPA Reactivity Ref. Methane CH4 50,000 5,000 22.7 537 -4 1 0 NJ DOH Carbon Monoxide CO 12,500 1,500 27.6 609 -4 2 0 CDC.gov Ethylene C2H4 27,000 -2.9 490 -4 2 2 Matheson MSDS H2S H2S 4,000 300 4,000.0 260 -4 4 0 CDC.gov Hydrogen Fluoride HF -30 miscible -0 4 0 CDC.gov Hydrogen Chloride HCl -100 720.0 -1500 0 3 1 CDC.gov Hydrogen Cyanide HCN -50 miscible -4 4 2 CDC.gov V2O5 Dust V2O5 -35 mg/m^3 0.8 -0 3 0 CDC.gov Pb Vapor, salts, dust Pb -700 mg/m^3 10^-5 to 4400 -0 2 0 CDC.gov SO2 SO2 -100 94,000.0 -0 3 0 CDC.gov Concentration (ppm unless otherwise noted) DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 14 www.dnvgl.com 3.9 Technical Parameters Data System parameters and characteristics are based on DNV GL’s industry experience, internal research, and publicly available data. They are subject to the assumptions detailed in the previous sections. Table 8 Technical Parameters and Performance Characteristics Data, from Both Cell and Project-Scale Perspectives Parameter/ Technology Li-Ion NCM Li-Ion LiFePO4 Li-Ion LTO NaS VRB ZnBr Zinc-air Power capability Available down to 1 MW1 Yes Yes Yes Yes Yes Yes Yes Maximum2 (MW) 35 35 40 50 20 20 15 Energy capacity3 SOC upper limit 90% 85% 98% 90% 95% 98% 98% SOC lower limit Recharge rates 1C 2C-1C 3C-1C 1C-0.5C 1C-0.25C 1C-0.25C 2C-1C Round trip efficiency 77 - 85% 78 - 83% 77 - 85% 77 - 83% 65 - 78% 65 - 80% 72 - 75% Availability 97% 97% 96% 95% 95% 95% 96% Carve Outs 72 hr/yr 72 hr/yr 72 hr/yr 72 hr/yr 1 wk/yr 1 wk/yr 72 hr/yr Energy Capacity Degradation4 Energy Applications 30-40% 20-40% 15-25% 15-30% 5-10% 5-10% 15-25% Power Applications Expected life5 Years 10 10 10 15 10 10 10 Cycles Environmental effect upon disposal?6 Yes Yes Yes Yes Yes Yes Yes 1 The minimum size of 1 MW was based on feedback from PacifiCorp based on their IRP planning needs. DNV GL notes that all of these technologies are available in sizes smaller than 1 MW and can be installed as customer-sited, behind-the-meter resources. 2 Maximum power capability based on largest publicly proposed project. 3 For usable energy capacity, manufacturers will commonly advertise their battery as allowing 100% DOD based on nameplate capacity. SOC limits given here reflect limits with respect to actual installed energy capacity. 4 Degradation value based on percent of installed nameplate capacity lost after 10 years of operation. These values assume maintenance is performed as a part of normal operation. Flow battery degradation (VRB and ZnBr) can be mitigated to an extant through normal maintenance and chemistry refresh. 5 Expected life in calendar years is given for the energy storage component of an ESS and is based on operation at 100% DOD, 25°C, 1C for the number of cycles shown. These values assume maintenance is performed as a part of normal operation. Full system life, including PCS and balance of plant equipment have been observed in range of 15-25 years, implying full replacement of energy storage system components. 6 Discussion of the severity and risk of these effects are discussed in detail in section 3.8. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 15 www.dnvgl.com 4 COST ESTIMATES AND TRENDS In addition to the commercial and technical review, PacifiCorp requested DNV GL utilize industry experience, in-house data, and market research to the prepare capital and O&M cost estimates for each technology, expressed in mid-2016 dollars. Costs estimates are broken down as follow: 1. Energy Storage Equipment 2. Power Conversion Equipment 3. Power Control System 4. Balance of System 5. Installation 6. Fixed Operation and Maintenance Each of these costs components are provided as a range covering currently observed industry estimates. In addition to current cost estimates, cost trends over 10 years will be provided as graphs demonstrating a breakdown of system costs in the requested components. The capital cost for an installed energy storage system is calculated for a system by adding the costs of the energy storage equipment, power conversion equipment, power control system, balance of system, and the installation costs. Each of these categories is accounted for separately because they provide different functions or cost components and are priced based on different system ratings. System component costs based on the power capacity ratings are priced in $/kW, while component costs based on the energy capacity ratings, such as the DC energy storage system, are priced in $/kWh. A description of the system and project development elements included in each cost component is provided below, followed by a summary table of all system costs and graphs depicting 10-year cost trends of relevant components. 4.1 Energy Storage Equipment Costs Energy storage equipment costs are inclusive of the DC battery system which includes the costs of the energy storage medium, such as Li-Ion battery cells or flow battery electrolyte, along with associated costs of assembling these components into a DC battery system. For Li-Ion systems, battery cells are arranged and connected into strings, modules, and packs which are then packaged into a DC system meeting the required power and energy specifications of the project. The DC system will include internal wiring, temperature and voltage monitoring equipment, and an associated battery management system responsible for managing low-level safety and performance of the DC battery system. For flow batteries, the DC system costs include electrolyte storage tanks, membrane power stacks and container costs for the system along with associated cycling pumps and battery management controls. Energy storage equipment costs are provided on a $/kWh basis which is most appropriate for quantifying the cost of an energy capacity constrained resource. The DC system cost trends are shown in Figure 3. 4.2 Power Conversion System Equipment Costs Power conversion system (PCS) costs are inclusive of the cost of the inverter, packaging, container, and controls. Inverters employed in energy storage systems are more expensive than the grid-tied inverters widely deployed for solar PV generation, and differentiated by their bi-directional, 4-quadrant operational DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 16 www.dnvgl.com capabilities. The cost of the power conversion equipment is proportional to the power rating of the system and provided in $/kW. The PCS cost trends are shown in Figure 4. 4.3 Power Control System Costs Unique to energy storage systems are the required high-level controllers being deployed to dispatch and operate the systems. With dispatch becoming an ever more important part of storage system design, controllers have to combine multiple functions – from forecasting the load, to understanding the tariff structure and factoring in the type of charge management required for a specific application and technology. The energy industry is currently seeing a number of software companies emerging which are focused solely on control and management of energy storage systems. This includes companies such as Geli, Greensmith, 1Energy Systems, and Intelligent Generation. System integrators and battery storage vendors themselves are also producing controls to operate their systems. These companies include storage and renewable energy companies such as Stem, Advanced Microgrid Systems, RES Americas and SolarCity, as well as established utility energy industry players such as General Electric, Schneider Electric, and ABB. For systems owned or operated by a utility, these controllers must additionally be integrated with utility monitoring and control systems such as Supervisory Control and Data Acquisition Systems (SCADA), Energy Management Systems (EMS), and Distribution Management Systems (DMS), among others. As more advanced applications are considered, such as the energy storage Virtual Power Plants (VPP) currently being considered at Duke Energy and Consolidated Edison, these control layers will become increasingly critical to the success of a given project. At present, the costs for the power control systems have been observed to vary widely and are provided here based on the power capacity of a plant as $/kW. The trend graphs show conservative reduction in costs over ten years; as controls grow more prevalent and efficiencies are found, the control requirements and designs will likely increase in intricacy. The controls cost trends are shown in Figure 5. 4.4 Balance of System The equipment cost of the storage system will further depend on ancillary equipment necessary for the full storage system interconnection. The balance of system cost here includes wiring, interconnecting transformer, and additional ancillary equipment. For some technologies, this may include the cost of centralized HVAC systems which is required for maintaining acceptable environmental equipment. The balance of system cost is proportional to the power rating of the system and provided in $/kW. The balance of system cost trends are shown in Figure 6. 4.5 Installation Installation cost accounts for associated Engineer-Procure-Construct (EPC) costs inclusive of installation parts and labor, permitting, site design, and procurement and transportation of all equipment. 4.6 Fixed O&M Yearly operation and maintenance costs is currently a debated issue for storage projects employing the technologies discussed in this report, as the industry does not yet have longer term operating experience DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 17 www.dnvgl.com with the technologies. O&M requirements for Li-Ion systems are generally assumed to be light and include maintenance of HVAC system, tightening of mechanical and electrical connections, cabinet touch up painting and cleaning, and landscaping maintenance. Further, the majority of projects being developed for utilities applications include some type of capacity maintenance agreement. This capacity maintenance agreement guarantees some fixed level of available energy capacity in the system over the term of the project. The cost of the capacity maintenance agreement can be accounted for in the Fixed O&M or as part of the upfront capital costs of the system. For flow battery systems, maintenance services include power stack and pump replacements, tightening of plumbing fixtures, tightening of mechanical and electrical connections, as well as semi-annual chemistry refresh and full discharge cycles to refresh capacity. Further, while many technologies are developing third party training and qualification programs for O&M services, at present many of vendors technology companies themselves are providing O&M services. Variable O&M costs, while typical to conventional generation sources, are generally assumed negligible for most energy storage systems. It is noted that systems operators can use a variable O&M cost as one means of including the capacity degradation within an energy storage dispatch model. However, there is not currently a uniform or industry acceptable methodology for quantifying variable O&M in this manner. For the purposes of this report, energy storage variable O&M is considered to be negligible. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 18 www.dnvgl.com 4.7 Total System Cost Estimates System costs are based on DNV GL’s industry experience, internal research, and publicly available data. These costs are provided in 2016 dollars. This information is given in further context in Section 4.9, which provides calculations for an example installation. Table 9 Energy storage system cost estimates1 1 All cost estimates provided in mid-2016 dollars 2 Energy storage equipment includes the full DC battery system which includes the costs of the energy storage medium, such as Li-Ion battery cells or flow battery electrolyte, internal wiring and connections, packaging and containers, and battery management system (BMS). 3 PCS equipment includes the inverter, packaging, container and inverter controls. 4 Control system includes supervisory control software, along with the controller and communications hardware required to dispatch and operate energy storage systems. 5 Balance of system includes site wiring, interconnecting transformer, and additional ancillary equipment. 6 Installation includes Engineer-Procure-Construct (EPC) costs inclusive of installation parts and labor, permitting, site design, procurement and transportation of equipment. 7 Fixed O&M costs are provided as real levelized dollars with assumed 20 year project life. Cost Parameter/ Technology Li-Ion NCM Li-Ion LiFePO4 Li-Ion LTO NaS VRB ZnBr Zinc-air Energy storage equipment cost ($/kWh)2 $325-$450 $350-$525 $500-$850 $800-$1000 $500-$700 $525-$725 $200-$400 Power conversion system equipment cost ($/kW)3 $350-$500 $350-$500 $350-$500 $500-$750 $500-$750 $500-$750 $350-$500 Power control system cost ($/kW)4 $80-$120 $80-$120 $80-$120 $80-$120 $100-$140 $100-$140 $100-$140 Balance of system ($/kW)5 $80-$100 $80-$100 $80-$100 $100-$125 $100-$125 $100-$125 $80-$100 Installation ($/kWh)6 $120-$180 $120-$180 $120-$180 $140-$200 $140-$200 $140-$200 $120-$180 Fixed O&M cost ($/kW yr)7 $6-$11 $6-$11 $6-$11 $7-$12 $7-$12 $7-$12 $6 - $12 DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 19 www.dnvgl.com 4.8 Example Installed Cost Calculation Table 10 below shows an example calculation to estimate the installed cost of 10 MW, 20 MWh NCM Li-Ion energy storage system using the cost estimates provided in Table 9. The provided cost estimates result in a low side estimate of $14,000,000 and a high side estimate of $19,800,000 for the system, with component sub-total costs based on the power or energy rating of the system. Table 10 Example Installed Capital Cost Calculation for 10 MW, 20 MWh NCM Li-Ion Energy Storage System Cost Parameter ESS Size Component Unit Cost Low Component Unit Cost High Component Sub-Total Low Component Sub-Total High Energy storage equipment cost ($/kWh) 20,000 kWh $325/kWh $450/kWh $6,500,000 $9,000,000 Power conversion equipment cost ($/kW) 10,000 kW $350/kW $500/kW $3,500,000 $5,000,000 Power control system cost ($/kW) 10,000 kW $80/kW $120/kW $800,000 $1,200,000 Balance of system ($/kW) 10,000 kW $80/kW $100/kW $800,000 $1,000,000 Installation ($/kWh) 20,000 kWh $120/kWh $180/kWh $2,400,000 $3,600,000 Low Total High Total $14,000,000 $19,800,000 Average DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 20 www.dnvgl.com 4.9 System 10-Year Cost Trends As referenced in sections 4.1 to 4.4, graphs depicting 10-year future cost trends are shown below. Cost trends are based on currently available industry projections, as well as DNV GL’s interaction with industry partners, and basic cost reduction assumptions, as well as the information discussed in the relevant section, 4.1 through 4.4. These trends are provided for the period from 2016 to 2026. Figure 3 Projected Energy Storage Equipment Cost Trends for Various Technologies, From 2016 to 2026 $- $100 $200 $300 $400 $500 $600 $700 $800 $900 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 $/ k W h Year Energy Storage Equipment Cost Trends NCM LiFePO4 LTO NaS VRB ZnBr Zinc-air DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 21 www.dnvgl.com PCS cost trends are shown in Figure 4. The PCS cost trends mirror each other across two technology groupings. The PCS costs for all Li-ion and Zinc-air technologies are expected to follow similar trends as they are pulling from the same manufacturers utilizing more mature PCS architectures. PCS costs for flow batteries, while currently offered at a higher price point, are expected to converge to similar costs as the Li-ion over time as these technologies mature and gain additional commercial adoption. While NAS is a more mature technology, current PCS costs are above those of Li-ion technologies with future cost reductions expected to benefit from increased adoption of flow battery PCS architectures. $- $100 $200 $300 $400 $500 $600 $700 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 $/ k W Year PCS Cost Trends Li-Ion, Zinc-air NaS, VRB, ZnBr DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 22 www.dnvgl.com Figure 4 Projected PCS Cost Trends for Various Technologies, From 2016 to 2026 Controls cost reductions, shown in Figure 5, are expected to be relatively uniform across all technologies. While competition in the space is expected to continue, the need for increasingly sophisticated controllers which interact with both utility and distributed behind-the-meter storage assets are expected to result in modest cost reductions over time, converging to a relatively uniform price across technologies. Figure 5 Projected Controls Cost Trends for Various Technologies, From 2016 to 2026 $- $20 $40 $60 $80 $100 $120 $140 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 $/ k W Year Controls Cost Trends Li-Ion, NaS VRB, ZnBr, Zinc-air DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 23 www.dnvgl.com Balance of system costs, shown in Figure 6, is expected to fall dramatically over the next 5 years with continued modest gains through 2026. Cost reductions are expected as project developers gain experience deploying these technologies and system interconnection requirements become more uniform for storage technologies. Li-ion technologies and Zinc-air follow similar trends due to similarities in construction and balance of plant requirements, while reductions for flow batteries and NaS systems are expected to follow similar patterns. Figure 6 Projected Balance of System Cost Trends for Various Technologies, From 2016 to 2026 $- $20 $40 $60 $80 $100 $120 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 $/ k W Year Balance of System Cost Trends NaS, VRB, ZnBr Li-Ion, Zinc-air DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 24 www.dnvgl.com 5 UTILITY APPLICATIONS AND VALUE STREAM In this chapter, an application-technology ranking is provided which is intended to indicate the applicability of each technology and their relative potential for generating economic value for at least one of eight (8) benefit cases within PacifiCorp’s service territory over the next 20 years. This assessment considers both the likelihood that a particular storage application is relevant to the current PacifiCorp market, as well as the appropriateness of a specific technology to serve the needs of that application. The eight applications identified by PacifiCorp for considerations are as follows: 1. Electric Energy Time Shift 2. Electric Supply Capacity 3. Regulation 4. Spinning, Non-Spinning, and Supplemental Reserves 5. Voltage Support 6. Load Following/Ramping Support for Renewables 7. Frequency Response 8. T&D Congestion Relief In this chapter, definitions of each application will be provided, followed by an overview of regulatory concerns specific to PacifiCorp territory providing an assessment of both planned regulatory initiatives and local network and market conditions in the PacifiCorp region. These will be reviewed specifically as they relate to energy storage potential. Finally, results of the assessment are provided indicating the applicability of each technology and the relative potential for generating economic value for at least one of the benefit cases within PacifiCorp’s service territory over the next 20 years. These rankings are provided on a 1 to 10 scale. At PacifiCorp’s request, this report additionally includes an assessment on applicability of each technology and the relative potential for generating economic value under an alternative market scenario with PacifiCorp operating under market rules similar to those implemented in California ISO (CAISO). 5.1 Considered Applications DNV GL reviewed applications for energy storage systems based on the regulations and standards in place in PacifiCorp territories, including the availability of financial resources to support energy storage development, as well as the general expansion of demand. Descriptions of these applications are provided below, based on the Department of Energy’s Energy Storage Handbook and DNV GL’s recommended practice guide, GRIDSTOR. • Electric energy time shift – Energy storage systems operating within an electrical energy time- shift application are charged with inexpensive electrical energy and discharged when prices for electricity are high. On a shorter timescale, energy storage systems can provide a similar time-shift duty by storing excess energy production from, for example, renewable energy sources with a variable energy production, as this might otherwise be curtailed. If the difference in energy prices is the main driver and energy is stored to compensate for (for example) diurnal energy consumption patterns, this application is often referred to as arbitrage. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 25 www.dnvgl.com Storing energy (i.e. in charge mode) at moments of peak power to prevent curtailment or overload is a form of peak shaving. Peak shaving can be applied for peak generation and also – in discharge mode – for peak demand (e.g. in cases of imminent overload). Peak shaving implicates that the energy charged or discharged is discharged or recharged, respectively, at a later stage. Therefore, peak shaving is a form of the energy time-shift application. An energy storage system used for energy time-shift could be located at or near the energy generation site or in other parts of the grid, including at or near loads. When the energy storage system used for time-shift is located at or near loads, the low-value charging power is transmitted during off-peak times. Important for an energy storage system operating in this application are the variable operating costs (non-energy related), the storage round-trip efficiency and the storage performance decline as it is being used (i.e. ageing effects). • Electric Supply Capacity - An energy storage system could be used to defer or reduce the need to buy new central station generation capacity and/or purchase capacity in the wholesale electricity market. In this application, the energy storage system supplies part of the peak capacity when the demand is high, thus relieving the generator by limiting the required capacity peak. Following a (partial) discharge, the energy storage system is recharged when the demand is lower. The power supply capacity application is a form of generation peak shaving, therefore a form of electrical energy time-shift. An energy storage system participating in the electrical capacity market may be subject to restrictions/requirements of this market, for example required availability during some periods. • Regulation - Regulation is used to reconcile momentary differences between demand and generation inside a control area or momentary deviations in interchange flows between control areas, caused by fluctuations in generation and loads. In other words, this is a power balancing application. Conventional power plants are often less suited for this application, where rapid changes in power output could incur significant wear and tear. Energy storage systems with a rapid-response characteristic are suitable for operation in a regulation application. Energy storage used in regulation applications should have access to and be able to respond to the area control error (ACE) signal (where applicable), which may require a response time of fewer than five seconds. Furthermore, energy storage used in regulation applications should be reliable with a high quality, stable (power) output characteristics. • Spinning, Non-spinning, and supplemental reserves - A certain reserve capacity is usually available when operating an electrical power system. This reserve capacity can be called upon in case some generation capacity becomes unavailable unexpectedly, thus ensuring system operation and availability. A subdivision can be made based on how quickly a reserve capacity is available: o Spinning reserve is reserve capacity connected and synchronized with the grid and can respond to compensate for generation or transmission outages. In remote grids spinning reserve is mainly present to cover for volatile consumption. In case a reserve is used to maintain system frequency, the reserve should be able to respond quickly. Spinning reserves are the first type of backup that is used when a power shortage occurs. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 26 www.dnvgl.com o Non-spinning reserve is connected but not synchronized with the grid and usually available within 10 minutes. Examples are offline generation capacity or a block of interruptible loads. o Supplemental reserve is available within one hour and is usually a backup for spinning and non-spinning reserves. Supplemental reserves are used after all spinning reserves are online. Stored energy reserves are usually charged energy backups that have to be available for discharge when required to ensure grid stability. An example of a spinning reserve is an uninterruptible power supply (UPS) system, which can provide nearly instantaneous power in the event of a power interruption or a protection from a sudden power surge. Large UPS systems can sometimes maintain a whole local grid in case of a power outage; this application is called island operation. • Voltage support - Grid operators are required to maintain the grid voltage within specified limits. This usually requires management of reactive power (but also active power, e.g. in the LV grid), therefore also referred to as Volt/VAr support. Voltage support is especially valuable during peak load hours when distribution lines and transformers are the most stressed. An application of an energy storage system could be to serve as a source or sink of the reactive power. These energy storage systems could be placed strategically at central or distributed locations. Voltage support typically is a local issue at low voltage (LV), medium voltage (MV) or high voltage (HV) level. The distributed placement of energy storage systems allows for voltage support near large loads within the grid. Voltage support can also be provided by operation of generators, loads, and other devices. A possible advantage of energy storage systems over these other systems is that energy storage systems are available to the grid even when not generating or demanding power. Note that no (or low) real power is required from an energy storage system operating within a voltage/VAr support application, so cycles per year are not applicable for this application and storage system size is indicated in MVAr rather than MW. The converter needs to be capable of operating at a non-unity power factor in order to source or sink reactive power. The nominal duration needed for voltage support is estimated to be 30 minutes, which allows the grid time to stabilize and/or begin orderly load shedding. • Load following / ramping support for renewables - Load following is one of the ancillary services required to operate a stable electricity grid. Energy storage systems used in load following applications are used to supply (discharge) or absorb (charge) power to compensate for load variations. Therefore, this is a power balancing application. In general, the load variations should stay within certain limits for the rate of change, or ramp rate. Therefore, this application is a form of ramp rate control. The same holds for generation variations, which is very applicable to renewable energy sources. Due to the intermittency of renewables production, having a storage device with several hour durations can provide a large advantage to renewable efficiencies, easing of grid impacts, and renewable production. Conventional power generation can also operate with a load following (or RES compensating) application. Within these applications, the benefits of energy storage systems over conventional power generation are that: o most systems can operate at partial load with relatively modest performance penalties o most systems can respond quickly with respect to a varying load DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 27 www.dnvgl.com o systems are suitable for both load following down (as the load decreases) and load following up (as the load increases) by either charging or discharging. Note that an energy storage system operating with a load-following or ramp rate control application within a market area needs to purchase (when charging) or sell (when discharging) energy at the going wholesale price. As such the energy storage efficiency is important when determining the value of the load following application. • Frequency response - Synthetic inertia behavior is the increase or decrease in power output proportional to the change of grid frequency; physical inertia is provided by conventional power generators, i.e. synchronous generators. If the total amount of physical inertia decreases in a power system, the amount of synthetic inertia should be increased to maintain a certain minimum amount of total inertia. Many grid-connected renewable energy sources do not provide additional synthetic inertia. Therefore, larger grid frequency deviations may occur as the total inertia in the power system decreases. Keeping track of the total system inertia could be a future task of ISOs. Some energy storage systems add synthetic inertia to the system and can thereby be used to compensate for fluctuations in the grid frequency. Causes of fluctuations could be the loss of a generation unit or a transmission line (causing a sudden power imbalance). Various generator response actions are needed to counteract a sudden frequency deviation, often within seconds. Energy storage within a frequency response application could support the grid operator and thereby assure a smoother transition from an upset period to normal operation. For a frequency response type of application, the energy storage is required to provide support within milliseconds. Storage helps to maintain the grid frequency and to comply with Control Performance Standards (CPSs) 1 and 2 of the North American Reliability Council (NERC). Aside from this quick response, the frequency response application is similar to load following and regulation, as described previously. • Transmission and distribution congestion relief – During moments of peak demand, it may occur that the available transmission lines do not provide enough capacity to deliver the least-cost energy to some or all of the connected loads. This transmission congestion may increase the energy cost. Energy storage systems at strategic positions within the electricity grid help to avoid congestion- related costs and charges. The energy storage system can be charged when there is no congestion and discharged when congestion occurs. Energy storage can, in this way, additionally delay and sometimes avoid the need to upgrade a transmission or distribution system. 5.2 PacifiCorp Territory Regulatory Concerns and Application Drivers Currently, the largest drivers of energy storage deployment nationally have been a direct result of state and federal level regulatory actions encouraging or mandating procurement and installation of energy storage technologies. Much of the regulatory action has come as follow-up initiatives to more aggressive renewable portfolio standards (RPS) with storage seen as an enabling technology which can mitigate issues associated with higher level of renewable penetration. To a lesser extent, regulatory action around energy security has additionally spurred some development opportunities for energy storage as a reliability resource. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 28 www.dnvgl.com Additionally, a small set of cost-effective applications in select markets, such as frequency regulation, supply capacity, and transmission and distribution deferral have been driving installations. Where market operators have permitted energy storage systems to obtain capacity credits, larger-scale energy storage systems have been justified financially based on the capacity payments over 10-20 year contracts. These structures have additionally supported storage applications for transmission and distribution (T&D) congestion relief. Finally, markets which have developed mechanisms to compensate fast regulation or pay-for-performance market products, have allowed for an opportunity for battery energy storage systems which can obtain high- performance scores in these markets. Of note, the growth of commercial and industrial behind-the-meter storage installations has been driven in select markets where customers are exposed to high retail rates, and more importantly, high monthly peak demand charges. At the residential level, in select markets where net-metering rules are unfavorable to customers installing solar generation, and high retail energy rates exist, residential self-supply is also seen as a cost-effective energy storage application. Based on these current trends, storage applications related to capacity such as supply capacity and T&D congestion relief, as well as applications supporting renewable integration, such as renewable time shifting, regulation, and load following, and to a lesser extent, frequency response and voltage support, are likely to be the more likely application for storage over the next 20 years. The relative ranking of these applications is more nuanced and requires a look at the policies in-place or planned for PacifiCorp’s service territory. The PacifiCorp territory is comprised of regions throughout California, Oregon, and Washington (under PacificPower), and Idaho, Utah, and Wyoming (under Rocky Mountain Power). Each state observes a variety of regulations relating to energy security, distribution, and storage. Further, the federal government provides additional regulation that must be observed. At both the state and federal level, incentives are additionally provided in some cases. The PacificPower region, in particular, has a well-developed set of regulations and incentives already in place. Oregon, Washington, and California all have Renewable Portfolio Standards (RPS) as well as other legislation that encourages utility pursuit of clean energy and potentially energy storage systems. Oregon’s most influential energy storage-specific legislation that passed in 2015, HB 2193, directs the state’s electric utility companies to procure one or more energy storage systems capable of storing a specified energy capacity by 2020, allowing them to recover all costs through electrical rates. Additionally, SB 1547 passed in 2016, requiring, among other things, an RPS which would amount to 50% renewables for PacifiCorp by 2040, and the elimination of coal-generated energy utilization by 2030. This legislation will put additional pressure for energy storage to support the growing renewables portfolio. In the state of Washington, several bills have been passed that create a supportive infrastructure for energy storage. For example, HB 1897 established a program in support of R&D to develop next generation clean energy technology sustainably; HB 1296 legislated that an IRP is required to include energy storage; SB 5025 amended laws to support the meeting of renewable energy targets by utilities and minimum standards for energy efficient buildings; and HB 1895, a bill currently pending a hearing, if passed would promote the deployment of clean distributed energy, and prioritizes deployment of smart grids and microgrids. Further, the Energy Independence Act, or I-937, specifically requires a 15% RPS by 2020. The pursuit of these standards has recently been supported by HB 1115. This legislation sets aside $44 million in grants that are to be directed towards renewables advancement and technology, specifically including energy storage. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 29 www.dnvgl.com California has for many years been a leading state in the pursuit of clean energy. Many pieces of legislation support renewable technology infrastructure, especially focused on the causes of reducing emissions and improving energy resiliency. For instance, SB 1358 specifies emission performance standards and SB 350 requires an increase in the amount of electricity generated and sold from renewable energy resources in order to strengthen the diversity and resilience of the electrical system. California further passed SB 83, requiring public utilities to enact net metering tariffs to enhance diversification and reliability of the state’s energy resources. Recently, AB 1530 states that clean distributed energy must be deployed by utilities, and prioritizes deployment of smart grids and microgrids. Specifically, California utilities must meet an RPS of 50% by 2030, with intermediate goals, as initiated by AB 327 and SB 350, noted previously. In contrast, the Rocky Mountain Power region does not have as many or as specific regulation or support. While Utah provides a renewable energy target of 20% by 2025, but not an RPS, neither Idaho nor Wyoming has any RPS or voluntary renewable goals. There are, however, several pieces of legislation that support, directly or indirectly, energy storage, chiefly as a method to support reliability and resiliency. Utah leads the way with SB 0115, called the Sustainable Transportation and Energy Plan (STEP) Act. This bill allows for the Public Service Commission to authorize the implementation of tariffs by utilities in order to establish electric efficiency technology programs, allows the utility to provide incentives for air quality improvement technology and electric vehicle infrastructure development, and provides support for clean energy programs implemented by utilities. PacifiCorp has already reacted to this legislation with their STEP initiative. This includes the STEP Pilot programs, 5-year programs providing funding to, among other projects, battery storage development. Additionally, PacifiCorp has applied to the Public Service Commission to offer large customers the option to participate in a Renewable Energy Tariff, paying directly to get part or all of their electricity from a specific renewable project. Further, Utah has passed SB 280, which promotes the development of diverse energy resources, including nonrenewable and renewable resources, nuclear, and alternative transportation fuels. This distributed generation policy’s focus is to promote resiliency and reliability of the grid, and will likely naturally lead to an investigation of energy storage procurement and integration. Idaho passed HB 189, which removed all property taxes on renewable generation sites, in favor of a 3-3.5% tax on generation. Otherwise, although Idaho has neither net metering law nor RPS, it does offer tax credits for renewable energy. Wyoming, meanwhile, has no net metering law and provides no credits or exemptions for clean distributed energy resources. Further, Wyoming taxes wind generation and is currently considering further raising those taxes. As noted previously, Wyoming has no RPS. Finally, the Federal Government has put in place regulations to encourage renewables and energy storage. Widely known and utilized is the Investment Tax Credit provided by the Federal government. This 30% direct tax credit was extended until 2019, reduced stepwise annually after that, to 26% in 2020, 22% in 2021, and 10% in 2022, before ending. As to standards, the Clean Power Plan, as regulated by the EPA, assigns each state an emissions reduction target by 2030, contributing to a 32% reduction nationwide. Specific to PacifiCorp, Wyoming, Utah, and Washington have aggressive reduction targets, above 31%, while California, Oregon, and Idaho have reduction targets below 20%, in comparison with 2012 levels. These targets are based on, among other things, generation activity, as well as actions already taken to reduce emissions. States are required to submit a plan for compliance by September 2016, or be subject to a DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 30 www.dnvgl.com federally developed plan, both likely to directly affect utilities. Although there is some Congressional action to block these requirements, none has currently passed. 5.3 Application Ranking Methodology and Results DNV GL developed a ranking system for the various applications that battery energy storage systems may be utilized for within PacifiCorp territory. Within this ranking system, information about each technology is used to ascertain its appropriateness for a particular application. The battery type’s typical size, technology maturity level, market penetration, as well as technical parameters and various costs influenced these rankings. First, each application was defined by its requirements for power, energy, cycling, and response time. These Application Requirements were scored on a comparative scale. For instance, in the case of the application of Electric Energy Time Shift, the energy capacity of the system is paramount and thus ranked highly. Alternatively, in the case of the application for Frequency Response, the energy capacity of the system is of lesser importance while response time and power capability are the prioritized requirements. Each technology was then defined by its capabilities to meet these requirements for power, energy, cycling, and response time. These technology capabilities were similarly scored on a comparative scale. For instance, Li- ion technology provides nearly instantaneous response time and was thus ranked highest in that parameter. Flow batteries, on the other hand, scored highest for cycling as they are capable of fully discharging daily with less impact on lifetime and degradation. A Technology Maturity score was then also assigned to technology each based on its current stage of commercialization and scale of field deployments. The Application Requirements and Technology Capability scores were then compared, defining how well- matched a specific technology was for a given application. For instance, if an application required fast response time, the technologies that provide a fast response time would score highest. Scores across each property were then averaged to provide a Technology Application score for each technology providing each application. A PacifiCorp Application Need score was then assigned to each application based on the high-level cost- effectiveness and regulatory analysis of the PacifiCorp territory. Based on current PacifiCorp market scenario, storage applications with high value that are not dependent on market-related rule changes, such as T&D congestion relief, are expected to be the most likely candidates for PacifiCorp to deploy energy storage. Additionally, as noted in the review, renewable portfolio standards across the PacifiCorp region will drive some renewable integration applications such as renewable time shifting, regulation, and load following. Faster regulation applications such frequency response and voltage support are likely to be lower value applications. A second set of Scores for PacifiCorp Application Need scores were provided for the alternative market scenario with PacifiCorp operating under market rules similar to those implemented in California ISO (CAISO). For this scenario, CAISO market rules which directly allow storage to qualify for supply capacity credit increased this application score. Also, further developed fast regulation and emerging ramping market products increased the PacifiCorp Application Need score for frequency regulation and applications tied to renewable integration. Finally, PacifiCorp application rankings were computed for each application and technology under each market rules scenarios. The final rankings were computed by taking the average score over the Technology Application score, the Technology Maturity Score, and the PacifiCorp Need score. This methodology resulted in Table 11 and Table 12. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 31 www.dnvgl.com Table 11 Application Rankings in Current Market Rules Scenario Application Current Market Scenario Li-Ion NCM Li-Ion LiFePO4 Li-Ion LTO NaS VRB ZnBr Zinc-air Electric Energy Time Shift 9 8 8 9 8 8 7 Electric Supply Capacity 9 9 9 9 8 8 7 Regulation 9 9 9 9 8 8 7 Spinning, Non-spin, Supplemental reserves 8 8 9 8 8 8 7 Voltage support 7 8 8 7 6 6 6 Load following / ramping support for renewables 8 8 9 8 8 8 7 Frequency response 7 7 8 7 6 6 5 Transmission and distribution congestion relief 9 9 9 9 9 9 8 DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 32 www.dnvgl.com Table 12 Application Rankings for CAISO Market Rules Scenario Application CAISO Market Scenario Li-Ion NCM Li-Ion LiFePO4 Li-Ion LTO NaS VRB ZnBr Zinc-air Electric Energy Time Shift 9 9 9 9 9 9 7 Electric Supply Capacity 9 9 9 9 9 9 8 Regulation 9 9 9 9 8 8 7 Spinning, Non-spin, Supplemental reserves 9 9 9 9 8 8 7 Voltage support 7 8 8 7 6 6 6 Load following / ramping support for renewables 9 9 9 9 8 8 7 Frequency response 7 7 8 7 6 6 5 Transmission and distribution congestion relief 9 9 9 9 9 9 8 DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 33 www.dnvgl.com 6 CONCLUSION The data from this study is intended to support PacifiCorp in making decisions regarding energy storage procurement and grid integration to support their 2017 IRP, giving confidence in the current state of the industry while providing insight into what trends and regulations which will prevail in the future. Further, this study is intended to provide general guidance on the appropriateness of each presented technology for specific applications, as needs and requirements vary across each PacifiCorp region. The inclusion of battery energy storage, particularly when paired with other distributed energy resources, will allow PacifiCorp to comply with emerging energy regulations while also providing greater flexibility, resiliency, and efficiency in the allocation of resources. DNV GL – Document No.: 128197#-P-01-A, Date of Issue: August 22, 2016 Page 34 www.dnvgl.com ABOUT DNV GL Driven by our purpose of safeguarding life, property and the environment, DNV GL enables organizations to advance the safety and sustainability of their business. We provide classification and technical assurance along with software and independent expert advisory services to the maritime, oil and gas, and energy industries. We also provide certification services to customers across a wide range of industries. Operating in more than 100 countries, our 16,000 professionals are dedicated to helping our customers make the world safer, smarter, and greener. FINAL BULK STORAGE STUDY FOR THE 2017 INTEGRATED RESOURCE PLAN B&V PROJECT NO. 192472 PREPARED FOR PacifiCorp 19 AUGUST 2016 ® ® ©B l a c k & Ve a t c h Ho l d i n g Co m p a n y 20 1 6. All rig h t s re s e r v e d . PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Table of Contents ii Table of Contents 1.0 Introduction .............................................................................................................................................. 1 2.0 Pumped Storage Hydroelectric .......................................................................................................... 2 2.1 General ...................................................................................................................................................................... 2 2.2 Swan Lake North ................................................................................................................................................... 3 2.3 JD Pool ....................................................................................................................................................................... 4 2.4 Seminoe..................................................................................................................................................................... 5 2.5 Operating Characteristics and Regulatory Overview ............................................................................ 6 2.6 Capital, Operating, and Maintenance Costs ................................................................................................ 6 2.7 Summary .................................................................................................................................................................. 9 3.0 Compressed Air Energy Storage ...................................................................................................... 10 3.1 CAES Technology Description ...................................................................................................................... 10 Appendix A. Data Tables ................................................................................................................................ 14 LIST OF TABLES Table 1 Swan Lake North Pumped Storage Project Facilities Summary ................................................. 14 Table 2 JD Pool Pumped Storage Project Facilities Summary ..................................................................... 16 Table 3 Seminoe Pumped Storage Project Facilities Summary .................................................................. 18 Table 4 Cost Opinion Comparison ........................................................................................................................... 20 Table 5 Annual Cost Comparison ............................................................................................................................ 20 Table 6 Pumped Storage Technology Summary Matrix ................................................................................. 21 Table 7 Estimated 5-year EPC expenditure pattern for a pumped storage facility ............................ 22 Table 8 Technology Categories of Compressed Air Energy Storage (CAES) and Liquid Air Energy Storage (LAES) as of June 14, 2016 ................................................................................. 23 Table 9 CAES and LAES project descriptions ..................................................................................................... 24 Table 10 CAES and LAES project descriptions (continued) ............................................................................ 25 Table 11 Magnum CAES Data ....................................................................................................................................... 26 LIST OF FIGURES Figure 1 Estimated 5-year EPC expenditure pattern for a pumped storage facility ............................ 22 PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Legal Notice iii Legal Notice This report was prepared for PacifiCorp Energy ("Client") by Black &Veatch (“Consultant”). In performing the services, Consultant has made certain assumptions or forecasts of conditions, events, or circumstances that may occur in the future. Consultant has taken reasonable efforts to assure that assumptions and forecasts made are reasonable and the basis upon which they are made follow generally accepted practices for such assumptions or projections under similar circumstances. Client expressly acknowledges that actual results may differ significantly from those projected as influenced by conditions, events, and circumstances that actually occur. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Introduction 1 1.0 Introduction Black & Veatch Corporation (B&V) was retained by PacifiCorp to perform a Bulk Energy Storage Study (Study) to support PacifiCorp’s 2017 Integrated Resource Plan (IRP). IRPs are developed by power utilities to evaluate a portfolio of generating resources and energy storage options for their system in order to balance increasing levels of variable energy resources and, as generation from variable energy resources and their relative percentage of load grow, the need for additional system flexibility to assure grid reliability. For PacifiCorp, generating resource options include fossil fuel options, such as coal and natural gas, as well as renewable options including wind, geothermal, hydro, biomass, and solar. Energy storage technologies have been evaluated in the past by PacifiCorp. HDR Engineering (HDR) was retained by PacifiCorp to perform an energy storage study titled “Energy Storage Screening Study For Integrating Variable Energy Resources within the PacifiCorp System” dated December 9, 2011, to support PacifiCorp’s 2013 IRP. To support PacifiCorp’s 2015 IRP, HDR provided an updated version of their 2011 study titled “Update to Energy Storage Screening Study for Integrating Variable Energy Resources within the PacifiCorp System” dated July 9, 2014. As requested by PacifiCorp to support their 2017 IRP, the scope of work for this Study is only an update of the estimates of costs, schedules, and operating/performance characteristics provided in the previous HDR energy storage studies with a focus on two primary energy storage technologies with specific projects of each in various stages of planning as follows. Pumped Storage Hydroelectric ● Swan Lake North ● JD Pool - Klikitat ● Seminoe Compressed Air Energy Storage ● Magnum Energy The results of the Study are provided in the following report sections and appendices. The information presented has been gathered from and is based on public and private documentation, studies, reports, and project data of the specific projects associated with the two primary energy storage technologies of the scope of work. Although not included in the scope of work for this Study, a thorough and applicable discussion of considerations for integrating variable energy resources into power systems is provided in HDR’s 2011 and 2014 reports for information purposes and will not be restated herein. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Pumped Storage Hydroelectric 2 2.0 Pumped Storage Hydroelectric The previous HDR 2011 and 2014 energy storage studies considered potential pumped storage hydroelectric projects within the PacifiCorp operating power system region as follows: HDR 2011 Study ● Swan Lake North ● Yale-Merwin ● JD Pool ● Parker Knoll HDR 2014 Study ● Swan Lake North ● JD Pool ● Black Canyon1 For this Study, PacifiCorp has requested that only the estimated costs, schedules, and operating/performance characteristics from the HDR 2014 study be updated for the Swan Lake North, JD Pool, and Seminoe projects. 2.1 GENERAL A pumped storage hydroelectric facility requires a lower and upper reservoir. During times of minimal load demand or when required to absorb energy, excess energy is used to pump water from a lower reservoir to an upper reservoir. When energy is required (during a high value or a peak electrical demand period), water in the upper reservoir is released through a turbine to produce electricity. The pumping and generating is typically accomplished by a reversible pump- turbine/motor-generator. In addition to providing electricity at times of peak power demand, applications for pumped storage hydroelectric projects include: Providing transmission system support through ancillary services, such as load shifting and following, frequency control, grid stabilization, and reserve generation, etc. Energy storage for less dependable renewable resources, such as wind and solar energy. Pumped storage projects may be categorized as either open-loop or closed-loop pumped storage projects. The Federal Energy Regulatory Commission (FERC) defines these classifications as follows: Open-loop pumped storage projects are continuously connected to a naturally-flowing water feature. 1 Black Canyon Pumped Storage Project is a precursor to the Seminoe Pumped Storage Project. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Pumped Storage Hydroelectric 3 Closed-loop pumped storage projects are not continuously connected to a naturally-flowing water feature. For open-loop pumped storage systems, acquisition of environmental approvals has become increasingly challenging due to the need to develop a lower reservoir on an active river or existing lake. To mitigate this issue, many recent pumped storage developments have proposed closed-loop systems, which often utilize existing features such as abandoned quarries or underground mines as the lower reservoir of the pumped storage system. This allows the pumped storage project to be developed and operated off-stream, reducing environmental impacts and also reducing costs associated with development of the lower reservoir. 2.2 SWAN LAKE NORTH 2.2.1 Current Project Status In HDR’s 2014 study, it is noted that various preliminary Federal Energy Regulatory Commission (FERC) permits and a draft license application were filed for the Swan Lake North Pumped Storage Project (FERC No. 13318) (Project) between 2010 and 2012. Over this period, the proposed capacity of the project went from 1,000 megawatts (MW) to 600 MW due to the developer, Swan Lake North Hydro LLC, making a number of changes to the project layout, size of reservoirs, water conveyance arrangement, and consideration of surface penstocks. The 600 MW project capacity was the basis for HDR’s 2014 study. Since 2014, a Final License Application (FLA) was filed by Swan Lake North Hydro LLC on October 27, 2015, and is currently under consideration by the FERC. In this document, the proposed project capacity was further reduced to 400 MW due to further project optimization during the course of final license application development. Although drawings from the final license application are not publically available through the FERC website, it is assumed that the general project configuration will be similar to the site layout and profile provided in the HDR 2014 study, only at a lower capacity. The 400 MW project capacity and the description of the project facilities provided in the final license application exhibits that is publically available from the FERC website are the basis for this Study. 2.2.2 Project Description The Project is a closed-loop pumped storage system with an installed capacity of 393.3 MW in generating mode. It will be located approximately 11 miles northwest of Klamath Falls, Oregon. A general summary of the proposed Project facilities is provided in Table 1 in Appendix A. 2.2.3 Schedule The proposed construction schedule for the Project is described and presented in Exhibit C of the FLA. The schedule assumes approximately 24 months for final design with an expected completion date in 2017. Final review and approval of the design is anticipated to take 6 to 12 months after which construction will begin. Construction will take approximately 4 years to complete. The proposed commercial operation date is November 2022, assuming a FERC Notice-to-Proceed in January 2018. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Pumped Storage Hydroelectric 4 2.3 JD POOL 2.3.1 Current Status In HDR’s 2014 study, it is noted that an original preliminary FERC permit and a successive application had been filed by the Public Utility District No. 1 of Klickitat County, Washington (KPUD) for the JD Pool Pumped Storage Project (FERC No. 13333) (Project) on November 29, 2008, and April 30, 2012, respectively. The information provided in the successive application was the basis of information for HDR’s 2014 study. The proposed Project capacity at that time was 1,500 MW. After the HDR 2014 study, a Pre-Application Document (PAD) was filed by KPUD in October 2014. The information in the PAD revised the project configuration and reduced the Project proposed capacity to 1,200 MW. Due to the effective date of the successive application, KPUD filed a second successive preliminary permit application on November 3, 2015, in order to extend the effective date of the application. At the same time, Clean Power Development LLC (Clean Power) filed a competing preliminary permit application for the proposed Columbia Gorge Renewable Energy Balancing Project (FERC No. 14729) (Columbia Gorge Project) at the same location. The lower reservoir site for both applications is currently undergoing a cleanup process due to decades of contamination from the former operation of the Columbia Gorge Aluminum smelter. Given the uncertainty of the timeline for the site cleanup and its suitability for development, FERC found it not prudent to issue a preliminary permit for the site and dismissed both applications. The above information concerning the Project status and dismissal of the preliminary permit applications filed by KUPD and Clean Power is summarized from FERC’s “ORDER DISMISSING PRELIMINARY PERMIT APPLICATIONS” document dated December 23, 2015. FERC also notes in this document that they may consider development applications in the future for the site, but the applications must thoroughly address all concerns related to developing the Project at a previously contaminated site. Thus, permitting this site in the future may require special considerations, and its timeline is unknown at this time. Based on the public information available from the FERC website, the 1,200 MW project capacity and the description of the project facilities provided in the PAD are the basis for this Study. 2.3.2 Project Description The Project is a closed-loop pumped storage system with an installed capacity of 1,200 MW in generating mode. It will be located approximately 8 miles southwest of Goldendale, Washington. A general summary of the proposed Project facilities is provided in Table 2 in Appendix A. Based on a review of the PAD information, there is a high likelihood that the Project can be further optimized to reduce costs, such as finalizing the total storage requirement of the reservoirs and the number and/or size of the water conveyance conduits. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Pumped Storage Hydroelectric 5 2.3.3 Schedule The proposed development and construction schedule for the Project is outlined in the PAD as follows: Pre-filing Schedule for Filing License Application: 1 year Pre-construction Development Activities after FERC Issuance of License, Including Design/Construction Drawings: 3 years Project Construction: 5 years Anticipated Commissioning of Project: 5th Year of Construction 2.4 SEMINOE 2.4.1 Current Status The HDR 2014 study included the Black Canyon Pumped Storage Project (FERC No. P-14087). A preliminary FERC permit application for the project was prepared by Gridflex Energy, LLC and filed by Black Canyon Hydro, LLC on January 25, 2011. The application showed several possible alternatives for pumped storage development that included two new upper reservoirs that could be connected to one of two existing lower reservoirs, the Seminoe and Kortes Reservoirs. Both of the existing reservoirs are owned and operated by the U.S. Department of Interior’s Bureau of Reclamation. The original preliminary permit for the project, along with Gridflex’s response to HDR’s Request for Information (RFI), was the basis of information for HDR’s 2014 study. As noted by HDR, there was conflicting information relative to generating and pumping capacities between the original preliminary permit and the RFI response. On July 1, 2014, Gridflex prepared and Black Canyon Hydro, LLC filed a successive preliminary permit application for the Black Canyon Pumped Storage Project (FERC No. P-14087). This filing occurred about the time HDR had concluded their 2014 study. The successive application identified and included an additional alternative for consideration. However, on November 26, 2014, FERC issued an order denying the successive preliminary permit on the general basis that very little progress toward the filing of a development application had been made during the course of the original three-year permit term and did not warrant a successive permit. Gridflex prepared and Black Canyon Hydro, LLC filed a preliminary FERC permit application for the Seminoe Pumped Storage Project (FERC No. P-14787) (Project) on June 16, 2016. This Project is similar to and utilizes the concept of the Black Canyon Pumped Storage Project. Per FERC letter dated June 21, 2016, some deficiencies and the need for additional information were identified with regard to the application. Gridflex prepared and Black Canyon Hydro, LLC filed an amended preliminary FERC permit application on June 28, 2016, which was accepted by FERC on June 30, 2016. The proposed total Project capacity is 700 MW and consists of two developments (i.e. East and West) that utilize the existing Seminoe Reservoir as their lower reservoir. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Pumped Storage Hydroelectric 6 2.4.2 Project Description The Project is an open-loop pumped storage system with a total installed capacity of 700 MW in the generating mode. It will be located approximately 30 miles northeast of Rawlins, Wyoming. The Project utilizes the water resources of the North Platte River as stored and conveyed through the existing reservoir. The Project includes two new forebay reservoirs (i.e. East and West), two underground powerhouses, two power tunnels between the forebays and powerhouses, and two tailrace tunnels between the powerhouses and the existing Seminoe Reservoir. In the generating mode, the East and West powerhouses have installed capacities of 400 and 300 MW, respectively, for a total Project installed capacity of 700 MW. A general summary of the proposed Project facilities is provided in Table 3 in Appendix A. 2.4.3 Schedule The preliminary permit includes a three-year duration schedule for studies to design the technical aspects of the Project and confirm its economic viability. No overall schedule for Project implementation was provided; however, it would be anticipated that the FERC final license application would be completed in 2019 with final engineering, construction, and commercial operation of the Project completed during the 2020 through 2025 timeframe. 2.5 OPERATING CHARACTERISTICS AND REGULATORY OVERVIEW A relevant discussion of typical pumped storage hydroelectric project operating characteristics relating to the beneficial services that such projects can provide, and general considerations and important aspects concerning environmental and regulatory factors with regard to siting and developing a potential pumped storage project are provided in HDR’s 2014 report for information purposes and will not be restated herein. 2.6 CAPITAL, OPERATING, AND MAINTENANCE COSTS The following sections provide an update of the cost estimates from the HDR 2014 study with regard to expected capital and operation and maintenance (O&M) costs for the three potential pumped storage projects in the PacifiCorp region selected for this Study. Costs provided are expressed in mid-2016 dollars. 2.6.1 Capital Cost The HDR 2014 study provided a general discussion of capital costs associated with pumped storage projects. As noted in the HDR 2014, which is particularly true, the direct cost to construct a pumped storage facility may vary greatly and is dependent upon a number of physical site factors. The HDR 2014 study also notes the direct and indirect cost items generally included for capital costs, which would also generally include Owner project contingency, development, and project team costs. In addition to those cost items, capital cost assumptions for this Study include an Engineer-Procure- Construct (EPC) type of project delivery methodology and estimates reflecting a +/- 30% order of accuracy, which would approach an Association for the Advancement of Cost Engineering (AACE) Class 4 cost estimate classification. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Pumped Storage Hydroelectric 7 2.6.1.1 Swan Lake North As reported in the HDR 2014 study, EDF provided an AACE Class 4 cost estimate of $2,300/kW for the envisioned 600 MW facility at that time, which apparently compared favorably to earlier cost opinions prepared by HDR for the Project. Escalating this cost to mid-2016 dollars using a rate of 3% per year results in a total project cost of approximately $2,500/kW. The 3% per year escalation rate was used in the HDR 2014 study and is considered appropriate for escalating HDR values to mid-2016 dollars for this Study. No recent cost information was available from Swan Lake North Hydro LLC for the current Project capacity of 400 MW and description provided in their FLA dated October 27, 2015. Based on our review of the Project described in the FLA, a cost opinion on the order of $2,600/kW would be expected, which compares favorably to the developer’s escalated unit cost of $2,500/kW. 2.6.1.2 JD Pool As reported in the HDR 2014 study, HDR performed a reconnaissance level study and AACE Class 5 cost opinion in 2005 for the 1,500 MW Project envisioned at that time. Their study resulted in an escalated cost opinion of $2,500/kW in 2014 dollars. Escalating to 2016 using a rate of 3% per year, this cost opinion would be approximately $2,700/kW. No recent cost information was available from KPUD for the current Project described in their PAD dated October 2014, having a capacity of 1,200 MW. However, as reported in the HDR 2014 report, KPUD did provide a cost opinion of $2 billion to $2.5 billion for a 1,000 to 1,200 MW project in their Preliminary Permit Application, which equated to unit costs of $1,700 to $2,500/kW. Escalating to 2016 using a rate of 3% per year, these cost opinions would be approximately $1,800 to $2,700/kW. Based on our review of the Project described in the PAD, a cost opinion on the order of $2,700/kW would be expected, which compares favorably to the developer’s escalated unit cost for a 1,200 MW Project. 2.6.1.3 Seminoe As reported in the HDR 2014 study, HDR noted that the Developer’s estimated cost of $1,500/kW in 2014 dollars appeared too low to satisfactorily cover the direct and indirect costs (i.e. capital costs) of the original Black Canyon Pumped Storage Project, which has a different installed capacity than the Seminoe Pumped Storage Project. HDR’s cost opinion for Black Canyon was on the order of $2,000 to $2,300/kW in 2014 dollars. Escalating to 2016 using a rate of 3% per year, these costs would be approximately $1,600/kW and $2,100 to $2,400/kW, respectively. Based on our review of the 700 MW Seminoe Project described in the preliminary permit, an average cost opinion for the combined East and West facilities on the order of $2,600/kW would be expected, which compares favorably to the upper range of HDR’s escalated cost opinion for the Black Canyon Project. 2.6.1.4 Summary A comparison of the cost opinions is provided in Table 4 in Appendix A. It would appear that the capital cost of a pumped storage hydroelectric project would be in the range of $1,800 to $2,700/kW. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Pumped Storage Hydroelectric 8 2.6.2 Annual Operation and Maintenance (O&M) Costs The “Pumped Storage Planning and Evaluation Guide” dated January 1990 by the Electric Power Research Institute (EPRI) is an appropriate resource for estimating annual costs for pumped storage hydroelectric projects and was used by HDR in their 2014 study. Based on this document, estimating the annual costs to operate and maintain a pumped storage hydroelectric project would include the following. Operation and Maintenance (O&M). O&M costs can be estimated by the following equation: O&M Costs (1987$/yr) = 34,730 x C 0.32 x E 0.33 where: C = Plant Capacity, MW E – Annual Energy, GWh General expenses. A 35% surcharge of the site specific O&M cost is suggested to cover administration expenditures. Insurance. To cover payments for insurance, a surcharge of 0.1% of the plant investment cost is suggested. As noted in the HDR 2014 study, using the EPRI information, a 2.06 escalation factor had to be used to obtain the annual costs in 2014 dollars. Escalating to 2016, using 3% per year, this factor becomes 2.19. Table 5 in Appendix A summarizes the annual costs for the three Projects considered for this Study. 2.6.3 Bi-Annual Outage Costs As noted in the HDR 2014 study, it is recommended within the hydro industry that bi-annual outages be conducted for inspections and possible repairs following the inspections. The frequency of inspections and possible repairs can vary greatly from project to project depending upon the usage (hours/year) and cycling of the units that may occur, along with site specific conditions that may impact the condition of the units over time. The assumption of taking two units out of service during a 3-week outage every two years for a 4 unit, 1,000 MW powerhouse at an estimated cost of $262,000 in 2014 dollars is reasonable. Escalating this cost using 3% per year would be approximately $280,000 in 2016 dollars and appropriate for budgeting purposes. Our review of the bi-annual outage cost compares favorably with the escalated value; assuming only nominal repairs are required. 2.6.4 Major Maintenance Costs As noted in the HDR 2014 study, it is also recommended within the hydro industry that a pump- turbine overhaul (i.e. major unit rehabilitation) and generator rewind be scheduled at year 20, and the typical outage duration for this work is approximately 6 to 8 months. Because of the nature of this type of facility, pumped storage projects typically operate more hours per year than PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Pumped Storage Hydroelectric 9 conventional generating units. This results in increased cycling of the units, which impacts service life requiring major maintenance. These are reasonable assumptions and suggested for this Study. Because the scope of this type of rehabilitation work can vary greatly, HDR in their 2014 study suggested an estimated cost of $6.28 million for reversible Francis units at year 20. Escalating this value using 3% per year would be approximately $6.7 million in 2016 dollars. This value appears to be slightly low. In using the “Hydropower Modernization Guide” date July 1989 by the EPRI, a range of major rehabilitation average costs for the size of units being considered at Swan Lake North, JD Pool, and Seminoe (i.e. 100 MW to 300 MW) would be approximately $3.7 to $8.0 million. We suggest using this range of costs for major maintenance costs during the plant life. 2.7 SUMMARY A matrix of operating parameters and costs for the pumped storage bulk energy storage option is provided in Table 6 in Appendix A. An estimated EPC expenditure timeline for a pumped storage facility based on a 5-year EPC schedule is also provided in Table 7 and Figure 1 in Appendix A. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Compressed Air Energy Storage 10 3.0 Compressed Air Energy Storage 3.1 CAES TECHNOLOGY DESCRIPTION 3.1.1 Current Project Status The DOE maintains a Global Energy Storage Database.2 Black & Veatch filtered and sorted the data as shown in Table 8 in Appendix A. The characteristics of the identified projects included in the DOE database for the Technology Categories of Compressed Air Energy Storage (CAES) and Liquid Air Energy Storage (LAES) as of June 14, 2016 are shown. Descriptions for these projects as given in the DOE database are provided in Table 8, Table 9 and Table 10 in Appendix A. While the information in the DOE database is informative, not all the data is current. As noted in the HDR 2014 study, only two CAES plants are currently in operation; the Power South (formerly AEC) McIntosh plant rated at 110 MW in McIntosh, Alabama which began operation in June 1991 and the 290 MW Huntorf facility which began operation in December 1978 in Hannover, Germany. Both of these plants use a solution mined salt cavity and are diabatic type CAES plants. Other large CAES plants have been proposed but, as of yet, have not moved forward beyond conceptual design or have been cancelled. With respect to the larger CAES projects, several were identified in the HDR 2014 study and include the following; Western Energy Hub Project Norton Energy Storage (NES) Project PG&E Kern County CAES Plant ADELE CAES Plant in Stassfut, Germany Updates for CAES plants are as follows: 3.1.1.1 Western Energy Hub Project The Western Energy Hub is situated directly above a salt dome at a nominal depth of 3,000 feet. Three-dimensional seismic mapping of the formation indicates the salt dome measures at least one mile thick and is approximately three miles wide. The Western Energy Hub project is planned to include multiple phases and services to support the expansion and utilization of renewable energy technologies. The Western Energy Hub will feature solution-mined salt caverns capable of storing natural gas, compressed air, and liquid energy products (including refined products of aviation fuel, diesel, and motor gasoline) underground. 2 http://www.energystorageexchange.org/projects PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Compressed Air Energy Storage 11 Magnum is currently developing the Magnum Refined Products phase and it is expected to be the first underground salt cavern storage facility for refined products in the Rocky Mountain Region. The Magnum Gas Storage Project would also include the first High-Deliverability Multi-Cycle (HDMC) storage facility in the Rocky Mountain Region. The facility will contain four solution mined storage caverns capable of storing 54 billion cubic feet of natural gas. It will be interconnected with the interstate natural gas pipeline system by a new 61-mile-long header pipeline. In addition to these services, the Western Energy Hub project will include a CAES plant in conjunction with a combined-cycle power generation project. The CAES plant will include additional solution-mined caverns to store compressed air. Off-peak renewable generation will be used to compress air into the caverns. The compressed air will be released to produce power during periods of peak power demand. Magnum anticipates an in-service date for the CAES plant of around 2021. Additional information on the CAES plant as provided to PacifiCorp by Magnum is included in Table 11 in Appendix A. 3.1.1.2 Norton Energy Storage (NES) As noted in the HDR 2014 study; “In December 2012, First Energy suspended construction on the project due to unfavorable economic conditions including low cost of power prices and insufficient demand. As of September 2013, the Ohio Power Siting Board invalidated the certificate at this site.” No further activity has been noted. 3.1.1.3 PG&E Kern County CAES PG&E continues to evaluate the potential development of a Compressed Air Energy Storage (CAES) project and issued a Request for Offers (RFO) on October 9, 2016. Offers were received on June 1, 2016 with potential negotiations with shortlisted bidders to commence in August 2016. PG&E anticipates the project would be between 100 and 350 MW and would be required to have a minimum storage duration of 4 hours. The RFO is intended to potentially procure products and services related to the CAES project, and to determine the technical and economic feasibility of energy storage using compressed air in a depleted natural gas reservoir in a porous rock formation, approximately one half to one mile underground. The depleted natural gas field in San Joaquin County, California was selected for the project site and was subjected to air injection/withdrawal testing. PG&E notes that specific findings on geology, preliminary engineering, environmental analysis, and other information was gathered through testing and analyses for the site. 3.1.1.4 ADELE CAES No new information could be found for the adiabatic ADELE CAES plant. It does not appear that there has been any recent development activity. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Compressed Air Energy Storage 12 3.1.1.5 APEX Bethel Energy Center This 317 MW CAES plant with 96 hours of storage was announced in 2013. In 2014 the project was placed on hold. It does not appear that there has been any recent development activity. 3.1.2 Performance Characteristics 3.1.2.1 Site Elevation Site elevation will impact the compression work required to charge the storage for any CAES technology. Given the compressor section is not directly connected to the expansion turbine for conventional CAES operation, the volume flow of compressed air made available to the expansion turbine is not affected by site atmospheric pressure, but is instead driven by storage pressure. There is only a minor impact for conventional CAES plant output due to variation in exhaust pressure due to site elevation. Other configurations which may include a combustion turbine would see a greater impact due to site elevation. 3.1.2.2 Reliability/Availability In addition to the historic availability data given in the HDR 2014 study, the Huntorf CAES plant has reportedly operated with 99 percent starting reliability. 3.1.2.3 Start Times In addition to the start times given in the HDR 2014 study, newer CAES plants can achieve start times and fast ramp rates as noted in Table 11 in Appendix A. This data was provided to PacifiCorp by APEX Magnum. 3.1.2.4 Emission Profiles/Rates No updates. 3.1.2.5 Air Quality Control System Design In addition to Dry-Low NOx combustion technology, water injection may also be used to control NOx. A selective catalytic reduction (SCR) system can be included in the recuperator design to further reduce NOx emissions. CO catalysts can also be incorporated into the recuperator design to control CO emissions if required by the CAES plant design and air permit requirements. 3.1.3 Geological Considerations In addition to the geological formations generally considered for storing compressed air: salt domes, aquifers, and rock caverns; depleted methane reservoirs, which are being considered for the PG&E Kern River CAES plant, can be used. For the Huntorf and McIntosh plants, there were large vertical salt domes that were accessible for solution mining of single caverns for compressed air storage. In some parts of the country, the salt PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Compressed Air Energy Storage 13 is deposited between rock layers, creating shorter, squatter caverns with susceptibility to overhead shale spalling. These cavern costs can be higher. In addition, underwater storage reservoirs, as offered by Hydrostor, are possible. Above ground storage can be considered for smaller plants or when geological conditions are not favorable for a site. 3.1.4 Capital, Operating, and Maintenance Cost Data Regarding the HDR 2014 study’s discussion of project schedule, it is noted the project durations can be driven by the storage system development. Based on a Front End Engineering Design (FEED) study prepared for the NYSEG Seneca CAES Project for a 136 MW to 210 MW utility-owned facility, it is noted that the development time required to complete the three cavern system required for the site was estimated at approximately six years. The CAES plant would have initially gone into service with only one third of the required storage capacity and would not achieve full capability until after approximately five years of commercial operation. The above emphasizes the point that the time required to develop storage can be very site dependent. 3.1.4.1 Capital Costs The HDR 2014 study assumes project capital costs to include project direct costs associated with equipment procurement, installation labor, and commodity procurement as well as construction management, project management, engineering, and other project and owner indirect costs. The HDR estimate does not include storage cavern cost. Values were presented in 2014 dollars. Table 11 in Appendix A shows a capital cost, including site development costs, of $1,740/kW as provided by APEX Magnum. No further cost breakdown or clarification for this cost was provided. Black & Veatch interprets this cost to be the installed cost including the solution-mined caverns. This cost is assumed to not include any Owners costs. Site-specific factors can strongly influence the design of the CAES plant, the cavern and associated costs and ultimately the project economics. 3.1.4.2 Operating Costs In addition to the operating costs given in the 2014 report, expected O&M costs for the Magnum CAES facility are given in Table 11 in Appendix A. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 14 Appendix A. Data Tables Table 1 Swan Lake North Pumped Storage Project Facilities Summary3 ITEM DESCRIPTION Project Type: Closed-Loop Pumped Storage Upper Reservoir: Storage: Total: 3,229 acre-feet (ac-ft) Live: 2,562 ac-ft Surface Area: Maximum Fill: 64.21 acres (ac) Minimum Fill: 45.87 ac Operating Levels: Maximum: 6,128 mean sea level (msl) Minimum: 6,084 msl Elevation Change During Operation: 44 feet Overflow Spillway Capacity: 3,230 cubic feet/sec (cfs) Reservoir Lining: Asphaltic concrete with geomembrane liner and underdrain system Lower Reservoir: Storage: Total: 3,206 ac-ft Live: 2,581 ac-ft Surface Area: Maximum Fill: 60.41 ac Minimum Fill: 39.89 ac Operating Levels: Maximum: 4,457 msl Minimum: 4,408 msl Elevation Change During Operation: 49 ft Overflow Spillway Capacity: 3,230 cfs Reservoir Lining: Asphaltic concrete with geomembrane liner and underdrain system Source of Initial Fill and Long-term Refill: Local Groundwater Agriculture Pumping System (Three existing wells) Water Conveyance: Headrace Penstock: Diameter: 13.8 ft (4.2 meter)(1 pipe) Length: 9,655 ft 3 The information in this table has been obtained from Exhibits A and B of the FLA filed by Swan Lake North Hydro LLC on October 27, 2015 PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 15 ITEM DESCRIPTION PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 16 Table 2 JD Pool Pumped Storage Project Facilities Summary4 ITEM DESCRIPTION Project Type: Closed-Loop Pumped Storage Upper Reservoirs: Configuration: Two Reservoirs Connected By Tunnel Total Active Storage: 11,800 ac-ft Reservoir 1: Storage: Total: 5,000 ac-ft Active: 4,700 ac-ft Surface Area at Maximum Operating Level: 46 ac Operating Levels: Maximum: 2,935 msl Minimum: 2,785 msl Elevation Change During Operation: 150 feet Reservoir 2: Storage: Total: 7,700 ac-ft Active: 7,100 ac-ft Surface Area at Maximum Operating Level: 67 ac Operating Levels: Maximum: 2,935 msl Minimum: 2,785 msl Elevation Change During Operation: 150 feet Dams: Type: Rockfill Embankment Reservoir 1: Height: 165 ft Length: 5,200 ft Reservoir 2: Height: 165 ft Length: 6,300 ft Overflow Spillway: None Reservoir Linings: Concrete Lower Reservoir: Storage: Total: 12,100 ac-ft Active: 11,800 ac-ft Surface Area at Maximum Operating Level: 100 ac 4 The information in this table has been obtained from the PAD filed by KPUD in October 2014 PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 17 ITEM DESCRIPTION PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 18 ITEM DESCRIPTION Table 3 Seminoe Pumped Storage Project Facilities Summary5 ITEM DESCRIPTION Project Type: Open-Loop Pumped Storage Configuration: Two new forebay reservoirs (i.e. East and West), two underground powerhouses, two power tunnels between the forebays and powerhouses, and two tailrace tunnels between the powerhouses and the existing Seminoe Reservoir Upper Reservoirs: East Forebay: Storage: 4,800 ac-ft Surface Area: 85 ac Operating Level: 7,370 msl Dam Embankment A: Type: Concrete-Faced Rockfill (CFRD) Height: 85 ft Crest Length: 1,320 ft Dam Embankment B: Type: CFRD Height: Varies (5 ft at grade to 55 ft) Crest Length: 5,890 ft West Forebay: Storage: 3,740 ac-ft Surface Area: 63 ac Operating Level: 7,400 msl Dam Embankment: Type: CFRD Height: Varies (5 ft at grade to 60 ft) 5 The information in this table has been obtained from the Preliminary FERC Permit filed by Black Canyon Hydro, LLC in June 2016. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 19 ITEM DESCRIPTION PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 20 ITEM DESCRIPTION Table 4 Cost Opinion Comparison ITEM (COSTS ARE EXPRESSED IN 2016$) SWAN LAKE NORTH JD POOL SEMINOE (EAST AND WEST) 6 Table 5 Annual Cost Comparison ITEM (COSTS ARE EXPRESSED IN 2016$) SWAN LAKE NORTH JD POOL SEMINOE (EAST AND WEST) 6 As noted in HDR’s 2014 study, developer’s estimated capital cost was deemed too low. HDR’s cost opinion is shown. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 21 Table 6 Pumped Storage Technology Summary Matrix ITEM SWAN LAKE NORTH JD POOL SEMINOE (EAST AND WEST) General Criteria Location OR WA WY FERC Licensing Status Final License Application Filed Preliminary Permits Dismissed Preliminary Permit Filed Project Type (Closed/Open Loop) Closed Loop Closed Loop Open Loop Upper Reservoir Maximum Operating Elevation (msl) 6,128 2,935 7,370 (East) 7,400 (West) Lower Reservoir Maximum Operating Elevation (msl) 4,457 580 6,359 Static Head (maximum/minimum) (ft) 1,720/1,627 2,505/2,205 1,079 (East)(max.) 1,098 (West)(max.) Upper Reservoir Usable Volume (ac-ft) 2,562 11,800 4,800 (East) 3,740 (West) Lower Reservoir Usable Volume (ac-ft) 2,581 11,800 > 8,540 Distance to Electrical Transmission Interconnection (mi) 32.8 < 1 35 (approximate) Interconnection Size (kV) 230 230 230 Performance Characteristics7 Energy Storage/Day (MWh) 3,800 12,000 7,000 Assumed Hours of Storage/Day (hrs) 9.5 10.0 10.0 Installed Capacity (MW) 400 1,200 700 Estimated Annual Generation (GWh) 1,187 4,200 1,840 Annual Forced Outage Rate (% of time) 0 – 3%8 Type of Pump-Turbine/Motor-Generator Variable Speed Round Trip Efficiency (%) 77 Expected Life of Generating Equipment (yrs) 20+ Expected Life of Project (yrs) 50+ Basis of Cost Opinions (Costs are expressed in 2016 dollars.) Range of Capital Costs ($/kW) $1,800 - $2,700 Range of O&M Costs ($/kW-yr) $4.45 - $6.99 Bi-annual Outage Costs ($) $280,000 Range of Major Maintenance Costs/Unit ($) $3,700,000 - $8,000,000 Replacement Frequency (yrs) 20 7 Other performance characteristics, such as ramp rate, minimum loads, and time to switch from pumping to generating modes and vice versa for variable speed units, are presented in Table 3 of HDR’s 2014 study and are reasonable and appropriate for this Study. 8 Range of annual forced outage rate aligns with values presented in HDR’s 2014 study. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 22 Table 7 Estimated 5-year EPC expenditure pattern for a pumped storage facility YEAR QUARTER CUMULATIVE QUARTER QUARTERLY EXPENDITURE (%) CUMULATIVE EXPENDITURE (%) 0 0% 0% 1 1 1 2% 2% 1 2 2 2% 4% 1 3 3 3% 7% 1 4 4 3% 10% 2 1 5 4% 14% 2 2 6 4% 18% 2 3 7 5% 23% 2 4 8 5% 28% 3 1 9 6% 34% 3 2 10 6% 40% 3 3 11 8% 48% 3 4 12 8% 56% 4 1 13 8% 64% 4 2 14 8% 72% 4 3 15 7% 79% 4 4 16 7% 86% 5 1 17 7% 93% 5 2 18 3% 96% 5 3 19 3% 99% 5 4 20 1% 100% Figure 1 Estimated 5-year EPC expenditure pattern for a pumped storage facility 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0 2 4 6 8 10 12 14 16 18 20 Cu m u l a t i v e E x p e n d i t u r e o f E P C C a p i t a l C o s t Quarter following EPC NTP PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 23 Table 8 Technology Categories of Compressed Air Energy Storage (CAES) and Liquid Air Energy Storage (LAES) as of June 14, 2016 Project Name McIntosh CAES Plant PG&E Advanced Underground Compressed Air Energy Storage (CAES) Next Gen CAES using Steel Piping - NYPA SustainX Inc Isothermal Compressed Air Energy Storage Highview Pilot Plant NYSEG Seneca/Watkins Glen CAES Project Texas Dispatchable Wind Apex Bethel Energy Center Hydrostor UCAES Demonstration Facility Hydrostor UCAES Aruba Project Kraftw erk Huntorf Pollegio-Loderio Tunnel ALACAES Demonstration Plant Pre-Commercial Liquid Air Energy Storage Technology Demonstrator ATK Launch Systems Microgrid CAES 1 Hybrid Compressed Air Energy Storage and Thermal Energy Storage - UCLA - Southern California Edison 1 Adele CAES Project 1 Technology Type In-ground Natural Gas Combustion Compressed Air In-ground Compressed Air Storage Modular Compressed Air Storage Modular Iso- thermal Compressed Air Modular Compressed Air Storage In-ground Compressed Air Storage In-ground Iso- thermal Compressed Air In-ground Compressed Air Storage Modular Compressed Air Storage Modular Compressed Air Storage In-ground Natural Gas Combustion Compressed Air Adiabatic Compressed Air Storage Liquid Air Energy Storage Modular Compressed Air Storage Compressed Air Storage In-ground Iso- thermal Compressed Air Record Created 6/28/2012 6/29/2012 6/29/2012 7/18/2012 10/31/2012 5/2/2013 5/21/2013 10/11/2013 10/25/2013 10/25/2013 1/30/2014 6/25/2014 5/25/2016 5/6/2013 9/10/2015 11/4/2013 Last Updated 5/23/2016 6/14/2016 5/24/2016 5/24/2016 5/26/2016 9/5/2014 5/18/2016 1/28/2015 5/10/2016 7/23/2014 4/18/2016 5/19/2016 5/26/2016 7/11/2014 9/28/2015 10/27/2014 Rated Pow er in kW 110,000 300,000 9,000 1,500 350 0 2,000 317,000 1,000 1,000 321,000 500 5,000 80 0 200,000 Duration at Rated Pow er HH:MM 26:0.00 10:0.00 4:30.00 1:0.00 7:0.00 0:0.00 250:0.00 96:0.00 4:0.00 8:0.00 2:0.00 4:0.00 3:0.00 0:45.00 0:0.00 5:0.00 Status Operational Announced Announced Operational Operational Announced Operational Announced Under Contracted Operational Under Under Under Announced Under City McIntosh San Joaquin Queens Seabrook Slough Reading Seminole Tennessee Toronto San Nicolas Große Hellmer 1E Loderio Bury Promontory Pomona Staßfurt State/Province Alabama California New York New Hampshire Berkshire New York Texas Texas Ontario Aruba Elsfleth Ticino Lancashire Utah California Sachsen-Anhalt Country United States United States United States United States United Kingdom United States United States United States Canada Netherlands Germany Sw itzerland United Kingdom United States United States Germany Announcement Date 01.01.2010 01.06.2012 01.03.2010 30.11.2010 01.07.2013 01.10.2013 01.01.2013 13.02.2014 06.05.2013 20.08.2015 Construction Date 01.02.2011 01.01.2011 01.01.2013 01.02.2015 13.06.2014 26.02.2015 01.01.2013 Commissioning Date 01.01.1991 01.01.2020 11.09.2013 31.07.2011 19.12.2012 01.09.2014 12.01.1978 01.06.2016 ISO/RTO N/A CAISO NYISO ISO-NE N/A NYISO SPP ERCOT IESO N/A N/A N/A N/A N/A N/A N/A Utility Pow erSouth Pacific Gas and Electric Company New York Pow er Authority (NYPA) SSE (Scottish and Southern Energy) New York State Electric & Gas (NYSEG)WEB Aruba N.V.E.ON Electricity North West Rocky Mountain Pow er Southern California Edison Energy Storage Technology Provider Dresser-Rand SustainX Highview Pow er Storage General Compression, Inc.Dresser-Rand Hydrostor Hydrostor BBC, Alstom ALACAES Highview Pow er Storage Expected Use Cases: Black Start X X X X Electric Supply Reserve Capacity - Non-Spinning X X Electric Supply Reserve Capacity - Spinning X X X X X X X Load Follow ing (Tertiary Balancing)X Ramping X X Voltage Support X Electric Energy Time Shift X X X X X X X X Electric Supply Capacity X X Transmission Congestion Relief X X X Transmission Support X Renew ables Capacity Firming X X X X X X Distribution upgrade due to solar Distribution upgrade due to w ind Transmission upgrades due to solar Transmission upgrades due to w ind Electric Bill Management X X X Grid-Connected Commercial (Reliability & Quality) Grid-Connected Residential (Reliability) Frequency Regulation X X X X X X X Transportable Transmission/Distribution Upgrade Deferral Stationary Transmission/Distribution Upgrade Deferral Onsite Renew able Generation Shifting X Electric Bill Management w ith Renew ables Renew ables Energy Time Shift X X X X X X X On-Site Pow er X Transportation Services Microgrid Capability Resiliency Demand Response Note 1: DOE still verifying record entry. Source: DOE Global Energy Storage Database ( http://w w w .energystorageexchange.org/projects) PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 24 Table 9 CAES and LAES project descriptions Project Name Rated Power in kW Duration at Rated Power HH:MM Description McIntosh CAES Plant 110,000 26:0.00 The 2nd commercial CAES plant, in operation since 1991. Like the Huntorf plant, the McIntosh Unit 1 facility stores compressed air in a solution-mined salt cavern. The cavern is 220 ft in diameter and 1,000 ft tall, for a total volume of 10 million cubic feet. At full charge, the cavern is pressurized to 1,100 psi, and it is discharged down to 650 psi. During discharge, 340 pounds of air flow out of the cavern each second. The cavern can discharge for 26 hours. The plant also utilizes nuclear-sourced night-time power for compression and then produces peak power during the day by releasing the compressed air into a 110-MW gas-fired combustion turbine built by Dresser Rand. The turbine unit also makes use of an air-to-air heat exchanger to preheat air from the cavern with waste heat from the turbine. The waste heat recovery system reduces fuel usage by roughly 25%. Compared to conventional combustion turbines, the CAES-fed system can start up in 15 minutes rather than 30 minutes, uses only 30% to 40% of the natural gas, and operates efficiently down to low loads (about 25% of full load). The key function of the facility is for peak shaving. PG&E Advanced Underground Compressed Air Energy Storage (CAES) 300,000 10:0.00 A 300 MW A-CAES demo plant will use an underground storage container (depleted gas reservoir), and next-generation turbomachinery. The project has 3 phases: Phase 1 - preliminary engineering, geologic reservoir engineering, econmoic analyses, and regulatory permitting; Phase 2 - Construction and plant commissioning; Phase 3: Plant operation and plant performance monitoring. Ph 2 of the project will go ahead if the Ph1 results show PG&E and California regulatory management that the project is cost effective. Next Gen CAES using Steel Piping - NYPA 9,000 4:30.00 9-MW plant will use steel piping to hold pressurized air instead of geologic based air store. Preliminary plant design complete; NYSERDA funding expected in July 2012; Vendors, utility sponsor, and site location determined. Groundbreaking slated for 2013 to 2014 time frame. SustainX Inc Isothermal Compressed Air Energy Storage 1,500 1:0.00 SustainX is constructing a 1.5MW pilot system in Seabrook, New Hampshire to demonstrate their modular isothermal compressed air energy storage system (ICAES). This second generation ICAES system is scheduled for completion in 2013, with the third generation field-deployed ICAES system ready for operation by 2014. The current schedule would have SustainX's isothermal system ready for commercial production in 2015. SustainX’s ICAES system captures the heat from compression in water and stores the captured heat until it is needed again for expansion. Storing the captured heat eliminates the need for a gas combustion turbine and improves efficiency. SustainX achieves isothermal cycling by combining patented innovations with a design control on mature industrial components and principles. The system is designed for a 20-year lifetime. It achieves full power output from start-up in less than one minute, and it does not use toxic chemicals. Highview Pilot Plant 350 7:0.00 Highview‘s technology uses off-peak or ‘wrong-time’ power to liquefy air (710 litres of air becomes one litre of liquid air), which is then held in a tank until electricity is required. The liquid air is then returned to gaseous form, expanding 710 times, to drive a turbine. Extreme cold is recovered and stored to assist with subsequent liquefaction, thus greatly improving the overall efficiency of the system. If waste heat is available (e.g. from a neighbouring power plant or industrial process) then this can be introduced at the expansion phase, enhancing system efficiency. NYSEG Seneca/Watkins Glen CAES Project 0 0:0.00 ***09/2012: NYSEG has concluded that the economics of the project are not favorable for development in the current and forecast wholesale electric market in New York State, and further project development work is not warranted.*** Read the final project report here: http://goo.gl/HbiWQ9 New York State Electric & Gas (NYSEG) intended to build an advanced compressed air energy storage (CAES) plant with a rated capacity of 150 MW (2.4 GWh) using an existing 4.5 million cubic foot underground salt cavern in Reading, New York. The plant was to be sited between the bulk of U.S. wind resources and the heavy population centers of the East Coast. The plant will have the capacity to operate 16 hours a day and will provide energy arbitrage for approximately 2,300-2,500 hours each year. It will use off-peak electricity to compress air into the cavern. When electricity is needed the air will be withdrawn, heated, and passed through a turbine to drive an electric generator, burning one-third the amount of fuel compared to conventional combustion turbines. NYSEG’s CAES plant will provide flexible generation capability to accommodate fluctuations in load. The plant will be tied to NYSEG’s cross-state 230 kV/345 kV transmission system that feeds major metropolitan centers in Central New York. The 230 kV line is the recipient of a large proportion of wind power and is tied to the New York City load areas. It will provide redundancy in capacity, ensure against congestion and power fluctuations, and can provide improved power quality to the grid. Iberdrola USA, the parent of NYSEG, plans to conduct a feasibility study in the future to determine the ability to increase the plant’s capacity to 360 MW or greater. Texas Dispatchable Wind 2,000 250:0.00 The Gaines, Texas Dispatchable Wind Project is a 2.0MW wind generation project located in West Texas. It is owned and operated by Texas Dispatachable Wind 1, LLC, a subsidiary of General Compression. The project consists of a wind turbine, a General Compression Advanced Energy Storage (GCAES™) system, a storage cavern, and other electrical & ancillary facilities. The project has the capability to, during periods of low demand, store portions of the energy generated by the wind turbine and later, during periods of increased demand, release the stored energy. Construction of the project began in 2011 and the project was commissioned in late 2012. Apex Bethel Energy Center 317,000 96:0.00 Development of the 317 MW compressed air energy storage facility with 96 hours of storage has been put on hold as of 10/2014. New information on development is anticipated in summer 2015. PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 25 Table 10 CAES and LAES project descriptions (continued) Project Name Rated Power in kW Duration at Rated Power HH:MM Description Hydrostor UCAES Demonstration Facility 1,000 4:0.00 Construction is underway on a 1 MW/4 MWh demonstration facility to showcase Hydrostor’s first-of-a-kind system. Located Approx. 5km from the shore of Toronto, the system will be situated in Lake Ontario at a depth of 80m. Hydrostor UCAES Aruba Project 1,000 8:0.00 Hydrostor's proprietary technology is based on a simple idea: Anchor a low-cost air cavity to the bottom of a lake or ocean floor, and store energy in it by filling it with compressed air created using surplus renewable energy. The energy is discharged from the system by releasing the air stored underwater to drive a turbine recreating electricity when it is most needed - either to meet daily demand peaks or to cover periods of calm winds or cloud cover that prevent power from being harnessed. Kraftwerk Huntorf 321,000 2:0.00 1st commercial CAES plant, operational since 1978. The 321-MW plant utilizes nuclear-sourced night-time power for compression and produces peak power during the day via a natural gas turbine. The facility stores the compressed air in two ""solution-mined"" salt caverns which comprise a total of 310,000 cubic meters. (Water was pumped into and out of a salt deposit to dissolve the salt and form the cavern.) The depth of the caverns is more than 600 m which ensures the stability of the air for several months' storage, and guarantees the specified maximum pressure of 100 bar. One cavern is cycled on a diurnal basis. The second cavern serves as a black start asset if the nearby nuclear power plant unexpectedly goes down. Pollegio-Loderio Tunnel ALACAES Demonstration Plant 500 4:0.00 A demonstration plant to test a novel advanced adiabatic compressed air energy storage concept. An abandoned tunnel in the Swiss alps is used as the air storage cavern and a packed bed of rocks thermal energy storage is used to store the heat created during compression. The thermal energy storage is placed inside the pressure cavern. Project construction concluded in April 2016. The project is operating in the commissioning phase from April 2016 until June 2016. In June 2016 the plant will start full operation. Pre-Commercial Liquid Air Energy Storage Technology Demonstrator 5,000 3:0.00 Highview and project partners, leading UK renewable energy and recycling company Viridor, were awarded funding of more than £8 million ($11.6 million) by the British Government Department of Energy & Climate Change (DECC) for a 5 MW Liquid Air Energy Storage (LAES) technology system. The funding is supporting the design, build and testing of a Pre- Commercial LAES Technology Demonstrator alongside Viridor's landfill gas generation plant at Pilsworth in Greater Manchester UK. In addition to providing energy storage, the LAES technology plant will convert low grade waste heat from the onsite landfill gas engines to electrical power. The project will operate for at least one year and will demonstrate LAES providing a number of grid balancing services in the UK, including Short Term Operating Reserve (STOR), Secondary frequency response testing, Triad Avoidance (supporting the grid during the winter peaks) and also testing for the US regulation market. ATK Launch Systems Microgrid CAES 1 80 0:45.00 The Alliant Techsystems (ATK) Launch Systems project takes place at a single customer site – but, it’s a large one. ATK Launch Systems in Promontory, Utah comprises over 540 buildings on a sprawling 19,900-acre site accessible by 75 miles of roads. Their power system of three main substations and 60 miles of power lines deliver about 17 MW (on-peak) to the facilities, with an annual energy bill of over $15 million. In recent years, utility tariff changes have significantly increased the portion of the monthly bills attributable to demand charges. ATK’s Corporate Energy Team, established in 2003, and has already implemented a number of energy saving projects, realizing energy costs reductions of $2 million/year or more. As a result of a comprehensive plant-wide energy assessment (partially funded by DOE) in 2006/2007, ATK identified a new set of energy projects at the Promontory site. This project will integrate an ambitious and highly diverse set of distributed resources. These include four heat recovery systems using organic Rankin cycle (ORC) generators connected to Ormat energy converters, for a total of 1400 kW. Heat for the system will be supplied by a concentrating solar thermal array, air compressor waste heat and low pressure steam. The project will also incorporate about 140 kW of wind turbines, a yet-to-be-determined amount of hydro turbine capacity, and about 40 kW of micro-hydro turbines. For storage, the project includes up to 1440 kW of pumped hydro capacity for two - four hours, and an above-ground compressed air energy storage (CAES) and generation system (80 kW capacity for 30-60 minutes). Hybrid Compressed Air Energy Storage and Thermal Energy Storage - UCLA - Southern California Edison 1 0 0:0.00 Engineers from the University of California Los Angeles Henry Samueli School of Engineering and Applied Science have won a $1.62 million grant to build a hybrid energy storage system. The team with work with Southern California Edison, which will help operate the system on the Cal Poly Pomona campus upon completion, to build a system to store "energy harvested from intermittently productive renewable sources such as solar panels and wind farms, then releases that energy into the grid when demand is high," according to a news release. Lead by Pirouz Kavehpour, a professor of mechanical and aerospace engineering at UCLA, the team will build a system that uses both compressed air and thermal energy storage technologies to enhance capacity and reduce costs. "Our estimated cost of energy for this unit is about $100 per kilowatt hour, which is much lower than any battery system of which we are aware," said Kavehpour, in a prepared statement. Adele CAES Project 1 200,000 5:0.00 The first adiabatic CAES project; the heat that appears during compression is also stored, and then returned to the air when the air is expanded. Construction will begin in 2013 in Staßfurt, a city in Sachsen-Anhalt, Germany (ADELE stands for the German acronym for adiabatic compressed air energy storage for electricity supply). The project is a joint effort between RWE, General Electric, Zueblin, and the German Aerospace Center. The German Federal Ministry of Economics is also providing state funding. Altogether, the project members will contribute an amount of EUR 10 million. Note 1: DOE still verifying record entry. Source: DOE Global Energy Storage Database ( http://w w w .energystorageexchange.org/projects) PacifiCorp | Bulk Storage Study for the 2017 Integrated Resource Plan Black & Veatch | Data Tables 26 Table 11 Magnum CAES Data RESOURCE CAES Installation Name 320 MW Magnum CAES Base Capital ($) 556,800,000 Pro-rated site development cost ($) included in Base Capital Net Capacity (MW) 320 Rated Energy Capacity (MWh) 15,360 Expected use cases Energy, capacity, spinning, regulation, non-spinning, black start Total Implementation Time (yrs) 3 Commercial Operation Year 2021 Design Life (yrs) 30+ Base Capital ($/KW) 1,740 Var O&M ($/MWh) 0.77 Fraction Var O&M Capitalized 0.41 Fixed O&M ($/KW-yr) 18.9 Fraction Fixed O&M Capitalized 0 Average Full Load Heat Rate (HHV Btu/KWh) 4,227 EFOR (%) 3% POR (%) 1.5% Heat Input for Warm Start (HHV, MMBtu) 0 Water Consumed (Gal/MWh) 294 SO2 (lbs/MMBtu) 0.001 NOx (lbs/MMBtu) 0.009 Hg (lbs/TBTu) N/A CO2 (lbs/MMBtu) 117 Minimum Capacity (MW) 3.3 Spinning Reserves (MW) 156.7 Run-up Rate (first fire to min capacity, warm start, MW/hr) 180 Ramp Up Rate (min capacity to full load, MW/min) 32 Ramp Down Rate (full load to min capacity, MW/min) 32 Start-Up Time to Minimum Capacity (min) 5 min Minimum Operational Up Time (hr) N/A Minimum Operational Down Time (hr) N/A Recharge rate (MWh/hour) 150 AC to AC efficiency (%) 1 ~50% Note 1: The basis for this efficiency value is unclear. PacifiCorp has requested Magnum to clarify the definition used to determine this value but at the time of this report, clarification had not been received. Given the technology for CAES can include the use of fuel during the discharge mode, parameters for Energy Charge Ratio (kWhin/kWhout) and Net Heat Rate (Btu/kWh) during discharge mode (which considers the fuel added) are metrics typically used.